Table of contents

The US residential solar market is growing quickly, and as solar adoption diffuses into new populations, later adopters may differ significantly from earlier ones. Using a unique household-level survey dataset including 1234 adopters and 790 non-adopters from San Diego County, California, we explore differences in attitudinal and socio-economic factors for three groups: (i) adopters and non-adopters; (ii) early and more recent adopters; (iii) consumers adopting via buying or leasing. Our results suggest that adopters overall have higher incomes, are more educated, live in larger homes, and expect to stay in their homes for longer than their non-adopting peers. They also differ in their expectations of electricity retail rate changes and the impact solar could have on their home resale value. When examining differences between early and more recent adopters, we find that recent adopters are more representative of general homeowners and more politically moderate. They are also increasingly installing solar to protect against future electricity price increases and to lower electricity costs as opposed to adopting strictly for environmental reasons. Furthermore, more recent adopters differ significantly from earlier adopters in the situations that prompted them to adopt. The findings demonstrate how solar markets are evolving, reflecting changes in the underlying drivers of consumer adoption as well as innovative solar marketing strategies.

We aim to address the question of whether or not there is a significant recent 'hiatus', 'pause' or 'slowdown' of global temperature rise. Using a statistical technique known as change point (CP) analysis we identify the changes in four global temperature records and estimate the rates of temperature rise before and after these changes occur. For each record the results indicate that three CPs are enough to accurately capture the variability in the data with no evidence of any detectable change in the global warming trend since ∼1970. We conclude that the term 'hiatus' or 'pause' cannot be statistically justified.

The impact of geoengineering on crops has to date been studied by examining mean yields. We present the first work focusing on the rate of crop failures under a geoengineered climate. We investigate the impact of a future climate and a potential geoengineering scheme on the number of crop failures in two regions, Northeastern China and West Africa. Climate change associated with a doubling of atmospheric carbon dioxide increases the number of crop failures in Northeastern China while reducing the number of crop failures in West Africa. In both regions marine cloud brightening is likely to reduce the number crop failures, although it is more effective at reducing mild crop failure than severe crop failure. We find that water stress, rather than heat stress, is the main cause of crop failure in current, future and geoengineered climates. This demonstrates the importance of irrigation and breeding for tolerance to water stress as adaptation methods in all futures. Analysis of global rainfall under marine cloud brightening has the potential to significantly reduce the impact of climate change on global wheat and groundnut production.

We examined new satellite climate data records documenting frozen (FR) season and snow cover extent (SCE) changes from 1979 to 2011 over all northern vegetated land areas (≥45 °N). New insight on the spatial and temporal characteristics of seasonal FR ground and snowpack melt changes were revealed by integrating the independent FR and SCE data records. Similar decreasing trends in annual FR and SCE durations coincided with widespread warming (0.4 °C decade⁻¹). Relatively strong declines in FR and SCE durations in spring and summer are partially offset by increasing trends in fall and winter. These contrasting seasonal trends result in relatively weak decreasing trends in annual FR and SCE durations. A dominant SCE retreat response to FR duration decreases was observed, while the sign and strength of this relationship was spatially complex, varying by latitude and regional snow cover, and climate characteristics. The spatial extent of FR conditions exceeds SCE in early spring and is smaller during snowmelt in late spring and early summer, while FR ground in the absence of snow cover is widespread in the fall. The integrated satellite record, for the first time, reveals a general increasing trend in annual snowmelt duration from 1.3 to 3.3 days decade⁻¹ (p < 0.01), occurring largely in the fall. Annual FR ground durations are declining from 0.8 to 1.3 days decade⁻¹. These changes imply extensive biophysical impacts to regional snow cover, soil and permafrost regimes, surface water and energy budgets, and climate feedbacks, while ongoing satellite microwave missions provide an effective means for regional monitoring.

Determining the seasonality of terrestrial carbon exchange with the atmosphere remains a challenge in tropical forests because of the heterogeneity of ecosystem and climate. The magnitude and spatial variability of this flux are unknown, particularly in Amazonia where empirical upscaling approaches from spatially sparse in situ measurements and simulations from process-based models have been challenged in recent scientific literature. Here, we use satellite proxy observations of canopy structure, skin temperature, water content, and optical properties over a period of 10 years (2000–2009) to constrain and quantify the spatial pattern and seasonality of carbon exchange of Amazonian forests. We identify nine regions through an optimized cluster approach with distinct leaf phenology synchronized with either water or light availability and corresponding seasonal cycles of gross primary production (GPP), covering more than 600 million ha of remaining old growth forests of Amazonia. We find South and Southwestern regions show strong seasonality of GPP with a peak in the wet season; while from Central Western to Northeastern Amazonia cover three regions with rising GPP in the dry season. The remaining four regions have significant but weak seasonality. These patterns agree with satellite florescence observations, a better proxy for photosynthetic activity. Our results suggest that only one-third of the patterns can be explained by the spatial autocorrelation caused by intra-annual variability of climate over Amazonia. The remaining two-thirds of variations are due to biogeography of the Amazon basin driven by forest composition, structure, and nutrients. These patterns, for the first time, provide a complex picture of seasonal changes of tropical forests related to photosynthesis and influenced by water, light, and stomatal responses of trees that can improve modeling of regional carbon cycle and future prediction of impacts of climate change.

The decline in Arctic sea ice cover has been widely documented and it is clear that this change is having profound impacts locally. An emerging and highly uncertain area of scientific research, however, is whether such Arctic change has a tangible effect on weather and climate at lower latitudes. Of particular societal relevance is the open question: will continued Arctic sea ice loss make mid-latitude weather more extreme? Here we analyse idealized atmospheric general circulation model simulations, using two independent models, both forced by projected Arctic sea ice loss in the late twenty-first century. We identify robust projected changes in regional temperature and precipitation extremes arising solely due to Arctic sea ice loss. The likelihood and duration of cold extremes are projected to decrease over high latitudes and over central and eastern North America, but to increase over central Asia. Hot extremes are projected to increase in frequency and duration over high latitudes. The likelihood and severity of wet extremes are projected to increase over high latitudes, the Mediterranean and central Asia; and their intensity is projected to increase over high latitudes and central and eastern Asia. The number of dry days over mid-latitude Eurasia and dry spell duration over high latitudes are both projected to decrease. There is closer model agreement for projected changes in temperature extremes than for precipitation extremes. Overall, we find that extreme weather over central and eastern North America is more sensitive to Arctic sea ice loss than over other mid-latitude regions. Our results are useful for constraining the role of Arctic sea ice loss in shifting the odds of extreme weather, but must not be viewed as deterministic projections, as they do not account for drivers other than Arctic sea ice loss.

Storms following wildfires are known to impair drinking water supplies in the southwestern United States, yet our understanding of the role of precipitation in post-wildfire water quality is far from complete. We quantitatively assessed water-quality impacts of different hydrologic events in the Colorado Front Range and found that for a three-year period, substantial hydrologic and geochemical responses downstream of a burned area were primarily driven by convective storms with a 30 min rainfall intensity >10 mm h⁻¹. These storms, which typically occur several times each year in July–September, are often small in area, short-lived, and highly variable in intensity and geographic distribution. Thus, a rain gage network with high temporal resolution and spatial density, together with high-resolution stream sampling, are required to adequately characterize post-wildfire responses. We measured total suspended sediment, dissolved organic carbon (DOC), nitrate, and manganese concentrations that were 10–156 times higher downstream of a burned area compared to upstream during relatively common (50% annual exceedance probability) rainstorms, and water quality was sufficiently impaired to pose water-treatment concerns. Short-term water-quality impairment was driven primarily by increased surface runoff during higher intensity convective storms that caused erosion in the burned area and transport of sediment and chemical constituents to streams. Annual sediment yields downstream of the burned area were controlled by storm events and subsequent remobilization, whereas DOC yields were closely linked to annual runoff and thus were more dependent on interannual variation in spring runoff. Nitrate yields were highest in the third year post-wildfire. Results from this study quantitatively demonstrate that water quality can be altered for several years after wildfire. Because the southwestern US is prone to wildfires and high-intensity rain storms, the role of storms in post-wildfire water-quality impacts must be considered when assessing water-quality vulnerability.

The European Parliament recently called for urgent measures to halve food waste in the EU, where consumers are responsible for a major part of total waste along the food supply chain. Due to a lack of data on national food waste statistics, uncertainty in (consumer) waste quantities (and the resulting associated quantities of natural resources) is very high, but has never been previously assessed in studies for the EU. Here we quantify: (1) EU consumer food waste, and (2) associated natural resources required for its production, in term of water and nitrogen, as well as estimating the uncertainty of these values. Total EU consumer food waste averages 123 (min 55–max 190) kg/capita annually (kg/cap/yr), i.e. 16% (min 7–max 24%) of all food reaching consumers. Almost 80%, i.e. 97 (min 45–max 153) kg/cap/yr is avoidable food waste, which is edible food not consumed. We have calculated the water and nitrogen (N) resources associated with avoidable food waste. The associated blue water footprint (WF) (the consumption of surface and groundwater resources) averages 27 litre per capita per day (min 13–max 40 l/cap/d), which slightly exceeds the total blue consumptive EU municipal water use. The associated green WF (consumptive rainwater use) is 294 (min 127–max 449) l/cap/d, equivalent to the total green consumptive water use for crop production in Spain. The nitrogen (N) contained in avoidable food waste averages 0.68 (min 0.29–max 1.08) kg/cap/yr. The food production N footprint (any remaining N used in the food production process) averages 2.74 (min 1.02–max 4.65) kg/cap/yr, equivalent to the use of mineral fertiliser by the UK and Germany combined. Among all the food product groups wasted, meat accounts for the highest amounts of water and N resources, followed by wasted cereals. The results of this study provide essential insights and information on sustainable consumption and resource efficiency for both EU policies and EU consumers.

Air quality is heavily influenced by weather conditions. In this study, we assessed the impact of long-term weather changes on air quality and health in the US during 1994–2012. We quantified past weather-related increases, or 'weather penalty', in ozone (O₃) and fine particulate matter (PM_2.5), and thereafter estimated the associated excess deaths. Using statistical regression methods, we derived the weather penalty as the additional increases in air pollution relative to trends assuming constant weather conditions (i.e., weather-adjusted trends). During our study period, temperature increased and wind speed decreased in most US regions. Nationally, weather-related 8 h max O₃ increases were 0.18 ppb per year (95% CI: 0.06, 0.31) in the warm season (May–October) and 0.07 ppb per year (95% CI: 0.02, 0.13) in the cold season (November–April). The weather penalties on O₃ were relatively larger than PM_2.5 weather penalties, which were 0.056 μg m⁻³ per year (95% CI: 0.016, 0.096) in warm months and 0.027 μg m⁻³ per year (95% CI: 0.010, 0.043) in cold months. Weather penalties on O₃ and PM_2.5 were associated with 290 (95% CI: 80, 510) and 770 (95% CI: 190, 1350) excess annual deaths, respectively. Over a 19-year period, this amounts to 20 300 excess deaths (5600 from O₃, 14 700 from PM_2.5) attributable to the weather penalty on air quality.

We combine Landsat and MODIS data in a land model to assess the impact of urbanization on US surface climate. For cities built within forests, daytime urban land surface temperature (LST) is much higher than that of vegetated lands. For example, in Washington DC and Atlanta, daytime mean temperature differences between impervious and vegetated lands reach 3.3 and 2.0 °C, respectively. Conversely, for cities built within arid lands, such as Phoenix, urban areas are 2.2 °C cooler than surrounding shrubs. We find that the choice and amount of tree species in urban settings play a commanding role in modulating cities' LST. At continental and monthly scales, impervious surfaces are 1.9 °C ± 0.6 °C warmer than surroundings during summer and expel 12% of incoming precipitation as surface runoff compared to 3.2% over vegetation. We also show that the carbon lost to urbanization represents 1.8% of the continental total, a striking number considering urbanization occupies only 1.1% of the US land. With a small areal extent, urbanization has significant effects on surface energy, water and carbon budgets and reveals an uneven impact on surface climate that should inform upon policy options for improving urban growth including heat mitigation and carbon sequestration.

We quantify the source contributions to surface PM2.5 (fine particulate matter) pollution over North China from January 2013 to 2015 using the GEOS-Chem chemical transport model and its adjoint with improved model horizontal resolution (1/4° × 5/16°) and aqueous-phase chemistry for sulfate production. The adjoint method attributes the PM2.5 pollution to emissions from different source sectors and chemical species at the model resolution. Wintertime surface PM2.5 over Beijing is contributed by emissions of organic carbon (27% of the total source contribution), anthropogenic fine dust (27%), and SO₂ (14%), which are mainly from residential and industrial sources, followed by NH₃ (13%) primarily from agricultural activities. About half of the Beijing pollution originates from sources outside of the city municipality. Adjoint analyses for other cities in North China all show significant regional pollution transport, supporting a joint regional control policy for effectively mitigating the PM2.5 air pollution.

A remarkable feature of nanobubbles (<10^–6 m in diameter) is their long lifetime in water. Supplying oxygen-nanobubbles (NBs) to continuously flooded paddy soil may retard the development of reductive conditions, thereby reducing the emission of methane (CH₄), a potent greenhouse gas, and dissolution of arsenic, an environmental load. We tested this hypothesis by performing a pot experiment and measuring redox-related variables. The NBs were introduced into control water (with properties similar to those of river water) using a commercially available generator. Rice (Oryza sativa L.) growth did not differ between plants irrigated with NB water and those irrigated with control water, but NB water significantly (p < 0.05) reduced cumulative CH₄ emission during the rice-growing season by 21%. The amounts of iron, manganese, and arsenic that leached into the drainage water before full rice heading were also reduced by the NB water. Regardless of the water type, weekly-measured CH₄ flux was linearly correlated with the leached iron concentration during the rice-growing season (r = 0.74, p < 0.001). At the end of the experiment, the NB water significantly lowered the soil pH in the 0–5 cm layer, probably because of the raised redox potential. The population of methanogenic Archaea (mcrA copy number) in the 0–5 cm layer was significantly increased by the NB water, but we found no correlation between the mcrA copy number and the cumulative CH₄ emission (r = –0.08, p = 0.85). In pots without rice plants, soil reduction was not enhanced, regardless of the water type. The results indicate that NB water reduced CH₄ emission and arsenic dissolution through an oxidative shift of the redox conditions in the flooded soil. We propose the use of NB water as a tool for controlling redox conditions in flooded paddy soils.

The increased exposure of human populations to heat stress is one of the likely consequences of global warming, and it has detrimental effects on health and labor capacity. Here, we consider the evolution of heat stress under climate change using 21 general circulation models (GCMs). Three heat stress indicators, based on both temperature and humidity conditions, are used to investigate present-day model biases and spreads in future climate projections. Present day estimates of heat stress indicators from observational data shows that humid tropical areas tend to experience more frequent heat stress than other regions do, with a total frequency of heat stress 250–300 d yr⁻¹. The most severe heat stress is found in the Sahel and south India. Present-day GCM simulations tend to underestimate heat stress over the tropics due to dry and cold model biases. The model based estimates are in better agreement with observation in mid to high latitudes, but this is due to compensating errors in humidity and temperature. The severity of heat stress is projected to increase by the end of the century under climate change scenario RCP8.5, reaching unprecedented levels in some regions compared with observations. An analysis of the different factors contributing to the total spread of projected heat stress shows that spread is primarily driven by the choice of GCMs rather than the choice of indicators, even when the simulated indicators are bias-corrected. This supports the utility of the multi-model ensemble approach to assess the impacts of climate change on heat stress.

Incorporation of charcoal produced by biomass pyrolysis (biochar) in agricultural soils is a potentially sustainable strategy for climate change mitigation. However, some side effects of large-scale biochar application need to be investigated. In particular a massive use of a low-reflecting material on large cropland areas may impact the climate via changes in surface albedo. Twelve years of MODIS-derived albedo data were analysed for three pairs of selected agricultural sites in central Italy. In each pair bright and dark coloured soil were identified, mimicking the effect of biochar application on the land surface albedo of complex agricultural landscapes. Over this period vegetation canopies never completely masked differences in background soil colour. This soil signal, expressed as an albedo difference, induced a local instantaneous radiative forcing of up to 4.7 W m⁻² during periods of high solar irradiance. Biochar mitigation potential might therefore be reduced up to ∼30%. This study proves the importance of accounting for crop phenology and crop management when assessing biochar mitigation potential and provides more insights into the analysis of its environmental feedback.

Ozone air pollution is identified as one of the main threats bearing upon human health and ecosystems, with 25 000 deaths in 2005 attributed to surface ozone in Europe (IIASA 2013 TSAP Report #10). In addition, there is a concern that climate change could negate ozone pollution mitigation strategies, making them insufficient over the long run and jeopardising chances to meet the long term objective set by the European Union Directive of 2008 (Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008) (60 ppbv, daily maximum). This effect has been termed the ozone climate penalty. One way of assessing this climate penalty is by driving chemistry-transport models with future climate projections while holding the ozone precursor emissions constant (although the climate penalty may also be influenced by changes in emission of precursors). Here we present an analysis of the robustness of the climate penalty in Europe across time periods and scenarios by analysing the databases underlying 11 articles published on the topic since 2007, i.e. a total of 25 model projections. This substantial body of literature has never been explored to assess the uncertainty and robustness of the climate ozone penalty because of the use of different scenarios, time periods and ozone metrics. Despite the variability of model design and setup in this database of 25 model projection, the present meta-analysis demonstrates the significance and robustness of the impact of climate change on European surface ozone with a latitudinal gradient from a penalty bearing upon large parts of continental Europe and a benefit over the North Atlantic region of the domain. Future climate scenarios present a penalty for summertime (JJA) surface ozone by the end of the century (2071–2100) of at most 5 ppbv. Over European land surfaces, the 95% confidence interval of JJA ozone change is [0.44; 0.64] and [0.99; 1.50] ppbv for the 2041–2070 and 2071–2100 time windows, respectively.

With growing concerns regarding future impacts of sea-level in major coastal cities, the most accurate information is required regarding local sea-level changes with respect to the coast. Besides global and regional sea-level changes, local coastal vertical ground motions can substantially contribute to local changes in sea-level. In some cases, such ground motions can also limit the usefulness of tide-gauge records, which are a unique source of information to evaluate global sea-level changes before the altimetry era. Using satellite synthetic aperture radar interferometry, this study aims at characterizing vertical coastal ground motion in Dakar (Senegal), where a unique century-long record in Africa has been rediscovered. Given the limited number of available images, we use a stacking procedure to compute ground motion velocities in the line of sight over 1992–2010. Despite a complex geology and a rapid population growth and development, we show that the city as a whole is unaffected by differential ground motions larger than 1 mm year⁻¹. Only the northern part of the harbor displays subsidence patterns after 2000, probably as a consequence of land reclamation works. However, these ground motions do not affect the historical tide gauge. Our results highlight the value of the historical sea-level records of Dakar, which cover a 100 year time-span in a tropical oceanic region of Africa, where little data are available for past sea-level reconstructions.

Projected future trends in water availability are associated with large uncertainties in many regions of the globe. In mountain areas with complex topography, climate models have often limited capabilities to adequately simulate the precipitation variability on small spatial scales. Also, their validation is hampered by typically very low station density. In the Central Andes of South America, a semi-arid high-mountain region with strong seasonality, zonal wind in the upper troposphere is a good proxy for interannual precipitation variability. Here, we combine instrumental measurements, reanalysis and paleoclimate data, and a 57-member ensemble of CMIP5 model simulations to assess changes in Central Andes precipitation over the period AD 1000–2100. This new database allows us to put future projections of precipitation into a previously missing multi-centennial and pre-industrial context. Our results confirm the relationship between regional summer precipitation and 200 hPa zonal wind in the Central Andes, with stronger Westerly winds leading to decreased precipitation. The period of instrumental coverage (1965–2010) is slightly dryer compared to pre-industrial times as represented by control simulations, simulations from the past Millennium, ice core data from Quelccaya ice cap and a tree-ring based precipitation reconstruction. The model ensemble identifies a clear reduction in precipitation already in the early 21st century: the 10 year running mean model uncertainty range (ensemble 16–84% spread) is continuously above the pre-industrial mean after AD 2023 (AD 2028) until the end of the 21st century in the RCP2.6 (RCP8.5) emission scenario. Average precipitation over AD 2071–2100 is outside the range of natural pre-industrial variability in 47 of the 57 model simulations for both emission scenarios. The ensemble median fraction of dry years (defined by the 5th percentile in pre-industrial conditions) is projected to increase by a factor of 4 until 2071–2100 in the RCP8.5 scenario. Even under the strong reduction of greenhouse gas emissions projected by the RCP2.6 scenario, the Central Andes will experience a reduction in precipitation outside pre-industrial natural variability. This is of concern for the Central Andes, because society and economy are highly vulnerable to changes in the hydrological cycle and already have to face decreases in fresh water availability caused by glacier retreat.

Albedo modification (AM) is sometimes characterized as a potential means of avoiding climate threshold responses, including large-scale ice sheet mass loss. Previous work has investigated the effects of AM on total sea-level rise over the present century, as well as AM's ability to reduce long-term (≫10³ yr) contributions to sea-level rise from the Greenland Ice Sheet (GIS). These studies have broken new ground, but neglect important feedbacks in the GIS system, or are silent on AM's effectiveness over the short time scales that may be most relevant for decision-making (<10³ yr). Here, we assess AM's ability to reduce GIS sea-level contributions over decades to centuries, using a simplified ice sheet model. We drive this model using a business-as-usual base temperature forcing scenario, as well as scenarios that reflect AM-induced temperature stabilization or temperature drawdown. Our model results suggest that (i) AM produces substantial near-term reductions in the rate of GIS-driven sea-level rise. However, (ii) sea-level rise contributions from the GIS continue after AM begins. These continued sea level rise contributions persist for decades to centuries after temperature stabilization and temperature drawdown begin, unless AM begins in the next few decades. Moreover, (iii) any regrowth of the GIS is delayed by decades or centuries after temperature drawdown begins, and is slow compared to pre-AM rates of mass loss. Combined with recent work that suggests AM would not prevent mass loss from the West Antarctic Ice Sheet, our results provide a nuanced picture of AM's possible effects on future sea-level rise.

Floating persistent debris, primarily made from plastic, disperses long distances from source areas and accumulates in oceanic gyres. However, biofouling can increase the density of debris items to the point where they sink. Buoyancy is related to item volume, whereas fouling is related to surface area, so small items (which have high surface area to volume ratios) should start to sink sooner than large items. Empirical observations off South Africa support this prediction: moving offshore from coastal source areas there is an increase in the size of floating debris, an increase in the proportion of highly buoyant items (e.g. sealed bottles, floats and foamed plastics), and a decrease in the proportion of thin items such as plastic bags and flexible packaging which have high surface area to volume ratios. Size-specific sedimentation rates may be one reason for the apparent paucity of small plastic items floating in the world's oceans.

Long term memory (LTM) scaling behavior in worldwide tree-ring proxies and subsequent climate reconstructions is analyzed for and compared with the memory structure inherent to instrumental temperature and precipitation data. Detrended fluctuation analysis is employed to detect LTM, and its scaling exponent α is used to evaluate LTM. The results show that temperature and precipitation reconstructions based on ring width measurements (mean $\alpha =0.8$) contain more memory than records based on maximum latewood density (mean $\alpha =0.7$). Both exceed the memory inherent to regional instrumental data ($\alpha =0.6$ for temperature, $\alpha =0.5$ for precipitation) in the time scales ranging from 1 year up to 50 years. We compare memory-free ($\alpha =0.5$) pseudo-instrumental precipitation data with pseudo-reconstructed precipitation data with LTM ($\alpha \gt 0.5$), and demonstrate the biasing influences of LTM on climate reconstructions. We call for attention to statistical analysis with regard to the variability of proxy-based chronologies or reconstructions, particularly with respect to the contained (i) trends, (ii) past warm/cold period and wet/dry periods; and (iii) extreme events.

Recent declines in productivity and tree survival have been widely observed in boreal forests. We used early warning signals (EWS) in tree ring data to anticipate premature mortality in jack pine (Pinus banksiana)—an extensive and dominant species occurring across the moisture-limited southern boreal forest in North America. We sampled tree rings from 113 living and 84 dead trees in three soil moisture regimes (subxeric, submesic, subhygric) in central Saskatchewan, Canada. We reconstructed annual increments of tree basal area to investigate (1) whether we could detect EWS related to mortality of individual trees, and (2) how water availability and tree growth history may explain the mortality warning signs. EWS were evident as punctuated changes in growth patterns prior to transition to an alternative state of reduced growth before dying. This transition was likely triggered by a combination of severe drought and insect outbreak. Higher moisture availability associated with a soil moisture gradient did not appear to reduce tree sensitivity to stress-induced mortality. Our results suggest tree rings offer considerable potential for detecting critical transitions in tree growth, which are linked to premature mortality.

Irrigated agriculture is placing increasing pressure on finite freshwater resources, especially in developing countries, where water extraction is often unregulated, un-priced and even subsidized. To shift agriculture to a more sustainable use of water without harming the food security and livelihoods of hundreds of millions of smallholders, substantial improvements of water use efficiency will be required. Here, we use detailed hydroclimatic and agricultural data to estimate the potential for the widespread adoption of efficient irrigation technologies to halt the depletion of India's groundwater resources. Even though we find substantial technical potential for reversing water table declines, we show that the impacts are highly sensitive to assumptions about farmers' water use decisions. For example, we find that widespread adoption of proven technologies that include drip and sprinkler irrigation has the potential to reduce the amount of excessive extraction of groundwater by two thirds. However, under more realistic assumptions about farmers' irrigation choices, half of these reductions are lost due to the expansion of irrigated area. Our results suggest that without the introduction of incentives for conservation, much of the potential impact of technology adoption on aquifers may be lost. The analysis provides quantitative input to the debate of incentive versus technology based water policies.

The term 'carbon lock-in' refers to the tendency for certain carbon-intensive technological systems to persist over time, 'locking out' lower-carbon alternatives, and owing to a combination of linked technical, economic, and institutional factors. These technologies may be costly to build, but relatively inexpensive to operate and, over time, they reinforce political, market, and social factors that make it difficult to move away from, or 'unlock' them. As a result, by investing in assets prone to lock-in, planners and investors restrict future flexibility and increase the costs of achieving agreed climate protection goals. Here, we develop a straight-forward approach to assess the speed, strength, and scale of carbon lock-in for major energy-consuming assets in the power, buildings, industry, and transport sectors. We pilot the approach at the global level, finding that carbon lock-in is greatest, globally, for coal power plants, gas power plants, and oil-based vehicles. The approach can be readily applied at the national or regional scale, and may be of particular relevance to policymakers interested in enhancing flexibility in their jurisdictions for deeper emissions cuts in the future, and therefore in limiting the future costs associated with 'stranded assets'.

Sea level rates up to three times the global mean rate are being observed in the western tropical Pacific since 1993 by satellite altimetry. From recently published studies, it is not yet clear whether the sea level spatial trend patterns of the Pacific Ocean observed by satellite altimetry are mostly due to internal climate variability or if some anthropogenic fingerprint is already detectable. A number of recent studies have shown that the removal of the signal corresponding to the Pacific Decadal Oscillation (PDO)/Interdecadal Pacific Oscillation (IPO) from the observed altimetry sea level data over 1993–2010/2012 results in some significant residual trend pattern in the western tropical Pacific. It has thus been suggested that the PDO/IPO-related internal climate variability alone cannot account for all of the observed trend patterns in the western tropical Pacific and that the residual signal could be the fingerprint of the anthropogenic forcing. In this study, we investigate if there is any other internal climate variability signal still present in the residual trend pattern after the removal of IPO contribution from the altimetry-based sea level over 1993–2013. We show that subtraction of the IPO contribution to sea level trends through the method of linear regression does not totally remove the internal variability, leaving significant signal related to the non-linear response of sea level to El Niño Southern Oscillation (ENSO). In addition, by making use of 21 CMIP5 coupled climate models, we study the contribution of external forcing to the Pacific Ocean regional sea level variability over 1993–2013, and show that according to climate models, externally forced and thereby the anthropogenic sea level fingerprint on regional sea level trends in the tropical Pacific is still too small to be observable by satellite altimetry.

Background: The relationship between air borne particulate matter ≤10 μm (PM₁₀) exposure and pregnancy-induced hypertension (PIH) is inconclusive. Few studies have been conducted, and fewer were conducted in areas with high levels of PM₁₀. Methods: To examine the association between PM₁₀ and PIH by different exposure time windows during pregnancy, we analyzed data from a birth cohort study conducted in Lanzhou, China including 8 745 pregnant women with available information on air pollution during pregnancy. A total of 333 PIH cases (127 gestational hypertension (GH) and 206 preeclampsia (PE)) were identified. PM₁₀ daily average concentrations of each subject were calculated according to the distance between home/work addresses and monitor stations using an inverse-distance weighting approach. Results: Average PM₁₀ concentration over the duration of entire pregnancy was significantly associated with PIH (OR = 1.12, 95%CI: 1.02, 1.23 per 10 μg m⁻³ increase), PE (OR = 1.16, 95%CI: 1.03, 1.30 per 10 μg m⁻³ increase), late onset PE (OR = 1.17, 95% CI: 1.03, 1.32 per10 μg m⁻³ increase), and severe PE (OR = 1.25, 95% CI: 1.06, 1.48 per 10 μg m⁻³ increase). Average PM₁₀ during the first 12 gestational weeks was associated with the risk of GH (OR = 1.10, 95% CI: 1.00, 1.21 per 10 μg m⁻³ increase), and PM₁₀ exposure before 20 gestational weeks was associated with the risk of severe PE (OR = 1.14, 95% CI: 1.01, 1.30 per 10 μg m⁻³ increase). Conclusions: We found that high level exposure to ambient PM₁₀ during pregnancy was associated with an increased risk of PIH, GH and PE and that the strength of the association varied by timing of exposure during pregnancy.

Existing carbon offset protocols for improved cookstoves do not require emissions testing. They are based only on estimated reductions in the use of non-renewable biomass generated by a given stove, and use simplistic calculations to convert those fuel savings to imputed emissions of carbon dioxide (CO₂). Yet recent research has shown that different cookstoves vary tremendously in their combustion quality, and thus in their emissions profiles of both CO₂ and other products of incomplete combustion. Given the high global warming potential of some of these non-CO₂ emissions, offset protocols that do not account for combustion quality may thus not be assigning either appropriate absolute or relative climate values to different technologies. We use statistical resampling of recent emissions studies to estimate the actual radiative forcing impacts of traditional and improved cookstoves. We compare the carbon offsets generated by protocols in the four carbon markets that currently accept cookstove offsets (Clean Development Mechanism, American Carbon Registry, Verified Carbon Standard, and Gold Standard) to a theoretical protocol that also accounts for emissions of carbonaceous aerosols and carbon monoxide, using appropriate statistical techniques to estimate emissions factor distributions from the literature. We show that current protocols underestimate the climate value of many improved cookstoves and fail to distinguish between (i.e., assign equal offset values to) technologies with very different climate impacts. We find that a comprehensive carbon accounting standard would generate significantly higher offsets for some improved cookstove classes than those generated by current protocols, and would create much larger separation between different cookstove classes. Finally, we provide compelling evidence for the inclusion of renewable biomass into current protocols, and propose guidelines for the statistics needed in future emissions tests in order to accurately estimate the climate impact (and thus offsets generated by) cookstoves and other household energy technologies.

Scenarios of future changes in small scale precipitation extremes for the Netherlands are presented. These scenarios are based on a new approach whereby changes in precipitation extremes are set proportional to the change in water vapor amount near the surface as measured by the 2m dew point temperature. This simple scaling framework allows the integration of information derived from: (i) observations, (ii) a new unprecedentedly large 16 member ensemble of simulations with the regional climate model RACMO2 driven by EC-Earth, and (iii) short term integrations with a non-hydrostatic model Harmonie. Scaling constants are based on subjective weighting (expert judgement) of the three different information sources taking also into account previously published work. In all scenarios local precipitation extremes increase with warming, yet with broad uncertainty ranges expressing incomplete knowledge of how convective clouds and the atmospheric mesoscale circulation will react to climate change.

An analysis of the climate impact of various forms of beef production is carried out, with a particular eye to the comparison between systems relying primarily on grasses grown in pasture ('grass-fed' or 'pastured' beef) and systems involving substantial use of manufactured feed requiring significant external inputs in the form of synthetic fertilizer and mechanized agriculture ('feedlot' beef). The climate impact is evaluated without employing metrics such as ${\mathrm{CO}}_{2}{\rm{e}}$ or global warming potentials. The analysis evaluates the impact at all time scales out to 1000 years. It is concluded that certain forms of pastured beef production have substantially lower climate impact than feedlot systems. However, pastured systems that require significant synthetic fertilization, inputs from supplemental feed, or deforestation to create pasture, have substantially greater climate impact at all time scales than the feedlot and dairy-associated systems analyzed. Even the best pastured system analyzed has enough climate impact to justify efforts to limit future growth of beef production, which in any event would be necessary if climate and other ecological concerns were met by a transition to primarily pasture-based systems. Alternate mitigation options are discussed, but barring unforseen technological breakthroughs worldwide consumption at current North American per capita rates appears incompatible with a 2 °C warming target.

By applying the concept of the coupled natural and human system (CNH), we compared spatiotemporal changes in livestock (LSK), land cover, and ecosystem production to understand the relative roles that natural and social driving forces have on CNH dynamics on the Mongolia plateau. We used socioeconomic and physical data at prefecture level for Inner Mongolia and Mongolia from 1981 through 2010 to represent changes in net primary productivity (NPP), enhanced vegetation index (EVI), precipitation, annual average temperature, LSK, livestock density (LSKD), land cover change (LCC), gross domestic production (GDP), and population (POP). The ratios such as LSK:NPP, LSKD: EVI, LSKD:albedo, LSK:POP, and LSK:GDP were examined and compared between Inner Mongolia and Mongolia, and structural equation modeling (SEM) was applied to quantify the complex interactions. Substantial differences in LSK, POP, and economic development were found among the biomes and between Inner Mongolia and Mongolia. When various indicators for policy shifts—such as the World Trade Organization (WTO) for China, the Third Campaign to Reclaim Abandoned Agriculture Lands (ATAR-3), and the Grain for Green Program for China (GFG)—were added into our SEM, the results showed significant change in the strength of the above relationships. After China joined the WTO, the relationships in Inner Mongolia between LSKD:LCC and LSKD:NPP were immensely strengthened, whereas relationships in NPP:LCC were weakened. In Mongolia, the ATAR-3 program first appeared to be an insignificant policy, but the Collapse of the Soviet Union enhanced the correlation between LSKD:LCC, weakened the connection of LCC:NPP, and did not affect LSKD:NPP. We conclude that human influences on the Mongolian CNH system exceeded those of the biophysical changes, but that the significance varies in time and per biome, as well as between Inner Mongolia and Mongolia.

An analysis of observed trends in African annual-average near-surface temperatures over the last five decades reveals drastic increases, particularly over parts of the subtropics and central tropical Africa. Over these regions, temperatures have been rising at more than twice the global rate of temperature increase. An ensemble of high-resolution downscalings, obtained using a single regional climate model forced with the sea-surface temperatures and sea-ice fields of an ensemble of global circulation model (GCM) simulations, is shown to realistically represent the relatively strong temperature increases observed in subtropical southern and northern Africa. The amplitudes of warming are generally underestimated, however. Further warming is projected to occur during the 21st century, with plausible increases of 4–6 °C over the subtropics and 3–5 °C over the tropics by the end of the century relative to present-day climate under the A2 (a low mitigation) scenario of the Special Report on Emission Scenarios. High impact climate events such as heat-wave days and high fire-danger days are consistently projected to increase drastically in their frequency of occurrence. General decreases in soil-moisture availability are projected, even for regions where increases in rainfall are plausible, due to enhanced levels of evaporation. The regional dowscalings presented here, and recent GCM projections obtained for Africa, indicate that African annual-averaged temperatures may plausibly rise at about 1.5 times the global rate of temperature increase in the subtropics, and at a somewhat lower rate in the tropics. These projected increases although drastic, may be conservative given the model underestimations of observed temperature trends. The relatively strong rate of warming over Africa, in combination with the associated increases in extreme temperature events, may be key factors to consider when interpreting the suitability of global mitigation targets in terms of African climate change and climate change adaptation in Africa.

Fires associated with agricultural and plantation development in Indonesia impact ecosystem services and release emissions into the atmosphere that degrade regional air quality and contribute to greenhouse gas concentrations. In this study, we estimate the relative contributions of the oil palm, timber (for wood pulp and paper), and logging industries in Sumatra and Kalimantan to land cover change, fire activity, and regional population exposure to smoke concentrations. Concessions for these three industries cover 21% and 49% of the land area in Sumatra and Kalimantan respectively, with the highest overall area in lowlands on mineral soils instead of more carbon-rich peatlands. In 2012, most remaining forest area was located in logging concessions for both islands, and for all combined concessions, there was higher remaining lowland and peatland forest area in Kalimantan (45% and 46%, respectively) versus Sumatra (20% and 27%, respectively). Emissions from all combined concessions comprised 41% of total fire emissions (within and outside of concession boundaries) in Sumatra and 27% in Kalimantan for the 2006 burning season, which had high fire activity relative to decadal emissions. Most fire emissions were observed in concessions located on peatlands and non-forested lowlands, the latter of which could include concessions that are currently under production, cleared in preparation for production, or abandoned lands. For the 2006 burning season, timber concessions from Sumatra (47% of area and 88% of emissions) and oil palm concessions from Kalimantan (33% of area and 67% of emissions) contributed the most to concession-related fire emissions from each island. Although fire emissions from concessions were higher in Kalimantan, emissions from Sumatra contributed 63% of concession-related smoke concentrations for the population-weighted region because fire sources were located closer to population centers. In order to protect regional public health, our results highlight the importance of limiting the use of fire by the timber and oil palm industries, particularly on concessions that contain peatlands and non-forest, by such methods as improving monitoring systems, local-level management, and enforcement of existing fire bans.

This letter assesses low carbon scenarios for India at the subnational level in the passenger road transport sector. We estimate the future passenger mobility demand and assess the impact of carbon mitigation policies using the Asia–Pacific Integrated Assessment/Enduse models. This letter focuses on the transitions of energy and emissions of passenger transport in India in alternate scenarios i.e. the business-as-usual scenario and a low carbon scenario that aligns to the 2 °C temperature stabilization target agreed under the global climate change negotiations. The modelling results show that passenger mobility demand will rise in all sub-national regions of India in the coming few decades. However, the volume and modal structure will vary across regions. Modelling assessment results show that aligning global low carbon policies with local policies has potential to deliver significant air quality co-benefits. This analysis provides insights into the comparative dynamics of environmental policymaking at sub-national levels.

Methane (CH₄) is a potent greenhouse gas (GHG) that affects the global climate system. Knowledge about land–atmospheric CH₄ exchanges on the Qinghai-Tibetan Plateau (QTP) is insufficient. Using a coupled biogeochemistry model, this study analyzes the net exchanges of CH₄ and CO₂ over the QTP for the period of 1979–2100. Our simulations show that the region currently acts as a net CH₄ source with 0.95 Tg CH₄ y⁻¹ emissions and 0.19 Tg CH₄ y⁻¹ soil uptake, and a photosynthesis C sink of 14.1 Tg C y⁻¹. By accounting for the net CH₄ emission and the net CO₂ sequestration since 1979, the region was found to be initially a warming source until the 2010s with a positive instantaneous radiative forcing peak in the 1990s. In response to future climate change projected by multiple global climate models (GCMs) under four representative concentration pathway (RCP) scenarios, the regional source of CH₄ to the atmosphere will increase by 15–77% at the end of this century. Net ecosystem production (NEP) will continually increase from the near neutral state to around 40 Tg C y⁻¹ under all RCPs except RCP8.5. Spatially, CH₄ emission or uptake will be noticeably enhanced under all RCPs over most of the QTP, while statistically significant NEP changes over a large-scale will only appear under RCP4.5 and RCP4.6 scenarios. The cumulative GHG fluxes since 1979 will exert a slight warming effect on the climate system until the 2030s, and will switch to a cooling effect thereafter. Overall, the total radiative forcing at the end of the 21st century is 0.25–0.35 W m⁻², depending on the RCP scenario. Our study highlights the importance of accounting for both CH₄ and CO₂ in quantifying the regional GHG budget.

This article examines studies related to environmental justice in the criminological literature and from a criminological perspective. Criminologists have long been concerned with injustices in the criminal justice system related to the enforcement of criminal law. In the 1990s, following the emergence of green criminology, a handful of criminologists have drawn attention to environmental justice as an extension of more traditional criminological studies of justice and injustice. Relevant criminological studies of environmental justice are reviewed, and suggestions for future environmental justice research are offered.

Satellite remote sensing is an efficient tool for identifying buoyant river plumes in the coastal ocean that are formed by the interaction between river discharge and ambient seawater. A new method for reconstructing the volume rates of river discharge based on the shape, extent and orientation of plumes is described that combines the output from a Lagrangian numerical model and analyses of satellite imagery. At the first step in the procedure, a high resolution satellite image is used to identify the river plume. The spatial characteristics of the plume as seen in the image are not determined solely by the current river discharge rate, as they also depend on the hydrographic features in the sea and atmospheric forcing. A previously developed and validated hydrodynamic model for river plumes is run with a variety of forcing conditions to identify the discharge rate that provides the best match between modeled and observed plumes. The method can be applied to estimate indirectly discharge from small rivers and streams, many of which lack direct measurements. Here it has been applied and validated against in situ data for two rivers feeding the eastern part of the Black Sea.

Previous studies have combined climate, crop and economic models to examine the impact of climate change on agricultural production and food security, but results have varied widely due to differences in models, scenarios and input data. Recent work has examined (and narrowed) these differences through systematic model intercomparison using a high-emissions pathway to highlight the differences. This paper extends that analysis to explore a range of plausible socioeconomic scenarios and emission pathways. Results from multiple climate and economic models are combined to examine the global and regional impacts of climate change on agricultural yields, area, production, consumption, prices and trade for coarse grains, rice, wheat, oilseeds and sugar crops to 2050. We find that climate impacts on global average yields, area, production and consumption are similar across shared socioeconomic pathways (SSP 1, 2 and 3, as we implement them based on population, income and productivity drivers), except when changes in trade policies are included. Impacts on trade and prices are higher for SSP 3 than SSP 2, and higher for SSP 2 than for SSP 1. Climate impacts for all variables are similar across low to moderate emissions pathways (RCP 4.5 and RCP 6.0), but increase for a higher emissions pathway (RCP 8.5). It is important to note that these global averages may hide regional variations. Projected reductions in agricultural yields due to climate change by 2050 are larger for some crops than those estimated for the past half century, but smaller than projected increases to 2050 due to rising demand and intrinsic productivity growth. Results illustrate the sensitivity of climate change impacts to differences in socioeconomic and emissions pathways. Yield impacts increase at high emissions levels and vary with changes in population, income and technology, but are reduced in all cases by endogenous changes in prices and other variables.

The articles in this special issue examine the critical nexus of electricity, water, and climate, emphasizing connections among resources;  the prospect of increasing vulnerabilities of water resources and electricity generation in a changing climate;  and the opportunities for research to inform integrated energy and water policy and management measures aimed at reducing vulnerability and increasing resilience. Here, we characterize several major themes emerging from this research and highlight some of the uptake of this work in both scientific and public spheres.  Underpinning much of this research is the recognition that water resources are expected to undergo substantial changes based on the global warming that results primarily from fossil energy-based carbon emissions.  At the same time, the production of electricity from fossil fuels, nuclear power, and some renewable technologies (biomass, geothermal and concentrating solar power) can be highly water-intensive.  Energy choices now and in the near future will have a major impact not just on the global climate, but also on water supplies and the resilience of energy systems that currently depend heavily on them.