Table of contents

The Environmental Research Letters focus issue on 'Cumulative Emissions, Global Carbon Budgets and the Implications for Climate Mitigation Targets' was launched in 2015 to highlight the emerging science of the climate response to cumulative emissions, and how this can inform efforts to decrease emissions fast enough to avoid dangerous climate impacts. The 22 research articles published represent a fantastic snapshot of the state-or-the-art in this field, covering both the science and policy aspects of cumulative emissions and carbon budget research. In this Review and Synthesis, we summarize the findings published in this focus issue, outline some suggestions for ongoing research needs, and present our assessment of the implications of this research for ongoing efforts to meet the goals of the Paris climate agreement.

Vehicle-to-grid (V2G) refers to efforts to bi-directionally link the electric power system and the transportation system in ways that can improve the sustainability and security of both. A transition to V2G could enable vehicles to simultaneously improve the efficiency (and profitability) of electricity grids, reduce greenhouse gas emissions for transport, accommodate low-carbon sources of energy, and reap cost savings for owners, drivers, and other users. To understand the recent state of this field of research, here we conduct a systematic review of 197 peer-reviewed articles published on V2G from 2015 to early 2017. We find that the majority of V2G studies in that time period focus on technical aspects of V2G, notably renewable energy storage, batteries, or load balancing to minimize electricity costs, in some cases including environmental goals as constraints. A much lower proportion of studies focus on the importance of assessing environmental and climate attributes of a V2G transition, or on the role of consumer acceptance and knowledge of V2G systems. Further, there is need for exploratory work on natural resource use and externalities, discourses and narratives as well as social justice, gender, and urban resilience considerations. These research gaps need to be addressed if V2G is to achieve the societal transition its advocates seek.

As a result of global increases in both temperature and specific humidity, heat stress is projected to intensify throughout the 21st century. Some of the regions most susceptible to dangerous heat and humidity combinations are also among the most densely populated. Consequently, there is the potential for widespread exposure to wet bulb temperatures that approach and in some cases exceed postulated theoretical limits of human tolerance by mid- to late-century. We project that by 2080 the relative frequency of present-day extreme wet bulb temperature events could rise by a factor of 100–250 (approximately double the frequency change projected for temperature alone) in the tropics and parts of the mid-latitudes, areas which are projected to contain approximately half the world's population. In addition, population exposure to wet bulb temperatures that exceed recent deadly heat waves may increase by a factor of five to ten, with 150–750 million person-days of exposure to wet bulb temperatures above those seen in today's most severe heat waves by 2070–2080. Under RCP 8.5, exposure to wet bulb temperatures above 35 °C—the theoretical limit for human tolerance—could exceed a million person-days per year by 2080. Limiting emissions to follow RCP 4.5 entirely eliminates exposure to that extreme threshold. Some of the most affected regions, especially Northeast India and coastal West Africa, currently have scarce cooling infrastructure, relatively low adaptive capacity, and rapidly growing populations. In the coming decades heat stress may prove to be one of the most widely experienced and directly dangerous aspects of climate change, posing a severe threat to human health, energy infrastructure, and outdoor activities ranging from agricultural production to military training.

Limited data exists on emissions from agriculture-driven deforestation, and available data are typically uncertain. In this paper, we provide comparable estimates of emissions from both all deforestation and agriculture-driven deforestation, with uncertainties for 91 countries across the tropics between 1990 and 2015. Uncertainties associated with input datasets (activity data and emissions factors) were used to combine the datasets, where most certain datasets contribute the most. This method utilizes all the input data, while minimizing the uncertainty of the emissions estimate. The uncertainty of input datasets was influenced by the quality of the data, the sample size (for sample-based datasets), and the extent to which the timeframe of the data matches the period of interest. Area of deforestation, and the agriculture-driver factor (extent to which agriculture drives deforestation), were the most uncertain components of the emissions estimates, thus improvement in the uncertainties related to these estimates will provide the greatest reductions in uncertainties of emissions estimates. Over the period of the study, Latin America had the highest proportion of deforestation driven by agriculture (78%), and Africa had the lowest (62%). Latin America had the highest emissions from agriculture-driven deforestation, and these peaked at 974 ± 148 Mt CO₂ yr⁻¹ in 2000–2005. Africa saw a continuous increase in emissions between 1990 and 2015 (from 154 ± 21–412 ± 75 Mt CO₂ yr⁻¹), so mitigation initiatives could be prioritized there. Uncertainties for emissions from agriculture-driven deforestation are ± 62.4% (average over 1990–2015), and uncertainties were highest in Asia and lowest in Latin America. Uncertainty information is crucial for transparency when reporting, and gives credibility to related mitigation initiatives. We demonstrate that uncertainty data can also be useful when combining multiple open datasets, so we recommend new data providers to include this information.

Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 general circulation models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over the entirety of Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from −11% at 1.5 K up to −30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (< ±10%) are observed for river basins in Central Europe and the British Isles under different levels of warming. Projected higher annual precipitation increases high flows in Scandinavia, but reduced snow melt equivalent decreases flood events in this region. Neglecting uncertainties originating from internal climate variability, downscaling technique, and hydrologic model parameters, the contribution by the GCMs to the overall uncertainties of the ensemble is in general higher than that by the HMs. The latter, however, have a substantial share in the Mediterranean and Scandinavia. Adaptation measures for limiting the impacts of global warming could be similar under 1.5 K and 2 K global warming, but have to account for significantly higher changes under 3 K global warming.

While grid-scale electricity storage (hereafter 'storage') could be crucial for deeply decarbonizing the electric power system, it would increase carbon dioxide (CO₂) emissions in current systems across the United States. To better understand how storage transitions from increasing to decreasing system CO₂ emissions, we quantify the effect of storage on operational CO₂ emissions as a power system decarbonizes under a moderate and strong CO₂ emission reduction target through 2045. Under each target, we compare the effect of storage on CO₂ emissions when storage participates in only energy, only reserve, and energy and reserve markets. We conduct our study in the Electricity Reliability Council of Texas (ERCOT) system and use a capacity expansion model to forecast generator fleet changes and a unit commitment and economic dispatch model to quantify system CO₂ emissions with and without storage. We find that storage would increase CO₂ emissions in the current ERCOT system, but would decrease CO₂ emissions in 2025 through 2045 under both decarbonization targets. Storage reduces CO₂ emissions primarily by enabling gas-fired generation to displace coal-fired generation, but also by reducing wind and solar curtailment. We further find that the market in which storage participates drives large differences in the magnitude, but not the direction, of the effect of storage on CO₂ emissions.

Pricing carbon is one of the most important tools to reduce emissions and mitigate climate change. Already, about 40 nations have implemented explicit or implicit carbon prices, and a carbon price was explicitly stated as a mitigation strategy by many nations in their emission pledges submitted to the Paris Agreement. The coverage of carbon prices varies significantly between nations though, often only covering a subset of sectors in the economy. We investigate the propagation of carbon prices along the global supply-chain when the carbon price is applied at the point where carbon is removed from the ground (extraction), is combusted (production), or where goods and services are consumed (consumption). We consider both the regional and sectoral effects, and compare the carbon price income and costs relative to economic output. We find that implementation using different accounting systems makes a significant difference to revenues and increased expenditure, and that domestic and global trade plays a significant role in spreading the carbon price between sectors and countries. A few single sectors experience the largest relative price increases (especially electricity and transport), but most of the carbon price is ultimately paid by households for goods and services due to the large expenditure and indirect supply chain impacts. We finally show that a global carbon price will generate a larger share of revenue relative to GDP in non-OECD nations than OECD nations, independent on the point of implementation.

This study represents the first attempt to quantify the effects of autonomous adaptation on the projection of global flood hazards and to assess future flood risk by including this effect. A vulnerability scenario, which varies according to the autonomous adaptation effect for conventional disaster mitigation efforts, was developed based on historical vulnerability values derived from flood damage records and a river inundation simulation. Coupled with general circulation model outputs and future socioeconomic scenarios, potential future flood fatalities and economic loss were estimated. By including the effect of autonomous adaptation, our multimodel ensemble estimates projected a 2.0% decrease in potential flood fatalities and an 821% increase in potential economic losses by 2100 under the highest emission scenario together with a large population increase. Vulnerability changes reduced potential flood consequences by 64%–72% in terms of potential fatalities and 28%–42% in terms of potential economic losses by 2100. Although socioeconomic changes made the greatest contribution to the potential increased consequences of future floods, about a half of the increase of potential economic losses was mitigated by autonomous adaptation. There is a clear and positive relationship between the global temperature increase from the pre-industrial level and the estimated mean potential flood economic loss, while there is a negative relationship with potential fatalities due to the autonomous adaptation effect. A bootstrapping analysis suggests a significant increase in potential flood fatalities (+5.7%) without any adaptation if the temperature increases by 1.5 °C–2.0 °C, whereas the increase in potential economic loss (+0.9%) was not significant. Our method enables the effects of autonomous adaptation and additional adaptation efforts on climate-induced hazards to be distinguished, which would be essential for the accurate estimation of the cost of adaptation to climate change.

Recent studies have used satellite-derived normalized difference vegetation index (NDVI) time series to explore geographic patterns in boreal forest greening and browning. A number of these studies indicate that boreal forests are experiencing widespread browning, and have suggested that these patterns reflect decreases in forest productivity induced by climate change. Here we use NDVI time series from Landsat, which has much higher quality and spatial resolution than imagery used in most previous studies, to characterize biogeographic patterns in greening and browning across Canada's boreal forest and to explore the drivers behind observed trends. Our results show that the majority of NDVI changes in Canada's boreal forest reflect disturbance-recovery dynamics not climate change impacts, that greening and browning trends outside of disturbed forests are consistent with expected ecological responses to regional changes in climate, and that observed NDVI changes are geographically limited and relatively small in magnitude. By examining covariance between changes in NDVI and temperature and precipitation in locations not affected by disturbance, our results isolate and characterize the nature and magnitude of greening and browning directly associated with climate change. Consistent with biogeographic theory, greening and browning unrelated to disturbance tended to be located in ecotones near boundaries of the boreal forest bioclimatic envelope. We observed greening to be most prevalent in Eastern Canada, which is more humid, and browning to be most prevalent in Western Canada, where forests are more prone to moisture stress. We conclude that continued long-term climate change has the potential to significantly alter the character and function of Canada's boreal forest, but recent changes have been modest and near-term impacts are likely to be focused in or near ecotones.

Changes in society's vulnerability to natural hazards are important to understand, as they determine current and future risks, and the need to improve protection. Very large impacts including high numbers of fatalities occur due to single storm surge flood events. Here, we report on impacts of global coastal storm surge events since the year 1900, based on a compilation of events and data on loss of life. We find that over the past, more than eight thousand people are killed and 1.5 million people are affected annually by storm surges. The occurrence of very substantial loss of life (>10 000 persons) from single events has however decreased over time. Moreover, there is a consistent decrease in event mortality, measured by the fraction of exposed people that are killed, for all global regions, except South East Asia. Average mortality for storm surges is slightly higher than for river floods, but lower than for flash floods. We also find that for the same coastal surge water level, mortality has decreased over time. This indicates that risk reduction efforts have been successful, but need to be continued with projected climate change, increased rates of sea-level rise and urbanisation in coastal zones.

Urban areas have broad ecological footprints with complex impacts on natural systems. In coastal areas, growing populations are advancing their urban footprint into the ocean through the construction of seawalls and other built infrastructure. While we have some understanding of how urbanisation might drive functional change in terrestrial ecosystems, coastal systems have been largely overlooked. This study is one of the first to directly assess how changes in diversity relate to changes in ecosystem properties and functions (e.g. productivity, filtration rates) of artificial and natural habitats in one of the largest urbanised estuaries in the world, Sydney Harbour. We complemented our surveys with an extensive literature search. We found large and important differences in the community structure and function between artificial and natural coastal habitats. However, differences in diversity and abundance of organisms do not necessarily match observed functional changes. The abundance and composition of important functional groups differed among habitats with rocky shores having 40% and 70% more grazers than seawalls or pilings, respectively. In contrast, scavengers were approximately 8 times more abundant on seawalls than on pilings or rocky shores and algae were more diverse on natural rocky shores and seawalls than on pilings. Our results confirm previous findings in the literature. Oysters were more abundant on pilings than on rocky shores, but were also smaller. Interestingly, these differences in oyster populations did not affect in situ filtration rates between habitats. Seawalls were the most invaded habitats while pilings supported greater secondary productivity than other habitats. This study highlights the complexity of the diversity-function relationship and responses to ocean sprawl in coastal systems. Importantly, we showed that functional properties should be considered independently from structural change if we are to design and manage artificial habitats in ways to maximise the services provided by urban coastal systems and minimise their ecological impacts.

Continued growth of the human population on Earth will increase pressure on already stressed terrestrial water resources required for drinking water, agriculture, and industry. This stress demands improved understanding of critical controls on water resource availability, particularly in water-limited regions. Mechanistic predictions of future water resource availability are needed because non-stationary conditions exist in the form of changing climatic conditions, land management paradigms, and ecological disturbance regimes. While historically ecological disturbances have been small and could be neglected relative to climatic effects, evidence is accumulating that ecological disturbances, particularly wildfire, can increase regional water availability. However, wildfire hydrologic impacts are typically estimated locally and at small spatial scales, via disparate measurement methods and analysis techniques, and outside the context of climate change projections. Consequently, the relative importance of climate change driven versus wildfire driven impacts on streamflow remains unknown across the western USA. Here we show that considering wildfire in modeling streamflow significantly improves model predictions. Mixed effects modeling attributed 2%−14% of long-term annual streamflow to wildfire effects. The importance of this wildfire-linked streamflow relative to predicted climate change-induced streamflow reductions ranged from 20%−370% of the streamflow decrease predicted to occur by 2050. The rate of post-wildfire vegetation recovery and the proportion of watershed area burned controlled the wildfire effect. Our results demonstrate that in large areas of the western USA affected by wildfire, regional predictions of future water availability are subject to greater structural uncertainty than previously thought. These results suggest that future streamflows may be underestimated in areas affected by increased prevalence of hydrologically relevant ecological disturbances such as wildfire.

We describe a consistent framework developed to quantify current and future anthropogenic emissions of nitrous oxide and the available technical abatement options by source sector for 172 regions globally. About 65% of the current emissions derive from agricultural soils, 8% from waste, and 4% from the chemical industry. Low-cost abatement options are available in industry, wastewater, and agriculture, where they are limited to large industrial farms. We estimate that by 2030, emissions can be reduced by about 6% ±2% applying abatement options at a cost lower than 10 €/t CO₂-eq. The largest abatement potential at higher marginal costs is available from agricultural soils, employing precision fertilizer application technology as well as chemical treatment of fertilizers to suppress conversion processes in soil (nitrification inhibitors). At marginal costs of up to 100 €/t CO₂-eq, about 18% ±6% of baseline emissions can be removed and when considering all available options, the global abatement potential increases to about 26% ±9%. Due to expected future increase in activities driving nitrous oxide emissions, the limited technical abatement potential available means that even at full implementation of reduction measures by 2030, global emissions can be at most stabilized at the pre-2010 level. In order to achieve deeper reductions in emissions, considerable technological development will be required as well as non-technical options like adjusting human diets towards moderate animal protein consumption.

Extreme temperatures affect populous regions, like eastern China, causing substantial socio-economic losses. It is beneficial to explore whether the frequencies of absolute or threshold-based extreme temperatures have been changed by human activities, such as anthropogenic emissions of greenhouse gases (GHGs). In this study, we compared observed and multi-model-simulated changes in the frequencies of summer days, tropical nights, icy days and frosty nights in eastern China for the years 1960–2012 by using an optimal fingerprinting method. The observed long-term trends in the regional mean frequencies of these four indices were +2.36, +1.62, −0.94, −3.02 days decade⁻¹. The models performed better in simulating the observed frequency change in daytime extreme temperatures than nighttime ones. Anthropogenic influences are detectable in the observed frequency changes of these four temperature extreme indices. The influence of natural forcings could not be detected robustly in any indices. Further analysis found that the effects of GHGs changed the frequencies of summer days (tropical nights, icy days, frosty nights) by +3.48 ± 1.45 (+2.99 ± 1.35, −2.52 ± 1.28, −4.11 ± 1.48) days decade⁻¹. Other anthropogenic forcing agents (dominated by anthropogenic aerosols) offset the GHG effect and changed the frequencies of these four indices by −1.53 ± 0.78, −1.49 ± 0.94, +1.84 ± 1.07, +1.45 ± 1.26 days decade⁻¹, respectively. Little influence of natural forcings was found in the observed frequency changes of these four temperature extreme indices.

In many regions of the world, intensive livestock farming has become a significant source of organic river pollution. As the international meat trade is growing rapidly, the environmental impacts of meat production within one country can occur either domestically or internationally. The goal of this paper is to quantify the impacts of the international meat trade on global organic river pollution at multiple scales (national, regional and gridded). Using the biological oxygen demand (BOD) as an overall indicator of organic river pollution, we compute the spatially distributed organic pollution in global river networks with and without a meat trade, where the without-trade scenario assumes that meat imports are replaced by local production. Our analysis reveals a reduction in the livestock population and production of organic pollutants at the global scale as a result of the international meat trade. However, the actual environmental impact of trade, as quantified by in-stream BOD concentrations, is negative; i.e. we find a slight increase in polluted river segments. More importantly, our results show large spatial variability in local (grid-scale) impacts that do not correlate with local changes in BOD loading, which illustrates: (1) the significance of accounting for the spatial heterogeneity of hydrological processes along river networks, and (2) the limited value of looking at country-level or global averages when estimating the actual impacts of trade on the environment.

With increasing levels of urbanization in the near future, understanding the impact of urbanization on urban heat islands (UHIs) is critical to adapting to regional climate and environmental changes. However, our understanding of the UHI effect relies mainly on its intensity or magnitude. The present study evaluates the impact of urbanization on UHI duration changes by comparing three stations with different rates of urbanization, including highly developed and developing urban areas throughout Hong Kong, from 1990–2015. Results show that the 26 year average UHI intensity in highly urbanized regions is much higher than that in developing areas, and the 26 year average of UHI duration is similar. Over the past 25 years, however, UHI duration has increased only in developing urban areas, from 13.59–17.47 hours. Both earlier UHI starting and later UHI ending times concurrently contribute to the UHI effect being experienced for a longer duration. The differences in UHI duration change between the two areas are supported by population and by night light changes from space. Increasing night light, which suggests enhancements in the economic infrastructure, occurred only in the developing urban areas. Our results suggest that changes in UHI duration should be included in an assessment of regional climate change as well as in urban planning in a megacity.

May 2016 was the third wettest May on record since 1961 over central eastern China based on station observations, with total monthly rainfall 40% more than the climatological mean for 1961–2013. Accompanying disasters such as waterlogging, landslides and debris flow struck part of the lower reaches of the Yangtze River. Causal influence of anthropogenic forcings on this event is investigated using the newly updated Met Office Hadley Centre system for attribution of extreme weather and climate events. Results indicate that there is a significant increase in May 2016 rainfall in model simulations relative to the climatological period, but this increase is largely attributable to natural variability. El Niño years have been found to be correlated with extreme rainfall in the Yangtze River region in previous studies—the strong El Niño of 2015–2016 may account for the extreme precipitation event in 2016. However, on smaller spatial scales we find that anthropogenic forcing has likely played a role in increasing the risk of extreme rainfall to the north of the Yangtze and decreasing it to the south.

In April 2015, the Governor of California mandated a 25% statewide reduction in water consumption (relative to 2013 levels) by urban water suppliers. The more than 400 public water agencies affected by the regulation were also required to report monthly progress towards the conservation goal to the State Water Resources Control Board. This paper uses the reported data to assess how the water utilities have responded to this mandate and to estimate the electricity savings and greenhouse gas (GHG) emissions reductions associated with reduced operation of urban water infrastructure systems. The results show that California succeeded in saving 524 000 million gallons (MG) of water (a 24.5% decrease relative to the 2013 baseline) over the mandate period, which translates into 1830 GWh total electricity savings, and a GHG emissions reduction of 521 000 metric tonnes of carbon dioxide equivalents (MT CO₂e). For comparison, the total electricity savings linked to water conservation are approximately 11% greater than the savings achieved by the investor-owned electricity utilities' efficiency programs for roughly the same time period, and the GHG savings represent the equivalent of taking about 111 000 cars off the road for a year. These indirect, large-scale electricity and GHG savings were achieved at costs that were competitive with existing programs that target electricity and GHG savings directly and independently. Finally, given the breadth of the results produced, we built a companion website, called 'H2Open' (https://cwee.shinyapps.io/greengov/), to this research effort that allows users to view and explore the data and results across scales, from individual water utilities to the statewide summary.

A nitrogen (N) flow, divided into production, food supply, and consumption phases, was designed to calculate the virtual N factors (VNFs) and N footprints (NFs) of China's main food crops. It covered four food groups—cereals, tubers, vegetables, and fruits—comprising 24 food crops. A meta-analysis of 4896 relevant examples from 443 publications was conducted to build a database on N availability and N loss rates during each stage. We calculated N loss from each food group during each phase, and estimated VNFs and NFs based on N loss. It was found that 39.2%–67.6% of N inputs were lost during the production phase, 6.6%–15.2% during the food supply phase, and 0.9%–6.7% during the consumption phase. VNFs for cereals, tubers, vegetables, and fruits were 2.1, 2.9, 4.1 and 8.6, respectively. To raise public awareness, we also calculated the NFs, which were 30.9, 6.7, 7.4, and 17.2 g N kg⁻¹ for cereals, tubers, vegetables, and fruits consumed, respectively, equal to 9.3 kg N capita⁻¹ yr⁻¹ consumption for these four food crops in China. We concluded that policies and strategies to reduce N loss, especially N loss embedded in food loss, must be taken into account to improve the technologies, infrastructure, approaches, and social awareness in reducing nutrient loss during food production and consumption phases.

Climate change mediated drying of boreal peatlands is expected to enhance peatland afforestation and wildfire vulnerability. The water table depth–afforestation feedback represents a positive feedback that can enhance peat drying and consolidation and thereby increase peat burn severity; exacerbating the challenges and costs of wildfire suppression efforts and potentially shifting the peatland to a persistent source of atmospheric carbon. To address this wildfire management challenge, we examined burn severity across a gradient of drying in a black spruce dominated peatland that was partially drained in 1975−1980 and burned in the 2016 Fort McMurray Horse River wildfire. We found that post-drainage black spruce annual ring width increased substantially with intense drainage. Average (±SD) basal diameter was 2.6 ± 1.2 cm, 3.2 ± 2.0 cm and 7.9 ± 4.7 cm in undrained (UD), moderately drained (MD) and heavily drained (HD) treatments, respectively. Depth of burn was significantly different between treatments (p < 0.001) and averaged (±SD) 2.5 ± 3.5 cm, 6.4 ± 5.0 cm and 36.9 ± 29.6 cm for the UD, MD and HD treatments, respectively. The high burn severity in the HD treatment included 38% of the treatment that experienced combustion of the entire peat profile, and we estimate that overall 51% of the HD pre-burn peat carbon stock was lost. We argue that the HD treatment surpassed an ecohydrological tipping point to high severity peat burn that may be identified using black spruce stand characteristics in boreal plains bogs. While further studies are needed, we believe that quantifying this threshold will aid in developing effective adaptive management techniques and protecting boreal peatland carbon stocks.

Recent years have seen an increased frequency of wildfire events in different parts of Arctic tundra ecosystems. Contemporary studies have largely attributed these wildfire events to the Arctic's rapidly changing climate and increased atmospheric disturbances (i.e. thunderstorms). However, existing research has primarily examined the wildfire–climate dynamics of individual large wildfire events. No studies have investigated wildfire activity, including climatic drivers, for the entire tundra biome across multiple years, i.e. at the planetary scale. To address this limitation, this paper provides a planetary/circumpolar scale analyses of space-time patterns of tundra wildfire occurrence and climatic association in the Arctic over a 15 year period (2001–2015). In doing so, we have leveraged and analyzed NASA Terra's MODIS active fire and MERRA climate reanalysis products at multiple temporal scales (decadal, seasonal and monthly). Our exploratory spatial data analysis found that tundra wildfire occurrence was spatially clustered and fire intensity was spatially autocorrelated across the Arctic regions. Most of the wildfire events occurred in the peak summer months (June–August). Our multi-temporal (decadal, seasonal and monthly) scale analyses provide further support to the link between climate variability and wildfire activity. Specifically, we found that warm and dry conditions in the late spring to mid-summer influenced tundra wildfire occurrence, spatio-temporal distribution, and fire intensity. Additionally, reduced average surface precipitation and soil moisture levels in the winter–spring period were associated with increased fire intensity in the following summer. These findings enrich contemporary knowledge on tundra wildfire's spatial and seasonal patterns, and shed new light on tundra wildfire–climate relationships in the circumpolar context. Furthermore, this first pan-Arctic analysis provides a strong incentive and direction for future studies which integrate multiple datasets (i.e. climate, fuels, topography, and ignition sources) to accurately estimate carbon emission from tundra burning and its global climate feedbacks in coming decades.

The grassland of the Tibetan Plateau forms a globally significant biome, which represents 6% of the world's grasslands and 44% of China's grasslands. However, large uncertainties remain concerning the vegetation carbon storage and turnover time in this biome. In this study, we quantified the pool size of both the aboveground and belowground biomass and turnover time of belowground biomass across the Tibetan Plateau by combining systematic measurements taken from a substantial number of surveys (i.e. 1689 sites for aboveground biomass, 174 sites for belowground biomass) with a machine learning technique (i.e. random forest, RF). Our study demonstrated that the RF model is effective tool for upscaling local biomass observations to the regional scale, and for producing continuous biomass estimates of the Tibetan Plateau. On average, the models estimated 46.57 Tg (1 Tg = 10¹²g) C of aboveground biomass and 363.71 Tg C of belowground biomass in the Tibetan grasslands covering an area of 1.32 × 10⁶ km². The turnover time of belowground biomass demonstrated large spatial heterogeneity, with a median turnover time of 4.25 years. Our results also demonstrated large differences in the biomass simulations among the major ecosystem models used for the Tibetan Plateau, largely because of inadequate model parameterization and validation. This study provides a spatially continuous measure of vegetation carbon storage and turnover time, and provides useful information for advancing ecosystem models and improving their performance.

It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA's Gravity Recovery and Climate Experiment (GRACE) mission with the USDA Forest Service's historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25 degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship's utility for the future development of national-scale predictive capability.

Nationally Determined Contributions (NDCs), submitted by Parties to the United Nations Framework Convention on Climate Change before and after the 21st Conference of Parties, summarize domestic objectives for greenhouse gas (GHG) emissions reductions for the 2025–2030 time horizon. In the absence, for now, of detailed guidelines for the format of NDCs, ancillary data are needed to interpret some NDCs and project GHG emissions in 2030. Here, we provide an analysis of uncertainty sources and their impacts on 2030 global GHG emissions based on the sole and full achievement of the NDCs. We estimate that NDCs project into 56.8–66.5 Gt CO₂eq yr⁻¹ emissions in 2030 (90% confidence interval), which is higher than previous estimates, and with a larger uncertainty range. Despite these uncertainties, NDCs robustly shift GHG emissions towards emerging and developing countries and reduce international inequalities in per capita GHG emissions. Finally, we stress that current NDCs imply larger emissions reduction rates after 2030 than during the 2010–2030 period if long-term temperature goals are to be fulfilled. Our results highlight four requirements for the forthcoming 'climate regime': a clearer framework regarding future NDCs' design, an increasing participation of emerging and developing countries in the global mitigation effort, an ambitious update mechanism in order to avoid hardly feasible decarbonization rates after 2030 and an anticipation of steep decreases in global emissions after 2030.

The availability of freshwater supplies to meet future demand is a growing concern. Water availability metrics are needed to inform future water development decisions. With the help of water managers, water availability was mapped for over 1300 watersheds throughout the 31 contiguous states in the eastern US complimenting a prior study of the west. The compiled set of water availability data is unique in that it considers multiple sources of water (fresh surface and groundwater, wastewater and brackish groundwater); accommodates institutional controls placed on water use; is accompanied by cost estimates to access, treat and convey each unique source of water; and is compared to projected future growth in consumptive water use to 2030. Although few administrative limits have been set on water availability in the east, water managers have identified 315 fresh surface water and 398 fresh groundwater basins (with 151 overlapping basins) as areas of concern (AOCs) where water supply challenges exist due to drought related concerns, environmental flows, groundwater overdraft, or salt water intrusion. This highlights a difference in management where AOCs are identified in the east which simply require additional permitting, while in the west strict administrative limits are established. Although the east is generally considered 'water rich' roughly a quarter of the basins were identified as AOCs; however, this is still in strong contrast to the west where 78% of the surface water basins are operating at or near their administrative limit. Little effort was noted on the part of eastern or western water managers to quantify non-fresh water resources.

'Super' Storm Desmond broke meteorological and hydrological records during a record warm year in the British–Irish Isles (BI). The severity of the storm may be a harbinger of expected changes to regional hydroclimate as global temperatures continue to rise. Here, we adopt a process-based approach to investigate the potency of Desmond, and explore the extent to which climate change may have been a contributory factor. Through an Eulerian assessment of water vapour flux we determine that Desmond was accompanied by an atmospheric river (AR) of severity unprecedented since at least 1979, on account of both high atmospheric humidity and high wind speeds. Lagrangian air-parcel tracking and moisture attribution techniques show that long-term warming of North Atlantic sea surface temperatures has significantly increased the chance of such high humidity in ARs in the vicinity of the BI. We conclude that, given exactly the same dynamical conditions associated with Desmond, the likelihood of such an intense AR has already increased by 25% due to long-term climate change. However, our analysis represents a first-order assessment, and further research is needed into the controls influencing AR dynamics.

Our results from playas, which are topographic low areas situated in closed-catchments in drylands, indicated that projected climate change in Southwestern USA would have a net positive impact over runon and groundwater recharge beneath playas. Expected increased precipitation variability can cause up to a 300% increase in annual groundwater recharge beneath playas. This increase will overshadow the effect of decreased precipitation amount that could cause up to a 50% decrease in recharge beneath playas. These changes could have a significant impact on groundwater and carbon storage. These results are important given that groundwater resources in Southwestern USA continue to decline due to human consumption outpacing natural recharge of aquifers. Here, we report on groundwater recharge rates ranging from less than 1 mm to greater than 25 mm per year beneath desert playas. Playas located in larger and steeper catchments with finer-textured soils had the highest rates of recharge. Vegetation cover had no effect on recharge beneath playas. We modeled catchment runoff generation and found that the amount of runon a playa receives annually strongly correlated to the rate of groundwater recharge beneath that playa. Runon occurred during precipitation events larger than 20 mm and increased linearly with events above that threshold.

Identification of the interactive responses of water quantity and quality to changes in nature and human stressors is important for the effective management of water resources. Many studies have been conducted to determine the influence of these stressors on river discharge and water quality. However, there is little information about whether sewage treatment plants can improve water quality in a region where river streamflow has decreased sharply. In this study, a seasonal trend decomposition method was used to analyze long-term (1996–2015) and seasonal trends in the streamflow and water quality of the Guanting Reservoir Basin, which is located in a semi-arid region of China. The results showed that the streamflow in the Guanting Reservoir Basin decreased sharply from 1996–2000 due to precipitation change and human activities (human use and reservoir regulation), while the streamflow decline over the longer period of time (1996–2015) could be attributed to human activities. During the same time, the river water quality improved significantly, having a positive relationship with the capacity of wastewater treatment facilities. The water quality in the Guanting Reservoir showed a deferred response to the reduced external loading, due to internal loading from sediments. These results implied that for rivers in which streamflow has declined sharply, the water quality could be improved significantly by actions to control water pollution control. This study not only provides useful information for water resource management in the Guanting Reservoir Basin, but also supports the implementation of water pollution control measures in other rivers with a sharp decline in streamflow.

In environments where climate policy has partial coverage or unequal participation, carbon dioxide (CO₂) emissions or economic activity may shift to locations and sectors where emissions are unregulated. This is referred to as leakage. Leakage can offset or augment emissions reductions associated with a policy, which has important environmental and economic implications. Although leakage has been studied at national levels, analysis of leakage for subnational policies is limited. This is despite greater market integration and many existing state and regional environmental regulations in the US. This study explores leakage potential, net emissions changes, and other social implications in the US energy system with regionally differentiated pricing of power sector CO₂ emissions. We undertake an economic analysis using EPRI's US-REGEN model, where power sector CO₂ emissions are priced in individual US regions with a range of social cost of carbon (SCC) values. SCC estimates are being considered by policy-makers for valuing potential societal damages from CO₂ emissions. In this study, we evaluate the emissions implications within the SCC pricing region, within the power sector outside the SCC region, and outside the power sector (i.e. in the rest of the energy system). Results indicate that CO₂ leakage is possible within and outside the electric sector, ranging from negative 70% to over 80% in our scenarios, with primarily positive leakage outcomes. Typically ignored in policy analysis, leakage would affect CO₂ reduction benefits. We also observe other potential societal effects within and across regions, such as higher electricity prices, changes in power sector investments, and overall consumption losses. Efforts to reduce leakage, such as constraining power imports into the SCC pricing region likely reduce leakage, but could also result in lower net emissions reductions, as well as larger price increases. Thus, it is important to look beyond leakage and consider a broader set of environmental and economic metrics. Leakage rates, net emissions outcomes, electricity price changes, fuel market effects, and macroeconomic costs vary by region of the country, time, policy stringency, policy design (e.g. leakage mitigation provisions), policy environment in neighboring regions, and price responsiveness of demand.

Reducing tropical deforestation is potentially a large-scale and low-cost strategy for mitigating climate change. Yet previous efforts to project the cost-effectiveness of policies to reduce greenhouse gas emissions from future deforestation across the tropics were hampered by crude available data on historical forest loss. Here we use recently available satellite-based maps of annual forest loss between 2001–2012, along with information on topography, accessibility, protected status, potential agricultural revenue, and an observed inverted-U-shaped relationship between forest cover loss and forest cover, to project tropical deforestation from 2016–2050 under alternative policy scenarios and to construct new marginal abatement cost curves for reducing emissions from tropical deforestation. We project that without new forest conservation policies 289 million hectares of tropical forest will be cleared from 2016–2050, releasing 169 GtCO₂. A carbon price of US$20/tCO₂ ($50/tCO₂) across tropical countries would avoid 41 GtCO₂ (77 GtCO₂) from 2016–2050. By comparison, we estimate that Brazil's restrictive policies in the Amazon between 2004–2012 successfully decoupled potential agricultural revenue from deforestation and reduced deforestation by 47% below what would have otherwise occurred, preventing the emission of 5.2 GtCO₂. All tropical countries enacting restrictive anti-deforestation policies as effective as those in the Brazilian Amazon between 2004–2012 would avoid 58 GtCO₂ from 2016–2050.

Africa, a continent exceptionally rich in biodiversity, is rapidly urbanizing. Africa's urbanization is manifest in the growth of its megacities as well as that of its smaller towns and cities. The conservation planning and practice will increasingly need to account for direct and indirect impacts of the continent's urbanization. The objective of our study is to pinpoint the outstanding challenges and opportunities afforded by the growing cities on the continent to the conservation goals and practices. While there have been many studies on the impacts of urbanization and development on conservation in Africa these studies tended to focus on specific issues. Here, we provide a synthesis of this body of work supported by new analysis. Urban areas, growing both in population and in land cover, pose threats to the integrity of the continent's ecosystems and biodiversity but their growth also create opportunities for conservation. The burgeoning urban populations, especially in Sub-Saharan Africa, increase the strain on already insufficient infrastructure and bring new governance challenges. Yet, Africa's ecosystems can serve as foundations for green infrastructure to serve the needs of its urban populations while safeguarding fragile biodiversity. Overall, while worsening social problems overshadow the concerns for biodiversity there are also promising initiatives to bring these concerns into the fold to address social, institutional, and ecological challenges that emerge with the continued urbanization of the continent.

Irrigated rice croplands are among the world's most important agro-ecosystems. They provide food for more than 3.5 billion people and a range of other ecosystem services (ESS). However, the sustainability of rice agro-ecosystems is threatened by continuing climate and land-use changes. To estimate their combined effects on a bundle of ESS, we applied the vegetation and hydrology model LPJmL to seven study areas in the Philippines and Vietnam. We quantified future changes in the provision of four essential ESS (carbon storage, carbon sequestration, provision of irrigation water and rice production) under two climate scenarios (until 2100) and three site-specific land-use scenarios (until 2030), and examined the synergies and trade-offs in ESS responses to these drivers. Our results show that not all services can be provided in the same amounts in the future. In the Philippines and Vietnam the projections estimated a decrease in rice yields (by approximately 30%) and in carbon storage (by 15%) and sequestration (by 12%) towards the end of the century under the current land-use pattern. In contrast, the amount of available irrigation water was projected to increase in all scenarios by 10%–20%. However, the results also indicate that land-use change may partially offset the negative climate impacts in regions where cropland expansion is possible, although only at the expense of natural vegetation. When analysing the interactions between ESS, we found consistent synergies between rice production and carbon storage and trade-offs between carbon storage and provision of irrigation water under most scenarios. Our results show that not only the effects of climate and land-use change alone but also the interaction between ESS have to be considered to allow sustainable management of rice agro-ecosystems under global change.

Forests are expected to become more vulnerable to drought-induced tree mortality owing to rising temperatures and changing precipitation patterns that amplify drought lethality. There is a crucial knowledge gap regarding drought–pathogen interactions and their effects on tree mortality. The objectives of this research were to examine whether stand dynamics and 'background' mortality rates were affected by a severe drought in 2012; and to evaluate the importance of drought–pathogen interactions within the context of a mortality event that killed 10.0% and 26.5% of white (Quercus alba L.) and black (Q. velutina Lam.) oak stems, respectively, in a single year. We synthesized (i) forest inventory data (24 years), (ii) 11 years of ecosystem flux data with supporting biological data including predawn leaf water potential and annual forest inventories, (iii) tree-ring analyses of individual white oaks that were alive and ones that died in 2013, and (iv) documentation of a pathogen infection. This forest displayed stand dynamics consistent with expected patterns of decreasing tree density and increasing basal area. Continued basal area growth outpaced mortality implying a net accumulation of live biomass, which was supported by eddy covariance ecosystem carbon flux observations. Individual white and black oaks that died in 2013 displayed historically lower growth with the majority of dead trees exhibiting Biscogniauxia cankers. Our observations point to the importance of event-based oak mortality and that drought–Biscogniauxia interactions are important in shaping oak stand dynamics in this region. Although forest function has not been significantly impaired, these drought–pathogen interactions could amplify mortality under future climate conditions and thus warrant further investigation.

Atmospheric carbon dioxide removal (CDR) technologies may be critical to achieving deep decarbonization. Yet a lack of technical and commercial maturity of CDR technologies hinders potential deployment. Needs for commercialization span research, development, and demonstration (RD&D) activities, including development of new materials, reactors, and processes, and rigorous monitoring of a portfolio of demonstration projects. As a world leader in supporting science and engineering, the United States (US) can play an important role in reducing costs and clarifying the sustainable scale of CDR. To date, federal agencies have focused on voluntary or piecemeal CDR programs.

Here, we present a synthesis of research and developement needs, relevant agency authority, barriers to coordination, and interventions to enhance RD&D across the federal government of the US. On the basis of agency authority and expertise, the Department of Energy, Department of Agriculture, Department of the Interior, National Oceanic and Atmospheric Administration, and National Science Foundation are most central to conducting research, funding projects, monitoring effects, and promulgating regulations. Key enablers for successful programs include embracing technological diversity and administrative efficiency, fostering agency buy-in, and achieving commercial deployment. Based on these criteria, the executive branch could effectively coordinate RD&D strategy through two complementary pathways: (1) renewing intra-agency commitment to CDR in five primary agencies, including both research and demonstration, and (2) coordinating research prioritization and outcomes across agencies, led by the Office of Science and Technology Policy and loosely based on the National Nanotechnology Initiative. Both pathways can be stimulated by executive order or Congressional mandate. Executive branch implementation can begin at any time; future Farm and Energy Bills provide legislative vehicles for enhancing programs.

Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which result in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement.

In our study, we use ANOVA (analyses of variance) to allocate and quantify the main sources of uncertainty in the hydrological impact modelling chain. In turn we determine the statistical significance of different sources of uncertainty. We achieve this by using a set of five climate models and up to 13 hydrological models, for nine large scale river basins across the globe, under four emissions scenarios. The impact variable we consider in our analysis is daily river discharge. We analyze overall water availability and flow regime, including seasonality, high flows and low flows. Scaling effects are investigated by separately looking at discharge generated by global and regional hydrological models respectively. Finally, we compare our results with other recently published studies.

We find that small differences in global temperature rise associated with some emissions scenarios have mostly significant impacts on river discharge—however, climate model related uncertainty is so large that it obscures the sensitivity of the hydrological system.

Bioenergy is booming as nations seek to cut their greenhouse gas emissions. The European Union declared biofuels to be carbon-neutral, triggering a surge in wood use. But do biofuels actually reduce emissions? A molecule of CO₂ emitted today has the same impact on radiative forcing whether it comes from coal or biomass. Biofuels can only reduce atmospheric CO₂ over time through post-harvest increases in net primary production (NPP). The climate impact of biofuels therefore depends on CO₂ emissions from combustion of biofuels versus fossil fuels, the fate of the harvested land and dynamics of NPP. Here we develop a model for dynamic bioenergy lifecycle analysis. The model tracks carbon stocks and fluxes among the atmosphere, biomass, and soils, is extensible to multiple land types and regions, and runs in ≈1s, enabling rapid, interactive policy design and sensitivity testing. We simulate substitution of wood for coal in power generation, estimating the parameters governing NPP and other fluxes using data for forests in the eastern US and using published estimates for supply chain emissions. Because combustion and processing efficiencies for wood are less than coal, the immediate impact of substituting wood for coal is an increase in atmospheric CO₂ relative to coal. The payback time for this carbon debt ranges from 44–104 years after clearcut, depending on forest type—assuming the land remains forest. Surprisingly, replanting hardwood forests with fast-growing pine plantations raises the CO₂ impact of wood because the equilibrium carbon density of plantations is lower than natural forests. Further, projected growth in wood harvest for bioenergy would increase atmospheric CO₂ for at least a century because new carbon debt continuously exceeds NPP. Assuming biofuels are carbon neutral may worsen irreversible impacts of climate change before benefits accrue. Instead, explicit dynamic models should be used to assess the climate impacts of biofuels.