Table of contents

Air pollution from the use of solid household fuels is now recognized to be a major health risk in developing countries. Accordingly, there has been some shift in development thinking and investment from previous efforts, which has focused only on improving the efficiency of household fuel use, to those that focus on reducing exposure to the air pollution that leads to health impact. Unfortunately, however, this is occurring just as the climate agenda has come to dominate much of the discourse and action on international sustainable development. Thus, instead of optimizing approaches that centrally focus on the large health impact, the household energy agenda has been hampered by the constraints imposed by a narrow definition of sustainability—one primarily driven by the desire to mitigate greenhouse emissions by relying on renewable biomass fueling so-called improved cookstoves. In reality, however, solid biomass is extremely difficult to burn sufficiently cleanly in household stoves to reach health goals. In comparison to the international development community, however, some large countries, notably Brazil historically and more recently, India have substantially expanded the use of liquefied petroleum gas (LPG) in their household energy mix, using their own resources, having a major impact on their national energy picture. The net climate impact of such approaches compared to current biomass stoves is minimal or non-existent, and the social and health benefits are, in contrast, potentially great. LPG can be seen as a transition fuel for clean household energy, with induction stoves powered by renewables as the holy grail (an approach already being adopted by Ecuador as also discussed here). The enormous human and social benefits of clean energy, rather than climate concerns, should dominate the household energy access agenda today.

Individual-based models (IBMs) of complex systems emerged in the 1960s and early 1970s, across diverse disciplines from astronomy to zoology. Ecological IBMs arose with seemingly independent origins out of the tradition of understanding the ecosystems dynamics of ecosystems from a 'bottom-up' accounting of the interactions of the parts. Individual trees are principal among the parts of forests. Because these models are computationally demanding, they have prospered as the power of digital computers has increased exponentially over the decades following the 1970s.

This review will focus on a class of forest IBMs called gap models. Gap models simulate the changes in forests by simulating the birth, growth and death of each individual tree on a small plot of land. The summation of these plots comprise a forest (or set of sample plots on a forested landscape or region). Other, more aggregated forest IBMs have been used in global applications including cohort-based models, ecosystem demography models, etc. Gap models have been used to provide the parameters for these bulk models. Currently, gap models have grown from local-scale to continental-scale and even global-scale applications to assess the potential consequences of climate change on natural forests. Modifications to the models have enabled simulation of disturbances including fire, insect outbreak and harvest.

Our objective in this review is to provide the reader with an overview of the history, motivation and applications, including theoretical applications, of these models. In a time of concern over global changes, gap models are essential tools to understand forest responses to climate change, modified disturbance regimes and other change agents. Development of forest surveys to provide the starting points for simulations and better estimates of the behavior of the diversity of tree species in response to the environment are continuing needs for improvement for these and other IBMs.

Researchers and water managers have turned to green stormwater infrastructure, such as bioswales, retention basins, wetlands, rain gardens, and urban green spaces to reduce flooding, augment surface water supplies, recharge groundwater, and improve water quality. It is increasingly clear that green stormwater infrastructure not only controls stormwater volume and timing, but also promotes ecosystem services, which are the benefits that ecosystems provide to humans. Yet there has been little synthesis focused on understanding how green stormwater management affects ecosystem services. The objectives of this paper are to review and synthesize published literature on ecosystem services and green stormwater infrastructure and identify gaps in research and understanding, establishing a foundation for research at the intersection of ecosystems services and green stormwater management. We reviewed 170 publications on stormwater management and ecosystem services, and summarized the state-of-the-science categorized by the four types of ecosystem services. Major findings show that: (1) most research was conducted at the parcel-scale and should expand to larger scales to more closely understand green stormwater infrastructure impacts, (2) nearly a third of papers developed frameworks for implementing green stormwater infrastructure and highlighted barriers, (3) papers discussed ecosystem services, but less than 40% quantified ecosystem services, (4) no geographic trends emerged, indicating interest in applying green stormwater infrastructure across different contexts, (5) studies increasingly integrate engineering, physical science, and social science approaches for holistic understanding, and (6) standardizing green stormwater infrastructure terminology would provide a more cohesive field of study than the diverse and often redundant terminology currently in use. We recommend that future research provide metrics and quantify ecosystem services, integrate disciplines to measure ecosystem services from green stormwater infrastructure, and better incorporate stormwater management into environmental policy. Our conclusions outline promising future research directions at the intersection of stormwater management and ecosystem services.

Roughly 3% of the Earth's land surface burns annually, representing a critical exchange of energy and matter between the land and atmosphere via combustion. Fires range from slow smouldering peat fires, to low-intensity surface fires, to intense crown fires, depending on vegetation structure, fuel moisture, prevailing climate, and weather conditions. While the links between biogeochemistry, climate and fire are widely studied within Earth system science, these relationships are also mediated by fuels—namely plants and their litter—that are the product of evolutionary and ecological processes. Fire is a powerful selective force and, over their evolutionary history, plants have evolved traits that both tolerate and promote fire numerous times and across diverse clades. Here we outline a conceptual framework of how plant traits determine the flammability of ecosystems and interact with climate and weather to influence fire regimes. We explore how these evolutionary and ecological processes scale to impact biogeochemical and Earth system processes. Finally, we outline several research challenges that, when resolved, will improve our understanding of the role of plant evolution in mediating the fire feedbacks driving Earth system processes. Understanding current patterns of fire and vegetation, as well as patterns of fire over geological time, requires research that incorporates evolutionary biology, ecology, biogeography, and the biogeosciences.

Background. Policy makers and program managers need to better understand consumers' perceptions of their energy use and savings to design effective strategies for promoting energy savings. Methods. We reviewed 14 studies from the emerging interdisciplinary literature examining consumers' perceptions electricity use by specific appliances, and potential savings. Results. We find that: (1) electricity use is often overestimated for low-energy consuming appliances, and underestimated for high-energy consuming appliances; (2) curtailment strategies are typically preferred over energy efficiency strategies; (3) consumers lack information about how much electricity can be saved through specific strategies; (4) consumers use heuristics for assessing the electricity use of specific appliances, with some indication that more accurate judgments are made among consumers with higher numeracy and stronger pro-environmental attitudes. However, design differences between studies, such as variations in reference points, reporting units and assessed time periods, may affect consumers' reported perceptions. Moreover, studies differ with regard to whether accuracy of perceptions was evaluated through comparisons with general estimates of actual use, self-reported use, household-level meter readings, or real-time smart meter readings. Conclusion. Although emerging findings are promising, systematic variations in the measurement of perceived and actual electricity use are potential cause for concern. We propose avenues for future research, so as to better understand, and possibly inform, consumers' perceptions of their electricity use. Ultimately, this literature will have implications for the design of effective electricity feedback for consumers, and related policies.

The term tipping point has experienced explosive popularity across multiple disciplines over the last decade. Research on social-ecological systems (SES) has contributed to the growth and diversity of the term's use. The diverse uses of the term obscure potential differences between tipping behavior in natural and social systems, and issues of causality across natural and social system components in SES. This paper aims to create the foundation for a discussion within the SES research community about the appropriate use of the term tipping point, especially the relatively novel term 'social tipping point.' We review existing literature on tipping points and similar concepts (e.g. regime shifts, critical transitions) across all spheres of science published between 1960 and 2016 with a special focus on a recent and still small body of work on social tipping points. We combine quantitative and qualitative analyses in a bibliometric approach, rooted in an expert elicitation process. We find that the term tipping point became popular after the year 2000—long after the terms regime shift and critical transition—across all spheres of science. We identify 23 distinct features of tipping point definitions and their prevalence across disciplines, but find no clear taxonomy of discipline-specific definitions. Building on the most frequently used features, we propose definitions for tipping points in general and social tipping points in SES in particular.

The United Nations' Sustainable Development Goals (SDGs) provide guide-posts to society as it attempts to respond to an array of pressing challenges. One of these challenges is energy; thus, the SDGs have become paramount for energy policy-making. Yet, while governments throughout the world have already declared the SDGs to be 'integrated and indivisible', there are still knowledge gaps surrounding how the interactions between the energy SDG targets and those of the non-energy-focused SDGs might play out in different contexts. In this review, we report on a large-scale assessment of the relevant energy literature, which we conducted to better our understanding of key energy-related interactions between SDGs, as well as their context-dependencies (relating to time, geography, governance, technology, and directionality). By (i) evaluating the nature and strength of the interactions identified, (ii) indicating the robustness of the evidence base, the agreement of that evidence, and our confidence in it, and (iii) highlighting critical areas where better understanding is needed or context dependencies should be considered, our review points to potential ways forward for both the policy making and scientific communities. First, we find that positive interactions between the SDGs outweigh the negative ones, both in number and magnitude. Second, of relevance for the scientific community, in order to fill knowledge gaps in critical areas, there is an urgent need for interdisciplinary research geared toward developing new data, scientific tools, and fresh perspectives. Third, of relevance for policy-making, wider efforts to promote policy coherence and integrated assessments are required to address potential policy spillovers across sectors, sustainability domains, and geographic and temporal boundaries. The task of conducting comprehensive science-to-policy assessments covering all SDGs, such as for the UN's Global Sustainable Development Report, remains manageable pending the availability of systematic reviews focusing on a limited number of SDG dimensions in each case.

Arctic plant productivity is often limited by low soil N availability. This has been attributed to slow breakdown of N-containing polymers in litter and soil organic matter (SOM) into smaller, available units, and to shallow plant rooting constrained by permafrost and high soil moisture. Using ¹⁵N pool dilution assays, we here quantified gross amino acid and ammonium production rates in 97 active layer samples from four sites across the Siberian Arctic. We found that amino acid production in organic layers alone exceeded literature-based estimates of maximum plant N uptake 17-fold and therefore reject the hypothesis that arctic plant N limitation results from slow SOM breakdown. High microbial N use efficiency in organic layers rather suggests strong competition of microorganisms and plants in the dominant rooting zone. Deeper horizons showed lower amino acid production rates per volume, but also lower microbial N use efficiency. Permafrost thaw together with soil drainage might facilitate deeper plant rooting and uptake of previously inaccessible subsoil N, and thereby promote plant productivity in arctic ecosystems. We conclude that changes in microbial decomposer activity, microbial N utilization and plant root density with soil depth interactively control N availability for plants in the Arctic.

Heat waves (HWs) are among the most damaging climate extremes to human society. Climate models consistently project that HW frequency, severity, and duration will increase markedly over this century. For urban residents, the urban heat island (UHI) effect further exacerbates the heat stress resulting from HWs. Here we use a climate model to investigate the interactions between the UHI and HWs in 50 cities in the United States under current climate and future warming scenarios. We examine UHI_2m (defined as urban-rural difference in 2m-height air temperature) and UHI_s (defined as urban-rural difference in radiative surface temperature). Our results show significant sensitivity of the interaction between UHI and HWs to local background climate and warming scenarios. Sensitivity also differs between daytime and nighttime. During daytime, cities in the temperate climate region show significant synergistic effects between UHI and HWs in current climate, with an average of 0.4 K higher UHI_2m or 2.8 K higher UHI_s during HWs than during normal days. These synergistic effects, however, diminish in future warmer climates. In contrast, the daytime synergistic effects for cities in dry regions are insignificant in the current climate, but emerge in future climates. At night, the synergistic effects are similar across climate regions in the current climate, and are stronger in future climate scenarios. We use a biophysical factorization method to disentangle the mechanisms behind the interactions between UHI and HWs that explain the spatial-temporal patterns of the interactions. Results show that the difference in the increase of urban versus rural evaporation and enhanced anthropogenic heat emissions (air conditioning energy use) during HWs are key contributors to the synergistic effects during daytime. The contrast in water availability between urban and rural land plays an important role in determining the contribution of evaporation. At night, the enhanced release of stored and anthropogenic heat during HWs are the primary contributors to the synergistic effects.

Induced seismicity is a concern for multiple geoenergy applications, including low-carbon enhanced geothermal systems (EGS). We present the results of an international expert elicitation (n = 14) on EGS induced seismicity hazard and risk. Using a hypothetical scenario of an EGS plant and its geological context, we show that expert best-guess estimates of annualized exceedance probabilities of an M ≥ 3 event range from 0.2%–95% during reservoir stimulation and 0.2%–100% during operation. Best-guess annualized exceedance probabilities of M ≥ 5 event span from 0.002%–2% during stimulation and 0.003%–3% during operation. Assuming that tectonic M7 events could occur, some experts do not exclude induced (triggered) events of up to M7 too. If an induced M = 3 event happens at 5 km depth beneath a town with 10 000 inhabitants, most experts estimate a 50% probability that the loss is contained within 500 000 USD without any injuries or fatalities. In the case of an induced M = 5 event, there is 50% chance that the loss is below 50 million USD with the most-likely outcome of 50 injuries and one fatality or none. As we observe a vast diversity in quantitative expert judgements and underlying mental models, we conclude with implications for induced seismicity risk governance. That is, we suggest documenting individual expert judgements in induced seismicity elicitations before proceeding to consensual judgements, to convene larger expert panels in order not to cherry-pick the experts, and to aim for multi-organization multi-model assessments of EGS induced seismicity hazard and risk.

The Arctic-alpine biome is warming rapidly, resulting in a gradual replacement of low statured species by taller woody species in many tundra ecosystems. In northwest North America, the remotely sensed normalized difference vegetation index (NDVI), suggests an increase in productivity of the Arctic and alpine tundra and a decrease in productivity of boreal forests. However, the responses of contrasting shrub species growing at the same sites to climate drivers remain largely unexplored.

Here, we test growth, climate, and NDVI relationships of two contrasting species: the expanding tall deciduous shrub Salix pulchra and the circumarctic evergreen dwarf shrub Cassiope tetragona from an alpine tundra site in the Pika valley in the Kluane Region, southwest Yukon Territories, Canada.

We found that annual growth variability of both species at this site is strongly driven by early summer temperatures, despite their contrasting traits and habitats. Shrub growth chronologies for both species were correlated with the regional climate signal and showed spatial correspondence with interannual variation in NDVI in surrounding alpine and Arctic regions. Our results suggest that early summer warming represents a common driver of vegetation change for contrasting shrub species growing in different habitats in the same alpine environments.

Previously, it was widely documented that an overall decrease in surface solar radiation occurred in China at least until 2005, in contrast to the general background of 'global brightening'. Increased anthropogenic aerosol emissions were speculated to be the source of the reduction. In this study, we extend the trend analysis to the most recent decade from 2005–2015 and find that surface solar radiation has shifted from 'dimming' to 'brightening' over East China, with the largest increase over the northeast and southeast parts. Meanwhile, satellite and ground observation both indicate a reduction in aerosol optical depth (AOD) during the same period, whereas no significant trends in cloud amount show up. Detailed analysis using co-located radiation and aerosol observation at the XiangHe station in North China suggests that both AOD and single scattering albedo (SSA) changes contribute to the radiation trends. AOD reduction contributes to the increase of direct solar radiation, also decreasing the diffuse radiation, while the increase of SSA serves to increase the diffuse fraction. Simple calculations using a radiative transfer model confirm that the two effects combined explain changes in the global solar radiation and its components effectively. Our results have implications for potential climate effects with the reduction of China's aerosol emissions, and the necessity to monitor aerosol composition in addition to its loading.

Recent studies have presented conflicting results regarding the 11 year solar cycle (SC) influences on winter climate over the North Atlantic/European region. Analyses of only the most recent decades suggest a synchronized North Atlantic Oscillation (NAO)-like response pattern to the SC. Analyses of long-term climate data sets dating back to the late 19th century, however, suggest a mean sea level pressure (mslp) response that lags the SC by 2–4 years in the southern node of the NAO (i.e. Azores region). To understand the conflicting nature and cause of these time dependencies in the SC surface response, the present study employs a lead/lag multi-linear regression technique with a sliding window of 44 years over the period 1751–2016. Results confirm previous analyses, in which the average response for the whole time period features a statistically significant 2–4 year lagged mslp response centered over the Azores region. Overall, the lagged nature of Azores mslp response is generally consistent in time. Stronger and statistically significant SC signals tend to appear in the periods when the SC forcing amplitudes are relatively larger. Individual month analysis indicates the consistent lagged response in December–January–February average arises primarily from early winter months (i.e. December and January), which has been associated with ocean feedback processes that involve reinforcement by anomalies from the previous winter. Additional analysis suggests that the synchronous NAO-like response in recent decades arises primarily from late winter (February), possibly reflecting a result of strong internal noise.

Dramatic climate changes, especially the largest sea ice retreat during September and October, in the Chukchi–Beaufort Seas could be a consequence of, and further enhance, complex air–ice–sea interactions. To detect these interaction signals, statistical relationships between surface wind speed, sea surface temperature (SST), and sea ice concentration (SIC) were analyzed. The results show a negative correlation between wind speed and SIC. The relationships between wind speed and SST are complicated by the presence of sea ice, with a negative correlation over open water but a positive correlation in sea ice dominated areas. The examination of spatial structures indicates that wind speed tends to increase when approaching the ice edge from open water and the area fully covered by sea ice. The anomalous downward radiation and thermal advection, as well as their regional distribution, play important roles in shaping these relationships, though wind-driven sub-grid scale boundary layer processes may also have contributions. Considering the feedback loop involved in the wind–SST–SIC relationships, climate model experiments would be required to further untangle the underlying complex physical processes.

Cities are particularly vulnerable to climate risks due to their agglomeration of people, buildings and infrastructure. Differences in methodology, hazards considered, and climate models used limit the utility and comparability of climate studies on individual cities. Here we assess, for the first time, future changes in flood, heat-waves (HW), and drought impacts for all 571 European cities in the Urban Audit database using a consistent approach. To capture the full range of uncertainties in natural variability and climate models, we use all climate model runs from the Coupled Model Inter-comparison Project Phase 5 (CMIP5) for the RCP8.5 emissions scenario to calculate Low, Medium and High Impact scenarios, which correspond to the 10th, 50th and 90th percentiles of each hazard for each city. We find that HW days increase across all cities, but especially in southern Europe, whilst the greatest HW temperature increases are expected in central European cities. For the low impact scenario, drought conditions intensify in southern European cities while river flooding worsens in northern European cities. However, the high impact scenario projects that most European cities will see increases in both drought and river flood risks. Over 100 cities are particularly vulnerable to two or more climate impacts. Moreover, the magnitude of impacts exceeds those previously reported highlighting the substantial challenge cities face to manage future climate risks.

The chemical weathering of rocks currently absorbs about 1.1 Gt CO₂ a⁻¹ being mainly stored as bicarbonate in the ocean. An enhancement of this slow natural process could remove substantial amounts of CO₂ from the atmosphere, aiming to offset some unavoidable anthropogenic emissions in order to comply with the Paris Agreement, while at the same time it may decrease ocean acidification. We provide the first comprehensive assessment of economic costs, energy requirements, technical parameterization, and global and regional carbon removal potential. The crucial parameters defining this potential are the grain size and weathering rates. The main uncertainties about the potential relate to weathering rates and rock mass that can be integrated into the soil. The discussed results do not specifically address the enhancement of weathering through microbial processes, feedback of geogenic nutrient release, and bioturbation. We do not only assess dunite rock, predominantly bearing olivine (in the form of forsterite) as the mineral that has been previously proposed to be best suited for carbon removal, but focus also on basaltic rock to minimize potential negative side effects. Our results show that enhanced weathering is an option for carbon dioxide removal that could be competitive already at 60 US $ t⁻¹ CO₂ removed for dunite, but only at 200 US $ t⁻¹ CO₂ removed for basalt. The potential carbon removal on cropland areas could be as large as 95 Gt CO₂ a⁻¹ for dunite and 4.9 Gt CO₂ a⁻¹ for basalt. The best suited locations are warm and humid areas, particularly in India, Brazil, South-East Asia and China, where almost 75% of the global potential can be realized. This work presents a techno-economic assessment framework, which also allows for the incorporation of further processes.

Understanding how continuing increases in global mean temperature will exacerbate societal exposure to extreme weather events is a question of profound importance. However, determining population exposure to the impacts of heat extremes at 1.5 °C and 2 °C of global mean warming requires not only (1) a robust understanding of the physical climate system response, but also consideration of (2) projected changes to overall population size, as well as (3) changes to where people will live in the future. This analysis introduces a new framework, adapted from studies of probabilistic event attribution, to disentangle the relative importance of regional climate emergence and changing population dynamics in the exposure to future heat extremes across multiple densely populated regions in Southern Asia and Eastern Africa (SAEA). Our results reveal that, when population is kept at 2015 levels, exposure to heat considered severe in the present decade across SAEA will increase by a factor of 4.1 (2.4–9.6) and 15.8 (5.0–135) under a 1.5°- and 2.0°-warmer world, respectively. Furthermore, projected population changes by the end of the century under an SSP1 and SSP2 scenario can further exacerbate these changes by a factor of 1.2 (1.0–1.3) and 1.5 (1.3–1.7), respectively. However, a large fraction of this additional risk increase is not related to absolute increases in population, but instead attributed to changes in which regions exhibit continued population growth into the future. Further, this added impact of population redistribution will be twice as significant after 2.0 °C of warming, relative to stabilisation at 1.5 °C, due to the non-linearity of increases in heat exposure. Irrespective of the population scenario considered, continued African population expansion will place more people in locations where emergent changes to future heat extremes are exceptionally severe.

Excessive nitrogen (N) application and reduced nitrogen use efficiency (NUE) are the key reasons behind N notoriety worldwide, including in Pakistan. We estimated the changes in NUE of Pakistan by calculating the N budget of Pakistan's agriculture during the last 53 years (1961–2013). A more than ten-fold increase in N input (including N fertilizer, biological N fixation, manure, and atmospheric deposition) from 408 GgNyr⁻¹ (1961–1965) to 4636 GgNyr⁻¹ (2009–2013) highlights the fact that Pakistan is experiencing a massive expansion of N consumption. Significantly declining NUE (from 58% to 23%) and sharply increasing surplus N (171 GgNyr⁻¹ to 3581 GgNyr⁻¹) may cause N-related environment problems in the future if not handled immediately. Escalating gaseous N emissions of NH₃, N₂O, and NO (70, 10, and 1 GgNyr⁻¹ to 1023, 155, and 46 GgNyr⁻¹, respectively) is already posing a serious threat in terms of impaired air quality. There is a dire need to devise/adapt strategies and consistent policies for improving NUE, using proper management approaches at the grass root level and applying appropriate legislative measures for judicious N use as per crops requirements. Moreover, promotion of a balanced use of fertilizers would help in improving NUE in agriculture.

Exposure and vulnerability are the main contributing factors of growing impact from climate-related disasters globally. Understanding the spatiotemporal dynamic patterns of vulnerability is important for designing effective disaster risk mitigation and adaptation measures. At national scale, most cross-country studies have suggested that economic vulnerability to disasters decreases as income increases, especially for developing countries. Research covering sub-national climate-related natural disasters is indispensable to obtaining a comprehensive understanding of the effect of regional economic growth on vulnerability reduction. Taking China as a case, this subnational scale study shows that economic development is correlated with the significant reduction in human fatalities but increase in direct economic losses (DELs) from climate-related disasters since 1949. The long-term trend in climate-related disaster vulnerability, reflected by mortality (1978–2015) and DELs (1990–2015) as a share of the total population and Gross Domestic Product, has seen significant decline among all economic regions in China. While notable differences remain among its West, Central and East economic regions, the temporal vulnerability change has been converging. The study further demonstrated that economic development level is correlated with human and economic vulnerability to climate-related disasters, and this vulnerability decreased with the increase of per-capita income. This study suggested that economic development can have nuanced effects on overall human and economic vulnerability to climate-related disasters. We argue that climate change science needs to acknowledge and examine the different pathways of vulnerability effects related to economic development.

To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 °C above pre-industrial levels, with the ambition to keep warming to 1.5 °C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 °C versus 2.0 °C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 °C compared to 1.5 °C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security.

Anthropogenic heat flux is the heat generated by human activities in the urban canopy layer, which is considered the main contributor to the urban heat island (UHI). The UHI can in turn increase the use and energy consumption of air-conditioning systems. In this study, two effective methods for water-cooling air-conditioning systems in non-domestic areas, including the direct cooling system and central piped cooling towers (CPCTs), are physically based, parameterized, and implemented in a weather research and forecasting model at the city scale of Hong Kong. An extreme high temperature event (June 23–28, 2016) in the urban areas was examined, and we assessed the effects on the surface thermal environment, the interaction of sea–land breeze circulation and urban heat island circulation, boundary layer dynamics, and a possible reduction of energy consumption. The results showed that both water-cooled air-conditioning systems could reduce the 2 m air temperature by around 0.5 °C–0.8 °C during the daytime, and around 1.5 °C around 7:00–8:00 pm when the planetary boundary layer (PBL) height was confined to a few hundred meters. The CPCT contributed around 80%–90% latent heat flux and significantly increased the water vapor mixing ratio in the atmosphere by around 0.29 g kg⁻¹ on average. The implementation of the two alternative air-conditioning systems could modify the heat and momentum of turbulence, which inhibited the evolution of the PBL height (a reduction of 100–150 m), reduced the vertical mixing, presented lower horizontal wind speed and buoyant production of turbulent kinetic energy, and reduced the strength of sea breeze and UHI circulation, which in turn affected the removal of air pollutants. Moreover, the two alternative air-conditioning systems could significantly reduce the energy consumption by around 30% during extreme high temperature events. The results of this study suggest potential UHI mitigation strategies and can be extended to other megacities to enable them to be more resilient to UHI effects.

Reducing greenhouse gas (GHG) emissions from agriculture has become a critical target in national climate change policies. More than 80% of the countries in Sub-Saharan Africa (SSA) refer to the reduction of agricultural emissions, including livestock, in their nationally determined contribution (NDC) to mitigate climate change. The livestock sector in Kenya contributes largely to the gross domestic product and to GHG emissions from the land use sector. The government has recently pledged in its NDC to curb total GHG emissions by 30% by 2030. Quantifying and linking the mitigation potential of farm practices to national targets is required to support realistically the implementation of NDCs. Improvements in feed and manure management represent promising mitigation options for dairy production. This study aimed (i) to assess mitigation and food production benefits of feed and manure management scenarios, including land use changes covering Kenya's entire dairy production region and (ii) to analyse the contribution of these practices to national targets on milk production and mitigation, and their biophysical feasibility given the availability of arable land. The results indicate that improving forage quality by increasing the use of Napier grass and supplementing dairy concentrates supports Kenya's NDC target, reduces emission intensities by 26%–31%, partially achieves the national milk productivity target for 2030 by 38%–41%, and shows high feasibility given the availability of arable land. Covering manure heaps may reduce emissions from manure management by 68%. In contrast, including maize silage in cattle diets would not reduce emission intensities due to the risk of ten-fold higher emissions from the conversion of land required to grow additional maize. The shortage of arable land may render the implementation of these improved feed practices largely infeasible. This assessment provides the first quantitative estimates of the potential of feed intensification and manure management to mitigate GHG emissions and to increase milk yields at sectoral-level and at a high spatial resolution for an SSA country. The scientific evidence is tailored to support actual policy and decision-making processes at the national level, such as 'Nationally Appropriate Mitigation Actions'. Linking feed intensification and manure management strategies with spatially-explicit estimates of mitigation and food production to national targets may help the sector to access climate financing while contributing to food security.

The Tambora eruption (1815 AD) was one of the major eruptions of the last two millennia and has no equivalents over the last two centuries. Here, we collected an extensive network of early meteorological time series, climate simulation data and numerous, well-replicated proxy records from Eastern Canada to analyze the strength and the persistence of the Tambora impact on the regional climate and forest processes. Our results show that the Tambora impacts on the terrestrial biosphere were stronger than previously thought, and not only affected tree growth and carbon uptake for a longer period than registered in the regional climate, but also determined forest demography and structure. Increased tree mortality, four times higher than the background level, indicates that the Tambora climatic impact propagated to influence the structure of the North American taiga for several decades. We also show that the Tambora signal is more persistent in observed data (temperature, river ice dynamics, forest growth, tree mortality) than in simulated ones (climate and forest-growth simulations), indicating that our understanding of the mechanisms amplifying volcanic perturbations on climates and ecosystems is still limited, notably in the North American taiga.

Urban land in floodplains (ULF) is a vital component of flood exposure and its variations can cause changes in flood risk. In the context of rapid urbanization, ULF is expanding rapidly in China and imperiling societal sustainability. However, a national-scale analysis of ULF patterns and dynamics has yet to be conducted. Therefore, this study aims to investigate the spatiotemporal changes in China's ULF at different spatial scales (the country, region, basin, and sub-basin scales) from 1992–2015. We found that ULF accounted for 44.41% of the total urban land in China in 2015, which was 3.68 times greater than the proportion of floodplains relative to the total land area in China (12.06%). From 1992–2015, the ULF area increased by 26.43 × 10³ km², or 542.21%. Moreover, the ULF area is expected to grow by 16.89 × 10³ km² (53.38%) between 2015 and 2050. ULF growth was strongly associated with the flood occurrence in China, and continued growth will pose a considerable challenge to urban sustainability, particularly in basins with poor flood defenses. Greater attention should thus be paid to ULF dynamics in China.

This study measures the damages that surface ozone pollution causes within the Chinese agricultural sector under 2014 conditions. It also analyzes the agricultural benefits of ozone reductions. The analysis is done using a partial equilibrium model of China's agricultural sector. Results indicate that there are substantial, spatially differentiated damages that are greatest in ozone-sensitive crop growing areas with higher ozone concentrations. The estimated damage to China's agricultural sector range is between CNY 1.6 trillion and 2.2 trillion, which for comparison is about one fifth of 2014 agricultural revenue. When considering concentration reduction we find a 30% ozone reduction yields CNY 678 billion in sectoral benefits. These benefits largely fall to consumers with producers losing as the production gains lead to lower prices.

The effects of vertical wind shear (VWS) with different directions on tropical cyclone (TC) intensity change are compared in this statistical study based on TCs occurring between 1982 and 2015 over the western North Pacific (WNP). Results show that a westerly VWS has a much higher correlation (−0.36) with change in TC intensity than an easterly VWS (−0.07) over the WNP, especially south-westerly VWS (−0.43). Sea surface temperature (SST) is found to modulate the effect of VWS on TC intensity change as it has a close relationship with zonal VWS (−0.48). The favorable effect of SST, which increases with increase in easterly VWS, could offset the detrimental effect of VWS, leading to a relatively low correlation coefficient between easterly VWS and TC intensity change. By contrast, westerly VWS increases with decreasing SST, and the largest correlation coefficient appears when SST is around 301 K. Therefore, it is suggested that the direction of VWS as well as its value is taken into consideration in models used to predict TC intensity.

Civic engagement is one important way citizens can influence the rate of decarbonization in the electricity sector. However, motivating engagement can be challenging even if people are affected and interested in participating. Here we employed a randomized controlled trial to assess the effect of clean energy campaigns emphasizing cost savings, health, climate, or health and climate, or no additional information at all (control) on civic engagement behaviors (signing a petition or making a phone call). We targeted parents as they have been shown to be powerful agents of political and business practice change in other contexts, and hence, could play an important role in the decarbonization of the electricity sector. In Study 1, we recruited n = 292 parents already engaged in climate advocacy; in Study 2, we recruited a representative sample of n = 1254 parents drawn from the general public. Both studies were conducted in Michigan, Florida, and California, as these states have sizable advocacy group membership, divergent energy profiles, and strategic importance to the climate movement. In both studies, we find the odds of taking action are reduced by over 90% when participants are asked to make a phone call and leave a voicemail message, versus signing an online petition. Among the parents already engaged in advocacy, we observe a ceiling effect regarding attitudes towards clean energy and find the cost campaign produces unintended consequences. Among our public sample, we find that participants who believe the campaign to be credible and comprehendible are more likely to take action than those who discredit the campaign or do not understand its message. Additionally, we find parents who have children under the age of 18 negatively adjust their attitudes towards fossil fuels after being presented with health information. Ultimately, we find that campaign messages can influence energy attitudes and parents are willing to take action on the topic if the advocacy action seems like an effective approach.

This paper modeled the proximate determinants of rice outputs and groundwater depths in 27 Indian states during 1980–2010. Dynamic random effects models were estimated by maximum likelihood at state and well levels. The main findings from models for rice outputs were that temperatures and rainfall levels were significant predictors, and the relationships were quadratic with respect to rainfall. Moreover, nonlinearities with respect to population changes indicated greater rice production with population increases. Second, groundwater depths were positively associated with temperatures and negatively with rainfall levels and there were nonlinear effects of population changes. Third, dynamic models for in situ groundwater depths in 11 795 wells in mainly unconfined aquifers, accounting for latitudes, longitudes and altitudes, showed steady depletion. Overall, the results indicated that population pressures on food production and environment need to be tackled via long-term healthcare, agricultural, and groundwater recharge policies in India.

Past attempts to estimate rainfall-driven flood risk across the US either have incomplete coverage, coarse resolution or use overly simplified models of the flooding process. In this paper, we use a new 30 m resolution model of the entire conterminous US with a 2D representation of flood physics to produce estimates of flood hazard, which match to within 90% accuracy the skill of local models built with detailed data. These flood depths are combined with exposure datasets of commensurate resolution to calculate current and future flood risk. Our data show that the total US population exposed to serious flooding is 2.6–3.1 times higher than previous estimates, and that nearly 41 million Americans live within the 1% annual exceedance probability floodplain (compared to only 13 million when calculated using FEMA flood maps). We find that population and GDP growth alone are expected to lead to significant future increases in exposure, and this change may be exacerbated in the future by climate change.

Mobilization of soil/sediment organic carbon into inland waters constitutes a substantial, but poorly-constrained, component of the global carbon cycle. Radiocarbon (¹⁴C) analysis has proven a valuable tool in tracing the sources and fate of mobilized carbon, but aquatic ¹⁴C studies in permafrost regions rarely detect 'old' carbon (assimilated from the atmosphere into plants and soil prior to AD1950). The emission of greenhouse gases derived from old carbon by aquatic systems may indicate that carbon sequestered prior to AD1950 is being destabilized, thus contributing to the 'permafrost carbon feedback' (PCF). Here, we measure directly the ¹⁴C content of aquatic CO₂, alongside dissolved organic carbon, in headwater systems of the western Canadian Arctic—the first such concurrent measurements in the Arctic. Age distribution analysis indicates that the age of mobilized aquatic carbon increased significantly during the 2014 snow-free season as the active layer deepened. This increase in age was more pronounced in DOC, rising from 101–228 years before sampling date (a 120%–125% increase) compared to CO₂, which rose from 92–151 years before sampling date (a 59%–63% increase). 'Pre-industrial' aged carbon (assimilated prior to ~AD1750) comprised 15%–40% of the total aquatic carbon fluxes, demonstrating the prevalence of old carbon to Arctic headwaters. Although the presence of this old carbon is not necessarily indicative of a net positive PCF, we provide an approach and baseline data which can be used for future assessment of the PCF.

The extent of wildfires in the western United States is increasing, but how land ownership, firefighting, and reserve status influence fire probability is unclear. California serves as a unique natural experiment to estimate the impact of these factors, as ownership is split equally between federal and non-federal landowners; there is a relatively large proportion of reserved lands where extractive uses are prohibited and fire suppression is limited; and land ownership and firefighting responsibility are purposefully not always aligned. Panel Poisson regression techniques and pre-regression matching were used to model changes in annual fire probability from 1950–2015 on reserve and non-reserve lands on federal and non-federal ownerships across four vegetation types: forests, rangelands, shrublands, and forests without commercial species. Fire probability was found to have increased over time across all 32 categories. A marginal effects analysis showed that federal ownership and firefighting was associated with increased fire probability, and that the difference in fire probability on federal versus non-federal lands is increasing over time. Ownership, firefighting, and reserve status, played roughly equal roles in determining fire probability, and were found to have much greater influence than average maximum temperature (°C) during summer months (June, July, August), average annual precipitation (cm), and average annual topsoil moisture content by volume, demonstrating the critical role these factors play in western fire regimes and the importance of including them in future analysis focused on understanding and predicting wildfire in the Western United States.

South Asia (SA) has been considered one of the most remarkable regions for changing vegetation greenness, accompanying its major expansion of agricultural activities, especially irrigated farming. The influence of the monsoon climate on the seasonal trends and anomalies of vegetation greenness is poorly understood in this area. Herein, we used the satellite-based Normalized Difference Vegetation Index (NDVI) to investigate various spatiotemporal patterns in vegetation activity during summer and winter monsoon (SM and WM) seasons and among irrigated croplands (IC), rainfed croplands (RC), and natural vegetation (NV) areas during 1982–2013. Seasonal NDVI variations with climatic factors (precipitation and temperature) and land use and cover changes (LUCC) have also been investigated. This study demonstrates that the seasonal dynamics of vegetation could improve the detailed understanding of vegetation productivity over the region. We found distinct greenness trends between two monsoon seasons and among the major land use/cover classes. Winter monsoons contributed greater variability to the overall vegetation dynamics of SA. Major greening occurred due to the increased productivity over irrigated croplands during the winter monsoon season; meanwhile, browning trends were prominent over NV areas during the same season. Maximum temperatures had been increasing tremendously during the WM season; however, the precipitation trend was not significant over SA. Both the climate variability and LUCC revealed coupled effects on the long term NDVI trends in NV areas, especially in the hilly regions, whereas anthropogenic activities (agricultural advancements) played a pivotal role in the rest of the area. Until now, advanced cultivation techniques have proven to be beneficial for the region in terms of the productivity of croplands. However, the crop productivity is at risk under climate change.

Mountain forests provide the main water resources and lumber for Northwest China. The understanding of the differences in forests growing among individual slope aspects in mountainous regions is of great significance to the wise management and planning of these natural systems. The aim of this study was to investigate the impacts of slope aspect on forest dynamic succession in Northwest China by using the dynamic forest succession model (FAREAST).

First, the simulated forest composition and vertical forest zonation produced by the model were compared against recorded data in three sub-regions of the Altai Mountains. The FAREAST model accurately reproduced the vertical zonation, forest composition, growth curves of the dominant species (Larix sibirica), and forest biomass in the Altai Mountains. Transitions along the forest zones of the Altai Mountains averaged about a 400 m difference between the northern and southern sites. Biomass for forests on north-facing slopes were 11.0, 15.3 and 55.9 t C ha⁻¹ higher than for south-facing slopes in the Northeast, Central and Southeast sub-regions, respectively.

Second, our analyses showed that the FAREAST model can be used to predict dynamic forest succession in Northwest China under the influence of slope and aspect. In the Altai Mountains, the north-facing slopes supported the best forest growth, followed by the west- and east-facing slopes. South-facing slopes consistently exhibited the lowest growth, biomass storage and forest diversity.

The Western Siberian Lowlands (WSL) store large quantities of organic carbon that will be exposed and mobilized by the thawing of permafrost. The fate of mobilized carbon, however, is not well understood, partly because of inadequate knowledge of hydrological controls in the region which has a vast low-relief surface area, extensive lake and wetland coverage and gradually increasing permafrost influence. We used stable water isotopes to improve our understanding of dominant landscape controls on the hydrology of the WSL. We sampled rivers along a 1700 km South–North transect from permafrost-free to continuous permafrost repeatedly over three years, and derived isotope proxies for catchment hydrological responsiveness and connectivity. We found correlations between the isotope proxies and catchment characteristics, suggesting that lakes and wetlands are intimately connected to rivers, and that permafrost increases the responsiveness of the catchment to rainfall and snowmelt events, reducing catchment mean transit times. Our work provides rare isotope-based field evidence that permafrost and lakes/wetlands influence hydrological pathways across a wide range of spatial scales (10–10⁵ km²) and permafrost coverage (0%–70%). This has important implications, because both permafrost extent and lake/wetland coverage are affected by permafrost thaw in the changing climate. Changes in these hydrological landscape controls are likely to alter carbon export and emission via inland waters, which may be of global significance.

Short-term forecasts of vegetation activity are currently not well constrained due largely to our lack of understanding of coupled climate-vegetation dynamics mediated by complex interactions between atmospheric teleconnection patterns. Using ecoregion-scale estimates of North American vegetation activity inferred from remote sensing (1982–2015), we examined seasonal and spatial relationships between land surface phenology and the atmospheric components of five teleconnection patterns over the tropical Pacific, north Pacific, and north Atlantic. Using a set of regression experiments, we also tested for interactions among these teleconnection patterns and assessed predictability of vegetation activity solely based on knowledge of atmospheric teleconnection indices. Autumn-to-winter composites of the Southern Oscillation Index (SOI) were strongly correlated with start of growing season timing, especially in the Pacific Northwest. The two leading modes of north Pacific variability (the Pacific-North American, PNA, and West Pacific patterns) were significantly correlated with start of growing season timing across much of southern Canada and the upper Great Lakes. Regression models based on these Pacific teleconnections were skillful predictors of spring phenology across an east-west swath of temperate and boreal North America, between 40°N–60°N. While the North Atlantic Oscillation (NAO) was not strongly correlated with start of growing season timing on its own, we found compelling evidence of widespread NAO-SOI and NAO-PNA interaction effects. These results suggest that knowledge of atmospheric conditions over the Pacific and Atlantic Oceans increases the predictability of North American spring phenology. A more robust consideration of the complexity of the atmospheric circulation system, including interactions across multiple ocean basins, is an important step towards accurate forecasts of vegetation activity.

The Mekong River Basin in Southeast Asia is undergoing extensive hydropower development, but the magnitudes of related greenhouse gas emissions (GHG) are not well known. We provide the first screening of GHG emissions of 141 existing and planned reservoirs in the basin, with a focus on atmospheric gross emissions through the reservoir water surface. The emissions were estimated using statistical models that are based on global emission measurements. The hydropower reservoirs (119) were found to have an emission range of 0.2–1994 kg CO₂e MWh⁻¹ over a 100 year lifetime with a median of 26 kg CO₂e MWh⁻¹. Hydropower reservoirs facilitating irrigation (22) had generally higher emissions reaching over 22 000 kg CO₂e MWh⁻¹. The emission fluxes for all reservoirs (141) had a range of 26–1813 000 t CO₂e yr⁻¹ over a 100 year lifetime with a median of 28 000 t CO₂e yr⁻¹. Altogether, 82% of hydropower reservoirs (119) and 45% of reservoirs also facilitating irrigation (22) have emissions comparable to other renewable energy sources (<190 kg CO₂e MWh⁻¹), while the rest have higher emissions equalling even the emission from fossil fuel power plants (>380 kg CO₂e MWh⁻¹). These results are tentative and they suggest that hydropower in the Mekong Region cannot be considered categorically as low-emission energy. Instead, the GHG emissions of hydropower should be carefully considered case-by-case together with the other impacts on the natural and social environment.

Sustainable intensification is an emerging model for agriculture designed to reconcile accelerating global demand for agricultural products with long-term environmental stewardship. Defined here as increasing agricultural production while maintaining or improving environmental quality, sustainable intensification hinges upon decision-making by agricultural producers, consumers, and policy-makers. The Long-Term Agroecosystem Research (LTAR) network was established to inform these decisions. Here we introduce the LTAR Common Experiment, through which scientists and partnering producers in US croplands, rangelands, and pasturelands are conducting 21 independent but coordinated experiments. Each local effort compares the outcomes of a predominant, conventional production system in the region ('business as usual') with a system hypothesized to advance sustainable intensification ('aspirational'). Following the logic of a conceptual model of interactions between agriculture, economics, society, and the environment, we identified commonalities among the 21 experiments in terms of (a) concerns about business-as-usual production, (b) 'aspirational outcomes' motivating research into alternatives, (c) strategies for achieving the outcomes, (d) practices that support the strategies, and (e) relationships between practice outreach and adoption. Network-wide, concerns about business as usual include the costs of inputs, opportunities lost to uniform management approaches, and vulnerability to accelerating environmental changes. Motivated by environmental, economic, and societal outcomes, scientists and partnering producers are investigating 15 practices in aspirational treatments to sustainably intensify agriculture, from crop diversification to ecological restoration. Collectively, the aspirational treatments reveal four general strategies for sustainable intensification: (1) reducing reliance on inputs through ecological intensification, (2) diversifying management to match land and economic potential, (3) building adaptive capacity to accelerating environmental changes, and (4) managing agricultural landscapes for multiple ecosystem services. Key to understanding the potential of these practices and strategies are informational, economic, and social factors—and trade-offs among them—that limit their adoption. LTAR is evaluating several actions for overcoming these barriers, including finding financial mechanisms to make aspirational production systems more profitable, resolving uncertainties about trade-offs, and building collaborative capacity among agricultural producers, stakeholders, and scientists from a broad range of disciplines.

Water scarcity is a global concern that necessitates a global perspective, but it is also the product of multiple regional issues that require regional solutions. Water markets constitute a regionally applicable non-structural measure to counter water scarcity that has received the attention of academics and policy-makers, but there is no global view on their applicability. We present the global distribution of potential nations and states where water markets could be instituted in a legal sense, by investigating 296 water laws internationally, with special reference to a minimum set of key rules: legalization of water reallocation, the separation of water rights and landownership, and the modification of the cancellation rule for non-use. We also suggest two additional globally distributed prerequisites and policy implications: the predictability of the available water before irrigation periods and public control of groundwater pumping throughout its jurisdiction.

Thermal pollution from power plants degrades riverine ecosystems with ramifications beyond the natural environment as it affects power supply. The transport of thermal effluents along river reaches may lead to plant-to-plant interferences by elevating condenser inlet temperatures at downstream locations, which lower thermal efficiencies and trigger regulatory-forced power curtailments. We evaluate thermal pollution impacts on rivers and power supply across 128 plants with once-through cooling technologies in the Mississippi River watershed. By leveraging river network topologies with higher resolutions (0.05°) than previous studies, we reveal the need to address the issue in a more spatially resolved manner, capable of uncovering diverse impacts across individual plants, river reaches and sub-basins. Results show that the use of coarse river network resolutions may lead to substantial overestimations in magnitude and length of impaired river reaches. Overall, there is a modest limitation on power production due to thermal pollution, given existing infrastructure, regulatory and climate conditions. However, tradeoffs between thermal pollution and electricity generation show important implications for the role of alternative cooling technologies and environmental regulation under current and future climates. Recirculating cooling technologies may nearly eliminate thermal pollution and improve power system reliability under stressed climate-water conditions. Regulatory limits also reduce thermal pollution, but at the expense of significant reductions in electricity generation capacity. However, results show several instances when power production capacity rises at individual plants when regulatory limits reduce upstream thermal pollution. These dynamics across energy-water systems highlight the need for high-resolution simulations and the value of coherent planning and optimization across infrastructure with mutual dependencies on natural resources to overcome climate-water constraints on productivity and bring to fruition energy and environmental win-win opportunities.

The Nationally Determined Contributions are allowing countries to examine options for reducing emissions through a range of domestic policies. India, like many developing countries, has committed to reducing emissions through specific policies, including building energy codes. Here we assess the potential of these sectoral policies to help in achieving mitigation targets. Collectively, it is critically important to see the potential impact of such policies across developing countries in meeting national and global emission goals.

Buildings accounted for around one third of global final energy use in 2010, and building energy consumption is expected to increase as income grows in developing countries. Using the Global Change Assessment Model, this study finds that implementing a range of energy efficiency policies robustly can reduce total Indian building energy use by 22% and lower total Indian carbon dioxide emissions by 9% in 2050 compared to the business-as-usual scenario. Among various policies, energy codes for new buildings can result in the most significant savings. For all building energy policies, well-coordinated, consistent implementation is critical, which requires coordination across different departments and agencies, improving capacity of stakeholders, and developing appropriate institutions to facilitate policy implementation.

Skin cancer mortality resulting from stratospheric ozone depletion has been widely studied. Similarly, there is a deep body of literature on surface ozone and its health impacts, with modeling and observational studies demonstrating that surface ozone concentrations can be increased when stratospheric air mixes to the Earth's surface. We offer the first quantitative estimate of the trade-off between these two effects, comparing surface air quality benefits and UV-related harms from stratospheric ozone depletion. Applying an idealized ozone loss term in the stratosphere of a chemistry-transport model for modern-day conditions, we find that each Dobson unit of stratospheric ozone depletion results in a net decrease in the global annual mortality rate of ~40 premature deaths per billion population (d/bn/DU). The impacts are spatially heterogeneous in sign and magnitude, composed of a reduction in premature mortality rate due to ozone exposure of ~80 d/bn/DU concentrated in Southeast Asia, and an increase in skin cancer mortality rate of ~40 d/bn/DU, mostly in Western Europe. This is the first study to quantify air quality benefits of stratospheric ozone depletion, and the first to find that marginal decreases in stratospheric ozone around modern-day values could result in a net reduction in global mortality due to competing health impact pathways. This result, which is subject to significant methodological uncertainty, highlights the need to understand the health and environmental trade-offs involved in policy decisions regarding anthropogenic influences on ozone chemistry over the 21st century.

This study uses daily precipitation records from 517 Russian stations (1966–2010) to examine the relationships between continuous dry and wet day duration and surface air temperature for all four seasons. The study found that both mean and extreme durations of dry periods increase with air temperature at about 7.0% (0.24 day/°C) and 7.7% (0.86 day/°C) respectively, while those of wet periods decrease at about 1.3% (−0.02 day/°C) and 2.2% (−0.10 day/°C) respectively averaged over the entire study region during summer. An increase in the duration of dry periods with higher air temperature is also found in other seasons at locations with a mean seasonal air temperature of about −5 °C or higher. Opposite relationships of shorter durations of dry periods and longer wet periods associated with higher air temperature are observed over the northern part of the study region in winter. The changes in durations of both dry and wet periods have significant correlations with the changes in total dry and wet days but are about 2.5 times higher for dry periods and 0.5 times lower for wet periods. The study also found that locations with longer durations of dry periods experience faster rates of increase in air temperature, suggesting the likelihood of exacerbating drought severity in drier and/or warmer locations for all seasons.

Global models of biophysical suitability for oil palm consistently rank Brazil as having the greatest potential for expansion, with estimates as high as 238 Mha of suitable lands. In 2010, Brazil launched the Sustainable Palm Oil Production Program (SPOPP) to incentivize oil palm development without deforestation on as much as 30 Mha. Here we examine oil palm expansion before and after the SPOPP's launch. In Pará, the major oil palm producing state in Brazil, we analyze the extent and change in oil palm cultivation from 2006−2014 using satellite imagery, ground-truthed verification, site-based interviews, and rural environmental (land) registration data. Between 2006−2014, oil palm area (≥9 ha) expanded >200% to ~219 000 ha. Of the ~148 000 ha of oil palm developed, ~91% converted pasturelands while ~8% replaced natural vegetation, including intact and secondary forests. Although >80% of all oil palm parcels rest <0.5 km from intact forests, direct conversion of intact forests declined from ~4% pre-SPOPP (2006−2010) to <1% post-SPOPP (2010−2014).

Despite low and declining deforestation rates associated with oil palm expansion in Pará, our results also show a low area of oil palm development overall compared with reported land suitability. To explore potential contributing factors, we conducted semi-structured interviews with researchers, company representatives, and government officials involved in the sector to characterize the perceived factors influencing oil palm development and the role of agro-ecological suitability mapping among them. Interviews indicated that: (1) individual effects of suitability mapping efforts to encourage oil palm expansion on cleared areas, i.e. without deforestation, cannot be disentangled from pre-existing public and private deforestation reduction initiatives; and, (2) socio-economic constraints, e.g. high relative production costs and limited familiarity with this crop, appear to partially explain the major discrepancy between estimated potential suitable areas with realized oil palm development.

China has emerged as the global manufacturing center for solar photovoltaic (PV) products. Chinese firms have entered all stages of the supply chain, producing most of the installed solar modules around the world. Meanwhile, production costs are at record lows. The decisions that Chinese solar producers make today will influence the path for the solar industry and its role towards de-carbonization of global energy systems in the years to come. However, to date, there have been no assessments of the future costs and efficiency of solar PV systems produced by the Chinese PV industry. We perform an expert elicitation to assess the technological and non-technological factors that led to the success of China's silicon PV industry as well as likely future costs and performance. Experts evaluated key metrics such as efficiency, costs, and commercial viability of 17 silicon and non-silicon solar PV technologies by 2030. Silicon-based technologies will continue to be the mainstream product for large-scale electricity generation application in the near future, with module efficiency reaching as high as 23% and production cost as low as $0.24/W. The levelized cost of electricity for solar will be around $34/MWh, allowing solar PV to be competitive with traditional energy resources like coal. The industry's future developments may be affected by overinvestment, overcapacity, and singular short-term focus.

Carbon budgets provide a useful tool for policymakers to help meet the global climate targets, as they specify total allowable carbon emissions consistent with limiting warming to a given temperature threshold. Non-CO₂ forcings have a net warming effect in the Representative Concentration Pathways (RCP) scenarios, leading to reductions in remaining carbon budgets based on CO₂ forcing alone. Carbon budgets consistent with limiting warming to below 2.0 °C, with and without accounting for the effects of non-CO₂ forcings, were assessed in inconsistent ways by the Intergovernmental Panel on Climate Change (IPCC), making the effects of non-CO₂ forcings hard to identify. Here we use a consistent approach to compare 1.5 °C and 2.0 °C carbon budgets with and without accounting for the effects of non-CO₂ forcings, using CO₂-only and RCP8.5 simulations. The median allowable carbon budgets for 1.5 °C and 2.0 °C warming are reduced by 257 PgC and 418 PgC, respectively, and the uncertainty ranges on the budgets are reduced by more than a factor of two when accounting for the net warming effects of non-CO₂ forcings. While our overall results are consistent with IPCC, we use a more robust methodology, and explain the narrower uncertainty ranges of carbon budgets when non-CO₂ forcings are included. We demonstrate that most of the reduction in carbon budgets is a result of the direct warming effect of the non-CO₂ forcings, with a secondary contribution from the influence of the non-CO₂ forcings on the carbon cycle. Such carbon budgets are expected to play an increasingly important role in climate change mitigation, thus understanding the influence of non-CO₂ forcings on these budgets and their uncertainties is critical.

Sea-level rise (SLR) is magnifying the frequency and severity of extreme sea levels (ESLs) that can cause coastal flooding. The rate and amount of global mean sea-level (GMSL) rise is a function of the trajectory of global mean surface temperature (GMST). Therefore, temperature stabilization targets (e.g. 1.5 °C and 2.0 °C of warming above pre-industrial levels, as from the Paris Agreement) have important implications for coastal flood risk. Here, we assess, in a global network of tide gauges, the differences in the expected frequencies of ESLs between scenarios that stabilize GMST warming at 1.5 °C, 2.0 °C, and 2.5 °C above pre-industrial levels. We employ probabilistic, localized SLR projections and long-term hourly tide gauge records to estimate the expected frequencies of historical and future ESLs for the 21st and 22nd centuries. By 2100, under 1.5 °C, 2.0 °C, and 2.5 °C GMST stabilization, the median GMSL is projected to rise 48 cm (90% probability of 28–82 cm), 56 cm (28–96 cm), and 58 cm (37–93 cm), respectively. As an independent comparison, a semi-empirical sea level model calibrated to temperature and GMSL over the past two millennia estimates median GMSL rise within 7–8 cm of these projections. By 2150, relative to the 2.0 °C scenario and based on median sea level projections, GMST stabilization of 1.5 °C spares the inundation of lands currently home to about 5 million people, including 60 000 individuals currently residing in Small Island Developing States. We quantify projected changes to the expected frequency of historical 10-, 100-, and 500-year ESL events using frequency amplification factors that incorporate uncertainty in both local SLR and historical return periods of ESLs. By 2150, relative to a 2.0 °C scenario, the reduction in the frequency amplification of the historical 100 year ESL event arising from a 1.5 °C GMST stabilization is greatest in the eastern United States, with ESL event frequency amplification being reduced by about half at most tide gauges. In general, smaller reductions are projected for Small Island Developing States.

Very few annually resolved millennial-length temperature reconstructions exist for the Southern Hemisphere. Here we present four 979-year reconstructions for southeastern Australia for the austral summer months of December–February. Two of the reconstructions are based on the Australian Water Availability Project dataset and two on the Berkeley Earth Surface Temperature dataset. For each climate data set, one reconstruction is based solely on Lagarostrobos franklinii (restricted reconstructions) while the other is based on multiple Tasmanian conifer species (unrestricted reconstructions). Each reconstruction calibrates ~50−60% of the variance in the temperature datasets depending on the number of tree-ring records available for the reconstruction. We found little difference in the temporal variability of the reconstructions, although extremes are amplified in the restricted reconstructions relative to the unrestricted reconstructions. The reconstructions highlight the occurrence of numerous individual years, especially in the 15th−17th Centuries, for which temperatures were comparable with those of the late 20th Century. The 1950−1999 period, however, stands out as the warmest 50-year period on average for the past 979 years, with a sustained shift away from relatively low mean temperatures, the length of which is unique in the 979-year record. The reconstructions are strongly and positively related to temperatures across the southeast of the Australian continent, negatively related to temperatures in the north and northeast of the continent, and uncorrelated with temperatures in the west. The lack of a strong relationship with temperatures across the continent highlights the necessity of a sub-regional focus for Australasian temperature reconstructions.

Drought monitoring and early warning (M&EW) systems are an important component of agriculture/silviculture drought risk assessment. Many operational information systems rely mostly on meteorological indicators, and a few incorporate vegetation state information. However, the relationships between meteorological drought indicators and agricultural/silvicultural drought impacts vary across Europe. The details of this variability have not been elucidated sufficiently on a continental scale in Europe to inform drought risk management at administrative scales. The objective of this study is to fill this gap and evaluate how useful the variety of meteorological indicators are to assess agricultural/silvicultural drought across Europe. The first part of the analysis systematically linked meteorological drought indicators to remote sensing based vegetation indices (VIs) for Europe at NUTs3 administrative regions scale using correlation analysis for crops and forests. In a second step, a stepwise multiple linear regression model was deployed to identify variables explaining the spatial differences observed. Finally, corn crop yield in Germany was chosen as a case study to verify VIs' representativeness of agricultural drought impacts. Results show that short accumulation periods of SPI and SPEI are best linked to crop vegetation stress in most cases, which further validates the use of SPI3 in existing operational drought monitors. However, large regional differences in correlations are also revealed. Climate (temperature and precipitation) explained the largest proportion of variance, suggesting that meteorological indices are less informative of agricultural/silvicultural drought in colder/wetter parts of Europe. These findings provide important context for interpreting meteorological indices on widely used national to continental M&EW systems, leading to a better understanding of where/when such M&EW tools can be indicative of likely agricultural stress and impacts.

Climate mitigation requires emissions to peak then decline within two decades, but many mitigation models include 100 EJ or more of bioenergy, ignoring emissions from biomass oxidation. Treatment of bioenergy as 'low carbon' or carbon neutral often assumes fuels are agricultural or forestry residues that will decompose and emit CO₂ if not burned for energy. However, for 'low carbon' assumptions about residues to be reasonable, two conditions must be met: biomass must genuinely be material left over from some other process; and cumulative net emissions, the additional CO₂ emitted by burning biomass compared to its alternative fate, must be low or negligible in a timeframe meaningful for climate mitigation. This study assesses biomass use and net emissions from the US bioenergy and wood pellet manufacturing sectors. It defines the ratio of cumulative net emissions to combustion, manufacturing and transport emissions as the net emissions impact (NEI), and evaluates the NEI at year 10 and beyond for a variety of scenarios. The analysis indicates the US industrial bioenergy sector mostly burns black liquor and has an NEI of 20% at year 10, while the NEI for plants burning forest residues ranges from 41%–95%. Wood pellets have a NEI of 55%–79% at year 10, with net CO₂ emissions of 14–20 tonnes for every tonne of pellets; by year 40, the NEI is 26%–54%. Net emissions may be ten times higher at year 40 if whole trees are harvested for feedstock. Projected global pellet use would generate around 1% of world bioenergy with cumulative net emissions of 2 Gt of CO₂ by 2050. Using the NEI to weight biogenic CO₂ for inclusion in carbon trading programs and to qualify bioenergy for renewable energy subsidies would reduce emissions more effectively than the current assumption of carbon neutrality.

Arctic tundra is becoming greener and shrubbier due to recent warming. This is impacting climate feedbacks and wildlife, yet the spatial distribution of plant biomass in tundra ecosystems is uncertain. In this study, we mapped plant and shrub above-ground biomass (AGB; kg m⁻²) and shrub dominance (%; shrub AGB/plant AGB) across the North Slope of Alaska by linking biomass harvests at 28 field sites with 30 m resolution Landsat satellite imagery. We first developed regression models (p < 0.01) to predict plant AGB (r² = 0.79) and shrub AGB (r² = 0.82) based on the normalized difference vegetation index (NDVI) derived from imagery acquired by Landsat 5 and 7. We then predicted regional plant and shrub AGB by combining these regression models with a regional Landsat NDVI mosaic built from 1721 summer scenes acquired between 2007 and 2016. Our approach employed a Monte Carlo uncertainty analysis that propagated sampling and sensor calibration errors. We estimated that plant AGB averaged 0.74 (0.60, 0.88) kg m⁻² (95% CI) and totaled 112 (91, 135) Tg across the region, with shrub AGB accounting for ~43% of regional plant AGB. The new maps capture landscape variation in plant AGB visible in high resolution satellite and aerial imagery, notably shrubby riparian corridors. Modeled shrub AGB was strongly correlated with field measurements of shrub canopy height at 25 sites (r_s = 0.88) and with a regional map of shrub cover (r_s = 0.76). Modeled plant AGB and shrub dominance were higher in shrub tundra than graminoid tundra and increased between areas with the coldest and warmest summer air temperatures, underscoring the fact that future warming has the potential to greatly increase plant AGB and shrub dominance in this region. These new biomass maps provide a unique source of ecological information for a region undergoing rapid environmental change.

The Paris Agreement of the United Nation Framework Convention on Climate Change calls for a balance of anthropogenic greenhouse emissions and removals in the latter part of this century. Mexico indicated in its Intended Nationally Determined Contribution and its Climate Change Mid-Century Strategy that the land sector will contribute to meeting GHG emission reduction goals. Since 2012, the Mexican government through its National Forestry Commission, with international financial and technical support, has been developing carbon dynamics models to explore climate change mitigation options in the forest sector. Following a systems approach, here we assess the biophysical mitigation potential of forest ecosystems, harvested wood products and their substitution benefits (i.e. the change in emissions resulting from substitution of wood for more emissions-intensive products and fossil fuels), for policy alternatives considered by the Mexican government, such as a net zero deforestation rate and sustainable forest management. We used available analytical frameworks (Carbon Budget Model of the Canadian Forest Sector and a harvested wood products model), parameterized with local input data in two contrasting Mexican states. Using information from the National Forest Monitoring System (e.g. forest inventories, remote sensing, disturbance data), we demonstrate that activities aimed at reaching a net-zero deforestation rate can yield significant CO₂e mitigation benefits by 2030 and 2050 relative to a baseline scenario ('business as usual'), but if combined with increasing forest harvest to produce long-lived products and substitute more energy-intensive materials, emissions reductions could also provide other co-benefits (e.g. jobs, illegal logging reduction). We concluded that the relative impact of mitigation activities is locally dependent, suggesting that mitigation strategies should be designed and implemented at sub-national scales. We were also encouraged about the ability of the modeling framework to effectively use Mexico's data, and showed the need to include multiple sectors and types of collaborators (scientific and policy-maker communities) to design more comprehensive portfolios for climate change mitigation.

Projected changes of the thermal growing season (TGS) over Northern Eurasia at 1.5 °C and 2 °C global warming levels are investigated using 22 CMIP5 models under both RCP4.5 and RCP8.5 scenarios. The multi-model mean projections indicate Northern Eurasia will experience extended and intensified TGSs in a warmer world. The prolongation of TGSs under 1.5 °C and 2 °C warming is attributed to both earlier onset and later termination, with the latter factor playing a dominating role. Interestingly, earlier onset is of greater importance under RCP4.5 than under RCP8.5 in prolonging TGS as the world warms by an additional 0.5 °C. Under both RCPs, growing degree day sum (GDD) above 5 °C is anticipated to increase by 0 °C–450 °C days and 0 °C–650 °C days over Northern Eurasia at 1.5 °C and 2 °C warming, respectively. However, effective GDD (EGDD) which accumulates optimum temperature for the growth of wheat, exhibits a decline in the south of Central Asia under warmer climates. Therefore, for wheat production over Northern Eurasia, adverse effects incurred by scorching temperatures and resultant inadequacy in water availability may counteract benefits from lengthening and warming TGS. In response to a future 1.5 °C and 2 °C warmer world, proper management and scientifically-tailored adaptation are imperative to optimize local-regional agricultural production.

Warming in the boreal forest region has already led to changes in the fire regime. This may result in increasing fire frequency or severity in peatlands, which could cause these ecosystems to shift from a net sink of carbon (C) to a net source of C to the atmosphere. Similar to C cycling, peatlands serve as a net sink for mercury (Hg), which binds strongly to organic matter and accumulates in peat over time. This stored Hg is also susceptible to re-release to the atmosphere during peat fires. Here we investigate the physical properties that influence depth of burn in experimental peat columns and the resulting emissions of CO, CO₂, CH₄, and gaseous and particulate Hg. As expected, bulk density and soil moisture content were important controls on depth of burn, CO₂ emissions, and CO emissions. However, our results show that CH₄ and Hg emissions are insensitive to combustion temperature or fuel moisture content. Emissions during the burning of peat, across a wide range of moisture conditions, were associated with low particulate Hg and high gaseous Hg release. Due to strong correlations between total Hg and CO emissions and because high Hg emissions occurred despite incomplete combustion of total C, our results suggest that Hg release during peat burning is governed by the thermodynamics of Hg reduction more so than by the release of Hg associated with peat combustion. Our measured emissions ratios, particularly for CH₄:CO₂, are higher than values typically used in the upscaling of boreal forest or peatland fire emissions. These emission ratios have important implications not only for our understanding of smouldering chemistry, but also for potential influences of peat fires on the Earth's climate system.

The mid-depth temperature maximum (TeM) was measured in an estuarine Bol'shoi Vilyui Lake (Kamchatka peninsula, Russia) in summer 2015. We applied 1D k–ε model LAKE to the case, and found it successfully simulating the phenomenon. We argue that the main prerequisite for mid-depth TeM development is a salinity increase below the freshwater mixed layer, sharp enough in order to increase the temperature with depth not to cause convective mixing and double diffusion there. Given that this condition is satisfied, the TeM magnitude is controlled by physical factors which we identified as: radiation absorption below the mixed layer, mixed-layer temperature dynamics, vertical heat conduction and water-sediments heat exchange. In addition to these, we formulate the mechanism of temperature maximum 'pumping', resulting from the phase shift between diurnal cycles of mixed-layer depth and temperature maximum magnitude. Based on the LAKE model results we quantify the contribution of the above listed mechanisms and find their individual significance highly sensitive to water turbidity. Relying on physical mechanisms identified we define environmental conditions favouring the summertime TeM development in salinity-stratified lakes as: small-mixed layer depth (roughly, ~< 2 m), transparent water, daytime maximum of wind and cloudless weather. We exemplify the effect of mixed-layer depth on TeM by a set of selected lakes.

Woodfuels constitute nearly 80% of Haiti's primary energy supply. Forests are severely degraded and the nation has long been considered an archetypal case of woodfuel-driven deforestation. However, there is little empirical evidence that woodfuel demand directly contributes to deforestation, but may contribute to degradation. We use MoFuSS (Modeling Fuelwood Sustainability Scenarios), a dynamic landscape model, to assess whether current woodfuel demand is as impactful as it is often depicted by simulating changes in land cover that would result if current demand continues unabated. We also simulate several near-term interventions focused on woodfuel demand reduction to analyze the land cover impacts of different energy trajectories. We find that current demand may contribute to moderate levels of degradation, but it is not as severe as is typically portrayed. Under a business-as-usual scenario, the simulated regenerative capacity of woody biomass is insufficient to meet Haiti's increasing demand for wood energy and, as a result, between 2017 and 2027 stocks of above-ground (woody) biomass could decline by 4% ± 1%. This is an annual loss of 302 ± 29 kton of wood and would emit 555 ± 54 kton CO₂ yr⁻¹. Aggressive interventions to reduce woodfuel demand could slow or even reverse woodfuel-driven degradation, allowing woody biomass to recover in some regions. We discuss the policy implications and propose steps to reduce uncertainty and validate the model.

Tropical Dry Forests (TDFs) have been broadly converted into pastures and crops, with direct consequences to biodiversity, ecosystem services, and social welfare. Such land use and cover changes (LUCC) usually are strongly influenced by government environmental and development policies. The present study aimed at analyzing LUCC in Brazilian TDFs between 2000 and 2015, using the north of Minas Gerais state (128 000 km²) as a case study. We evaluated the potential biophysical and social-economic drivers of TDF loss, natural regeneration and net area change at the county level. Further, we determined the effects of these LUCC variables on socioeconomic indicators. We identified a considerable change in TDF cover, expressed as 9825 km² of deforestation and 6523 km² of regeneration, which resulted in a net loss of 3302 km². The annual rate of TDF cover change was −1.2%, which is extremely high for a vegetation type that is protected as part of the Atlantic Rain Forest biome since 1993. TDF deforestation was directly affected by county area and by the increase in cattle density, and inversely affected by terrain declivity, indicating that land conversion is mostly driven by cattle ranching in flat regions. TDF regeneration was directly affected by county area and inversely affected by the increase in population density and terrain declivity. LUCC variables did not affect welfare indicators, undermining claims from rural sectors that TDF protection would cause a socioeconomic burden for northern Minas Gerais. Our results highlight the importance of naturally regenerating secondary forests to the maintenance of ecosystem integrity and its services, which are frequently neglected in conservation strategies. Hegemonic macroeconomic policies affecting TDFs have been deeply rooted in deforestation for commodities production, and need urgent review because they cause long-term environmental impacts without evidence of welfare gains.

Following the 2015 Paris agreement, the Intergovernmental Panel on Climate Change was tasked with assessing climate change impacts and mitigation options for a world that limits warming to 1.5 °C in a special report. To aid the scientific assessment process three low-warming ensembles were generated over the 21st century based on the Paris targets using NCAR-DOE community model, CESM1-CAM5. This study used those simulation results and computed ten extreme climate indices, from definitions created by the Expert Team on Climate Change Detection and Indices, to determine if the three different scenarios cause different intensity and frequency of extreme precipitation or temperature over the 21st century. After computing the indices, statistical tests were used to determine if significant changes affect their characteristics. It was found that at the grid point level significant changes emerge in all scenarios, for nearly all indices. The temperature indices show widespread significant change, while the behavior of precipitation indices reflects the larger role that internal variability plays, even by the end of the century. Nonetheless differences can be assessed, in substantial measure for many of these indices: changes in nearly all indices have a strong correlation to global mean temperature, so that scenarios and times with greater temperature change experience greater index changes for many regions. This is particularly true of the temperature-related indices, but can be assessed for some regions also for the indices related to precipitation intensity. These results thus show that even for scenarios that are separated by only half of a degree in global average temperature, the statistics of extremes are significantly different.

Clean cooking technologies—ranging from efficient cookstoves to clean fuels—are widely deployed to reduce household air pollution and alleviate adverse health and climate consequences. Although much progress has been made on the technical aspects, sustained and proper use of clean cooking technologies by populations with the most need has been problematic. Only by understanding how clean cooking as an intervention is embedded within complex community processes can we ensure its sustained implementation. Using a community-based system dynamics approach, we engaged two rural communities in co-creating a dynamic model to explain the processes influencing the uptake and transition to sustained use of biogas (an anaerobic methane digester), a clean fuel and cooking technology. The two communities provided contrasting cases: one abandoned biogas while the other continues to use it. We present a system dynamics simulation model, associated analyses, and experiments to understand what factors drive transition and sustained use. A central insight of the model is community processes influencing the capacity to solve technical issues. Model analysis shows that families begin to abandon the technology when it takes longer to solve problems. The momentum in the community then shifts from a determination to address issues with the cooking technology toward caution in further adhering to it. We also conducted experiments using the simulation model to understand the impact of interventions aimed at renewing the use of biogas. A combination of theoretical interventions, including repair of non-functioning biogas units and provision of embedded technical support in communities, resulted in a scenario where the community can continue using the technology even after support is retracted. Our study also demonstrates the utility of a systems approach for engaging local stakeholders in delineating complex community processes to derive significant insights into the dynamic feedback mechanisms involved in the sustained use of biogas by the poor.

In their recent review, 'Geoengineering with seagrasses: is credit due where credit is given?,' Johannessen and Macdonald (2016) invoke the prospect of carbon offset-credit over-allocation by the Verified Carbon Standard as a pretense for their concerns about published seagrass carbon burial rate and global stock estimates. Johannessen and Macdonald (2016) suggest that projects seeking offset-credits under the Verified Carbon Standard methodology VM0033: Methodology for Tidal Wetland and Seagrass Restoration will overestimate long-term (100 yr) sediment organic carbon (SOC) storage because issues affecting carbon burial rates bias storage estimates. These issues warrant serious consideration by the seagrass research community; however, VM0033 does not refer to seagrass SOC 'burial rates' or 'storage.' Projects seeking credits under VM0033 must document greenhouse gas emission reductions over time, relative to a baseline scenario, in order to receive credits. Projects must also monitor changes in carbon pools, including SOC, to confirm that observed benefits are maintained over time. However, VM0033 allows projects to conservatively underestimate project benefits by citing default values for specific accounting parameters, including CO₂ emissions reductions. We therefore acknowledge that carbon crediting methodologies such as VM0033 are sensitive to the quality of the seagrass literature, particularly when permitted default factors are based in part on seagrass burial rates. Literature-derived values should be evaluated based on the concerns raised by Johannessen and Macdonald (2016), but these issues should not lead to credit over-allocation in practice, provided VM0033 is rigorously followed. These issues may, however, affect the feasibility of particular seagrass offset projects.

In their comment on the review paper, 'Geoengineering with seagrasses: is credit due where credit is given?,' Oreska et al2018 state that some of the concerns raised in the review 'warrant serious consideration by the seagrass research community,' but they argue that these concerns are either not relevant to the Voluntary Carbon Standard protocol, VM0033, or are already addressed by specific provisions in the protocol. The VM0033 protocol is a strong and detailed document that includes much of merit, but the methodology for determining carbon sequestration in sediment is flawed, both in the carbon stock change method and in the carbon burial method. The main problem with the carbon stock change method is that the labile carbon in the surface layer of sediments is vulnerable to remineralization and resuspension; it is not sequestered on the 100 year timescale required for carbon credits. The problem with the carbon burial method is chiefly in its application. The protocol does not explain how to apply ²¹⁰Pb-dating to a core, leaving project proponents to apply the inappropriate methods frequently reported in the blue carbon literature, which result in overestimated sediment accumulation rates. Finally, the default emission factors permitted by the protocol are based on literature values that are themselves too high. All of these problems can be addressed, which should result in clearer, more rigorous guidelines for awarding carbon credits for the protection or restoration of seagrass meadows.