Table of contents

Wynes and Nicholas (2017Environ. Res. Lett.12 074024) claim that some of the most important actions individuals can take to mitigate climate change have been overlooked, particularly in educational messages for adolescents, and estimate the potential impact of some of these, including having fewer children and living car free. These estimates raise questions that deserve serious analysis, but they are based only on the technical potential of the actions and do not consider the plasticity of the behaviors and the feasibility of policies to support them. The actions identified as having the greatest potential are lifestyle changes that accrue benefits over a lifetime or longer, so are not realistic alternatives to actions that can be enacted immediately. But presenting lifestyle choices and the relative impacts of different actions as discussion starters for adolescents could be promising, especially if the discussions highlight issues of behavioral plasticity, policy plasticity, and time scale. Research has identified design principles for interventions to achieve the strongest emissions reductions at time scales up to the decadal. Design principles for achieving longer-lasting changes deserve careful analytic attention, as well as a stronger focus in adolescent textbooks and messages to the general population. Both adolescents and researchers would do well to think carefully about what could promote the generational changes needed to reach a climate change target such as 'well below 2 °C'.

Brazil's Rural Environmental Registry (CAR) is a potentially promising avenue to slow deforestation on private properties as it facilitates the monitoring of land use. Yet limited empirical evidence exists on how the CAR affects smallholders' behavior and recent scholarly efforts have in fact indicated that it may be doing less to protect forests than previously assumed. Based on 1177 smallholder surveys conducted in the Cerrado, we assess 1) whether the CAR might incentivize smallholders to pursue deforestation and 2) which factors are associated with smallholders' intended deforestation behavior. We find that upon CAR registration, factors significantly associated with smallholders' intention to deforest are: the existing percentage of native vegetation on the property, the use of agricultural loans, property owner's age, and livestock production experience. To curb deforestation that may follow expressed intentions of smallholders, the CAR, and environmental registration programs alike, should account for existing land use by, for example, improving the system already in place for trading areas of native vegetation as this system is not widely adopted by those smallholders with more native vegetation than the legal cut-off. Also, such programs should assess the role of whether conditions related to land cover maintenance may protect against deforestation if credit access is supported especially to younger smallholders and/or livestock producers with a high percentage of native vegetation in their properties.

Climate change is altering the dynamics of terrestrial vegetation, with consequences for the functioning of Earth's biomes and the provisioning of ecosystem services. Changes in forest dynamics due to drought events or short-term drying trends have been described at different ecological scales, but few observational studies have determined the relative effects of short- and long-term precipitation trends (e.g. decade and century, respectively) on forest canopy structure and functioning. Using gridded annual precipitation maps from 1920 to 2012, and temporal data from airborne light detection and ranging (LiDAR) and MODIS Enhanced Vegetation Index (EVI), we present evidence for a large-scale decline in forest canopy volume (area vs. height) and greenness (a metric of photosynthetic function) driven by a long-term drying trend on Hawaii island. Decreases in canopy greenness were observed in step with shorter-term (10 y) precipitation declines, but decreases in greenness were two-fold greater where longer-term (∼100 y) precipitation declines had occurred. Canopy volume mainly reduced where long-term precipitation declines occurred. We conclude that long-term precipitation trends critically impact forest canopy structure and functioning, which likely has cascading consequences for numerous ecological processes such as subcanopy light availability, species interactions, carbon storage, and animal habitat.

Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil's national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

Gold mining in Amazonia involves forest removal, soil excavation, and the use of liquid mercury, which together pose a major threat to biodiversity, water quality, forest carbon stocks, and human health. Within the global biodiversity hotspot of Madre de Dios, Peru, gold mining has continued despite numerous 2012 government decrees and enforcement actions against it. Mining is now also thought to have entered federally protected areas, but the rates of miner encroachment are unknown. Here, we utilize high-resolution remote sensing to assess annual changes in gold mining extent from 1999 to 2016 throughout the Madre de Dios region, including the high-diversity Tambopata National Reserve and buffer zone. Regionally, gold mining-related losses of forest averaged 4437 ha yr⁻¹. A temporary downward inflection in the annual growth rate of mining-related forest loss following 2012 government action was followed by a near doubling of the deforestation rate from mining in 2013–2014. The total estimated area of gold mining throughout the region increased about 40% between 2012 and 2016, including in the Tambopata National Reserve. Our results reveal an urgent need for more socio-environmental effort and law enforcement action to combat illegal gold mining in the Peruvian Amazon.

Information about past volcanic impact on climate is mostly derived from historic documentary data and sulfate depositions in polar ice sheets. Although these archives have provided important insights into the Earth's volcanic eruption history, the climate forcing and exact dating of many events is still vague. Here we apply a new method of break detection to the first millennium-length maximum latewood density reconstruction of Northern Hemisphere summer temperatures to develop an alternative record of large volcanic eruptions. The analysis returns fourteen outstanding cooling events, all of which agree well with recently developed volcanic forcing records from high-resolution bipolar ice cores. In some cases, however, the climatic impact detected with our new method peaks in neighboring years, likely due to either dating errors in the polar ice cores or uncertainty in the interpretation of atmospheric aerosol transport to polar ice core locations. The most apparent mismatches between forcing and cooling estimates occur in the 1450s and 1690s. Application of the algorithm to two additional and recently developed reconstructions that blend maximum latewood density and ring width data reproduces twelve of the detected events among which eight are retrieved in all three of the dendroclimatic reconstructions. Collectively, the new estimates of volcanic activity with precise age control provide independent evidence for forcing records during the last millennium. Evaluating the cooling magnitude in response to detected events yields an upper benchmark for the volcanic impact on climate. The average response to the ten major events in the density derived reconstruction is −0.60 °C ± 0.13 °C. Other last millennium temperature records from proxies and model simulations reveal higher cooling estimates, which is, to some degree, related to the very different high frequency variance in these timeseries.

Typically 20–40 extreme cyclone events (sometimes called 'weather bombs') occur in the Arctic North Atlantic per winter season, with an increasing trend of 6 events/decade over 1979–2015, according to 6 hourly station data from Ny-Ålesund. This increased frequency of extreme cyclones is consistent with observed significant winter warming, indicating that the meridional heat and moisture transport they bring is a factor in rising temperatures in the region. The winter trend in extreme cyclones is dominated by a positive monthly trend of about 3–4 events/decade in November–December, due mainly to an increasing persistence of extreme cyclone events. A negative trend in January opposes this, while there is no significant trend in February. We relate the regional patterns of the trend in extreme cyclones to anomalously low sea-ice conditions in recent years, together with associated large-scale atmospheric circulation changes such as 'blockinglike' circulation patterns (e.g. Scandinavian blocking in December and Ural blocking during January–February).

Regional temperature changes are a crucial factor in affecting agriculture, ecosystems and societies, which depend greatly on local temperatures. We identify a nonuniform warming pattern in summer around the mid-1990s over the Eurasian continent, with a predominant amplified warming over Europe–West Asia and Northeast Asia but much weaker warming over Central Asia. It is found that the nonuniform warming concurs with both the phase shift of the Atlantic Multi-decadal Oscillation (AMO) and the decadal change in the Silk Road Pattern (SRP), which is an upper-tropospheric teleconnection pattern over the Eurasian continent during summer. We suggest that the AMO may modulate the decadal change in SRP and then induce the zonal asymmetry in temperature changes. Our results have important implications for decadal prediction of regional warming pattern in Eurasia based on the predictable AMO.

A single layer urban canopy model (SLUCM) with enhanced hydrologic processes, is evaluated in a tropical city, Singapore. The evaluation was performed using an 11 month offline simulation with the coupled Noah land surface model/SLUCM over a compact low-rise residential area. Various hydrological processes are considered, including anthropogenic latent heat release, and evaporation from impervious urban facets. Results show that the prediction of energy fluxes, in particular latent heat flux, is improved when these processes were included. However, the simulated latent heat flux is still underestimated by ∼40%. Considering Singapore's high green cover ratio, the tree evapotranspiration process is introduced into the model, which significantly improves the simulated latent heat flux. In particular, the systematic error of the model is greatly reduced, and becomes lower than the unsystematic error in some seasons. The effect of tree evapotranspiration on the urban surface energy balance is further demonstrated during an unusual dry spell. The present study demonstrates that even at sites with relatively low (11%) tree coverage, ignoring evapotranspiration from trees may cause serious underestimation of the latent heat flux and atmospheric humidity. The improved model is also transferable to other tropical or temperate regions to study the impact of tree evapotranspiration on urban climate.

A 2007 earthquake in the western Solomon Islands resulted in a localised subsidence event in which sea level (relative to the previous coastal settings) rose approximately 30–70 cm, providing insight into impacts of future rapid changes to sea level on coastal ecosystems. Here, we show that increasing sea level by 30–70 cm can have contrasting impacts on mangrove, seagrass and coral reef ecosystems. Coral reef habitats were the clear winners with a steady lateral growth from 2006–2014, yielding a 157% increase in areal coverage over seven years. Mangrove ecosystems, on the other hand, suffered the largest impact through a rapid dieback of 35% (130 ha) of mangrove forest in the study area after subsidence. These forests, however, had partially recovered seven years after the earthquake albeit with a different community structure. The shallow seagrass ecosystems demonstrated the most dynamic response to relative shifts in sea level with both losses and gains in areal extent at small scales of 10–100 m. The results of this study emphasize the importance of considering the impacts of sea-level rise within a complex landscape in which winners and losers may vary over time and space.

This work introduces a generalizable approach for estimating the field-scale agricultural yield losses due to soil salinization. When integrated with regional data on crop yields and prices, this model provides high-resolution estimates for revenue losses over large agricultural regions. These methods account for the uncertainty inherent in model inputs derived from satellites, experimental field data, and interpreted model results. We apply this method to estimate the effect of soil salinity on agricultural outputs in California, performing the analysis with both high-resolution (i.e. field scale) and low-resolution (i.e. county-scale) data sources to highlight the importance of spatial resolution in agricultural analysis. We estimate that soil salinity reduced agricultural revenues by $3.7 billion ($1.7–$7.0 billion) in 2014, amounting to 8.0 million tons of lost production relative to soil salinities below the crop-specific thresholds. When using low-resolution data sources, we find that the costs of salinization are underestimated by a factor of three. These results highlight the need for high-resolution data in agro-environmental assessment as well as the challenges associated with their integration.

Food security will be increasingly challenged by climate change, natural resource degradation, and population growth. Wheat yields, in particular, have already stagnated in many regions and will be further affected by warming temperatures. Despite these challenges, wheat yields can be increased by improving management practices in regions with existing yield gaps. To identify the magnitude and causes of current yield gaps in India, one of the largest wheat producers globally, we produced 30 meter resolution yield maps from 2001 to 2015 across the Indo-Gangetic Plains (IGP), the nation's main wheat belt. Yield maps were derived using a new method that translates satellite vegetation indices to yield estimates using crop model simulations, bypassing the need for ground calibration data. This is one of the first attempts to apply this method to a smallholder agriculture system, where ground calibration data are rarely available. We find that yields can be increased by 11% on average and up to 32% in the eastern IGP by improving management to current best practices within a given district. Additionally, if current best practices from the highest-yielding state of Punjab are implemented in the eastern IGP, yields could increase by almost 110%. Considering the factors that most influence yields, later sow dates and warmer temperatures are most associated with low yields across the IGP. This suggests that strategies to reduce the negative effects of heat stress, like earlier sowing and planting heat-tolerant wheat varieties, are critical to increasing wheat yields in this globally-important agricultural region.

We provide evidence from a nationally representative survey on Americans' willingness to pay (WTP) for a carbon tax, and public preferences for how potential carbon-tax revenue should be spent. The average WTP for a tax on fossil fuels that increases household energy bills is US$177 per year. This translates into an average WTP of 14% more on average for households across the United States, where energy costs differ significantly across states. Regarding the tax revenues, Americans are most in support of using the money to invest in clean energy and infrastructure. There is relatively less support for reducing income or payroll taxes, returning dividends to households, and other expenditure categories. Finally, Americans support using the tax revenues to assist displaced workers in the coal industry enough to compensate each miner nearly US$146 000 upon passage of a carbon tax.

Increasing atmospheric methane (CH₄) concentrations have contributed to approximately 20% of anthropogenic climate change. Despite the importance of CH₄ as a greenhouse gas, its atmospheric growth rate and dynamics over the past two decades, which include a stabilization period (1999–2006), followed by renewed growth starting in 2007, remain poorly understood. We provide an updated estimate of CH₄ emissions from wetlands, the largest natural global CH₄ source, for 2000–2012 using an ensemble of biogeochemical models constrained with remote sensing surface inundation and inventory-based wetland area data. Between 2000–2012, boreal wetland CH₄ emissions increased by 1.2 Tg yr⁻¹ (−0.2–3.5 Tg yr⁻¹), tropical emissions decreased by 0.9 Tg yr⁻¹ (−3.2−1.1 Tg yr⁻¹), yet globally, emissions remained unchanged at 184 ± 22 Tg yr⁻¹. Changing air temperature was responsible for increasing high-latitude emissions whereas declines in low-latitude wetland area decreased tropical emissions; both dynamics are consistent with features of predicted centennial-scale climate change impacts on wetland CH₄ emissions. Despite uncertainties in wetland area mapping, our study shows that global wetland CH₄ emissions have not contributed significantly to the period of renewed atmospheric CH₄ growth, and is consistent with findings from studies that indicate some combination of increasing fossil fuel and agriculture-related CH₄ emissions, and a decrease in the atmospheric oxidative sink.

Despite the backdrop of continuous global warming, sea ice extent has been found not to consistently decrease across the globe, and instead exhibit heterogeneous variability at middle to high latitudes. However, the existing studies are focused primarily on high latitude frozen seas, while studies on the long-term variability of sea ice cover at middle latitudes are generally lacking. Afforded by continuous satellite imagery, evolution of sea ice cover over nearly three decades from 1988 to 2015 in the Bohai Sea as a peculiar mid-latitude frozen sea area is reported for the first time. An anomalous trend of slight overall increase of 1.38 ± 1.00% yr^–1 (R = 1.38, i.e. at a statistical significance of 80%) in Bohai Sea ice extent was observed over the 28 year period. The detrended annual average ice area (AAIA) was further found to correlate with a slight decreasing mean ice-period average temperature (IAT, r = –0.58, p < 0.01) of 11 meteorological stations around the Bohai Sea as well as a mild increasing cumulative freezing degree days (CFDD, r = 0.65, p < 0.01). Correlation with decreasing Arctic Oscillation (AO) index (r = –0.60, p < 0.01) and North Atlantic Oscillation (NAO) index (r = –0.69, p < 0.01) over the study period suggested AO and NAO as the primary large-scale climate factors for Bohai Sea ice. In addition, the seasonal cycle of ice cover showed a single peak with longer freezing phase than melting phase, due to the different temperature change rate during the freezing and melting phases. The results can provide important references for monitoring the recent climate change in the region and beyond.

We estimate the lifetime magnitude and distribution of the private and public benefits and costs of currently installed distributed solar PV systems in the United States. Using data for recently-installed systems, we estimate the balance of benefits and costs associated with installing a non-utility solar PV system today. We also study the geographical distribution of the various subsidies that are made available to owners of rooftop solar PV systems, and compare it to distributions of population and income. We find that, after accounting for federal subsidies and local rebates and assuming a discount rate of 7%, the private benefits of new installations will exceed private costs only in seven of the 19 states for which we have data and only if customers can sell excess power to the electric grid at the retail price. These states are characterized by abundant sunshine (California, Texas and Nevada) or by high electricity prices (New York). Public benefits from reduced air pollution and climate change impact exceed the costs of the various subsidies offered system owners for less than 10% of the systems installed, even assuming a 2% discount rate. Subsidies flowed disproportionately to counties with higher median incomes in 2006. In 2014, the distribution of subsidies was closer to that of population income, but subsidies still flowed disproportionately to the better-off. The total, upfront, subsidy per kilowatt of installed capacity has fallen from $5200 in 2006 to $1400 in 2014, but the absolute magnitude of subsidy has soared as installed capacity has grown explosively. We see considerable differences in the balance of costs and benefits even within states, indicating that local factors such as system price and solar resource are important, and that policies (e.g. net metering) could be made more efficient by taking local conditions into account.

While carbon dioxide emissions from energy use must be the primary target of climate change mitigation efforts, land use and land cover change (LULCC) also represent an important source of climate forcing. In this study we compute time series of global surface temperature change separately for LULCC and non-LULCC sources (primarily fossil fuel burning), and show that because of the extra warming associated with the co-emission of methane and nitrous oxide with LULCC carbon dioxide emissions, and a co-emission of cooling aerosols with non-LULCC emissions of carbon dioxide, the linear relationship between cumulative carbon dioxide emissions and temperature has a two-fold higher slope for LULCC than for non-LULCC activities. Moreover, projections used in the Intergovernmental Panel on Climate Change (IPCC) for the rate of tropical land conversion in the future are relatively low compared to contemporary observations, suggesting that the future projections of land conversion used in the IPCC may underestimate potential impacts of LULCC. By including a 'business as usual' future LULCC scenario for tropical deforestation, we find that even if all non-LULCC emissions are switched off in 2015, it is likely that 1.5 °C of warming relative to the preindustrial era will occur by 2100. Thus, policies to reduce LULCC emissions must remain a high priority if we are to achieve the low to medium temperature change targets proposed as a part of the Paris Agreement. Future studies using integrated assessment models and other climate simulations should include more realistic deforestation rates and the integration of policy that would reduce LULCC emissions.

Diesel cars have been emitting four to seven times more NO_x in on-road driving than in type approval tests. These 'excess emissions' are a consequence of deliberate design of the vehicle's after-treatment system, as investigations during the 'Dieselgate' scandal have revealed. Here we calculate health and environmental impacts of these excess NO_x emissions in all European countries for the year 2013. We use national emissions reported officially under the UNECE Convention for Long-range Transport of Atmospheric Pollutants and employ the EMEP MSC-W Chemistry Transport Model and the GAINS Integrated Assessment Model to determine atmospheric concentrations and resulting impacts. We compare with impacts from hypothetical emissions where light duty diesel vehicles are assumed to emit only as much as their respective type approval limit value or as little as petrol cars of the same age. Excess NO₂ concentrations can also have direct health impacts, but these overlap with the impacts from particulate matter (PM) and are not included here. We estimate that almost 10 000 premature deaths from PM_2.5 and ozone in the adult population (age >30 years) can be attributed to the NO_x emissions from diesel cars and light commercial vehicles in EU28 plus Norway and Switzerland in 2013. About 50% of these could have been avoided if diesel limits had been achieved also in on-road driving; and had diesel cars emitted as little NO_x as petrol cars, 80% of these premature deaths could have been avoided. Ecosystem eutrophication impacts (critical load exceedances) from the same diesel vehicles would also have been reduced at similar rates as for the health effects.

Riverine nitrogen (N) export is a crucial process that links upstream and downstream ecosystems and coastal zones. However, the driving forces of riverine N export that is closely related to water N pollution are still not well understood. In this study, we used a mass balance approach to quantify the sources of N discharge and analyzed the effect of land use composition on riverine N export, taking Zhejiang Province, China as a case study. We found that the total reactive N discharge to rivers in Zhejiang increased from 0.22 to 0.26 Tg yr⁻¹ from 2000 to 2015. At the watershed scale, our estimate of N export agrees well with the monitored riverine N concentration in the eight major watersheds in Zhejiang. Direct discharge of domestic wastewater and effluents from wastewater treatment plants are dominant sources of riverine N export, followed by agricultural non-point sources. Although riverine N export increases with the increasing proportion of urban and agricultural land uses, we did not find any relationship between land use change and changes in riverine N export. This suggests that the dominant factor affecting riverine N export should be human activities (e.g. wastewater discharge and fertilization level), while land use only mediates riverine N export.

Hydrocarbon fuel production and utilization are considered water intensive processes due to the high volumes of water used in source development and fuel processing. At the same time, there is significant water formed during combustion. However, this water is not currently widely harvested at the site of production. Instead, it is added to the hydrologic cycle, often in a different location from the fuel production site. This study quantifies the water formed from combustion of these fuels and analyzes the magnitudes of formation in the context of other hydrologic sources and sinks in order to facilitate future assessments of water harvesting technology and/or atmospheric impacts of combustion. Annual water formation from stoichiometric combustion of hydrocarbon fuels, including natural gas, oil- and natural gas liquid-derived products, and coal, in the United States and worldwide are presented and compared with quantities of water sequestered, evaporated, and stored in the atmosphere. Water production factors in terms of mass and energy of fuel consumed, WPFm and WPFe, respectively, are defined for the comparison of fuels and incorporation into future life cycle analyses (LCAs). Results show that water formation from combustion has increased worldwide from 2005 to 2015, with the largest increase coming from growth in combustion of natural gas. Water formation from combustion of hydrocarbon fuels equals or exceeds water sequestered from the hydrologic cycle through deep well injection in the US annually. Overall, water formation is deemed significant enough to warrant consideration by LCAs of water intensity in fuel production and use, and should be included in future analyses.

The cost of energy produced by onshore wind turbines is among the lowest available; however, onshore wind turbines are often positioned in a complex terrain, where the wind resources and wind conditions are quite uncertain due to the surrounding topography and/or vegetation. In this study, we use a scale model in a three-dimensional wind-testing chamber to show how minor changes in the terrain can result in significant differences in the flow at turbine height. These differences affect not only the power performance but also the life-time and maintenance costs of wind turbines, and hence, the economy and feasibility of wind turbine projects. We find that the mean wind, wind shear and turbulence level are extremely sensitive to the exact details of the terrain: a small modification of the edge of our scale model, results in a reduction of the estimated annual energy production by at least 50% and an increase in the turbulence level by a factor of five in the worst-case scenario with the most unfavorable wind direction. Wind farm developers should be aware that near escarpments destructive flows can occur and their extent is uncertain thus warranting on-site field measurements.

A SAM-based price model for Mexico is developed in order to assess the effects of the carbon tax, which was part of the fiscal reform approved in 2014. The model is formulated based on a social accounting matrix (SAM) that distinguishes households by the official poverty condition and geographical area. The main results are that the sector that includes coke, refined petroleum and nuclear fuel shows the highest price increase due to the direct impact of the carbon tax; in addition, air transport and inland transport are the most affected sectors, in an indirect manner, because both employ inputs from the former sector. Also, it is found that welfare diminishes more in the rural strata than in the urban one. In the urban area, the carbon tax is regressive: the negative impact of carbon tax on family welfare is greater on the poorest families.

Forest and peatland fires during the 2015 El Niño drought were amongst the worst on record in Southeast Asia. They were a major contributor of carbon emissions across the region, with the associated smoke-induced haze causing an air pollution crisis that affected millions of people. We present evidence of air pollution impacts on biodiversity. Using daily acoustic recordings in central Singapore, we monitored the dawn chorus before, during and after the haze event. We demonstrate that levels of ecological community acoustic activity dropped dramatically during the haze, and that this decline was significantly associated with levels of air pollution considered 'unhealthy' to the human population. Acoustic disruption was apparent across four common indices of soundscape activity, with only a partial recovery to pre-haze levels observed 16 weeks after the smoke had dissipated. These impacts on ecological communities were likely to be even more severe closer to the fires, where air pollution levels were reported to be 15-fold greater than those recorded in Singapore. Our results indicate that large-scale air pollution crises may have hitherto underestimated and potentially far-reaching impacts on biodiversity, especially in parts of the world prone to extensive forest fires.

Renewable portfolio standards (RPS) exist in 29 US states and the District of Columbia. This article summarizes the first national-level, integrated assessment of the future costs and benefits of existing RPS policies; the same metrics are evaluated under a second scenario in which widespread expansion of these policies is assumed to occur. Depending on assumptions about renewable energy technology advancement and natural gas prices, existing RPS policies increase electric system costs by as much as $31 billion, on a present-value basis over 2015−2050. The expanded renewable deployment scenario yields incremental costs that range from $23 billion to $194 billion, depending on the assumptions employed. The monetized value of improved air quality and reduced climate damages exceed these costs. Using central assumptions, existing RPS policies yield $97 billion in air-pollution health benefits and $161 billion in climate damage reductions. Under the expanded RPS case, health benefits total $558 billion and climate benefits equal $599 billion. These scenarios also yield benefits in the form of reduced water use. RPS programs are not likely to represent the most cost effective path towards achieving air quality and climate benefits. Nonetheless, the findings suggest that US RPS programs are, on a national basis, cost effective when considering externalities.

Wood based energy is the main source of cooking and heating fuel in Sub-Saharan Africa. Its use rises as the population increases. Inefficient cook stoves result in fuel wastage and health issues associated with smoke in the kitchen. As users are poor women, they tend not to be consulted on cook stove development, hence the need for participatory development of efficient woodfuel cooking systems. This paper presents the findings of a study carried out in Embu, Kenya to assess energy use efficiency and concentrations of carbon monoxide and fine particulate matter from charcoal produced using gasifier cook stoves, compared to conventional wood charcoal. Charcoal made from Grevillea robusta prunings, Zea mays cob (maize cob) and Cocos nucifera (coconut shells) had calorific values of 26.5 kJ g⁻¹, 28.7 kJ g⁻¹ and 31.7 kJ g⁻¹ respectively, which are comparable to conventional wood charcoal with calorific values of 33.1 kJ g⁻¹. Cooking with firewood in a gasifier cook stove and use of the resultant charcoal as by-product to cook another meal in a conventional charcoal stove saved 41% of the amount of fuel compared to cooking with firewood in the traditional three stone open fire. Cooking with firewood based on G. robusta prunings in the traditional open fire resulted in a concentration of fine particulate matter of 2600 μg m⁻³, which is more than 100 times greater than from cooking with charcoal made from G. robusta prunings in a gasifier. Thirty five percent of households used the gasifier for cooking dinner and lunch, and cooks preferred using it for food that took a short time to prepare. Although the gasifier cook stove is energy and emission efficient there is a need for it to be developed further to better suit local cooking preferences. The energy transition in Africa will have to include cleaner and more sustainable wood based cooking systems.

Vegetation in the arctic tundra typically consists of a small-scale mosaic of plant communities, with species differing in growth forms, seasonality, and biogeochemical properties. Characterization of this variation is essential for understanding and modeling the functioning of the arctic tundra in global carbon cycling, as well as for evaluating the resolution requirements for remote sensing. Our objective was to quantify the seasonal development of the leaf-area index (LAI) and its variation among plant communities in the arctic tundra near Tiksi, coastal Siberia, consisting of graminoid, dwarf shrub, moss, and lichen vegetation. We measured the LAI in the field and used two very-high-spatial resolution multispectral satellite images (QuickBird and WorldView-2), acquired at different phenological stages, to predict landscape-scale patterns. We used the empirical relationships between the plant community-specific LAI and degree-day accumulation (0 °C threshold) and quantified the relationship between the LAI and satellite NDVI (normalized difference vegetation index). Due to the temporal difference between the field data and satellite images, the LAI was approximated for the imagery dates, using the empirical model. LAI explained variation in the NDVI values well (R²_adj. 0.42–0.92). Of the plant functional types, the graminoid LAI showed the largest seasonal amplitudes and was the main cause of the varying spatial patterns of the NDVI and the related LAI between the two images. Our results illustrate how the short growing season, rapid development of the LAI, yearly climatic variation, and timing of the satellite data should be accounted for in matching imagery and field verification data in the Arctic region.

Much research has been carried out on the potential impacts of climate change on forest fire activity in the boreal forest. Indeed, there is a general consensus that, while change will vary regionally across the vast extent of the boreal, in general the fire environment will become more conducive to fire. Land management agencies must consider ways to adapt to these new conditions. This paper examines the impact of that changed fire environment on overall wildfire suppression capability. We use multiple General Circulation Models and carbon emission pathways to generate future fire environment scenarios for Canada's forested region. We then use these scenarios with the Canadian Forest Fire Behaviour Prediction System and spatial coverages of the current forest fuel composition across the landscape to examine potential variation in key fire behaviour outputs that influence whether fire management resources can effectively suppress fire. Specifically, we evaluate how the potential for crown fire occurrence and active growth of fires changes with the changing climate. We also examine future fire behaviour through the lens of operational fire intensity thresholds used to guide decisions about resources effectiveness. Results indicate that the proportion of days in fire seasons with the potential for unmanageable fire will increase across Canada's forest, more than doubling in some regions in northern and eastern boreal forest.

Universal access to electricity is deemed critical for improving living standards and indispensable for eradicating poverty and achieving sustainable development. In 2003, the 'Luz para Todos' (LpT—Light for All) program was launched aiming to universalize access to electricity in Brazil. The program focused on rural and isolated areas, also targeting to bring development to those regions along with electrification. This paper evaluates the results of the LpT program in improving socio-economic development in the poorest regions of Brazil. After an initial qualitative analysis, an empirical quantitative assessment of the influence of increased electrification rates on the components of the Human Development Index (HDI) is performed. The empirical results of this study showed that electrification had a positive influence on all dimensions of the HDI, with the education component having the strongest effect. Although complementary policies were needed to achieve this, results show that electricity access is a major requirement to improve quality of life.

Amazon droughts directly increase forest flammability by reducing forest understory air and fuel moisture. Droughts also increase forest flammability indirectly by decreasing soil moisture, triggering leaf shedding, branch loss, and tree mortality—all of which contribute to increased fuel loads. These direct and indirect effects can cause widespread forest fires that reduce forest carbon stocks in the Amazon, with potentially important consequences for the global carbon cycle. These processes are expected to become more widespread, common, and intense as global climate changes, yet the mechanisms linking droughts, wildfires, and associated changes in carbon stocks remain poorly understood. Here, we expanded the capabilities of a dynamic forest carbon model to better represent (1) drought effects on carbon and fuel dynamics and (2) understory fire behavior and severity. We used the refined model to quantify changes in Pan-Amazon live carbon stocks as a function of the maximum climatological water deficit (MCWD) and fire intensity, under both historical and future climate conditions. We found that the 2005 and 2010 droughts increased potential fire intensity by 226 kW m⁻¹ and 494 kW m⁻¹, respectively. These increases were due primarily to increased understory dryness (109 kW m⁻¹ in 2005; 124 kW m⁻¹ in 2010) and altered forest structure (117 kW m⁻¹ in 2005; 370 kW m⁻¹ in 2010) effects. Combined, these historic droughts drove total simulated reductions in live carbon stocks of 0.016 (2005) and 0.027 (2010) PgC across the Amazon Basin. Projected increases in future fire intensity increased simulated carbon losses by up to 90% per unit area burned, compared with modern climate. Increased air temperature was the primary driver of changes in simulated future fire intensity, while reduced precipitation was secondary, particularly in the eastern portion of the Basin. Our results show that fire-drought interactions strongly affect live carbon stocks and that future climate change, combined with the synergistic effects of drought on forest flammability, may strongly influence the stability of tropical forests in the future.

Food production is key to achieving food security in the drylands of sub-Saharan Africa. Since agricultural productivity is limited, however, due to inherent agro-ecological constraints and land degradation, sustainable agricultural intensification has been widely discussed as an opportunity for improving food security and reducing vulnerability. Yet vulnerability determinants are distributed heterogeneously in the drylands of sub-Saharan Africa and sustainable intensification cannot be achieved everywhere in cost-effective and efficient ways. To better understand the heterogeneity of farming systems' vulnerability in order to support decision making at regional scales, we present archetypes, i.e. socio-ecological patterns, of farming systems' vulnerability in the drylands of sub-Saharan Africa and reveal their nestedness. We quantitatively indicated the most relevant farming systems' properties at a sub-national resolution. These factors included water availability, agro-ecological potential, erosion sensitivity, population pressure, urbanisation, remoteness, governance, income and undernourishment. Cluster analysis revealed eight broad archetypes of vulnerability across all drylands of sub-Saharan Africa. The broad archetype representing better governance and highest remoteness in extremely dry and resource-constrained regions encompassed the largest area share (19%), mainly indicated in western Africa. Moreover, six nested archetypes were identified within those regions with better agropotential and prevalent agricultural livelihoods. Among these patterns, the nested archetype depicting regions with highest erosion sensitivity, severe undernourishment and lower agropotential represented the largest population (30%) and area (28%) share, mainly found in the Sahel region. The nested archetype indicating medium undernourishment, better governance and lowest erosion sensitivity showed particular potential for sustainable agricultural intensification, mainly in western and some parts of southeastern and eastern Africa. Insights into the nestedness of archetypes allowed a more differentiated discussion of vulnerability and sustainable intensification opportunities, enhancing the evaluation of key interlinkages between land management and food security. The archetypes may support the transfer of successful intensification strategies based on similarities among the drylands in sub-Saharan Africa.

Although development organizations agree that reliable access to energy and energy services—one of the 17 Sustainable Development Goals—is likely to have profound and perhaps disproportionate impacts on women, few studies have directly empirically estimated the impact of energy access on women's empowerment. This is a result of both a relative dearth of energy access evaluations in general and a lack of clarity on how to quantify gender impacts of development projects. Here we present an evaluation of the impacts of the Solar Market Garden—a distributed photovoltaic irrigation project—on the level and structure of women's empowerment in Benin, West Africa. We use a quasi-experimental design (matched-pair villages) to estimate changes in empowerment for project beneficiaries after one year of Solar Market Garden production relative to non-beneficiaries in both treatment and comparison villages (n = 771). To create an empowerment metric, we constructed a set of general questions based on existing theories of empowerment, and then used latent variable analysis to understand the underlying structure of empowerment locally. We repeated this analysis at follow-up to understand whether the structure of empowerment had changed over time, and then measured changes in both the levels and likelihood of empowerment over time. We show that the Solar Market Garden significantly positively impacted women's empowerment, particularly through the domain of economic independence. In addition to providing rigorous evidence for the impact of a rural renewable energy project on women's empowerment, our work lays out a methodology that can be used in the future to benchmark the gender impacts of energy projects.

In September 2015 UN announced 17 Sustainable Development goals (SDG) from which goal number 7 envisions universal access to modern energy services for all by 2030. In Kenya only about 46% of the population currently has access to electricity. This paper analyses hypothetical scenarios, and selected implications, investigating pathways that would allow the country to reach its electrification targets by 2030. Two modelling tools were used for the purposes of this study, namely OnSSET and OSeMOSYS. The tools were soft-linked in order to capture both the spatial and temporal dynamics of their nature. Two electricity demand scenarios were developed representing low and high end user consumption goals respectively. Indicatively, results show that geothermal, coal, hydro and natural gas would consist the optimal energy mix for the centralized national grid. However, in the case of the low demand scenario a high penetration of stand-alone systems is evident in the country, reaching out to approximately 47% of the electrified population. Increasing end user consumption leads to a shift in the optimal technology mix, with higher penetration of mini-grid technologies and grid extension.

Unclean combustion of solid fuel for cooking and other household energy needs leads to severe household air pollution and adverse health impacts in adults and children. Replacing traditional solid fuel stoves with high efficiency, low-polluting semi-gasifier stoves can potentially contribute to addressing this global problem. The success of semi-gasifier cookstove implementation initiatives depends not only on the technical performance and safety of the stove, but also the compatibility of the stove design with local cooking practices, the needs and preferences of stove users, and community economic structures. Many past stove design initiatives have failed to address one or more of these dimensions during the design process, resulting in failure of stoves to achieve long-term, exclusive use and market penetration. This study presents a user-centered, iterative engineering design approach to developing a semi-gasifier biomass cookstove for rural Chinese homes. Our approach places equal emphasis on stove performance and meeting the preferences of individuals most likely to adopt the clean stove technology. Five stove prototypes were iteratively developed following energy market and policy evaluation, laboratory and field evaluations of stove performance and user experience, and direct interactions with stove users. The most current stove prototype achieved high performance in the field on thermal efficiency (ISO Tier 3) and pollutant emissions (ISO Tier 4), and was received favorably by rural households in the Sichuan province of Southwest China. Among household cooks receiving the final prototype of the intervention stove, 88% reported lighting and using it at least once. At five months post-intervention, the semi-gasifier stoves were used at least once on an average of 68% [95% CI: 43, 93] of days. Our proposed design strategy can be applied to other stove development initiatives in China and other countries.

We compare predictions of a simple process-based crop model (Soltani and Sinclair 2012), a simple statistical model (Schlenker and Roberts 2009), and a combination of both models to actual maize yields on a large, representative sample of farmer-managed fields in the Corn Belt region of the United States. After statistical post-model calibration, the process model (Simple Simulation Model, or SSM) predicts actual outcomes slightly better than the statistical model, but the combined model performs significantly better than either model. The SSM, statistical model and combined model all show similar relationships with precipitation, while the SSM better accounts for temporal patterns of precipitation, vapor pressure deficit and solar radiation. The statistical and combined models show a more negative impact associated with extreme heat for which the process model does not account. Due to the extreme heat effect, predicted impacts under uniform climate change scenarios are considerably more severe for the statistical and combined models than for the process-based model.

Geiger et al (Environ. Res. Lett. 2016 11 084012) employ two functional relationships to characterize hurricane damage in the USA—either based on GDP (one exponent) or on per capita GDP and population (two exponents). From the Akaike Information Criterion the authors cannot reject the former kind in favor of the latter. The different approaches, however, lead to divergent projections of future hurricane losses. In this comment, we argue that there is no rigorous evidence in [1] to give preference to one or the other approach, and the conclusion that high-income does not protect against hurricane losses needs to be revisited. As a perspective, it needs to be mentioned that the previously published relationship between GDP and population could unify both approaches.

Recently a multitude of empirically derived damage models have been applied to project future tropical cyclone (TC) losses for the United States. In their study (Geiger et al 2016 Environ. Res. Lett.11 084012) compared two approaches that differ in the scaling of losses with socio-economic drivers: the commonly-used approach resulting in a sub-linear scaling of historical TC losses with a nation's affected gross domestic product (GDP), and the disentangled approach that shows a sub-linear increase with affected population and a super-linear scaling of relative losses with per capita income. Statistics cannot determine which approach is preferable but since process understanding demands that there is a dependence of the loss on both GDP per capita and population, an approach that accounts for both separately is preferable to one which assumes a specific relation between the two dependencies. In the accompanying comment, Rybski et al argued that there is no rigorous evidence to reach the conclusion that high-income does not protect against hurricane losses. Here we affirm that our conclusion is drawn correctly and reply to further remarks raised in the comment, highlighting the adequateness of our approach but also the potential for future extension of our research.