Table of contents

The launch of volume 8 of Environmental Research Letters (ERL) comes at a critical time in terms of innovations and exciting areas of science, but particularly in the areas linking environmental research and action.

The most recent climate change Conference of the Parties meeting (COP), in Doha in December 2012, has now come and gone. As has been dissected in the press, very little was accomplished. Some will see this as a failure, as I do, and others will reasonably enough note that this meeting, the 18th such COP was¹ never intended to be a milestone moment. The current plan, in fact, is for a 'post-Kyoto' international climate agreement to be adopted only at the COP20 summit in December 2015.

As we lead up to COP20, and potentially other regional or national approaches to climate protection, innovations in science, innovations in policy tools, and political commitment must come together. The science of climate change only continues to get clearer and clearer, and bleaker [1]. Later this year the IPCC will release its Fifth Assessment Report, AR5. The draft versions are out for review now.

ERL has published a number of papers on climate change science, mitigation and adaptation, but one area where the world needs a particular focus is on the nexus of science and action.

A summary of the Intergovernmental Panel on Climate Change's findings from the first assessment report (FAR; 1990) to the latest report is presented in figure 1. This graphic is specifically not about the scientific record alone. What is most important about this figure is the juxtaposition of the language of science and the language of ... language.

Figure 1. A superposition of the state of climate science in three key data sets, and the dates of the first, second, third and fourth assessment reports (FAR, SAR, TAR, and AR4, respectively) plotted as vertical lines. On the right are the key statements from each of these reports, along with the conclusion of the Special Report on Renewable Energy (SRREN, completed in 2011) which found that up to an 80% decarbonization of the global economy was possible if we can enable and launch a large-scale transition to a clean energy system consistent with what a number of 'leading edge' cities, regions, and nations have already accomplished or started.

Note, in particular, that as the physical climate change metrics have progressed, the words—shown on the right—have also progressed. In 1990, at the time of the FAR the strongest scientific consensus statement was that another decade of data would likely be needed to clearly observe climate change. Through the second to fourth (SAR, TAR, and AR4) reports, increasing clarity on the science of climate change translated into a consensus of overwhelming blame on human activities. The key statements from each report are not only about the growing evidence for anthropogenically driven climate change, but they have moved into the ecological and social impacts of this change. AR4 critically concluded that climate change would lead to climate injustice as the poor, globally, bear the brunt of the impacts. Despite this 'Rosetta Stone' translating science to language, we have failed to act collectively.

One area where ERL can advance the overall conversation is on this science/action interface. As AR5 emerges, the climate change/climate response interface will need deep, substantive, action that responds rapidly to new ideas and opportunities. The rapid publication and open access features of ERL are particularly critical here as events a such as Hurricane Sandy, economic or political advances in climate response made by cities, regions or nations, all warrant assessment and response. This is one of many areas where ERL has been at the forefront of the conversation, through not only research letters, but also commentary-style Perspective pieces and the conversation that ERL's sister community website environmentalresearchweb can facilitate.

This process of translating proposed solutions—innovations—between interest groups, has been in far too short supply recently. One promising example has been the science/action dialog between a leading climate research center and the World Bank [2].

'The Earth system's responses to climate change appear to be non-linear', points out Potsdam Institute for Climate Impact Research (PIK) Director, John Schellnhuber. 'If we venture far beyond the 2° guardrail, towards the 4° line, the risk of crossing tipping points rises sharply. The only way to avoid this is to break the business-as-usual pattern of production and consumption'.

This assessment came in a report on climate science commissioned by the World Bank. Dr Jim Yong Kim, president of the World Bank noted succinctly and critically that: '... most importantly, a 4 °C world is so different from the current one that it comes with high uncertainty and new risks that threaten our ability to anticipate and plan for future adaptation needs.'

This statement warrants careful discussion. Not only is World Bank President Kim affirming the results of the PIK study, and by direct extension the IPCC (because the same authors at PIK are also central to the work of the IPCC), but he is clearly noting that while many climate analysts rightly talk about the need to not exceed a 2° temperature increase, the path the world is currently on, namely 4°–6° will be catastrophic. This may come as too soft a statement to many in the scientific community, but it opens the door to an increasingly detailed dialog between climate change science and agencies engaged in action.

Where ERL and other outlets for this conversation can play a critical role is in the many dimensions of climate change and response. The story is far from one only at the global level. As http://climatehotmap.org and many other location specific assessments detail, the environmental change story is playing out in millions of critical cases. Each warrants reporting and action, as well as integration with assessments of current data gathering and 'big data' needs, and with wider socioeconomic questions of effective political, and policy response. Through that, dialog papers in ERL will be critically important to advancing not only climate science, but the interactive dialog between knowledge and action.

References

[1] Hansen J, Sato M and Ruedy R 2012 Perception of climate change Proc. Natl Acad. Sci. USA109 E2415–23

[2] Potsdam Institute for Climate Impact 2013 Turn Down the Heat: Why a 4 °C Warmer World Must be Avoided (Washington, DC: The World Bank)

¹ The Kyoto Protocol was adopted on 11 December 1997 in Kyoto, Japan, and entered into force on 16 February 2005. As of September 2011, 191 states have signed and ratified the protocol. The United States signed but did not ratify the Protocol and Canada withdrew from it in 2011.

Abstract

Stabilizing CO₂ emissions at current levels for fifty years is not consistent with either an atmospheric CO₂ concentration below 500 ppm or global temperature increases below 2 °C. Accepting these targets, solving the climate problem requires that emissions peak and decline in the next few decades, and ultimately fall to near zero. Phasing out emissions over 50 years could be achieved by deploying on the order of 19 'wedges', each of which ramps up linearly over a period of 50 years to ultimately avoid 1 GtC y⁻¹ of CO₂ emissions. But this level of mitigation will require affordable carbon-free energy systems to be deployed at the scale of tens of terawatts. Any hope for such fundamental and disruptive transformation of the global energy system depends upon coordinated efforts to innovate, plan, and deploy new transportation and energy systems that can provide affordable energy at this scale without emitting CO₂ to the atmosphere.

1. Introduction

In 2004, Pacala and Socolow published a study in Science arguing that '[h]umanity can solve the carbon and climate problem in the first half of this century simply by scaling up what we already know how to do' [1]. Specifically, they presented 15 options for 'stabilization wedges' that would grow linearly from zero to 1 Gt of carbon emissions avoided per year (GtC y⁻¹; 1 Gt = 10¹² kg) over 50 years. The solution to the carbon and climate problem, they asserted, was 'to deploy the technologies and/or lifestyle changes necessary to fill all seven wedges of the stabilization triangle'. They claimed this would offset the growth of emissions and put us on a trajectory to stabilize atmospheric CO₂ concentration at 500 ppm if emissions decreased sharply in the second half of the 21st century.

The wedge concept has proven popular as an analytical tool for considering the potential of different technologies to reduce CO₂ emissions. In the years since the paper was published, it has been cited more than 400 times, and stabilization wedges have become a ubiquitous unit in assessing different strategies to mitigate climate change (e.g. [2–5]). But the real and lasting potency of the wedge concept was in dividing the daunting problem of climate change into substantial but tractable portions of mitigation: Pacala and Socolow gave us a way to believe that the energy-carbon-climate problem was manageable.

An unfortunate consequence of their paper, however, was to make the solution seem easy (see, e.g. [6, 7]). And in the meantime, the problem has grown. Since 2004, annual emissions have increased and their growth rate has accelerated, so that more than seven wedges would now be necessary to stabilize emissions and—more importantly—stabilizing emissions at current levels for 50 years does not appear compatible with Pacala and Socolow's target of an atmospheric CO₂ concentration below 500 ppm nor the international community's goal of limiting the increase in global mean temperature to 2 °C more than the pre-industrial era.

Here, we aim to revitalize the wedge concept by redefining what it means to 'solve the carbon and climate problem for the next 50 years'. This redefinition makes clear both the scale and urgency of innovating and deploying carbon-emissions-free energy technologies.

2. Solving the climate problem

Stabilizing global climate requires decreasing CO₂ emissions to near zero [8–11]. If emissions were to stop completely, global temperatures would quickly stabilize and decrease gradually over time [8, 12, 13]. But socioeconomic demands and dependence on fossil-fuel energy effectively commit us to many billions of tons of CO₂ emissions [14], and at the timescale of centuries, each CO₂ emission to the atmosphere contributes another increment to global warming: peak warming is proportional to cumulative CO₂ emissions [15, 16]. Cumulative emissions, in turn, integrate all past emissions as well as those occurring during three distinct phases of mitigation: (1) slowing growth of emissions, (2) stopping growth of emissions, and (3) reducing emissions. Although they noted that stabilizing the climate would require emissions to 'eventually drop to zero', Pacala and Socolow nonetheless defined 'solv[ing] the carbon and climate problem over the next half-century' as merely stopping the growth of emissions (phases 1 and 2). Further reductions (phase 3), they said, could wait 50 years if the level of emissions were held constant in the meantime.

But growth of emissions has not stopped (phase 2) or even slowed (phase 1), it has accelerated [17, 18]. In 2010, annual CO₂ emissions crested 9 GtC. At this level, holding emissions constant for 50 years (phase 2) is unlikely to be sufficient to avoid the benchmark targets of 500 ppm or 2 °C.

To support this assertion, we performed ensemble simulations using the UK Met Office coupled climate/carbon cycle model, HadCM3L (see supplementary material available at stacks.iop.org/ERL/8/011001/mmedia), to project changes in atmospheric CO₂ and global mean temperature in response to emissions scenarios in which seven wedges (W7) and nine wedges (W9) were immediately subtracted from the A2 marker scenario of the Intergovernmental Panel on Climate Change (IPCC)'s Special Report on Emissions Scenarios (SRES) [19] beginning in 2010 (figure 1). In the first half of this century, the A2 scenario is near the center of the plume of variation of the SRES emissions scenarios [20]. Indeed, actual annual emissions have exceeded A2 projections for more than a decade [21, 22]. During this period, strong growth of global emissions has been driven by the rapid, carbon-intensive growth of emerging economies [23, 24], which has continued despite the global financial crisis of 2008–9 [18]. For these reasons we believe that, among the SRES scenarios, A2 represents a reasonable 'business-as-usual' scenario. However, if emissions were to suddenly decline and follow a lower emissions business-as-usual trajectory such as B2, fewer wedges would be necessary to stabilize emissions, and deployment of seven wedges would reduce annual emissions to 4.5 GtC in 2060. Thus, mitigation effort (wedges) required to stabilize emissions is dependent on the choice of baseline scenario, but a half-century of emissions at the current level will have the same effect on atmospheric CO₂ and the climate regardless of what scenario is chosen.

Figure 1. Modeled effects of deploying wedges. (A) Future CO₂ emissions under SRES A2 marker scenario and the A2 scenario reduced by deployment of 7 wedges (W7). The response of (B) atmospheric CO₂ and (C) global mean surface temperature under W7. (D) Future CO₂ emissions under SRES A2 marker scenario and stabilized at 2010 levels (reduced by approximately 9 wedges relative to the A2 scenario) (W9). The response of (E) atmospheric CO₂ and (F) global mean surface temperature under W9. Error bars in ((C) and (F)) are 2-sigma. Dashed lines in (A), (B), (D) and (E) show emissions and concentrations of representative concentration pathways RCP4.5, RCP6, and RCP8.5 [38]. Mean temperatures reflect warming relative to the pre-industrial era.

We also note that the climate model we used, HadCM3L, has a strong positive climate/carbon cycle feedback mainly associated with the dieback of the Amazon rainforest [25]. As a result, HadCM3L projected the highest level of atmospheric CO₂ concentrations among eleven Earth system models that were driven by a certain CO₂ emission scenario [26]. However, this strong positive climate/carbon cycle feedback operates in simulations of both the A2 and wedge (W7 and W9) scenarios. Therefore, the relative effect of wedges, as opposed to the absolute values of projected atmospheric CO₂ and temperature, is expected to be less dependent on the strength of climate/carbon cycle feedback.

Atmospheric CO₂ concentration and mean surface temperatures continue to rise under the modeled W7 scenario (figures 1(A)–(C)). Deploying 7 wedges does not alter projected mean surface temperatures by a statistically significant increment until 2046 (α = 0.05 level), at which time the predicted difference between mean temperatures in the A2 and W7 scenarios is 0.14 ± 0.08 °C. In 2060, the difference in projected mean temperatures under the two scenarios is 0.47 ± 0.07 °C. Further, under the W7 scenario, our results indicate atmospheric CO₂ levels will exceed 500 ppm in 2042 (reaching 567 ± 1 ppm in 2060) (figure 1(B)), and 2 °C of warming in 2052 (figure 1(C)). Immediately stabilizing global emissions at 2010 levels (∼10.0 GtCy⁻¹), which would require approximately nine wedges (thus W9) under the A2 scenario, has a similarly modest effect on global mean surface temperatures and atmospheric CO₂, with warming of 1.92 ± 0.4 °C in 2060 and atmospheric CO₂ exceeding 500 ppm by 2049 (figures 1(D)–(F)). Our projections therefore indicate that holding emissions constant at current levels for the next half-century would cause substantial warming, approaching or surpassing current benchmarks [27–29] even before any reduction of emissions (phase 3) begins.

Insofar as current climate targets accurately reflect the social acceptance of climate change impacts, then, solving the carbon and climate problem means not just stabilizing but sharply reducing CO₂ emissions over the next 50 years.

We are not alone in drawing this conclusion (see, e.g. [30–32]). For example, at least some integrated assessment models have now found that the emissions reductions required to prevent atmospheric CO₂ concentration from exceeding 450 ppm are no longer either physically or economically feasible [11, 33, 34], and that preventing CO₂ concentration from exceeding 550 ppm will also be difficult if participation of key countries such as China and Russia is delayed [11]. Most model scenarios that allow CO₂ concentrations to stabilize at 450 ppm entail negative carbon emissions, for example by capturing and storing emissions from bioenergy [11].

A different body of literature has concluded that cumulative emissions of 1 trillion tons of carbon (i.e. 1000 GtC) are likely to result in warming of 2 °C [15, 35]. Whereas Pacala and Socolow's original proposal implied roughly 944 GtC of cumulative emissions (305 GtC prior to 2004, 389 GtC between 2004 and 2054, and another 250 GtC between 2054 and 2104 if emissions decrease at 2% y⁻¹ as they suggested), stabilizing emissions at 2010 levels for 50 y and decreasing at 2% y⁻¹ afterward increases the cumulative total to 1180 GtC of emissions (356 GtC prior to 2010, 491 GtC between 2010 and 2060, and 336 GtC between 2060 and 2110 at which time annual emissions remain at nearly 3.2 GtC y⁻¹). Lastly, we note that even though emissions in the lowest of the new representative concentration pathways (RCP2.6) peak in 2020 at just 10.3 GtC y⁻¹ and decline sharply to only 2.0 GtC y⁻¹ in 2060 (figure 2), the concentration of atmospheric CO₂ nonetheless reaches 443 ppm in 2050 [36–38]. In contrast, emissions of the intermediate pathway RCP4.5 rise modestly to 11.5 GtC y⁻¹ in 2040 before declining to 9.6 GtC y⁻¹ in 2060, which leads to atmospheric CO₂ concentrations of 509 ppm in 2060 on the way to 540 ppm in 2100. These pathways, along with the integrated assessment models and cumulative emissions simulations all support our finding that 50 y of current emissions is not a solution to climate change.

Figure 2. Idealization of future CO₂ emissions under the business-as-usual SRES A2 marker scenario. Future emissions are divided into hidden (sometimes called 'virtual') wedges (brown) of emissions avoided by expected decreases in the carbon intensity of GDP by ∼1% per year, stabilization wedges (green) of emissions avoided through mitigation efforts that hold emissions constant at 9.8 GtC y⁻¹ beginning in 2010, phase-out wedges (purple) of emissions avoided through complete transition of technologies and practices that emit CO₂ to the atmosphere to ones that do not, and allowed emissions (blue). Wedges expand linearly from 0 to 1 GtC y⁻¹ from 2010 to 2060. The total avoided emissions per wedge is 25 GtC, such that altogether the hidden, stabilization and phase-out wedges represent 775 GtC of cumulative emissions.

Unless current climate targets are sacrificed, solving the climate problem requires significantly reducing emissions over the next 50 years. Just how significant those reductions need to be will depend on a global trade-off between the damages imposed by climatic changes and the costs of avoiding them. But given substantial uncertainties associated with climate model projections (e.g., climate sensitivity), the arbitrary nature of targets like 500 ppm and 2 °C, and the permanence implied by the term 'solution', the ultimate solution to the climate problem is a complete phase-out of carbon emissions.

3. Counting wedges

But significantly reducing current emissions while also sustaining historical growth rates of the global economy is likely to require many more than seven wedges. Gross world product (GWP) projections embedded in the A2 scenario imply as many as 31 wedges would be required to completely phase-out emissions, grouped into three distinct groups: (1) 12 'hidden' wedges that represent the continued decarbonization of our energy system at historical rates (i.e. decreases in the carbon intensity of the global economy that are assumed to regardless of any additional efforts to mitigate emissions) [9, 39]. (2) 9 'stabilization' wedges that represent additional efforts to mitigate emissions above and beyond the technological progress already assumed by the scenario [1]. And (3), 10 'phase-out' wedges that represent the complete transition from energy infrastructure and land-use practices that emit CO₂ (on net) to the atmosphere to infrastructure and practices which do not (figure 2) [9, 14, 40].

There is good reason to be concerned that at least some number of the hidden wedges will not come to be—that the rates of decarbonization assumed by almost all scenarios of future emissions may underestimate the extent to which rising energy demand will be met by increased use of coal and unconventional fossil fuels [24, 41]. Moreover, there is no way to know whether a wedge created by deploying carbon-free energy technology represents additional mitigation effort (i.e. a stabilization wedge) or something that would have happened in the course of normal technological progress (i.e. a hidden wedge). Thus, in assessing the efficacy of efforts to reduce emissions, it may be more useful to tabulate wedges based only on the current carbon intensity of global energy and food production and projected demand for energy and food, without reference to any particular technology scenario. Doing so would clarify the full level of decarbonization necessary and remove the question of whether emissions reductions that do occur should count as mitigation or not. But even assuming that historical rates of decarbonization will persist and therefore that many hidden wedges will materialize, phasing-out emissions altogether will entail nearly three times the number of additional wedges that Pacala and Socolow originally proposed—a total of 19 wedges under the A2 scenario (figure 2).

4. The urgent need for innovation

Confronting the need for as many as 31 wedges (12 hidden, 9 stabilization and 10 phase-out), the question is whether there are enough affordable mitigation options available, and—because the main source of CO₂ emissions is the burning of fossil fuels—the answer depends upon an assessment of carbon-free energy technologies. There is a longstanding disagreement in the literature between those who argue that existing technologies, improved incrementally, are all that is needed to solve the climate problem (e.g. [1]) and others who argue that more transformational change is necessary (e.g. 42]). Although the disagreement has turned on the definitions of incremental and transformative and the trade-offs of a near-term versus a longer-term focus, the root difference lies in the perceived urgency of the climate problem [6]. The emission reductions required by current targets, let alone a complete phase-out of emissions, demand fundamental, disruptive changes in the global energy system over the next 50 years. Depending on what sort of fossil-fuel infrastructure is replaced and neglecting any emissions produced to build and maintain the new infrastructure (see, e.g. [43]), a single wedge represents 0.7–1.4 terawatts (TW) of carbon-free energy (or an equivalent decrease in demand for fossil energy). Whether the changes to the energy system are called incremental or revolutionary, few would dispute that extensive innovation of technologies will be necessary to afford many terawatts of carbon-free energy and reductions in energy demand [42, 44, 45].

Currently, only a few classes of technologies might conceivably provide carbon-free power at the scale of multiple terawatts, among them fossil fuels with carbon capture and storage (CCS), nuclear, and renewables (principally solar and wind, and perhaps biomass) [42, 46, 47]. However, CCS has not yet been commercially deployed at any centralized power plant; the existing nuclear industry, based on reactor designs more than a half-century old and facing renewed public concerns of safety, is in a period of retrenchment, not expansion; and existing solar, wind, biomass, and energy storage systems are not yet mature enough to provide affordable baseload power at terawatt scale. Each of these technologies must be further developed if they are to be deployed at scale and at costs competitive with fossil energy.

Yet because investments in the energy sector tend to be capital intensive and long term, research successes are often not fully appropriable [48], and technologies compete almost entirely on the price of delivered electricity, private firms tend to underinvest in R&D, which has made energy one of the least innovative industry sectors in modern economies [44]. Supporting deployment of newer energy technologies at large scales will undoubtedly lead to further development and reduced costs [49, 50], but additional public support for early stage R&D will also be necessary to induce needed innovation [6, 44, 45, 51–53]. Moreover, it is imperative that policies and programs also address the intermediate stages of development, demonstration, and commercialization, when ideas born of public-funded research must be transferred to and diffused among private industries [44, 54, 55].

5. Conclusions

In 2004, Pacala and Socolow concluded that 'the choice today is between action and delay'. After eight years of mostly delay, the action now required is significantly greater. Current climate targets of 500 ppm and 2 °C of warming will require emissions to peak and decline in the next few decades. Solving the climate problem ultimately requires near-zero emissions. Given the current emissions trajectory, eliminating emissions over 50 years would require 19 wedges: 9 to stabilize emissions and an additional 10 to completely phase-out emissions. And if historical, background rates of decarbonization falter, 12 'hidden' wedges will also be necessary, bringing the total to a staggering 31 wedges.

Filling this many wedges while sustaining global economic growth would mean deploying tens of terawatts of carbon-free energy in the next few decades. Doing so would entail a fundamental and disruptive overhaul of the global energy system, as the global energy infrastructure is replaced with new infrastructure that provides equivalent amounts of energy but does not emit CO₂. Current technologies and systems cannot provide the amounts of carbon-free energy needed soon enough or affordably enough to achieve this transformation. An integrated and aggressive set of policies and programs is urgently needed to support energy technology innovation across all stages of research, development, demonstration, and commercialization. No matter the number required, wedges can still simplify and quantify the challenge. But the problem was never easy.

Acknowledgments

We thank six anonymous reviewers for their comments on various versions of the manuscript. We also especially thank R Socolow for several thoughtful and stimulating discussions of this work.

1. Introduction

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.

The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

2. Agriculture and climate change mitigation

The main agricultural GHGs—methane and nitrous oxide—account for 10%–12% of anthropogenic emissions globally (Smith et al 2008), or around 50% and 60% of total anthropogenic methane and nitrous oxide emissions, respectively, in 2005. Net carbon dioxide fluxes between agricultural land and the atmosphere linked to food production are relatively small, although significant carbon emissions are associated with degradation of organic soils for plantations in tropical regions (Smith et al 2007, FAO 2012). Population growth and shifts in dietary patterns toward more meat and dairy consumption will lead to increased emissions unless we improve production efficiencies and management. Developing countries currently account for about three-quarters of direct emissions and are expected to be the most rapidly growing emission sources in the future (FAO 2011).

Reducing agricultural emissions and increasing carbon sequestration in the soil and biomass has the potential to reduce agriculture's contribution to climate change by 5.5–6.0 gigatons (Gt) of carbon dioxide equivalent (CO₂eq)/year. Economic potentials, which take into account costs of implementation, range from 1.5 to 4.3 GT CO₂eq/year, depending on marginal abatement costs assumed and financial resources committed, with most of this potential in developing countries (Smith et al 2007). The opportunity for mitigation in agriculture is thus significant, and, if realized, would contribute to making this sector carbon neutral. Yet it is only through a robust and shared understanding of how much carbon can be stored or how much CO₂ is reduced from mitigation practices that informed decisions can be made about how to identify, implement, and balance a suite of mitigation practices as diverse as enhancing soil organic matter, increasing the digestibility of feed for cattle, and increasing the efficiency of nitrogen fertilizer applications. Only by selecting a portfolio of options adapted to regional characteristics and goals can mitigation needs be best matched to also serve rural development goals, including food security and increased resilience to climate change.

Expansion of agricultural land also remains a major contributor of greenhouse gases, with deforestation, largely linked to clearing of land for cultivation or pasture, generating 80% of emissions from developing countries (Hosonuma et al 2012). There are clear opportunities for these countries to address mitigation strategies from the forest and agriculture sector, recognizing that agriculture plays a large role in economic and development potential. In this context, multiple development goals can be reinforced by specific climate funding granted on the basis of multiple benefits and synergies, for instance through currently negotiated mechanisms such as Nationally Appropriate Mitigation Actions (NAMAs) (REDD+, Kissinger et al 2012).

3. Challenges to quantifying GHG information for the agricultural sector

The quantification of GHG emissions from agriculture is fundamental to identifying mitigation solutions that are consistent with the goals of achieving greater resilience in production systems, food security, and rural welfare. GHG emissions data are already needed for such varied purposes as guiding national planning for low-emissions development, generating and trading carbon credits, certifying sustainable agriculture practices, informing consumers' choices with regard to reducing their carbon footprints, assessing product supply chains, and supporting farmers in adopting less carbon-intensive farming practices. Demonstrating the robustness, feasibility, and cost effectiveness of agricultural GHG inventories and monitoring is a necessary technical foundation for including agriculture in the international negotiations under the United Nations Framework Convention on Climate Change (UNFCCC), and is needed to provide robust data and methodology platforms for global corporate supply-chain initiatives (e.g., SAFA, FAO 2012).

Given such varied drivers for GHG reductions, there are a number of uses for agricultural GHG information, including (1) reporting and accounting at the national or company level, (2) land-use planning and management to achieve specific objectives, (3) monitoring and evaluating impact of management, (4) developing a credible and thus tradable offset credit, and (5) research and capacity development. The information needs for these uses is likely to differ in the required level of certainty, scale of analysis, and need for comparability across systems or repeatability over time, and they may depend on whether descriptive trends are sufficient or an understanding of drivers and causes are needed. While there are certainly similar needs across uses and users, the necessary methods, data, and models for quantifying GHGs may vary. Common challenges for quantification noted in an informal survey of users of GHG information by Olander et al (2013) include the following.

3.1. Need for user-friendly methods that work across scales, regions, and systems

Much of the data gathered and models developed by the research community provide high confidence in data or indicators computed at one place or for one issue, thus they are relevant for only specific uses, not transparent, or not comparable. These research approaches need to be translated to practitioners though the development of farmer friendly, transparent, comparable, and broadly applicable methods. Many users noted the need for quantification data and methods that work and are accurate across region and scales. One of the interviewed users, Charlotte Streck, summed it up nicely: 'A priority would be to produce comparable datasets for agricultural GHG emissions of particular agricultural practices for a broad set of countries ... with a gradual increase in accuracy'.

3.2. Need for lower cost, feasible approaches

Concerns about cost and complexity of existing quantification methods were raised by a number of users interviewed in the survey. In the field it is difficult to measure changes in GHGs from agricultural management due to spatial and temporal variability, and the scale of the management-induced changes relative to background pools and fluxes. Many users noted data gaps and inconsistencies and insufficient technical capacity and infrastructure to generate necessary information, particularly in developing countries. The need for creative approaches for data collection and analysis, such as crowd sourcing and mobile technology, were noted.

3.3. Need for methods that can crosswalk between emission-reduction strategy and inventories or reporting

A few users emphasized the need for information and quantification approaches that cannot only track GHGs but also help with strategic planning on what to grow where and when to maximize mitigation and adaptation benefits. Methods need to incorporate the quantification context, taking into account climate impacts, viability, and cost of management options. Thus, data and methods are needed that integrate climate impacts into models used to assess the potential and costs of GHG mitigation strategies.

3.4. Need for confidence thresholds and rules that are appropriate for use

Users noted that national inventories through the UNFCCC or Intergovernmental Panel on Climate Change (IPCC) require 95% confidence, while some offset market standards leave confidence levels to the discretion of the developer, using discounts in value for greater uncertainty. Nonetheless, these standards tend to have expectations of 20% confidence or better. In fact, both regulatory and voluntary reporting suffer from large uncertainties in the underlying activity data as well as in emission factors. In some circumstances emissions factors may add as much as 50–150% uncertainty to GHG estimates (IPCC 2006). Uncertainty clearly needs to be assessed in implementing projects and programs. In some cases there are uncertainty thresholds, while in others uncertainty is assessed and used as part of the quantification process. What is not always clear is where uncertainty thresholds are necessary to maintain the usefulness of the information and where they are hindering early progress.

3.5. Easily understood and common metrics for policy and market users

Inventories usually track tons of CO₂ equivalents, while supply-chain and corporate reporting are more likely to track efficiency metrics, such as GHG emissions per unit of product; offsets protocols may combine both approaches. As demand for food rises, efficiency of production becomes an increasingly important metric, even if total CO₂ equivalents need to be tracked in parallel to assess climate impacts. For livestock systems it is unclear which metrics are most important to track, GHGs per unit of meat or milk or perhaps per calorie? Different metrics are likely needed for different uses.

3.6. Capacity development in developing countries

There is need to improve on the current lack of capacities to monitor land use and land-use change and their associated GHG emissions and removals for national inventories (UNFCCC 2008, Romijn et al 2012). Since there are ongoing efforts to improve, data, methods and capacities for monitoring forests in the context of REDD+ (Herold and Skutsch 2011), synergies should be sought to use and build upon joint data sources and approaches, such as remote sensing, field inventories, crowd sourcing. and human capacities to estimate and report on GHG balance in both forests and agriculture.

A number of specific objectives to meet these challenges are discussed in this special issue.

• Improve the accuracy of emissions factors across regional differences.

• Improve national inventory data of management activities, crop type and variety, and livestock breeds.

• Use historical data and data collection over time to show trends.

• Test the extent of model applications through field validation (e.g., can they be used in regions with less data?).

• Enhance technical capacity and infrastructure for data acquisition and for application of mitigation strategies in field programs.

• Increase understanding of which mitigation practices result in more resilient systems.

• Improve understanding of the GHG tradeoffs of expanding fertilizer use.

While data sources and methods are improving and research and operational monitoring are increasing, the international community can be strategic in targeting support for this work and coordinating data and information collection to move toward revised good practice guidelines that would address the particular circumstances and practices dominant in developing countries.

4. Current data infrastructure and systems supporting GHG quantification in the agricultural sector

To understand the challenges facing GHG quantification it is helpful to understand the existing supporting infrastructure and systems for quantification. The existing and developing structures for national and local data acquisition and management are the foundation for the empirical and process-based models used by most countries and projects currently quantifying agricultural greenhouse gases. Direct measurement can be used to complement and supplement such models, but this is not yet sufficient by itself given costs, complexities, and uncertainties.

One of the primary purposes of data acquisition and quantification is for national-level inventories and planning. For such efforts countries are conducting national-level collection of activity data (who is doing which agricultural practices where) and some are also developing national or regional-level emissions factors.

Infrastructure that supports these efforts includes intergovernmental panels, global alliances, and data-sharing networks. Multilateral data sharing for applications, such as the FAO Statistical Database (FAOSTAT) (FAO 2012), the IPCC Emission Factor Database (IPCC 2012), and UNFCCC national inventories (UNFCCC 2012), are building greater consistency and standardization by using global standards such as the IPCC's Good Practice Guidance for Land Use, Land-Use Change and Forestry (e.g., IPCC 1996, 2003, 2006). There is also work on common quantification methods and accounting, for example agreed on global warming potentials for different contributing gases and GHG quantification methodologies for projects (e.g., the Verified Carbon Standard Sustainable Agricultural Land Management [SALM] protocol, VCS 2011). Other examples include the Global Research Alliance on Agricultural Greenhouse Gases (2012) and GRACEnet (Greenhouse gas Reduction through Agricultural Carbon Enhancement network) (USDA Agricultural Research Service 2011), which aim to improve consistency of field measurement and data collection for soil carbon sequestration and soil nitrous oxide fluxes.

Often these national-level activity data and emissions factors are the basis for regional and smaller-scale applications. Such data are used for model-based estimates of changes in GHGs at a project or regional level (Olander et al 2011). To complement national data for regional-, landscape-, or field-level applications, new data are often collected through farmer knowledge or records and field sampling. Ideally such data could be collected in a standardized manner, perhaps through some type of crowd sourcing model to improve regional—and national—level data, as well as to improve consistency of locally collected data.

Data can also be collected by companies working with agricultural suppliers and in country networks, within efforts aimed at understanding firm and product (supply-chain) sustainability and risks (FAO 2009). Such data may feed into various certification processes or reporting requirements from buyers. Unfortunately, this data is likely proprietary. A new process is needed to aggregate and share private data in a way that would not be a competitive concern so such data could complement or supplement national data and add value.

A number of papers in this focus issue discuss issues surrounding quantification methods and systems at large scales, global and national levels, while others explore landscape- and field-scale approaches. A few explore the intersection of top-down and bottom-up data measurement and modeling approaches.

5. The agricultural greenhouse gas quantification project and ERL focus issue

Important land management decisions are often made with poor or few data, especially in developing countries. Current systems for quantifying GHG emissions are inadequate in most low-income countries, due to a lack of funding, human resources, and infrastructure. Most non-Annex 1 countries reporting agricultural emissions to the UNFCCC have used only Tier I default emissions factors (Nihart 2012, unpublished data), yet default numbers are based on a very limited number of studies. Furthermore, most non-Annex I countries have reported their National Communications only one or two times in the period 1990–2010. China, for instance, has not submitted agricultural inventory data since 1994.

As we move toward the next IPCC assessment report on climate change and while UNFCCC negotiations give greater attention to the role of agriculture within international agreements, it is valuable to understand our current and potential near-term capacity to quantify and track emissions and assess mitigation potential in the agriculture sector, providing countries—especially least developed countries (LDCs)—with the information they need to promote and implement actions that, while conducive to mitigation, are also consistent with their rural development and food security goals. The purpose of this focus issue is to improve the knowledge and practice of quantifying GHG emissions from agriculture around the globe. The issue discusses methodological, data, and capacity gaps and needs across scales of quantification, from global and national-scale inventories to landscape- and farm-scale measurement. The inherent features of agriculture and especially smallholder farming have made quantification expensive and complicated, as farming systems and farmers' practices are diverse and impermanent and exhibit high temporal and spatial variability. Quantifying the emissions of the complex crop livestock or diverse cropping systems that characterize smallholder systems presents particular challenges. New ideas, methods, and uses of technology are needed to address these challenges. Many papers in this special issue synthesize the state of the art in their respective fields, analyze gaps, identify innovations, and make recommendations for improving quantification. Special attention is given to methods appropriate to low-income countries, where strategies are needed for getting robust data with extremely limited resources in order to support national mitigation planning within widely accepted standards and thus provide access to essential international support, including climate funding.

Managing agricultural emissions needs to occur in tandem with managing for agricultural productivity, resilience to climate change, and ecosystem impacts. Management decisions and priorities will require measures and information that identify GHG efficiencies in production and reduce inputs without reducing yields, while addressing climate resilience and maintaining other essential environmental services, such as water quality and support for pollinators. Another set of papers in this issue considers the critical synergies and tradeoffs possible between these multiple objectives of mitigation, resilience, and production efficiency to help us understand how we need to tackle these in our quantification systems.

Significant capacity to quantify greenhouse gases is already built, and with some near-term strategic investment, could become an increasingly robust and useful tool for planning and development in the agricultural sector around the world.

Acknowledgments

The Climate Change Agriculture and Food Security Program of the Consultative Group on International Agricultural Research, the Technical Working Group on Agricultural Greenhouse Gases (T-AGG) at Duke University's Nicholas Institute for Environmental Policy Solutions, and the United Nations Food and Agriculture Organization (FAO) have come together to guide the development of this focus issue and associated activities and papers, given their common desire to improve our understanding of the state of agricultural greenhouse gas (GHG) quantification and to advance ideas for building data and methods that will help mitigation policy and programs move forward around the world. We thank the David and Lucile Packard Foundation for their support of this initiative. The project has been developed with guidance from an esteemed steering group of experts and users of mitigation information (http://nicholasinstitute.duke.edu/ecosystem/t-agg/international-project). Many of the papers in this issue were commissioned. Authors of each of the commissioned papers met with guest editors at FAO in Rome in April 2012 to further develop their ideas, synthesize state of the art knowledge and generate new ideas (http://nicholasinstitute.duke.edu/ecosystem/t-agg/events-and-presentations). Additional interesting and important research has come forward through the general call for papers and has been incorporated into this issue.

References

CCAFS (Climate Change, Agriculture and Food Security) 2011 Victories for food and farming in Durban climate deals Press Release 13 December 2011 (http://ccafs.cgiar.org/news/press-releases/victories-food-and-farming-durban-climate-deals)

FAO (Food and Agriculture Organization of the United Nations) 2009 Expert consultation on GHG emissions and mitigation potentials in the agricultural, forestry and fisheries sectors (Rome: FAO)

FAO 2011 Linking Sustainability and Climate Financing: Implications for Agriculture (Rome: FAO)

FAO 2012 FAOSTAT online database (http://faostat.fao.org/)

Global Research Alliance on Agricultural Greenhouse Gases 2012 www.globalresearchalliance.org/

Herold M and Skutsch M 2011 Monitoring, reporting and verification for national REDD+ programmes: two proposals Environ. Res. Lett.6 014002

Hosonuma N, Herold M, De Sy V, De Fries R S, Brockhaus M, Verchot L, Angelsen A and Romijn E 2012 An assessment of deforestation and forest degradation drivers in developing countries Environ. Res. Lett.7 044009

IPCC (Intergovernmental Panel on Climate Change) 1996 Guidelines for National Greenhouse Gas Inventories (Paris: Organisation for Economic Co-operation and Development)

IPCC 2003 Good Practice Guidance for Land Use, Land-Use Change and Forestry (Hayama: IPCC National Greenhouse Gas Inventories Programme)

IPCC 2006 Guidelines for National Greenhouse Gas Inventories. Prepared by the National Greenhouse Gas Inventories Programme ed H S Eggleston et al (Hayama: IGES)

IPCC 2012 IPCC Emission Factor Database (EFDB) (www.ipcc-nggip.iges.or.jp/EFDB/main.php)

Kissinger G, Herold M and De Sy V 2012 Drivers of Deforestation and Forest Degradation: A Synthesis Report for REDD+ Policymakers (Vancouver: Lexeme Consulting) (www.decc.gov.uk/assets/decc/11/tackling-climate-change/international-climate-change/6316-drivers-deforestation-report.pdf)

Murphy D, McCandless M and Drexhage J 2010 Expanding Agriculture's Role in the International Climate Change Regime: Capturing the Opportunities (Winnipeg: International Institute for Sustainable Development)

Nihart A 2012 unpublished data

Olander L, Wollenberg L and Van de Bogert A 2013 Understanding the users and uses of agricultural greenhouse gas information CCAFS/NI T-AGG Report (in progress)

Olander L P and Haugen-Kozyra K with contributions from Del Grosso S, Izaurralde C, Malin D, Paustian K and Salas W 2011 Using Biogeochemical Process Models to Quantify Greenhouse Gas Mitigation from Agricultural Management Projects (Durham, NC: Nicholas Institute for Environmental Policy Solutions, Duke University) (http://nicholasinstitute.duke.edu/ecosystem/t-agg/using-biogeochemical-process)

Romijn J E, Herold M, Kooistra L, Murdiyarso D and Verchot L 2012 Assessing capacities of non-Annex I countries for national forest monitoring in the context of REDD+ Environ. Sci. Policy20 33–48

Smith P et al 2007 Agriculture Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed B Metz, O R Davidson, P R Bosch, R Dave and L A Meyer (Cambridge: Cambridge University Press)

Smith P et al 2008 Greenhouse gas mitigation in agriculture Phil. Trans. R. Soc. B363 789–813

UNFCCC (United Nations Framework Convention on Climate Change) 2008 Financial support provided by the Global Environment Facility for the preparation of National Communications from Parties not included in Annex I to the Convention FCCC/SBI/2008/INF.10 (http://unfccc.int/resource/docs/2008/sbi/eng/inf10.pdf)

UNFCCC 2012 GHG Data from UNFCCC (http://unfccc.int/ghg_data/ghg_data_unfccc/items/4146.php)

USDA (US Department of Agriculture) 2011 Agricultural Research Service (www.ars.usda.gov/research/programs/programs.htm?np_code=204&docid=17271)

VCS (Verified Carbon Standard) 2011 New Methodology: VM0017 Sustainable Agricultural Land Management (http://v-c-s.org/SALM_methodology_approved)

^* We dedicate this special issue to the memory of Daniel Martino, a generous leader in greenhouse gas quantification and accounting from agriculture, land-use change, and forestry.

The potential for improving productivity and increasing the resilience of smallholder agriculture, while also contributing to climate change mitigation, has recently received considerable political attention (Beddington et al 2012). Financial support for improving smallholder agriculture could come from performance-based funding including sale of carbon credits or certified commodities, payments for ecosystem services, and nationally appropriate mitigation action (NAMA) budgets, as well as more traditional sources of development and environment finance. Monitoring the greenhouse gas fluxes associated with changes to agricultural practice is needed for performance-based mitigation funding, and efforts are underway to develop tools to quantify mitigation achieved and assess trade-offs and synergies between mitigation and other livelihood and environmental priorities (Olander 2012). High levels of small scale variability in carbon stocks and emissions in smallholder agricultural systems (Ziegler et al 2012) mean that data intensive approaches are needed for precise and unbiased mitigation monitoring. The cost of implementing such monitoring programmes is likely to be high, and this introduces the risk that projects will not be developed in areas where there is the greatest need for agricultural improvements, which are likely to correspond with areas where existing data or research infrastructure are lacking. When improvements to livelihoods and food security are expected as co-benefits of performance-based mitigation finance, the risk of inaction is borne by the rural poor as well as the global climate.

In situ measurement of carbon accumulation in smallholders' soils are not usually feasible because of the costs associated with sampling in a heterogeneous landscape, although technological advances could improve the situation (Milori et al 2012). Alternatives to in situ measurement are to estimate greenhouse gas fluxes by extrapolating information from existing research to other areas with similar land uses and environmental conditions, or to combine information on land use activities with process-based models that describe expected emissions and carbon accumulation under specified conditions.

Unfortunately long-term studies that have measured biomass and soil organic carbon accumulation in smallholder agriculture are scarce, and default values developed for national level emissions assessments (IPCC 2006) fail to capture local variability and may not scale linearly, so cannot be applied at the project scale without introducing considerable uncertainty and the potential for bias. If there is reliable information on the agricultural activities and environmental conditions at a project site, process-based models can provide accurate estimations of agricultural greenhouse gas fluxes that capture temporal and spatial variability (Olander 2012) but collecting the necessary data to parameterize and drive the models can be costly and time consuming. Assessing and monitoring greenhouse gas fluxes in smallholder agriculture therefore involves a balance between the resources required to collect information from thousands of smallholders across large areas, and the accuracy and precision of model predictions.

Accuracy, or the absence of bias, is clearly an important consideration in the quantification of mitigation benefits for performance-based finance since a bias towards over-estimation of mitigation achieved would risk misallocating limited finance to projects that have not achieved mitigation benefits. Such a bias would also lead to a net increase in emissions if credits were used to offset emissions elsewhere. The accuracy of model predictions is related to uncertainty in model input data, which affects the precision of predictions, and errors in the model structure (Olander 2012). To limit the risk that projects receive credit for mitigation benefits that are not real, a precise-or-conservative approach to carbon accounting has emerged that requires projects to report mitigation benefits to a prescribed level of precision—for example with a 90% confidence interval that is less than 20% of the estimated mitigation benefit; and if this level of precision is not reached then the lower confidence limit of the value is encouraged (VCS 2012). This helps to ensure projects that lack precision in their estimates are biased towards an underestimation of mitigation benefits, which helps limit the risk of increasing net greenhouse gas emissions. It can also mean that finance from the sale of emission reduction certificates is insufficient to support smallholder agricultural projects without donor assistance to cover the cost of project establishment (Seebauer et al 2012).

Understanding the mitigation benefits of improving agricultural practice is important for many purposes other than developing carbon offsets however, and with appropriate accounting approaches risks to smallholders can be reduced and scarce resources channelled to improving land use practices. Less precision is tolerable when making payments for a broad range ecosystem services, or assessing the impacts of donor support, than it is for industrial carbon offsets. Approaches that have greater uncertainty in expected emission reductions or removals may therefore be more appropriate if there is an equal emphasis on the livelihood and environmental benefits of projects as there is on mitigation benefits.

One way to balance the risk of inaction against the need for accuracy is to use process-based models in greenhouse gas accounting and decision support tools, which give users control over the precision and cost of their accounting. Such models can be parameterized and driven using readily available information or best estimates for input data, as well as site specific environmental and activity data. The potential for bias in model predictions can be limited by making use of appropriate models that are validated against regionally specific data. Although process-based models have been adopted for quantifying mitigation benefit in smallholder agriculture systems (for example Seebauer et al 2012), their use is currently limited to those with specialist knowledge or access to detailed site specific information. Web-based tools that link existing global, regional, and local environmental data with process-based models (such as RothC (Coleman and Jenkinson 1996), CENTURY (Parton et al 1987), DNDC (Li et al 1994) and DAYCENT (Del Grosso et al 2002)) that have been validated for specific areas allow users to generate initial estimates of the carbon sequestration potential of agricultural systems simply by specifying the location and intervention. This can support assessments of the feasibility of supporting these interventions through various funding sources. The same tools can also generate accurate, site specific assessments and monitoring to varying levels of detail, when required, given the inclusion of new data collected in situ .

When accounting for greenhouse gases in smallholder agriculture systems users should be free to decide whether it is worthwhile to invest in collecting input data to estimate mitigation benefits with sufficient precision to meet the requirements for carbon offsets, or if greater uncertainty is tolerable. By using tools that do not require specialist support and accepting estimates of mitigation benefits that are less precise, and not necessarily conservative, those providing performance-based finance can help ensure that a greater proportion of limited budgets are spent on the activities that directly benefit smallholders and that are likely to benefit the global climate. The Small-Holder Agriculture Monitoring and Baseline Assessment methodology and prototype tool (SHAMBA 2012), which has been trialled with fifteen agroforestry and conservation agriculture projects in Malawi and is currently under review for validation under the Plan Vivo Standard (Plan Vivo 2012), provides a proof of this concept and a platform on which greater functionality and flexibility can be built. We hope that this, and other similar initiatives, will deliver approaches to greenhouse gas accounting that reduce risks and maximize benefits to smallholder farmers.

References

Beddington J R et al 2012 What next for agriculture after Durban? Science335 289–90

Coleman K and Jenkinson D S 1996 RothC 26.3 a model for the turnover of carbon in soil Evaluation of Soil Organic Matter Models Using Existing, Long-Term Datasets ed D S Powlson, P Smith and J U Smith (Heidelberg: Springer)

Del Grosso S J, Ojima D S, Parton W J, Mosier A R, Petereson G A and Schimel D S 2002 Simulated effects of dryland cropping intensification on soil organic matter and greenhouse gas exchanges using the DAYCENT ecosystem model Environ. Pollut.116 S75–83

IPCC (Intergovenmental Panel on Climate Change) 2006 Guidelines for National Greenhouse Gas Inventories. Prepared by the National Greenhouse Gas Inventories Programme (Hayama: IGES) (www.ipcc-nggip.iges.or.jp/public/2006gl/index.html)

Li C, Frolking S and Harris R 1994 Modeling carbon biogeochemistry in agricultural soils Glob. Biogeochem. Cycles8 237–54

Milori D M B P, Segini A, Da Silva W T L, Posadas A, Mares V, Quiroz R and Ladislau M N 2012 Emerging techniques for soil carbon measurements Climate Change Mitigation and Agriculture ed E Wollenberg, A Nihart, M-L Tapio-Bistrom and M Greig-Gran (Abingdon: Earthscan)

Olander L P 2012 Using biogeochemical process models to quantify greenhouse gas mitigation from agricultural management Climate Change Mitigation and Agriculture ed E Wollenberg, A Nihart, M-L Tapio-Bistrom and M Greig-Gran (Abingdon: Earthscan)

Parton W J, Schimel D S, Cole C V and Ojima D S 1987 Analysis of factors controlling soil organic matter levels in Great Plains grasslands Soil Sci. Soc. Am. J.51 1173–9

Plan Vivo 2012 The Plan Vivo Standard For Community Payments for Ecosystem Services Programmes Version 2012 (available from: www.planvivo.org/)

Seebauer M et al 2012 Carbon accounting for smallholder agricultural soil carbon projects Climate Change Mitigation and Agriculture ed E Wollenberg, A Nihart, M-L Tapio-Bistrom and M Greig-Gran (Abingdon: Earthscan)

SHAMBA (Small-Holder Agriculture Monitoring and Baseline Assessment) 2012 Project webpage: http://tinyurl.com/shambatool

VCS (Verified Carbon Standard) 2012 Veified Carbon Standard Requiements Document Version 3.2 (http://v-c-s.org/program-documents)

Ziegler A D et al 2012 Carbon outcomes of major land-cover transitions in SE Asia: great uncertainties and REDD+ policy implications Glob. Change Biol.18 3087–99

The recent paper by Girod et al (2013) analyses the implications of stringent global GHG mitigation targets for the intensities of, inter alia , broad consumption categories like food, shelter and transport. This type of scenario modeling analysis and inverse reasoning helps us to better understand the potential or required contribution of changes in consumption patterns to mitigation.

This is welcome because while there is a growing literature on the behavioral and consumption dimensions of mitigation, there is still no widely accepted framework for studying systematically the interactions between supply and demand, behavior and technology, production and consumption. So we are left with the question: what do we need to do exactly to stabilize GHG concentrations?

Intuitively, we take our cue from Aristotelian logic: if A implies B, then in order to avoid B we had better prevent A. At this level it is clear that we need either to decarbonize our energy systems to start with, or to suck out CO₂ from the atmosphere. When multiple causes are at work, however, our neat Aristotelian picture is no longer appropriate (Cartwright 2003). Leaving capturing and storage aside, we need to decarbonize our systems, but we also need to reduce the energy intensity, change our personal habits, eat less meat, use more public transportation, etc.

What is the right balance between these factors? Can we do just one thing, say, eat less meat, but not another, and still achieve some pretty ambitious mitigation goals? In other words, what are necessary and what are sufficient sets of measures to reach these goals?

Let us first look at the question of necessary measures. This gets tricky when applied to individual consumers: it is somewhat akin to the notorious question whether a heap of sand is still a heap when you take away one grain (Sainsbury 2011). If you are inclined to say yes, think once more. What happens when you take away another one, and another one, and another one, and so forth? Eventually you are forced call a single grain a heap.

By a similar type of reasoning none of us consumers makes any difference individually. It is tempting to conclude that therefore consumption side mitigation is not sufficient. But it also does not really seem necessary in the strict sense of the word as long as some supply side measure can compensate for a demand side measure not taken. Thus each one of us could go on as before, as long as someone else or some technology is compensating for our own failure to change. To be sure, such elusive argument is, to say the least, not very helpful, but it highlights the difficulty to derive very specific courses of action from aggregate goals.

So it takes a more prescriptive approach to get things going. The pragmatic mitigation wedge analysis by, e.g., Pacala and Socolow (2004) has highlighted that a relatively small number of dedicated and practicable measures is sufficient to achieve deep emission cuts, but the balance of these measures in the analyses is understandably somewhat arbitrary.

Other analysis, based on Integrated Assessment Models (IAMs) has focused more specifically on the questions of where and when measures would be implemented in the most cost-effective manner. From such studies one can learn about carbon price trajectories, technology diffusion rates, and possibly about conditional probabilities for reaching targets over time. However, IAMs are rarely used to assess systematically the necessary or sufficient conditions for reaching a given target, and when they do the outcome often is—with the occasional exception—disappointingly generic.

Moreover, the controversies arising from value-laden allocations derived from IAMs are well-known: in these models emissions are typically reduced where it (supposedly) can be done cheapest, i.e. in low-wage countries, or according to some burden sharing scheme. The allocation of mitigation over time is essentially determined by the magnitude of the discount rate and thus a valuation of future versus present expenditures.

Refreshingly, Girod et al (2013) discuss a selection of allocation schemes across sectors, including consumers, that allow us to get an impression of the requirements and bounds for each of a set of stylized demand activities within the context of a plausible overall IAM story. Thus Girod et al (2013), make progress in addressing consumer behavior in the context of a wider set of activities contributing to GHG emissions and technological options to reduce these, without being committed to any particular allocation scheme.

Further work will have to address issues raised by a recent study (Schweizer and Kriegler 2012) on the limitations of the scenario space in earlier IPCC assessments to avoid past omissions. Moreover, IAMs in general need to become more transparent and more responsive to the needs of stakeholders. They also need to be applied specifically to identify concrete incentives, such as co-benefits of mitigation (Wagner 2012) and mechanisms (beyond stylized carbon markets) that nudge us towards low emission pathways.

References

Cartwright N 2003 Hunting Causes and Using Them: Approaches in Philosophy and Economics 1st edn (Cambridge: Cambridge University Press)

Girod B, Van Vuuren D P and Hertwich E G 2013 Global climate targets and future consumption level: an evaluation of the required GHG intensity Environ. Res. Lett.8 014016

Pacala S and Socolow R 2004 Stabilization wedges: solving the climate problem for the next 50 years with current technologies Science305 968–72

Sainsbury R M 2011 Paradoxes 3rd edn (Cambridge: Cambridge University Press)

Schweizer V J and Kriegler E 2012 Improving environmental change research with systematic techniques for qualitative scenarios Environ. Res. Lett.7 044011

Wagner F 2012 Mitigation here and now or there and then: the role of co-benefits Carbon Manag.3 325–7

Planning and financing of wind power installations require very importantly accurate resource estimation in addition to a number of other considerations relating to environment and economy. Furthermore, individual wind energy installations cannot in general be seen in isolation.

It is well known that the spacing of turbines in wind farms is critical for maximum power production. It is also well established that the collective effect of wind turbines in large wind farms or of several wind farms can limit the wind power extraction downwind. This has been documented by many years of production statistics. For the very large, regional sized wind farms, a number of numerical studies have pointed to additional adverse changes to the regional wind climate, most recently by the detailed studies of Adams and Keith [1]. They show that the geophysical limit to wind power production is likely to be lower than previously estimated. Although this problem is of far future concern, it has to be considered seriously. In their paper they estimate that a wind farm larger than 100 km² is limited to about 1 W m^-2. However, a 20 km² off shore farm, Horns Rev 1, has in the last five years produced 3.98 W m^-2 [5]. In that light it is highly unlikely that the effects pointed out by [1] will pose any immediate threat to wind energy in coming decades.

Today a number of well-established mesoscale and microscale models exist for estimating wind resources and design parameters and in many cases they work well. This is especially true if good local data are available for calibrating the models or for their validation.

The wind energy industry is still troubled by many projects showing considerable negative discrepancies between calculated and actually experienced production numbers and operating conditions. Therefore it has been decided on a European Union level to launch a project, 'The New European Wind Atlas', aiming at reducing overall uncertainties in determining wind conditions.

The project is structured around three areas of work, to be implemented in parallel.

• Creation and publication of a European wind atlas in electronic form [2], which will include the underlying data and a new EU wind climate database which will as a minimum include: wind resources and their associated uncertainty; extreme wind and uncertainty; turbulence characteristics; adverse weather conditions such as heavy icing, electrical storms and so on together with the probability of occurrence; the level of predictability for short-term forecasting and assessment of uncertainties; guidelines and best practices for the use of data especially for micro-siting.

• Development of dynamical downscaling methodologies and open-source models validated through measurement campaigns, to enable the provision of accurate wind resource and external wind load climatology and short-term prediction at high spatial resolution and covering Europe. The developed downscaling methodologies and models will be fully documented and made publicly available and will be used to produce overview maps of wind resources and other relevant data at several heights and at high horizontal resolution.

• Measurement campaigns to validate the model chain used in the wind atlas. At least five coordinated measurement campaigns will be undertaken and will cover complex terrains (mountains and forests), offshore, large changes in surface characteristics (roughness change) and cold climates.

One of the great challenges to the project is the application of mesoscale models for wind resource calculation, which is by no means a simple matter [3]. The project will use global reanalysis data as boundary conditions. These datasets, which are time series of the large-scale meteorological situation covering decades, have been created by assimilation of measurement data from around the globe in a dynamical consistent fashion using large-scale numerical models. For wind energy, the application of the reanalysis datasets is as a long record of the large-scale wind conditions. The large-scale reanalyses are performed in only a few global weather prediction centres using models that have been developed over many years, and which are still being developed and validated and are being used in operational services. Mesoscale models are more diverse, but nowadays quite a number have a proven track record in applications such as regional weather prediction and also wind resource assessment. There are still some issues, and use of model results without proper validation may lead to gross errors. For resource assessment it is necessary to include direct validation with in situ observed wind data over sufficiently long periods. In doing so, however, the mesoscale model output must be downscaled using some microscale physical or empirical/statistical model. That downscaling process is not straightforward, and the microscale models themselves tend to disagree in some terrain types as shown by recent blind tests [4]. All these 'technical' details and choices, not to mention the model formulation itself, the numerical schemes used, and the effective spatial and temporal resolution, can have a significant impact on the results. These problems, as well as the problem of how uncertainties are propagated through the model chain to the calculated wind resources, are central in the work with the New European Wind Atlas. The work of [1] shows that when wind energy has been implemented on a very massive scale, it will affect the power production from entire regions and that has to be taken into account.

References

[1] Adams A S and Keith D W 2013 Are global wind power resource estimates overstated? Environ. Res. Lett.8 015021

[2] 2011 A New EU Wind Energy Atlas: Proposal for an ERANET+ Project (Produced by the TPWind Secretariat) Nov.

[3] Petersen E L Troen I 2012 Wind conditions and resource assessment WIREs Energy Environ.1 206–17

[4] Bechmann A, Sørensen N N, Berg J, Mann J Rethore P-E 2011 The Bolund experiment, part II: blind comparison of microscale flow models Boundary-Layer Meteorol.141 245–71

[5] www.lorc.dk/offshore-wind-farms-map/horns-rev-1

www.ens.dk

Rahmstorf et al 's (2012) conclusion that observed climate change is comparable to projections, and in some cases exceeds projections, allows further inferences if we can quantify changing climate forcings and compare those with projections. The largest climate forcing is caused by well-mixed long-lived greenhouse gases. Here we illustrate trends of these gases and their climate forcings, and we discuss implications. We focus on quantities that are accurately measured, and we include comparison with fixed scenarios, which helps reduce common misimpressions about how climate forcings are changing.

Annual fossil fuel CO₂ emissions have shot up in the past decade at about 3% yr^-1, double the rate of the prior three decades (figure 1). The growth rate falls above the range of the IPCC (2001) 'Marker' scenarios, although emissions are still within the entire range considered by the IPCC SRES (2000). The surge in emissions is due to increased coal use (blue curve in figure 1), which now accounts for more than 40% of fossil fuel CO₂ emissions.

Figure 1. CO₂ annual emissions from fossil fuel use and cement manufacture, an update of figure 16 of Hansen (2003) using data of British Petroleum (BP 2012) concatenated with data of Boden et al (2012).

The resulting annual increase of atmospheric CO₂ (12-month running mean) has grown from less than 1 ppm yr^-1 in the early 1960s to an average ~2 ppm yr^-1 in the past decade (figure 2). Although CO₂ measurements were not made at sufficient locations prior to the early 1980s to calculate the global mean change, the close match of global and Mauna Loa data for later years suggests that Mauna Loa data provide a good approximation of global change (figure 2), thus allowing a useful estimate of annual global change beginning with the initiation of Mauna Loa measurements in 1958 by Keeling et al (1973).

Figure 2. Annual increase of CO₂ based on data from the NOAA Earth System Research Laboratory (ESRL 2012). CO₂ change and global temperature change are 12-month running means of differences for the same month of consecutive years. Nino index (Nino3.4 area) is 12-month running mean. Both temperature indices use data from Hansen et al (2010). Annual mean CO₂ amount in 1958 was 315 ppm (Mauna Loa) and in 2012 was 394 ppm (Mauna Loa) and 393 ppm (Global).

Interannual variability of CO₂ growth is correlated with ENSO (El Nino Southern Oscillation) variations of tropical temperatures (figure 2). Ocean–atmosphere CO₂ exchange is affected by ENSO (Chavez et al 1999), but ENSO seems to have a greater impact on atmospheric CO₂ via the terrestrial carbon cycle through effects on the water cycle, temperature, and fire, as discussed in a large body of literature (referenced, e.g., by Schwalm et al 2011). In addition, volcanoes, such as the 1991 Mount Pinatubo eruption, slow the increase of atmospheric CO₂ (Rothenberg et al 2012), at least in part because photosynthesis is enhanced by the increased proportion of diffuse sunlight (Gu et al 2003, Mercado et al 2009). Watson (1997) suggests that volcanic dust deposited on the ocean surface may also contribute to CO₂ uptake by increasing ocean productivity.

An important question is whether ocean and terrestrial carbon sinks will tend to saturate as human-made CO₂ emissions continue. Piao et al (2008) and Zhao and Running (2010) suggest that there already may be a reduction of terrestrial carbon uptake, while Le Quéréet al (2007) and Schuster and Watson (2007) find evidence of decreased carbon uptake in the Southern Ocean and North Atlantic Ocean, respectively. However, others (Knorr 2009, Sarmiento et al 2010, Ballantyne et al 2012) either cast doubt on the reality of a reduced uptake strength or find evidence for increased uptake.

An informative presentation of CO₂ observations is the ratio of annual CO₂ increase in the air divided by annual fossil fuel CO₂ emissions (Keeling et al 1973), the 'airborne fraction' (figure 3, right scale). An alternative definition of airborne fraction includes in the denominator of this ratio an estimated net anthropogenic CO₂ source from changes in land use, but this latter term is much more uncertain than the two terms involved in the Keeling et al (1973) definition. For example, analysis by Harris et al (2012) reveals a range as high as a factor of 2–4 in estimates of recent land use emissions; see also the discussion by Sarmiento et al (2010). However, note that the airborne fraction becomes smaller when estimated land use emissions are included, with the uptake fraction (one minus airborne fraction) typically greater than 0.5.

Figure 3. Fossil fuel CO₂ emissions (left scale) and airborne fraction, i.e., the ratio of observed atmospheric CO₂ increase to fossil fuel CO₂ emissions. Final three points are 5-, 3- and 1-year means.

The simple Keeling airborne fraction, clearly, is not increasing (figure 3). Thus the net ocean plus terrestrial sink for carbon emissions has increased by a factor of 3–4 since 1958, accommodating the emissions increase by that factor.

Remarkably, and we will argue importantly, the airborne fraction has declined since 2000 (figure 3) during a period without any large volcanic eruptions. The 7-year running mean of the airborne fraction had remained close to 60% up to 2000, except for the period affected by Pinatubo. The airborne fraction is affected by factors other than the efficiency of carbon sinks, most notably by changes in the rate of fossil fuel emissions (Gloor et al 2010). However, it is the dependence of the airborne fraction on fossil fuel emission rate that makes the post-2000 downturn of the airborne fraction particularly striking. The change of emission rate in 2000 from 1.5% yr^-1 to 3.1% yr^-1 (figure 1), other things being equal, would have caused a sharp increase of the airborne fraction (the simple reason being that a rapid source increase provides less time for carbon to be moved downward out of the ocean's upper layers).

A decrease in land use emissions during the past decade (Harris et al 2012) could contribute to the decreasing airborne fraction in figure 3, although Malhi (2010) presents evidence that tropical forest deforestation and regrowth are approximately in balance, within uncertainties. Land use change can be only a partial explanation for the decrease of the airborne fraction; something more than land use change seems to be occurring.

We suggest that the huge post-2000 increase of uptake by the carbon sinks implied by figure 3 is related to the simultaneous sharp increase in coal use (figure 1). Increased coal use occurred primarily in China and India (Boden et al 2012; BP 2012; see graphs at www.columbia.edu/~mhs119/Emissions/Emis_moreFigs/). Satellite radiance measurements for July–December, months when desert dust does not dominate aerosol amount, yield an increase of aerosol optical depth in East Asia of about 4% yr^-1 during 2000–2006 (van Donkelaar et al 2008). Associated gaseous and particulate emissions increased rapidly after 2000 in China and India (Lu et al 2011, Tian et al 2010). Some decrease of the sulfur component of emissions occurred in China after 2006 as wide application of flue-gas desulfurization began to be initiated (Lu et al 2010), but this was largely offset by continuing emission increases from India (Lu et al 2011).

We suggest that the surge of fossil fuel use, mainly coal, since 2000 is a basic cause of the large increase of carbon uptake by the combined terrestrial and ocean carbon sinks. One mechanism by which fossil fuel emissions increase carbon uptake is by fertilizing the biosphere via provision of nutrients essential for tissue building, especially nitrogen, which plays a critical role in controlling net primary productivity and is limited in many ecosystems (Gruber and Galloway 2008). Modeling (e.g., Thornton et al 2009) and field studies (Magnani et al 2007) confirm a major role of nitrogen deposition, working in concert with CO₂ fertilization, in causing a large increase in net primary productivity of temperate and boreal forests. Sulfate aerosols from coal burning also might increase carbon uptake by increasing the proportion of diffuse insolation, as noted above for Pinatubo aerosols, even though the total solar radiation reaching the surface is reduced.

Thus we see the decreased CO₂ airborne fraction since 2000 as sharing some of the same causes as the decreased airborne fraction after the Pinatubo eruption (figure 3). CO₂ fertilization is likely the major effect, as a plausible addition of 5 TgN yr^-1 from fossil fuels and net ecosystem productivity of 200 kgC kgN^-1 (Magnani et al 2007, 2008) yields an annual carbon drawdown of 1 GtC yr^-1, which is of the order of what is needed to explain the post-2000 anomaly in airborne CO₂. However, an aerosol-induced increase of diffuse radiation might also contribute. Although tropospheric aerosol properties are not accurately monitored, there are suggestions of an upward trend of stratospheric background aerosols since 2000 (Hofmann et al 2009, Solomon et al 2011), which could be a consequence of more tropospheric aerosols at low latitudes where injection of tropospheric air into the stratosphere occurs (Holton et al 1995). We discuss climate implications of the reduced CO₂ airborne fraction after presenting data for other greenhouse gases.

Atmospheric CH₄ is increasing more slowly than in IPCC scenarios (figure 4), which were defined more than a decade ago (IPCC 2001). However, after remaining nearly constant for several years, CH₄ has increased during the past five years, pushing slightly above the level that was envisaged in the Alternative Scenario of Hansen et al (2000). Reduction of CH₄, besides slowdown in CO₂ growth in the twenty first century and a decline of CO₂ in the twenty second century, is a principal requirement to achieve a low climate forcing that stabilizes climate, in part because CH₄ also affects tropospheric ozone and stratospheric water vapor. The Alternative Scenario, defined in detail by Hansen and Sato (2004), keeps maximum global warming at ~1.5 °C relative to 1880–1920, under the assumption that fast-feedback climate sensitivity is ~3 °C for doubled CO₂ (Hansen et al 2007). The Alternative Scenario allows CO₂ to reach 475 ppm in 2100 before declining slowly; this scenario assumes that reductions of non-CO₂ greenhouse gases and black carbon aerosols can be achieved sufficient to balance the warming effect of likely future decreases of reflective aerosols.

Figure 4. Observed atmospheric CH₄ amount and scenarios for twenty first century. Alternative scenario (Hansen et al 2000, Hansen and Sato 2004) yields maximum global warming ~1.5 °C above 1880–1920. Other scenarios are from IPCC (2001). Forcing on right hand scale is adjusted forcing, Fa, relative to values in 2000 (Hansen et al 2007).

There are anthropogenic sources of CH₄ that potentially could be reduced, indeed, the leveling off of CH₄ amount during the past 20 years seems to have been caused by decreased venting in oil fields (Simpson et al 2012), but the feasibility of overall CH₄ reduction also depends on limiting global warming itself, because of the potential for amplifying climate-CH₄ feedbacks (Archer et al 2009, Koven et al 2011). Furthermore, reduction of atmospheric CH₄ might become problematic if unconventional mining of gas, such as 'hydro-fracking', expands widely (Cipolla 2009), as discussed further below.

The growth rate for the total climate forcing by well-mixed greenhouse gases has remained below the peak values reached in the 1970s and early 1980s, has been relatively stable for about 20 years, and is falling below IPCC (2001) scenarios (figure 5). However, the greenhouse gas forcing is growing faster than in the Alternative Scenario. MPTGs and OTGs in figure 5 are Montreal Protocol Trace Gases and Other Trace Gases (Hansen and Sato 2004).

Figure 5. Five-year mean of the growth rate of climate forcing by well-mixed greenhouse gases, an update of figure 4 of Hansen and Sato (2004). Forcing calculations use equations of Hansen et al (2000). The moderate uncertainties in radiative calculations affect the scenarios and actual greenhouse gas results equally and thus do not alter the conclusion that the actual forcing falls below that of the IPCC scenarios.

If greenhouse gases were the only climate forcing, we would be tempted to infer from Rahmstorf's conclusion (that actual climate change has exceeded IPCC projections) and our conclusion (that actual greenhouse gas forcings are slightly smaller than IPCC scenarios) that actual climate sensitivity is on the high side of what has generally been assumed. Although that may be a valid inference, the evidence is weakened by the fact that other climate forcings are not negligible in comparison to the greenhouse gases and must be accounted for.

Natural forcings, by changing solar irradiance and volcanic aerosols, are well-measured since the late 1970s and included in most IPCC (2007) climate simulations. The difficulty is human-made aerosols. Aerosols are readily detected in satellite observations, but determination of their climate forcing requires accurate knowledge of changes in aerosol amount, size distribution, absorption and vertical distribution on a global basis—as well as simultaneous data on changes in cloud properties to allow inference of the indirect aerosol forcing via induced cloud changes. Unfortunately, the first satellite mission capable of measuring the needed aerosol characteristics (Aerosol Polarimetry Sensor on the Glory satellite, (Mishchenko et al 2007)) suffered a launch failure and as yet there are no concrete plans for a replacement mission.

The human-made aerosol climate forcing thus remains uncertain. IPCC (2007) concludes that aerosols are a negative (cooling) forcing, probably between -0.5 and -2.5 W m^-2. Hansen et al (2011), based mainly on analysis of Earth's energy imbalance, derive an aerosol forcing -1.6 ± 0.3 W m^-2, consistent with an analysis of Murphy et al (2009) that suggests an aerosol forcing about -1.5 W m^-2 (see discussion in Hansen et al (2011)). This large negative aerosol forcing reduces the net climate forcing of the past century by about half (IPCC 2007; figure 1 of Hansen et al 2011). Coincidentally, this leaves net climate forcing comparable to the CO₂ forcing alone.

Reduction of the net human-made climate forcing by aerosols has been described as a 'Faustian bargain' (Hansen and Lacis 1990, Hansen 2009), because the aerosols constitute deleterious particulate air pollution. Reduction of the net climate forcing by half will continue only if we allow air pollution to build up to greater and greater amounts. More likely, humanity will demand and achieve a reduction of particulate air pollution, whereupon, because the CO₂ from fossil fuel burning remains in the surface climate system for millennia, the 'devil's payment' will be extracted from humanity via increased global warming.

So is the new data we present here good news or bad news, and how does it alter the 'Faustian bargain'? At first glance there seems to be some good news. First, if our interpretation of the data is correct, the surge of fossil fuel emissions, especially from coal burning, along with the increasing atmospheric CO₂ level is 'fertilizing' the biosphere, and thus limiting the growth of atmospheric CO₂. Also, despite the absence of accurate global aerosol measurements, it seems that the aerosol cooling effect is probably increasing based on evidence of aerosol increases in the Far East and increasing 'background' stratospheric aerosols.

Both effects work to limit global warming and thus help explain why the rate of global warming seems to be less this decade than it has been during the prior quarter century. This data interpretation also helps explain why multiple warnings that some carbon sinks are 'drying up' and could even become carbon sources, e.g., boreal forests infested by pine bark beetles (Kurz et al 2008) and the Amazon rain forest suffering from drought (Lewis et al 2011), have not produced an obvious impact on atmospheric CO₂.

However, increased CO₂ uptake does not necessarily mean that the biosphere is healthier or that the increased carbon uptake will continue indefinitely (Matson et al 2002, Galloway et al 2002, Heimann and Reichstein 2008, Gruber and Galloway 2008). Nor does it change the basic facts about the potential magnitude of the fossil fuel carbon source (figure 6) and the long lifetime of the CO₂ in the surface carbon reservoirs (atmosphere, ocean, soil, biosphere) once the fossil fuels are burned (Archer 2005). Fertilization of the biosphere affects the distribution of the fossil fuel carbon among these reservoirs, at least on the short run, but it does not alter the fact that the fossil carbon will remain in these reservoirs for millennia.

Figure 6. Fossil fuel CO₂ emissions and carbon content (1 ppm atmospheric CO₂~2.12 GtC). Historical emissions are from Boden et al (2012). Estimated reserves and potentially recoverable resources are based on energy content values of Energy Information Administration (EIA 2011), German Advisory Council (GAC 2011), and Global Energy Assessment (GEA 2012). We convert energy content to carbon content using emission factors of Table 4.2 of IPCC (2007) for coal, gas, and conventional oil, and, following IPCC, we use an emission factor of unconventional oil the same as that for coal.

Humanity, so far, has burned only a small portion (purple area in figure 6) of total fossil fuel reserves and resources. Yet deleterious effects of warming are apparent (IPCC 2007), even though only about half of the warming due to gases now in the air has appeared, the remainder still 'in the pipeline' due to the inertia of the climate system (Hansen et al 2011). Already it seems difficult to avoid passing the 'guardrail' of no more than 2 °C global warming that was agreed in the Copenhagen Accord of the United Nations Framework Convention on Climate Change (UNFCCC 2010). And Hansen et al (2008), based primarily on paleoclimate data and evidence of deleterious climate impacts already at 385 ppm CO₂, concluded that an appropriate initial target for CO₂ was 350 ppm, which implied a global temperature limit, relative to 1880–1920 of about 1 °C. What is clear is that most of the remaining fossil fuels must be left in the ground if we are to avoid dangerous human-made interference with climate.

The principal implication of our present analysis probably relates to the Faustian bargain. Increased short-term masking of greenhouse gas warming by fossil fuel particulate and nitrogen pollution represents a 'doubling down' of the Faustian bargain, an increase in the stakes. The more we allow the Faustian debt to build, the more unmanageable the eventual consequences will be. Yet globally there are plans to build more than 1000 coal-fired power plants (Yang and Cui 2012) and plans to develop some of the dirtiest oil sources on the planet (EIA 2011). These plans should be vigorously resisted. We are already in a deep hole—it is time to stop digging.

Acknowledgments

We thank ClimateWorks, Energy Foundation, Gerry Lenfest (Lenfest Foundation), Lee Wasserman (Rockefeller Family Foundation), and Stephen Toben (Flora Family Foundation) for research and communications support.

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This study considers different projections of climate-driven sea-level rise and uses a recently developed, generalized analytical model to investigate the responses of sea intrusion in unconfined sloping coastal aquifers to climate-driven sea-level rise. The results show high nonlinearity in these responses, implying important thresholds, or tipping points, beyond which the responses of seawater intrusion to sea-level rise shift abruptly from a stable state of mild change responses to a new stable state of large responses to small changes that can rapidly lead to full seawater intrusion into a coastal aquifer. The identified tipping points are of three types: (a) spatial, for the particular aquifers (sections) along a coastline with depths that imply critical risk of full sea intrusion in response to even small sea-level rise; (b) temporal, for the critical sea-level rise and its timing, beyond which the change responses and the risk of complete sea intrusion in an aquifer shift abruptly from low to very high; and (c) managerial, for the critical minimum values of groundwater discharge and hydraulic head that inland water management must maintain in an aquifer in order to avoid rapid loss of control and complete sea intrusion in response to even small sea-level rise. The existence of a tipping point depends on highly variable aquifer properties and groundwater conditions, in combination with more homogeneous sea conditions. The generalized analytical model used in this study facilitates parsimonious quantification and screening of sea-intrusion risks and tipping points under such spatio-temporally different condition combinations along extended coastlines.

We assessed the effects of nutrient enrichment on three stream ecosystems running through distinct biomes (Mediterranean, Pampean and Andean). We increased the concentrations of N and P in the stream water 1.6–4-fold following a before–after control–impact paired series (BACIPS) design in each stream, and evaluated changes in the biomass of bacteria, primary producers, invertebrates and fish in the enriched (E) versus control (C) reaches after nutrient addition through a predictive-BACIPS approach. The treatment produced variable biomass responses (2–77% of explained variance) among biological communities and streams. The greatest biomass response was observed for algae in the Andean stream (77% of the variance), although fish also showed important biomass responses (about 9–48%). The strongest biomass response to enrichment (77% in all biological compartments) was found in the Andean stream. The magnitude and seasonality of biomass responses to enrichment were highly site specific, often depending on the basal nutrient concentration and on windows of ecological opportunity (periods when environmental constraints other than nutrients do not limit biomass growth). The Pampean stream, with high basal nutrient concentrations, showed a weak response to enrichment (except for invertebrates), whereas the greater responses of Andean stream communities were presumably favored by wider windows of ecological opportunity in comparison to those from the Mediterranean stream. Despite variation among sites, enrichment globally stimulated the algal-based food webs (algae and invertebrate grazers) but not the detritus-based food webs (bacteria and invertebrate shredders). This study shows that nutrient enrichment tends to globally enhance the biomass of stream biological assemblages, but that its magnitude and extent within the food web are complex and are strongly determined by environmental factors and ecosystem structure.

The evolution of global and regional anthropogenic SO₂ emissions in the last decade has been estimated through a bottom-up calculation. After increasing until about 2006, we estimate a declining trend continuing until 2011. However, there is strong spatial variability, with North America and Europe continuing to reduce emissions, with an increasing role of Asia and international shipping. China remains a key contributor, but the introduction of stricter emission limits followed by an ambitious program of installing flue gas desulfurization on power plants resulted in a significant decline in emissions from the energy sector and stabilization of total Chinese SO₂ emissions. Comparable mitigation strategies are not yet present in several other Asian countries and industrial sectors in general, while emissions from international shipping are expected to start declining soon following an international agreement to reduce the sulfur content of fuel oil. The estimated trends in global SO₂ emissions are within the range of representative concentration pathway (RCP) projections and the uncertainty previously estimated for the year 2005.

A multi-model ensemble of regional climate projections for Europe is employed to investigate how the time of emergence (TOE) for seasonal sums and maxima of daily precipitation depends on spatial scale. The TOE is redefined for emergence from internal variability only; the spread of the TOE due to imperfect climate model formulation is used as a measure of uncertainty in the TOE itself. Thereby, the TOE becomes a fundamentally limiting timescale and translates into a minimum spatial scale on which robust conclusions can be drawn about precipitation trends. Thus, minimum temporal and spatial scales for adaptation planning are also given. In northern Europe, positive winter trends in mean and heavy precipitation, and in southwestern and southeastern Europe, summer trends in mean precipitation already emerge within the next few decades. However, across wide areas, especially for heavy summer precipitation, the local trend emerges only late in the 21st century or later. For precipitation averaged to larger scales, the trend, in general, emerges earlier.

PM_2.5 (particulate matter with aerodynamic diameters less than 2.5 μm) and PM₁₀ (particulate matter with aerodynamic diameters less than 10 μm) samples were collected by high-volume air samplers simultaneously at a rural site and an urban site in Beijing, China. Various carbohydrates were quantified by high-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD), including the sugar alcohols mannitol and arabitol, recently proposed as molecular tracers for fungal aerosol. The annual average concentrations of arabitol in PM_2.5 and PM₁₀ at the urban site were 7.4 ± 9.4 and 21.0 ± 20.4 ng m⁻³, and the respective mannitol concentrations were 10.3 ± 9.5 and 31.9 ± 26.9 ng m⁻³. During summer and autumn, higher arabitol and mannitol levels than during spring and winter were observed in coarse particles, probably due to different dominant sources of fungal spores in different seasons. In the dry season (i.e., winter and spring) in Beijing, probably only the suspension from exposed surfaces (e.g., soil resuspension, transported dust, etc) can be regarded as the main sources for fungal aerosols. On the other hand, in summer and autumn, fungal spores in the atmosphere can be derived from more complex sources, including plants, vegetation decomposition and agricultural activity, such as ploughing; these fungal spore sources may contribute more to coarse PM. Moreover, statistical analysis according to typical seasonal patterns, including a dry season (December 2010 to March 2011) and a wet season (July to September 2011), revealed different variations of fungal spores in different seasons. Although fungal spore levels at rural sites were reported to be consistently higher than those at urban sites in other studies, our findings showed the opposite pattern, indicating a high abundance of fungal spores in the urban area of this Chinese megacity.

Temporal and spatial patterns in northern midlatitude atmospheric ozone levels measured outside the cabin by MOZAIC aircraft are investigated to consider trends in human exposure to ozone during commercial flights. Average and 1 h peak ozone levels for flights during 2000 to 2005 range from 50 to 500 ppb, and 90 to 900 ppb, respectively, for flights between Munich and New York (N = 318), or Chicago (N = 372), or Los Angeles (N = 175). Ozone levels vary through the year as expected on the basis of known trends in tropopause height. Timing and amplitude of the mean annual cycle are consistent across routes. A linear regression model predicts flight average and 1 h peak levels that are, respectively, 180 ppb and 360 ppb higher in April than during October–November. High ozone outliers to the model occur in January–March in the western North Atlantic region and may be linked to episodic stratosphere-to-troposphere exchanges. No systematic variation in atmospheric ozone is observed with latitude for the routes surveyed. On average, ozone levels increase by 70 ppb per km increase in flight altitude, although the relationship between altitude and ozone level is highly variable. In US domestic airspace, ozone levels greater than 100 ppb are routinely encountered outside the aircraft cabin.

Wood and charcoal supply the majority of sub-Saharan Africa's rural energy needs. The long-term supply of fuelwood is in jeopardy given high consumption rates. Using airborne light detection and ranging (LiDAR), we mapped and investigated savanna aboveground biomass across contrasting land uses, ranging from densely populated communal areas to highly protected areas in the Lowveld savannas of South Africa. We combined the LiDAR observations with socio-economic data, biomass production rates and fuelwood consumption rates in a supply–demand model to predict future fuelwood availability. LiDAR-based biomass maps revealed disturbance gradients around settlements up to 1.5 km, corresponding to the maximum distance walked to collect fuelwood. At current levels of fuelwood consumption (67% of households use fuelwood exclusively, with a 2% annual reduction), we calculate that biomass in the study area will be exhausted within thirteen years. We also show that it will require a 15% annual reduction in consumption for eight years to a level of 20% of households using fuelwood before the reduction in biomass appears to stabilize to sustainable levels. The severity of dwindling fuelwood reserves in African savannas underscores the importance of providing affordable energy for rural economic development.

Trends in the duration or extent of snow cover are expected to feedback to temperature trends. We analyzed trends in dates of onset and termination of snow cover in relation to temperature over the past 27 years (1980–2006) from over 636 meteorological stations in the Northern Hemisphere. Different trends in snow duration are observed over North America and Eurasia. Over North America, the termination date of snow cover remained stable during the 27 years, whereas over Eurasia it has advanced by 2.6 ± 5.6 d decade⁻¹. Earlier snow cover termination is systematically correlated on a year-to-year basis with a positive temperature anomaly during the snowmelt month with a sensitivity of −0.077 °C d⁻¹. These snow feedbacks to air temperature are more important in spring, because high net radiation is coupled with thin snow cover.

Ongoing global warming induced by anthropogenic emissions has opened the debate as to whether geoengineering is a 'quick fix' option. Here we analyse the intended and unintended effects of one specific geoengineering approach, which is enhanced weathering via the open ocean dissolution of the silicate-containing mineral olivine. This approach would not only reduce atmospheric CO₂ and oppose surface ocean acidification, but would also impact on marine biology. If dissolved in the surface ocean, olivine sequesters 0.28 g carbon per g of olivine dissolved, similar to land-based enhanced weathering. Silicic acid input, a byproduct of the olivine dissolution, alters marine biology because silicate is in certain areas the limiting nutrient for diatoms. As a consequence, our model predicts a shift in phytoplankton species composition towards diatoms, altering the biological carbon pumps. Enhanced olivine dissolution, both on land and in the ocean, therefore needs to be considered as ocean fertilization. From dissolution kinetics we calculate that only olivine particles with a grain size of the order of 1 μm sink slowly enough to enable a nearly complete dissolution. The energy consumption for grinding to this small size might reduce the carbon sequestration efficiency by ∼30%.

Poyang Lake is China's largest freshwater lake with a high degree of spatio-temporal variation. The lake has shrunk in size in recent years, resulting in significant hydrological, ecological and economic consequences. It remains unknown whether the shrinkage is a trend or a regime shift, which is of high importance for policymakers as it may lead to different decisions. This study constructed a four-decade record of the lake area using multi-temporal satellite images and hydrological data. The Mann–Kendall analysis revealed a decreasing trend of Poyang Lake but it was statistically insignificant. The Rodionov sequential approach disclosed an abrupt change of the lake in 2006, implying a regime shift. Basically, the lake change was a synthetic result of precipitation, evapotranspiration and outflow discharge. However, precipitation and outflow did not show any significant trend or abrupt change, and evapotranspiration had an increasing trend in addition to an abrupt change in 1998. The trigger for the recent lake declines was principally ascribed to a weakened blocking effect of the Yangtze River. The findings provide an example of hydrologic non-stationarity and are valuable for effective promotion of climate adaptation and water resource management.

Projections of future changes in weather extremes on the regional and local scale depend on a realistic representation of trends in extremes in regional climate models (RCMs). We have tested this assumption for moderate high temperature extremes (the annual maximum of the daily maximum 2 m temperature, T_ann.max). Linear trends in T_ann.max from historical runs of 14 RCMs driven by atmospheric reanalysis data are compared with trends in gridded station data. The ensemble of RCMs significantly underestimates the observed trends over most of the north-western European land surface. Individual models do not fare much better, with even the best performing models underestimating observed trends over large areas. We argue that the inability of RCMs to reproduce observed trends is probably not due to errors in large-scale circulation. There is also no significant correlation between the RCM T_ann.max trends and trends in radiation or Bowen ratio. We conclude that care should be taken when using RCM data for adaptation decisions.

In order to quantify the impact of recent efforts to abate surface ozone (O₃) pollution, we analyze changes in the frequency and return level of summertime (JJA) high surface O₃ events over the eastern United States (US) from 1988–1998 to 1999–2009. We apply methods from extreme value theory (EVT) to maximum daily 8-hour average ozone (MDA8 O₃) observed by the Clean Air Status and Trends Network (CASTNet) and define O₃ extremes as days on which MDA8 O₃ exceeds a threshold of 75 ppb (MDA8 O₃>75). Over the eastern US, we find that the number of summer days with MDA8 O₃>75 declined on average by about a factor of two from 1988–1998 to 1999–2009. The applied generalized Pareto distribution (GPD) fits the high tail of MDA8 O₃ much better than a Gaussian distribution and enables the derivation of probabilistic return levels (describing the probability of exceeding a value x within a time window T) for high O₃ pollution events. This new approach confirms the significant decline in both frequency and magnitude of high O₃ pollution events over the eastern US during recent years reported in prior studies. Our analysis of 1-yr and 5-yr return levels at each station demonstrates the strong impact of changes in air quality regulations and subsequent control measures (e.g., the 'NO_x SIP Call'), as the 5-yr return levels of the period 1999–2009 correspond roughly to the 1-yr return levels of the earlier time period (1988–1998). Regionally, the return levels dropped between 1988–1998 and 1999–2009 by about 8 ppb in the Mid-Atlantic (MA) and Great Lakes (GL) regions, while the strongest decline, about 13 ppb, is observed in the Northeast (NE) region. Nearly all stations (21 out of 23) have 1-yr return levels well below 100 ppb and 5-yr return levels well below 110 ppb in 1999–2009. Decreases in eastern US O₃ pollution are largest after full implementation of the nitrogen oxide (NO_x) reductions under the 'NO_x SIP Call'. We conclude that the application of EVT methods provides a useful approach for quantifying return levels of high O₃ pollution in probabilistic terms, which may help to guide long-term air quality planning.

The prediction of global sea-level rise is one of the major challenges of climate science. While process-based models are still being improved to capture the complexity of the processes involved, semi-empirical models, exploiting the observed connection between global-mean sea level and global temperature and calibrated with data, have been developed as a complementary approach. Here we investigate whether twentieth century sea-level rise could have been predicted with such models given a knowledge of twentieth century global temperature increase. We find that either proxy or early tide gauge data do not hold enough information to constrain the model parameters well. However, in combination, the use of proxy and tide gauge sea-level data up to 1900 AD allows a good prediction of twentieth century sea-level rise, despite this rise being well outside the rates experienced in previous centuries during the calibration period of the model. The 90% confidence range for the linear twentieth century rise predicted by the semi-empirical model is 13–30 cm, whereas the observed interval (using two tide gauge data sets) is 14–26 cm.

Global land use research to date has focused on quantifying uncertainty effects of three major drivers affecting competition for land: the uncertainty in energy and climate policies affecting competition between food and biofuels, the uncertainty of climate impacts on agriculture and forestry, and the uncertainty in the underlying technological progress driving efficiency of food, bioenergy and timber production. The market uncertainty in fossil fuel prices has received relatively less attention in the global land use literature. Petroleum and natural gas prices affect both the competitiveness of biofuels and the cost of nitrogen fertilizers. High prices put significant pressure on global land supply and greenhouse gas emissions from terrestrial systems, while low prices can moderate demands for cropland.

The goal of this letter is to assess and compare the effects of these core uncertainties on the optimal profile for global land use and land-based GHG emissions over the coming century. The model that we develop integrates distinct strands of agronomic, biophysical and economic literature into a single, intertemporally consistent, analytical framework, at global scale. Our analysis accounts for the value of land-based services in the production of food, first- and second-generation biofuels, timber, forest carbon and biodiversity. We find that long-term uncertainty in energy prices dominates the climate impacts and climate policy uncertainties emphasized in prior research on global land use.

Most studies of short-term particulate matter (PM) exposure use 24 h averages. However, other pollutants have stronger effects in shorter timeframes, which has influenced policy (e.g., ozone 8 h maximum). The selection of appropriate exposure timeframes is important for effective regulation. The US EPA identified health effects for sub-daily PM exposures as a critical research need. Unlike most areas, Seoul, Korea has hourly measurements of PM₁₀, although not PM_2.5. We investigated PM₁₀ and mortality (total, cardiovascular, respiratory) in Seoul (1999–2009) considering sub-daily exposures: 24 h, daytime (7 am–8 pm), morning (7–10 am), nighttime (8 pm–7 am), and 1 h daily maximum. We applied Poisson generalized linear modeling adjusting for temporal trends and meteorology. All PM₁₀ metrics were significantly associated with total mortality. Compared to other exposure timeframes, morning exposure had the most certain effect on total mortality (based on statistical significance). Increases of 10 μg m⁻³ in 24 h, daytime, morning, nighttime, and 1 h maximum PM₁₀ were associated with 0.15% (95% confidence interval 0.02–0.28%), 0.14% (0.01–0.27%), 0.10% (0.03–0.18%), 0.12% (0.03–0.22%), and 0.10% (0.00–0.21%) increases in total mortality, respectively. PM₁₀ was significantly associated with cardiovascular mortality for 24 h, morning, and nighttime exposures. We did not identify significant associations with respiratory mortality. The results support use of a 24 h averaging time as an appropriate metric for health studies and regulation, particularly for PM₁₀ and mortality.

Discussion and analysis on international climate policy often focuses on the rather abstract level of total national and regional greenhouse gas (GHG) emissions. At some point, however, emission reductions need to be translated to consumption level. In this article, we evaluate the implications of the strictest IPCC representative concentration pathway for key consumption categories (food, travel, shelter, goods, services). We use IPAT style identities to account for possible growth in global consumption levels and indicate the required change in GHG emission intensity for each category (i.e. GHG emission per calorie, person kilometer, square meter, kilogram, US dollar). The proposed concept provides guidance for product developers, consumers and policymakers. To reach the 2 °C climate target (2.1 tCO₂-eq. per capita in 2050), the GHG emission intensity of consumption has to be reduced by a factor of 5 in 2050. The climate targets on consumption level allow discussion of the feasibility of this climate target at product and consumption level. In most consumption categories products in line with this climate target are available. For animal food and air travel, reaching the GHG intensity targets with product modifications alone will be challenging and therefore structural changes in consumption patterns might be needed. The concept opens up possibilities for further research on potential solutions on the consumption and product level to global climate mitigation.

This letter provides a first-order estimate of conventional air pollutant emissions, and the monetary value of the associated environmental and health damages, from the extraction of unconventional shale gas in Pennsylvania. Region-wide estimated damages ranged from $7.2 to $32 million dollars for 2011. The emissions from Pennsylvania shale gas extraction represented only a few per cent of total statewide emissions, and the resulting statewide damages were less than those estimated for each of the state's largest coal-based power plants. On the other hand, in counties where activities are concentrated, NO_x emissions from all shale gas activities were 20–40 times higher than allowable for a single minor source, despite the fact that individual new gas industry facilities generally fall below the major source threshold for NO_x. Most emissions are related to ongoing activities, i.e., gas production and compression, which can be expected to persist beyond initial development and which are largely unrelated to the unconventional nature of the resource. Regulatory agencies and the shale gas industry, in developing regulations and best practices, should consider air emissions from these long-term activities, especially if development occurs in more populated areas of the state where per-ton emissions damages are significantly higher.

This letter reports on the design and pilot installation of GridShares, devices intended to alleviate brownouts caused by peak power use on isolated, village-scale mini-grids. A team consisting of the authors and partner organizations designed, built and field-tested GridShares in the village of Rukubji, Bhutan. The GridShare takes an innovative approach to reducing brownouts by using a low cost device that communicates the state of the grid to its users and regulates usage before severe brownouts occur. This demand-side solution encourages users to distribute the use of large appliances more evenly throughout the day, allowing power-limited systems to provide reliable, long-term renewable electricity to these communities. In the summer of 2011, GridShares were installed in every household and business connected to the Rukubji micro-hydro mini-grid, which serves approximately 90 households with a 40 kW nominal capacity micro-hydro system. The installation was accompanied by an extensive education program. Following the installation of the GridShares, the occurrence and average length of severe brownouts, which had been caused primarily by the use of electric cooking appliances during meal preparation, decreased by over 92%. Additionally, the majority of residents surveyed stated that now they are more certain that their rice will cook well and that they would recommend installing GridShares in other villages facing similar problems.

In what is arguably one of the most dramatic phenomena possibly associated with climate change or natural climate variability, the location of El Niño has shifted more to the central Pacific in recent decades. In this study, we use statistical analyses, numerical model experiments and case studies to show that the Central-Pacific El Niño enhances the drying effect, but weakens the wetting effect, typically produced by traditional Eastern-Pacific El Niño events on the US winter precipitation. As a result, the emerging Central-Pacific El Niño produces an overall drying effect on the US winter, particularly over the Ohio–Mississippi Valley, Pacific Northwest and Southeast. The enhanced drying effect is related to a more southward displacement of tropospheric jet streams that control the movements of winter storms. The results of this study imply that the emergence of the Central-Pacific El Niño in recent decades may be one factor contributing to the recent prevalence of extended droughts in the US.

High latitude drainage basins are experiencing higher average temperatures, earlier snowmelt onset in spring, and an increase in rain on snow (ROS) events in winter, trends that climate models project into the future. Snowmelt-dominated basins are most sensitive to winter temperature increases that influence the frequency of ROS events and the timing and duration of snowmelt, resulting in changes to spring runoff. Of specific interest in this study are early melt events that occur in late winter preceding melt onset in the spring. The study focuses on satellite determination and characterization of these early melt events using the Yukon River Basin (Canada/USA) as a test domain. The timing of these events was estimated using data from passive (Advanced Microwave Scanning Radiometer—EOS (AMSR-E)) and active (SeaWinds on Quick Scatterometer (QuikSCAT)) microwave remote sensors, employing detection algorithms for brightness temperature (AMSR-E) and radar backscatter (QuikSCAT). The satellite detected events were validated with ground station meteorological and hydrological data, and the spatial and temporal variability of the events across the entire river basin was characterized. Possible causative factors for the detected events, including ROS, fog, and positive air temperatures, were determined by comparing the timing of the events to parameters from SnowModel and National Centers for Environmental Prediction North American Regional Reanalysis (NARR) outputs, and weather station data. All melt events coincided with above freezing temperatures, while a limited number corresponded to ROS (determined from SnowModel and ground data) and a majority to fog occurrence (determined from NARR). The results underscore the significant influence that warm air intrusions have on melt in some areas and demonstrate the large temporal and spatial variability over years and regions. The study provides a method for melt detection and a baseline from which to assess future change.

Solar geoengineering is the deliberate reduction in the absorption of incoming solar radiation by the Earth's climate system with the aim of reducing impacts of anthropogenic climate change. Climate model simulations project a diversity of regional outcomes that vary with the amount of solar geoengineering deployed. It is unlikely that a single small actor could implement and sustain global-scale geoengineering that harms much of the world without intervention from harmed world powers. However, a sufficiently powerful international coalition might be able to deploy solar geoengineering. Here, we show that regional differences in climate outcomes create strategic incentives to form coalitions that are as small as possible, while still powerful enough to deploy solar geoengineering. The characteristics of coalitions to geoengineer climate are modeled using a 'global thermostat setting game' based on climate model results. Coalition members have incentives to exclude non-members that would prevent implementation of solar geoengineering at a level that is optimal for the existing coalition. These incentives differ markedly from those that dominate international politics of greenhouse-gas emissions reduction, where the central challenge is to compel free riders to participate.

Diffusion of microgeneration technologies, particularly rooftop photovoltaic (PV), represents a key option in reducing emissions in the residential sector. We use a uniquely rich dataset from the burgeoning residential PV market in Texas to study the nature of the consumer's decision-making process in the adoption of these technologies. In particular, focusing on the financial metrics and the information decision-makers use to base their decisions upon, we study how the leasing and buying models affect individual choices and, thereby, the adoption of capital-intensive energy technologies. Overall, our findings suggest that the leasing model more effectively addresses consumers' informational requirements and that, contrary to some other studies, buyers and lessees of PV do not necessarily differ significantly along socio-demographic variables. Instead, we find that the leasing model has opened up the residential PV market to a new, and potentially very large, consumer segment—those with a tight cash-flow situation.

The hourly rainfall at 21 ground stations in Taiwan is used to investigate changes in the frequency, intensity, and duration of rainfall, which can be divided into typhoon and non-typhoon rainfall, in the period of 1970–2010. As a whole, the frequency of rainfall shows a decreasing trend for lighter rain and an increasing trend for heavier rain. Also, the typhoon rainfall shows a significant increase for all intensities, while the non-typhoon rainfall exhibits a general trend of decreasing, particularly for lighter rain. In rainfall intensity, both typhoon and non-typhoon rainfall extremes become more intense, with an increased rate much greater than the Clausius–Clapeyron thermal scaling. Moreover, rainfall extremes associated with typhoons have tended to affect Taiwan rainfall for longer in recent decades. The more frequent, intense and long-lasting typhoon rainfall is mainly induced by the slower translation speed of the typhoons over the neighborhood of Taiwan, which could be associated with a weakening of steering flow in the western North Pacific and the northern South China Sea.

Climate models predict a large range of possible future temperatures for a particular scenario of future emissions of greenhouse gases and other anthropogenic forcings of climate. Given that further warming in coming decades could threaten increasing risks of climatic disruption, it is important to determine whether model projections are consistent with temperature changes already observed. This can be achieved by quantifying the extent to which increases in well mixed greenhouse gases and changes in other anthropogenic and natural forcings have already altered temperature patterns around the globe. Here, for the first time, we combine multiple climate models into a single synthesized estimate of future warming rates consistent with past temperature changes. We show that the observed evolution of near-surface temperatures appears to indicate lower ranges (5–95%) for warming (0.35–0.82 K and 0.45–0.93 K by the 2020s (2020–9) relative to 1986–2005 under the RCP4.5 and 8.5 scenarios respectively) than the equivalent ranges projected by the CMIP5 climate models (0.48–1.00 K and 0.51–1.16 K respectively). Our results indicate that for each RCP the upper end of the range of CMIP5 climate model projections is inconsistent with past warming.

Urbanization will place significant pressures on biodiversity across the world. However, there are large uncertainties in the amount and location of future urbanization, particularly urban land expansion. Here, we present a global analysis of urban extent circa 2000 and probabilistic forecasts of urban expansion for 2030 near protected areas and in biodiversity hotspots. We estimate that the amount of urban land within 50 km of all protected area boundaries will increase from 450 000 km² circa 2000 to 1440 000 ± 65 000 km² in 2030. Our analysis shows that protected areas around the world will experience significant increases in urban land within 50 km of their boundaries. China will experience the largest increase in urban land near protected areas with 304 000 ± 33 000 km² of new urban land to be developed within 50 km of protected area boundaries. The largest urban expansion in biodiversity hotspots, over 100 000 ± 25 000 km², is forecasted to occur in South America. Uncertainties in the forecasts of the amount and location of urban land expansion reflect uncertainties in their underlying drivers including urban population and economic growth. The forecasts point to the need to reconcile urban development and biodiversity conservation strategies.

Climate warming affects permafrost soil carbon pools in two opposing ways: enhanced vegetation growth leads to higher carbon inputs to the soil, whereas permafrost melting accelerates decomposition and hence carbon release. Here, we study the spatial and temporal dynamics of these two processes under scenarios of climate change and evaluate their influence on the carbon balance of the permafrost zone. We use the dynamic global vegetation model LPJmL, which simulates plant physiological and ecological processes and includes a newly developed discrete layer energy balance permafrost module and a vertical carbon distribution within the soil layer. The model is able to reproduce the interactions between vegetation and soil carbon dynamics as well as to simulate dynamic permafrost changes resulting from changes in the climate. We find that vegetation responds more rapidly to warming of the permafrost zone than soil carbon pools due to long time lags in permafrost thawing, and that the initial simulated net uptake of carbon may continue for some decades of warming. However, once the turning point is reached, if carbon release exceeds uptake, carbon is lost irreversibly from the system and cannot be compensated for by increasing vegetation carbon input. Our analysis highlights the importance of including dynamic vegetation and long-term responses into analyses of permafrost zone carbon budgets.

A climatology of low cloud surface precipitation occurrence and intensity from the new CloudSat 2C-RAIN-PROFILE algorithm is presented from June 2006 through December 2010 for the southeastern Pacific region of marine stratocumulus. Results show that over 70% of low cloud precipitation falls as drizzle. Application of an empirical evaporation model suggests that 50–80% of the precipitation evaporates before it reaches the surface. Segregation of the CloudSat ascending and descending overpasses shows that the majority of precipitation occurs at night. Examination of the seasonal cycle shows that the precipitation is most frequent during the austral winter and spring; however there is considerable regional variability. Conditional rain rates increase from east to west with a maximum occurring in the region influenced by the South Pacific Convergence Zone. Area average rain rates are highest in the region where precipitation rates are moderate, but most frequent. The area average surface rain rate for low cloud precipitation for this region is ∼0.22 mm d⁻¹, in good agreement with in situ estimates, and is greatly improved over earlier CloudSat precipitation products. These results provide a much-needed quantification of surface precipitation in a region that is currently underestimated in existing satellite-based precipitation climatologies.

Analysis of 20th century simulations of the High resolution Global Environment Model (HiGEM) and the Third Coupled Model Intercomparison Project (CMIP3) models shows that most have a cold sea-surface temperature (SST) bias in the northern Arabian Sea during boreal winter. The association between Arabian Sea SST and the South Asian monsoon has been widely studied in observations and models, with winter cold biases known to be detrimental to rainfall simulation during the subsequent monsoon in coupled general circulation models. However, the causes of these SST biases are not well understood. Indeed this is one of the first papers to address causes of the cold biases. The models show anomalously strong north-easterly winter monsoon winds and cold air temperatures in north-west India, Pakistan and beyond. This leads to the anomalous advection of cold, dry air over the Arabian Sea. The cold land region is also associated with an anomalously strong meridional surface temperature gradient during winter, contributing to the enhanced low-level convergence and excessive precipitation over the western equatorial Indian Ocean seen in many models.

Some fungal spore species have been found in laboratory studies to be very efficient ice nuclei. However, their potential impact on clouds and precipitation is not well known and needs to be investigated. Fungal spores as a new aerosol species were introduced into the global climate model (GCM) ECHAM5-HAM. The inclusion of fungal spores acting as ice nuclei in a GCM leads to only minor changes in cloud formation and precipitation on a global level; however, changes in the liquid water path and ice water path as well as stratiform precipitation can be observed in the boreal regions where tundra and forests act as sources of fungal spores. Although fungal spores contribute to heterogeneous freezing, their impact is reduced by their low numbers as compared to other heterogeneous ice nuclei.

We use single-forcing historical simulations with a coupled atmosphere–ocean global climate model to compare the effects of anthropogenic aerosols (AAs) and increasing long-lived greenhouse gases (LLGHGs) on simulated winter circulation in the Southern Hemisphere (SH). Our primary focus is on the subtropical jet, which is an important source of baroclinic instability, especially in the Australasian region, where the speed of the jet is largest. For the period 1950 to 2005, our simulations suggest that AAs weaken the jet, whereas increasing LLGHGs strengthen the jet. The different responses are explained in terms of thermal wind balance: increasing LLGHGs preferentially warm the tropical mid-troposphere and upper troposphere, whereas AAs have a similar effect of opposite sign. In the mid-troposphere, the warming (cooling) effect of LLGHGs (AAs) is maximal between 20S and 30S; this coincides with the descending branch of the Hadley circulation, which may advect temperature changes from the tropical upper troposphere to the subtropics of the SH. It follows that LLGHGs (AAs) increase (decrease) the mid-tropospheric temperature gradient between low latitudes and the SH mid-latitudes. The strongest effects are seen at longitudes where the southward branches of the Hadley cell in the upper troposphere are strongest, notably at those that correspond to Asia and the western Pacific warm pool.

In this letter, modern society's intimate bond to the convenience and reliability of delivered energy services results in a form of identification I call the Homo Energeticus. The Homo Energeticus relies upon a mature system of services for achieving an equivalency of status and prestige that is historically similar to the morality of a noble class. I describe the uniqueness of this identity by its imperative for acquiring experience through an invisibility of energy expenditures. In this way, the Homo Energeticus cultivates a highly individualized life whose ambience of perfection, while created personally, is only successful insofar as it conceals energy expenditures in labor and supply.

Pollen taxon in sediment samples can be identified by analyzing pollen morphology. Identification of related species based on pollen morphology is difficult and is limited primarily to genus or family. Because pollen grains of various ages are preserved at below 0 °C in glaciers and thus are more likely to remain intact or to suffer little DNA fragmentation, genetic information from such pollen grains should enable identification of plant taxa below the genus level. However, no published studies have attempted detailed identification using DNA sequences obtained from pollen found in glaciers. As a preliminary step, this study attempted to analyze the DNA of Pinus pollen grains extracted from surface snow collected from the Belukha glacier in the Altai Mountains of Russia in the summer of 2003. A 150-bp rpoB fragment from the chloroplast genome in each Pinus pollen grain was amplified by polymerase chain reaction, and DNA products were sequenced to identify them at the section level. A total of 105 pollen grains were used for the test, and sequences were obtained from eight grains. From the sequences obtained, the pollen grains were identified as belonging to the section Quinquefoliae. Trees of the extant species Pinus sibirica in the section Quinquefoliae are currently found surrounding the glacier. The consistency of results for this section suggests that the pollen in the glacier originated from the same Pinus trees as those found in the immediate surroundings.

Equivalence metrics used to quantify the relative climate impacts of different atmospheric forcers serve an essential function in policy and economic discussions about global climate change. The 100-year global warming potential (GWP-100), the most established greenhouse gas (GHG) equivalence metric, is used within the Kyoto Protocol, and in most emissions inventory, trading and offset mechanisms, to assign the mitigation value of non-carbon dioxide greenhouse gases relative to carbon dioxide. In recent literature the GWP-100 and alternative metrics have been used to compare various anthropogenic climate forcers with respect to a wide range of environmental and economic goals. Building on this work, we examine how 16 different static and time-varying CO₂-equivalence schemes might influence GHG mitigation across sectors and gases in a perfect and fluid global mitigation regime. This mitigation regime is guided by achieving a global mean radiative forcing (RF) of 5.7 Wm⁻² in 2100 from 1765 levels through a mitigation policy of prescribed emissions reductions in each decade. It was found that static metrics defined on 20- instead of 100-year time horizons favor mitigation strategies that maximize the abatement of short-lived gases (e.g. methane), on average resulting in an RF from methane in 2100 of 0.5 Wm⁻² instead of 1.1 Wm⁻² from 100-year metrics. Similarly, metrics that consider integrated rather than end-point climate impacts imply mitigation strategies that maximize mitigation of shorter-lived GHGs, resulting in higher abatement of agriculture and waste emissions. Comparing extreme scenarios, these mitigation shifts across gases and sectors result in a nearly 30% difference in the representation of methane in global cumulative emissions reductions. This shift across gases and sectors to mitigate shorter-lived GHGs, in lieu of longer-lived GHGs like carbon dioxide, has implications for the long-term warming commitment due to 21st century emissions.

Aerosols exhibit periodic or cyclic variations depending on natural and anthropogenic sources over a region, which can become modulated by synoptic meteorological parameters such as winds, rainfall and relative humidity, and long-range transport. Information on periodicity and phase in aerosol properties assumes significance in prediction as well as examining the radiative and climate effects of aerosols including their association with changes in cloud properties and rainfall. Periodicity in aerosol optical depth, which is a columnar measure of aerosol distribution, is determined using continuous wavelet transform over 35 locations (capitals of states and union territories) in India. Continuous wavelet transform is used in the study because continuous wavelet transform is better suited to the extraction of the periodic and local modulations present in various frequency ranges when compared to Fourier transform. Monthly mean aerosol optical depths (AODs) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite at 1° × 1° resolution from January 2001 to December 2012 are used. Annual and quasi-biennial oscillations (QBOs) in AOD are evident in addition to the weak semi-annual (5–6 months) and quasi-triennial oscillations (∼40 months). The semi-annual and annual oscillations are consistent with the seasonal and yearly cycle of variations in AODs. The QBO type periodicity in AOD is found to be non-stationary while the annual period is stationary. The 40 month periodicity indicates the presence of long term correlations in AOD. The observed periodicities in MODIS Terra AODs are also evident in the ground-based AOD measurements made over Kanpur in the Indo-Gangetic Plain. The phase of the periodicity in AOD is stable in the mid-frequency range, while local disturbances in the high-frequency range and long term changes in the atmospheric composition give rise to unstable phases in the low-frequency range. The presence of phase relations among different locations reveals that modulations in AOD over a location/region can influence aerosol characteristics over other locations/regions.

Because of climate change, much attention is drawn to the Amazon River basin, whose hydrology has already been strongly affected by extreme events during the past 20 years. Hydrological annual extreme variations (i.e. low/high flows) associated with precipitation (and evapotranspiration) changes are investigated over the Amazon River sub-basins using the land surface model ORCHIDEE and a multimodel approach. Climate change scenarios from up to eight AR4 Global Climate Models based on three emission scenarios were used to build future hydrological projections in the region, for two periods of the 21st century. For the middle of the century under the SRESA1B scenario, no change is found in high flow on the main stem of the Amazon River (Óbidos station), but a systematic discharge decrease is simulated during the recession period, leading to a 10% low-flow decrease. Contrasting discharge variations are pointed out depending on the location in the basin. In the western upper part of the basin, which undergoes an annual persistent increase in precipitation, high flow shows a 7% relative increase for the middle of the 21st century and the signal is enhanced for the end of the century (12%). By contrast, simulated precipitation decreases during the dry seasons over the southern, eastern and northern parts of the basin lead to significant low-flow decrease at several stations, especially in the Xingu River, where it reaches −50%, associated with a 9% reduction in the runoff coefficient. A 18% high-flow decrease is also found in this river. In the north, the low-flow decrease becomes higher toward the east: a 55% significant decrease in the eastern Branco River is associated with a 13% reduction in the runoff coefficient. The estimation of the streamflow elasticity to precipitation indicates that southern sub-basins (except for the mountainous Beni River), that have low runoff coefficients, will become more responsive to precipitation change (with a 5 to near 35% increase in elasticity) than the western sub-basins, experiencing high runoff coefficient and no change in streamflow elasticity to precipitation. These projections raise important issues for populations living near the rivers whose activity is regulated by the present annual cycle of waters. The question of their adaptability has already arisen.

The satellite record since 1979 shows downward trends in Arctic sea ice extent in all months, which are smallest in winter and largest in September. Previous studies have linked changes in winter atmospheric circulation, anomalously cold extremes and large snowfalls in mid-latitudes to rapid decline of Arctic sea ice in the preceding autumn. Using observational analyses, we show that the winter atmospheric circulation change and cold extremes are also associated with winter sea ice reduction through an apparently distinct mechanism from those related to autumn sea ice loss. Associated with winter sea ice reduction, a high-pressure anomaly prevails over the subarctic, which in part results from fewer cyclones owing to a weakened gradient in sea surface temperature and lower baroclinicity over sparse sea ice. The results suggest that the winter atmospheric circulation at high northern latitudes associated with Arctic sea ice loss, especially in the winter, favors the occurrence of cold winter extremes at middle latitudes of the northern continents.

Anthropogenic climate change and energy security concerns have created a demand for new ways of meeting society's demand for energy. The Earth's crust is being targeted in a variety of energy developments to either extract energy or facilitate the use of other energy resources by sequestering emitted carbon dioxide. Unconventional fossil fuel developments are already being pursued in great numbers, and large scale carbon capture and sequestration and geothermal energy projects have been proposed. In many cases, these developments compete for the same subsurface environments and they are not necessarily compatible with each other. Policy to regulate the interplay between these developments is poorly developed. Here, the subsurface footprints necessary to produce a unit of energy from different developments are estimated to assist with subsurface planning. The compatibility and order of development is also examined to aid policy development. Estimated subsurface energy footprints indicate that carbon capture and sequestration and geothermal energy developments are better choices than unconventional gas to supply clean energy.

Meeting a greenhouse gas (GHG) reduction target of 80% below 1990 levels in the year 2050 requires detailed long-term planning due to complexity, inertia, and path dependency in the energy system. A detailed investigation of supply and demand alternatives is conducted to assess requirements for future California energy systems that can meet the 2050 GHG target. Two components are developed here that build novel analytic capacity and extend previous studies: (1) detailed bottom-up projections of energy demand across the building, industry and transportation sectors; and (2) a high-resolution variable renewable resource capacity planning model (SWITCH) that minimizes the cost of electricity while meeting GHG policy goals in the 2050 timeframe. Multiple pathways exist to a low-GHG future, all involving increased efficiency, electrification, and a dramatic shift from fossil fuels to low-GHG energy. The electricity system is found to have a diverse, cost-effective set of options that meet aggressive GHG reduction targets. This conclusion holds even with increased demand from transportation and heating, but the optimal levels of wind and solar deployment depend on the temporal characteristics of the resulting load profile. Long-term policy support is found to be a key missing element for the successful attainment of the 2050 GHG target in California.

To examine whether stream nitrogen concentrations in forested reference catchments have changed over time and if patterns were consistent across the USA, we synthesized up to 44 yr of data collected from 22 catchments at seven USDA Forest Service Experimental Forests. Trends in stream nitrogen presented high spatial variability both among catchments at a site and among sites across the USA. We found both increasing and decreasing trends in monthly flow-weighted stream nitrate and ammonium concentrations. At a subset of the catchments, we found that the length and period of analysis influenced whether trends were positive, negative or non-significant. Trends also differed among neighboring catchments within several Experimental Forests, suggesting the importance of catchment-specific factors in determining nutrient exports. Over the longest time periods, trends were more consistent among catchments within sites, although there are fewer long-term records for analysis. These findings highlight the critical value of long-term, uninterrupted stream chemistry monitoring at a network of sites across the USA to elucidate patterns of change in nutrient concentrations at minimally disturbed forested sites.

Sub-Saharan West Africa is a vulnerable region where a better quantification and understanding of the impact of climate change on crop yields is urgently needed. Here, we have applied the process-based crop model SARRA-H calibrated and validated over multi-year field trials and surveys at eight contrasting sites in terms of climate and agricultural practices in Senegal, Mali, Burkina Faso and Niger. The model gives a reasonable correlation with observed yields of sorghum and millet under a range of cultivars and traditional crop management practices. We applied the model to more than 7000 simulations of yields of sorghum and millet for 35 stations across West Africa and under very different future climate conditions. We took into account 35 possible climate scenarios by combining precipitation anomalies from −20% to 20% and temperature anomalies from +0 to +6 °C.

We found that most of the 35 scenarios (31/35) showed a negative impact on yields, up to −41% for +6 °C/ − 20% rainfall. Moreover, the potential future climate impacts on yields are very different from those recorded in the recent past. This is because of the increasingly adverse role of higher temperatures in reducing crop yields, irrespective of rainfall changes. When warming exceeds +2 °C, negative impacts caused by temperature rise cannot be counteracted by any rainfall change. The probability of a yield reduction appears to be greater in the Sudanian region (southern Senegal, Mali, Burkina Faso, northern Togo and Benin), because of an exacerbated sensitivity to temperature changes compared to the Sahelian region (Niger, Mali, northern parts of Senegal and Burkina Faso), where crop yields are more sensitive to rainfall change. Finally, our simulations show that the photoperiod-sensitive traditional cultivars of millet and sorghum used by local farmers for centuries seem more resilient to future climate conditions than modern cultivars bred for their high yield potential (−28% versus −40% for the +4 °C/ − 20% scenario). Photoperiod-sensitive cultivars counteract the effect of temperature increase on shortening cultivar duration and thus would likely avoid the need to shift to cultivars with a greater thermal time requirement. However, given the large difference in mean yields of the modern versus traditional varieties, the modern varieties would still yield more under optimal fertility conditions in a warmer world, even if they are more affected by climate change.

We sought to understand how knowledge about resilience is produced. We examined empirical research into resilience from the social and natural sciences, randomly selected a sample of these studies and analysed their methods using common criteria to enable comparison. We found that studies of resilience from social scientists largely focus on the response of individuals to human-induced change events, while those from natural scientists largely focus on the response of ecological communities and populations to both environmental and human-induced change events. Most studies were of change over short time periods and focused on small spatial scales. Social science studies were dominated by one-off surveys, whereas natural science studies used a diversity of study designs to draw inferences about cause-and-effect. Whilst these differences typically reflect epistemological and methodological traditions, they also imply quite different understandings of resilience. We suggest that there are significant methodological barriers to producing empirical evidence about interactions between complex social and ecological systems.

In 2010, nuclear power accounted for 27% of electricity production in Japan. The March 2011 disaster at the Fukushima Daiichi power station resulted in the closure of all of Japan's nuclear power plants and it remains an open question as to how many will reopen. Even before the loss of nuclear capacity, there were efforts in Japan to foster the use of renewable energy, including large scale solar power. Nuclear power plants in Japan provided more than just base-load by storing energy in large scale pumped hydroelectric storage systems, which was then released to provide some peaking capacity. If this storage were instead coupled to current generation rooftop solar systems in Tokyo, the combined system could help to meet peak requirements while at the same time providing ∼26.5% of the electricity Tokyo used to get from nuclear output, and do so 91% of the time. Data from a study of rooftop space and a 34 yr data set of average daily irradiance in the Tokyo metropolitan area were used. Using pumped hydroelectric storage with 5.6 times this rooftop area could completely provide for TEPCO's nuclear capacity.

Recently compiled observational data suggest a substantial decline in the global median chlorophyll a concentration over the 20th century, a trend that appears to be linked to ocean warming. Several modelling studies have considered changes in the ocean's physical structure as a possible cause, while experimental work supports a biological mechanism, namely an observed increase in zooplankton grazing rate that outpaces phytoplankton production at higher temperatures. Here, we present transient simulations derived from a coupled ocean general circulation and carbon cycle model forced by atmospheric fields under unabated anthropogenic global warming (IPCC SRES A1FI scenario). The simulations account for both physical and biological mechanisms, and can reproduce about one quarter of the observed chlorophyll a decline during the 20th century, when using realistically parameterized temperature sensitivity of zooplankton metabolism (Q₁₀ between 2 and 4) and phytoplankton growth (Q₁₀ ∼ 1.9). Therefore, we have employed and re-calibrated the standard ecosystem model which assumes a lower temperature sensitivity of zooplankton grazing (Q₁₀ = 1.1049) by re-scaling phytoplankton growth rates and zooplankton grazing rates. Our model projects a global chlorophyll a decline of >50% by the end of the 21st century. While phytoplankton abundance and chlorophyll a experience pronounced negative effects, primary production and zooplankton concentrations are less sensitive to ocean warming. Although changes in physical structure play an important role, much of the simulated change in chlorophyll a and productivity is related to the uneven temperature sensitivity of the marine ecosystem.

Realizing the environmental benefits of solar photovoltaics (PV) will require reducing costs associated with perception, informational gaps and technological uncertainties. To identify opportunities to decrease costs associated with residential PV adoption, in this letter we use multivariate regression models to analyze a unique, household-level dataset of PV adopters in Texas (USA) to systematically quantify the effect of different information channels on aspiring PV adopters' decision-making. We find that the length of the decision period depends on the business model, such as whether the system was bought or leased, and on special opportunities to learn, such as the influence of other PV owners in the neighborhood. This influence accrues passively through merely witnessing PV systems in the neighborhood, increasing confidence and motivation, as well as actively through peer-to-peer communications. Using these insights we propose a new framework to provide public information on PV that could drastically reduce barriers to PV adoption, thereby accelerating its market penetration and environmental benefits. This framework could also serve as a model for other distributed generation technologies.

The environmental benefits of plug-in electric vehicles (PEVs) increase if the vehicles are powered by electricity from 'green' sources such as solar, wind or small-scale hydroelectricity. Here, we explore the potential to build a market that pairs consumer purchases of PEVs with purchases of green electricity. We implement a web-based survey with three US samples defined by vehicle purchases: conventional new vehicle buyers (n = 1064), hybrid vehicle buyers (n = 364) and PEV buyers (n = 74). Respondents state their interest in a PEV as their next vehicle, in purchasing green electricity in one of three ways, i.e., monthly subscription, two-year lease or solar panel purchase, and in combining the two products. Although we find that a link between PEVs and green electricity is not presently strong in the consciousness of most consumers, the combination is attractive to some consumers when presented. Across all three respondent segments, pairing a PEV with a green electricity program increased interest in PEVs—with a 23% demand increase among buyers of conventional vehicles. Overall, about one-third of respondents presently value the combination of a PEV with green electricity; the proportion is much higher among previous HEV and PEV buyers. Respondents' reported motives for interest in both products and their combination include financial savings (particularly among conventional buyers), concerns about air pollution and the environment, and interest in new technology (particularly among PEV buyers). The results provide guidance regarding policy and marketing strategies to advance PEVs and green electricity demand.

In our globalizing world, the geographical locations of food production and consumption are becoming increasingly disconnected, which increases reliance on external resources and their trade. We quantified to what extent water and land constraints limit countries' capacities, at present and by 2050, to produce on their own territory the crop products that they currently import from other countries. Scenarios of increased crop productivity and water use, cropland expansion (excluding areas prioritized for other uses) and population change are accounted for.

We found that currently 16% of the world population use the opportunities of international trade to cover their demand for agricultural products. Population change may strongly increase the number of people depending on ex situ land and water resources up to about 5.2 billion (51% of world population) in the SRES A2r scenario. International trade will thus have to intensify if population growth is not accompanied by dietary change towards less resource-intensive products, by cropland expansion, or by productivity improvements, mainly in Africa and the Middle East. Up to 1.3 billion people may be at risk of food insecurity in 2050 in present low-income economies (mainly in Africa), if their economic development does not allow them to afford productivity increases, cropland expansion and/or imports from other countries.

Previous research has indicated that the response of globally average temperature is approximately proportional to cumulative CO₂ emissions, yet evidence of the robustness of this relationship over a range of CO₂ emission pathways is lacking. To address this, we evaluate the dependency of climate and carbon cycle change on CO₂ emission pathways using a fully coupled climate–carbon cycle model. We design five idealized pathways (including an overshoot scenario for cumulative emissions), each of which levels off to final cumulative emissions of 2000 GtC. The cumulative emissions of the overshoot scenario reach 4000 GtC temporarily, subsequently reducing to 2000 GtC as a result of continuous negative emissions. Although we find that responses of climatic variables and the carbon cycle are largely independent of emission pathways, a much weakened Atlantic meridional overturning circulation (AMOC) is projected in the overshoot scenario despite cessation of emissions. This weakened AMOC is enhanced by rapid warming in the Arctic region due to considerable temporary elevation of atmospheric CO₂ concentration and induces the decline of surface air temperature and decrease of precipitation over the northern Atlantic and Europe region. Moreover, the weakened AMOC reduces CO₂ uptake by the Atlantic and Arctic oceans. However, the weakened AMOC contributes little to the global carbon cycle. In conclusion, although climate variations have been found to be dependent on emission pathways, the global carbon cycle is relatively independent of these emission pathways, at least superficially.

Plant-emitted hydrocarbons mediate several key interactions between plants and insects. They enhance the ability of pollinators and herbivores to locate suitable host plants, and parasitoids to locate herbivores. While plant volatiles provide strong chemical signals, these signals are potentially degraded by exposure to pollutants such as ozone, which has increased in the troposphere and is projected to continue to increase over the coming decades. Despite the potential broad ecological significance of reduced plant signaling effectiveness, few studies have examined behavioral responses of insects to their hosts in polluted environments. Here, we use a laboratory study to test the effect of ozone concentration gradients on the ability of the striped cucumber beetle (Acalymma vittatum) to locate flowers of its host plant, Cucurbita foetidissima. Y-tube experiments showed that ozone mixing ratios below 80 parts per billion (ppb) resulted in beetles moving toward their host plant, but levels above 80 ppb resulted in beetles moving randomly with respect to host location. There was no evidence that beetles avoided polluted air directly. The results show that ozone pollution has great potential to perniciously alter key interactions between plants and animals.

Environmental impact studies of forest bioenergy systems usually account for CO₂ emissions and removals and identify the so-called carbon debt of bioenergy through comparison with a reference system. This approach is based on a simple sum of fluxes and does not consider any direct physical impact or climate system response. Other recent applications go one step further and elaborate impulse response functions (IRFs) and subsequent metrics for biogenic CO₂ emissions that are compatible with the life-cycle assessment (LCA) methodology. However, a thorough discussion about the role of the different metrics in the interpretation of the climate impacts of forest bioenergy systems is still missing. In this work, we assess a single LCA dataset of selected bioenergy systems using different emission metrics based on cumulative CO₂ emissions, radiative forcing and global surface temperature. We consider both absolute and normalized metrics for single pulses and sustained emissions. The key challenges are the choice of end point (emissions, concentration, radiative forcing, change in temperature, etc), the type of measure (instantaneous or time-integrated) and the treatment of time. Bioenergy systems usually perform better than fossil counterparts if assessed with instantaneous metrics, including global surface temperature change, and in some cases can give a net global cooling effect in the short term. The analysis of sustained, or continuous emissions, also shows that impacts from bioenergy systems are generally reversible, while those from fossil fuels are permanent.

As shown in this study, the metric choice can have a large influence on the results. The dominant role traditionally assigned to cumulative metrics in LCA studies and climate impact accounting schemes should therefore be reconsidered, because such metrics can fail to capture important time dependences unique to the biomass system under analysis (to which instantaneous metrics are well suited).

Energy demand for climate control was analyzed for Miami (the warmest large metropolitan area in the US) and Minneapolis (the coldest large metropolitan area). The following relevant parameters were included in the analysis: (1) climatological deviations from the desired indoor temperature as expressed in heating and cooling degree days, (2) efficiencies of heating and cooling appliances, and (3) efficiencies of power-generating plants. The results indicate that climate control in Minneapolis is about 3.5 times as energy demanding as in Miami. This finding suggests that, in the US, living in cold climates is more energy demanding than living in hot climates.

We evaluate the ability of process based models to reproduce observed global mean sea-level change. When the models are forced by changes in natural and anthropogenic radiative forcing of the climate system and anthropogenic changes in land-water storage, the average of the modelled sea-level change for the periods 1900–2010, 1961–2010 and 1990–2010 is about 80%, 85% and 90% of the observed rise. The modelled rate of rise is over 1 mm yr⁻¹ prior to 1950, decreases to less than 0.5 mm yr⁻¹ in the 1960s, and increases to 3 mm yr⁻¹ by 2000. When observed regional climate changes are used to drive a glacier model and an allowance is included for an ongoing adjustment of the ice sheets, the modelled sea-level rise is about 2 mm yr⁻¹ prior to 1950, similar to the observations. The model results encompass the observed rise and the model average is within 20% of the observations, about 10% when the observed ice sheet contributions since 1993 are added, increasing confidence in future projections for the 21st century. The increased rate of rise since 1990 is not part of a natural cycle but a direct response to increased radiative forcing (both anthropogenic and natural), which will continue to grow with ongoing greenhouse gas emissions.

The temperature sensitivity of the snowfall season (start, end, duration) over northern Eurasia (the former USSR) is analyzed from synoptic records of 547 stations from 1966 to 2000. The results find significant correlations between temperature and snowfall season at approximately 56% of stations (61% for the starting date and 56% for the ending date) with a mean snowfall season duration temperature sensitivity of −6.2 days °C⁻¹ split over the start (2.8 days) and end periods (−3.4 days). Temperature sensitivity was observed to increase with stations' mean seasonal air temperature, with the strongest relationships at locations of around 6 °C temperature. This implies that increasing air temperature in fall and spring will delay the onset and hasten the end of snowfall events, and reduces the snowfall season length by 6.2 days for each degree of increase. This study also clarifies that the increasing trend in snowfall season length during 1936/37–1994 over northern European Russia and central Siberia revealed in an earlier study is unlikely to be associated with warming in spring and fall seasons.

In this study, we investigate the change in multi-day precipitation extremes in late winter in Europe using observations and climate models. The objectives of the analysis are to determine whether climate models can accurately reproduce observed trends and, if not, to find the causes of the difference in trends.

Similarly to an earlier finding for mean precipitation trends, and despite a lower signal to noise ratio, climate models fail to reproduce the increase in extremes in much of northern Europe: the model simulations do not cover the observed trend in large parts of this area. A dipole in the sea-level pressure trend over continental Europe causes positive trends in extremes in northern Europe and negative trends in the Iberian Peninsula. Climate models have a much weaker pressure trend dipole and as a result a much weaker (extreme) precipitation response.

The inability of climate models to correctly simulate observed changes in atmospheric circulation is also primarily responsible for the underestimation of trends in the Rhine basin. When it has been adjusted for the circulation trend mismatch, the observed trend is well within the spread of the climate model simulations. Therefore, it is important that we improve our understanding of circulation changes, in particular related to the cause of the apparent mismatch between observed and modeled circulation trends over the past century.

Although crop yield generally responds positively to increased atmospheric CO₂ concentration ([CO₂]), the response depends on the species and environmental conditions. Thus, even though global [CO₂] is increasing roughly uniformly, regional yield response to increased [CO₂] will vary due to differences in climate and the mixture of crops. Although [CO₂] effects have been shown to be important for economic and food security impacts of climate change, regional [CO₂] effects are not often considered, and the few studies that have considered them disagree on regional patterns. Here regional yield effects of elevated [CO₂] are examined by combining experimentally determined CO₂ fertilization effect estimates with grid-level data on climate, crop areas, and yields. Production stimulation varies between regions, mostly driven by differences in climate but also by the mixture of crops. The variability in yield due to the variable response to elevated [CO₂] is about 50–70% of the variability in yield due to the variable response to climate. There is, however, little agreement between studies regarding which regions benefit most from elevated [CO₂]. This is likely because of interactions of CO₂ with temperature, species, water status, and nitrogen availability, but no models currently account for all these interactions. These results suggest that regional differences in CO₂ effects are of similar importance as regional differences in climate effects and should be included in models.

A necessary condition for a good probabilistic forecast is that the forecast system is shown to be reliable: forecast probabilities should equal observed probabilities verified over a large number of cases. As climate change trends are now emerging from the natural variability, we can apply this concept to climate predictions and compute the reliability of simulated local and regional temperature and precipitation trends (1950–2011) in a recent multi-model ensemble of climate model simulations prepared for the Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5). With only a single verification time, the verification is over the spatial dimension. The local temperature trends appear to be reliable. However, when the global mean climate response is factored out, the ensemble is overconfident: the observed trend is outside the range of modelled trends in many more regions than would be expected by the model estimate of natural variability and model spread. Precipitation trends are overconfident for all trend definitions. This implies that for near-term local climate forecasts the CMIP5 ensemble cannot simply be used as a reliable probabilistic forecast.

Water use by the electricity sector represents a significant portion of the United States water budget (41% of total freshwater withdrawals; 3% consumed). Sustainable management of water resources necessitates an accurate accounting of all water demands, including water use for generation of electricity. Since 1985, the Department of Energy (DOE) Energy Information Administration (EIA) has collected self-reported data on water consumption and withdrawals from individual power generators. These data represent the only annual collection of water consumption and withdrawals by the electricity sector. Here, we compile publically available information into a comprehensive database and then calculate water withdrawals and consumptive use for power plants in the US. In effect, we evaluate the quality of water use data reported by EIA for the year 2008. Significant differences between reported and calculated water data are evident, yet no consistent reason for the discrepancies emerges.

Large-scale wind farms, covering a significant portion of the land and ocean surface, may affect the transport of momentum, heat, mass and moisture between the atmosphere and the land locally and globally. To understand the wind-farm–atmosphere interaction, we conducted wind-tunnel experiments to study the surface scalar (heat) flux using model wind farms, consisting of more than ten rows of wind turbines—having typical streamwise and spanwise spacings of five and four rotor diameters—in a neutral boundary layer with a heated surface. The spatial distribution of the surface heat flux was mapped with an array of surface heat flux sensors within the quasi-developed regime of the wind-farm flow. Although the overall surface heat flux change produced by the wind farms was found to be small, with a net reduction of 4% for a staggered wind farm and nearly zero change for an aligned wind farm, the highly heterogeneous spatial distribution of the surface heat flux, dependent on the wind-farm layout, was significant. The difference between the minimum and maximum surface heat fluxes could be up to 12% and 7% in aligned and staggered wind farms, respectively. This finding is important for planning intensive agriculture practice and optimizing farm land use strategy regarding wind energy project development. The well-controlled wind-tunnel experiments presented in this study also provide a first comprehensive dataset on turbulent flow and scalar transport in wind farms, which can be further used to develop and validate new parameterizations of surface scalar fluxes in numerical models.

Increasing demand for crop-based biofuels, in addition to other human drivers of land use, induces direct and indirect land use changes (LUC). Our system dynamics tool is intended to complement existing LUC modeling approaches and to improve the understanding of global LUC drivers and dynamics by allowing examination of global LUC under diverse scenarios and varying model assumptions. We report on a small subset of such analyses. This model provides insights into the drivers and dynamic interactions of LUC (e.g., dietary choices and biofuel policy) and is not intended to assert improvement in numerical results relative to other works.

Demand for food commodities are mostly met in high food and high crop-based biofuel demand scenarios, but cropland must expand substantially. Meeting roughly 25% of global transportation fuel demand by 2050 with biofuels requires >2 times the land used to meet food demands under a presumed 40% increase in per capita food demand. In comparison, the high food demand scenario requires greater pastureland for meat production, leading to larger overall expansion into forest and grassland. Our results indicate that, in all scenarios, there is a potential for supply shortfalls, and associated upward pressure on prices, of food commodities requiring higher land use intensity (e.g., beef) which biofuels could exacerbate.

The US electricity sector is currently responsible for more than 40% of both energy-related carbon dioxide emissions and total freshwater withdrawals for power plant cooling (EIA 2012a Annual Energy Outlook 2012 (Washington, DC: US Department of Energy), Kenny et al 2009 Estimated Use of Water in the United States 2005 (US Geological Survey Circular vol 1344) (Reston, VA: US Geological Survey)). Changes in the future electricity generation mix in the United States will have important implications for water use, particularly given the changing water availability arising from competing demands and climate change and variability. However, most models that are used to make long-term projections of the electricity sector do not have sufficient regional detail for analyzing water-related impacts and informing important electricity- and water-related decisions. This paper uses the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) to model a range of low-carbon electricity futures nationally that are used to calculate changes in national water use (a sample result, on water consumption, is included here). The model also produces detailed sub-regional electricity results through 2050 that can be linked with basin-level water modeling. The results will allow for sufficient geographic resolution and detail to be relevant from a water management perspective.

The potential supply of bioenergy from farm-grown biomass is uncertain due to several poorly understood or volatile factors, including land availability, yield variability, and energy prices. Although biomass production for liquid fuel has received more attention, here we present a case study of biomass production for renewable heat and power in the state of Wisconsin (US), where heating constitutes at least 30% of total energy demand. Using three bioenergy systems (50 kW, 8.8 MW and 50 MW) and Wisconsin farm-level data, we determined the net farm income effect of producing switchgrass (Panicum virgatum) as a feedstock, either for on-farm use (50 kW system) or for sale to an off-farm energy system operator (8.8 and 50 MW systems). In southern counties, where switchgrass yields approach 10 Mg ha⁻¹ yr⁻¹, the main determinants of economic feasibility were the available land area per farm, the ability to utilize bioheat, and opportunity cost assumptions. Switchgrass yield temporal variability was less important. For the state median farm size and switchgrass yield, at least 25% (50 kW system) or 50% (8.8 MW system) bioheat utilization was required to economically offset propane or natural gas heat, respectively, and purchased electricity. Offsetting electricity only (50 MW system) did not generate enough revenue to meet switchgrass production expenses. Although the opportunity cost of small-scale (50 kW) on-farm bioenergy generation was higher, it also held greater opportunity for increasing farm net income, especially by replacing propane-based heat.

Environment migration research has sought to provide an account of how environmental risks and resources affect migration and mobility. Part of that effort has focused on the role of the environment in providing secure livelihoods through provisioning ecosystem services. However, many of the models of environment migration linkages fail to acknowledge the importance of social and psychological factors in the decision to migrate. Here, we seek to provide a more comprehensive model of migration decision-making under environmental change by investigating the attachment people form to place, and the role of the environment in creating that attachment. We hypothesize that environmental factors enter the migration decision-making process through their contribution to place utility, defined as a function of both affective and instrumental bonds to location, and that ecosystem services, the aspects of ecosystems that create wellbeing, contribute to both components of place utility. We test these ideas in four rural highland settlements in Peru sampled along an altitudinal gradient. We find that non-economic ecosystem services are important in creating place attachment and that ecological place attachment exists independently of use of provisioning ecosystem services. Individuals' attitudes to ecosystem services vary with the type of ecosystem services available at a location and the degree of rurality. While social and economic factors are the dominant drivers of migration in these locations, a loss of non-provisioning ecosystem services leads to a decrease in place utility and commitment to place, determining factors in the decision to migrate. The findings suggest that policy interventions encouraging migration as an adaptation to environmental change will have limited success if they only focus on provisioning services. A much wider set of individuals will experience a decrease in place utility, and migration will be unable to alleviate that decrease since the factors that create it are specific to place.

The production of biofuel from cellulosic residues can have both environmental and financial benefits. A particular benefit is that it can alleviate competition for land conventionally used for food and feed production. In this research, we investigate greenhouse gas (GHG) emissions associated with the production of ethanol, biomethane, limonene and digestate from citrus waste, a byproduct of the citrus processing industry. The study represents the first life cycle-based evaluations of citrus waste biorefineries. Two biorefinery configurations are studied—a large biorefinery that converts citrus waste into ethanol, biomethane, limonene and digestate, and a small biorefinery that converts citrus waste into biomethane, limonene and digestate. Ethanol is assumed to be used as E85, displacing gasoline as a light-duty vehicle fuel; biomethane displaces natural gas for electricity generation, limonene displaces acetone in solvents, and digestate from the anaerobic digestion process displaces synthetic fertilizer. System expansion and two allocation methods (energy, market value) are considered to determine emissions of co-products. Considerable GHG reductions would be achieved by producing and utilizing the citrus waste-based products in place of the petroleum-based or other non-renewable products. For the large biorefinery, ethanol used as E85 in light-duty vehicles results in a 134% reduction in GHG emissions compared to gasoline-fueled vehicles when applying a system expansion approach. For the small biorefinery, when electricity is generated from biomethane rather than natural gas, GHG emissions are reduced by 77% when applying system expansion. The life cycle GHG emissions vary substantially depending upon biomethane leakage rate, feedstock GHG emissions and the method to determine emissions assigned to co-products. Among the process design parameters, the biomethane leakage rate is critical, and the ethanol produced in the large biorefinery would not meet EISA's requirements for cellulosic biofuel if the leakage rate is higher than 9.7%. For the small biorefinery, there are no GHG emission benefits in the production of biomethane if the leakage rate is higher than 11.5%. Compared to system expansion, the use of energy and market value allocation methods generally results in higher estimates of GHG emissions for the primary biorefinery products (i.e., smaller reductions in emissions compared to reference systems).

The current environmental crisis permeates the discourse and concerns of people all over the world. Consideration of diverse environmental ethics showing the alternative ways in which people conceptualize and relate to nature and natural resources are critical for bringing about more sustainable human behaviors. After a brief review of Western historical notions of nature, this work explores the ecogony, or causal reasons, that trigger the behavior of the Jotï, an Amerindian people of the Venezuelan Amazon, with other entities and the forest that they inhabit. The analysis presented synthesizes 15 years of transdisciplinary ethno-ecological research comprising quantitative and qualitative methods (collection of herbarium voucher specimens, floristic inventories in forest plots, structured interviews focused on plot vegetation, semi-structured interviews of life-histories, participant observation, time allocation studies, food resource accounting, focal person following observations, garden crop inventories and censuses, mapping of wild resource harvest locations, among others). Jotï pragmatic and ideological tenets generate a distinctive environmental ethics based on ecogonic nodes. Notions of interdependence, humanity and person are articulated on a daily basis through several dynamics: (1) hyper-awareness of all living things' dependence on each other and other elements of the biophysical environment at macroscales and microscales, (2) the construction of human spiritual, conscious, physical and agentive constituents from a variety of diverse botanical and zoological species and mineral components of their homeland, and (3) an understanding of the aggregate surroundings, including a significant portion of the biotic and abiotic components, as potential subjects with awareness, creativity and moral stances. This condition of interdependence confers rights and duties on all the parts. Jotï horizontal communications with and among life-forms sustain their condition as committed actors in the configuration of the forests that they inhabit.

Greenhouse gas (GHG) emissions from agriculture, including crop and livestock production, forestry and associated land use changes, are responsible for a significant fraction of anthropogenic emissions, up to 30% according to the Intergovernmental Panel on Climate Change (IPCC). Yet while emissions from fossil fuels are updated yearly and by multiple sources—including national-level statistics from the International Energy Agency (IEA)—no comparable efforts for reporting global statistics for agriculture, forestry and other land use (AFOLU) emissions exist: the latest complete assessment was the 2007 IPCC report, based on 2005 emission data. This gap is critical for several reasons. First, potentially large climate funding could be linked in coming decades to more precise estimates of emissions and mitigation potentials. For many developing countries, and especially the least developed ones, this requires improved assessments of AFOLU emissions. Second, growth in global emissions from fossil fuels has outpaced that from AFOLU during every decade of the period 1961–2010, so the relative contribution of the latter to total climate forcing has diminished over time, with a need for regular updates. We present results from a new GHG database developed at FAO, providing a complete and coherent time series of emission statistics over a reference period 1961–2010, at country level, based on FAOSTAT activity data and IPCC Tier 1 methodology. We discuss results at global and regional level, focusing on trends in the agriculture sector and net deforestation. Our results complement those available from the IPCC, extending trend analysis to a longer historical period and, critically, beyond 2005 to more recent years. In particular, from 2000 to 2010, we find that agricultural emissions increased by 1.1% annually, reaching 4.6 Gt CO₂ yr⁻¹ in 2010 (up to 5.4–5.8 Gt CO₂ yr⁻¹ with emissions from biomass burning and organic soils included). Over the same decade 2000–2010, the ratio of agriculture to fossil fuel emissions has decreased, from 17.2% to 13.7%, and the decrease is even greater for the ratio of net deforestation to fossil fuel emissions: from 19.1% to 10.1%. In fact, in the year 2000, emissions from agriculture have been consistently larger—about 1.2 Gt CO₂ yr⁻¹ in 2010—than those from net deforestation.

The conversion of wetlands to agriculture through drainage and flooding, and the burning of wetland areas for agriculture have important implications for greenhouse gas (GHG) production and changing carbon stocks. However, the estimation of net GHG changes from mitigation practices in agricultural wetlands is complex compared to dryland crops. Agricultural wetlands have more complicated carbon and nitrogen cycles with both above- and below-ground processes and export of carbon via vertical and horizontal movement of water through the wetland.

This letter reviews current research methodologies in estimating greenhouse gas production and provides guidance on the provision of robust estimates of carbon sequestration and greenhouse gas emissions in agricultural wetlands through the use of low cost reliable and sustainable measurement, modelling and remote sensing applications. The guidance is highly applicable to, and aimed at, wetlands such as those in the tropics and sub-tropics, where complex research infrastructure may not exist, or agricultural wetlands located in remote regions, where frequent visits by monitoring scientists prove difficult.

In conclusion, the proposed measurement-modelling approach provides guidance on an affordable solution for mitigation and for investigating the consequences of wetland agricultural practice on GHG production, ecological resilience and possible changes to agricultural yields, variety choice and farming practice.

Current methods for assessing soil organic carbon (SOC) stocks are generally not well suited for understanding variations in SOC stocks in landscapes. This is due to the tedious and time-consuming nature of the sampling methods most commonly used to collect bulk density cores, which limits repeatability across large areas, particularly where information is needed on the spatial dynamics of SOC stocks at scales relevant to management and for spatially explicit targeting of climate change mitigation options. In the current study, approaches were explored for (i) field-based estimates of SOC stocks and (ii) mapping of SOC stocks at moderate to high resolution on the basis of data from four widely contrasting ecosystems in East Africa. Estimated SOC stocks for 0–30 cm depth varied both within and between sites, with site averages ranging from 2 to 8 kg m⁻². The differences in SOC stocks were determined in part by rainfall, but more importantly by sand content. Results also indicate that managing soil erosion is a key strategy for reducing SOC loss and hence in mitigation of climate change in these landscapes. Further, maps were developed on the basis of satellite image reflectance data with multiple R-squared values of 0.65 for the independent validation data set, showing variations in SOC stocks across these landscapes. These maps allow for spatially explicit targeting of potential climate change mitigation efforts through soil carbon sequestration, which is one option for climate change mitigation and adaptation. Further, the maps can be used to monitor the impacts of such mitigation efforts over time.

Successful adaptation of agriculture to ongoing climate changes would help to maintain productivity growth and thereby reduce pressure to bring new lands into agriculture. In this paper we investigate the potential co-benefits of adaptation in terms of the avoided emissions from land use change. A model of global agricultural trade and land use, called SIMPLE, is utilized to link adaptation investments, yield growth rates, land conversion rates, and land use emissions. A scenario of global adaptation to offset negative yield impacts of temperature and precipitation changes to 2050, which requires a cumulative 225 billion USD of additional investment, results in 61 Mha less conversion of cropland and 15 Gt carbon dioxide equivalent (CO₂e) fewer emissions by 2050. Thus our estimates imply an annual mitigation co-benefit of 0.35 GtCO₂e yr⁻¹ while spending $15 per tonne CO₂e of avoided emissions. Uncertainty analysis is used to estimate a 5–95% confidence interval around these numbers of 0.25–0.43 Gt and $11–$22 per tonne CO₂e. A scenario of adaptation focused only on Sub-Saharan Africa and Latin America, while less costly in aggregate, results in much smaller mitigation potentials and higher per tonne costs. These results indicate that although investing in the least developed areas may be most desirable for the main objectives of adaptation, it has little net effect on mitigation because production gains are offset by greater rates of land clearing in the benefited regions, which are relatively low yielding and land abundant. Adaptation investments in high yielding, land scarce regions such as Asia and North America are more effective for mitigation.

To identify data needs, we conduct a sensitivity analysis using the Morris method (Morris 1991 Technometrics 33 161–74). The three most critical parameters for improving estimates of mitigation potential are (in descending order) the emissions factors for converting land to agriculture, the price elasticity of land supply with respect to land rents, and the elasticity of substitution between land and non-land inputs. For assessing the mitigation costs, the elasticity of productivity with respect to investments in research and development is also very important. Overall, this study finds that broad-based efforts to adapt agriculture to climate change have mitigation co-benefits that, even when forced to shoulder the entire expense of adaptation, are inexpensive relative to many activities whose main purpose is mitigation. These results therefore challenge the current approach of most climate financing portfolios, which support adaptation from funds completely separate from—and often much smaller than—mitigation ones.

Among the main greenhouse gases (CO₂, CH₄ and N₂O), N₂O has the highest global warming potential. N₂O emission is mainly connected to agricultural activities, increasing as nitrogen concentrations increase in the soil with nitrogen fertilizer application. We evaluated N₂O emissions due to application of increasing doses of ammonium nitrate and urea in two sugarcane fields in the mid-southern region of Brazil: Piracicaba (São Paulo state) and Goianésia (Goiás state). In Piracicaba, N₂O emissions exponentially increased with increasing N doses and were similar for urea and ammonium nitrate up to a dose of 107.9 kg ha⁻¹ of N. From there on, emissions exponentially increased for ammonium nitrate, whereas for urea they stabilized. In Goianésia, N₂O emissions were lower, although the behavior was similar to that at the Piracicaba site. Ammonium nitrate emissions increased linearly with N dose and urea emissions were adjusted to a quadratic equation with a maximum amount of 113.9 kg N ha⁻¹. This first effort to measure fertilizer induced emissions in Brazilian sugarcane production not only helps to elucidate the behavior of N₂O emissions promoted by different N sources frequently used in Brazilian sugarcane fields but also can be useful for future Brazilian ethanol carbon footprint studies.

Soil tillage and other methods of soil management may influence CO₂ emissions because they accelerate the mineralization of organic carbon in the soil. This study aimed to quantify the CO₂ emissions under conventional tillage (CT), minimum tillage (MT) and reduced tillage (RT) during the renovation of sugarcane fields in southern Brazil. The experiment was performed on an Oxisol in the sugarcane-planting area with mechanical harvesting. An undisturbed or no-till (NT) plot was left as a control treatment. The CO₂ emissions results indicated a significant interaction (p < 0.001) between tillage method and time after tillage. By quantifying the accumulated emissions over the 44 days after soil tillage, we observed that tillage-induced emissions were higher after the CT system than the RT and MT systems, reaching 350.09 g m⁻² of CO₂ in CT, and 51.7 and 5.5 g m⁻² of CO₂ in RT and MT respectively. The amount of C lost in the form of CO₂ due to soil tillage practices was significant and comparable to the estimated value of potential annual C accumulation resulting from changes in the harvesting system in Brazil from burning of plant residues to the adoption of green cane harvesting. The CO₂ emissions in the CT system could respond to a loss of 80% of the potential soil C accumulated over one year as result of the adoption of mechanized sugarcane harvesting. Meanwhile, soil tillage during the renewal of the sugar plantation using RT and MT methods would result in low impact, with losses of 12% and 2% of the C that could potentially be accumulated during a one year period.

We assessed the impacts of extreme late-summer drought on carbon balance in a semi-arid forest region in Arizona. To understand drought impacts over extremes of forest cover, we measured net ecosystem production (NEP), gross primary production (GPP), and total ecosystem respiration (TER) with eddy covariance over five years (2006–10) at an undisturbed ponderosa pine (Pinus ponderosa) forest and at a former forest converted to grassland by intense burning. Drought shifted annual NEP from a weak source of carbon to the atmosphere to a neutral carbon balance at the burned site and from a carbon sink to neutral at the undisturbed site. Carbon fluxes were particularly sensitive to drought in August. Drought shifted August NEP at the undisturbed site from sink to source because the reduction of GPP (70%) exceeded the reduction of TER (35%). At the burned site drought shifted August NEP from weak source to neutral because the reduction of TER (40%) exceeded the reduction of GPP (20%). These results show that the lack of forest recovery after burning and the exposure of undisturbed forests to late-summer drought reduce carbon sink strength and illustrate the high vulnerability of forest carbon sink strength in the southwest US to predicted increases in intense burning and precipitation variability.

Environmental education is frequently undertaken as a conservation intervention designed to change the attitudes and behaviour of recipients. Much conservation education is aimed at children, with the rationale that children influence the attitudes of their parents, who will consequently change their behaviour. Empirical evidence to substantiate this suggestion is very limited, however. For the first time, we use a controlled trial to assess the influence of wetland-related environmental education on the knowledge of children and their parents and household behaviour. We demonstrate adults exhibiting greater knowledge of wetlands and improved reported household water management behaviour when their child has received wetland-based education at Seychelles wildlife clubs. We distinguish between 'folk' knowledge of wetland environments and knowledge obtained from formal education, with intergenerational transmission of each depending on different factors. Our study provides the first strong support for the suggestion that environmental education can be transferred between generations and indirectly induce targeted behavioural changes.

Improved understanding of Greenland ice sheet hydrology is critically important for assessing its impact on current and future ice sheet dynamics and global sea level rise. This has motivated the collection and integration of in situ observations, model development, and remote sensing efforts to quantify meltwater production, as well as its phase changes, transport, and export. Particularly urgent is a better understanding of albedo feedbacks leading to enhanced surface melt, potential positive feedbacks between ice sheet hydrology and dynamics, and meltwater retention in firn. These processes are not isolated, but must be understood as part of a continuum of processes within an integrated system. This letter describes a systems approach to the study of Greenland ice sheet hydrology, emphasizing component interconnections and feedbacks, and highlighting research and observational needs.

The present and future concentration of atmospheric carbon dioxide depends on both anthropogenic and natural sources and sinks of carbon. Most proposed climate mitigation strategies rely on a progressive transition to carbon-efficient technologies to reduce industrial emissions, substantially supported by policies to maintain or enhance the terrestrial carbon stock in forests and other ecosystems. This strategy may be challenged if terrestrial sequestration capacity is affected by future climate feedbacks, but how and to what extent is little understood. Here, we show that climate mitigation strategies are highly sensitive to future natural disturbance rates (e.g. fires, hurricanes, droughts), because of the potential effect of disturbances on the terrestrial carbon balance. Generally, altered disturbance rates affect the pace of societal and technological transitions required to achieve the mitigation target, with substantial consequences on the energy sector and the global economy. An understanding of the future dynamics and consequences of natural disturbances on terrestrial carbon balance is thus essential for developing robust climate mitigation strategies and policies.

Landscape scale quantification enables farmers to pool resources and expertise. However, the problem remains of how to quantify these gains. This article considers current greenhouse gas (GHG) quantification methods that can be used in a landscape scale analysis in terms of relevance to areas dominated by smallholders in developing countries. In landscape scale carbon accounting frameworks, measurements are an essential element. Sampling strategies need careful design to account for all pools/fluxes and to ensure judicious use of resources. Models can be used to scale-up measurements and fill data gaps. In recent years a number of accessible models and calculators have been developed which can be used at the landscape scale in developing country areas. Some are based on the Intergovernmental Panel on Climate Change (IPCC) method and others on dynamic ecosystem models. They have been developed for a range of different purposes and therefore vary in terms of accuracy and usability. Landscape scale assessments of GHGs require a combination of ground sampling, use of data from census, remote sensing (RS) or other sources and modelling. Fitting of all of these aspects together needs to be performed carefully to minimize uncertainties and maximize the use of scarce resources. This is especially true in heterogeneous landscapes dominated by smallholders in developing countries.

The productive cellulosic crops switchgrass and Miscanthus are considered as viable biofuel sources. To meet the 2022 national biofuel target mandate, actions must be taken, e.g., maize cultivation must be intensified and expanded, and other biofuel crops (switchgrass and Miscanthus) must be cultivated. This raises questions on the use efficiencies of land and water; to date, the demand on these resources to meet the national biofuel target has rarely been analyzed. Here, we present a data-model assimilation analysis, assuming that maize, switchgrass and Miscanthus will be grown on currently available croplands in the US. Model simulations suggest that maize can produce 3.0–5.4 kiloliters (kl) of ethanol for every hectare of land, depending on the feedstock to ethanol conversion efficiency; Miscanthus has more than twice the biofuel production capacity relative to maize, and switchgrass is the least productive of the three potential sources of ethanol. To meet the biofuel target, about 26.5 million hectares of land and over 90 km³ of water (of evapotranspiration) are needed if maize grain alone is used. If Miscanthus was substituted for maize, the process would save half of the land and one third of the water. With more advanced biofuel conversion technology for Miscanthus, only nine million hectares of land and 45 km³ of water would probably meet the national target. Miscanthus could be a good alternative biofuel crop to maize due to its significantly lower demand for land and water on a per unit of ethanol basis.

Estimates of the global wind power resource over land range from 56 to 400 TW. Most estimates have implicitly assumed that extraction of wind energy does not alter large-scale winds enough to significantly limit wind power production. Estimates that ignore the effect of wind turbine drag on local winds have assumed that wind power production of 2–4 W m⁻² can be sustained over large areas. New results from a mesoscale model suggest that wind power production is limited to about 1 W m⁻² at wind farm scales larger than about 100 km². We find that the mesoscale model results are quantitatively consistent with results from global models that simulated the climate response to much larger wind power capacities. Wind resource estimates that ignore the effect of wind turbines in slowing large-scale winds may therefore substantially overestimate the wind power resource.

Climate change will affect the concentrations of air pollutants in buildings. The resulting shifts in human exposure may influence public health. Changes can be anticipated because of altered outdoor pollution and also owing to changes in buildings effected in response to changing climate. Three classes of factors govern indoor pollutant levels in occupied spaces: (a) properties of pollutants; (b) building factors, such as the ventilation rate; and (c) occupant behavior. Diversity of indoor conditions influences the public health significance of climate change. Potentially vulnerable subpopulations include not only the young and the infirm but also those who lack resources to respond effectively to changing conditions. Indoor air pollutant levels reflect the sum of contributions from indoor sources and from outdoor pollutants that enter with ventilation air. Pollutant classes with important indoor sources include the byproducts of combustion, radon, and volatile and semivolatile organic compounds. Outdoor pollutants of special concern include particulate matter and ozone. To ensure good indoor air quality it is important first to avoid high indoor emission rates for all pollutants and second to ensure adequate ventilation. A third factor is the use of air filtration or air cleaning to achieve further improvements where warranted.

To help address the built environmental issues of both heat island and stormwater runoff, strategies that make pavements cooler and permeable have been investigated through measurements and modeling of a set of pavement test sections. The investigation included the hydraulic and thermal performance of the pavements. The permeability results showed that permeable interlocking concrete pavers have the highest permeability (or infiltration rate, ∼0.5 cm s⁻¹). The two permeable asphalt pavements showed the lowest permeability, but still had an infiltration rate of ∼0.1 cm s⁻¹, which is adequate to drain rainwater without generating surface runoff during most typical rain events in central California. An increase in albedo can significantly reduce the daytime high surface temperature in summer. Permeable pavements under wet conditions could give lower surface temperatures than impermeable pavements. The cooling effect highly depends on the availability of moisture near the surface layer and the evaporation rate. The peak cooling effect of watering for the test sections was approximately 15–35 °C on the pavement surface temperature in the early afternoon during summer in central California. The evaporative cooling effect on the pavement surface temperature at 4:00 pm on the third day (25 h after watering) was still 2–7 °C lower compared to that on the second day, without considering the higher air temperature on the third day. A separate and related simulation study performed by UCPRC showed that full depth permeable pavements, if designed properly, can carry both light-duty traffic and certain heavy-duty vehicles while retaining the runoff volume captured from an average California storm event. These preliminarily results indicated the technical feasibility of combined reflective and permeable pavements for addressing the built environment issues related to both heat island mitigation and stormwater runoff management.

Biofuels are increasingly promoted worldwide as a means for reducing greenhouse gas (GHG) emissions from transport. However, current regulatory frameworks and most academic life cycle analyses adopt a deterministic approach in determining the GHG intensities of biofuels and thus ignore the inherent risk associated with biofuel production. This study aims to develop a transparent stochastic method for evaluating UK biofuels that determines both the magnitude and uncertainty of GHG intensity on the basis of current industry practices. Using wheat ethanol as a case study, we show that the GHG intensity could span a range of 40–110 gCO₂e MJ⁻¹ when land use change (LUC) emissions and various sources of uncertainty are taken into account, as compared with a regulatory default value of 44 gCO₂e MJ⁻¹. This suggests that the current deterministic regulatory framework underestimates wheat ethanol GHG intensity and thus may not be effective in evaluating transport fuels. Uncertainties in determining the GHG intensity of UK wheat ethanol include limitations of available data at a localized scale, and significant scientific uncertainty of parameters such as soil N₂O and LUC emissions. Biofuel polices should be robust enough to incorporate the currently irreducible uncertainties and flexible enough to be readily revised when better science is available.

The predicted future of the global marine environment, as a combined result of forcing due to climate change (e.g. warming and acidification) and other anthropogenic perturbation (e.g. eutrophication), presents a challenge to the sustainability of ecosystems from tropics to high latitudes. Among the various associated phenomena of ecosystem deterioration, hypoxia can cause serious problems in coastal areas as well as oxygen minimum zones in the open ocean (Diaz and Rosenberg 2008 Science321 926–9, Stramma et al 2008 Science320 655–8). The negative impacts of hypoxia include changes in populations of marine organisms, such as large-scale mortality and behavioral responses, as well as variations of species distributions, biodiversity, physiological stress, and other sub-lethal effects (e.g. growth and reproduction). Social and economic activities that are related to services provided by the marine ecosystems, such as tourism and fisheries, can be negatively affected by the aesthetic outcomes as well as perceived or real impacts on seafood quality (STAP 2011 (Washington, DC: Global Environment Facility) p 88). Moreover, low oxygen concentration in marine waters can have considerable feedbacks to other compartments of the Earth system, like the emission of greenhouse gases to the atmosphere, and can affect the global biogeochemical cycles of nutrients and trace elements. It is of critical importance to prediction and adaptation strategies that the key processes of hypoxia in marine environments be precisely determined and understood (cf Zhang et al 2010 Biogeosciences7 1–24).

Cosmic rays produce molecular cluster ions as they pass through the lower atmosphere. Neutral molecular clusters such as dimers and complexes are expected to make a small contribution to the radiative balance, but atmospheric absorption by charged clusters has not hitherto been observed. In an atmospheric experiment, a narrowband thermopile filter radiometer centred on 9.15 μm, an absorption band previously associated with infra-red absorption of molecular cluster ions, was used to monitor changes following events identified by a cosmic ray telescope sensitive to high-energy (>400 MeV) particles, principally muons. The average change in longwave radiation in this absorption band due to molecular cluster ions is 7 mWm⁻². The integrated atmospheric energy density for each event is 2 Jm⁻², representing an amplification factor of 10¹² compared to the estimated energy density of a typical air shower. This absorption is expected to occur continuously and globally, but calculations suggest that it has only a small effect on climate.

Layer clouds are globally extensive. Their lower edges are charged negatively by the fair weather atmospheric electricity current flowing vertically through them. Using polar winter surface meteorological data from Sodankylä (Finland) and Halley (Antarctica), we find that when meteorological diurnal variations are weak, an appreciable diurnal cycle, on average, persists in the cloud base heights, detected using a laser ceilometer. The diurnal cloud base heights from both sites correlate more closely with the Carnegie curve of global atmospheric electricity than with local meteorological measurements. The cloud base sensitivities are indistinguishable between the northern and southern hemispheres, averaging a (4.0 ± 0.5) m rise for a 1% change in the fair weather electric current density. This suggests that the global fair weather current, which is affected by space weather, cosmic rays and the El Niño Southern Oscillation, is linked with layer cloud properties.

Efforts to reduce the environmental impacts of transportation infrastructure have generally overlooked many of the efficiencies that can be obtained by considering the relevant engineering and economic aspects as a system. Here, we present a framework for quantifying the burdens of ground transportation in urban settings that incorporates travel time, vehicle fuel and pavement maintenance costs. A Pareto set of bi-directional lane configurations for two-lane roadways yields non-dominated combinations of lane width, bicycle lanes and curb parking. Probabilistic analysis and microsimulation both show dramatic mobility reductions on road segments of insufficient width for heavy vehicles to pass bicycles without encroaching on oncoming traffic. This delay is positively correlated with uphill grades and increasing traffic volumes and inversely proportional to total pavement width. The response is nonlinear with grade and yields mixed uphill/downhill optimal lane configurations. Increasing bicycle mode share is negatively correlated with total costs and emissions for lane configurations allowing motor vehicles to safely pass bicycles, while the opposite is true for configurations that fail to facilitate passing. Spatial impacts on mobility also dictate that curb parking exhibits significant spatial opportunity costs related to the total cost Pareto curve. The proposed framework provides a means to evaluate relatively inexpensive lane reconfiguration options in response to changing modal share and priorities. These results provide quantitative evidence that efforts to reallocate limited pavement space to bicycles, like those being adopted in several US cities, could appreciably reduce costs for all users.

This letter is intended to help potential users select the most appropriate calculator for a landscape-scale greenhouse gas (GHG) assessment of activities for agriculture and forestry. Eighteen calculators were assessed. These calculators were designed for different aims and to be used in different geographical areas and they use slightly different accounting methodologies. The classification proposed is based on the main aim of the assessment: raising awareness, reporting, project evaluation or product assessment. When the aims have been clearly formulated, the most suitable calculator can be selected from the comparison tables, taking account of the geographical area and the scope of the calculation as well as the time and skills required for the calculation. The main issues for interpreting GHG assessments are discussed, highlighting the difficulty of comparing the results obtained from different calculators, mainly owing to differences in scope, calculation methods and reporting units. A major problem is the poor accounting for land use change; the calculators are usually able to account satisfactorily for other emission sources. One of the main challenges at landscape-scale level is to produce a realistic assessment of the various production systems as the uncertainty levels are very high. The results should always give some indication of the link between GHG emissions and the productivity of the area, although no single indicator is able to encompass all the services produced by agriculture and forestry (e.g. food, goods, landscape value and revenue).

Developing countries face many challenges when constructing national inventories of greenhouse gas (GHG) emissions, such as lack of activity data, insufficient measurements for deriving country-specific emission factors, and a limited basis for assessing GHG mitigation options. Emissions from agricultural production are often significant sources in developing countries, particularly soil nitrous oxide, and livestock enteric and manure methane, in addition to wetland rice methane. Consequently, estimating GHG emissions from agriculture is an important part of constructing developing country inventories. While the challenges may seem insurmountable, there are ways forward such as: (a) efficiently using resources to compile activity data by combining censuses and surveys; (b) using a tiered approach to measure emissions at appropriately selected sites, coupled with modeling to derive country-specific emission factors; and (c) using advanced software systems to guide compilers through the inventory process. With a concerted effort by compilers and assistance through capacity-building efforts, developing country compilers could produce transparent, accurate, complete, consistent and comparable inventories, as recommended by the IPCC (Intergovernmental Panel on Climate Change). In turn, the resulting inventories would provide the foundation for robust GHG mitigation analyses and allow for the development of nationally appropriate mitigation actions and low emission development strategies.

This article provides consolidated estimates of water withdrawal and water consumption for the full life cycle of selected electricity generating technologies, which includes component manufacturing, fuel acquisition, processing, and transport, and power plant operation and decommissioning. Estimates were gathered through a broad search of publicly available sources, screened for quality and relevance, and harmonized for methodological differences. Published estimates vary substantially, due in part to differences in production pathways, in defined boundaries, and in performance parameters. Despite limitations to available data, we find that: water used for cooling of thermoelectric power plants dominates the life cycle water use in most cases; the coal, natural gas, and nuclear fuel cycles require substantial water per megawatt-hour in most cases; and, a substantial proportion of life cycle water use per megawatt-hour is required for the manufacturing and construction of concentrating solar, geothermal, photovoltaic, and wind power facilities. On the basis of the best available evidence for the evaluated technologies, total life cycle water use appears lowest for electricity generated by photovoltaics and wind, and highest for thermoelectric generation technologies. This report provides the foundation for conducting water use impact assessments of the power sector while also identifying gaps in data that could guide future research.

We present a simple method of probabilistic risk analysis for ecosystems. The only requirements are time series—modelled or measured—of environment and ecosystem variables. Risk is defined as the product of hazard probability and ecosystem vulnerability. Vulnerability is the expected difference in ecosystem performance between years with and without hazardous conditions. We show an application to drought risk for net primary productivity of coniferous forests across Europe, for both recent and future climatic conditions.

Recently deglaciated areas are ideal environments to study soil formation and primary microbial succession where phototrophic microorganisms may play a role as primary producers. The aim of our study was to investigate the cyanobacterial and green algal community composition in three different successional stages of the Damma glacier forefield in the Swiss Alps using 16S rDNA and ITS rDNA clone libraries. Cyanobacterial target sequences varied along the glacier forefield, with the highest cyanobacterial 16S rRNA gene copies found in sparsely vegetated soils. Sequence analysis revealed that the phototrophic communities were distinct in each of the three soil environments. The majority of the cyanobacterial sequences retrieved from barren soils were related to the Oscillatoriales. The diversity in sparsely vegetated soils was low, and sequences closely related to Nostoc sp. dominated. The majority of the algal phylotypes are related to members of the Trebouxiophyceae known to live as symbiotic partners in lichens. We conclude that the community composition appears to shift markedly along the chronosequence, indicating that each soil environment selects for its phototrophic community. When cyanobacteria occur together with eukaryotic microalgae, they form a rich source of organic matter and may be important contributors of carbon in nutrient-deficient deglaciated soils.

This letter addresses the indigenous discourse on a set of plant species used by the Witoto Indians of Northwest Amazonia to extract ash or vegetable salt, obtained from the combustion of the tissues of vegetable species, filtering of the ashes, and desiccation of the resulting brine. It aims to demonstrate how the study of the human condition is carried out through a reading of natural entities. The method employed is the indexical analysis of a discourse uttered by the elder Enokakuiodo in the Witoto language from 1995 to 1998, in a verbal genre called rafue, one of several genres of the 'language of the yard of coca'. The species used to extract ash salt are conceived of as coming from the body of the Creator and as an image of the human body. The rafue of salt performs, in words and gestures, a narrative of human affects and capacities by reading ecological, biological, cultural and linguistic indices from a set of plant species. This discourse on plant species is a discourse on the control and management of bodily affects and capacities, represented as ash salts, that are lessons about sexual development which the Creator left for humanity as a guide—a 'sexual education'.

Recent expansion of tall shrubs in Low Arctic tundra is widely seen as a response to climate warming, but shrubification is not occurring as a simple function of regional climate trends. We show that establishment of tall alder (Alnus) is strongly facilitated by small, widely distributed cryogenic disturbances associated with patterned-ground landscapes. We identified expanding and newly established shrub stands at two northwest Siberian sites and observed that virtually all new shrubs occurred on bare microsites ('circles') that were disturbed by frost-heave. Frost-heave associated with circles is a widespread, annual phenomenon that maintains mosaics of mineral seedbeds with warm soils and few competitors that are immediately available to shrubs during favorable climatic periods. Circle facilitation of alder recruitment also plausibly explains the development of shrublands in which alders are regularly spaced. We conclude that alder abundance and extent have increased rapidly in the northwest Siberian Low Arctic since at least the mid-20th century, despite a lack of summer warming in recent decades. Our results are consistent with findings in the North American Arctic which emphasize that the responsiveness of Low Arctic landscapes to climate change is largely determined by the frequency and extent of disturbance processes that create mineral-rich seedbeds favorable for tall shrub recruitment. Northwest Siberia has high potential for continued expansion of tall shrubs and concomitant changes to ecosystem function, due to the widespread distribution of patterned-ground landscapes.

Determining the factors that influence the transmission of parasites among hosts is important for directing surveillance of animal parasites before they successfully emerge in humans, and increasing the efficacy of programs for the control and management of zoonotic diseases. Here we present a review of recent advances in the study of parasite sharing, wildlife ecology, and epidemiology that could be extended and incorporated into proactive surveillance frameworks for multi-host infectious diseases. These methods reflect emerging interdisciplinary techniques with significant promise for the identification of future zoonotic parasites and unknown reservoirs of current zoonoses, strategies for the reduction of parasite prevalence and transmission among hosts, and decreasing the burden of infectious diseases.

Healthy governance systems are key to delivering sound environmental management outcomes from global to local scales. There are, however, surprisingly few risk assessment methods that can pinpoint those domains and sub-domains within governance systems that are most likely to influence good environmental outcomes at any particular scale, or those if absent or dysfunctional, most likely to prevent effective environmental management. This paper proposes a new risk assessment method for analysing governance systems. This method is then tested through its preliminary application to a significant real-world context: governance as it relates to the health of Australia's Great Barrier Reef (GBR). The GBR exists at a supra-regional scale along most of the north eastern coast of Australia. Brodie et al (2012 Mar. Pollut. Bull. 65 81–100) have recently reviewed the state and trend of the health of the GBR, finding that overall trends remain of significant concern. At the same time, official international concern over the governance of the reef has recently been signalled globally by the International Union for the Conservation of Nature (IUCN). These environmental and political contexts make the GBR an ideal candidate for use in testing and reviewing the application of improved tools for governance risk assessment.

The sustainable development of brownfields reflects a fundamental, yet logical, shift in thinking and policymaking regarding pollution prevention. Life-cycle assessment (LCA) is a tool that can be used to assist in determining the conformity of brownfield development projects to the sustainability paradigm. LCA was applied to the process of a real brownfield redevelopment project, now known as the Chicago Center for Green Technology, to determine the cumulative energy required to complete the following redevelopment stages: (1) brownfield assessment and remediation, (2) building rehabilitation and site development and (3) ten years of operation. The results of the LCA have shown that operational energy is the dominant life-cycle stage after ten years of operation. The preservation and rehabilitation of the existing building, the installation of renewable energy systems (geothermal and photovoltaic) on-site and the use of more sustainable building products resulted in 72 terajoules (TJ) of avoided energy impacts, which would provide 14 years of operational energy for the site.

Cost-effective protected area networks require that decision makers have sufficient information to allocate investments in ways that generate the greatest positive impacts. With applications in more than 50 countries, the Rapid Assessment and Prioritization of Protected Area Management (RAPPAM) method is arguably the tool used most widely to assist such prioritization. The extent to which its indicators provide useful measures of a protected area's capacity to achieve its conservation objectives, however, has seldom been subject to empirical scrutiny. We use a rich spatial dataset and time series data from 66 forest protected areas in the Brazilian Amazon to examine whether RAPPAM scores are associated with success in avoiding deforestation. We find no statistically significant association between avoided deforestation and indicators that reflect preferential targets of conservation investments, including budget, staff, equipment, management plans and stakeholder collaboration. Instead, we find that the absence of unsettled land tenure conflicts is consistently associated strongly with success in reducing deforestation pressures. Our results underscore the importance of tracking and resolving land tenure in protected area management, and lead us to call for more rigorous assessments of existing strategies for assessing and prioritizing management interventions in protected areas.

We present a focus issue of Environmental Research Letters on the 'Recent dynamics of arctic and sub-arctic vegetation'. The focus issue includes three perspective articles (Verbyla 2011 Environ. Res. Lett.6 041003, Williams et al 2011 Environ. Res. Lett.6 041004, Loranty and Goetz 2012 Environ. Res. Lett.7 011005) and 22 research articles. The focus issue arose as a result of heightened interest in the response of high-latitude vegetation to natural and anthropogenic changes in climate and disturbance regimes, and the consequences that these vegetation changes might have for northern ecosystems. A special session at the December 2010 American Geophysical Union Meeting on the 'Greening of the Arctic' spurred the call for papers. Many of the resulting articles stem from intensive research efforts stimulated by International Polar Year projects and the growing acknowledgment of ongoing climate change impacts in northern terrestrial ecosystems.

Public transportation systems are often part of strategies to reduce urban environmental impacts from passenger transportation, yet comprehensive energy and environmental life-cycle measures, including upfront infrastructure effects and indirect and supply chain processes, are rarely considered. Using the new bus rapid transit and light rail lines in Los Angeles, near-term and long-term life-cycle impact assessments are developed, including consideration of reduced automobile travel. Energy consumption and emissions of greenhouse gases and criteria pollutants are assessed, as well the potential for smog and respiratory impacts. Results show that life-cycle infrastructure, vehicle, and energy production components significantly increase the footprint of each mode (by 48–100% for energy and greenhouse gases, and up to 6200% for environmental impacts), and emerging technologies and renewable electricity standards will significantly reduce impacts. Life-cycle results are identified as either local (in Los Angeles) or remote, and show how the decision to build and operate a transit system in a city produces environmental impacts far outside of geopolitical boundaries. Ensuring shifts of between 20–30% of transit riders from automobiles will result in passenger transportation greenhouse gas reductions for the city, and the larger the shift, the quicker the payback, which should be considered for time-specific environmental goals.

In the article 'Energy and air emission implications of a decentralized wastewater system' published in Environmental Research Letters (2012 Environ. Res. Lett.7 024007), Shehabi et al compared a decentralized and a centralized system on the basis of energy use, greenhouse gas emissions and air pollutants, and claimed that economies of scale lower the environmental impacts from a centralized system on a per-volume basis. In this comment, we present literature and data from New York State, USA to argue that the authors' comparison between a small decentralized system (0.015 MGD) and a large centralized system (66.5 MGD) is unconventional and inappropriate.

Complementing centralized water-related infrastructure with decentralized facilities is being considered in some communities and a life-cycle perspective is needed for informed decision making. Our 2012 study presents a framework for analyzing the environmental effects of decentralized wastewater systems. While the analysis framework could be applied to cases with a variety of sizes, we evaluated two currently operating systems in California, one decentralized and one centralized plant with a much larger capacity. The disparate scales of the two plants represent an 'off-the-grid' suburban neighborhood-scale system compared with a similarly sized neighborhood connecting to an adjacent large centralized plant. Deciding whether or not to connect expanding developments to nearby centralized plants is a realistic scenario for future growth, making the treatment plants evaluated in our study a realistic choice for comparison.

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