Table of contents

Studies of environmental injustice have been intensely scrutinized by social science researchers since the publication of the United Church of Christ's Commission for Racial Justice report entitled Toxic Wastes and Race in the United States in 1987. Importantly, there has been an emphasis on analysing longitudinal data to answer the question 'which came first, people or pollution?' In addition, determining where environmental hazards are located and how demographics around those hazards are estimated has become central to any empirical enquiry on the topic. This new letter by Mohai and Saha (2015 Environ. Res. Lett. 10 115008) adds to our emerging understanding of environmental justice by analysing the distribution of Treatment, Storage and Disposal Facilities across the United States to determine why they are concentrated in non-white and low income neighbourhoods. The researchers clearly demonstrate how longitudinal analysis and advances in geographic information system methodology can help address meaningful social questions about environmental inequality that are central to environmental policy and practice.

Among the many consequences of rising atmospheric greenhouse gas concentrations, is a change to the medium through which planes fly. An emerging area of research is the impact that these changes may have on the airline industry, with studies addressing aspects ranging from the impact of rising temperatures on aeroplane weight restrictions (Coffel and Horton 2015 Wea. Climate Soc.7 94–102) to the impact of changing wind shears on the occurrence of clear air turbulence (Williams and Joshi 2014 Nat. Clim. Change3 644–8). Now, a recent study by Paul Williams (2016 Environ. Res. Lett.11 024008), assesses the impact that changing winds may have on the duration of transatlantic flights.

This study systematically identifies, characterizes, and critically evaluates community-level climate change vulnerability assessments published over the last 25 years (n = 274). We find that while the field has advanced considerably in terms of conceptual framing and methodological approaches, key shortcomings remain in how vulnerability is being studied at the community-level. We argue that vulnerability research needs to more critically engage with the following: methods for evaluating future vulnerability, the relevance of vulnerability research for decision-making, interdependencies between social and ecological systems, attention to researcher / subject power dynamics, critical interpretation of key terms, and consideration of the potentially positive opportunities presented by a changing climate. Addressing these research needs is necessary for generating knowledge that supports climate-affected communities in navigating the challenges and opportunities ahead.

Average annual absolute minimum temperatures (TN_n) provide a means of delineating agriculturally relevant climate zones and are used to define cold hardiness zones (CHZ) by the United States Department of Agriculture. Projected changes in TN_n, mean winter minimum temperatures, and CHZs over the conterminous United States (CONUS) were assessed using an ensemble of statistically downscaled daily climate model output through the mid 21st century (2041–2070). Warming of TN_n is on average ∼40% greater than that of mean winter minimum temperatures across CONUS with an average climate velocity of 21.4 km decade⁻¹ resulting in widespread shifts in CHZs. These changes enable a geographic expansion of thermally suitable areas for the cultivation of cold-intolerant perennial agriculture including almond, kiwi, and orange crops. Beyond these crops, warming of TN_n has broad implications for food security and biotic interactions.

To assess the biogeophysical impacts of land cover/land use change (LCLUC) on surface temperature, two observation-based metrics and their applicability in climate modeling were explored in this study. Both metrics were developed based on the surface energy balance, and provided insight into the contribution of different aspects of land surface change (such as albedo, surface roughness, net radiation and surface heat fluxes) to changing climate. A revision of the first metric, the intrinsic biophysical mechanism, can be used to distinguish the direct and indirect effects of LCLUC on surface temperature. The other, a decomposed temperature metric, gives a straightforward depiction of separate contributions of all components of the surface energy balance. These two metrics well capture observed and model simulated surface temperature changes in response to LCLUC. Results from paired FLUXNET sites and land surface model sensitivity experiments indicate that surface roughness effects usually dominate the direct biogeophysical feedback of LCLUC, while other effects play a secondary role. However, coupled climate model experiments show that these direct effects can be attenuated by large scale atmospheric changes (indirect feedbacks). When applied to real-time transient LCLUC experiments, the metrics also demonstrate usefulness for assessing the performance of climate models and quantifying land–atmosphere interactions in response to LCLUC.

While changes in temperature and precipitation extremes are evident, their influence on crop yield variability remains unclear. Here we present a global analysis detecting yield variability change and attributing it to recent climate change using spatially-explicit global data sets of historical yields and an agro-climatic index based on daily weather data. The agro-climatic index used here is the sum of effective global radiation intercepted by the crop canopy during the yield formation stage that includes thresholds for extreme temperatures and extreme soil moisture deficit. Results show that year-to-year variations in yields of maize, soybean, rice and wheat in 1981–2010 significantly decreased in 19%–33% of the global harvested area with varying extent of area by crop. However, in 9%–22% of harvested area, significant increase in yield variability was detected. Major crop-producing regions with increased yield variability include maize and soybean in Argentina and Northeast China, rice in Indonesia and Southern China, and wheat in Australia, France and Ukraine. Examples of relatively food-insecure regions with increased yield variability are maize in Kenya and Tanzania and rice in Bangladesh and Myanmar. On a global scale, over 21% of the yield variability change could be explained by the change in variability of the agro-climatic index. More specifically, the change in variability of temperatures exceeding the optimal range for yield formation was more important in explaining the yield variability change than other abiotic stresses, such as temperature below the optimal range for yield formation and soil water deficit. Our findings show that while a decrease in yield variability is the main trend worldwide across crops, yields in some regions of the world have become more unstable, suggesting the need for long-term global yield monitoring and a better understanding of the contributions of technology, management, policy and climate to ongoing yield variability change.

Residential yards across the US look remarkably similar despite marked variation in climate and soil, yet the drivers of this homogenization are unknown. Telephone surveys of fertilizer and irrigation use and satisfaction with the natural environment, and measurements of inherent water and nitrogen availability in six US cities (Boston, Baltimore, Miami, Minneapolis-St. Paul, Phoenix, Los Angeles) showed that the percentage of people using irrigation at least once in a year was relatively invariant with little difference between the wettest (Miami, 85%) and driest (Phoenix, 89%) cities. The percentage of people using fertilizer at least once in a year also ranged narrowly (52%–71%), while soil nitrogen supply varied by 10x. Residents expressed similar levels of satisfaction with the natural environment in their neighborhoods. The nature and extent of this satisfaction must be understood if environmental managers hope to effect change in the establishment and maintenance of residential ecosystems.

Global demand for agricultural and forestry products fundamentally affects regional land-use change associated with environmental impacts (EIs) such as erosion. In contrast to aggregated global metrics such as greenhouse gas (GHG) balances, local/regional EIs of different agricultural and forestry production regions need methods which enable worldwide EI comparisons. The key aspect is to control environmental heterogeneity to reveal man-made differences of EIs between production regions. Environmental heterogeneity is the variation in biotic and abiotic environmental conditions. In the present study, we used three approaches to control environmental heterogeneity: (i) environmental stratification, (ii) potential natural vegetation (PNV), and (iii) regional environmental thresholds to compare EIs of solid biomass production. We compared production regions of managed forests and plantation forests in subtropical (Satilla watershed, Southeastern US), tropical (Rufiji basin, Tanzania), and temperate (Mulde watershed, Central Germany) climates. All approaches supported the comparison of the EIs of different land-use classes between and within production regions. They also standardized the different EIs for a comparison between the EI categories. The EIs for different land-use classes within a production region decreased with increasing degree of naturalness (forest, plantation forestry, and cropland). PNV was the most reliable approach, but lacked feasibility and relevance. The PNV approach explicitly included most of the factors that drive environmental heterogeneity in contrast to the stratification and threshold approaches. The stratification approach allows consistent global application due to available data. Regional environmental thresholds only included arbitrarily selected aspects of environmental heterogeneity; they are only available for few EIs. Especially, the PNV and stratification approaches are options to compare regional EIs of biomass or crop production such as erosion, biodiversity, or water quality impacts worldwide and thereby complement existing metrics assessing global EIs such as GHG emissions.

Here we present the analysis of lightning activity over the Mediterranean, based on a 10 year long dataset (2005–2014) provided by the ZEUS long-range lightning detection system. The major hot-spots of lightning activity are identified, with a clear predominance during the warm period of the year over land in the vicinity of the major topographic features of the area. Special emphasis is also given on the discussion of the seasonal distribution of lightning. In addition, we investigate the relationship of lightning with sea-surface temperature, obtained by high-resolution satellite measurements and we conclude that the number of lightning strokes is positively correlated with the sea-surface temperature during autumn when also the maximum lightning activity over the sea is depicted. We suggest that higher sea surface temperature further destabilises the lower tropospheric layers, enhancing thus convection and therefore lightning.

Chronic nitrogen deposition has measureable impacts on soil and plant health. We investigate burning emissions from biomass grown in areas of high and low NO_x deposition. Gas and aerosol-phase emissions were measured as a function of photochemical aging in an environmental chamber at UC-Riverside. Though aerosol chemical speciation was not available, results indicate a systemic compositional difference between biomass grown in high and low deposition areas. Aerosol emissions from biomass grown in areas of high NO_x deposition exhibit a lower volatility than biomass grown in a low deposition area. Furthermore, fuel elemental analysis, NO_x emission rates, and aerosol particle number distributions differed significantly between the two sites. Despite the limited scale of fuels explored, there is strong evidence that the atmospheric emissions community must pay attention to the regional air quality of biomass fuels growth areas.

A Landsat-based humid tropical forest disturbance alert was implemented for Peru, the Republic of Congo and Kalimantan, Indonesia. Alerts were mapped on a weekly basis as new terrain-corrected Landsat 7 and 8 images were made available; results are presented for all of 2014 and through September 2015. The three study areas represent different stages of the forest land use transition, with all featuring a variety of disturbance dynamics including logging, smallholder agriculture, and agroindustrial development. Results for Peru were formally validated and alerts found to have very high user's accuracies and moderately high producer's accuracies, indicating an appropriately conservative product suitable for supporting land management and enforcement activities. Complete pan-tropical coverage will be implemented during 2016 in support of the Global Forest Watch initiative. To date, Global Forest Watch produces annual global forest loss area estimates using a comparatively richer set of Landsat inputs. The alert product is presented as an interim update of forest disturbance events between comprehensive annual updates. Results from this study are available for viewing and download at http://glad.geog.umd.edu/forest-alerts and www.globalforestwatch.org.

Global warming over the past several decades is now large enough that regional climate change is emerging above the noise of natural variability, especially in the summer at middle latitudes and year-round at low latitudes. Despite the small magnitude of warming relative to weather fluctuations, effects of the warming already have notable social and economic impacts. Global warming of 2 °C relative to preindustrial would shift the 'bell curve' defining temperature anomalies a factor of three larger than observed changes since the middle of the 20th century, with highly deleterious consequences. There is striking incongruity between the global distribution of nations principally responsible for fossil fuel CO₂ emissions, known to be the main cause of climate change, and the regions suffering the greatest consequences from the warming, a fact with substantial implications for global energy and climate policies.

Proximity to the coast and elevation are important geographical considerations for human settlement. Little is known, however, about how spatial variation in these factors exactly relates to human settlements and activities, and how this has developed over time. Such knowledge is important for identifying vulnerable regions that are at risk from phenomena such as food shortages and water stress. Human activities are a key driving force in global change, and thus detailed information on population distribution is an important input to any research framework on global change. In this paper we assess the global geospatial patterns of the distribution of human population and related factors, with regard to the altitude above sea level and proximity to the coast. The investigated factors are physical conditions, urbanisation, agricultural practices, economy, and environmental stress. An important novel element in this study, is that we included the temporal evolution in various factors related to human settlements and agricultural practices over the 20th century, and used projections for some of these factors up to the year 2050. We found population pressure in the proximity of the coast to be somewhat greater than was found in other studies. Yet, the distribution of population, urbanisation and wealth are evolving to become more evenly spread across the globe than they were in the past. Therefore, the commonly believed tendency of accumulation of people and wealth along coasts is not supported by our results. At the same time, food production is becoming increasingly decoupled from the trends in population density. Croplands are spreading from highly populated coastal zones towards inland zones. Our results thus indicate that even though people and wealth continue to accumulate in proximity to the coast, population densities and economic productivity are becoming less diverse in relation to elevation and distance from the coast.

Quantifying water implications of energy transitions is important for assessing long-term freshwater sustainability since large volumes of water are currently used throughout the energy sector. In this paper, we assess direct global energy sector water use and thermal water pollution across a broad range of energy system transformation pathways to assess water impacts of a 2 °C climate policy. A global integrated assessment model is equipped with the capabilities to account for the water impacts of technologies located throughout the energy supply chain. The model framework is applied across a broad range of 2 °C scenarios to highlight long-term water impact uncertainties over the 21st century. We find that water implications vary significantly across scenarios, and that adaptation in power plant cooling technology can considerably reduce global freshwater withdrawals and thermal pollution. Global freshwater consumption increases across all of the investigated 2 °C scenarios as a result of rapidly expanding electricity demand in developing regions and the prevalence of freshwater-cooled thermal power generation. Reducing energy demand emerges as a robust strategy for water conservation, and enables increased technological flexibility on the supply side to fulfill ambitious climate objectives. The results underscore the importance of an integrated approach when developing water, energy, and climate policy, especially in regions where rapid growth in both energy and water demands is anticipated.

The reduction in global-mean precipitation when stratospheric aerosol geoengineering is used to counterbalance global warming from increasing carbon dioxide (CO₂) concentrations has been mainly attributed to the temperature-independent effect of CO₂ on atmospheric radiative cooling. We demonstrate here that stratospheric sulphate aerosol itself also acts to reduce global-mean precipitation independent of its effects on temperature. The temperature-independent effect of stratospheric aerosol geoenginering on global-mean precipitation is calculated by removing temperature-dependent effects from climate model simulations of the Geoengineering Model Intercomparison Project (GeoMIP). When sulphate aerosol is injected into the stratosphere at a rate of 5 Tg SO₂ per year the aerosol reduces global-mean precipitation by approximately 0.2 %, though multiple ensemble members are required to separate this effect from internal variability. For comparison, the precipitation reduction from the temperature-independent effect of increasing CO₂ concentrations under the RCP4.5 scenario of the future is approximately 0.5 %. The temperature-independent effect of stratospheric sulphate aerosol arises from the aerosol's effect on tropospheric radiative cooling. Radiative transfer calculations show this is mainly due to increasing downward emission of infrared radiation by the aerosol, but there is also a contribution from the stratospheric warming the aerosol causes. Our results suggest climate model simulations of solar dimming can capture the main features of the global-mean precipitation response to stratospheric aerosol geoengineering.

Wind energy resource is subject to changes in climate. To investigate the impacts of climate change on future European wind power generation potential, we analyze a multi-model ensemble of the most recent EURO-CORDEX regional climate simulations at the 12 km grid resolution. We developed a mid-century wind power plant scenario to focus the impact assessment on relevant locations for future wind power industry. We found that, under two greenhouse gas concentration scenarios, changes in the annual energy yield of the future European wind farms fleet as a whole will remain within ±5% across the 21st century. At country to local scales, wind farm yields will undergo changes up to 15% in magnitude, according to the large majority of models, but smaller than 5% in magnitude for most regions and models. The southern fleets such as the Iberian and Italian fleets are likely to be the most affected. With regard to variability, changes are essentially small or poorly significant from subdaily to interannual time scales.

As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climate change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%–85% of permafrost carbon release can still be avoided if human emissions are actively reduced.

Solar variability represents a source of uncertainty in the future forcings used in climate model simulations. Current knowledge indicates that a descent of solar activity into an extended minimum state is a possible scenario. With aid of experiments from a state-of-the-art Earth system model,we investigate the impact of a future solar minimum on Northern Hemisphere climate change projections. This scenario is constructed from recent 11 year solar-cycle minima of the solar spectral irradiance, and is therefore more conservative than the 'grand' minima employed in some previous modeling studies. Despite the small reduction in total solar irradiance (0.36 W m⁻²), relatively large responses emerge in the winter Northern Hemisphere, with a reduction in regional-scale projected warming by up to 40%. To identify the origin of the enhanced regional signals, we assess the role of the different mechanisms by performing additional experiments forced only by irradiance changes at different wavelengths of the solar spectrum. We find that a reduction in visible irradiance drives changes in the stationary wave pattern of the North Pacific and sea–ice cover. A decrease in UV irradiance leads to smaller surface signals, although its regional effects are not negligible. These results point to a distinct but additive role of UV and visible irradiance in the Earth's climate, and stress the need to account for solar forcing as a source of uncertainty in regional scale projections.

Assessing socio-economic vulnerability to climate change impacts to support regional decision-making is conceptually and practically challenging. We report on research that tested a rapid assessment approach of socio-economic vulnerability in Australia's natural resource management regions. The approach focuses on regionally important economic sectors, identified using existing datasets, which are likely to be sensitive to climate change impacts. Disaggregated spatial representations of factors known to be associated with vulnerability function as multiple lines of evidence for highlighting intra-regional hotspots of high potential vulnerability. Our results show that a small number of factors based upon contextually relevant empirical evidence offers a low-cost, rapid assessment process, which is readily transferable across regions and provides end-users with guidance for interpreting the results within the context of regional conditions.

The United States (US) Clean Power Plan established state-specific carbon dioxide (CO₂) emissions reduction goals for fossil fuel-fired electricity generating units (EGUs). States may achieve these goals through multiple mechanisms, including measures that can achieve equivalent CO₂ reductions such as residential energy efficiency, which will have important co-benefits. Here, we develop state-resolution simulations of the economic, health, and climate benefits of increased residential insulation, considering EGUs and residential combustion. Increasing insulation to International Energy Conservation Code 2012 levels for all single-family homes in the US in 2013 would lead to annual reductions of 80 million tons of CO₂ from EGUs, with annual co-benefits including 30 million tons of CO₂ from residential combustion and 320 premature deaths associated with criteria pollutant emissions from both EGUs and residential combustion sources. Monetized climate and health co-benefits average $49 per ton of CO₂ reduced from EGUs (range across states: $12–$390). State-specific co-benefit estimates can inform development of optimal Clean Power Plan implementation strategies.

This study investigated impacts of urban forms on the future thermal environment over Beijing, the capital city of China. Beijing is experiencing remarkable urban expansion and is planned to undergo the transformation of urban forms from single-centric (compact-city) to poly-centric city (dispersed-city). Impacts of urban forms on the future thermal environment were compared and evaluated by conducting numerical experiments based on a regional atmospheric model coupled with a single-layer urban canopy model as well as future climate forcing output from a global climate model. Results show that a dispersed city is efficient in reducing mean urban heat island intensity, but produces larger thermal loading and deeper thermal feedback at the regional scale compared to a compact city. Thermal comfort over downtown areas is reduced in compact-city scenario under future climate conditions. Future climate contributes almost 80% of the additional thermal loading over urban areas, with the remaining 20% contributed by urbanization (for both the compact-city and dispersed-city scenarios). The thermal contrast between the two urban forms is dominated by the expected future climate change. This study leads to two complementary conclusions: (i) for developing assessments related to current climate comfort, urban form of the city is important; (ii) for assessing future climate change impacts, the areal coverage of the city and urbanization extent emerges to be more important than the details related to how the urbanization will evolve.

We examine the influence of winter and summer Arctic Oscillation (AO) on variations in the September Arctic sea ice extent (SIE). The winter and summer atmospheric patterns associated with year-to-year variations and detrended September SIE correlate with the positive winter AO and the negative summer AO, respectively. However, the interannual variations of winter and summer AO indices after 2007 are more weakly connected with year-to-year variations in the September SIE. Since 2007, the surface air temperatures over the Beaufort, Chukchi and East Siberian Seas are related to the interannual variations of the September SIE. Recent summer atmospheric patterns associated with the September SIE correlate with the summer AO pattern, but the summer anticyclonic circulation over the Arctic favours the recent low September SIE more than the seesaw pattern between mid- and high- latitudes. Recent winters' positive AO have not contributed to the recent low September SIE because winter anticyclonic circulation over northern Eurasia is more directly connected with recent September SIE.

An understanding of potential factors controlling methane emissions from natural wetlands is important to accurately project future atmospheric methane concentrations. Here, we examine the relative contributions of climatic and environmental factors, such as precipitation, temperature, atmospheric CO₂ concentration, nitrogen deposition, wetland inundation extent, and land-use and land-cover change, on changes in wetland methane emissions from preindustrial to present day (i.e., 1850–2005). We apply a mechanistic methane biogeochemical model integrated in the Community Land Model version 4.5 (CLM4.5), the land component of the Community Earth System Model. The methane model explicitly simulates methane production, oxidation, ebullition, transport through aerenchyma of plants, and aqueous and gaseous diffusion. We conduct a suite of model simulations from 1850 to 2005, with all changes in environmental factors included, and sensitivity studies isolating each factor. Globally, we estimate that preindustrial methane emissions were higher by 10% than present-day emissions from natural wetlands, with emissions changes from preindustrial to the present of +15%, −41%, and −11% for the high latitudes, temperate regions, and tropics, respectively. The most important change is due to the estimated change in wetland extent, due to the conversion of wetland areas to drylands by humans. This effect alone leads to higher preindustrial global methane fluxes by 33% relative to the present, with the largest change in temperate regions (+80%). These increases were partially offset by lower preindustrial emissions due to lower CO₂ levels (10%), shifts in precipitation (7%), lower nitrogen deposition (3%), and changes in land-use and land-cover (2%). Cooler temperatures in the preindustrial regions resulted in our simulations in an increase in global methane emissions of 6% relative to present day. Much of the sensitivity to these perturbations is mediated in the model by changes in methane substrate production and the areal extent of wetlands. The detrended interannual variability of high-latitude methane emissions is explained by the variation in substrate production and wetland inundation extent, whereas the tropical emission variability is explained by both of those variables and precipitation.

The observed forest carbon sink, i.e. positive net ecosystem productivity (NEP), in East Asia reported by the eddy covariance flux tower network is an integrated result of forests themselves (e.g. age) and abiotic factors such as climate. However the relative contribution of climate alone to that sink is highly uncertain and has been in debate. In this study we de-trended a primary effect of forest age on carbon sinks by a statistical regression model between NEP and forest ages. Then, modeled residual NEP was regressed against climate factors again so that its relative contribution could be evaluated appropriately in the region. The analysis for data from the 2000s showed that forest age appeared to be the primary impact factor on the carbon sink of the region (R² = 0.347), and the mean annual temperature (MAT) was the second (R² = 0.23), while the mean annual precipitation effect might not be as apparent as MAT. Particularly for forests in China, climate might contribute to about 31.7% of the total NEP of 0.540 Pg C yr⁻¹. Given that forests in China are relatively young under current climate conditions, we predicted that they would be capable of atmospheric carbon sequestration in the near future.

The adoption of the Sustainable Development Goals (SDGs) and the new international climate treaty could put 2015 into the history books as a defining year for setting human development on a more sustainable pathway. The global climate policy and SDG agendas are highly interconnected: the way that the climate problem is addressed strongly affects the prospects of meeting numerous other SDGs and vice versa. Drawing on existing scenario results from a recent energy-economy-climate model inter-comparison project, this letter analyses these synergies and (risk) trade-offs of alternative 2 °C pathways across indicators relevant for energy-related SDGs and sustainable energy objectives. We find that limiting the availability of key mitigation technologies yields some co-benefits and decreases risks specific to these technologies but greatly increases many others. Fewer synergies and substantial trade-offs across SDGs are locked into the system for weak short-term climate policies that are broadly in line with current Intended Nationally Determined Contributions (INDCs), particularly when combined with constraints on technologies. Lowering energy demand growth is key to managing these trade-offs and creating synergies across multiple energy-related SD dimensions. We argue that SD considerations are central for choosing socially acceptable 2 °C pathways: the prospects of meeting other SDGs need not dwindle and can even be enhanced for some goals if appropriate climate policy choices are made. Progress on the climate policy and SDG agendas should therefore be tracked within a unified framework.

The equilibration of rising atmospheric ${\mathrm{CO}}_{2}$ with the ocean is lowering $\mathrm{pH}$ in tropical waters by about 0.01 every decade. Coral reefs and the ecosystems they support are regarded as one of the most vulnerable ecosystems to ocean acidification, threatening their long-term viability. In response to this threat, different strategies for buffering the impact of ocean acidification have been proposed. As the $\mathrm{pH}$ experienced by individual corals on a natural reef system depends on many processes over different time scales, the efficacy of these buffering strategies remains largely unknown. Here we assess the feasibility and potential efficacy of a reef-scale (a few kilometers) carbon removal strategy, through the addition of seaweed (fleshy multicellular algae) farms within the Great Barrier Reef at the Heron Island reef. First, using diagnostic time-dependent age tracers in a hydrodynamic model, we determine the optimal location and size of the seaweed farm. Secondly, we analytically calculate the optimal density of the seaweed and harvesting strategy, finding, for the seaweed growth parameters used, a biomass of 42 g N m⁻² with a harvesting rate of up 3.2 g N m⁻² d⁻¹ maximises the carbon sequestration and removal. Numerical experiments show that an optimally located 1.9 km² farm and optimally harvested seaweed (removing biomass above 42 g N m⁻² every 7 d) increased aragonite saturation by 0.1 over 24 km² of the Heron Island reef. Thus, the most effective seaweed farm can only delay the impacts of global ocean acidification at the reef scale by 7–21 years, depending on future global carbon emissions. Our results highlight that only a kilometer-scale farm can partially mitigate global ocean acidification for a particular reef.

Natural gas worth tens of billions of dollars is flared annually, which leads to resource waste and environmental issues. This work introduces and analyzes a novel concept for flared gas utilization, wherein the gas that would have been flared is instead used to condense atmospheric moisture. Natural gas, which is currently being flared, can alternatively power refrigeration systems to generate the cooling capacity for large scale atmospheric water harvesting (AWH). This approach solves two pressing issues faced by the oil–gas industry, namely gas flaring, and sourcing water for oilfield operations like hydraulic fracturing, drilling and water flooding. Multiple technical pathways to harvest atmospheric moisture by using the energy of natural gas are analyzed. A modeling framework is developed to quantify the dependence of water harvest rates on flared gas volumes and ambient weather. Flaring patterns in the Eagle Ford Shale in Texas and the Bakken Shale in North Dakota are analyzed to quantify the benefits of AWH. Overall, the gas currently flared annually in Texas and North Dakota can harvest enough water to meet 11% and 65% of the water consumption in the Eagle Ford and the Bakken, respectively. Daily harvests of upto 30 000 and 18 000 gallons water can be achieved using the gas currently flared per well in Texas and North Dakota, respectively. In fifty Bakken sites, the water required for fracturing or drilling a new well can be met via onsite flared gas-based AWH in only 3 weeks, and 3 days, respectively. The benefits of this concept are quantified for the Eagle Ford and Bakken Shales. Assessments of the global potential of this concept are presented using data from countries with high flaring activity. It is seen that this waste-to-value conversion concept offers significant economic benefits while addressing critical environmental issues pertaining to oil–gas production.

Climate change is increasing the frequency and intensity of thermokarst, but the influences of regional climate and physiography remain poorly understood. Retrogressive thaw slumping is one of the most dynamic forms of thermokarst and affects many areas of glaciated terrain across northwestern Canada. In this study, we used airphotos and satellite imagery to investigate the influence of climate and landscape factors on thaw slump dynamics. We assessed slump size, density, and growth rates in four regions of ice-rich terrain with contrasting climate and physiographic conditions: the Jesse Moraine, the Tuktoyaktuk Coastlands, the Bluenose Moraine, and the Peel Plateau. Observed increases in: (1) the area impacted by slumps (+2 to +407%), (2) average slump sizes (+0.31 to +1.82 ha), and (3) slump growth rates (+169 to +465 m² yr⁻¹) showed that thermokarst activity is rapidly accelerating in ice-rich morainal landscapes in the western Canadian Arctic, where slumping has become a dominant driver of geomorphic change. Differences in slump characteristics among regions indicate that slump development is strongly influenced by topography, ground ice conditions, and Quaternary history. Observed increases in slump activity occurred in conjunction with increases in air temperature and precipitation, but variation in slump activity among the four regions suggests that increased precipitation has been an important driver of change. Our observation that the most rapid intensification of slump activity occurred in the coldest environment (the Jesse Moraine on Banks Island) indicates that ice-cored landscapes in cold permafrost environments are highly vulnerable to climate change.

Recent research has shown evidence of a linear climate response to cumulative CO₂ emissions, which implies that the source, timing, and amount of emissions does not significantly influence the climate response per unit emission. Furthermore, these analyses have generally assumed that the climate response to land-use CO₂ emissions is equivalent to that of fossil fuels under the assumption that, once in the atmosphere, the radiative forcing induced by CO₂ is not sensitive to the emissions source. However, land-cover change also affects surface albedo and the strength of terrestrial carbon sinks, both of which have an additional climate effect. In this study, we use a coupled climate-carbon cycle model to assess the climate response to historical and future cumulative land-use CO₂ emissions, in order to compare it to the response to fossil fuel CO₂. We find that when we isolate the CO₂-induced (biogeochemical) temperature changes associated with land-use change, then the climate response to cumulative land-use emissions is equivalent to that of fossil fuel CO₂. We show further that the globally-averaged albedo-induced biophysical cooling from land-use change is non-negligible and may be of comparable magnitude to the biogeochemical warming, with the result that the net climate response to land-use change is substantially different from a linear response to cumulative emissions. However, our new simulations suggest that the biophysical cooling from land-use change follows its own independent (negative) linear response to cumulative net land-use CO₂ emissions, which may provide a useful scaling factor for certain applications when evaluating the full transient climate response to emissions.

Fire regime characteristics in North America are expected to change over the next several decades as a result of anthropogenic climate change. Although some fire regime characteristics (e.g., area burned and fire season length) are relatively well-studied in the context of a changing climate, fire severity has received less attention. In this study, we used observed data from 1984 to 2012 for the western United States (US) to build a statistical model of fire severity as a function of climate. We then applied this model to several (n = 20) climate change projections representing mid-century (2040–2069) conditions under the RCP 8.5 scenario. Model predictions suggest widespread reduction in fire severity for large portions of the western US. However, our model implicitly incorporates climate-induced changes in vegetation type, fuel load, and fire frequency. As such, our predictions are best interpreted as a potential reduction in fire severity, a potential that may not be realized due human-induced disequilibrium between plant communities and climate. Consequently, to realize the reductions in fire severity predicted in this study, land managers in the western US could facilitate the transition of plant communities towards a state of equilibrium with the emerging climate through means such as active restoration treatments (e.g., mechanical thinning and prescribed fire) and passive restoration strategies like managed natural fire (under suitable weather conditions). Resisting changes in vegetation composition and fuel load via activities such as aggressive fire suppression will amplify disequilibrium conditions and will likely result in increased fire severity in future decades because fuel loads will increase as the climate warms and fire danger becomes more extreme. The results of our study provide insights to the pros and cons of resisting or facilitating change in vegetation composition and fuel load in the context of a changing climate.

Climate dynamics at diurnal, seasonal and inter-annual scales shape global fire activity, although difficulties of assembling reliable fire and meteorological data with sufficient spatio-temporal resolution have frustrated quantification of this variability. Using Australia as a case study, we combine data from 4760 meteorological stations with 12 years of satellite-derived active fire detections to determine day and night time fire activity, fire season start and end dates, and inter-annual variability, across 61 objectively defined climate regions in three climate zones (monsoon tropics, arid and temperate). We show that geographic patterns of landscape burning (onset and duration) are related to fire weather, resulting in a latitudinal gradient from the monsoon tropics in winter, through the arid zone in all seasons except winter, and then to the temperate zone in summer and autumn. Peak fire activity precedes maximum lightning activity by several months in all regions, signalling the importance of human ignitions in shaping fire seasons. We determined median daily McArthur forest fire danger index (FFDI₅₀) for days and nights when fires were detected: FFDI₅₀ varied substantially between climate zones, reflecting effects of fire management in the temperate zone, fuel limitation in the arid zone and abundance of flammable grasses in the monsoon tropical zone. We found correlations between the proportion of days when FFDI exceeds FFDI₅₀ and the Southern Oscillation index across the arid zone during spring and summer, and Indian Ocean dipole mode index across south-eastern Australia during summer. Our study demonstrates that Australia has a long fire weather season with high inter-annual variability relative to all other continents, making it difficult to detect long term trends. It also provides a way of establishing robust baselines to track changes to fire seasons, and supports a previous conceptual model highlighting multi-temporal scale effects of climate in shaping continental-scale pyrogeography.

Wildfire activity is projected to increase in boreal forests as a result of climate warming. The consequences of increased wildfire activity for soil carbon (C) storage in boreal forests may depend on the sensitivity of soil microbes to fire severity, but microbial responses to boreal forest fire severity are not well known. Here, we combine remote sensing of fire severity and field sampling to characterize the response of soil microbial biomass per g soil, microbial respiration of CO₂ per g soil, and fungal groups to fire severity in a boreal forest ecosystem. We used remote sensing measurements of differenced normalized burn ratio from Landsat as a measure of fire severity. Our results demonstrate that fire severity controls soil microbial responses to boreal forest fires. In comparison to unburned stands, burned stands had a 52% and 56% reduction in soil microbial biomass and basal respiration, respectively. Within burned stands, we found that microbial biomass and basal respiration significantly declined with increasing fire severity. In addition, mycorrhizal taxa and basidiomycetes displayed particularly low tolerances for severe fire. Although wildfires result in the immediate loss of soil C, our study provides evidence that decreases in microbial biomass and respiration following high severity fires may reduce the capacity of the soil microbial community to decompose soil C over longer time scales. Therefore, models of C cycle responses to climate warming may need to represent the sensitivity of microbial biomass and fungal community composition to fire severity in boreal forests.

While tropical deforestation remains widespread, some countries experienced a forest transition—a shift from net deforestation to net reforestation. Costa Rica had one of the highest deforestation rates in the 1980s and is now considered as a model of environmental sustainability, despite being a major producer of bananas and pineapples. We tested three land use processes that are thought to facilitate forest transitions. First, forest transitions may be accompanied by land use displacement through international trade of land-based products, which may undermine the global-scale environmental benefits of national forest protection. Second, reforestation is often associated with land use intensification in agriculture and forestry, allowing for land sparing. Third, this intensification may partly result from a geographical redistribution of land use at the sub-national scale to better match land use with land suitability. These hypotheses were verified for Costa Rica's forest transition. We also tested whether forest increased mainly in regions with a low ecological value and agriculture expanded in regions with a high ecological value. Intensification and land use redistribution accounted for 76% of land spared during the forest transition, with 32% of this spared area corresponding to net reforestation. Decreasing meat exports led to a contraction of pastures, freeing an area equivalent to 80% of the reforested area. The forest transition in Costa Rica was environmentally beneficial at the global scale, with the reforested area over 1989–2013 corresponding to 130% of the land use displaced abroad through imports of agricultural products. However, expansion of export-oriented cropland caused deforestation in the most ecologically valuable regions of Costa Rica. Moreover, wood extraction from forest plantations increased to produce the pallets needed to export fruits. This highlights the importance of a multi-scale analysis when evaluating causes and impacts of national-scale forest transitions.

Trade in staple crop commodities has become increasingly important in the global food system, with ramifications for both food security and water resources sustainability. It is thus essential to understand how the water footprint (WF) of staple crop trade may change in the future. To this end, we project international staple crop trade and its WF under climate and policy scenarios for the year 2030. We use the H08 global hydrologic model to determine the impact of climatic changes to staple crop yields and evapotranspiration. Using the yield changes projected with the H08 model, we estimate the bilateral trade of staple crops using the Global Trade Analysis Project model. We combine these projections to obtain the total and blue WF of agricultural trade and global water savings (GWS) across scenarios. This approach enables us to determine the direct impact of climate change and trade liberalization—together and in isolation—on the WF of staple crop trade. Importantly, we show that trade liberalization leads to greater WF, making it a potentially important adaptation measure to a changing climate, although future work is needed to distinguish high resolution crop water use, water stress, and commodity transfers.

The 2008–2010 food crisis might have been a harbinger of fundamental climate-induced food crises with geopolitical implications. Heat-wave-induced yield losses in Russia and resulting export restrictions led to increases in market prices for wheat across the Middle East, likely contributing to the Arab Spring. With ongoing climate change, temperatures and temperature variability will rise, leading to higher uncertainty in yields for major nutritional crops. Here we investigate which countries are most vulnerable to teleconnected supply-shocks, i.e. where diets strongly rely on the import of wheat, maize, or rice, and where a large share of the population is living in poverty. We find that the Middle East is most sensitive to teleconnected supply shocks in wheat, Central America to supply shocks in maize, and Western Africa to supply shocks in rice. Weighing with poverty levels, Sub-Saharan Africa is most affected. Altogether, a simultaneous 10% reduction in exports of wheat, rice, and maize would reduce caloric intake of 55 million people living in poverty by about 5%. Export bans in major producing regions would put up to 200 million people below the poverty line at risk, 90% of which live in Sub-Saharan Africa. Our results suggest that a region-specific combination of national increases in agricultural productivity and diversification of trade partners and diets can effectively decrease future food security risks.

Trade can allow countries to overcome local or regional losses (shocks) to their food supply, but reliance on international food trade also exposes countries to risks from external perturbations. Countries that are nutritionally or economically dependent on international trade of a commodity may be adversely affected by such shocks. While exposure to shocks has been studied in financial markets, communication networks, and some infrastructure systems, it has received less attention in food-trade networks. Here, we develop a forward shock-propagation model to quantify how trade flows are redistributed under a range of shock scenarios and assess the food-security outcomes by comparing changes in national fish supplies to indices of each country's nutritional fish dependency. Shock propagation and distribution among regions are modeled on a network of historical bilateral seafood trade data from UN Comtrade using 205 reporting territories grouped into 18 regions. In our model exposure to shocks increases with total imports and the number of import partners. We find that Central and West Africa are the most vulnerable to shocks, with their vulnerability increasing when a willingness-to-pay proxy is included. These findings suggest that countries can reduce their overall vulnerability to shocks by reducing reliance on imports and diversifying food sources. As international seafood trade grows, identifying these types of potential risks and vulnerabilities is important to build a more resilient food system.

In a changing climate and society, large storage systems can play a key role for securing water, energy, and food, and rebalancing their cross-dependencies. In this letter, we study the role of large storage operations as flexible means of adaptation to climate change. In particular, we explore the impacts of different climate projections for different future time horizons on the multi-purpose operations of the existing system of large dams in the Red River basin (China–Laos–Vietnam). We identify the main vulnerabilities of current system operations, understand the risk of failure across sectors by exploring the evolution of the system tradeoffs, quantify how the uncertainty associated to climate scenarios is expanded by the storage operations, and assess the expected costs if no adaptation is implemented. Results show that, depending on the climate scenario and the time horizon considered, the existing operations are predicted to change on average from -7 to +5% in hydropower production, +35 to +520% in flood damages, and +15 to +160% in water supply deficit. These negative impacts can be partially mitigated by adapting the existing operations to future climate, reducing the loss of hydropower to 5%, potentially saving around 34.4 million US$ year^-1 at the national scale. Since the Red River is paradigmatic of many river basins across south east Asia, where new large dams are under construction or are planned to support fast growing economies, our results can support policy makers in prioritizing responses and adaptation strategies to the changing climate.

Human societies rely on food reserves and the importation of agricultural goods as means to cope with crop failures and associated food shortage. While food trade has been the subject of intensive investigations in recent years, food reserves remain poorly quantified. It is unclear how food stocks are changing and whether they are declining. In this study we use food stock records for 92 products to reconstruct 50 years of aggregated food reserves, expressed in caloric equivalent (kcal), at the regional and global scales. A detailed statistical analysis demonstrates that the overall regional and global per-capita food stocks are stationary, challenging a widespread impression that food reserves are shrinking. We develop a statistically-sound stochastic representation of stock dynamics and take the stock-halving probability as a measure of the natural variability of the process. We find that there is a 20% probability that the global per-capita stocks will be halved by 2050. There are, however, some strong regional differences: Western Europe and the region encompassing North Africa and the Middle East have smaller halving probabilities and smaller per-capita stocks, while North America and Oceania have greater halving probabilities and greater per-capita stocks than the global average. Africa exhibits low per-capita stocks and relatively high probability of stock halving by 2050, which reflects a state of higher food insecurity in this continent.

This paper develops an economic analysis of climate change impacts in the global forest sector. It illustrates how potential future climate change impacts can be integrated into a dynamic forestry economics model using data from a global dynamic vegetation model, the MC2 model. The results suggest that climate change will cause forest outputs (such as timber) to increase by approximately 30% over the century. Aboveground forest carbon storage also is projected to increase, by approximately 26 Pg C by 2115, as a result of climate change, potentially providing an offset to emissions from other sectors. The effects of climate mitigation policies in the energy sector are then examined. When climate mitigation in the energy sector reduces warming, we project a smaller increase in forest outputs over the timeframe of the analysis, and we project a reduction in the sink capacity of forests of around 12 Pg C by 2115.

Agriculture will need to significantly intensify in the next decades to continue providing essential nutritive food to a growing global population. However, it can have harmful environmental impacts, due to the use of natural and synthetic resources and the emission of greenhouse gases, which alter the water, carbon and nitrogen cycles, and threaten the fertility, health and biodiversity of landscapes. Because of the spatial heterogeneity of resource productivity, farming practices, climate, and land and water availability, the environmental impact of producing food is highly dependent on its origin. For this reason, food trade can either increase or reduce the overall environmental impacts of agriculture, depending on whether or not the impact is greater in the exporting region. Here, we review current scientific understanding of the environmental impacts of food trade, focusing on water and land use, pollution and greenhouse gas emissions. In the case of water, these impacts are mainly beneficial. However, in the cases of pollution and greenhouse gas emissions, this conclusion is not as clear. Overall, there is an urgent need for a more comprehensive, integrated approach to estimate the global impacts of food trade on the environment. Second, research is needed to improve the evaluation of some key aspects of the relative value of each resource depending on the local and regional biophysical and socio–economic context. Finally, to enhance the impact of such evaluations and their applicability in decision-making, scenario analyses and accounting of key issues like deforestation and groundwater exhaustion will be required.

Projected longer-term droughts and intense floods underscore the need to store more water to manage climate extremes. Here we show how depleted aquifers have been used to store water by substituting surface water use for groundwater pumpage (conjunctive use, CU) or recharging groundwater with surface water (managed aquifer recharge, MAR). Unique multi-decadal monitoring from thousands of wells and regional modeling datasets for the California Central Valley and central Arizona were used to assess CU and MAR. In addition to natural reservoir capacity related to deep water tables, historical groundwater depletion further expanded aquifer storage by ∼44 km³ in the Central Valley and by ∼100 km³ in Arizona, similar to or exceeding current surface reservoir capacity by up to three times. Local river water and imported surface water, transported through 100s of km of canals, is substituted for groundwater (≤15 km³ yr⁻¹, CU) or is used to recharge groundwater (MAR, ≤1.5 km³ yr⁻¹) during wet years shifting to mostly groundwater pumpage during droughts. In the Central Valley, CU and MAR locally reversed historically declining water-level trends, which contrasts with simulated net regional groundwater depletion. In Arizona, CU and MAR also reversed historically declining groundwater level trends in active management areas. These rising trends contrast with current declining trends in irrigated areas that lack access to surface water to support CU or MAR. Use of depleted aquifers as reservoirs could expand with winter flood irrigation or capturing flood discharges to the Pacific (0–1.6 km³ yr⁻¹, 2000–2014) with additional infrastructure in California. Because flexibility and expanded portfolio options translate to resilience, CU and MAR enhance drought resilience through multi-year storage, complementing shorter term surface reservoir storage, and facilitating water markets.

Watershed and global-scale nitrogen (N) budgets indicate that the majority of the N surplus in anthropogenic landscapes does not reach the coastal oceans. While there is general consensus that this 'missing' N either exits the landscape via denitrification or is retained within watersheds as nitrate or organic N, the relative magnitudes of these pools and fluxes are subject to considerable uncertainty. Our study, for the first time, provides direct, large-scale evidence of N accumulation in the root zones of agricultural soils that may account for much of the 'missing N' identified in mass balance studies. We analyzed long-term soil data (1957–2010) from 2069 sites throughout the Mississippi River Basin (MRB) to reveal N accumulation in cropland of 25–70 kg ha⁻¹ yr⁻¹, a total of 3.8 ± 1.8 Mt yr⁻¹ at the watershed scale. We then developed a simple modeling framework to capture N depletion and accumulation dynamics under intensive agriculture. Using the model, we show that the observed accumulation of soil organic N (SON) in the MRB over a 30 year period (142 Tg N) would lead to a biogeochemical lag time of 35 years for 99% of legacy SON, even with complete cessation of fertilizer application. By demonstrating that agricultural soils can act as a net N sink, the present work makes a critical contribution towards the closing of watershed N budgets.

To date, assessments of the sustainability of agricultural commodity supply chains have largely relied on some combination of macro-scale footprint accounts, detailed life-cycle analyses and fine-scale traceability systems. Yet these approaches are limited in their ability to support the sustainability governance of agricultural supply chains, whether because they are intended for coarser-grained analyses, do not identify individual actors, or are too costly to be implemented in a consistent manner for an entire region of production. Here we illustrate some of the advantages of a complementary middle-ground approach that balances detail and scale of supply chain transparency information by combining consistent country-wide data on commodity production at the sub-national (e.g. municipal) level with per shipment customs data to describe trade flows of a given commodity covering all companies and production regions within that country. This approach can support supply chain governance in two key ways. First, enhanced spatial resolution of the production regions that connect to individual supply chains allows for a more accurate consideration of geographic variability in measures of risk and performance that are associated with different production practices. Second, identification of key actors that operate within a specific supply chain, including producers, traders, shippers and consumers can help discriminate coalitions of actors that have shared stake in a particular region, and that together are capable of delivering more cost-effective and coordinated interventions. We illustrate the potential of this approach with examples from Brazil, Indonesia and Colombia. We discuss how transparency information can deepen understanding of the environmental and social impacts of commodity production systems, how benefits are distributed among actors, and some of the trade-offs involved in efforts to improve supply chain sustainability. We then discuss the challenges and opportunities of our approach to strengthen supply chain governance and leverage more effective and fair accountability systems.

Previous regional studies in Siberia have demonstrated climate warming and associated changes in distribution of vegetation and forest types, starting at the end of the 20th century. In this study we used two regional bioclimatic envelope models to simulate potential changes in forest types distribution and developed new regression models to simulate changes in stand height in tablelands and southern mountains of central Siberia under warming 21st century climate. Stand height models were based on forest inventory data (2850 plots). The forest type and stand height maps were superimposed to identify how heights would change in different forest types in future climates. Climate projections from the general circulation model Hadley HadCM3 for emission scenarios B1 and A2 for 2080s were paired with the regional bioclimatic models. Under the harsh A2 scenario, simulated changes included: a 80%–90% decrease in forest-tundra and tundra, a 30% decrease in forest area, a ∼400% increase in forest-steppe, and a 2200% increase in steppe, forest-steppe and steppe would cover 55% of central Siberia. Under sufficiently moist conditions, the southern and middle taiga were simulated to benefit from 21st century climate warming. Habitats suitable for highly-productive forests (≥30–40 m stand height) were simulated to increase at the expense of less productive forests (10–20 m). In response to the more extreme A2 climate the area of these highly-productive forests would increase 10%–25%. Stand height increases of 10 m were simulated over 35%–50% of the current forest area in central Siberia. In the extremely warm A2 climate scenario, the tall trees (25–30 m) would occur over 8%–12% of area in all forest types except forest-tundra by the end of the century. In forest-steppe, trees of 30–40 m may cover some 15% of the area under sufficient moisture.