Environmental Research Letters

Published by IOP Publishing
Online ISSN: 1748-9326
Discipline: Environmental Sciences, Meteorology & Atmospheric Sciences
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Environmental Research Letters covers all of environmental science, providing a coherent and integrated approach including research articles, perspectives and review articles.

 

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Recent publications
When addressing concrete carbonation as a carbon mitigation option, studies leave out the effect that a temporal difference between the CO2 emissions and uptake happening throughout concrete’s life cycle have on climate change. In this study, the role played by carbonation on concrete’s carbon mitigation potential is investigated through a dynamic life cycle assessment, to properly position CO2 uptake and release. The carbon balance in concrete structures built and demolished from 2018 to 2050 is modelled as a case study. The potential uptake due to crushed concrete carbonation is over 9% of the cumulative global warming effect of concrete manufacturing. It is comparable to the reduction potential of the most promising strategy, namely replacing clinker, totaling 12%. If stimulated in a wide scale, crushed concrete carbonation can push the industry towards meeting carbon mitigation targets faster. Future environmental impact assessments should rely on dynamic models to increasingly consider this phenomenon.
 
Widespread floods that affect several catchments are associated with large damages and costs. To improve flood protection, a better understanding of the driving processes of such events is needed. Here, we assess how spatial flood connectedness varies with the flood generation process using a flood event classification scheme that distinguishes between rainfall-driven and snowmelt-influenced flood types. Our results show that the dominant flood generation processes in Europe vary by region, season, and event severity. Specifically, we show that severe floods are more often associated with snow-related processes than moderate events. In addition, we find that snow-influenced events show stronger spatial connections than rainfall-driven events. The spatial connectedness of rainfall-driven events depends on the rainfall duration, and the connectedness decreases with increasing duration. These findings have potential implications for flood risk in a warming climate, both locally and regionally. The projected decrease in the frequency of occurrence of snowmelt-influenced floods may translate into a decrease in the frequency of severe and widespread floods in catchments where snowmelt processes are important for flood generation.
 
Human-wildlife conflicts in cities are becoming increasingly common worldwide and are a challenge to urban biodiversity management and landscape planning. In comparison to compensatory management, which often focuses on addressing emergency conflicts, precautionary management allows decision-makers to better allocate limited resources on prioritized areas and initiate long-term actions in advance. However, precautionary approaches have rarely been developed or applied in biodiversity conservation. Since 2020, human-raccoon dog conflicts in Shanghai, one of the largest cities in the world, have tripled in reported number due to the rapid spread of the species in the city from 70 residential districts in 2020 to 249 residential districts in 2022. Here, we use ensemble and circuit modeling to predict suitable raccoon dog habitat and identify their potential dispersal pathways to aid the development of precautionary management strategies. We find that raccoon dog distribution is positively associated with several anthropogenic factors, including residential buildings and nighttime light, which could be signs that the species’ foraging behavior has adapted to the urban environment. We find that raccoon dogs only occupy 10.1% of its suitable habitat, and thus there is a high potential for the expansion of the raccoon dog population and more frequent human-raccoon dog conflicts in the near future. We predict 60 potential dispersal pathways across Shanghai, seven of which cross densely human populated areas and are likely to trigger excessive conflicts. Based on our findings, we propose priority areas where precautionary management strategies, such as constraining stray animal feeding and wildlife-vehicle collision prevention, would potentially alleviate human-raccoon dog conflicts. We present the first study on the precautionary approach of human-wildlife conflict in China’s major cities, and provide a practical example of how comprehensive modeling approaches can be used as the foundation of precautionary management in urban landscapes.
 
Seafood is one of the most internationally-traded food commodities. International markets can provide higher revenues that benefit small-scale fishing communities but can also drive a decline in fished populations. Collective action in collective organizations such as fishing cooperatives is thought to enhance the sustainability of fished populations. However, our knowledge of how collective action enables fishing cooperatives to achieve positive social-ecological outcomes is dispersed across case studies. Here, we present a quantitative, national-level analysis exploring the relationship between different levels of collective action and social-ecological outcomes. We found that strong collective action in Mexican lobster cooperatives was related to both sustaining their fisheries and benefiting from international trade. In the 15-year study period, lobster cooperatives that demonstrate characteristics associated with strong collective action captured benefits from trade through high catch volumes and revenue. Despite lower (but stable) average prices, the biomass of their lobster populations was not compromised to reap these benefits. Individual case studies previously found that fishing cooperatives can support both positive social and ecological outcomes in small-scale fisheries. Our results confirm these findings at a national level and highlight the importance of strong collective action. Thus, our work contributes to a better understanding of the governance arrangements to promote fishing communities' welfare and benefits from international trade and, therefore, will be invaluable to advancing small-scale fisheries governance.
 
Global economic development and urbanization during the past two decades have driven the increases in demand of personal and commercial vehicle fleets, especially in developing countries, which has likely resulted in changes in year-to-year vehicle tailpipe emissions associated with aerosols and trace gases. However, long-term trends of impacts of global gasoline and diesel emissions on air quality and human health are not clear. In this study, we employ the Community Earth System Model (CESM) in conjunction with the newly developed Community Emissions Data System (CEDS) as anthropogenic emission inventory to quantify the long-term trends of impacts of global gasoline and diesel emissions on ambient air quality and human health for the period of 2000-2015. Global gasoline and diesel emissions contributed to regional increases in annual mean surface PM2.5 (particulate matter with aerodynamic diameters ≦ 2.5 µm) concentrations by up to 17.5 and 13.7 µg/m3, and surface ozone (O3) concentrations by up to 7.1 and 7.2 ppbv, respectively, for 2000-2015. However, we also found substantial declines of surface PM2.5 and O3 concentrations over Europe, the US, Canada, and China for the same period, which suggested the co-benefits of air quality and human health from improving gasoline and diesel fuel quality and tightening vehicle emissions standards. Globally, we estimate the mean annual total PM2.5- and O3-induced premature deaths are 139,700-170,700 for gasoline and 205,200-309,300 for diesel, with the corresponding years of life lost of 2.74-3.47 and 4.56-6.52 million years, respectively. Diesel and gasoline emissions create health-effect disparities between the developed and developing countries, which are likely to aggravate afterwards.
 
China plays an important role in the international trade of agricultural commodities. Considering the dynamic reactive nitrogen (Nr) losses of agricultural systems in China, a hypothesis was proposed that crop conversion in China would be correlated with the extent of crop trade, influencing Nr losses in agricultural systems. The objective of this study was to verify the hypothesis based on a hybrid approach, which incorporated life cycle analysis (LCA), copula-Markov Chain Monte Carlo (MCMC) simulation, and copula sampling. The approach was proven to be of benefit in (a) evaluating Nr losses in crop planting based on a LCA framework, (b) identifying dependencies and co-movements of the correlated variables in planting structures and crop trade using copula-MCMC simulations, and (c) recognizing fluctuations in Nr losses of crop planting in the future using copula-based sampling method. The planting structures and international trade of four types of crops (i.e., wheat, soybeans, maize, and rice) in twenty provinces of China indicated significant correlations, thus supporting the initial hypothesis. With the improvement of self-sufficiency in crop production, especially soybeans, Nr losses from the crop production of China in 2025 and 2030 would decrease by 8.43% and 4.26%, compared with those in 2018 (i.e., 1916.74 kt N).
 
Effective citizen engagement is generally accepted as one of the most important steps for the success of citizen science programs. However, there is a lack of a common theoretical framework for recruitment and most projects rely on intuition or trial-and-error to develop their engagement strategies. Effective citizen science engagement needs theoretical participation frameworks and the concurrent action of different engagement roles to implement the framework. Besides, we must consider the various short-term and long-term engagement needs of the communities involved in the project. Furthermore, citizen science platforms are evolving towards infrastructures with technical but also social components to ensure long-term engagement. In this study, we have developed and tested an engagement framework for environmental citizen science projects using a novel approach that combines strategies and theoretical models that have proven efficient in other disciplines, such as human behaviour change and persuasion. Our framework is based on four interconnected pillars that feed each other: theoretical engagement models for behavioural change; social design for citizen science platforms, strategies for maintaining volunteer motivation; and strategies to increment the volunteers’ ability. The combination of these four pillars results in a framework that integrates both short-term and long-term interaction mechanisms. This multi-temporal approach ensures keeping volunteers motivated and engaged for long periods, a requirement for many citizen science-monitoring programs. In addition, the theoretical framework points out the benefits of considering citizen science projects as a collaboration between multiple stakeholders to ensure long-term engagement. These stakeholders include the volunteers, but also new roles such as enabling communities that act as a bridge between volunteers and academia. Specifically, we have successfully tested this framework in a marine citizen science case study that monitors urban beaches. Furthermore, together with the proposed framework, we provide specific guidelines to help managers to design tailored strategies for their citizen science projects.
 
Freshwater ecosystems are the most vulnerable environments worldwide and the most biodiverse, providing essential ecosystem services. The role of land management in agriculture is paramount with the dramatic increase in pesticides: two million tonnes used worldwide (47.5% herbicides, 29.5% insecticides, and 17.5% fungicides) are jeopardising freshwater ecosystems. Concerns about the risk of pesticide contamination from viticulture have led to implementing nature-based mitigation measures (buffer strips and hedgerows) and technical improvements. The general aim is to assess spatial proximity among vineyards and river networks within the Prosecco DOCG area to identify potential critical areas for pesticide contamination. Specific objectives are: i) mapping vineyards within the Prosecco DOCG area, ii) identifying river banks with a higher probability of experiencing pesticide contamination, and iii) mapping critical areas potentially affected by pesticide contamination. Spatial modelling was based on very high geometric resolution ortophotos (50 cm), LiDAR data (1 m), and morpho-hydrological parameters of the river network. Proximity and morpho-hydrological modelling showed that due to little distance from Prosecco cropland (5–20 m), freshwater ecosystems may be affected in different basins by spray drift pesticide contamination. Distances between vineyards and streams were shown to be critical, as 35.7% and 13.9% of river banks were within 20 m and 5 m distance from vineyards, respectively. Furthermore, 52% of basins presented river banks intersecting vineyards at 5 m, while 37% were within 20 m distance. Such hotspots should be investigated in the field for watershed-based quality assessment. However, mitigation scenarios indicate that spray drift contamination might be reduced by 75%, minimising the effect from 20 m to 5 m distance from vineyards and, therefore, avoiding reaching part of riparian and aquatic ecosystems. Geovisualisation of river banks proximity at watershed level offered insight into area with high probability of experiencing pesticide contamination from vineyards due to spray drift.
 
Global change may contribute to ecological changes in high-elevation lakes and reservoirs, but a lack of data makes it difficult to evaluate spatiotemporal patterns. Remote sensing imagery can provide more complete records to evaluate whether consistent changes across a broad geographic region are occurring. We used Landsat surface reflectance data to evaluate spatial patterns of contemporary lake color (2010-2020) in 940 lakes in the U.S. Rocky Mountains, a historically understudied area for lake water quality. Intuitively, we found that most of the lakes in the region are blue (66%) and were found in steep-sided watersheds (>22.5º) or alternatively were relatively deep (>4.5m) with mean annual air temperature (MAAT) <4.5ºC. Most green/brown lakes were found in relatively shallow sloped watersheds with MAAT ≥4.5ºC. We extended the analysis of contemporary lake color to evaluate changes in color from 1984-2020 for a subset of lakes with the most complete time series (n=527). We found limited evidence of lakes shifting from blue to green states, but rather, 55% of the lakes had no trend in lake color. Surprisingly, where lake color was changing, 32% of lakes were trending toward bluer wavelengths, and only 13% shifted toward greener wavelengths. Lakes and reservoirs with the most substantial shifts toward blue wavelengths tended to be in urbanized, human population centers at relatively lower elevations. In contrast, lakes that shifted to greener wavelengths did not relate clearly to any lake or landscape features that we evaluated, though declining winter precipitation and warming summer and fall temperatures may play a role in some systems. Collectively, these results suggest that the interactions between local landscape factors and broader climatic changes can result in heterogeneous, context-dependent changes in lake color.
 
Climate change is altering wildfire behavior and vegetation regimes in California’s forested ecosystems. Present day fires are seeing an increase in high burn severity area and high severity patch size. The ability to predict future burn severity patterns would support better policy and land management decisions. Here we demonstrate a methodology to first, statistically estimate individual burn severity classifications at 30 meters and second, cluster and smooth high severity patches onto a landscape. Our goal here was not to exactly replicate observed burn severity maps, but rather to utilize observed maps as one realization of a random process dependent on climate, topography, fire weather, and fuels, to inform creation of additional realizations through our simulation technique. We developed two sets of empirical models with two different vegetation datasets to test if coarse vegetation could accurately model for burn severity. While visual acuity can be used to assess the performance of our simulation process, we also employ the Ripley’s K function to compare spatial point processes at different scales to test if the simulation is capturing an appropriate amount of clustering. We utilize FRAGSTATS to obtain high severity patch metrics to test the contiguity of our high severity simulation. Ripley’s K function helped identify the number of clustering iterations and FRAGSTATS showed how different focal window sizes affected our ability to cluster high severity patches. High severity patch simulations was comparable between the coarse and fine resolution vegetation datasets. Improving our ability to simulate burn severity will help advance our understanding of the potential influence of land and fuels management on ecosystem-level response variables that are important for decision-makers. Simulated burn severity maps can support managing habitat and estimating risks of habitat loss, protecting infrastructure and homes, improving future wildfire emissions projections, and better mapping and planning for fuels treatment scenarios.
 
Rapid increase in global mortality caused by anthropogenic ozone. The y-axis shows the premature deaths attributable to total ozone (a) and transboundary ozone (b) caused by anthropogenic emissions in four income groups. The wide bars with dark colors indicate the mortality contributions by individual groups. The narrower bars with lighter colors indicate the individual effects of changes in ozone, population and baseline mortality rate. The change in baseline mortality rate before 1990 is not accounted for, due to limited data availability.
Mortality contribution caused by transboundary ozone from a source versus a receptor perspective. The x-axis shows the ratio of nonlocal to global premature deaths caused by a source region, and the y-axis shows the ratio of foreign to total impact exerted upon a receptor region. The circles denote results for individual years, with the lightest colors representing 1951 and the darkest for 2019. The colors differentiate the income groups: high-income (red), upper middle (orange), lower middle (green), and low-income (blue). The circles with thick black coats denote the average situations over 1951–2019.
Bi-directional transboundary ozone related health responsibility. Each cell in the grid shows the premature deaths in a receptor region due to anthropogenic emissions per million people in a source region. HI, UMI, LMI and LI is short for high-income, upper middle income, lower middle income and low-income group, respectively.
Linking regional affluence level to its mortality contribution attributable to transboundary ozone. The y-axis shows transboundary ozone related factional mortality impact (the ratio of mortality to total population outside the source region) (a), transboundary population-weighted MDA8 ozone (b), NO x emissions (c) and NMVOC emissions (d) caused by every million people in each source region. The x-axis shows per capita GDP of each source region.
Ozone pollution is a major transboundary threat to global health. Systematic improvement of mitigation strategy for transboundary ozone requires a socioeconomic understanding of historical lessons in countries at different affluence levels. Here, we explore the changes in transboundary ozone related premature deaths over 1951–2019 driven by anthropogenic emissions of four country groups categorized by income level. By integrating global emission datasets, a chemical transport model (GEOS-Chem), in situ ozone measurements worldwide and an ozone exposure-response model, we find that mortality caused by transboundary anthropogenic ozone increases by 27 times from 1951 to 2019, and on average contributes about 27% of global anthropogenic ozone related deaths. All groups exert and suffer from substantial transboundary ozone related mortality. The high-income and upper middle groups have each experienced an inverted U-shaped relationship between its affluence and per-million-people contribution to mortality caused by transboundary ozone, with the turning point around 23,000 USD and 6,300 USD, respectively. The lower middle group has gradually matched the growth pathway of the upper middle group with a turning point less clear. Concerted efforts to ensure early turning points in less affluent countries will have considerable global health benefits.
 
Recent decades have seen the rapid expansion of scholarship that identifies societal responses to past climatic fluctuations. This fast-changing scholarship, which was recently synthesized as the History of Climate and Society (HCS), is today undertaken primary by archaeologists, economists, geneticists, geographers, and paleoclimatologists. This review is the first to consider how all scholars in all of these disciplines approach HCS studies. It begins by explaining how climatic changes and anomalies are reconstructed by paleoclimatologists and historical climatologists. It then provides a broad overview of major changes and anomalies over the 300,000-year history of Homo sapiens, explaining both the causes and environmental consequences of these fluctuations. Next, it introduces the sources, methods, and models employed by scholars in major HCS disciplines. It continues by describing the debates, themes, and findings of HCS scholarship in its major disciplines, and then outlines the potential of transdisciplinary, “consilient” approaches to the field. It concludes by explaining how HCS scholars increasingly attempt to identify relationships between past climatic and human histories that can inform policy development and activism around anthropogenic global warming.
 
As components of terrestrial carbon sinks, vegetation and soil carbon pools are important for offsetting CO2 emissions. However, differences in their carbon sequestration capacities and their responses to global change in the future are poorly understood. This study assessed the changes in vegetation and soil carbon and their ratios and drivers under the SSP126 scenario from 2015 to 2060, using Coupled Model Intercomparison Project phase 6 (CMIP6) simulations in China, a major carbon sink region in global terrestrial ecosystems. The content of vegetation carbon (29±1 PgC) was observed to be lower than that of soil carbon (113±23 PgC), and the ratio of vegetation to soil carbon was the highest in the subtropical-tropical monsoon climatic region (0.55±0.12). Moreover, the total stock of vegetation and soil carbon increased by 10±1 PgC during the study period, and the increase in vegetation carbon was 4.31 times that of soil carbon, because the responses of vegetation carbon stocks to increased forest coverage and atmospheric CO2 were greater than that of soil carbon stocks, especially in the subtropical-tropical and temperate monsoonal climatic regions. However, bare land encroachment on grasslands reduced their increments in the temperate monsoonal and high-cold Tibetan Plateau climatic regions. Furthermore, compared with SSP245 and SSP585 scenarios, vegetation and soil carbon sinks can offset a greater amount of carbon emissions in 2060 under the SSP126 scenario, accounting for 53% of all carbon emissions, offsetting 60%–79% of carbon emissions from China under its policy of increasing forest coverage. The study revealed the important role of afforestation in increasing ecosystem carbon stocks, additionally, grassland conservation and deep reductions in carbon emissions cannot be ignored in the future. This study provides a basis for determining the response of vegetation and soil carbon to environmental factors and the realization of net-zero emissions globally.
 
A state-of-the-art regio an l assessment of future directional wave spectra in the Mediterranean Sea and the projected changes with respect to hindcast is presented. A multi-model EURO-CORDEX regional ensemble of bias-adjusted wave climate projections in eleven locations of the Mediterranean are used for the assessment of future se sa onal changes in the directional wave spectra under the high-emission scenario RCP8.5. This analysis allows to ide tn ify climate change effects on the spec rt al energy of the swell and wind-sea modes and their seasonal variability which cannot be captured with the standard integrated wave parameters such as significant wave height and mean wave direction. The results show an overall robust decrease in the predominant wave modes resulting in a likely decrease in the significant wave height in agreement with previous studies. However, the resu tl s depict a robust increase in other less energetic frequencies and directions lead ng to a proji ected behavioral change from unimodal to bimodal/multimodal wave climate in many locations which has strong repercussions on the vulnerability of coastal assets and ports operability.
 
The regressed JASO mean SST with reference to original time series of PCs of the first two leading EOF modes of simultaneous North Pacific SST (a), (b) from 1965 to 2020, respectively (in °C). Bar charts in (c) show the time series of the PCs of the first leading EOF modes. The black curve in (c) indicates the interannual variation of WNP total TCG. (d), (e) Correlation maps between the decadal component of WNP TCG and PC1 from 1965 to 2020 on the 2° × 2° (d) and 5° × 5° grid (e). The green boxes in (d) and (e) outline the major regions of significant positive (region A, 5° N–35° N, 120° E–140° E) and negative (region B, 5° N–30°N, 140° E–170° E) correlation. Dots and × indicate that the correlation coefficients are statistically significant at a 95% confidence level. The effective degrees of freedom on a decadal time scale in (d) range from 28 to 35 among different grid points.
(a) The regression field of the ENGPI index with respect to PC1. JASO mean ENGPI anomaly associated with PC1-regressed changes in (b) total anomalies, (c) 850 hPa relative vorticity (S850), (d) 600 hPa relative humidity (RH), (e) maximum potential intensity (MPI) and (f) 850–200 hPa vertical wind shear (VWS), respectively. The mean contributions of each term to ENGPI anomalies over region A and region B are shown in panel (g). Dots indicate that the regression coefficient is statistically significant at the 95% confidence level. The black boxes outline the same region as that in figure 3. The green contours on panel (a) show ENGPI climatology from 1965 to 2020.
Same as figure 2 but for DGPI. (a) PC1-regressed field of DGPI. (b)–(f) JASO mean DGPI anomaly associated with PC1-regressed changes in (b) total anomalies, (c) 850 hPa relative vorticity (S850), (d) 500 hPa meridional gradient of zonal wind (Uy), (e) 500 hPa omega (W500) and (f) 850–200 hPa vertical wind shear (VWS), respectively. The mean contributions of each term to DGPI anomalies over regions A and B are shown in panels (g) and (h), respectively.
The PC1-regressed fields of (a) SST (°C), (b) precipitation (mm d⁻¹), geopotential height (shading, m² s⁻²) and wind field (vector, m s⁻¹) at (c) 850 hPa and (d) 200 hPa, (e) 500 hPa omega (10⁻³ Pa s⁻¹), (f) 850–200 hPa vertical wind shear (m s⁻¹), (g) 600 hPa relative humidity (%) and (h) off-equatorial east–west secondary circulation on a decadal time scale. All data, including PC1, SST and circulations are firstly filtered using a 7 year low-pass Butterworth filter before producing the regression fields. The off-equatorial circulation is composed of vertical velocity (Pa s–1) and zonal wind (m s⁻¹) averaged between 5° N and 30° N. The vertical velocity is multiplied by a scale factor calculated as the mean zonal wind speed divided by the mean vertical velocity. Only a statistically significant wind (vector) at the 95% confidence level is shown.
Consequential box diagram of the mechanism by which the NPGO affects WNP TCG.
North Pacific Gyre Oscillation (NPGO) is one of the important modes of decadal variability in the North Pacific sea surface temperature (SST) and sea surface height (SSH). This study investigated the potential influence of NPGO on spatial characteristics of the peak season (July to October) tropical cyclones (TCs) genesis (TCG) number over the western North Pacific (WNP) from 1965 to 2020. We show that NPGO is the first leading Empirical Orthogonal Function (EOF) mode of the North Pacific SST during the TC peak season in the recent 56 years. On the decadal time scale, NPGO has opposite impacts on TCG in the west and east WNP. The relatively weak positive correlation in the west of 140°E and the strong positive correlation in the east of 140°E result in an overall significant negative correlation between NPGO and WNP total TCG number (r = -0.49), which is much more robust than the relationship between Pacific Decadal Oscillation (PDO) and TCG. The critical factors of NPGO affecting TCG are the vertical motion in the west WNP and vertical wind shear (VWS) in the east WNP. The positive NPGO pattern could induce an anomalous off-equatorial vertical circulation, resulting in an upward motion and increased convective precipitation in the west WNP, favoring local TCG. The anomalous convective precipitation enhances the zonal gradient of the atmospheric heat source in the east WNP, increasing VWS. The North Pacific low-level anticyclonic and upper-level cyclonic associated with NPGO further enhance the VWS in the east WNP and lead to the negative low-level relative vorticity, inhibiting local TCG. This study emphasizes the importance of the NPGO’s climate impact in recent decades. The findings here have significant implications for the decadal prediction of WNP TCG change.
 
In this study, we investigate whether the Pacific Decadal Oscillation (PDO) can enhance or diminish El Niño Southern Oscillation (ENSO) temperature and precipitation teleconnections over North America using five single model initial-condition large ensembles (SMILEs). The use of SMILEs facilitates a statistically robust comparison of ENSO events that occur during different phases of the PDO. We find that a positive PDO enhances winter and spring El Niño temperature and precipitation teleconnections and diminishes La Niña teleconnections. A negative PDO has the opposite effect. The modulation of ENSO by the PDO is mediated by differences in the location and strength of the Aleutian Low and Pacific Jet during ENSO events under different phases of the PDO. This modulation is a simple combination of the individual effects of the PDO and ENSO over North America. Finally, we show that ENSO and the PDO can be used to evaluate the likelihood of the occurrence of temperature and precipitation anomalies in different regions, but cannot be used as a deterministic predictor of these anomalies due to the large variability between individual events.
 
Introduction: Although cities globally are increasingly mobilizing re-naturing projects to address diverse urban socio-environmental and health challenges, there is mounting evidence that these interventions may also be linked to the phenomenon known as green gentrification. However, to date the empirical evidence on the relationship between greenspaces and gentrification regarding associations with different greenspace types remains scarce. Methods: This study focused on 28 mid-sized cities in North America and Western Europe. We assessed improved access to different types of greenspace (i.e. total area of parks, gardens, nature preserves, recreational areas or greenways (i) added before the 2000s or (ii) added before the 2010s) and gentrification processes (including (i) gentrification for the 2000s; (ii) gentrification for the 2010s; (iii) gentrification throughout the decades of the 2000s and 2010s) in each small geographical unit of each city. To estimate the associations, we developed a Bayesian hierarchical spatial model for each city and gentrification time period (i.e. a maximum of three models per city). Results: Our study reveals that parks – together with other factors such as proximity to the city center – may contribute to gentrification processes, particularly in the US context, except in historically Black disinvested postindustrial cities with lots of vacant land. We also found some indications of newly designated nature preserves being negatively associated with gentrification processes, particularly when considering gentrification throughout the 2000s and the 2010s and in the US. Meanwhile, for new gardens, recreational spaces and greenways, our research shows mixed results. Conclusions: Considering the environmental and health benefits of urban re-naturing projects, cities should keep investing in improving park access while simultaneously implementing anti-displacement and inclusive green policies.
 
The main seasonal characteristics in the tropics include both spatial patterns and temporal parameters of onset, cessation, duration, and the number of wet and dry seasons. Previous studies showed that wet seasons shortened and dry seasons extended with global warming, but the changes in spatial distribution and the number of wet and dry seasons are still unclear. Here, we analyze the climatic characteristics of once wet and dry season a year (annual regime) and twice wet and dry seasons a year (biannual regime), and find that regimes of wet and dry seasons have changed from 1935 to 2014. Across the equator and the Tropic of Cancer and Capricorn, some regions where there used to be an annual regime have become a biannual regime; instead, other regions have shifted from a biannual regime into an annual regime. With seasonal regimes shifting, areas of the biannual regime have expanded at a rate of 31000 km2/decade. Meanwhile, in annual regime regions, wet seasons have been shortened in 60.3% of regions, with an average of 7 days; the onset dates of wet seasons have been delayed in 64.8%, with an average of 6 days. Besides, wet seasons have become wetter in 51.1% of regions, and dry seasons have become drier in 59.9%. In biannual regime regions, the shortened wet seasons have occurred in 83.7% of regions, with an average shortening of 8 days, and precipitation has decreased in both wet and dry seasons. Moreover, the shorter wet seasons will amplify further by the end of the 21st century. The continuous seasonal changes will threaten agricultural, ecological security, and even human well-being.
 
Distribution of scores obtained on each of the 16 food groups [Scores 1, 2 and 3 generally refer to consumption within acceptable limits of a food group. A 0 score generally means
Percent of households meeting the EAT-Lancet guidelines by number of food groups [Total number of food
Facilitating dietary change is pivotal to improving population health, increasing food system resilience, and minimizing adverse impacts on the environment, but assessment of the current 'status-quo' and identification of bottlenecks for improvement has been lacking to date. We assessed deviation of the Gambian diet from the EAT-Lancet guidelines for healthy and sustainable diets and identified leverage points to improve nutritional and planetary health. We analysed the 2015/16 Gambian Integrated Household Survey dataset comprising food consumption data from 12,713 households. Consumption of different food groups was compared against the EAT-Lancet reference diet targets to assess deviation from the guidelines. We computed a "sustainable and healthy diet index (SHDI)" based on deviation of different food groups from the EAT-Lancet recommendations and modelled the socio-economic and geographic determinants of households that achieved higher scores on this index, using multivariable mixed effects regression. The average Gambian diet had very low adherence to EAT-Lancet recommendations. The diet was dominated by refined grains and added sugars which exceeded the recommendations. SHDI scores for nutritionally important food groups such as fruits, vegetables, nuts, dairy, poultry, and beef and lamb were low. Household characteristics associated with higher SHDI scores included: being a female-headed household, having a relatively small household size, having a schooled head of the household, having a high wealth index, and residing in an urban settlement. Furthermore, diets reported in the dry season and households with high crop production diversity showed increased adherence to the targets. While average Gambian diets include lower amounts of food groups with harmful environmental footprint, they are also inadequate in healthy food groups and are high in sugar. There are opportunities to improve diets without increasing their environmental footprint by focusing on the substitution of refined grains by wholegrains, reducing sugar and increasing fruit and vegetables consumption.
 
Annual total malaria cases from 1976 to 2016 for Costa Rica and Panama.
Date of Bd-driven amphibian decline (DoD) in Costa Rica and Panama. Observed DoD points are directly labeled with years. Color shading indicates county-level earliest DoD, estimated using a spatial spread process model. Hashing indicates counties excluded in the preferred specification.
Estimated effect on malaria cases per 1000 population (vertical axis) of year k (horizontal axis) relative to Bd-driven date of amphibian decline (DoD). Confidence intervals are given by shading (95%) and dashed lines (90%).
Biodiversity in ecosystems plays an important role in supporting human welfare, including regulating the transmission of infectious diseases. Many of these services are not fully-appreciated due to complex environmental dynamics and lack of baseline data. Multicontinental amphibian decline due to the fungal pathogen Batrachochytrium dendrobatidis (Bd) provides a stark example. Even though amphibians are known to affect natural food webs—including mosquitoes that transmit human diseases—the human health impacts connected to their massive decline have received little attention. Here we leverage a unique ensemble of ecological surveys, satellite data, and newly digitized public health records to show an empirical link between a wave of Bd-driven collapse of amphibians in Costa Rica and Panama and increased human malaria incidence. Subsequent to the estimated date of Bd-driven amphibian decline in each ‘county’ (canton or distrito), we find that malaria cases are significantly elevated for several years. For the six year peak of the estimated effect, the annual expected county-level increase in malaria ranges from 0.76 to 1.1 additional cases per 1000 population. This is a substantial increase given that cases country-wide per 1000 population peaked during the timeframe of our study at approximately 1.5 for Costa Rica and 1.1 for Panama. This previously unidentified impact of biodiversity loss illustrates the often hidden human welfare costs of conservation failures. These findings also show the importance of mitigating international trade-driven spread of similar emergent pathogens like Batrachochytrium salamandrivorans.
 
Ecological restoration (ER) programs play an important role in local and global climate change and carbon management policy interventions. Water resource is a key criterion for assessing the sustainability of ERs. Herein, we explored the spatiotemporal patterns of rainfall interception (RI, an important component of ecosystem water budgets), and its drivers after ER implementation in China. Further, we assessed whether ERs are sustainable by analyzing the trends of RI and water supply. As expected, we found that ERs caused an increase in RI in China from 2001 to 2018 (0.64 mm yr −1 , p < 0.01). Changes in the normalized difference vegetation index and leaf area index contributed to a higher change in RI compared with other drivers. The decrease in RI was mainly recorded in the Qinghai-Tibet Plateau in Southwest, northern North, and southern Central and Southern China. Conversely, an increasing trend of RI was recorded in the Loess Plateau in Northwest, Northeast, and East China. Moreover, ERs are not always unsustainable in China, especially in Northeast, East, Central and Southern, and high-latitude regions of northern North China. Even in the Loess Plateau, which was criticized by previous studies, the unsustainability occurred only in the semi-humid region. Future ERs should be prioritized in southern parts of Eastern, Central, and Southern China, and must be appropriately considered in the Northeast and high-latitude regions in North China. It should be alert to the pressures of ERs on water supply, and its demand remains vigilant in the Qinghai-Tibet Plateau and semihumid areas of the Loess Plateau. This study provides new ideas for accurately evaluating the impact of ERs on water security and the sustainability of ERs.
 
(a)–(k) Display the distributions of PM10 concentration, population size, number of available homes, percent of owner-occupied homes, median home value, per capita income, median rent cost, and racial composition measures for the 30, 434 census tract-year observations that compose the sample. Black dots represent individual observations, area plots represent the probability densities of observations across all tracts. Box and whisker plots represent summary statistics, with the thick vertical bar being the median value, the box the interquartile range (IQR), and the lines the l.5 IQR extent.
(a)–(k) Display the distributions of PM10 concentration, population size, number of available homes, percent of owner-occupied homes, median home value, per capita income, median rent cost, and racial composition measures for the 30, 434 census tract-year observations that compose the sample, conditioned upon HOLC grade. Black dots represent individual observations, area plots represent the probability densities of observations across tracts, conditioned on HOLC grade. Box and whisker plots represent summary statistics, with the thick vertical bar being the median value, the box the interquartile range (IQR), and the lines the l.5 IQR extent. HOLC score is along the vertical axis of the plot.
(a)–(d) Display the estimated outcomes of the interactions presented in models 3–6 of table 1. Solid lines represent estimates. Shaded area represents 95% confidence intervals. For ease of interpretation we only show estimates for tracts with HOLC scores of A (green) and D (red).
We explore how Home Owners' Loan Corporation (HOLC) scores of the 1930s impact 2010 and 2015 inhalable particulate matter (PM10) concentrations for 15,232 census tracts, clustered in 196 cities throughout the contiguous United States. Using areal apportionment, we assign a HOLC score to housing tracts and construct hierarchical linear models to examine the relationship between the policy practice of redlining, particulate matter pollution, and urban economic development. We find that redlining is associated with higher PM10 concentrations, and that higher HOLC grades also intensify the association of per capita income, median rent, median home values, and racial composition with PM10. These findings suggest that historical policy programs that were grounded in racial logics– such as the HOLC practice of “redlining”– have an inertia that results in them influencing development pathways and environmental outcomes of built environments for decades.
 
Illustration of the method gap limiting our understanding of source/sink attribution and regulation of GHG fluxes. Enclosure-based methods yield local flux measurements at m² scales that are challenging to extrapolate to large scales (upper left; different colors denote different flux levels). Open methods yield net flux over larger areas (upper right; the mean net flux for the whole area detected as denoted by the ‘mean color’). Needed GHG flux measurement methods bridging this gap and detect fluxes at multiple scales simultaneously are visualized in the lower panel, where differences between local fluxes and their localization would be resolved over the entire landscape. Please note that methods to quantify GHG fluxes (i.e. not just GHG concentrations) are in focus here.
Reaching climate goals depends on appropriate and accurate methods to quantify greenhouse gas (GHG) fluxes and to verify that efforts to mitigate GHG emissions are effective. We here highlight critical advantages, limitations, and needs regarding GHG flux measurement methods, identified from an analysis of >13500 scientific publications regarding three long-lived GHGs, carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). While existing methods are well-suited for assessing atmospheric changes and local fluxes, they are expensive and have limited accessibility. Further, we are typically forced to choose between methods for very local GHG sources and sinks and their regulation (m2-scaled measurements), or methods for aggregated net fluxes at > ha or km2 scales measurements. The results highlight the key need of accessible and affordable GHG flux measurement methods for the many flux types not quantifiable from fossil fuel use, to better verify inventories and mitigation efforts for transparency and accountability under the Paris agreement. The situation also calls for novel methods, capable of quantifying large scale GHG flux patterns while simultaneously distinguishing local source and sink dynamics and reveal flux regulation, representing key knowledge for quantitative GHG flux modeling. Possible strategies to address the identified GHG flux measurement method needs are discussed. The analysis also generated indications of how GHG flux measurements have been distributed geographically and across flux types, which are reported.
 
The timing and rate of northern high latitude spring snowmelt plays a critical role in surface albedo, hydrology, and soil carbon cycling. Ongoing changes in the abundance and distribution of trees and shrubs in tundra and boreal ecosystems can alter snowmelt via canopy impacts on surface energy partitioning. It is unclear whether vegetation-related processes observed at the ecosystem scale influence snowmelt patterns at regional or continental scales. We examined the influence of vegetation cover on snowmelt across the boreal and Arctic region across a ten-year reference period (2000-2009) using a blended Snow Water Equivalent (SWE) data product and gridded estimates of surface temperature, tree cover, and land cover characterized by the dominant plant functional type. Snow melt rates were highest in locations with a late onset of melt, higher temperatures during the melt period, and higher maximum SWE before the onset of melt. After controlling for temperature, melt onset, and the maximum SWE, we found snow melt rates were highest in evergreen needleleaf forest, mixed boreal forest, and herbaceous tundra compared to deciduous needleleaf forest and deciduous shrub tundra. Tree canopy cover had little effect on snowmelt rate within each land cover type. While accounting for the influence of vegetative land cover type is necessary for predictive understanding of snowmelt rate variability across the Arctic-Boreal region. The relationships differed from observations at the ecosystem and catchment scales in other studies. Thus highlighting the importance of spatial scale in identifying snow-vegetation relationships.
 
Relation among data sources and models within the global integrated dynamic optimization model of the forest and agriculture sectors.
Biomes projected by MC2 DGVM and changes in aboveground forest and woodland carbon stock over the course of the 21st century. (a) Forest and woodland biomes in the MC2 model. Absolute (b) and relative (c) changes in carbon stock between recent historical period (1983–2021) and the end of the 21st century (2070–2099) produced by MC2 DGVM under the reference climate change scenario, a high-warming scenario analogous to RCP 8.5 (Kim et al 2017). The △C maps represent the average of 70 simulations performed under the reference scenario. The 70 simulations result from seven variations in model configurations, each variation replicated ten times to capture variability in MC2’s stochastic behavior. The variations in model configurations include different climate sensitivity, net aerosol forcing, and natural variability (initial conditions) and are described in detail in section 2.1 and table 1 in Kim et al (2017).
Impacts of climate change on forests. (a) Relationship between CO2 concentration and change in forest growth, defined as the percent change in new tree biomass growth over the course of one decade, in five biomes in the United States (Southern Pine, Southern Mixed, Northern Mixed, Western Conifer, and Woodland) and four biomes in the rest of the world (Boreal, Temperate cool, Temperate warm, Tropical). Forest growth in the Woodland biome in the RoW does not change with increased CO2 concentration. (b) The relationship between temperature anomaly (relative to the beginning of the 21st century) and dieback rate is defined as the percent reductions in forest stocks per decade due to forest fires. The relationship for the Woodland biome in the RoW is similar to the one for Temperate Warm in the RoW and is not shown. Crosses are simulation results from the MC2 DGVM (Kim et al 2017) for the three emissions scenarios (see section 5 in the supplementary information). The solid line represents the fitted relationship between change in timber growth and CO2 concentration (a) and dieback rate and change in global surface temperature (b). Dashed lines represent lower and upper bounds on fitted relationships.
Impact of climate change on aboveground forest carbon stock in managed and natural forests in 2100 by biome, %. The impacts are calculated as the difference between forest carbon stock with and without impacts of climate change in 2100, relative to forest carbon stock in 2100 when climate impacts are not considered. Green ( g ), orange ( d ) and yellow ( a ) columns show deviations in forest carbon stock when impacts of climate change on growth, dieback, and crops, respectively, are incorporated into the model one at a time. Brown columns (s) show deviations in forest carbon stock when all three impacts are incorporated into the model. s≈1+g/100∗1+d/100∗1+a/100−1∗100 . The reduction in forest carbon stock in the Woodland biome in the RoW is small (0.28%) and not shown.
Change in the cost of reaching forest carbon stock targets due to climate change impacts (CCI) relative to the costs of reaching the same targets under no climate impacts assumption, %. Low, medium, and high targets correspond to global forest carbon stocks increased by 5%, 10%, and 20% in 2100 relative to optimal forest carbon stock in the no-climate-impact baseline. Costs of the policies are evaluated when all CCI, on timber growth, dieback, and crop yields (first set of bars), only CCI on timber growth (second set of bars), only CCI on dieback (third set of bars), CCI on both timber growth and dieback (fourth set of bars), and only CCI on crops (fifth set of bars) are considered. Error bars show uncertainty in the relative change in forest carbon sequestration costs due to uncertainty in climate change impacts on forests and crops. The uncertainty is quantified as described in the table 1 caption. The uncertainty in the change in costs due to both CCI on timber growth and dieback is quantified using a combination of upper (lower) bounds on the fitted relationship between change in global surface temperature and dieback, and lower (upper) bounds on the fitted relationship between CO2 concentration and timber growth to find a positive (negative) error.
Forests play a critical role in mitigating climate change, and, at the same time, are predicted to experience large-scale impacts of climate change that will affect the efficiency of forests in mitigation efforts. Projections of future carbon sequestration potential typically do not account for the changing economic costs of timber and agricultural production and land use change. We integrated a dynamic forward-looking economic optimization model of global land use with results from a dynamic global vegetation model and meta-analysis of climate impacts on crop yields to project future carbon sequestration in forests. We find that the direct impacts of climate change on forests, represented by changes in dieback and forest growth, and indirect effects due to lost crop productivity, together result in a net gain of 17 Gt C in aboveground forest carbon storage from 2000 to 2100. Increases in climate-driven forest growth rates will result in an 81-99% reduction in costs of reaching a range of global forest carbon stock targets in 2100, while the increases in dieback rates are projected to raise the costs by 57-132%. When combined, these two direct impacts are expected to reduce the global costs of climate change mitigation in forests by more than 70%. Inclusion of the third, indirect impact of climate change on forests through reduction in crop yields, and the resulting expansion of cropland, raises the costs by 11-38% and widens the uncertainty range. While we cannot rule out the possibility of climate change increasing mitigation costs, the central outcomes of the simultaneous impacts of climate change on forests and agriculture are 64-86% reductions in the mitigation costs. Overall, the results suggest that concerns about climate driven dieback in forests should not inhibit the ambitions of policy makers in expanding forest-based climate solutions.
 
Natural gas production occurs in specific regions of the U.S., after which it is processed and transported via an interconnected network of high-pressure interstate pipelines. While the presence of hazardous air pollutants (HAPs) in unprocessed, upstream natural gas has been documented, little has been published on their presence in the midstream natural gas supply. We systematically evaluated publicly available, industry-disclosed HAP composition data sourced from Federal Energy Regulatory Commission (FERC) natural gas infrastructure applications submitted between 2017-2020. Natural gas composition data from these filings represent approximately 45% of the U.S. onshore natural gas transmission system by pipeline mileage. Overall, 51% of approved expansion projects failed to disclose any natural gas HAP composition data. Of those applications that disclosed composition data, HAP concentrations were typically higher for separator flash gas and condensate tank vapor compared to LNG and transmission-grade natural gas, with mean benzene concentrations of 1106, 7050, 77, and 37 parts per million (ppm) respectively. We externally validated the FERC application data using real-time natural gas HAP data from five operating transmission pipelines, which independently verified the presence of HAPs in natural gas with two notable exceptions: One pipeline did not disclose any HAP data in their FERC applications even though its gas consistently contained HAPs by real-time measurement, and mercury was detectable in 14% of real-time natural gas measurements but was not reported in any FERC applications. Given that natural gas infrastructure releases natural gas during routine operations and off-normal, uncontrolled loss of containment events (e.g., blowouts), these gas composition data can be useful for conducting air quality and health-based evaluations of natural gas infrastructure.
 
Recent research has found anthropogenic forcing to also affect day-to-day variability of temperatures. For many people, the climate is not only becoming hotter but also more volatile. Based on the new climate-economy literature, I explore the historical impact of day-to-day temperature variation on mortality in the United States over a 35-year period. I find that an extra +1C of daily temperature variability caused an additional 0.206 deaths per 100,000, equal to a 0.28% increase in the average monthly mortality rate. There is, however, evidence of adaptation to daily temperature variability as income and access to air-conditioning have increased and as people have become accustomed to large seasonal variation in temperatures. Given the deadly effect of day-to-day temperature variation, falling average daily temperature variability in the US since 1970 could have resulted in as many as 1,400 and 1,600 premature deaths avoided every winter and summer, respectively. In comparison, the increase in the number of days with a mean temperature above 35C could have caused an additional 655 premature deaths every year. These back-of-the-envelope calculations show that current estimates of the social cost of carbon are omitting an important channel for the mortality impact of climate change by not considering this additional effect of temperature volatility.
 
Ecosystem restoration has the potential to improve the ecological environment, increase ecosystem service delivery capability, and promote biodiversity conservation. Although Habitat quality (HQ) is being widely used as a metric for large-scale biodiversity conservation, it is poorly understood and measured in areas with significant vegetation restoration. This study proposes a modified approach based on the InVEST-HQ module by coupling Normalized Difference Vegetation Index (NDVI) to measure the HQ in the Yellow River Basin (YRB) with extensive vegetation restoration in recent decades. The results show that the vegetation restoration area with significant increases in both Leaf Area Index (LAI) and Net Primary Production (NPP) accounts for 29.7% of the total area of the YRB. The original and modified modules were compared. Based on the InVEST-HQ module, the results show that HQ has a tendency for very small changes in the years 2000, 2010, and 2020, with first a small increase and then a small decrease; however, habitat quality based on the modified method has a significantly increasing trend, which is consistent with the ecological restoration status of the study area and the trend of key ecosystem parameters. The modified method effectively expresses habitat quality changes with vegetation restoration, making it more appropriate for usage in areas where nature conservation and ecosystem restoration are important management actions, allowing for realistic decision-making and data support for regional biodiversity conservation and habitat management.
 
Introduction: An individual’s relation to time may be an important driver of pro-environmental behaviour. Objective: We studied whether young individual's gender and time-orientation are associated with pro-environmental behaviour. Methods: In a controlled laboratory environment with students in Germany, participants earned money by performing a real-effort task and were then offered the opportunity to invest their money into an environmental project that supports climate protection. Afterwards, we controlled for their time orientation. Results: In this consequential behavioural setting, we find that males who scored higher on future-negative orientation showed significantly more pro-environmental behaviour compared to females who scored higher on future-negative orientation and males who scored lower on future-negative orientation. Interestingly, our results are completely reversed when it comes to past-positive orientation. Conclusion: These findings have practical implications regarding the most appropriate way to address individuals in order to achieve more pro-environmental behaviour.
 
Glacier health across High Mountain Asia (HMA) is highly heterogeneous and strongly governed by regional climate, which is variably influenced by monsoon dynamics and the westerlies. We explore four decades of glacier energy and mass balance at three climatically distinct sites across HMA by utilising a detailed land surface model driven by bias-corrected Weather Research and Forecasting (WRF) meteorological forcing. All three glaciers have experienced long-term mass losses (ranging from -0.04$\pm$0.09 to -0.59$\pm$0.20 m w. e. a$^{-1}$) consistent with widespread warming across the region. However, complex and contrasting responses of glacier energy and mass balance to the patterns of the Indian Summer Monsoon were evident, largely driven by the role snowfall timing, amount and phase. A later monsoon onset generates less total snowfall to the glacier in the southeastern Tibetan Plateau during May-June, augmenting net shortwave radiation and affecting annual mass balance (-0.5 m w.e. on average compared to early onset years). Conversely, timing of the monsoon's arrival has limited impact for the Nepalese Himalaya which is more strongly governed by the temperature and snowfall amount during the core monsoon season. In the arid central Tibetan Plateau, a later monsoon arrival results in a 40 mm (58\%) increase of May-June snowfall on average compared to early onset years, likely driven by the greater interaction of westerly storm events. Meanwhile,a late monsoon cessation at this site sees an average 200 mm (192\%) increase in late summer precipitation due to monsoonal storms. A trend toward weaker intensity monsoon conditions in recent decades, combined with long-term warming patterns, has produced predominantly negative glacier mass balances for all sites (up to 1 m w.e. more mass loss in the Nepalese Himalaya compared to strong monsoon intensity years) but sub-regional variability in monsoon timing can additionally complicate this response.
 
Schematic diagram of the applied modelling framework.
(a) Geographical location of the study region in India subdivided into Region 1, Region 2, Region 3 and Region 4. (b) CGWB well locations within the study domain. (c) Mean fraction of GW to total water used for irrigation averaged over the years 1998–2014. Mean seasonal irrigation water uses for Kharif (d) and Rabi season (e) in mm averaged over the years 1998–2014.
Validation of simulated depth to GW (m bgl) against in-situ well observations. Time series of depth to GW spatially averaged over Region 1 (a), Region 2 (b) and Region 3 (c) from 1998 to 2014. Here, depth to GW for January, May, August and November are selected for each year from 1998 to 2014 based on well observation data availability. Annual trend in GW depth from 1998 to 2014 for (d) observed (e) VIC_AMBHAS simulated and (f) VIC_AMBHAS_IRR simulated.
GW response to the change in irrigation technique and interval. Time series of depth to GW spatially averaged over Region 1 (a), Region 2 (b) and Region 3 (c) for VIC_AMBHAS_IRR, VIC_AMBHAS_DRIP and VIC_AMBHAS_INTER experiments for a period 1998–2014. (d) Mean fraction of paddy croplands in Kharif season averaged for years 1998–2014. (e) Climatology of recharge spatially averaged over paddy croplands in Kharif season calculated for years 1998–2014. (f) Mean fraction of other croplands in Kharif season averaged for years 1998–2014. (g) Climatology of recharge spatially averaged over other croplands in Kharif season calculated for 1998–2014.
Indian river basins are intensively managed with country-specific agricultural practices of cultivating submerged paddy and uncontrolled groundwater irrigation. Numerical experiments with the state-of-the-art land surface models, such as Variable Infiltration Capacity (VIC), without incorporating region-specific practices, could be misleading. Here, we coupled VIC with 2D groundwater model AMBHAS, incorporating India-specific irrigation practices and crop practices, including submerged paddy fields. We performed numerical experiments to understand the causal factors of groundwater depletion in the Northwest Indo-Gangetic plain. We identify widespread flood irrigation and cultivation of water-intensive paddy as critical drivers of the declining groundwater scenario. Our numerical experiments suggest that the introduction of drip irrigation reduces groundwater depletion in the Northwest, but does not change the sign of groundwater level trends. The groundwater levels in the non-paddy fields of the middle IGP are less sensitive to irrigation practices due to the high return flow to groundwater for flood irrigation.
 
Relative mobility and pollution effects.
Latin America, as other regions in the world, imposed mobility restrictions to tackle the COVID-19 pandemic. Although recent research has analyzed the effect of mobility restrictions on air quality in several regions, a scarce literature explores the causal effects of the lockdowns in Latin America at a city scale whose results may guide local policymaking. This article, based on a quasi-experimental approach, estimates the causal short-term impacts of lockdowns on air quality considering the influence of forest fires on pollution in four megacities in Latin America (Bogotá, Mexico City, Santiago, and Sao Paulo). Results show that nitrogen oxides and carbon monoxide consistently declined (from 16% to 68%), nevertheless, fine particles rarely decreased across cities. Only Bogotá exhibited an overall reduction in fine particles (45% for PM2.5). Mexico City obtained the lowest reduction in pollutants, whereas Bogotá outperformed other cities in several pollutants. Evidence from mobility statistics supports the decrease in air pollution by a reduction in driving, transit use, and other mobility indicators.
 
Map of India showing (a) children’s district-level mean ambient PM2.5 exposure in-utero (μg m⁻³) and households using polluting cooking fuel (%) in 2015, and (b) district-level prevalence of stunting among children under-5 in 2015. All values are weighted using sampling weights of NFHS-4.
Cumulative preventable number of stunted children (in million) from changes in household air pollution (orange), ambient air pollution (green) and household and ambient air pollution combined (dashed black line) according to mitigation scenario and year relative to NPi scenario.
Projected trends in stunting prevalence (children under-5) by population sub-group under NPi and 2 °C MFR with access policy scenarios.
Percent difference in projected prevalence of child stunting in 2050 between the 2 °C MFR with access policy and NPi scenarios according to administrative district.
Baseline and projected exposure variables according to scenario and year
Many children in India face the double burden of high exposure to ambient (AAP) and household air pollution (HAP), both of which can affect their linear growth. Although climate change mitigation is expected to decrease AAP, climate policies could increase the cost of clean cooking fuels. Here, we develop a static microsimulation model to project the air pollution-related burden of child stunting in India up to 2050 under four scenarios combining climate change mitigation (2°C target) with national policies for AAP control and subsidised access to clean cooking. We link data from a nationally representative household survey, satellite-based estimates of fine particulate matter (PM2.5), multi-dimensional demographic projection and PM2.5 and clean cooking access projections from an integrated assessment model. We find that the positive effects on child linear growth from reductions in AAP under the 2°C Paris Agreement target could be fully offset by the negative effects of climate change mitigation through reduced clean cooking access. Targeted AAP control or subsidised access to clean cooking could shift this trade-off to result in net benefits of 2.8 (95% uncertainty interval [UI]: 1.4, 4.2) or 6.5 (UI: 6.3, 6.9) million cumulative prevented cases of child stunting between 2020-50 compared to business-as-usual. Implementation of integrated climate, air quality, and energy access interventions has a synergistic impact, reducing cumulative number of stunted children by 12.1 (UI: 10.7, 13.7) million compared to business-as-usual, with the largest health benefits experienced by the most disadvantaged children and geographic regions. Findings underscore the importance of complementing climate change mitigation efforts with targeted air quality and energy access policies to concurrently deliver on carbon mitigation, health and air pollution and energy poverty reduction goals in India.
 
Climate model simulations provide useful information to assess changes in climate extremes (e.g., droughts and hot extremes) under global warming for climate policies and mitigation measures. Due to systematic biases in climate model simulations, bias correction methods have been employed to improve simulations of climate variables such as precipitation and temperature. Previous studies mostly focus on individual variables while the correction of precipitation-temperature dependence, which is closely related to compound dry and hot events (CDHEs) that may lead to amplified impacts, is still limited. In this study, we evaluated the performance of the multivariate bias correction (MBC) approach (i.e., MBCn and MBCr) for adjusting precipitation-temperature (P-T) dependence and associated likelihoods of CDHEs in China based on 20 Coupled Model Intercomparison Project Phase 6 (CMIP6) models with observations from CN05.1. Data for the period 1961-1987 were used for model calibrations and those for 1988-2014 were used for model validations. Overall, the MBC can improve the simulation of P-T dependence and associated CDHEs with large regional variations. For P-T dependence, the median values of RMSE for corrected simulations show a decreased bias of 5.0% and 4.3% for MBCn and MBCr, respectively, compared with those of raw CMIP6 models. For the likelihood of CDHEs, a decrease of 1.0% and 7.2% in RMSE is shown based on the MBCn and MBCr, respectively. At the regional scale, the performance of the MBC varies substantially, with the reduced RMSE up to 34.8% and 18.7% for P-T dependence and likelihood of CDHEs, respectively, depending on regions and MBC methods. This study can provide useful insights for improving model simulations of compound weather and climate extremes for impact studies and mitigation measures.
 
Climate change is intensifying fire regimes across boreal regions, and thus both burned area and carbon emissions from combustion are expected to increase significantly over the next several decades. Fire management through initial suppression of fires is effective at reducing burned area, but limited work has addressed the role that fire management can play in reducing wildfire carbon emissions and their impacts on climate change. In this work, we draw on historical data covering fire and fire management in Alaska to project burned area and management outcomes to 2100. We allow management to both respond to and impact variations in annual burned area and carbon emissions, while keeping decadal-average burned area at or above historical levels. The total cost of a fire is calculated as the combination of management expenditures and the social cost of carbon emissions during combustion, using the Social Cost of Carbon framework. Incorporating the tradeoff between management expenditures and burned area, we project that by 2100, increasing management effort by 5-10 times relative to current expenditures would minimize combined management and emissions costs. This is driven by the finding that the social costs of carbon emissions greatly exceed management costs unless burned area is constrained to near the average historical level. Our analysis does not include the many health, economic, and non-CO2 climate impacts from fires, so we likely underestimate the benefits of increased fire suppression and thus the optimal management level. As fire regimes continue to intensify, our work suggests increased management expenditures will be necessary to counteract increasing carbon combustion and lower overall climate impact.
 
Ammonia (NH 3 ) is a key precursor of haze particles and fine particulate matter (PM 2.5 ) and its spatiotemporal variabilities are poorly constrained. In this study, we present measurements of NH 3 over the Indian subcontinent region from the IASI and CrIS satellite instruments. This region exhibits a complex emission profile due to the number of varied sources, including crop burning, fossil fuel combustion, fertilizer application, livestock and industrial sources. Observations from the CrIS and IASI instruments are oversampled to a resolution of 0.02° x 0.02°. Five regions with distinct spatiotemporal NH 3 profiles are determined using k-means clustering. Maximum NH 3 columns are seen in July over the western India with column densities of 6.2 x10 ¹⁷ mol. cm ⁻² and 7.2 x10 ¹⁷ mol. cm ⁻² respectively for IASI and CrIS. The seasonality of measured NH 3 columns show annual maxima occurring in spring in Eastern India and Bangladesh and in mid-summer for the western Indo-Gangetic plain. Our observational constraints suggest that the impact of local farming practices on NH 3 emissions is not well captured in emission inventories such as CMIP6, which exhibits peaks in the late spring and autumn. The spatial variability in the seasonal patterns of NH 3 is also not captured by the single emissions profile used in CMIP6 for India. The high-resolution maps obtained from these measurements can be used to improve NH 3 emission inventories in order to understand its sources for more accurate predictions of air quality in the Indian subcontinent.
 
Marine oil spill produces the oil-related hazardous material (OHM), which has seriously affected the coastal economic development such as tourism and aquaculture, causing damage to the marine ecological environment. The turbulent momentum and energy generated by wave breaking process have a significant effect on accelerating the mixing of OHM and seawater, which is one of the main factors for the formation of sunken and submerged oil. In order to explore the influence of offshore wave breaking on the formation and transportation of OHM, the wave breaking process was simulated in a two-dimensional laboratory flume, and the behavior process of OHM was identified and tracked in this paper. Five groups of breaking waves with different significant wave height (SWH) were set up in the experiment, and then oil hazardous material with the same density and mass were added respectively to observe the sinking process under the action of wave-induced turbulence. The results show that the turbulence intensity is closely related to the phase of wave, and the turbulence activity is violent at the wave crest, and the vertical distribution of turbulent energy dissipation rate in turbulent mixing zone remains basically unchanged. Under the actions of wave breaking and turbulence, the OHM’s submergence depth shows a good binomial growth trend. For SWH=12.45cm, the OHM stays under the water for nearly 2.32s, and it reaches the deepest position of 0.165m. Compared with SWH=12.45cm, the submergence depths for waves with significant wave heights of 20.61cm, 26.81cm, 32.32cm, and 36.54cm are increased by 8%, 37%, 80%, and 159%, respectively. Then, the other four waves’ submergence depths are increased progressively, and the growth rates are 8%, 26%, 31%, 44%, respectively (compared with the same period of the previous wave)
 
Weather constitutes a major source of risks facing households in rural areas, which are being amplified under climate change. In this context, two main rural financial services, weather index insurance and microcredit, have been increasingly adopted by farmers worldwide. However, the understanding of the socioeconomic and ecological impacts of these rural finance schemes, including potential maladaptive outcomes, remains ambiguous. We review the recent literature on weather index insurance and microcredit for farmers and find that both rural financial services have positive economic impacts, though benefits to the poorest populations remain controversial. Moreover, their impacts on the ecological systems are less studied and are found to be mainly negative. In addition, considering that both financial instruments have strengths and limitations, we argue that combination schemes (e.g., a hybrid product) may generate positive synergistic effects on building socioeconomic resilience to climate risks in agricultural regions. However, this may also add new economic risk to local financial institutions. This comprehensive review provides a reference for the potential benefits and risks of agricultural finance innovations. Further studies on the ecological impacts of rural financial services and the synergistic effects of the combination on socioeconomic and ecosystem resilience in rural contexts are needed to fill the current research gap.
 
Since the 1980s, external forcing from increasing greenhouse gases and declining aerosols has had a large e ect on European summer temperatures. The forcing may therefore provide an important source of forecast skill, even for timescales as short as a season ahead. However, the relative importance of such forcing for seasonal forecasts has thus far not been quanti ed, particularly on a regional scale. In this study, we investigate forcing-induced skill by comparing the temperature skill of a multi-model ensemble of operational seasonal predictions from the Copernicus Climate Change Service (C3S) archive to that of an uninitialised ensemble of CMIP6 projections for European summers spanning the years 1993-2016. We show that in some regions, such as northern Europe, summer 2m temperature skill is relatively limited and the forced trend provides the primary source of skill in current seasonal forecast models at 2-4 month lead-times. Over large parts of northern Europe, summer temperature skill is actually higher in uninitialised predictions and in runs with long lead-times than at short lead-times suggesting that there may be problems with the initialisation. Conversely, 2m temperature in southern Europe is generally well predicted by seasonal forecast models out to 3-5 months due to a combination of dynamical skill and a strong forced trend. These results indicate that even uninitialised predictions can provide useful information for seasonal forecasts of European summer temperatures and secondly that the ability of models to capture dynamical signals for northern European summers requires further research.
 
Food systems are major drivers of environmental and health impacts. While the emissions and other pressures causing these impacts mainly occur in primary agricultural production, the deeper causes and much of the mitigation potential are distributed throughout food systems, including dietary choices and multiple inefficiencies in the whole chain from agricultural production to consumption and waste management. An environmental indicator based on this systems perspective is the nitrogen (N) footprint, defined as the emissions of reactive N due to the consumption of an individual or other entity. Here, we present a method to estimate the N footprint of Swedish food consumption, using a detailed inventory of agricultural production, food and feed processing, food waste, waste management, and wastewater treatment. Limitations of data sources and methods are discussed in detail. The estimated Swedish food N footprint is 12.1 kg N capita ⁻¹ year ⁻¹ , of which 42% is emitted in Swedish production, 38% in production abroad, 1% in consumer waste management, and 19% in wastewater treatment. Animal food products account for 81% of the food N footprint and 70% of the protein intake. Average protein intake exceeds nutritional requirements by about 60%, which suggests that at least 35% reduction of food-related reactive N emissions could be achieved through dietary change. Of the apparent food N consumption (6.9 kg N capita ⁻¹ year ⁻¹ ), about 22% is food waste N (1.5 kg N capita ⁻¹ year ⁻¹ ). We estimate that 76% of food waste N is unavoidable (bones and other parts not commonly eaten). Avoidable food waste is about 7% of the edible food supply, implying that a hypothetical complete elimination of food waste would reduce emissions by about 7%. In summary, we present a detailed method, discuss its limitations, and demonstrate possible uses of the N footprint as a complement to existing territorial and sectoral environmental indicators.
 
Potatoes are a mainstay of human diets and 4 million metric tons are produced annually in the United States. Simulations of future crop production show that climate change is likely to reduce the yields of the major grain crops around the world, but the impacts on potato production have yet to be determined. A model ensemble consisting of five process-based and one statistical model was used to estimate the impact of climate change on fully irrigated, well-fertilized potato crop across the USA under the RCP8.5 scenario of high emissions. Results indicate that increasing temperature will reduce potato yields, but this will be mostly compensated by elevated atmospheric CO2. Yields are projected to decline with climate change in the current highest-yielding areas, which would experience the highest rises in growing season temperature during short hot summers. Simulated yields increase slightly elsewhere in the southern regions of the USA. Planting potatoes earlier as adaptation to avoid hot summers would improve yields in most regions. Water use by the potato crop is projected to decline despite higher temperatures, due to a shorter growing season and increased water use efficiency under elevated atmospheric CO2. With higher yields in many regions, crop uptake for NPK fertilizer will increase, despite the reduced concentration of nutrients in potatoes due to a growth stimulus from elevated atmospheric CO2. With earlier planting, by 2050 water use will decline by 11.7%, NPK fertilizer uptake will increase by 10.4%, and yields of slightly less nutritious potatoes will increase by 14.9% nationally.
 
Irrigation has enhanced food security and biofuel production throughout the world. However, the sustainability of irrigation faces challenges from climate variability and extremes, increasing consumption from irrigated cropland expansion, and competing demands from other water use sectors. In this study, we investigated the agricultural water withdrawal landscape of the contiguous US (CONUS) over 1981-2015, assessed its spatial and temporal changes and analyzed the factors driving the changes. We introduced the concept of “center of mass” to calculate the spatiotemporal trajectory of water withdrawal, along with climatic and agricultural factors at state, regional and CONUS scales. At the CONUS level, the total agricultural water withdrawal has decreased during 1981-2015, and the centroid of water withdrawal consistently moved toward the east, caused by reduced water withdrawal in the western states and increased withdrawal in the eastern states. While the CONUS irrigation trajectory was resilient to climate variability, prolonged regional drought may interrupt the trend. In the Western US, irrigation withdrawal reduction was mainly achieved by adoption of high-efficiency irrigation technology. Under drought conditions, irrigation withdrawal often switched from surface water to groundwater sources, posing challenges on groundwater sustainability under prolonged drought conditions. The Eastern US has experienced accelerating agricultural withdrawal from both surface water and groundwater sources. This was mainly driven by increased irrigated acreage in the Midwest and lower Mississippi River, with irrigated croplands supplied by mixed flood irrigation and high-efficiency irrigation methods. At the state level, some states exhibited discrepancy in agricultural withdrawal centroids from surface water and groundwater sources, as results of climate heterogeneity, water availability and infrastructure development. This study provides understanding of the driving forces in the spatiotemporal trends of CONUS agricultural water withdrawal in different regions and implications for predicting future agricultural withdrawal under changing climatic and socioeconomic uncertainties.
 
Increased variability of the water cycle manifested by climate change is a growing global threat to agriculture with strong implications for food and livelihood security. Thus, there is an urgent need for adaptation in agriculture. Agricultural water management (AWM) interventions, interventions for managing water supply and demand, are extensively promoted and implemented as adaptation measures in multiple development programs globally. Studies assessing these adaptation measures overwhelmingly focus on positive impacts, however, there is a concern that these studies may be biased towards well-managed and successful projects and often miss out on reporting negative externalities. These externalities result from coevolutionary dynamics of human-water systems as AWM interventions impact hydrological flows and their use and adoption is shaped by the societal response. We review the documented externalities of AWM interventions and present a conceptual framework classifying negative externalities linked to water and human systems into negative hydrological externalities and unexpected societal feedbacks. We show that these externalities can lead to long term unsustainable and inequitable outcomes. Understanding how the externalities lead to undesirable outcomes demands rigorous modeling of the feedbacks between human and water systems, for which we discuss the key criteria that such models should meet. Based on these criteria, we showcase that differentiated and limited inclusion of key feedbacks in current water modeling approaches (e.g., hydrological models, hydro-economic, and water resource models) is a critical limitation and bottleneck to understanding and predicting negative externalities of AWM interventions. To account for the key feedback, we find Agent Based Modeling (ABM) as the method that has the potential to meet the key criteria. Yet there are gaps that need to be addressed in the context of ABM as a tool to unravel the negative externalities of AWM interventions. We carry out a systemic review of ABM application to agricultural systems, capturing how it is currently being applied and identifying the knowledge gaps that need to be bridged to unravel the negative externalities of AWM interventions. We find that ABM has been extensively used to model agricultural systems and, in many cases, the resulting externalities with unsustainable and inequitable outcomes. However, gaps remain in terms of limited use of integrated surface-groundwater hydrological models, inadequate representation of farmers' behavior with heavy reliance on rational choice or simple heuristics and ignoring heterogeneity of farmers' characteristics within a population.
 
Background Prior mortality estimates of air pollution from coal-fired power plants in India use PM2.5 exposure-response functions from settings that may not be representative, and do not include other potentially harmful effects of these plants, such as fly ash pollution and heavy freshwater consumption. Methods We use a national, district level dataset to assess the impact of coal-fired power plants on all-cause mortality (15-69 years) in 2014. We compare districts with coal-fired power plants (total capacity >1000 MW) to districts without a coal-fired power plant, estimating the effect of these power plants on all-cause mortality within districts that have these plants. Results Out of 597 districts in India in 2014, 60 districts had a coal-fired power plant. When compared to districts without a coal-fired power plant, districts with a coal-fired power plant (>1000 MW) had higher rates of age-standardized mortality in both women (0.38, 95% CI: -0.14 - 0.90) and men (0.55, -0.17 - 1.27). Similarly, these districts had higher rates of conditional probability of premature death in both women (2.22, -0.13 - 4.56) and men (2.12, -0.54 - 4.77). The point estimates for total excess deaths were 19,320 for women and 27,727 for men. In affected districts, the proportion of premature adult deaths attributable to coal-fired power plants was 5.8% (-0.3% – 11.9%) in women and 4.3% (-1.1% – 9.6%) in men. Conclusions We estimate that ~47,000 premature adult deaths can be attributed to large coal-fired power plants in India in 2014. These deaths are concentrated in the ~10% of districts that have the nation’s power plants, where they are associated with 1 out of 20 premature adult deaths. Effective regulation of emissions from these plants, coupled with a phaseout of coal-fired power plants, can help decrease this burden of inequitable and premature adult mortality.
 
Climate change is already having adverse impacts, with place- and problem-based implications for communities and activities through higher temperatures, prolonged droughts, and more frequent extremes. Despite uncertainty about the full extent of future change however, adaptation will be required. Adaptation pathways planning is increasingly used as a methodological approach to identify, evaluate, and sequence climate change adaptation options over time. A pathways approach links critical decisions to future conditions, providing a road map to support planning in the face of uncertainty. Using systematic review methods, this paper identifies, reviews, synthesises and assesses the rapidly growing adaptation pathways literature. Focusing on its application in diverse settings, conceptual and methodological differences, and best practice, we consider theoretical and practical advances to realise the full potential of pathways practice. Bibliometric and thematic analysis are used to highlight scholarly networks driving innovation in this area, characterise theoretical and conceptual differences in framing, and derive insights for best practice. Results show that from an initial focus on technological and engineered based approaches, and championed by a small number of authors, pathways planning has become increasingly diverse, participatory, and collaborative, and is used to address climate adaptation outcomes, within the broader context of interacting and compounding stressors. These results can help inform future research design, develop methodologies to better engage with stakeholders’ social, political, and economic concerns, and enhance learning for climate adapted futures.
 
Cities have historically developed close to rivers and coasts, increasing human exposure to flooding. That exposure is exacerbated by changes in climate and population, and by urban encroachment on floodplains. Although the mechanisms of how urbanization affects flooding are relatively well understood, there have been limited efforts to assess the magnitude of floodplain encroachment globally and how it has changed in both space and time. Highly resolved global datasets of both flood hazard and changes in urban area from 1985-2015 are now available, enabling the reconstruction of the history of floodplain encroachment at high spatial resolutions. Here we show that the urbanized area in floodplains that have an average probability of flooding of 1/100 years, has almost doubled since 1985. Further, the rate of urban expansion into these floodplains increased by a factor of 1.5 after the year 2000. We also find that urbanization rates were highest in the most hazardous areas of floodplains, with population growth in these urban floodplains suggesting an accompanying increase in population density. These results reveal the scope, trajectory and extent of global floodplain encroachment. With tangible implications for flood risk management, these data could be directly used with integrated models to assess adaptation pathways for urban flooding.
 
Permafrost thaw will release additional carbon dioxide into the atmosphere resulting in a positive feedback to climate change. However, the mineralization dynamics of organic matter (OM) stored in permafrost-affected soils remain unclear. We used physical soil fractionation, radiocarbon measurements, incubation experiments, and a dynamic decomposition model to identify distinct vertical pattern in OM decomposability. The observed differences reflect the type of OM input to the subsoil, either by cryoturbation or otherwise, e.g. by advective water-borne transport of dissolved OM. In non-cryoturbated subsoil horizons, most OM is stabilized at mineral surfaces or by occlusion in aggregates. In contrast, pockets of OM-rich cryoturbated soil contain sufficient free particulate OM for microbial decomposition. After thaw, OM turnover is as fast as in the upper active layer. Since cryoturbated soils store ca. 450 Pg carbon, identifying differences in decomposability according to such translocation processes has large implications for the future global carbon cycle and climate, and directs further process model development.
 
(a) Squared covariance (contours) of the leading maximum covariance analysis (MCA) mode between tropical Atlantic SST (20.5° N–20.5° S, 84.5° W–16.5° E) and Antarctic SIC (60.5° S–89.5° S, 179.5° W–179.5° E). Ordinate is the SIC calendar month and abscissa is the time lag in month, with negative for SST leading SIC. Shaded areas exceed 80% (dark blue), 85% (celeste) and 95% (yellow) confidence level based on the Monte Carlo test. (b) Heterogeneous map for SIC (shading, %) in May and (c) homogeneous map for SST (shading, °C) in March corresponding to the leading MCA mode at lag −2 month. (d) Corresponding normalized time coefficients of SST and SIC, and normalized NEA-minus-SEA time coefficients. Areas of > 95% confidence level are marked by black dots in (b) and (c).
Regressions of (a) convective precipitation (shading, mm) and 950 hPa wind (vectors, m s⁻¹), (b) vertical velocity (shading, Pa s⁻¹) and zonal wind (contours, interval 0.5 m s⁻¹) averaged over 2° N–2° S, (c) 200 hPa divergence (shading, s⁻¹) and divergent wind (vectors, m s⁻¹) in May onto the normalized SST time coefficients at lag −2 months. The blue and red box represent the Pacific and Atlantic sectors, respectively. In (a) and (c), green dashed lines represent the position of the equator. In (b), red (blue) shading represents downwelling (upwelling) flow, and solid (dashed) contours denote positive/eastward (negative/westward) winds. Areas of >95% confidence level are marked by white slashes in (b) or black dots in (a) and (c).
Regressions of (a) 200 hPa geopotential height (contours, interval 4 geopotential meter) and RWS (shading, s⁻²) (b) 500 hPa geopotential height (contours, interval 4 geopotential meter) and TN flux (vectors, m² s⁻²) in May onto the normalized SST time coefficients at lag −2 months. (c) Climatological mean of 200 hPa Rossby wavenumber K (shading, m⁻¹) and zonal wind (contours, interval 3 m s⁻¹) in May. In (a), the pink and green lines indicate the propagation of the wave trains, and areas of >95% confidence level are marked by black dots.
Regressions of (a) SLP (red and blue contours indicate positive and negative anomalies, respectively, 40 Pa interval) and 10 m wind (vectors, m s⁻¹), (b) SAT (shading, °C) in May onto the normalized SIC time coefficients at lag −2 months. (c) Correlations between SAT observations from 40 stations and normalized SIC time coefficients at lag −2 months (circles, with red/blue color showing positive/negative correlation, and size corresponding to confidence level). Areas of >95% confidence level are marked by black dots in (b).
Antarctic sea ice plays an important role in polar ecosystems and global climate, while its variability is affected by many factors. Teleconnections between the tropical and high latitudes have profound impacts on Antarctic climate changes through the stationary Rossby wave mechanism. Recent studies have connected long-term Antarctic sea ice changes to multidecadal variabilities of the tropical ocean, including the Atlantic Multidecadal Oscillation and the Interdecadal Pacific Oscillation. On interannual timescales, whether an impact exists from teleconnection of the tropical Atlantic is not clear. Here we find an impact of sea surface temperature (SST) variability of the tropical Atlantic meridional dipole mode on Antarctic sea ice that is most prominent in austral autumn. The meridional dipole SST anomalies in the tropical Atlantic force deep convection anomalies locally and over the tropical Pacific, generating stationary Rossby wave trains propagating eastward and poleward, which induce atmospheric circulation anomalies affecting sea ice. Specifically, convective anomalies over the equatorial Atlantic and Pacific are opposite-signed, accompanied by anomalous wave sources over the subtropical Southern Hemisphere. The planetary-scale atmospheric response has significant impacts on sea ice concentration anomalies in the Ross Sea, near the Antarctic Peninsula, and east of the Weddell Sea.
 
Sustainable management of grasslands has always been an urgent issue for policy-makers. The Three Rivers Source Region (TRSR) contains widely distributed natural grasslands and is sensitive to climate warming. To enable the sustainable development of the human-nature system in the TRSR, we propose a novel indicator based on the allocation of aboveground net primary production (ANPP). The indicator we proposed is the ANPP that can be used for human activities (UANPP). In the study, we simulated the spatial and temporal patterns of the UANPP in the alpine grasslands in the TRSR during 1979–2016 and explored the main driving factors of the UANPP. The results revealed that (1) the annual total UANPP in the TRSR was 13.22 TgC, approximately accounting for 47% of total ANPP. (2) The areas with negative UANPP values accounted for 17% of the entire TRSR, and they were primarily located within the Nature Reserve of the Yangtze and Yellow river source regions, while three-quarters of the area exhibited improvement trends. (3) The regional mean UANPP significantly increased during 1979–2016, at a rate of 0.28 gC m−2 year−1 (p < 0.01). In the entire TRSR, 87% of the area exhibited increasing trends. (4) The UANPP in most areas of the TRSR was strongly correlated with precipitation, and the effect of human activities on the UANNP increased slightly during the 38-year study period. The UANPP represents the upper limit of human use of nature. These findings provide a reference for policy-makers to make decisions toward human-nature system sustainability while meeting human needs for grassland resources. ANPP allocation between nature and human system is a potentially important tool from the standpoint of sustainable development.
 
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£1,850 / $2,545 / €2,195
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47%
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50 days
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6.947 (2021)
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1.445 (2021)
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2.111 (2021)
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Top-cited authors
Scott J Goetz
  • Northern Arizona University
Holly Gibbs
  • University of Wisconsin–Madison
Felix Creutzig
  • Technische Universität Berlin
Navin Ramankutty
  • University of British Columbia - Vancouver
Joeri Rogelj
  • International Institute for Applied Systems Analysis