Table of contents

The recent study by McGrath and Lobell (2013 Environ. Res. Lett. 8 014054) assesses the interaction of a changing climate and the carbon dioxide fertilization effect (CFE) on crop productivity. By accounting for the differential response of individual crops and using a finer geographic scale to assess climate effects on crops they have found that previous estimates of the CFE have likely overestimated future yields in some regions while underestimating yields in others. While this work improves our estimates of potential crop yields in an elevated CO₂ atmosphere, it also highlights knowledge gaps regarding the response of major crops to the effects of elevated CO₂ under the sub-optimal growing conditions predicted for many regions in the future.

First principles suggest that climate change is affecting human health, based on what is understood about the relationships between the mean and variability of temperature, precipitation, and other weather variables and climate-sensitive health outcomes, and the magnitude of climate change that has occurred. However, the complexity of these relationships and the multiple drivers of climate-sensitive health outcomes makes the detection and attribution of changing disease patterns to climate change very challenging. Nevertheless, efforts to do so are vital for informing policy and for prioritizing adaptation and mitigation options.

The article by Cook et al offers an interesting new methodological approach to the debate about (supposedly lacking) scientific consensus on global warming, showing that contrarian claims that there was no such consensus are clearly misleading. But once the attribution issue can be regarded as settled, new questions and controversies arise. They ultimately result from the different technological and organizational pathways towards a new global society model that takes its adverse climate change effects into account and seeks for new, but also risky solutions.

Estimates of global primary bioenergy potentials in the literature span almost three orders of magnitude. We narrow that range by discussing biophysical constraints on bioenergy potentials resulting from plant growth (NPP) and its current human use. In the last 30 years, terrestrial NPP was almost constant near 54 PgC yr⁻¹, despite massive efforts to increase yields in agriculture and forestry. The global human appropriation of terrestrial plant production has doubled in the last century. We estimate the maximum physical potential of the world's total land area outside croplands, infrastructure, wilderness and denser forests to deliver bioenergy at approximately 190 EJ yr⁻¹. These pasture lands, sparser woodlands, savannas and tundras are already used heavily for grazing and store abundant carbon; they would have to be entirely converted to bioenergy and intensive forage production to provide that amount of energy. Such a high level of bioenergy supply would roughly double the global human biomass harvest, with far-reaching effects on biodiversity, ecosystems and food supply. Identifying sustainable levels of bioenergy and finding ways to integrate bioenergy with food supply and ecological conservation goals remains a huge and pressing scientific challenge.

The perspective by Haberl et al (2013 Environ. Res. Lett.8 031004) entitled 'Bioenergy: how much can we expect for 2050?' is timely and valuable. It deals with an important subject since contrasting views on the subject make it very difficult for policy makers to adopt policies that would allow 'production and consumption of energy at sustainable levels', in the words of the authors. It is therefore very important to sort out from the abundant literature on the issue which are the facts and which are the biases and preferences.

Atmospheric rivers are impressive, intermittent circulation features in mid-latitude regions of the globe that can cause disastrous floods if they smash against mountainous terrain. While discovered by meteorologists and long feared by hydrologists they have only recently come to the broader attention of climate scientists. In a new letter published in Environmental Research Letters, Lavers et al (2013 Environ. Res. Lett.8 034010) investigate atmospheric rivers reaching the British Isles in the context of climate change. They consider these potentially devastating meteorological features in present and future climate model scenarios, and walk through possible mechanisms that could cause them to strengthen. This is a refreshingly new work that estimates extreme events in future climates with an impact driven approach.

An analysis of the interannual variability of surface air temperature during the boreal winter in the East Asian (EA) region from 1960 to 2009 reveals that the East Asian winter monsoon (EAWM) significantly weakens after the mid-1980s. The robust warming over the EA region in the lower and middle troposphere as well as at the surface is caused mainly by changes in circulations over the North Pacific and Eurasian continent. The 300 hPa East Asian jet and 500 hPa trough over the EA region, which are closely linked to cold surges, significantly weaken after the mid-1980s. The weakened northerly wind in the Siberian high region and north of the EA region interfere with cold advection toward the EA region. The anomalous southeasterlies over the East China Sea due to an enhanced North Pacific oscillation (NPO)-like sea level pressure (SLP) pattern lead to anomalous warm advection over the EA region. It is also found that the advection of mean temperature by anomalous wind and the advection of anomalous temperature by mean wind mainly contribute to the anomalous warm advection in the EA region after the mid-1980s. Consequently, these anomalous circulations provide a more favorable environment for weakening of the EAWM.

Global warming is expected to enhance fluxes of fresh water between the surface and atmosphere, causing wet regions to become wetter and dry regions drier, with serious implications for water resource management. Defining the wet and dry regions as the upper 30% and lower 70% of the precipitation totals across the tropics (30° S–30° N) each month we combine observations and climate model simulations to understand changes in the wet and dry regions over the period 1850–2100. Observed decreases in precipitation over dry tropical land (1950–2010) are also simulated by coupled atmosphere–ocean climate models (−0.3%/decade) with trends projected to continue into the 21st century. Discrepancies between observations and simulations over wet land regions since 1950 exist, relating to decadal fluctuations in El Niño southern oscillation, the timing of which is not represented by the coupled simulations. When atmosphere-only simulations are instead driven by observed sea surface temperature they are able to adequately represent this variability over land. Global distributions of precipitation trends are dominated by spatial changes in atmospheric circulation. However, the tendency for already wet regions to become wetter (precipitation increases with warming by 3% K⁻¹ over wet tropical oceans) and the driest regions drier (precipitation decreases of −2% K⁻¹ over dry tropical land regions) emerges over the 21st century in response to the substantial surface warming.

Coral reefs are among the most biodiverse ecosystems in the world. Today they are threatened by numerous stressors, including warming ocean waters and coastal pollution. Here we focus on the implications of ocean acidification for the open ocean chemistry surrounding coral reefs, as estimated from earth system models participating in the Coupled Model Intercomparison Project, Phase 5 (CMIP5). We project risks to reefs in the context of three potential aragonite saturation (Ωa) thresholds. We find that in preindustrial times, 99.9% of reefs adjacent to open ocean in the CMIP5 ensemble were located in regions with Ωa > 3.5. Under a business-as-usual scenario (RCP 8.5), every coral reef considered will be surrounded by water with Ωa < 3 by the end of the 21st century and the reefs' long-term fate is independent of their specific saturation threshold. However, under scenarios with significant CO₂ emissions abatement, the Ωa threshold for reefs is critical to projecting their fate. Our results indicate that to maintain a majority of reefs surrounded by waters with Ωa > 3.5 to the end of the century, very aggressive reductions in emissions are required. The spread of Ωa projections across models in the CMIP5 ensemble is narrow, justifying a high level of confidence in these results.

In order to meet stringent temperature targets, active removal of CO₂ from the atmosphere may be required in the long run. Such negative emissions can be materialized when well-performing bioenergy systems are combined with carbon capture and storage (BECCS). Here, we develop an integrated global energy system and climate model to evaluate the role of BECCS in reaching ambitious temperature targets. We present emission, concentration and temperature pathways towards 1.5 and 2 ° C targets. Our model results demonstrate that BECCS makes it feasible to reach temperature targets that are otherwise out of reach, provided that a temporary overshoot of the target is accepted. Additionally, stringent temperature targets can be met at considerably lower cost if BECCS is available. However, the economic benefit of BECCS nearly vanishes if an overshoot of the temperature target is not allowed. Finally, the least-cost emission pathway over the next 50 years towards a 1.5 ° C overshoot target with BECCS is almost identical to a pathway leading to a 2 ° C ceiling target.

Increased concentrations of ozone and fine particulate matter (PM_2.5) since preindustrial times reflect increased emissions, but also contributions of past climate change. Here we use modeled concentrations from an ensemble of chemistry–climate models to estimate the global burden of anthropogenic outdoor air pollution on present-day premature human mortality, and the component of that burden attributable to past climate change. Using simulated concentrations for 2000 and 1850 and concentration–response functions (CRFs), we estimate that, at present, 470 000 (95% confidence interval, 140 000 to 900 000) premature respiratory deaths are associated globally and annually with anthropogenic ozone, and 2.1 (1.3 to 3.0) million deaths with anthropogenic PM_2.5-related cardiopulmonary diseases (93%) and lung cancer (7%). These estimates are smaller than ones from previous studies because we use modeled 1850 air pollution rather than a counterfactual low concentration, and because of different emissions. Uncertainty in CRFs contributes more to overall uncertainty than the spread of model results. Mortality attributed to the effects of past climate change on air quality is considerably smaller than the global burden: 1500 (−20 000 to 27 000) deaths yr⁻¹ due to ozone and 2200 (−350 000 to 140 000) due to PM_2.5. The small multi-model means are coincidental, as there are larger ranges of results for individual models, reflected in the large uncertainties, with some models suggesting that past climate change has reduced air pollution mortality.

Observations of wakes from individual wind turbines and a multi-megawatt wind energy installation in the Midwestern US indicate that directly downstream of a turbine (at a distance of 190 m, or 2.4 rotor diameters (D)), there is a clear impact on wind speed and turbulence intensity (TI) throughout the rotor swept area. However, at a downwind distance of 2.1 km (26 D downstream of the closest wind turbine) the wake of the whole wind farm is not evident. There is no significant reduction of hub-height wind speed or increase in TI especially during daytime. Thus, in high turbulence regimes even very large wind installations may have only a modest impact on downstream flow fields. No impact is observable in daytime vertical potential temperature gradients at downwind distances of >2 km, but at night the presence of the wind farm does significantly decrease the vertical gradients of potential temperature (though the profile remains stably stratified), largely by increasing the temperature at 2 m.

Supraglacial lake drainage on the Greenland ice sheet opens surface-to-bed connections, reduces basal friction, and temporarily increases ice flow velocities by up to an order of magnitude. Existing field-based observations of lake drainages and their impact on ice dynamics are limited, and focus on one specific draining mechanism. Here, we report and analyse global positioning system measurements of ice velocity and elevation made at five locations surrounding two lakes that drained by different mechanisms and produced different dynamic responses. For the lake that drained slowly (>24 h) by overtopping its basin, delivering water via a channel to a pre-existing moulin, speedup and uplift were less than half those associated with a lake that drained rapidly (∼2 h) through hydrofracturing and the creation of new moulins in the lake bottom. Our results suggest that the mode and associated rate of lake drainage govern the impact on ice dynamics.

The representative concentration pathway (RCP) scenarios all assume stringent emissions controls on aerosols and their precursors, and hence include progressive decreases in aerosol and aerosol precursor emissions through the 21st century. Recent studies have suggested that the resultant decrease in aerosols could drive rapid near-term warming, which could dominate the effects of greenhouse gas (GHG) increases in the coming decades. In CanESM2 simulations, we find that under the RCP 2.6 scenario, which includes the fastest decrease in aerosol and aerosol precursor emissions, the contribution of aerosol reductions to warming between 2000 and 2040 is around 30%. Moreover, the rate of warming in the RCP 2.6 simulations declines gradually from its present-day value as GHG emissions decrease. Thus, while aerosol emission reductions contribute to gradual warming through the 21st century, we find no evidence that aerosol emission reductions drive particularly rapid near-term warming in this scenario. In the near-term, as in the long-term, GHG increases are the dominant driver of warming.

The United Nations Framework Convention on Climate Change (UNFCCC) defined the technical and financial modalities of policy approaches and incentives to reduce emissions from deforestation and forest degradation in developing countries (REDD+). Substantial technical challenges hinder precise and accurate estimation of forest-related emissions and removals, as well as the setting and assessment of reference levels. These challenges could limit country participation in REDD+, especially if REDD+ emission reductions were to meet quality standards required to serve as compliance grade offsets for developed countries' emissions. Using Panama as a case study, we tested the matrix approach proposed by Bucki et al (2012 Environ. Res. Lett.7 024005) to perform sensitivity and uncertainty analysis distinguishing between 'modelling sources' of uncertainty, which refers to model-specific parameters and assumptions, and 'recurring sources' of uncertainty, which refers to random and systematic errors in emission factors and activity data. The sensitivity analysis estimated differences in the resulting fluxes ranging from 4.2% to 262.2% of the reference emission level. The classification of fallows and the carbon stock increment or carbon accumulation of intact forest lands were the two key parameters showing the largest sensitivity. The highest error propagated using Monte Carlo simulations was caused by modelling sources of uncertainty, which calls for special attention to ensure consistency in REDD+ reporting which is essential for securing environmental integrity. Due to the role of these modelling sources of uncertainty, the adoption of strict rules for estimation and reporting would favour comparability of emission reductions between countries. We believe that a reduction of the bias in emission factors will arise, among other things, from a globally concerted effort to improve allometric equations for tropical forests. Public access to datasets and methodology used to evaluate reference level and emission reductions would strengthen the credibility of the system by promoting accountability and transparency. To secure conservativeness and deal with uncertainty, we consider the need for further research using real data available to developing countries to test the applicability of conservative discounts including the trend uncertainty and other possible options that would allow real incentives and stimulate improvements over time. Finally, we argue that REDD+ result-based actions assessed on the basis of a dashboard of performance indicators, not only in 'tonnes CO₂ equ. per year' might provide a more holistic approach, at least until better accuracy and certainty of forest carbon stocks emission and removal estimates to support a REDD+ policy can be reached.

Within the warm conveyor belt of extra-tropical cyclones, atmospheric rivers (ARs) are the key synoptic features which deliver the majority of poleward water vapour transport, and are associated with episodes of heavy and prolonged rainfall. ARs are responsible for many of the largest winter floods in the mid-latitudes resulting in major socioeconomic losses; for example, the loss from United Kingdom (UK) flooding in summer/winter 2012 is estimated to be about $1.6 billion in damages. Given the well-established link between ARs and peak river flows for the present day, assessing how ARs could respond under future climate projections is of importance in gauging future impacts from flooding. We show that North Atlantic ARs are projected to become stronger and more numerous in the future scenarios of multiple simulations from five state-of-the-art global climate models (GCMs) in the fifth Climate Model Intercomparison Project (CMIP5). The increased water vapour transport in projected ARs implies a greater risk of higher rainfall totals and therefore larger winter floods in Britain, with increased AR frequency leading to more flood episodes. In the high emissions scenario (RCP8.5) for 2074–2099 there is an approximate doubling of AR frequency in the five GCMs. Our results suggest that the projected change in ARs is predominantly a thermodynamic response to warming resulting from anthropogenic radiative forcing.

A growing number of countries regulate carbon dioxide (CO₂) emissions occurring within their borders, but due to rapid growth in international trade, the products consumed in many of the same countries increasingly rely on coal, oil and gas extracted and burned in other countries where CO₂ is not regulated. As a consequence, existing national and regional climate policies may be growing less effective every year. Furthermore, countries that are dependent on imported products or fossil fuels are more exposed to energy and climate policies in other countries. We show that the combined international trade in carbon (as fossil fuels and also embodied in products) increased from 12.3 GtCO₂ (55% of global emissions) in 1997 to 17.6 GtCO₂ (60%) in 2007 (growing at 3.7% yr⁻¹). Within this, trade in fossil fuels was larger (10.8 GtCO₂ in 2007) than trade in embodied carbon (6.9 GtCO₂), but the latter grew faster (4.6% yr⁻¹ compared with 3.1% yr⁻¹ for fuels). Most major economies demonstrate increased dependence on traded carbon, either as exports or as imports. Because energy is increasingly embodied in internationally traded products, both as fossil fuels and as products, energy and climate policies in other countries may weaken domestic climate policy via carbon leakage and mask energy security issues.

Surface snow investigated for its elemental carbon (EC) concentration, based on a thermal–optical method, at two different sites during winter and spring of 2010 demonstrates metre scale horizontal variability in concentration. Based on the two sites sampled, a clean and a polluted site, the clean site (Arctic Finland) presents the greatest variability. In side-by-side ratios between neighbouring samples, 5 m apart, a ratio of around two was observed for the clean site. The median for the polluted site had a ratio of 1.2 between neighbouring samples. The results suggest that regions exposed to snowdrift may be more sensitive to horizontal variability in EC concentration. Furthermore, these results highlight the importance of carefully choosing sampling sites and timing, as each parameter will have some effect on EC variability. They also emphasize the importance of gathering multiple samples from a site to obtain a representative value for the area.

Day-ahead load and wind power forecasts provide useful information for operational decision making, but they are imperfect and forecast errors must be offset with operational reserves and balancing of (real time) energy. Procurement of these reserves is of great operational and financial importance in integrating large-scale wind power. We present a probabilistic method to determine net load forecast uncertainty for day-ahead wind and load forecasts. Our analysis uses data from two different electric grids in the US with similar levels of installed wind capacity but with large differences in wind and load forecast accuracy, due to geographic characteristics. We demonstrate that the day-ahead capacity requirements can be computed based on forecasts of wind and load. For 95% day-ahead reliability, this required capacity ranges from 2100 to 5700 MW for ERCOT, and 1900 to 4500 MW for MISO (with 10 GW of installed wind capacity), depending on the wind and load forecast values. We also show that for each MW of additional wind power capacity for ERCOT, 0.16–0.30 MW of dispatchable capacity will be used to compensate for wind uncertainty based on day-ahead forecasts. For MISO (with its more accurate forecasts), the requirement is 0.07–0.13 MW of dispatchable capacity for each MW of additional wind capacity.

While numerous studies have addressed changes in climate extremes, analyses of concurrence of climate extremes are scarce, and climate change effects on joint extremes are rarely considered. This study assesses the occurrence of joint (concurrent) monthly continental precipitation and temperature extremes in Climate Research Unit (CRU) and University of Delaware (UD) observations, and in 13 Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate simulations. The joint occurrences of precipitation and temperature extremes simulated by CMIP5 climate models are compared with those derived from the CRU and UD observations for warm/wet, warm/dry, cold/wet, and cold/dry combinations of joint extremes. The number of occurrences of these four combinations during the second half of the 20th century (1951–2004) is assessed on a common global grid. CRU and UD observations show substantial increases in the occurrence of joint warm/dry and warm/wet combinations for the period 1978–2004 relative to 1951–1977. The results show that with respect to the sign of change in the concurrent extremes, the CMIP5 climate model simulations are in reasonable overall agreement with observations. However, the results reveal notable discrepancies between regional patterns and the magnitude of change in individual climate model simulations relative to the observations of precipitation and temperature.

Worldwide demand for crops is increasing rapidly due to global population growth, increased biofuel production, and changing dietary preferences. Meeting these growing demands will be a substantial challenge that will tax the capability of our food system and prompt calls to dramatically boost global crop production. However, to increase food availability, we may also consider how the world's crops are allocated to different uses and whether it is possible to feed more people with current levels of crop production. Of particular interest are the uses of crops as animal feed and as biofuel feedstocks. Currently, 36% of the calories produced by the world's crops are being used for animal feed, and only 12% of those feed calories ultimately contribute to the human diet (as meat and other animal products). Additionally, human-edible calories used for biofuel production increased fourfold between the years 2000 and 2010, from 1% to 4%, representing a net reduction of available food globally. In this study, we re-examine agricultural productivity, going from using the standard definition of yield (in tonnes per hectare, or similar units) to using the number of people actually fed per hectare of cropland. We find that, given the current mix of crop uses, growing food exclusively for direct human consumption could, in principle, increase available food calories by as much as 70%, which could feed an additional 4 billion people (more than the projected 2–3 billion people arriving through population growth). Even small shifts in our allocation of crops to animal feed and biofuels could significantly increase global food availability, and could be an instrumental tool in meeting the challenges of ensuring global food security.

As climate changes, temperatures will play an increasing role in determining crop yield. Both climate model error and lack of constrained physiological thresholds limit the predictability of yield. We used a perturbed-parameter climate model ensemble with two methods of bias-correction as input to a regional-scale wheat simulation model over India to examine future yields. This model configuration accounted for uncertainty in climate, planting date, optimization, temperature-induced changes in development rate and reproduction. It also accounts for lethal temperatures, which have been somewhat neglected to date. Using uncertainty decomposition, we found that fractional uncertainty due to temperature-driven processes in the crop model was on average larger than climate model uncertainty (0.56 versus 0.44), and that the crop model uncertainty is dominated by crop development. Simulations with the raw compared to the bias-corrected climate data did not agree on the impact on future wheat yield, nor its geographical distribution. However the method of bias-correction was not an important source of uncertainty. We conclude that bias-correction of climate model data and improved constraints on especially crop development are critical for robust impact predictions.

Forest protection policies potentially reduce deforestation and re-direct agricultural expansion to already-cleared areas. Using satellite imagery, we assessed whether deforestation for conversion to pasture and cropland decreased in the lowlands of northern Costa Rica following the 1996 ban on forest clearing, despite a tripling of area under pineapple cultivation in the last decade. We observed that following the ban, mature forest loss decreased from 2.2% to 1.2% per year, and the proportion of pineapple and other export-oriented cropland derived from mature forest declined from 16.4% to 1.9%. The post-ban expansion of pineapples and other crops largely replaced pasture, exotic and native tree plantations, and secondary forests. Overall, there was a small net gain in forest cover due to a shifting mosaic of regrowth and clearing in pastures, but cropland expansion decreased reforestation rates. We conclude that forest protection efforts in northern Costa Rica have likely slowed mature forest loss and succeeded in re-directing expansion of cropland to areas outside mature forest. Our results suggest that deforestation bans may protect mature forests better than older forest regrowth and may restrict clearing for large-scale crops more effectively than clearing for pasture.

Climatic warming of about 0.5 ° C in the global mean since the 1970s has strongly increased the occurrence-probability of heat extremes on monthly to seasonal time scales. For the 21st century, climate models predict more substantial warming. Here we show that the multi-model mean of the CMIP5 (Coupled Model Intercomparison Project) climate models accurately reproduces the evolution over time and spatial patterns of the historically observed increase in monthly heat extremes. For the near-term (i.e., by 2040), the models predict a robust, several-fold increase in the frequency of such heat extremes, irrespective of the emission scenario. However, mitigation can strongly reduce the number of heat extremes by the second half of the 21st century. Unmitigated climate change causes most (>50%) continental regions to move to a new climatic regime with the coldest summer months by the end of the century substantially hotter than the hottest experienced today. We show that the land fraction experiencing extreme heat as a function of global mean temperature follows a simple cumulative distribution function, which depends only on natural variability and the level of spatial heterogeneity in the warming.

Climate change policies must trade off uncertainties about future warming, about the social and ecological impacts of warming, and about the cost of reducing greenhouse gas emissions. We show that laxer carbon targets produce broader distributions for climate damages, skewed towards severe outcomes. However, if potential low-carbon technologies fill overlapping niches, then more stringent carbon targets produce broader distributions for the cost of reducing emissions, skewed towards high-cost outcomes. We use the technology-rich GCAM integrated assessment model to assess the robustness of 450 and 500 ppm carbon targets to each uncertain factor. The 500 ppm target provides net benefits across a broad range of futures. The 450 ppm target provides net benefits only when impacts are greater than conventionally assumed, when multiple technological breakthroughs lower the cost of abatement, or when evaluated with a low discount rate. Policy evaluations are more sensitive to uncertainty about abatement technology and impacts than to uncertainty about warming.

Characterization of the anticipated performance of energy technologies to inform policy decisions increasingly relies on expert elicitation. Knowledge about how elicitation design factors impact the probabilistic estimates emerging from these studies is, however, scarce. We focus on nuclear power, a large-scale low-carbon power option, for which future cost estimates are important for the design of energy policies and climate change mitigation efforts. We use data from three elicitations in the USA and in Europe and assess the role of government research, development, and demonstration (RD&D) investments on expected nuclear costs in 2030. We show that controlling for expert, technology, and design characteristics increases experts' implied public RD&D elasticity of expected costs by 25%. Public sector and industry experts' cost expectations are 14% and 32% higher, respectively than academics. US experts are more optimistic than their EU counterparts, with median expected costs 22% lower. On average, a doubling of public RD&D is expected to result in an 8% cost reduction, but the uncertainty is large. The difference between the 90th and 10th percentile estimates is on average 58% of the experts' median estimates. Public RD&D investments do not affect uncertainty ranges, but US experts are less confident about costs than Europeans.

Can today's global climate model ensembles characterize the 21st century climate in their own 'model-worlds'? This question is at the heart of how we design and interpret climate model experiments for both science and policy support. Using a low-dimensional nonlinear system that exhibits behaviour similar to that of the atmosphere and ocean, we explore the implications of ensemble size and two methods of constructing climatic distributions, for the quantification of a model's climate. Small ensembles are shown to be misleading in non-stationary conditions analogous to externally forced climate change, and sometimes also in stationary conditions which reflect the case of an unforced climate. These results show that ensembles of several hundred members may be required to characterize a model's climate and inform robust statements about the relative roles of different sources of climate prediction uncertainty.

Evaluation of built environment energy demand is necessary in light of global projections of urban expansion. Of particular concern are rapidly expanding urban areas in environments where consumption requirements for cooling are excessive. Here, we simulate urban air conditioning (AC) electric consumption for several extreme heat events during summertime over a semiarid metropolitan area with the Weather Research and Forecasting (WRF) model coupled to a multilayer building energy scheme. Observed total load values obtained from an electric utility company were split into two parts, one linked to meteorology (i.e., AC consumption) which was compared to WRF simulations, and another to human behavior. WRF-simulated non-dimensional AC consumption profiles compared favorably to diurnal observations in terms of both amplitude and timing. The hourly ratio of AC to total electricity consumption accounted for ∼53% of diurnally averaged total electric demand, ranging from ∼35% during early morning to ∼65% during evening hours. Our work highlights the importance of modeling AC electricity consumption and its role for the sustainable planning of future urban energy needs. Finally, the methodology presented in this article establishes a new energy consumption-modeling framework that can be applied to any urban environment where the use of AC systems is prevalent.

One major challenge to the improvement of regional climate scenarios for the northern high latitudes is to understand land surface feedbacks associated with vegetation shifts and ecosystem biogeochemical cycling. We employed a customized, Arctic version of the individual-based dynamic vegetation model LPJ-GUESS to simulate the dynamics of upland and wetland ecosystems under a regional climate model–downscaled future climate projection for the Arctic and Subarctic. The simulated vegetation distribution (1961–1990) agreed well with a composite map of actual arctic vegetation. In the future (2051–2080), a poleward advance of the forest–tundra boundary, an expansion of tall shrub tundra, and a dominance shift from deciduous to evergreen boreal conifer forest over northern Eurasia were simulated. Ecosystems continued to sink carbon for the next few decades, although the size of these sinks diminished by the late 21st century. Hot spots of increased CH₄ emission were identified in the peatlands near Hudson Bay and western Siberia. In terms of their net impact on regional climate forcing, positive feedbacks associated with the negative effects of tree-line, shrub cover and forest phenology changes on snow-season albedo, as well as the larger sources of CH₄, may potentially dominate over negative feedbacks due to increased carbon sequestration and increased latent heat flux.

Global agricultural models are becoming indispensable in the debate over climate change impacts and mitigation policies. Therefore, it is becoming increasingly important to validate these models and identify critical areas for improvement. In this letter, we illustrate both the opportunities and the challenges in undertaking such model validation, using the SIMPLE model of global agriculture. We look back at the long run historical period 1961–2006 and, using a few key historical drivers—population, incomes and total factor productivity—we find that SIMPLE is able to accurately reproduce historical changes in cropland use, crop price, crop production and average crop yields at the global scale. Equally important is our investigation into how the specific assumptions embedded in many agricultural models will likely influence these results. We find that those global models which are largely biophysical—thereby ignoring the price responsiveness of demand and supply—are likely to understate changes in crop production, while failing to capture the changes in cropland use and crop price. Likewise, global models which incorporate economic responses, but do so based on limited time series estimates of these responses, are likely to understate land use change and overstate price changes.

The hygroscopic growth of aerosols is controlled by the relative humidity (RH) and changes the aerosols' physical and hence optical properties. Observational studies of aerosol–cloud interactions evaluate the aerosol concentration using optical parameters, such as the aerosol optical depth (AOD), which can be affected by aerosol humidification. In this study we evaluate the RH background and variance values, in the lower cloudy atmosphere, an additional source of variance in AOD values beside the natural changes in aerosol concentration. In addition, we estimate the bias in RH and AOD, related to cloud thickness. This provides the much needed range of RH-related biases in studies of aerosol–cloud interaction.

Twelve years of radiosonde measurements (June–August) in thirteen globally distributed stations are analyzed. The estimated non-biased AOD variance due to day-to-day changes in RH is found to be around 20% and the biases linked to cloud development around 10%. Such an effect is important and should be considered in direct and indirect aerosol effect estimations but it is inadequate to account for most of the AOD trend found in observational studies of aerosol–cloud interactions.

Global warming is believed to be responsible for the reduction of snow amount and duration over the Alps. In fact, a rapid shortening of the snowy season has been measured and perceived by ecosystems and society in the past 30 years, despite the large year-to-year variability. This trend is projected to continue during the 21st century in the climate change scenarios with increasing greenhouse gas concentrations. Superimposed on the long-term trend, however, there is a low-frequency variability of snowfall associated with multi-decadal changes in the large-scale circulation. The amplitude of this natural low-frequency variation might be relatively large, determining rapid and substantial changes of snowfall, as recently observed. This is already known for winter snowfall over the Alps in connection with the recent tendency toward the positive phase of the North Atlantic Oscillation. In this study, we show that the low-frequency variability of Alpine spring snowfall in the past 150 years is affected by the Atlantic Multi-decadal Oscillation (AMO), which is a natural periodic fluctuation of Northern Atlantic sea surface temperature. Therefore, the recently observed spring snowfall reduction might be, at least in part, explained by the shift toward a positive AMO phase that happened in the 1990s.

Aviation NO_x emissions promote tropospheric ozone formation, which is linked to climate warming and adverse health effects. Modeling studies have quantified the relative impact of aviation NO_x on O₃ in large geographic regions. As these studies have applied forward modeling techniques, it has not been possible to attribute O₃ formation to individual flights. Here we apply the adjoint of the global chemistry–transport model GEOS-Chem to assess the temporal and spatial variability in O₃ production due to aviation NO_x emissions, which is the first application of an adjoint to this problem. We find that total aviation NO_x emitted in October causes 40% more O₃ than in April and that Pacific aviation emissions could cause 4–5 times more tropospheric O₃ per unit NO_x than European or North American emissions. Using this sensitivity approach, the O₃ burden attributable to 83 000 unique scheduled civil flights is computed individually. We find that the ten highest total O₃-producing flights have origins or destinations in New Zealand or Australia. The top ranked O₃-producing flights normalized by fuel burn cause 157 times more normalized O₃ formation than the bottom ranked ones. These results show significant spatial and temporal heterogeneity in environmental impacts of aviation NO_x emissions.

Biodiversity loss and climate change both result from tropical deforestation, yet strategies to address biodiversity loss have focused primarily on protected areas while strategies to address climate change have focused primarily on carbon payments. Conservation planning research has focused largely on where to prioritize protected areas to achieve the greatest representation of species at viable levels. Meanwhile research on reducing emissions from deforestation and forest degradation (REDD+) has focused largely on how to design payments to achieve the greatest additional reduction in greenhouse gases relative to baseline rates. This divergence of strategies and research agendas may be attributed to four factors: rare species are more heterogeneously distributed than carbon; species are more difficult to measure and monitor than carbon; species are more sensitive to ecological processes and human disturbance than carbon; and people's value for species diminishes beyond a threshold while their value for carbon storage does not. Conservation planning can achieve greater biodiversity benefits by adopting the concept of additionality from REDD+. REDD+ can achieve greater climate benefits by incorporating spatial prioritization from conservation planning. Climate and biodiversity benefits can best be jointly achieved from tropical forests by targeting the most additional actions to the most important places. These concepts are illustrated using data from the forests of Indonesia.

Wind power, a renewable energy source, can play an important role in electrical energy generation. Information regarding wind energy potential is important both for energy related modeling and for decision-making in the policy community. While wind speed datasets with high spatial and temporal resolution are often ultimately used for detailed planning, simpler assumptions are often used in analysis work. An accurate representation of the wind speed frequency distribution is needed in order to properly characterize wind energy potential. Using a power density method, this study estimated global variation in wind parameters as fitted to a Weibull density function using NCEP/climate forecast system reanalysis (CFSR) data over land areas. The Weibull distribution performs well in fitting the time series wind speed data at most locations according to R², root mean square error, and power density error. The wind speed frequency distribution, as represented by the Weibull k parameter, exhibits a large amount of spatial variation, a regionally varying amount of seasonal variation, and relatively low decadal variation. We also analyzed the potential error in wind power estimation when a commonly assumed Rayleigh distribution (Weibull k = 2) is used. We find that the assumption of the same Weibull parameter across large regions can result in non-negligible errors. While large-scale wind speed data are often presented in the form of mean wind speeds, these results highlight the need to also provide information on the wind speed frequency distribution.

This letter compares several bounding cases for understanding the economic viability of capturing large quantities of anthropogenic CO₂ from coal-fired power generators within the Electric Reliability Council of Texas electric grid and using it for pure CO₂ enhanced oil recovery (EOR) in the onshore coastal region of Texas along the Gulf of Mexico. All captured CO₂ in excess of that needed for EOR is sequestered in saline formations at the same geographic locations as the oil reservoirs but at a different depth. We analyze the extraction of oil from the same set of ten reservoirs within 20- and five-year time frames to describe how the scale of the carbon dioxide capture, utilization, and storage (CCUS) network changes to meet the rate of CO₂ demand for oil recovery. Our analysis shows that there is a negative system-wide net present value (NPV) for all modeled scenarios. The system comes close to breakeven economics when capturing CO₂ from three coal-fired power plants to produce oil via CO₂-EOR over 20 years and assuming no CO₂ emissions penalty. The NPV drops when we consider a larger network to produce oil more quickly (21 coal-fired generators with CO₂ capture to produce 80% of the oil within five years). Upon applying a CO₂ emissions penalty of 60$2009/tCO₂ to fossil fuel emissions to ensure that coal-fired power plants with CO₂ capture remain in baseload operation, the system economics drop significantly. We show near profitability for the cash flow of the EOR operations only; however, this situation requires relatively cheap electricity prices during operation.

Climate change poses challenges for decision makers across society, not just in preparing for the climate of the future but even when planning for the climate of the present day. When making climate sensitive decisions, policy makers and adaptation planners would benefit from information on local scales and for user-specific quantiles (e.g. the hottest/coldest 5% of days) and thresholds (e.g. days above 28 ° C), not just mean changes. Here, we translate observations of weather into observations of climate change, providing maps of the changing shape of climatic temperature distributions across Europe since 1950. The provision of such information from observations is valuable to support decisions designed to be robust in today's climate, while also providing data against which climate forecasting methods can be judged and interpreted. The general statement that the hottest summer days are warming faster than the coolest is made decision relevant by exposing how the regions of greatest warming are quantile and threshold dependent. In a band from Northern France to Denmark, where the response is greatest, the hottest days in the temperature distribution have seen changes of at least 2 ° C, over four times the global mean change over the same period. In winter the coldest nights are warming fastest, particularly in Scandinavia.

This modelling study demonstrates at what level of global mean temperature rise (ΔT_g) regions will be exposed to significant decreases of freshwater availability and changes to terrestrial ecosystems. Projections are based on a new, consistent set of 152 climate scenarios (eight ΔT_g trajectories reaching 1.5–5 ° C above pre-industrial levels by 2100, each scaled with spatial patterns from 19 general circulation models). The results suggest that already at a ΔT_g of 2 ° C and mainly in the subtropics, higher water scarcity would occur in >50% out of the 19 climate scenarios. Substantial biogeochemical and vegetation structural changes would also occur at 2 ° C, but mainly in subpolar and semiarid ecosystems. Other regions would be affected at higher ΔT_g levels, with lower intensity or with lower confidence. In total, mean global warming levels of 2 ° C, 3.5 ° C and 5 ° C are simulated to expose an additional 8%, 11% and 13% of the world population to new or aggravated water scarcity, respectively, with >50% confidence (while ∼1.3 billion people already live in water-scarce regions). Concurrently, substantial habitat transformations would occur in biogeographic regions that contain 1% (in zones affected at 2 ° C), 10% (3.5 ° C) and 74% (5 ° C) of present endemism-weighted vascular plant species, respectively. The results suggest nonlinear growth of impacts along with ΔT_g and highlight regional disparities in impact magnitudes and critical ΔT_g levels.

While the international community aims to limit global warming to below 2 ° C to prevent dangerous climate change, little progress has been made towards a global climate agreement to implement the emissions reductions required to reach this target. We use an integrated energy–economy–climate modeling system to examine how a further delay of cooperative action and technology availability affect climate mitigation challenges. With comprehensive emissions reductions starting after 2015 and full technology availability we estimate that maximum 21st century warming may still be limited below 2 ° C with a likely probability and at moderate economic impacts. Achievable temperature targets rise by up to ∼0.4 ° C if the implementation of comprehensive climate policies is delayed by another 15 years, chiefly because of transitional economic impacts. If carbon capture and storage (CCS) is unavailable, the lower limit of achievable targets rises by up to ∼0.3 ° C. Our results show that progress in international climate negotiations within this decade is imperative to keep the 2 ° C target within reach.

Soil microbial respiration (Rh) is a large but uncertain component of the terrestrial carbon cycle. Carbon–climate feedbacks associated with changes to Rh are likely, but Rh parameterization in Earth System Models (ESMs) has not been rigorously evaluated largely due to a lack of appropriate measurements. Here we assess, for the first time, Rh estimates from eight ESMs and their environmental drivers across several biomes against a comprehensive soil respiration database (SRDB-V2). Climatic, vegetation, and edaphic factors exert strong controls on annual Rh in ESMs, but these simple controls are not as apparent in the observations. This raises questions regarding the robustness of ESM projections of Rh in response to future climate change. Since there are many more soil respiration (Rs) observations than Rh data, two 'reality checks' for ESMs are also created using the Rs data. Guidance is also provided on the Rh improvement in ESMs.

The role of submarine groundwater discharge (SGD), the leakage of groundwater from aquifers into coastal waters, in coastal eutrophication has been demonstrated mostly for the North American and European coastlines, but poorly quantified in other regions. Here, we present the first spatially explicit global estimates of N inputs via SGD to coastal waters and show that it has increased from about 1.0 to 1.4 Tg of nitrate (NO₃-N) per year over the second half of the 20th century. Since this increase is not accompanied by an equivalent increase of groundwater phosphorus (P) and silicon (Si), SGD transport of nitrate is an important factor for the development of harmful algal blooms in coastal waters. Groundwater fluxes of N are linked to areas with high runoff and intensive anthropogenic activity on land, with Southeast Asia, parts of North and Central America, and Europe being hot spots.

Over the past 50 years, human water use has more than doubled and affected streamflow over various regions of the world. However, it remains unclear to what degree human water consumption intensifies hydrological drought (the occurrence of anomalously low streamflow). Here, we quantify over the period 1960–2010 the impact of human water consumption on the intensity and frequency of hydrological drought worldwide. The results show that human water consumption substantially reduced local and downstream streamflow over Europe, North America and Asia, and subsequently intensified the magnitude of hydrological droughts by 10–500%, occurring during nation- and continent-wide drought events. Also, human water consumption alone increased global drought frequency by 27 (±6)%. The intensification of drought frequency is most severe over Asia (35 ± 7%), but also substantial over North America (25 ± 6%) and Europe (20 ± 5%). Importantly, the severe drought conditions are driven primarily by human water consumption over many parts of these regions. Irrigation is responsible for the intensification of hydrological droughts over the western and central US, southern Europe and Asia, whereas the impact of industrial and households' consumption on the intensification is considerably larger over the eastern US and western and central Europe. Our findings reveal that human water consumption is one of the more important mechanisms intensifying hydrological drought, and is likely to remain as a major factor affecting drought intensity and frequency in the coming decades.

The summertime variability of the extratropical storm track over the Atlantic sector and its links to European climate have been analysed for the period 1948–2011 using observations and reanalyses. The main results are as follows. (1) The dominant mode of the summer storm track density variability is characterized by a meridional shift of the storm track between two distinct paths and is related to a bimodal distribution in the climatology for this region. It is also closely related to the Summer North Atlantic Oscillation (SNAO). (2) A southward shift is associated with a downstream extension of the storm track and a decrease in blocking frequency over the UK and northwestern Europe. (3) The southward shift is associated with enhanced precipitation over the UK and northwestern Europe and decreased precipitation over southern Europe (contrary to the behaviour in winter). (4) There are strong ocean–atmosphere interactions related to the dominant mode of storm track variability. The atmosphere forces the ocean through anomalous surface fluxes and Ekman currents, but there is also some evidence consistent with an ocean influence on the atmosphere, and that coupled ocean–atmosphere feedbacks might play a role. The ocean influence on the atmosphere may be particularly important on decadal timescales, related to the Atlantic Multidecadal Oscillation (AMO).

A functional measuring, monitoring, reporting and verification (MRV) system is essential to assess the additionality and impact on forest carbon in REDD+ (reducing emissions from deforestation and degradation) projects. This study assesses the MRV capacity and readiness of project developers at 20 REDD+ projects in Brazil, Peru, Cameroon, Tanzania, Indonesia and Vietnam, using a questionnaire survey and field visits. Nineteen performance criteria with 76 indicators were formulated in three categories, and capacity was measured with respect to each category. Of the 20 projects, 11 were found to have very high or high overall MRV capacity and readiness. At the regional level, capacity and readiness tended to be highest in the projects in Brazil and Peru and somewhat lower in Cameroon, Tanzania, Indonesia and Vietnam. Although the MRV capacities of half the projects are high, there are capacity deficiencies in other projects that are a source of concern. These are not only due to limitations in technical expertise, but can also be attributed to the slowness of international REDD+ policy formulation and the unclear path of development of the forest carbon market. Based on the study results, priorities for MRV development and increased investment in readiness are proposed.

The temperature response of atmosphere–ocean climate models is analyzed based on atmospheric CO₂ step-function-change simulations submitted to phase 5 of the Coupled Model Intercomparison Project (CMIP5). From these simulations and a control simulation, we estimate adjusted radiative forcing, the climate feedback parameter, and effective climate system thermal inertia, and we show that these results can be used to predict the temperature response to time-varying CO₂ concentrations. We evaluate several kinds of simple mathematical models for the CMIP5 simulation results, including single- and multiple-exponential models and a one-dimensional ocean-diffusion model. All of these functional forms, except the single-exponential model, can produce curves that fit most CMIP5 results quite well for both continuous and step-function CO₂-change pathways. Choice of model for any particular application would include consideration of factors such as the number of free parameters to be constrained and the conception of the underlying mechanistic model. Smooth curve fits to the CMIP5 simulation results realize approximately half (range 38%–61%) of equilibrium warming within the first decade after a CO₂ concentration increase, but approximately one quarter (range 14%–40%) of equilibrium warming occurs more than a century after the CO₂ increase. Following an instantaneous quadrupling of atmospheric CO₂, fits to four of the 20 simulation results reach 4 ° C of warming within the first decade, but fits to three of the 20 simulation results require more than a century to reach 4 ° C. These results indicate the need to reduce uncertainty in the temporal response of climate models and to consider this uncertainty when evaluating the risks posed by climate change.

One purpose of wind turbines is to provide pollution-free electric power at a reasonable price in an environmentally sound way. In this focus issue the latest research on the environmental impact of wind farms is presented. Offshore wind farms affect the marine fauna in both positive and negative ways. For example, some farms are safe havens for porpoises while other farms show fewer harbor porpoises even after ten years. Atmospheric computer experiments are carried out to investigate the possible impact and resource of future massive installations of wind turbines. The following questions are treated. What is the global capacity for energy production by the wind? Will the added turbulence and reduced wind speeds generated by massive wind farms cool or heat the surface? Can wind farms affect precipitation? It is also shown through life-cycle analysis how wind energy can reduce the atmospheric emission of eight air pollutants. Finally, noise generation and its impact on humans are studied.

Snow and ice algae are cold tolerant algae growing on the surface of snow and ice, and they play an important role in the carbon cycles for glaciers and snowfields in the world. Seasonal and altitudinal variations in seven major taxa of algae (green algae and cyanobacteria) were investigated on the Gulkana glacier in Alaska at six different elevations from May to September in 2001. The snow algal communities and their biomasses changed over time and elevation. Snow algae were rarely observed on the glacier in May although air temperature had been above 0 ° C since the middle of the month and surface snow had melted. In June, algae appeared in the lower areas of the glacier, where the ablation ice surface was exposed. In August, the distribution of algae was extended to the upper parts of the glacier as the snow line was elevated. In September, the glacier surface was finally covered with new winter snow, which terminated algal growth in the season. Mean algal biomass of the study sites continuously increased and reached 6.3 × 10 μl m⁻² in cell volume or 13 mg carbon m⁻² in September. The algal community was dominated by Chlamydomonas nivalis on the snow surface, and by Ancylonema nordenskiöldii and Mesotaenium berggrenii on the ice surface throughout the melting season. Other algae were less abundant and appeared in only a limited area of the glacier. Results in this study suggest that algae on both snow and ice surfaces significantly contribute to the net production of organic carbon on the glacier and substantially affect surface albedo of the snow and ice during the melting season.

Cryoconite is a microbe–mineral aggregate which darkens the ice surface of glaciers. Microbial process and marker gene PCR-dependent measurements reveal active and diverse cryoconite microbial communities on polar glaciers. Here, we provide the first report of a cryoconite metagenome and culture-independent study of alpine cryoconite microbial diversity. We assembled 1.2 Gbp of metagenomic DNA sequenced using an Illumina HiScanSQ from cryoconite holes across the ablation zone of Rotmoosferner in the Austrian Alps. The metagenome revealed a bacterially-dominated community, with Proteobacteria (62% of bacterial-assigned contigs) and Bacteroidetes (14%) considerably more abundant than Cyanobacteria (2.5%). Streptophyte DNA dominated the eukaryotic metagenome. Functional genes linked to N, Fe, S and P cycling illustrated an acquisitive trend and a nitrogen cycle based upon efficient ammonia recycling. A comparison of 32 metagenome datasets revealed a similarity in functional profiles between the cryoconite and metagenomes characterized from other cold microbe–mineral aggregates. Overall, the metagenomic snapshot reveals the cryoconite ecosystem of this alpine glacier as dependent on scavenging carbon and nutrients from allochthonous sources, in particular mosses transported by wind from ice-marginal habitats, consistent with net heterotrophy indicated by productivity measurements. A transition from singular snapshots of cryoconite metagenomes to comparative analyses is advocated.

Arctic snowpacks are often considered as chemical reactors for a variety of chemicals deposited through wet and dry events, but are overlooked as potential sites for microbial metabolism of reactive nitrogen species. The fate of deposited species is critical since warming leads to the transfer of contaminants to snowmelt-fed ecosystems. Here, we examined the role of microorganisms and the potential pathways involved in nitrogen cycling in the snow. Next generation sequencing data were used to follow functional gene abundances and a 16S rRNA (ribosomal ribonucleic acid) gene microarray was used to follow shifts in microbial community structure during a two-month spring-time field study at a high Arctic site, Svalbard, Norway (79° N). We showed that despite the low temperatures and limited water supply, microbial communities inhabiting the snow cover demonstrated dynamic shifts in their functional potential to follow several different pathways of the nitrogen cycle. In addition, microbial specific phylogenetic probes tracked different nitrogen species over time. For example, probes for Roseomonas tracked nitrate concentrations closely and probes for Caulobacter tracked ammonium concentrations after a delay of one week. Nitrogen cycling was also shown to be a dominant process at the base of the snowpack.

Globally, groundwater use is intensifying to meet demands for irrigation, urban supply, industrialization, and, in some instances, electrical power generation. In response to hydroclimatic variability, surface water is being substituted with groundwater, which must be viewed as a strategic resource for climate adaptation. In this sense, the supply of electricity for pumping is an adaptation policy tool. Additionally, planning for climate-change mitigation must consider CO₂ emissions resulting from pumping. This paper examines the influence of electricity supply and pricing on groundwater irrigation and resulting emissions, with specific reference to Mexico—a climate–water–energy 'perfect storm'. Night-time power supply at tariffs below the already-subsidized rates for agricultural groundwater use has caused Mexican farmers to increase pumping, reversing important water and electricity conservation gains achieved. Indiscriminate groundwater pumping, including for virtual water exports of agricultural produce, threatens the long-term sustainability of aquifers, non-agricultural water uses, and stream–aquifer interactions that sustain riparian ecosystems. Emissions resulting from agricultural groundwater pumping in Mexico are estimated to be 3.6% of total national emissions and are equivalent to emissions from transporting the same agricultural produce to market. The paper concludes with an assessment of energy, water, and climate trends coupled with policy futures to address these challenges.

In this study, we review federal datasets to assess the impacts of once-through power plant cooling systems on summer freshwater temperatures in the United States from 1996 to 2005. We find that maximum reported temperature discharges averaged 37 ° C (1996–2005) and were 9.5 ° C (1996–2000) to 10 ° C (2001–2005) higher than maximum reported intake temperatures during the summer. More than half of all power plant cooling systems report maximum temperature discharges that exceed 32 ° C and increase water temperatures enough to potentially impact aquatic life. However, current federal data on thermal discharges from power plants are insufficient to adequately assess their impact on in stream temperatures, or their subsequent effects on aquatic ecosystems and biodiversity. A preliminary analysis indicates that certain watersheds, primarily in the Southeastern and Midwestern United States, are good candidates for more focused study of power plant temperature impacts.

Since the European summer heat wave of 2003, considerable attention has been paid to the impacts of exceptional weather events on terrestrial ecosystems. While our understanding of the effects of summer drought on ecosystem carbon and water vapour fluxes has recently advanced, the effects of spring drought remain unclear. In Switzerland, spring 2011 (March–May) was the warmest and among the driest since the beginning of meteorological measurements. This study synthesizes Swiss FluxNet data from three grassland and two forest ecosystems to investigate the effects of this spring drought. Across all sites, spring phenological development was 11 days earlier in 2011 compared to the mean of 2000–2011. Soil moisture related reductions of gross primary productivity (GPP) were found at the lowland grassland sites, where productivity did not recover following grass cuts. In contrast, spring GPP was enhanced at the montane grassland and both forests (mixed deciduous and evergreen). Evapotranspiration (ET) was reduced in forests, which also substantially increased their water-use efficiency (WUE) during spring drought, but not in grasslands. These contrasting responses to spring drought of grasslands compared to forests reflect different adaptive strategies between vegetation types, highly relevant to biosphere–atmosphere feedbacks in the climate system.

Methane emissions from manure management represent an important mitigation opportunity, yet emission quantification methods remain crude and do not contain adequate detail to capture changes in agricultural practices that may influence emissions. Using the Canadian emission inventory methodology as an example, this letter explores three key aspects for improving emission quantification: (i) obtaining emission measurements to improve and validate emission model estimates, (ii) obtaining more useful activity data, and (iii) developing a methane emission model that uses the available farm management activity data. In Canada, national surveys to collect manure management data have been inconsistent and not designed to provide quantitative data. Thus, the inventory has not been able to accurately capture changes in management systems even between manure stored as solid versus liquid. To address this, we re-analyzed four farm management surveys from the past decade and quantified the significant change in manure management which can be linked to the annual agricultural survey to create a continuous time series. In the dairy industry of one province, for example, the percentage of manure stored as liquid increased by 300% between 1991 and 2006, which greatly affects the methane emission estimates. Methane emissions are greatest from liquid manure, but vary by an order of magnitude depending on how the liquid manure is managed. Even if more complete activity data are collected on manure storage systems, default Intergovernmental Panel on Climate Change (IPCC) guidance does not adequately capture the impacts of management decisions to reflect variation among farms and regions in inventory calculations. We propose a model that stays within the IPCC framework but would be more responsive to farm management by generating a matrix of methane conversion factors (MCFs) that account for key factors known to affect methane emissions: temperature, retention time and inoculum. This MCF matrix would be populated using a mechanistic emission model verified with on-farm emission measurements. Implementation of these MCF values will require re-analysis of farm surveys to quantify liquid manure emptying frequency and timing, and will rely on the continued collection of this activity data in the future. For model development and validation, emission measurement campaigns will be needed on representative farms over at least one full year, or manure management cycle (whichever is longer). The proposed approach described in this letter is long-term, but is required to establish baseline data for emissions from manure management systems. With these improvements, the manure management emission inventory will become more responsive to the changing practices on Canadian livestock farms.

Mitigation of the potential impacts of climate change is one of the leading policy concerns of the 21st century. However, there continues to be heated debate about the nature, the content and, most importantly, the impact of the policy actions needed to limit greenhouse gas emissions. One contributing factor is the lack of systematic evidence on the impact of mitigation policy on the welfare of the poor in developing countries. In this letter we consider two alternative policy scenarios, one in which only the Annex I countries take action, and the second in which the first policy is accompanied by a forest carbon sequestration policy in the non-Annex regions. Using an economic climate policy analysis framework, we assess the poverty impacts of the above policy scenarios on seven socio-economic groups in 14 developing countries. We find that the Annex-I-only policy is poverty friendly, since it enhances the competitiveness of non-Annex countries—particularly in agricultural production. However, once forest carbon sequestration incentives in the non-Annex regions are added to the policy package, the overall effect is to raise poverty in the majority of our sample countries. The reason for this outcome is that the dominant impacts of this policy are to raise returns to land, reduce agricultural output and raise food prices. Since poor households rely primarily on their own labor for income, and generally own little land, and since they also spend a large share of their income on food, they are generally hurt on both the earning and the spending fronts. This result is troubling, since forest carbon sequestration—particularly through avoided deforestation—is a promising, low cost option for climate change mitigation.

Recent warm, dry summers showed the vulnerability of the European power sector to low water availability and high river temperatures. Climate change is likely to impact electricity supply, in terms of both water availability for hydropower generation and cooling water usage for thermoelectric power production. Here, we show the impacts of climate change and changes in water availability and water temperature on European electricity production and prices. Using simulations of daily river flows and water temperatures under future climate (2031–2060) in power production models, we show declines in both thermoelectric and hydropower generating potential for most parts of Europe, except for the most northern countries. Based on changes in power production potentials, we assess the cost-optimal use of power plants for each European country by taking electricity import and export constraints into account. Higher wholesale prices are projected on a mean annual basis for most European countries (except for Sweden and Norway), with strongest increases for Slovenia (12–15%), Bulgaria (21–23%) and Romania (31–32% for 2031–2060), where limitations in water availability mainly affect power plants with low production costs. Considering the long design life of power plant infrastructures, short-term adaptation strategies are highly recommended to prevent undesired distributional and allocative effects.

Three broad approaches have emerged for energy and greenhouse gas (GHG) accounting for individual cities: (a) purely in-boundary source-based accounting (IB); (b) community-wide infrastructure GHG emissions footprinting (CIF) incorporating life cycle GHGs (in-boundary plus trans-boundary) of key infrastructures providing water, energy, food, shelter, mobility–connectivity, waste management/sanitation and public amenities to support community-wide activities in cities—all resident, visitor, commercial and industrial activities; and (c) consumption-based GHG emissions footprints (CBF) incorporating life cycle GHGs associated with activities of a sub-set of the community—its final consumption sector dominated by resident households. The latter two activity-based accounts are recommended in recent GHG reporting standards, to provide production-dominated and consumption perspectives of cities, respectively. Little is known, however, on how to normalize and report the different GHG numbers that arise for the same city. We propose that CIF and IB, since they incorporate production, are best reported per unit GDP, while CBF is best reported per capita. Analysis of input–output models of 20 US cities shows that GHG^CIF/GDP is well suited to represent differences in urban energy intensity features across cities, while GHG^CBF/capita best represents variation in expenditures across cities. These results advance our understanding of the methods and metrics used to represent the energy and GHG performance of cities.

Bioenergy has the unique potential to provide a dispatchable and carbon-negative component to renewable energy portfolios. However, the sustainability, spatial distribution, and capacity for bioenergy are critically dependent on highly uncertain land-use impacts of biomass agriculture. Biomass cultivation on abandoned agriculture lands is thought to reduce land-use impacts relative to biomass production on currently used croplands. While coarse global estimates of abandoned agriculture lands have been used for large-scale bioenergy assessments, more practical technological and policy applications will require regional, high-resolution information on land availability. Here, we present US county-level estimates of the magnitude and distribution of abandoned cropland and potential bioenergy production on this land using remote sensing data, agriculture inventories, and land-use modeling. These abandoned land estimates are 61% larger than previous estimates for the US, mainly due to the coarse resolution of data applied in previous studies. We apply the land availability results to consider the capacity of biomass electricity to meet the seasonal energy storage requirement in a national energy system that is dominated by wind and solar electricity production. Bioenergy from abandoned croplands can supply most of the seasonal storage needs for a range of energy production scenarios, regions, and biomass yield estimates. These data provide the basis for further down-scaling using models of spatially gridded land-use areas as well as a range of applications for the exploration of bioenergy sustainability.

Discontinuous permafrost in the North American boreal forest is strongly influenced by the effects of ecological succession on the accumulation of surface organic matter, making permafrost vulnerable to degradation resulting from fire disturbance. To assess factors affecting permafrost degradation after wildfire, we compared vegetation composition and soil properties between recently burned and unburned sites across three soil landscapes (rocky uplands, silty uplands, and sandy lowlands) situated within the Yukon Flats and Yukon-Tanana Uplands in interior Alaska. Mean annual air temperatures at our study sites from 2011 to 2012 were relatively cold (−5.5 ° C) and favorable to permafrost formation. Burning of mature evergreen forests with thick moss covers caused replacement by colonizing species in severely burned areas and recovery of pre-fire understory vegetation in moderately burned areas. Surface organic layer thickness strongly affected thermal regimes and thaw depths. On average, fire caused a five-fold decrease in mean surface organic layer thickness, a doubling of water storage in the active layer, a doubling of thaw depth, an increase in soil temperature at the surface (−0.6 to +2.1 ° C) and at 1 m depth (−1.7 to +0.4 ° C), and a two-fold increase in net soil heat input. Degradation of the upper permafrost occurred at all burned sites, but differences in soil texture and moisture among soil landscapes allowed permafrost to persist beneath the active layer in the silty uplands, whereas a talik of unknown depth developed in the rocky uplands and a thin talik developed in the sandy lowlands. A changing climate and fire regime would undoubtedly influence permafrost in the boreal forest, but the patterns of degradation or stabilization would vary considerably across the discontinuous permafrost zone due to differences in microclimate, successional patterns, and soil characteristics.

Climate change and permafrost thaw have been suggested to increase high latitude methane emissions that could potentially represent a strong feedback to the climate system. Using an integrated earth-system model framework, we examine the degradation of near-surface permafrost, temporal dynamics of inundation (lakes and wetlands) induced by hydro-climatic change, subsequent methane emission, and potential climate feedback. We find that increases in atmospheric CH₄ and its radiative forcing, which result from the thawed, inundated emission sources, are small, particularly when weighed against human emissions. The additional warming, across the range of climate policy and uncertainties in the climate-system response, would be no greater than 0.1 ° C by 2100. Further, for this temperature feedback to be doubled (to approximately 0.2 ° C) by 2100, at least a 25-fold increase in the methane emission that results from the estimated permafrost degradation would be required. Overall, this biogeochemical global climate-warming feedback is relatively small whether or not humans choose to constrain global emissions.

Forest residue has been proposed as a feasible candidate for cellulosic biofuels. However, the number of studies assessing its water use remains limited. This work aims to analyze the impacts of forest-based biofuel on water resources and quality by using a water footprint approach. A method established here is tailored to the production system, which includes softwood, hardwood, and short-rotation woody crops. The method is then applied to selected areas in the southeastern region of the United States to quantify the county-level water footprint of the biofuel produced via a mixed alcohol gasification process, under several logistic systems, and at various refinery scales. The results indicate that the blue water sourced from surface or groundwater is minimal, at 2.4 liters per liter of biofuel (l/l). The regional-average green water (rainfall) footprint falls between 400 and 443 l/l. The biofuel pathway appears to have a low nitrogen grey water footprint averaging 25 l/l at the regional level, indicating minimal impacts on water quality. Feedstock mix plays a key role in determining the magnitude and the spatial distribution of the water footprint in these regions. Compared with other potential feedstock, forest wood residue shows promise with its low blue and grey water footprint.

Climate-induced changes to permafrost are altering high latitude landscapes in ways that could increase the vulnerability of the vast soil carbon pools of the region. Permafrost thaw is temporally dynamic and spatially heterogeneous because, in addition to the thickening of the active layer, localized thermokarst features form when ice-rich permafrost thaws and the ground subsides. Thermokarst produces a diversity of landforms and alters the physical environment in dynamic ways. To estimate potential changes to the carbon cycle it is imperative to quantify the size and distribution of thermokarst landforms. By performing a supervised classification on a high resolution IKONOS image, we detected and mapped small, irregular thermokarst features occurring within an upland watershed in discontinuous permafrost of Interior Alaska. We found that 12% of the Eight Mile Lake (EML) watershed has undergone thermokarst, predominantly in valleys where tussock tundra resides. About 35% of the 3.7 km² tussock tundra class has likely transitioned to thermokarst. These landscape level changes created by permafrost thaw at EML have important implications for ecosystem carbon cycling because thermokarst features are forming in carbon-rich areas and are altering the hydrology in ways that increase seasonal thawing of the soil.

The diversity of ecosystems across boreal landscapes, successional changes after disturbance and complicated permafrost histories, present enormous challenges for assessing how vegetation, water and soil carbon may respond to climate change in boreal regions. To address this complexity, we used a chronosequence approach to assess changes in vegetation composition, water storage and soil organic carbon (SOC) stocks along successional gradients within four landscapes: (1) rocky uplands on ice-poor hillside colluvium, (2) silty uplands on extremely ice-rich loess, (3) gravelly–sandy lowlands on ice-poor eolian sand and (4) peaty–silty lowlands on thick ice-rich peat deposits over reworked lowland loess. In rocky uplands, after fire permafrost thawed rapidly due to low ice contents, soils became well drained and SOC stocks decreased slightly. In silty uplands, after fire permafrost persisted, soils remained saturated and SOC decreased slightly. In gravelly–sandy lowlands where permafrost persisted in drier forest soils, loss of deeper permafrost around lakes has allowed recent widespread drainage of lakes that has exposed limnic material with high SOC to aerobic decomposition. In peaty–silty lowlands, 2–4 m of thaw settlement led to fragmented drainage patterns in isolated thermokarst bogs and flooding of soils, and surface soils accumulated new bog peat. We were not able to detect SOC changes in deeper soils, however, due to high variability. Complicated soil stratigraphy revealed that permafrost has repeatedly aggraded and degraded in all landscapes during the Holocene, although in silty uplands only the upper permafrost was affected. Overall, permafrost thaw has led to the reorganization of vegetation, water storage and flow paths, and patterns of SOC accumulation. However, changes have occurred over different timescales among landscapes: over decades in rocky uplands and gravelly–sandy lowlands in response to fire and lake drainage, over decades to centuries in peaty–silty lowlands with a legacy of complicated Holocene changes, and over centuries in silty uplands where ice-rich soil and ecological recovery protect permafrost.

US cities are beginning to experiment with a regulatory approach to address information failures in the real estate market by mandating the energy benchmarking of commercial buildings. Understanding how a commercial building uses energy has many benefits; for example, it helps building owners and tenants identify poor-performing buildings and subsystems and it enables high-performing buildings to achieve greater occupancy rates, rents, and property values. This paper estimates the possible impacts of a national energy benchmarking mandate through analysis chiefly utilizing the Georgia Tech version of the National Energy Modeling System (GT-NEMS). Correcting input discount rates results in a 4.0% reduction in projected energy consumption for seven major classes of equipment relative to the reference case forecast in 2020, rising to 8.7% in 2035. Thus, the official US energy forecasts appear to overestimate future energy consumption by underestimating investments in energy-efficient equipment. Further discount rate reductions spurred by benchmarking policies yield another 1.3–1.4% in energy savings in 2020, increasing to 2.2–2.4% in 2035. Benchmarking would increase the purchase of energy-efficient equipment, reducing energy bills, CO₂ emissions, and conventional air pollution. Achieving comparable CO₂ savings would require more than tripling existing US solar capacity. Our analysis suggests that nearly 90% of the energy saved by a national benchmarking policy would benefit metropolitan areas, and the policy's benefits would outweigh its costs, both to the private sector and society broadly.

In this letter, we investigate the effects of crop yield and livestock feed efficiency scenarios on greenhouse gas (GHG) emissions from agriculture and land use change in developing countries. We analyze mitigation associated with different productivity pathways using the global partial equilibrium model GLOBIOM. Our results confirm that yield increase could mitigate some agriculture-related emissions growth over the next decades. Closing yield gaps by 50% for crops and 25% for livestock by 2050 would decrease agriculture and land use change emissions by 8% overall, and by 12% per calorie produced. However, the outcome is sensitive to the technological path and which factor benefits from productivity gains: sustainable land intensification would increase GHG savings by one-third when compared with a fertilizer intensive pathway. Reaching higher yield through total factor productivity gains would be more efficient on the food supply side but halve emissions savings due to a strong rebound effect on the demand side. Improvement in the crop or livestock sector would have different implications: crop yield increase would bring the largest food provision benefits, whereas livestock productivity gains would allow the greatest reductions in GHG emission. Combining productivity increases in the two sectors appears to be the most efficient way to exploit mitigation and food security co-benefits.

The vast amount of organic carbon (OC) stored in soils of the northern circumpolar permafrost region is a potentially vulnerable component of the global carbon cycle. However, estimates of the quantity, decomposability, and combustibility of OC contained in permafrost-region soils remain highly uncertain, thereby limiting our ability to predict the release of greenhouse gases due to permafrost thawing. Substantial differences exist between empirical and modeling estimates of the quantity and distribution of permafrost-region soil OC, which contribute to large uncertainties in predictions of carbon–climate feedbacks under future warming. Here, we identify research challenges that constrain current assessments of the distribution and potential decomposability of soil OC stocks in the northern permafrost region and suggest priorities for future empirical and modeling studies to address these challenges.

Increasing occurrences of climate extreme events urge us to study their impacts on terrestrial carbon sequestration. Ecosystem potential productivity deficits could characterize such impacts and display the ecosystem vulnerability and resilience to the extremes in climate change, whereas few studies have analyzed the yearly dynamics of forest potential productivity deficits. Based on a perfect-deficit approach, we used in situ eddy covariance flux data and meteorological observation data at Qianyanzhou station from 2003 to 2010 to explore the relationship between potential productivity and climate extremes, such as droughts in 2003 and 2007, ice rain in 2005, and an ice storm in 2008. We found (1) the monthly canopy photosynthetic capacity (CPC) deficits could be mainly explained by air temperature (Ta) deficits (R² = 0.45, p < 0.000 01); (2) a significant correlation was noted between seasonal CPC deficits and co-current Ta deficits (R² = 0.45, p < 0.000 01), especially in winter (R² = 0.79, p = 0.003); (3) drought in summer exerted a negatively lagged effect on potential productivity (R² = 0.59, p = 0.02), but at a short time scale; and (4) annual CPC deficits captured the impacts of climate extremes on the forest ecosystem potential productivity, and the two largest potential productivity deficits occurred in 2003 (relative CPC deficits = 0.34) and in 2005 (relative CPC deficits = 0.35), respectively. With the perfect-deficit approach, the forest ecosystem vulnerability to extremes was analyzed in a novel way.

During the austral summers of 2004 and 2009, we sampled a supraglacial stream on the Cotton Glacier, Antarctica. The stream dissolved organic matter (DOM) was low (44–48 μM C) and lacked detectable humic fluorescence signatures. Analysis of the excitation emissions matrices (EEMs) indicated that amino-acid fluorophores dominated, consistent with DOM of microbial origin, with little humic-like fluorescence. In most aquatic ecosystems, humic DOM attenuates harmful UV radiation and its absence may represent an additional stressor influencing the microbial community. Nonetheless, the stream contained an active microbial assemblage with bacterial cell abundances from 2.94 × 10⁴ to 4.97 × 10⁵ cells ml⁻¹, and bacterial production ranging from 58.8 to 293.2 ng C l⁻¹ d⁻¹. Chlorophyll-a concentrations ranged from 0.3 to 0.53 μg l⁻¹ indicating that algal phototrophs were the probable source of the DOM. Microbial isolates produced a rainbow of pigment colors, suggesting adaptation to stress, and were similar to those from other cryogenic systems (Proteobacteria and Bacteroidetes lineages). Supraglacial streams provide an example of contemporary microbial processes on the glacier surface and a natural laboratory for studying microbial adaptation to the absence of humics.

Pleistocene Yedoma permafrost contains nearly a third of all organic matter (OM) stored in circum-arctic permafrost and is characterized by the presence of massive ice wedges. Due to its rapid formation by sediment accumulation and subsequent frozen storage, Yedoma OM is relatively well preserved and highly biologically available (biolabile) upon thaw. A better understanding of the processes regulating Yedoma degradation is important to improve estimates of the response and magnitude of permafrost carbon feedbacks to climate warming. In this study, we examine the composition of ice wedges and the influence of ice wedge thaw on the biolability of Yedoma OM. Incubation assays were used to assess OM biolability, fluorescence spectroscopy to characterize the OM composition, and potential enzyme activity rates to examine the controls and regulation of OM degradation. We show that increasing amounts of ice wedge melt water in Yedoma-leached incubations enhanced the loss of dissolved OM over time. This may be attributed to the presence of low-molecular weight compounds and low initial phenolic content in the OM of ice wedges, providing a readily available substrate that promotes the degradation of Yedoma OC. The physical vulnerability of ice wedges upon thaw (causing irreversible collapse), combined with the composition of ice wedge-engrained OM (co-metabolizing old OM), underlines the particularly strong potential of Yedoma to generate a positive feedback to climate warming relative to other forms of non-ice wedge permafrost.

Cities now consume resources and produce waste in amounts that are incommensurate with the populations they contain. Quantifying and benchmarking the environmental impacts of cities is essential if urbanization of the world's growing population is to occur sustainably. Urban metabolism (UM) is a promising assessment form in that it provides the annual sum material and energy inputs, and the resultant emissions of the emergent infrastructural needs of a city's sociotechnical subsystems. By fusing UM and life cycle assessment (UM–LCA) this study advances the ability to quantify environmental impacts of cities by modeling pressures embedded in the flows upstream (entering) and downstream (leaving) of the actual urban systems studied, and by introducing an advanced suite of indicators. Applied to five global cities, the developed UM–LCA model provided enhanced quantification of mass and energy flows through cities over earlier UM methods. The hybrid model approach also enabled the dominant sources of a city's different environmental footprints to be identified, making UM–LCA a novel and potentially powerful tool for policy makers in developing and monitoring urban development policies. Combining outputs with socioeconomic data hinted at how these forces influenced the footprints of the case cities, with wealthier ones more associated with personal consumption related impacts and poorer ones more affected by local burdens from archaic infrastructure.

Increased snow depth already observed, and that predicted for the future are of critical importance to many geophysical and biological processes as well as human activities. The future characteristics of sub-arctic landscapes where permafrost is particularly vulnerable will depend on complex interactions between snow cover, vegetation and permafrost. An experimental manipulation was, therefore, set up on a lowland peat plateau with permafrost, in northernmost Sweden, to simulate projected future increases in winter precipitation and to study their effects on permafrost and vegetation. After seven years of treatment, statistically significant differences between manipulated and control plots were found in mean winter ground temperatures, which were 1.5 ° C higher in manipulated plots. During the winter, a difference in minimum temperatures of up to 9 ° C higher could be found in individual manipulated plots compared with control plots. Active layer thicknesses increased at the manipulated plots by almost 20% compared with the control plots and a mean surface subsidence of 24 cm was recorded in the manipulated plots compared to 5 cm in the control plots. The graminoid Eriophorum vaginatum has expanded in the manipulated plots and the vegetation remained green longer in the season.

The abundant thaw lakes and ponds in the circumarctic receive a new pool of organic carbon as permafrost peat soils degrade, which can be exposed to significant irradiance that potentially increases as climate warms and ice cover shortens. Exposure to sunlight is known to accelerate the transformation of dissolved organic matter (DOM) into molecules that can be more readily used by microbes. We sampled the water from two common classes of ponds found in the ice-wedge system of continuous permafrost regions of Canada, polygonal and runnel ponds, and followed the transformation of DOM over 12 days by looking at dissolved organic carbon (DOC) concentration and DOM absorption and fluorescence properties. The results indicate a relatively fast decay of color (3.4 and 1.6% loss d⁻¹ of absorption at 320 nm for the polygonal and runnel pond, respectively) and fluorescence (6.1 and 8.3% loss d⁻¹ of total fluorescent components, respectively) at the pond surface, faster in the case of humic-like components, but insignificant losses of DOC over the observed period. This result indicates that direct DOM mineralization (photochemical production of CO₂) is apparently minor in thaw ponds compared to the photochemical transformation of DOM into less chromophoric and likely more labile molecules with a greater potential for microbial mineralization. Therefore, DOM photolysis in arctic thaw ponds can be considered as a catalytic mechanism, accelerating the microbial turnover of mobilized organic matter from thawing permafrost and the production of greenhouse gases, especially in the most shallow ponds. Under a warming climate, this mechanism will intensify as summers lengthen.

The acceleration of electrons results in observable electromagnetic waves which can be used for remote sensing. Here, we make use of ∼4 Hz–66 MHz radio waves emitted by two consecutive intense positive lightning discharges to investigate their impact on the atmosphere above a thundercloud. It is found that the first positive lightning discharge initiates a sprite where electrons are accelerated during the exponential growth and branching of the sprite streamers. This preconditioned plasma above the thundercloud is subsequently exposed to a second positive lightning discharge associated with a bouncing-wave discharge. This discharge process causes a re-brightening of the existing sprite streamers above the thundercloud and initiates a subsequent relativistic electron beam.

Permafrost is tightly coupled to the organic soil layer, an interaction that mediates permafrost degradation in response to regional warming. We analyzed changes in permafrost occurrence and organic layer thickness (OLT) using more than 3000 soil pedons across a mean annual temperature (MAT) gradient. Cause and effect relationships between permafrost probability (PF), OLT, and other topographic factors were investigated using structural equation modeling in a multi-group analysis. Groups were defined by slope, soil texture type, and shallow (<28 cm) versus deep organic (≥28 cm) layers. The probability of observing permafrost sharply increased by 0.32 for every 10-cm OLT increase in shallow OLT soils (OLTs) due to an insulation effect, but PF decreased in deep OLT soils (OLTd) by 0.06 for every 10-cm increase. Across the MAT gradient, PF in sandy soils varied little, but PF in loamy and silty soils decreased substantially from cooler to warmer temperatures. The change in OLT was more heterogeneous across soil texture types—in some there was no change while in others OLTs soils thinned and/or OLTd soils thickened at warmer locations. Furthermore, when soil organic carbon was estimated using a relationship with thickness, the average increase in carbon in OLTd soils was almost four times greater compared to the average decrease in carbon in OLTs soils across all soil types. If soils follow a trajectory of warming that mimics the spatial gradients found today, then heterogeneities of permafrost degradation and organic layer thinning and thickening should be considered in the regional carbon balance.

The feasibility, cost, and air quality impacts of using electrical grids to shift water use from drought-stricken regions to areas with more water availability were examined. Power plant cooling represents a large portion of freshwater withdrawals in the United States, and shifting where electricity generation occurs can allow the grid to act as a virtual water pipeline, increasing water availability in regions with drought by reducing water consumption and withdrawals for power generation. During a 2006 drought, shifting electricity generation out of the most impacted areas of South Texas (∼10% of base case generation) to other parts of the grid would have been feasible using transmission and power generation available at the time, and some areas would experience changes in air quality. Although expensive, drought-based electricity dispatch is a potential parallel strategy that can be faster to implement than other infrastructure changes, such as air cooling or water pipelines.

Fire is an important factor controlling the composition and thickness of the organic layer in the black spruce forest ecosystems of interior Alaska. Fire that burns the organic layer can trigger dramatic changes in the underlying permafrost, leading to accelerated ground thawing within a relatively short time. In this study, we addressed the following questions. (1) Which factors determine post-fire ground temperature dynamics in lowland and upland black spruce forests? (2) What levels of burn severity will cause irreversible permafrost degradation in these ecosystems?

We evaluated these questions in a transient modeling–sensitivity analysis framework to assess the sensitivity of permafrost to climate, burn severity, soil organic layer thickness, and soil moisture content in lowland (with thick organic layers, ∼80 cm) and upland (with thin organic layers, ∼30 cm) black spruce ecosystems. The results indicate that climate warming accompanied by fire disturbance could significantly accelerate permafrost degradation. In upland black spruce forest, permafrost could completely degrade in an 18 m soil column within 120 years of a severe fire in an unchanging climate. In contrast, in a lowland black spruce forest, permafrost is more resilient to disturbance and can persist under a combination of moderate burn severity and climate warming.

Nitrification inhibitors have the potential to reduce N₂O emissions from maize fields, but optimal results may depend on deployment of integrated N fertilizer management systems that increase yields achieved per unit of N₂O lost. A new micro-encapsulated formulation of nitrapyrin for liquid N fertilizers became available to US farmers in 2010. Our research objectives were to (i) assess the impacts of urea–ammonium nitrate (UAN) management practices (timing, rate and nitrification inhibitor) and environmental variables on growing-season N₂O fluxes and (ii) identify UAN treatment combinations that both reduce N₂O emissions and optimize maize productivity. Field experiments near West Lafayette, Indiana in 2010 and 2011 examined three N rates (0, 90 and 180 kg N ha⁻¹), two timings (pre-emergence and side-dress) and presence or absence of nitrapyrin. Mean cumulative N₂O–N emissions (Q₁₀ corrected) were 0.81, 1.83 and 3.52 kg N₂O–N ha⁻¹ for the rates of 0, 90 and 180 kg N ha⁻¹, respectively; 1.80 and 2.31 kg N₂O–N ha⁻¹ for pre-emergence and side-dress timings, respectively; and 1.77 versus 2.34 kg N₂O–N ha⁻¹ for with and without nitrapyrin, respectively. Yield-scaled N₂O–N emissions increased with N rates as anticipated (averaging 167, 204 and 328 g N₂O–N Mg grain⁻¹ for the 0, 90 and 180 kg N ha⁻¹ rates), but were 22% greater with the side-dress timing than the pre-emergence timing (when averaged across N rates and inhibitor treatments) because of environmental conditions following later applications. Overall yield-scaled N₂O–N emissions were 22% lower with nitrapyrin than without the inhibitor, but these did not interact with N rate or timing.

Forests are major components of the carbon cycle, and disturbances are important influences of forest carbon. Our objective was to contribute to the understanding of forest carbon cycling by quantifying the amount of carbon in trees killed by two disturbance types, fires and bark beetles, in the western United States in recent decades. We combined existing spatial data sets of forest biomass, burn severity, and beetle-caused tree mortality to estimate the amount of aboveground and belowground carbon in killed trees across the region. We found that during 1984–2010, fires killed trees that contained 5–11 Tg C year⁻¹ and during 1997–2010, beetles killed trees that contained 2–24 Tg C year⁻¹, with more trees killed since 2000 than in earlier periods. Over their periods of record, amounts of carbon in trees killed by fires and by beetle outbreaks were similar, and together these disturbances killed trees representing 9% of the total tree carbon in western forests, a similar amount to harvesting. Fires killed more trees in lower-elevation forest types such as Douglas-fir than higher-elevation forest types, whereas bark beetle outbreaks also killed trees in higher-elevation forest types such as lodgepole pine and Engelmann spruce. Over 15% of the carbon in lodgepole pine and spruce/fir forest types was in trees killed by beetle outbreaks; other forest types had 5–10% of the carbon in killed trees. Our results document the importance of these natural disturbances in the carbon budget of the western United States.

Climate change has led to more frequent extreme winters (aka, dzud) and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–dzud and 2010 dzud were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between −1.5 and −0.5 and were statistically different (P < 0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (p < 0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI <− 1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (R² = 65 and 60, p < 0.05) than for the IM grassland biome (R² = 53, p < 0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and dzud) between the desert and grassland biomes on the Plateau.

Different methods have been developed for measuring carbon stocks and fluxes in the northern high latitudes, ranging from intensively measured small plots to space-based methods that use reflectance data to drive production efficiency models. The field of dendroecology has used samples of tree growth from radial increments to quantify long-term variability in ecosystem productivity, but these have very limited spatial domains. Since the cambium material in tree cores is itself a product of photosynthesis in the canopy, it would be ideal to link these two approaches. We examine the associations between the normalized differenced vegetation index (NDVI) and tree growth using 19 pairs of tree-ring widths (TRW) and maximum latewood density (MXD) across much of Siberia. We find consistent correlations between NDVI and both measures of tree growth and no systematic difference between MXD and TRW. At the regional level we note strong correspondence between the first principal component of tree growth and NDVI for MXD and TRW in a temperature-limited bioregion, indicating that canopy reflectance and cambial production are broadly linked. Using a network of 21 TRW chronologies from south of Lake Baikal, we find a similarly strong regional correspondence with NDVI in a markedly drier region. We show that tree growth is dominated by variation at decadal and multidecadal time periods, which the satellite record is incapable of recording given its relatively short record.

The demand for agricultural products continues to grow rapidly, but further agricultural expansion entails substantial environmental costs, making recultivating currently unused farmland an interesting alternative. The collapse of the Soviet Union in 1991 led to widespread abandonment of agricultural lands, but the extent and spatial patterns of abandonment are unclear. We quantified the extent of abandoned farmland, both croplands and pastures, across the region using MODIS NDVI satellite image time series from 2004 to 2006 and support vector machine classifications. Abandoned farmland was widespread, totaling 52.5 Mha, particularly in temperate European Russia (32 Mha), northern and western Ukraine, and Belarus. Differences in abandonment rates among countries were striking, suggesting that institutional and socio-economic factors were more important in determining the amount of abandonment than biophysical conditions. Indeed, much abandoned farmland occurred in areas without major constraints for agriculture. Our map provides a basis for assessing the potential of Central and Eastern Europe's abandoned agricultural lands to contribute to food or bioenergy production, or carbon storage, as well as the environmental trade-offs and social constraints of recultivation.

There is an urgent need to reduce the uncertainties in remotely sensed detection of phenological shifts of high latitude ecosystems in response to climate changes in past decades. In this study, vegetation phenology in western Arctic Russia (the Yamal Peninsula) was investigated by analyzing and comparing Normalized Difference Vegetation Index (NDVI) time series derived from the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and SPOT-Vegetation (VGT) during the decade 2000–2010. The spatial patterns of key phenological parameters were highly heterogeneous along the latitudinal gradients based on multi-satellite data. There was earlier SOS (start of the growing season), later EOS (end of the growing season), longer LOS (length of the growing season), and greater MaxNDVI from north to south in the region. The results based on MODIS and VGT data showed similar trends in phenological changes from 2000 to 2010, while quite a different trend was found based on AVHRR data from 2000 to 2008. A significantly delayed EOS (p < 0.01), thus increasing the LOS, was found from AVHRR data, while no similar trends were detected from MODIS and VGT data. There were no obvious shifts in MaxNDVI during the last decade. MODIS and VGT data were considered to be preferred data for monitoring vegetation phenology in northern high latitudes. Temperature is still a key factor controlling spatial phenological gradients and variability, while anthropogenic factors (reindeer husbandry and resource exploitation) might explain the delayed SOS in southern Yamal. Continuous environmental damage could trigger a positive feedback to the delayed SOS.

While grain crops are meeting much of the initial need for biofuels in the US, cellulosic or second generation (2G) materials are mandated to provide a growing portion of biofuel feedstocks. We sought to inform development of a 2G crop portfolio by assessing the profitability of novel cropping systems that potentially mitigate the negative effects of grain-based biofuel crops on food supply and environmental quality. We analyzed farm-gate costs and returns of five systems from an ongoing experiment in central Iowa, USA. The continuous corn cropping system was most profitable under current market conditions, followed by a corn–soybean rotation that incorporated triticale as a 2G cover crop every third year, and a corn–switchgrass system. A novel triticale–hybrid aspen intercropping system had the highest yields over the long term, but could only surpass the profitability of the continuous corn system when biomass prices exceeded foreseeable market values. A triticale/sorghum double cropping system was deemed unviable. We perceive three ways 2G crops could become more cost competitive with grain crops: by (1) boosting yields through substantially greater investment in research and development, (2) increasing demand through substantially greater and sustained investment in new markets, and (3) developing new schemes to compensate farmers for environmental benefits associated with 2G crops.

Data from a 500-year preindustrial control run of climate model INMCM4 show distinct climate variability in the Arctic and North Atlantic with a period of 35–50 years. The variability can be seen as anomalies of upper ocean density that appear in the Arctic and propagate to the North Atlantic. The density gradient in a northeast–southwest direction alternates with the density gradient in a northwest–southeast direction. A positive density anomaly in the Arctic is associated with a positive salinity anomaly, a positive surface temperature anomaly and a reduction of sea ice in the Barents and Kara Seas. The nature of the variability is a vertical advection of density by thermal currents similar to that proposed in Dijkstra et al (2008 Phil. Trans. R. Soc. A 366). The cycle of model variability shows that after a negative anomaly of density in the northwest Atlantic, one should expect warming in the Arctic in 5–10 years. The ensemble of decadal predictions with climate model INMCM4 starting from 1995 shows that warming in the western Arctic and especially in the Barents Sea observed in 1996–2010 can be reproduced by eight of ten ensemble members. Arctic climate predictability in this case is associated with a proposed mechanism of a 35–50 year North Atlantic–Arctic oscillation.

A growing body of literature discusses the CO₂ emissions of cities. Still, little is known about emission patterns across density gradients from remote rural places to highly urbanized areas, the drivers behind those emission patterns and the global emissions triggered by consumption in human settlements—referred to here as the carbon footprint. In this letter we use a hybrid method for estimating the carbon footprints of cities and other human settlements in the UK explicitly linking global supply chains to local consumption activities and associated lifestyles. This analysis comprises all areas in the UK, whether rural or urban. We compare our consumption-based results with extended territorial CO₂ emission estimates and analyse the driving forces that determine the carbon footprint of human settlements in the UK. Our results show that 90% of the human settlements in the UK are net importers of CO₂ emissions. Consumption-based CO₂ emissions are much more homogeneous than extended territorial emissions. Both the highest and lowest carbon footprints can be found in urban areas, but the carbon footprint is consistently higher relative to extended territorial CO₂ emissions in urban as opposed to rural settlement types. The impact of high or low density living remains limited; instead, carbon footprints can be comparatively high or low across density gradients depending on the location-specific socio-demographic, infrastructural and geographic characteristics of the area under consideration. We show that the carbon footprint of cities and other human settlements in the UK is mainly determined by socio-economic rather than geographic and infrastructural drivers at the spatial aggregation of our analysis. It increases with growing income, education and car ownership as well as decreasing household size. Income is not more important than most other socio-economic determinants of the carbon footprint. Possibly, the relationship between lifestyles and infrastructure only impacts carbon footprints significantly at higher spatial granularity.

Detection of changes in the hydrological cycles of permafrost regions is a critical issue in hydrology. Better understanding of groundwater dynamics in permafrost regions is needed to assess the vulnerability of the cryolithic water environment to changing climate. However, little is known about the age of groundwater in the Siberian Arctic region. In order to determine the residence time of permafrost groundwater in eastern Siberia, transient tracers including tritium (³H), chlorofluorocarbons (CFCs), and sulfur hexafluoride (SF₆) were used to analyze a mixture of supra-permafrost and intra-permafrost groundwater in the middle of the Lena River basin. Tritium analyses showed that the concentration ranges from 1.0 to 16.8 TU, and the apparent age of groundwater ranged from around 1 to 55 years. One of the spring waters appeared to contain more than 90% water recharged by precipitation before the 1960s nuclear testing era, and the water could be partly sourced from thawing permafrost. Comparisons of apparent groundwater ages estimated from different tracers imply that ³H and CFC-12 are the most applicable to groundwater vulnerability assessments in this region. Because the apparent age is a mixture of those from supra-permafrost and intra-permafrost groundwater, further analysis would be required to assess the contribution ratio of the two types of groundwater.

Electric power generation often involves the use of water for power plant cooling and steam generation, which typically involves the release of cooling water to nearby rivers and lakes. The resulting thermal pollution may negatively impact the ecosystems of these water bodies. Water resource systems models enable the examination of the implications of alternative electric generation on regional water resources. This letter documents the development, calibration, and validation of a climate-driven water resource systems model of the Apalachicola–Chattahoochee–Flint, the Alabama–Coosa–Tallapoosa, and the Tombigbee River basins in the states of Georgia, Alabama, and Florida, in the southeastern US. The model represents different water users, including power plants, agricultural water users, and municipal users. The model takes into account local population, per-capita use estimates, and changes in population growth. The water resources planning model was calibrated and validated against the observed, managed flows through the river systems of the three basins. Flow calibration was performed on land cover, water capacity, and hydraulic conductivity of soil horizons; river water temperature calibration was performed on channel width and slope properties. Goodness-of-fit statistics indicate that under 1980–2010 levels of water use, the model robustly represents major features of monthly average streamflow and water temperatures. The application of this integrated electricity generation–water resources planning model can be used to explore alternative electric generation and water implications. The implementation of this model is explored in the companion paper of this focus issue (Yates et al 2013 Environ. Res. Lett.8 035042).

Recent studies on the relationship between thermoelectric cooling and water resources have been made at coarse geographic resolution and do not adequately evaluate the localized water impacts on specific rivers and water bodies. We present the application of an integrated electricity generation–water resources planning model of the Apalachicola/Chattahoochee/Flint (ACF) and Alabama–Coosa–Tallapoosa (ACT) rivers based on the regional energy deployment system (ReEDS) and the water evaluation and planning (WEAP) system. A future scenario that includes a growing population and warmer, drier regional climate shows that benefits from a low-carbon, electricity fuel-mix could help maintain river temperatures below once-through coal-plants. These impacts are shown to be localized, as the cumulative impacts of different electric fuel-mix scenarios are muted in this relatively water-rich region, even in a warmer and drier future climate.

We compared planktonic primary and secondary production across twenty meltwater ponds on the surface of the McMurdo Ice Shelf in January 2007, including some ponds with basal brines created by meromictic stratification. Primary production ranged from 1.07 to 65.72 mgC m⁻³ h⁻¹ in surface waters. In stratified ponds primary production was always more than ten times higher in basal brines than in the corresponding mixolimnion. Regression tree analysis (r² = 0.80) identified inorganic nitrogen (as ${\mathrm{NH}}_{4}^{+}$) as the main factor limiting planktonic primary production. However, there was also evidence of inorganic carbon co-limitation of photosynthesis in some of the more oligotrophic waters. Neither C nor N limited carbon fixation at [NH₄–N] > 50 mg m⁻³, with photoinhibition the factor most likely limiting photosynthesis under such conditions. Primary production was the only factor significantly correlated to bacterial production and the relationship (r² = 0.56) was non-linear. Nitrogen limitation and tight coupling of planktonic primary and bacterial production is surprising in these ponds, as all have large pools of dissolved organic carbon (1.2–260 g m⁻³) and organic nitrogen (all >130 mg m⁻³). The dissolved pools of organic carbon and nitrogen appear to be recalcitrant and bacterial production to be constrained by limited release of labile organics from phytoplankton.

The aggregation of surface debris particles on melting glaciers into larger units (cryoconite) provides microenvironments for various microorganisms and metabolic processes. Here we investigate the microbial community on the surface of Aldegondabreen, a valley glacier in Svalbard which is supplied with carbon and nutrients from different sources across its surface, including colonies of seabirds. We used a combination of geochemical analysis (of surface debris, ice and meltwater), quantitative polymerase chain reactions (targeting the 16S ribosomal ribonucleic acid and amoA genes), pyrosequencing and multivariate statistical analysis to suggest possible factors driving the ecology of prokaryotic microbes on the surface of Aldegondabreen and their potential role in nitrogen cycling. The combination of high nutrient input with subsidy from the bird colonies, supraglacial meltwater flow and the presence of fine, clay-like particles supports the formation of centimetre-scale cryoconite aggregates in some areas of the glacier surface. We show that a diverse microbial community is present, dominated by the cyanobacteria, Proteobacteria, Bacteroidetes, and Actinobacteria, that are well-known in supraglacial environments. Importantly, ammonia-oxidizing archaea were detected in the aggregates for the first time on an Arctic glacier.

The Arctic net ecosystem exchange (NEE) of CO₂ between the land surface and the atmosphere is influenced by the timing of snow onset and melt. The objective of this study was to examine whether uncertainty in model estimates of NEE could be reduced by representing the influence of snow on NEE using remote sensing observations of snow cover area (SCA). Observations of NEE and time-lapse images of SCA were collected over four locations at a low Arctic site (Daring Lake, NWT) in May–June 2010. Analysis of these observations indicated that SCA influences NEE, and that good agreement exists between SCA derived from time-lapse images, Landsat and MODIS. MODIS SCA was therefore incorporated into the vegetation photosynthesis respiration model (VPRM). VPRM was calibrated using observations collected in 2005 at Daring Lake. Estimates of NEE were then generated over Daring Lake and Ivotuk, Alaska (2004–2007) using VPRM formulations with and without explicit representations of the influence of SCA on respiration and/or photosynthesis. Model performance was assessed by comparing VPRM output against unfilled eddy covariance observations from Daring Lake and Ivotuk (2004–2007). The uncertainty in VPRM estimates of NEE was reduced when respiration was estimated as a function of air temperature when SCA ≤ 50% and as a function of soil temperature when SCA > 50%.

Here, we assess current stress in the freshwater system based on the best available data in order to understand possible risks and vulnerabilities to regional water resources and the sectors dependent on freshwater. We present watershed-scale measures of surface water supply stress for the coterminous United States (US) using the water supply stress index (WaSSI) model which considers regional trends in both water supply and demand. A snapshot of contemporary annual water demand is compared against different water supply regimes, including current average supplies, current extreme-year supplies, and projected future average surface water flows under a changing climate. In addition, we investigate the contributions of different water demand sectors to current water stress. On average, water supplies are stressed, meaning that demands for water outstrip natural supplies in over 9% of the 2103 watersheds examined. These watersheds rely on reservoir storage, conveyance systems, and groundwater to meet current water demands. Overall, agriculture is the major demand-side driver of water stress in the US, whereas municipal stress is isolated to southern California. Water stress introduced by cooling water demands for power plants is punctuated across the US, indicating that a single power plant has the potential to stress water supplies at the watershed scale. On the supply side, watersheds in the western US are particularly sensitive to low flow events and projected long-term shifts in flow driven by climate change. The WaSSI results imply that not only are water resources in the southwest in particular at risk, but that there are also potential vulnerabilities to specific sectors, even in the 'water-rich' southeast.

Integrated assessment models suggest that the large-scale deployment of bioenergy could contribute to ambitious climate change mitigation efforts. However, such a shift would intensify the global competition for land, with possible consequences for 1.5 billion smallholder livelihoods that these models do not consider. Maintaining and enhancing robust livelihoods upon bioenergy deployment is an equally important sustainability goal that warrants greater attention. The social implications of biofuel production are complex, varied and place-specific, difficult to model, operationalize and quantify. However, a rapidly developing body of social science literature is advancing the understanding of these interactions. In this letter we link human geography research on the interaction between biofuel crops and livelihoods in developing countries to integrated assessments on biofuels. We review case-study research focused on first-generation biofuel crops to demonstrate that food, income, land and other assets such as health are key livelihood dimensions that can be impacted by such crops and we highlight how place-specific and global dynamics influence both aggregate and distributional outcomes across these livelihood dimensions. We argue that place-specific production models and land tenure regimes mediate livelihood outcomes, which are also in turn affected by global and regional markets and their resulting equilibrium dynamics. The place-specific perspective suggests that distributional consequences are a crucial complement to aggregate outcomes; this has not been given enough weight in comprehensive assessments to date. By narrowing the gap between place-specific case studies and global models, our discussion offers a route towards integrating livelihood and equity considerations into scenarios of future bioenergy deployment, thus contributing to a key challenge in sustainability sciences.

Climate models project considerable ranges and uncertainties in future climatic changes. To assess the potential impacts of climatic changes on mountain permafrost within these ranges of uncertainty, this study presents a sensitivity analysis using a permafrost process model combined with climate input based on delta-change approaches. Delta values comprise a multitude of coupled air temperature and precipitation changes to analyse long-term, seasonal and seasonal extreme changes on a typical low-ice content mountain permafrost location in the Swiss Alps. The results show that seasonal changes in autumn (SON) have the largest impact on the near-surface permafrost thermal regime in the model, and lowest impacts in winter (DJF). For most of the variability, snow cover duration and timing are the most important factors, whereas maximum snow height only plays a secondary role unless maximum snow heights are very small. At least for the low-ice content site of this study, extreme events have only short-term effects and have less impact on permafrost than long-term air temperature trends.

Variations in the annual mean of the galactic cosmic ray flux (GCR) are compared with annual variations in the most common meteorological variables: temperature, mean sea-level barometric pressure, and precipitation statistics. A multiple regression analysis was used to explore the potential for a GCR response on timescales longer than a year and to identify 'fingerprint' patterns in time and space associated with GCR as well as greenhouse gas (GHG) concentrations and the El Niño–Southern Oscillation (ENSO). The response pattern associated with GCR consisted of a negative temperature anomaly that was limited to parts of eastern Europe, and a weak anomaly in the sea-level pressure (SLP), but coincided with higher pressure over the Norwegian Sea. It had a similarity to the North Atlantic Oscillation (NAO) in the northern hemisphere and a wave train in the southern hemisphere. A set of Monte Carlo simulations nevertheless indicated that the weak amplitude of the global mean temperature response associated with GCR could easily be due to chance (p-value = 0.6), and there has been no trend in the GCR. Hence, there is little empirical evidence that links GCR to the recent global warming.

The relationship between urban form and greenhouse gas (GHG) emissions has been studied extensively during the last two decades. The prevailing paradigm arising from these studies is that a dense or compact urban form would best enable low-carbon living. However, the vast majority of these studies have actually concentrated on transportation and/or housing energy, whereas a growing number of studies argue that the GHG implications of other consumption should be taken into account and the relationships evaluated. With this two-part study of four different area types in Finland we illustrate the importance of including all the consumption activities into the GHG assessment. Furthermore, we add to the discussion the idea that consumption choices, or lifestyles, and the resulting GHGs are not just a product of the values of individuals but actually tied to the form of the surrounding urbanization: that is, lifestyles are situated. In part I (Heinonen et al 2013 Environ. Res. Lett.8 025003) we looked into this situation in Finland, showing how the residents of the most urbanized areas bring about the highest GHG emissions due to their higher consumption volumes and the economies-of-scale advantages in the less urbanized areas. In part II here, we concentrate only on the middle-income segment and look for differences in the lifestyles when the budget constraints are equal. Here we also add the variables housing type and motorization into the assessment. The same time-use and private expenditure data as in part I and the same GHG assessment method are used here to maintain high transparency and comparability between the two parts. The results of the study imply that larger family sizes and economies-of-scale effects in the less dense areas offset the advantages of more dense living when the emissions are assessed on per capita basis. Also, at equal income levels the carbon footprints vary surprisingly little due to complementary effects of the majority of low-carbon lifestyle choices. Motorization was still found to increase the emissions, but a similar pattern regarding housing type was not found.

The spatial and temporal variability of net ecosystem exchange (NEE) of CO₂ and evapotranspiration (ET) of a karst-hole sphagnum peat mire situated at the boundary between broad-leaved and forest–steppe zones in the central part of European Russia in the Tula region was described using results from field measurements. NEE and ET were measured using a portable measuring system consisting of a transparent ventilated chamber combined with an infrared CO₂/H₂O analyzer, LI-840A (Li-Cor, USA) along a transect from the southern peripheral part of the mire to its center under sunny clear-sky weather conditions in the period from May to September of 2012 and in May 2013. The results of the field measurements showed significant spatial and temporal variability of NEE and ET that was mainly influenced by incoming solar radiation and ground water level. The seasonal patterns of NEE and ET within the mire were quite different. During the entire growing season the central part of the mire was a sink of CO₂ for the atmosphere. NEE reached maximal values in June–July (−6.8 ± 4.2 μmol m⁻² s⁻¹). The southern peripheral part of the mire, due to strong shading by the surrounding forest, was a sink of CO₂ for the atmosphere in June–July only. ET reached maximal values in the well-lighted central parts of the mire in May (0.34 ± 0.20 mm h⁻¹) mainly because of high air and surface temperatures and the very wet upper peat horizon and sphagnum moss. Herbaceous species made the maximum contribution to the total gross primary production (GPP) in both the central and the peripheral parts of the mire. The contribution of sphagnum to the total GPP of these plant communities was relatively small and ranged on sunny days of July–August from −1.1 ± 1.1 mgC g⁻¹ of dry weight (DW) per hour in the peripheral zone of the mire to −0.6 ± 0.2 mgC g⁻¹ DW h⁻¹ at the mire center. The sphagnum layer made the maximum contribution to total ET at the mire center (0.25 ± 0.10 mm h⁻¹) and the herbaceous species on the peripheral part of the mire (0.03 ± 0.03 mm h⁻¹).

Carbon footprint is a key indicator of the contribution of food production to climate change and its importance is increasing worldwide. Although it has been used as a sustainability index for assessing production systems, it does not take into account many other biophysical environmental dimensions more relevant at the local scale, such as soil erosion, nutrient imbalance, and pesticide contamination. We estimated carbon footprint, fossil fuel energy use, soil erosion, nutrient imbalance, and risk of pesticide contamination for five real beef background-finishing systems with increasing levels of intensification in Uruguay, which were combinations of grazing rangelands (RL), seeded pastures (SP), and confined in feedlot (FL). Carbon footprint decreased from 16.7 (RL–RL) to 6.9 kg (SP–FL) CO₂ eq kg body weight⁻¹ (BW; 'eq': equivalent). Energy use was zero for RL–RL and increased up to 17.3 MJ kg BW⁻¹ for SP–FL. Soil erosion values varied from 7.7 (RL–RL) to 14.8 kg of soil kg BW⁻¹ (SP–FL). Nitrogen and phosphorus nutrient balances showed surpluses for systems with seeded pastures and feedlots while RL–RL was deficient. Pesticide contamination risk was zero for RL–RL, and increased up to 21.2 for SP–FL. For the range of systems studied with increasing use of inputs, trade-offs were observed between global and local environmental problems. These results demonstrate that several indicators are needed to evaluate the sustainability of livestock production systems.