The global water cycle has experienced significant changes over the last century due to anthropogenic activities coupled with climate change. Attributing and quantifying the respective contribution of these factors that drives the alteration in hydrological components is essential for better planning and management of water resources. Therefore, a significant number of studies spanning from pre- to post-industrial eras have tried to attribute observed hydrological changes to climate and humans. These studies employ various techniques ranging from process-based to semi-empirical to statistical to machine learning. This paper provides a comprehensive review of conventional and emerging attribution methods for major hydrological components, including streamflow, evapotranspiration, water levels, and groundwater storage. While each method offers unique strengths suited to a particular application, they also exhibit certain limitations creating space for potential improvement, which are further discussed in this review. Furthermore, numerous attribution studies around the globe are surveyed to highlight well-studied and overlooked basins along with their results. We found that approximately 70% of the studied basins exhibit stronger influence from human activities than from climatic factors. Finally, we propose a decision framework to guide the selection of attribution method under specific constraints. This review offers a structured guide to selecting appropriate techniques, foster advancements in methodologies, and expansion of attribution research to under-studied regions.
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- The following article is Open accessAttribution of climate change and anthropogenic activities on regional to global scale water cycle: a comprehensive review
Balaram Shaw et al 2026 Environ. Res. Commun. 8 082001
- The following article is Open accessAre rock glaciers useful climate indicators?
R Kenner 2026 Environ. Res. Commun. 8 082002
View article, Are rock glaciers useful climate indicators?PDF, Are rock glaciers useful climate indicators?Rock glaciers are ice-bearing, creeping landforms of the cryosphere, and their spatial occurrence and deformation velocity are sensitive to climate. Permafrost research has made several attempts to use this climate sensitivity to establish rock glaciers as climate indicators. A recent initiative succeeded to make rock glacier velocity (RGV) a quantity of the essential climate variable (ECV) permafrost. To justify this step, the initiators formulated the role of rock glaciers for the ECV permafrost with caution. In scientific practice, however, reference was made to the initiative in order to interpret the relevance of RGV more broadly and attribute a direct role of a climate indicator to it. This ambivalence should be converted into a consensus, recognizing the need for long-term rock glacier monitoring, but at the same time agreeing on the limits of a reasonable interpretation of RGV. Rock glacier-based paleoclimatology constitutes a second important approach to use rock glaciers as climate proxies. It is based on the comparison of the spatial distribution of active and relict rock glaciers to derive a climate signal. With slightly varying methodology, this approach has been used in numerous publications and over several decades. Taken together, the results reveal considerable variations, some of which are a consequence of conceptual weaknesses. Considering the current state of knowledge on rock glacier formation and referring to alternative climate reconstructions, the possibilities and limits of rock glacier-based paleoclimatology are evaluated. This review evaluates the general suitability of rock glaciers as climate indicators, particularly in comparison to other climate indicators from the research field of mountain permafrost. At the same time, it emphasises their complex climate sensitivity and the resulting need to monitor and investigate rock glaciers, since they play a significant role in alpine mass wasting and can be a hazard potential for mountain communities.
- The following article is Open accessThe relationship between data centers and the climate is a systems challenge: a spatial analysis of United States data centers
Abbey Kollar and Caitlin Grady 2025 Environ. Res. Commun. 7 111005
View article, The relationship between data centers and the climate is a systems challenge: a spatial analysis of United States data centersPDF, The relationship between data centers and the climate is a systems challenge: a spatial analysis of United States data centersData centers are a rapidly growing infrastructure that support digital and artificial intelligence needs. However, their expansion has raised concerns about impact based on electricity and water usage. Beyond quantifying the impact of the data center on the environment, this study presents an energy-climate operational risk analysis of over 2,400 data centers in the United States, focusing on location-specific water and heat risks and the dependency of emissions on local energy mixes. Findings highlight that current framing around the sustainability and reliability of data center operations could benefit from systems approaches for a more holistic understanding. We find that many data centers are in regions with significant water stress and are exposed to heat waves. These operational risks, along with the emissions variability due to regional grid differences, underscore the need for sustainable and reliable future planning of data centers.
- The following article is Open accessBayesian spatio-temporal modeling of fine particulate matter in data-scarce urban environments: a case study of Bujumbura, Burundi
Egide Ndamuzi et al 2026 Environ. Res. Commun. 8 081001
View article, Bayesian spatio-temporal modeling of fine particulate matter in data-scarce urban environments: a case study of Bujumbura, BurundiPDF, Bayesian spatio-temporal modeling of fine particulate matter in data-scarce urban environments: a case study of Bujumbura, BurundiSub-Saharan Africa, along with other data-scarce urban environments, suffers from a lack of reliable air quality data, limiting evidence-based actions for public health and urban sustainability. Bujumbura, Burundi’s largest and fastest-growing city, lacks systematic air quality monitoring despite rapid urbanization. This study presents a city-scale, high-resolution assessment of fine particulate matter (PM
) in Bujumbura using a hybrid deployment of low-cost sensors that combines fixed and rotating sites across 27 locations representing four land-use categories. Spatial and temporal dependencies were modeled using a Bayesian hierarchical framework based on the stochastic partial differential equation (SPDE) approach implemented with integrated nested Laplace approximation. The results reveal pronounced spatial contrasts, with lower concentrations in administrative, business, and industrial areas (48.3 g m) and higher levels in high-density residential and town background zones (59.5–60.6 g m). Diurnal and daily patterns show persistent morning–evening peaks, exceeding World Health Organization guideline values. Model validation based on out-of-sample cross-validation indicates moderate-to-strong predictive skill, with a root mean square error of 0.35 on the logarithmic scale (g m) and a correlation coefficient of . These findings demonstrate that combining cost-effective sensor networks with Bayesian SPDE-based modeling can yield actionable insights into urban PM exposure in data-limited cities. - The following article is Open accessSatellite based progressive in-season crop mapping for agricultural scheme governance
Murali Krishna Gumma et al 2026 Environ. Res. Commun. 8 081012
View article, Satellite based progressive in-season crop mapping for agricultural scheme governancePDF, Satellite based progressive in-season crop mapping for agricultural scheme governanceAccurate in-season crop information is critical for improving procurement planning and land-use policies in smallholder agricultural regions. Conventional satellite-based crop maps become available only after harvest, limiting their usefulness for real-time decision-making. This study presents a novel progressive in-season crop mapping framework that delivers district-level crop type, sowing windows, and production estimation at three time points (February–April) for 17 districts of Odisha (India) during the 2024–25 Rabi season. Using Google Earth Engine, multi-temporal Sentinel-2 normalised difference vegetation index, unsupervised clustering, and dynamic spectral signature matching, validated with 10 394 ground observations, the method achieved a classification accuracy of 92%. Unlike conventional end-of-season crop mapping approaches, the framework progressively updates crop area, type, and production estimates during the growing season, enabling timely agricultural monitoring and decision-making. The results reveal three distinct rice sowing–harvesting cycles, enabling pixel-level identification of early, normal, and late planting, an advancement over traditional end-season models. District-level analysis shows that 49% of the state’s rice production is harvested in May, indicating a critical period for procurement, storage, and logistical planning. Additionally, extensive rice-fallow and crop-fallow areas were identified, highlighting substantial potential for intensifying cropping systems by incorporating pulses, oilseeds, and climate-resilient crops. The proposed framework offers a scalable approach for real-time agricultural monitoring, enabling government agencies to align minimum support price procurement schedules, optimise warehouse allocation, prioritise irrigation support, and design district-specific crop diversification strategies. This operational, policy-relevant system demonstrates clear potential for integration into state-level digital agriculture missions and climate-resilient food system planning.
- The following article is Open accessPersistent spatial scales of temperature influence on forest productivity across China (1990-2018)
Pedro Cabral et al 2026 Environ. Res. Commun. 8 081002
View article, Persistent spatial scales of temperature influence on forest productivity across China (1990-2018)PDF, Persistent spatial scales of temperature influence on forest productivity across China (1990-2018)Understanding how forest productivity responds to climate variability requires identifying not only dominant climatic drivers but also the spatial scales at which climate-ecosystem interactions are expressed. We examined the geographical structure and temporal stability of temperature controls on forest gross primary productivity in mainland China from 1990 to 2018. Using spatially explicit regression, we quantified local variations in temperature sensitivity and compared spatial patterns nationwide before and after 2000, a period of sustained climatic warming. Results revealed pronounced spatial non-stationarity in temperature-productivity relationships, with strong positive sensitivities concentrated in cold and high-elevation forests and weak or near-zero sensitivities prevailing in warm, humid lowland forests of southern and eastern China, where productivity is less constrained by temperature. Despite higher mean temperatures in the post-2000 period, the geographical organization and characteristic spatial scale of local temperature sensitivity remained remarkably stable. Differences between periods were expressed primarily as changes in coefficient magnitude rather than spatial reorganization, indicating that recent climate change modified response intensity without fundamentally reorganizing the geographic pattern of temperature sensitivity. By explicitly resolving the spatial scale and persistence of temperature-productivity coupling, this study shows that forest productivity responses to climate change remain strongly conditioned by persistent climatic and geographical gradients rather than reorganizing uniformly under warming conditions.
- The following article is Open accessMicrometeorological effects and thermal-environmental benefits of cool pavements: findings from a detailed observational field study in Pacoima, California
Haider Taha 2024 Environ. Res. Commun. 6 035016
View article, Micrometeorological effects and thermal-environmental benefits of cool pavements: findings from a detailed observational field study in Pacoima, CaliforniaPDF, Micrometeorological effects and thermal-environmental benefits of cool pavements: findings from a detailed observational field study in Pacoima, CaliforniaCool pavements represent one of several strategies that can mitigate the effects of urban overheating by increasing albedo. By definition, this means increasing reflected and potentially re-absorbed short-wave radiation but also decreased surface and air temperatures and longwave upwelling, thus reducing radiant temperatures. So far, real-world studies have been inconclusive as to net effects from cool pavements. A project by GAF installed reflective pavements in Pacoima, California, in summer of 2022. This study set out to perform detailed, high spatiotemporal resolution, multi-platform observations to quantify micrometeorological benefits of the cool pavements and address concerns regarding glare, chemistry/air quality, and pedestrian thermal comfort. Results indicated large variability, as expected, but that the dominant effects were beneficial both in direct side-by-side, real-time comparisons (RT) between test and reference areas, as well as in difference-of-difference (DofD) to quantify local changes in test areas. During a heatwave in September 2022, maximum air-temperature differences (averaged over individual street segments) reached up to −1.9 °C RT in the afternoon. During non-heatwave, hot summer days, the largest street-segment-averaged afternoon air-temperature differences reached up to −1.4 °C RT or −2.8 °C DofD, and surface temperature up to −9.2 °C RT or −12.2 °C DofD. Whereas above values represent maximum effects, more typical street-segment averages also showed statistically significant benefits. In the afternoon, the mean of air-temperature differences was −0.2 °C RT and −1.2 °C DofD. The mean of surface-temperature differences was −2.6 °C RT and −4.9 °C DofD. Indicators of pedestrian thermal comfort also showed variability but predominantly a cooling effect. The mean of differences in mean radiant temperature was between −0.9 and −1.3 °C RT, and for physiological equivalent temperature, between −0.2 °C and −0.6 °C RT and −1.7 °C DofD. In terms of predicted mean vote, the mean of differences was −0.09 RT and −0.32 DofD.
- The following article is Open accessMining governance in the Philippines: interactions among governance mechanisms and stakeholder experiences
Cecilia Tortajada et al 2026 Environ. Res. Commun. 8 085027
View article, Mining governance in the Philippines: interactions among governance mechanisms and stakeholder experiencesPDF, Mining governance in the Philippines: interactions among governance mechanisms and stakeholder experiencesMining governance is essential for balancing mineral development with environmental protection, social equity, and sustainable resource management. In the Philippines, mining governance is implemented through regulatory, social, and community-based mechanisms that seek to protect indigenous rights, promote community development, and formalize artisanal and small-scale mining (ASM). However, limited research has examined how these governance mechanisms interact in practice and how they collectively influence governance outcomes. This study investigates the interactions among governance mechanisms, institutional relationships, and stakeholder experiences in shaping mining governance in the town of Itogon, Benguet Province, Philippines, where large-scale mining and ASM coexist. Data were collected using a key informant interviews and focus group discussions involving government agencies, mining companies, Indigenous Peoples’ representatives, local government officials, community leaders, and ASM stakeholders. The data were then analyzed using thematic analysis and interpreted using a political ecology framework. The findings indicate that mining governance is characterized by centralized decision-making, uneven stakeholder participation, barriers to equitable access to formal governance arrangements, fragmented institutional coordination, persistent environmental governance challenges, and unequal distribution of mining benefits. Although existing governance mechanisms provide an important institutional framework, their implementation is shaped by power relations, institutional capacity, and local socio-environmental conditions, resulting in different experiences and outcomes among stakeholder groups. The results demonstrate that mining governance is better understood by examining the interactions among governance mechanisms, institutions, and stakeholder experiences rather than individual governance instruments in isolation. These findings provide an integrated understanding of mining governance and offer empirical evidence to support more transparent, inclusive, and environmentally sustainable governance of mineral resources in the Philippines and other resource-dependent regions.
- The following article is Open accessEvaluating machine learning and baseline methods for crop yield forecasting using small datasets
Olena Kopishynska et al 2026 Environ. Res. Commun. 8 085008
View article, Evaluating machine learning and baseline methods for crop yield forecasting using small datasetsPDF, Evaluating machine learning and baseline methods for crop yield forecasting using small datasetsAccurate crop-yield forecasting is difficult when only small official-statistics datasets are available. This study evaluates a reproducible pre-season regional forecasting workflow for wheat, maize, and sunflower in Poltava region, Ukraine, using harmonised AgroStats records for 2010–2024. The analysis is based on one annual regional time series per crop; it is therefore a benchmark of temporal forecasting from official statistics rather than a gridded yield-prediction or spatial-mapping study. Forecast accuracy is assessed with mean absolute error (MAE), root mean squared error, and mean absolute percentage error. To avoid information leakage, feature transformations, imputations, scaling, and hyperparameter choices are performed only within the corresponding historical training window under a forward temporal design: training set 2010–2018, validation set 2019–2021, and held-out test set 2022–2024. In addition to ElasticNet, XGBoost, and LightGBM, the study compares transparent baseline forecasting methods: Naive, FORECAST.LINEAR, LINEST, and autoregressive integrated moving averag. Under the conservative lag-only scenario, the best 2022–2024 test results are obtained for maize (LightGBM, MAE 0.69 t ha−1) and sunflower (LightGBM, MAE 0.04 t ha−1), whereas for wheat the linear-trend baseline remains slightly better (MAE 0.49 t ha−1 versus 0.54 t ha−1 for ElasticNet). Supplementary analyses show that extended lag structures can improve selected crops and that seasonal NASA Prediction of Worldwide Energy Resources climate aggregates improve maize forecasts (MAE 0.52 t ha−1) but not wheat or sunflower. SHapley Additive exPlanations are used descriptively to examine whether the selected models rely on agronomically plausible predictors. The findings should be interpreted as crop-specific evidence under a small annual dataset: machine learning does not guarantee superiority over simple baselines, but it can provide a reproducible comparison framework and useful gains for selected regional forecasting tasks.
- The following article is Open accessMulti-scale numerical simulation of storm-driven sediment transport, resuspension and dispersal dynamics
Chunlei Wei et al 2026 Environ. Res. Commun. 8 085009
View article, Multi-scale numerical simulation of storm-driven sediment transport, resuspension and dispersal dynamicsPDF, Multi-scale numerical simulation of storm-driven sediment transport, resuspension and dispersal dynamicsFocusing on the scale-dependent sediment redistribution process driven by storm flow control conversion and terrain constraints during extreme storm surge, this study constructs a multi-scale three-dimensional storm surge-sediment coupling model to analyze sediment transport, bed resuspension and particle dispersion response during Typhoon Mangkhut in the Northern South China Sea. The focus of the study is to identify how the near-shore sediment system undergoes short-term pulse resuspension and redistribution after the tidal current background is changed to storm flow control. The study first integrates publicly available datasets such as the European Centre for Medium-Range Weather Forecasts Reanalysis, Version 5 (ERA5), the General Bathymetric Chart of the Oceans, and the Global Extreme Sea Level Analysis to construct a storm surge-sediment coupling model covering both regional and local fine-scale areas. Next, Eulerian concentration field analysis and Lagrangian particle tracking methods are applied to describe sediment behavior from both the continuous field and trajectory evolution perspectives. The results show that at 18: 00 UTC (coordinated universal time) on 16 September 2018, that is, 24 h after the starting point of formal analysis, the study area entered the peak response stage of the storm. At this time, the near-bottom velocity, bottom shear stress and turbulent kinetic energy are enhanced synchronously, and the sediment system is controlled by tidal current background to storm flow. Compared with the baseline of calm weather, suspended sediment concentration is increased by 5.00–5.93 times. The peak flux of 0.24–0.30 kg (m2·s)−1 corresponds to the equivalent thickness of 4.0–49.8 mm, which indicates that there is a potential bed response capability of millimeter to centimeter level at the peak stage of the storm. The local fine grid reveals that estuary convergence, shallow water shelf constraint and semi-enclosed bay topography jointly amplify the local resuspension and dispersion intensity. The research shows that the coastal sediment response during storm period should be understood as a resuspension-redistribution event triggered by storm flow control conversion and amplified by terrain constraints. It can provide process clues for the patrol survey of the channel edge after the incident, the recheck of shallow channel deposits and the disturbance screening of high turbidity areas, and does not directly replace the on-site erosion and deposition measurement or the determination of ecological threshold.
- The following article is Open accessPlace-by-place analysis as ideal representations of surface water plastics in Nunatsiavut, Labrador, Canada
Riley Cotter et al 2026 Environ. Res. Commun. 8 085037
View article, Place-by-place analysis as ideal representations of surface water plastics in Nunatsiavut, Labrador, CanadaPDF, Place-by-place analysis as ideal representations of surface water plastics in Nunatsiavut, Labrador, CanadaThe Nunatsiavut Government (NG) has long led interdisciplinary contaminants monitoring in Labrador, Canada, centring Inuit-led research priorities. As marine plastic pollution increasingly interacts with Arctic ecosystems and Indigenous foodways, community-based monitoring and mitigation become essential. Yet dominant Western approaches to marine surface-water plastic monitoring often produce results poorly suited to community inquiry, emphasizing broad oceanic-scale concentrations rather than local patterns. This study investigates plastics in Nunatsiavut’s marine surface waters (>333 µm) and advances two methodological approaches to improve community relevance. First, we develop a method to assess whether plastics likely originate locally or from long-range transport. Second, while we address regional patterns where appropriate, we conduct a place-by-place analysis that more accurately and meaningfully quantifies plastics than regional averages. Across most sites, plastic concentrations and plastic characteristics resembled those reported elsewhere in the Arctic, although site-level differences would have been obscured by aggregation. Most plastics were microplastics (<5 mm; 86%) and fragments (50.6%, n = 86), with wastewater microfibres (22%) and fishing-line threads (15%) as the most common identifiable sources. Our locality assessment method indicated that a greater proportion of plastic likely originated locally (39%) than from long-range transport (19%), while 42% remained indeterminate due to methodological constraints. We conclude by showing how community-oriented methods and site-level variation position place as a central analytic in surface-water plastics research.
- The following article is Open accessExperimental study of physicochemical and biological controls on dissolved oxygen in an urban tidal river
Guangling Huang et al 2026 Environ. Res. Commun. 8 085036
View article, Experimental study of physicochemical and biological controls on dissolved oxygen in an urban tidal riverPDF, Experimental study of physicochemical and biological controls on dissolved oxygen in an urban tidal riverDissolved oxygen (DO) is crucial for maintaining ecological integrity in tidal river tributaries. However, the relative roles of physical, chemical, and biological factors in urban tidal rivers remain unclear. In this study, controlled laboratory experiments were conducted to investigate the mechanisms by which these factors and their interactions influence DO dynamics in an urban tidal river. Temporal variations in DO and three nitrogen species were analyzed, and the implications for low-oxygen control were evaluated. The results indicate that physical factors mainly determine the background trajectory and overall range of DO variation. Higher flow velocities increase DO concentrations and accelerate recovery. Salinity showed no clear monotonic effect across the low-to-moderate range tested, whereas the highest salinity treatment produced lower DO levels. Among the chemical treatments, NH3-N removal maintained substantially higher DO than COD removal or raw-water conditions. Sediment addition caused rapid DO depletion under both chemical and flow treatments, followed by only partial recovery. The influence of biota on DO was condition-dependent and became clearer mainly under high-temperature and still-water conditions. These findings suggest that prioritizing NH3-N reduction, controlling sediment-related internal loading, and moderately enhancing mixing and reaeration are effective strategies for increasing and stabilizing DO levels.
- The following article is Open accessHigh geogenic cadmium with paradoxically low bioavailability in karstic Cambisols: variability across land uses of subtropical Guangxi
Na Li et al 2026 Environ. Res. Commun. 8 085035
View article, High geogenic cadmium with paradoxically low bioavailability in karstic Cambisols: variability across land uses of subtropical GuangxiPDF, High geogenic cadmium with paradoxically low bioavailability in karstic Cambisols: variability across land uses of subtropical GuangxiSoils derived from carbonate rocks are characterized by the accumulation of high levels of geogenic cadmium (Cd). Nevertheless, varying reports indicate that the bioavailability of this geogenic Cd is generally limited, possibly due to inherent soil properties, including high CaO concentration, strong alkalinity, and abundant Fe oxides that enhance Cd immobilization. However, the available evidence on the extent and consistency of this limited bioavailability remains inadequate and sometimes inconsistent across different karst systems. This study examined Cd in soils of Mashan County, Guangxi Zhuang Autonomous Region, a typical subtropical karst area in China. By conducting a comprehensive analysis of soil physicochemical properties across different land use types, we investigated the spatial distribution characteristics of soil Cd and its bioavailability, aiming to better understand the controlling factors governing Cd behavior in Cambisols. This study employed partial least squares path modeling (PLSPM) to assess the effects of lithology and land use on Cd bioavailability. Results showed that (1) Cd in these carbonate-derived Cambisols had an average concentration of 9.05 mg kg−1, 12 times higher than that of Acrisols in non-karst areas, but with low bioavailability (0.52%) compared to Acrisols (5.45%), partly due to substantially higher Fe2O3 concentrations (10.82% vs 5.52%), which may enhance Cd sorption. (2) The PLSPM revealed that land use had a strong influence on Cd bioavailability, exceeding the influence of lithology. Cd bioavailability in karst areas followed the order of drylands > abandoned farmlands > paddy fields > shrublands. (3) Soil organic matter (SOM) and pH, which are influenced by land use, were the key factors controlling Cd bioavailability in this karst region. Both Paddy fields and drylands exhibited lower SOM concentrations and lower pH levels than shrubland soils (i.e. undisturbed forest soils with minimal human disturbance). Lower pH levels increased Cd solubility while lower SOM concentrations reduced the adsorption and binding capacity for Cd mobility. These findings highlight land use and soil properties as critical controls of Cd bioavailability. Strategies, such as optimizing land use, pH buffering using different amendments, and increasing SOM, can mitigate Cd contamination, reduce crop uptake, and promote safer agriculture.
- The following article is Open accessSolar panel, vegetation management and legacy effects on vegetation in Western European solar parks
Lucas Etienne et al 2026 Environ. Res. Commun. 8 081016
View article, Solar panel, vegetation management and legacy effects on vegetation in Western European solar parksPDF, Solar panel, vegetation management and legacy effects on vegetation in Western European solar parksThe rapid development of renewable energy sources, such as photovoltaic electricity production, impacts natural and semi-natural habitats such as grasslands. The construction of solar parks involves earthworks usually destroying a part of the above-ground vegetation, related organisms and ecosystem services. However, subsequent management by grazing or cutting may also contribute to the création or restoration of semi-natural grasslands. We analysed the effects of solar panels, vegetation management and previous land use (legacy effect) on plant community characteristics such as cover, species richness, light indicator values and species composition in European solar parks. We used different data sets obtained from 2016 to 2025 in France, Germany and the United Kingdom, including 161 solar parks and 2429 survey plots. Our results showed that solar panels significantly reduced plant cover and species richness compared to inter-rows or plots outside the panels array. We also found significantly lower light indicator values under panels, reflecting a shift towards shade-tolerant vegetation. Surprisingly, vegetation management did not have a significant main effect on plant communities, but showed a significant interaction with plot location (under panels, inter-row or outside the panels array). Grazing and/or cutting changed the plant community composition only under panels but not between panel rows (inter-row) or outside panel arrays. Finally, a legacy effect of pre-construction habitats was detected. Species richness was lowest in former woodlands and highest in former industrial fields. Our study highlights the specific need for restoration measures to favour the colonisation by shade-tolerant species under panels and to introduce grassland species in solar parks on former woodlands, particularly in woodland dominated landscapes.
- The following article is Open accessThe role of meso-level organizations in climate adaptation for small-scale producers in Sub-Saharan Africa—insights from four African countries
Darlington Sibanda et al 2026 Environ. Res. Commun. 8 081018
View article, The role of meso-level organizations in climate adaptation for small-scale producers in Sub-Saharan Africa—insights from four African countriesPDF, The role of meso-level organizations in climate adaptation for small-scale producers in Sub-Saharan Africa—insights from four African countriesMeso-level organizations (MLOs) are core climate change adaptation (CCA) actors responsible for interweaving micro-level rural community needs with macro-level policy and finance intentions. This study draws on qualitative data from four African countries: Ghana, Kenya, Malawi, and South Africa to examine the role of MLOs in CCA targeting small-scale producers. The findings reveal a diverse and complex landscape of organizational actors operating across varied geographic and social contexts, with significant differences in capacities and functions. These variations are reflected in four key dimensions: stability, flexibility, specialization, and autonomy, which are critical for enabling locally led adaptation initiatives. While many MLOs demonstrate relative stability, they are often highly dependent on a limited number of funding sources, constraining their autonomy. The analysis deepens understanding of how adaptation systems are configured across these contexts and suggests that effective local adaptation governance does not require all organizations to perform strongly across every dimension. Instead, it highlights the importance of complementary organizational roles and provides valuable entry points for strengthening existing climate adaptation organizational ecosystems in Sub-Saharan Africa.
- The following article is Open accessAre rock glaciers useful climate indicators?
R Kenner 2026 Environ. Res. Commun. 8 082002
View article, Are rock glaciers useful climate indicators?PDF, Are rock glaciers useful climate indicators?Rock glaciers are ice-bearing, creeping landforms of the cryosphere, and their spatial occurrence and deformation velocity are sensitive to climate. Permafrost research has made several attempts to use this climate sensitivity to establish rock glaciers as climate indicators. A recent initiative succeeded to make rock glacier velocity (RGV) a quantity of the essential climate variable (ECV) permafrost. To justify this step, the initiators formulated the role of rock glaciers for the ECV permafrost with caution. In scientific practice, however, reference was made to the initiative in order to interpret the relevance of RGV more broadly and attribute a direct role of a climate indicator to it. This ambivalence should be converted into a consensus, recognizing the need for long-term rock glacier monitoring, but at the same time agreeing on the limits of a reasonable interpretation of RGV. Rock glacier-based paleoclimatology constitutes a second important approach to use rock glaciers as climate proxies. It is based on the comparison of the spatial distribution of active and relict rock glaciers to derive a climate signal. With slightly varying methodology, this approach has been used in numerous publications and over several decades. Taken together, the results reveal considerable variations, some of which are a consequence of conceptual weaknesses. Considering the current state of knowledge on rock glacier formation and referring to alternative climate reconstructions, the possibilities and limits of rock glacier-based paleoclimatology are evaluated. This review evaluates the general suitability of rock glaciers as climate indicators, particularly in comparison to other climate indicators from the research field of mountain permafrost. At the same time, it emphasises their complex climate sensitivity and the resulting need to monitor and investigate rock glaciers, since they play a significant role in alpine mass wasting and can be a hazard potential for mountain communities.
- The following article is Open accessAttribution of climate change and anthropogenic activities on regional to global scale water cycle: a comprehensive review
Balaram Shaw et al 2026 Environ. Res. Commun. 8 082001
View article, Attribution of climate change and anthropogenic activities on regional to global scale water cycle: a comprehensive reviewPDF, Attribution of climate change and anthropogenic activities on regional to global scale water cycle: a comprehensive reviewThe global water cycle has experienced significant changes over the last century due to anthropogenic activities coupled with climate change. Attributing and quantifying the respective contribution of these factors that drives the alteration in hydrological components is essential for better planning and management of water resources. Therefore, a significant number of studies spanning from pre- to post-industrial eras have tried to attribute observed hydrological changes to climate and humans. These studies employ various techniques ranging from process-based to semi-empirical to statistical to machine learning. This paper provides a comprehensive review of conventional and emerging attribution methods for major hydrological components, including streamflow, evapotranspiration, water levels, and groundwater storage. While each method offers unique strengths suited to a particular application, they also exhibit certain limitations creating space for potential improvement, which are further discussed in this review. Furthermore, numerous attribution studies around the globe are surveyed to highlight well-studied and overlooked basins along with their results. We found that approximately 70% of the studied basins exhibit stronger influence from human activities than from climatic factors. Finally, we propose a decision framework to guide the selection of attribution method under specific constraints. This review offers a structured guide to selecting appropriate techniques, foster advancements in methodologies, and expansion of attribution research to under-studied regions.
- The following article is Open accessWater resource impacts of lithium mining expansion in the Western U.S.
Jing Liu et al 2026 Environ. Res. Commun. 8 072005
View article, Water resource impacts of lithium mining expansion in the Western U.S.PDF, Water resource impacts of lithium mining expansion in the Western U.S.Rising global demand for lithium presents a dual challenge: lithium extraction is essential for clean energy technologies but can impose significant local environmental costs, particularly on water resources in arid regions. This narrative review focuses on the Western United States, where lithium mining is expanding but water-related impacts remain understudied. To provide context specific to this region, we examine the two most relevant resource types—brine and clay—and their associated extraction methods. We synthesize current knowledge on how these methods affect mine-site water quantity, quality, and hydrological processes across the mine life cycle, from exploration to closure. In addition, we highlight how regulatory frameworks—particularly those related to water rights, permitting, and procedural justice—mediate water risks and trade-offs. By addressing the governance and institutional dimensions often underexplored in the technical literature, this review aims to complement existing studies on extraction technologies and inform more sustainable water management in the face of growing lithium demand and development.
- The following article is Open accessMind the gap: a systematic review on how provisional ecosystem services are linked to human health and wellbeing in Africa
NB Selamolela et al 2026 Environ. Res. Commun. 8 072004
View article, Mind the gap: a systematic review on how provisional ecosystem services are linked to human health and wellbeing in AfricaPDF, Mind the gap: a systematic review on how provisional ecosystem services are linked to human health and wellbeing in AfricaBackground/Rationale. In spite of the fact that ecosystems are deteriorating and being degraded by humans, there is still a knowledge gap regarding their purpose and benefits to society. Provisioning ecosystem services are vital to both human existence and economic activity throughout Africa, yet the connections between these services and human health and wellbeing remain poorly understood. Objectives. This paper aims to highlight research conducted on provisioning ecosystem services in Africa and their impact on human health and wellbeing over the last three decades (1991–2021). Methods. According to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach, PSALSAR was used to identify studies conducted between 1991 and 2021 that examined the value of provisioning ecosystem services. In order to provide a comprehensive view of the existing literature, the paper combined bibliometric analysis with the PRISMA protocol. An analysis of the bibliometric data was visualized using the VOS viewer software. Results. With approximately 70 000 publications on ecosystem services, South Africa is the leading country in Africa in terms of knowledge contribution and analysis. Human health and ecosystem services research focuses primarily on ecosystem services management and zoonotic diseases. A similar approach is taken by researchers studying ecosystem services and human wellbeing in relation to challenges faced by landscapes, ecosystem conservation, biodiversity conservation, and management. Conclusions. The future trends are leaning towards the interconnectedness of social-ecological systems, biodiversity conservation and management, agriculture, and ecosystem function in the provision of ecosystem services.
- The following article is Open accessEnvironmental impacts of interbasin water transfers: a bibliometric analysis and systematic review of remote sensing evidence
Jorge Martínez-Angulo et al 2026 Environ. Res. Commun. 8 072003
View article, Environmental impacts of interbasin water transfers: a bibliometric analysis and systematic review of remote sensing evidencePDF, Environmental impacts of interbasin water transfers: a bibliometric analysis and systematic review of remote sensing evidenceInter-basin water transfers (IBWTs) are increasingly implemented to alleviate water scarcity; however, their environmental impacts remain heterogeneous and difficult to compare across projects. This study combined a bibliometric analysis of 643 unique articles and reviews indexed in Scopus and Web of Science (1971–2025) with a Preferred Reporting Items for Systematic reviews and Meta-Analyses-guided systematic review to examine the evolution of environmentally oriented IBWT research and to identify the environmental impacts quantified through remote sensing (RS) within the eligible evidence base. A total of 1018 records were initially retrieved; 13 studies met the final inclusion criteria and were incorporated into the comparative synthesis. Results indicate substantial growth in the field over the last two decades, accompanied by increasing international collaboration, predominantly led by China and the United States, and growing thematic convergence around water management, sustainability, governance, water quality, and biodiversity. However, within the systematic review subset, the eligible RS evidence base was narrow and geographically concentrated, with 11 of the 13 included studies conducted in China and 2 in Iran. In this 13-study subset, RS applications focused mainly on terrestrial and landscape-scale impacts, particularly vegetation, land-use/land-cover change, riparian condition, and integrated eco-environmental assessment. In contrast, aquatic, hydraulic, and process-level impacts were less consistently captured within the eligible RS evidence base. Landsat-based optical workflows, typically operating at a 30 m spatial resolution and relying on discrete multi-year observations, were the most commonly reported configuration among the included RS studies. By linking bibliometric breadth from the full indexed corpus with systematically extracted evidence from a small and geographically concentrated RS subset, this study provides a more reproducible picture of where RS-based IBWT environmental monitoring is strongest within the available eligible evidence, where major gaps persist, and which methodological limitations still constrain cross-case comparability and long-term environmental decision making. These findings suggest that future research should prioritize standardized, explicitly reported, and methodologically comparable remote-sensing approaches to strengthen environmental monitoring and improve cross-case assessment in IBWT systems.
- The following article is Open accessAn integrated machine learning framework for multidimensional cyclone vulnerability assessment and disaster risk reduction in Mozambique
Comia et al
View accepted manuscript, An integrated machine learning framework for multidimensional cyclone vulnerability assessment and disaster risk reduction in MozambiquePDF, An integrated machine learning framework for multidimensional cyclone vulnerability assessment and disaster risk reduction in MozambiqueCyclone impacts in data-scarce rural districts are often assessed through fragmented approaches, limiting evidence-based disaster-risk planning. This study developed and externally validated an integrated geospatial framework for Monapo district, Nampula Province, Mozambique, combining an Environmental Vulnerability Index (EVI), a Socioeconomic Vulnerability Index (SVI) at the administrative-post scale, and a Random Forest classifier. Landsat-8 imagery acquired immediately prior to Cyclone Gombe landfall (January-February 2022) and during the post-landfall period (July-December 2022) was used to derive NDVI, land surface temperature, and a four-class land-cover map, while SRTM elevation, FAO soils, and 2017 census data were used to construct the EVI and SVI surfaces using fixed 0.2-unit equal-interval classes. The Random Forest model was trained on 1,000 stratified samples and internally validated using repeated spatially blocked cross-validation. External validation used the 12 official displacement centres reported by INGC, which were excluded from model fitting. High and Very High EVI classes covered 42.3% of the district (2,061 km²), whereas High and Very High SVI classes covered 28.1% (1,370 km²) and included 34.2% of the population (134,724 residents). Model performance was strong, with an AUC of 0.924 and an overall accuracy of 87.5%. In external validation, 9 of the 12 official displacement centres (75.0%) fell within predicted High or Very High EVI zones, while 8 of the 12 centres (66.7%) were located in High or Very High SVI zones. Post-cyclone settlement expanded by 63 km², and 67.8% of this growth occurred in moderate-to-high vulnerability zones. The framework provides an evidence base for spatially explicit reconstruction planning and a transferable approach for cyclone vulnerability assessment in data-scarce settings.
- The following article is Open accessCircular Management of Decommissioned Wind Turbines in the Process of Sustainable Urban Development - Evidence from Shanghai
Zhuang et al
View accepted manuscript, Circular Management of Decommissioned Wind Turbines in the Process of Sustainable Urban Development - Evidence from ShanghaiPDF, Circular Management of Decommissioned Wind Turbines in the Process of Sustainable Urban Development - Evidence from ShanghaiRapid expansion of wind power plays a crucial role in advancing sustainable energy transition. However, many of them will retire soon, which poses emerging resource challenges. Under such a circumstance, this study aims to estimate the spatiotemporal distribution and compositions of decommissioned wind turbines in Shanghai by applying a technology-specific material flow analysis model. The associated environmental and economic impacts of different recycling strategies are also measured. Results show that the cumulative decommissioned capacity will reach 836.02 MW by 2045 and are mainly concentrated in Chongming, Pudong, and Fengxian districts. The total weight of these retired wind turbines will reach nearly 0.5 million tons, in which steel, concrete, and cast iron are the major components. By recycling these retired wind turbines, about 0.58~0.59 million tons (Mt) of GHG emissions will be reduced, and economic return will reach 12.03~43.76 million RMB. In addition, results show that different optimization strategies lead to different impacts, which can facilitate policy makers to prepare their own strategy by considering the local realities. Finally, we propose several policy recommendations to achieve efficient end-of-life management on decommissioned wind turbines.
- The following article is Open access"What is a realistic forecast?" Assessing data-driven weather forecasts, a journey from verification to falsification.
Ben-Bouallègue
View accepted manuscript, "What is a realistic forecast?" Assessing data-driven weather forecasts, a journey from verification to falsification.PDF, "What is a realistic forecast?" Assessing data-driven weather forecasts, a journey from verification to falsification.The artificial intelligence revolution is fueling a paradigm shift in weather forecasting: forecasts are generated with machine learning models trained on large datasets rather than with physics-based numerical models that solve partial differential equations. This new approach proved successful in improving forecast performance as measured with standard verification metrics such as the root mean squared error. At the same time, the realism of data-driven weather forecasts is often questioned and considered as an Achilles' heel of machine learning models. How forecast realism can be defined and how this forecast attribute can be assessed are the two questions simultaneously addressed here. Inspired by the seminal work of Murphy (1993) on the definition of forecast goodness, we identify 3 types of realism and discuss methodological paths for their assessment. In this framework, falsification arises as a complementary process to verification and diagnostics when assessing data-driven weather models.
- The following article is Open accessA satellite-based geospatial framework for screening potential artificial light at night exposure in rice-growing landscapes: a nationwide case study in Thailand
Changruenngam et al
View accepted manuscript, A satellite-based geospatial framework for screening potential artificial light at night exposure in rice-growing landscapes: a nationwide case study in ThailandPDF, A satellite-based geospatial framework for screening potential artificial light at night exposure in rice-growing landscapes: a nationwide case study in ThailandArtificial light at night (ALAN) is increasingly recognized as an emerging environmental stressor with potential implications for agricultural systems, particularly for photoperiod-sensitive crops such as rice. However, large-scale and spatially explicit assessments of potential ALAN exposure in agricultural landscapes remain limited. In this study, we present a reproducible geospatial framework for screening potential ALAN exposure in rice-growing landscapes by integrating high-resolution rice cultivation maps and road-network-based proxies representing public lighting infrastructure, with calibrated Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime radiance data providing a common spatial reference. To evaluate the sensitivity of road-based estimates, multiple road-network scenarios and nominal road-proximity masks were incorporated into the analysis, and rice--road intersections were aggregated to a common VIIRS-scale grid for national comparisons. The framework was demonstrated through a nationwide case study in Thailand, one of the world's major rice-producing countries. Our results show that national estimates are highly sensitive to road-network selection and that local-access roads contribute substantially to the final proximity estimates. Under the complete road-network scenario, estimated rice--road proximity areas increased from 11\,175 km$^2$ (11.80\%) to 16\,697 km$^2$ (17.63\%) for major-rice systems and from 1,527 km^2 (10.12%) to 2,598 km^2 (17.20%) for minor-rice systems when moving from one- to two-pixel proximity masks. These findings demonstrate that road proximity should be interpreted as a structural proxy rather than direct evidence of ALAN exposure or agricultural impacts. Consequently, the proposed approach should be regarded as a first-order screening tool rather than a direct assessment of crop damage or yield loss. Overall, this study provides a transparent, reproducible, and transferable approach for screening potential ALAN exposure in agricultural systems and highlights the importance of considering nighttime lighting as an emerging environmental factor in agroecosystems. The proposed framework can support future field-validation studies, light-aware agricultural management, and environmental monitoring in rapidly developing regions.
- The following article is Open accessMulti-pollutant Optimization of Solketal Dosed Waste Cooking Oil Biodiesel Blends Using Scenario-Based Desirability and Regret Analysis
Chinthalapudi et al
View accepted manuscript, Multi-pollutant Optimization of Solketal Dosed Waste Cooking Oil Biodiesel Blends Using Scenario-Based Desirability and Regret AnalysisPDF, Multi-pollutant Optimization of Solketal Dosed Waste Cooking Oil Biodiesel Blends Using Scenario-Based Desirability and Regret AnalysisThe aim of this study is to evaluate diesel, Waste cooking oil biodiesel (WCO-BD), B20 (20 vol.% WCO-BD+80 vol.% diesel) and B20 doped with Solketal additive (2, 6, 8 and 10 vol.%) and to identify a blend-speed combination that optimizes brake thermal efficiency (BTE), fuel economy and regulated emissions under realistic speed variability. The novelty lies in treating the tested engine speeds as discrete operating cases and applying a speed-wise robust desirability methodology integrated with regret analysis, non-parametric significance tests and bootstrap confidence intervals to rank blends on both average and worst-case performance. Experimentally, a single cylinder diesel engine was fueled with seven blends (diesel, WCO-BD, B20, B20-SK2/6/8/10) over 1200-2400 rpm, measuring combustion, performance and emission characteristics. These responses were mapped to Derringer-Suich desirability, aggregated into an overall index and then summarized via mean desirability, worst-case desirability and a composite robust index. WCO-BD production achieved a 92% mass yield, while B20-SK8 delivered 37.8% BTE at 2000 rpm versus 36.3% for B20 and 35.6% for WCO-BD, reduced NOx by 12-20% and smoke by 28-35% relative to diesel and WCO-BD. B20-SK8 attained the highest scenario-aggregated desirability (0.626) with a zero-regret profile and a high desirability band over 1600-2000 rpm. Practically, the results indicate that B20 doped by 8 vol.% Solketal offers a speed-robust, multi-pollutant improvement for retrofitting small diesel engines on B20. The scenario-based methodology is generalizable to other fuels derived from waste and dual fuel concepts, supporting future robust calibration of low-carbon diesel engines.
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- The following article is Open accessHow to estimate carbon footprint when training deep learning models? A guide and review
Lucía Bouza et al 2023 Environ. Res. Commun. 5 115014
View article, How to estimate carbon footprint when training deep learning models? A guide and reviewPDF, How to estimate carbon footprint when training deep learning models? A guide and reviewMachine learning and deep learning models have become essential in the recent fast development of artificial intelligence in many sectors of the society. It is now widely acknowledge that the development of these models has an environmental cost that has been analyzed in many studies. Several online and software tools have been developed to track energy consumption while training machine learning models. In this paper, we propose a comprehensive introduction and comparison of these tools for AI practitioners wishing to start estimating the environmental impact of their work. We review the specific vocabulary, the technical requirements for each tool. We compare the energy consumption estimated by each tool on two deep neural networks for image processing and on different types of servers. From these experiments, we provide some advice for better choosing the right tool and infrastructure.
- The following article is Open accessTechnical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS model
Lena Höglund-Isaksson et al 2020 Environ. Res. Commun. 2 025004
View article, Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS modelPDF, Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS modelMethane is the second most important greenhouse gas after carbon dioxide contributing to human-made global warming. Keeping to the Paris Agreement of staying well below two degrees warming will require a concerted effort to curb methane emissions in addition to necessary decarbonization of the energy systems. The fastest way to achieve emission reductions in the 2050 timeframe is likely through implementation of various technical options. The focus of this study is to explore the technical abatement and cost pathways for reducing global methane emissions, breaking reductions down to regional and sector levels using the most recent version of IIASA’s Greenhouse gas and Air pollution Interactions and Synergies (GAINS) model. The diverse human activities that contribute to methane emissions make detailed information on potential global impacts of actions at the regional and sectoral levels particularly valuable for policy-makers. With a global annual inventory for 1990–2015 as starting point for projections, we produce a baseline emission scenario to 2050 against which future technical abatement potentials and costs are assessed at a country and sector/technology level. We find it technically feasible in year 2050 to remove 54 percent of global methane emissions below baseline, however, due to locked in capital in the short run, the cumulative removal potential over the period 2020–2050 is estimated at 38 percent below baseline. This leaves 7.7 Pg methane released globally between today and 2050 that will likely be difficult to remove through technical solutions. There are extensive technical opportunities at low costs to control emissions from waste and wastewater handling and from fossil fuel production and use. A considerably more limited technical abatement potential is found for agricultural emissions, in particular from extensive livestock rearing in developing countries. This calls for widespread implementation in the 2050 timeframe of institutional and behavioural options in addition to technical solutions.
- The following article is Open accessValidation of FABDEM, a global bare-earth elevation model, against UAV-lidar derived elevation in a complex forested mountain catchment
Christopher B Marsh et al 2023 Environ. Res. Commun. 5 031009
View article, Validation of FABDEM, a global bare-earth elevation model, against UAV-lidar derived elevation in a complex forested mountain catchmentPDF, Validation of FABDEM, a global bare-earth elevation model, against UAV-lidar derived elevation in a complex forested mountain catchmentSpace-based, global-extent digital elevation models (DEMs) are key inputs to many Earth sciences applications. However, many of these applications require the use of a ‘bare-Earth’ DEM versus a digital surface model (DSM), the latter of which may include systematic positive biases due to tree canopies in forested areas. Critical topographic features may be obscured by these biases. Vegetation-free datasets have been created by using statistical relationships and machine learning to train on local-scale datasets (e.g., lidar) to de-bias the global-extent datasets. Recent advances in satellite platforms coupled with increased availability of computational resources and lidar reference products has allowed for a new generation of vegetation- and urban-canopy removals. One of these is the Forest And Buildings removed Copernicus DEM (FABDEM), based on the most recent and most accurate global DSM Copernicus-30. Among the more challenging landscapes to quantify surface elevations are densely forested mountain catchments, where even airborne lidar applications struggle to capture surface returns. The increasing affordability and availability of UAV-based lidar platforms have resulted in new capacity to fly modest spatial extents with unrivalled point densities. These data allow an unprecedented ability to validate global sub-canopy DEMs against representative UAV-based lidar data. In this work, the FABDEM is validated against up-scaled lidar data in a steep and forested mountain catchment considering elevation, slope, and Terrain Position Index (TPI) metrics. Comparisons of FABDEM with SRTM, MERIT, and the Copernicus-30 dataset are made. It was found that the FABDEM had a 24% reduction in elevation RMSE and a 135% reduction in bias compared to the Copernicus-30 dataset. Overall, the FABDEM provides a clear improvement over existing deforested DEM products in complex mountain topography such as the MERIT DEM. This study supports the use of FABDEM in forested mountain catchments as the current best-in-class data product.
- The following article is Open accessApplying IPCC 2014 framework for hazard-specific vulnerability assessment under climate change
Jagmohan Sharma and Nijavalli H Ravindranath 2019 Environ. Res. Commun. 1 051004
View article, Applying IPCC 2014 framework for hazard-specific vulnerability assessment under climate changePDF, Applying IPCC 2014 framework for hazard-specific vulnerability assessment under climate changeThe Intergovernmental Panel on Climate Change (IPCC), Working Group II Report (2014) presents vulnerability as a pre-existing characteristic property of a system. Accordingly, indicators for ‘sensitivity’ and ‘adaptive capacity’, which are internal properties of a system, are employed to assess it. Comparatively, the IPCC 2007 report includes ‘exposure’, an external factor, as the third component of vulnerability. We have compared the construct of vulnerability presented in IPCC 2007 and 2014 reports. It is argued that the results of vulnerability assessment obtained by adopting IPCC 2014 framework are practically more useful for reducing current vulnerability in preparedness to deal with an uncertain future. In the process, we have articulated the novel concepts of ‘selecting hazard-relevant vulnerability indicators’ and ‘assessing hazard-specific vulnerability’. Use of these concepts improves the contextualization of an assessment and thereby the acceptability of assessment results by the stakeholders.
- The following article is Open accessWhat climate and environmental benefits of regenerative agriculture practices? an evidence review
Emily Rehberger et al 2023 Environ. Res. Commun. 5 052001
View article, What climate and environmental benefits of regenerative agriculture practices? an evidence reviewPDF, What climate and environmental benefits of regenerative agriculture practices? an evidence reviewRegenerative agriculture aims to increase soil organic carbon (SOC) levels, soil health and biodiversity. Regenerative agriculture is often juxtaposed against ‘conventional’ agriculture which contributes to land degradation, biodiversity loss, and greenhouse gas emissions. Although definitions of regenerative agriculture may vary, common practices include no or reduced till, cover cropping, crop rotation, reduced use or disuse of external inputs such as agrichemicals, use of farm-derived organic inputs, increased use of perennials and agroforestry, integrated crop-livestock systems, and managed grazing. While the claims associated with some of these practices are supported by more evidence than others, some studies suggest that these practices can be effective in increasing soil organic carbon levels, which can have positive effects both agriculturally and environmentally. Studies across these different regenerative agriculture practices indicate that the increase in soil organic carbon, in comparison with conventional practices, varies widely (ranging from a nonsignificant difference to as high as 3 Mg C/ha/y). Case studies from a range of regenerative agriculture systems suggest that these practices can work effectively in unison to increase SOC, but regenerative agriculture studies must also consider the importance of maintaining yield, or risk the potential of offsetting mitigation through the conversion of more land for agriculture. The carbon sequestration benefit of regenerative practices could be maximized by targeting soils that have been intensively managed and have a high carbon storage potential. The anticipated benefits of regenerative agriculture could be tested by furthering research on increasing the storage of stable carbon, rather than labile carbon, in soils to ensure its permanence.
- The following article is Open accessIncreased frequency of and population exposure to extreme heat index days in the United States during the 21st century
Kristina Dahl et al 2019 Environ. Res. Commun. 1 075002
View article, Increased frequency of and population exposure to extreme heat index days in the United States during the 21st centuryPDF, Increased frequency of and population exposure to extreme heat index days in the United States during the 21st centuryThe National Weather Service of the United States uses the heat index—a combined measure of temperature and relative humidity—to define risk thresholds warranting the issuance of public heat alerts. We use statistically downscaled climate models to project the frequency of and population exposure to days exceeding these thresholds in the contiguous US for the 21st century with two emissions and three population change scenarios. We also identify how often conditions exceed the range of the current heat index formulation. These ‘no analog’ conditions have historically affected less than 1% of the US by area. By mid-21st century (2036–2065) under both emissions scenarios, the annual numbers of days with heat indices exceeding 37.8 °C (100 °F) and 40.6 °C (105 °F) are projected to double and triple, respectively, compared to a 1971–2000 baseline. In this timeframe, more than 25% of the US by area would experience no analog conditions an average of once or more annually and the mean duration of the longest extreme heat index event in an average year would be approximately double that of the historical baseline. By late century (2070–2099) with a high emissions scenario, there are four-fold and eight-fold increases from late 20th century conditions in the annual numbers of days with heat indices exceeding 37.8 °C and 40.6 °C, respectively; 63% of the country would experience no analog conditions once or more annually; and extreme heat index events exceeding 37.8 °C would nearly triple in length. These changes amount to four- to 20-fold increases in population exposure from 107 million person-days per year with a heat index above 37.8 °C historically to as high as 2 billion by late century. The frequency of and population exposure to these extreme heat index conditions with the high emissions scenario is roughly twice that of the lower emissions scenario by late century.
- The following article is Open accessGroundwater extraction may drown mega-delta: projections of extraction-induced subsidence and elevation of the Mekong delta for the 21st century
P S J Minderhoud et al 2020 Environ. Res. Commun. 2 011005
View article, Groundwater extraction may drown mega-delta: projections of extraction-induced subsidence and elevation of the Mekong delta for the 21st centuryPDF, Groundwater extraction may drown mega-delta: projections of extraction-induced subsidence and elevation of the Mekong delta for the 21st centuryThe low-lying and populous Vietnamese Mekong delta is rapidly losing elevation due to accelerating subsidence rates, primarily caused by increasing groundwater extraction. This strongly increases the delta’s vulnerability to flooding, salinization, coastal erosion and, ultimately, threatens its nearly 18 million inhabitants with permanent inundation. We present projections of extraction-induced subsidence and consequent delta elevation loss for this century following six mitigation and non-mitigation extraction scenarios using a 3D hydrogeological model with a coupled geotechnical module. Our results reveal the long-term physically response of the aquifer system following different groundwater extraction pathways and show the potential of the hydrogeological system to recover. When groundwater extraction is allowed to increase continuously, as it did over the past decades, extraction-induced subsidence has the potential to drown the Mekong delta single-handedly before the end of the century. Our quantifications also disclose the mitigation potential to reduce subsidence by limiting groundwater exploitation and hereby limiting future elevation loss. However, the window to mitigate is rapidly closing as large parts of the lowly elevated delta plain may already fall below sea level in the coming decades. Failure to mitigate groundwater extraction-induced subsidence may result in mass displacement of millions of people and could severely affect regional food security as the food producing capacity of the delta may collapse.
- The following article is Open accessGreen finance, sustainable infrastructure, and green technology innovation: pathways to achieving sustainable development goals in the belt and road initiative
Shahid Mahmood et al 2024 Environ. Res. Commun. 6 105036
View article, Green finance, sustainable infrastructure, and green technology innovation: pathways to achieving sustainable development goals in the belt and road initiativePDF, Green finance, sustainable infrastructure, and green technology innovation: pathways to achieving sustainable development goals in the belt and road initiativeAchieving the Sustainable Development Goals (SDGs) remains a significant challenge for many countries, particularly in the face of increasing environmental pollution. Balancing social, economic, and environmental sustainability under these conditions is especially complex. This study explores the role of green finance in promoting sustainable infrastructure, innovation in green technology, corporate social responsibility, economic stability, and environmental conservation within the framework of Belt and Road initiative (BRI), with a specific focus on the China-Pakistan Economic Corridor (CPEC) initiatives. Furthermore, the study examines the role of government support in facilitating the issuance of GF, emphasizing its significance in large-scale international development projects like CPEC. Data were collected through a structured questionnaire targeting a diverse group of respondents, including businessmen, CPEC officials, and representatives from the Ministry of Finance, Pakistan Environmental Protection Agency, and Ministry of Planning and Development. Partial Least Squares analysis was employed to test the proposed relationships and hypotheses. The results indicate a significant positive impact of green finance on the development of sustainable infrastructure and the innovation of green technology. Additionally, the results underscore the pivotal role of environmentally friendly technologies and sustainable infrastructure in driving the achievement of SDGs, especially in the social, economic, and environmental dimensions. The study findings offer actionable insights for policymakers, highlighting the critical need to integrate green finance with sustainable practices to foster economic growth and environmental protection. These findings provide a strategic roadmap for nations aiming to align their development goals with global sustainability standards.
- The following article is Open accessRice residue burning in Northern India: an assessment of environmental concerns and potential solutions – a review
Dilwar Singh Parihar et al 2023 Environ. Res. Commun. 5 062001
View article, Rice residue burning in Northern India: an assessment of environmental concerns and potential solutions – a reviewPDF, Rice residue burning in Northern India: an assessment of environmental concerns and potential solutions – a reviewEnvironmental alarms like climate change and rising air pollution levels in north India, particularly in the Delhi National Capital Region (NCR), draw attention to the severe issue of Rice straw burning. Straw burning is the common practice in Punjab and Haryana’s Indo-Gangetic plains. Large-scale burning of residues (straw and stubble) is a severe problem that emits Green House Gases (GHGs) while polluting the air, posing health problems, and eliminating micronutrients from burned-out field. Residue management has been a problem for the paddy farmers and as time changes, it is necessary to update their practices. For the disposal of rice residue, farmers are constrained by an insufficient technology base and a lack of viable economic solutions. Technical solutions are available, classified mainly as on-site (in situ) and off-site (ex situ) solutions, the in situ solution includes a variety of machines that can be used to incorporate or mulch residue efficiently. While ex situ management allow collecting the residue from field for various applications such as energy production, briquetting, composting, paper and cardboard making, and for mushroom cultivation. Farmers in North India are not aware of the prolific alternatives for managing stubble and, therefore, consider burning as the best option. Therefore, extensive awareness programs are needed to inform farmers about economic options and the effects of stubble burning. Zero till drill, happy seeder and super Straw Management System (SMS) are recommended for the farmers, and need to be supplied in sufficient quantity to evade residue burning in these regions. Meanwhile, alternative technology for straw management constitutes an active area of research, area-specific and crop-specific applications need to be evolved. All stakeholders i.e., farmers, researchers, extension agents and policy makers need to be engaged in understanding and harnessing the full potential of using crop residues with conservation agriculture for sustainability and resilience of Indian agriculture.
- The following article is Open accessHydrologic risk from consecutive dry and wet extremes at the global scale
M M Rashid and T Wahl 2022 Environ. Res. Commun. 4 071001
View article, Hydrologic risk from consecutive dry and wet extremes at the global scalePDF, Hydrologic risk from consecutive dry and wet extremes at the global scaleDry and wet extremes (i.e., droughts and floods) are the costliest hydrologic hazards for infrastructure and socio-environmental systems. Being closely interconnected and interdependent extremes of the same hydrological cycle, they often occur in close succession with the potential to exacerbate hydrologic risks. However, traditionally this is ignored and both hazards are considered separately in hydrologic risk assessments; this can lead to an underestimation of critical infrastructure risks (e.g., dams, levees, dikes, and reservoirs). Here, we identify and characterize consecutive dry and wet extreme (CDW) events using the Standardized Precipitation Evapotranspiration Index, assess their multi-hazard hydrologic risks employing copula models, and investigate teleconnections with large-scale climate variability. We identify hotspots of CDW events in North America, Europe, and Australia where the total numbers of CDW events range from 20 to 30 from 1901 to 2015. Decreasing trends in recovery time (i.e., time between termination of dry extreme and onset of wet extreme) and increasing trends in dry and wet extreme severities reveal the intensification of CDW events over time. We quantify that the joint exceedance probabilities of dry and wet extreme severities equivalent to 50-year and 100-year univariate return periods increase by several folds (up to 20 and 54 for 50-year and 100-year return periods, respectively) when CDW events and their associated dependence are considered compared to their independent and isolated counterparts. We find teleconnections between CDW and Niño3.4; at least 80% of the CDW events are causally linked to Niño3.4 at 50% of the grid locations across the hotspot regions. This study advances the understanding of multi-hazard hydrologic risks from CDW events and the presented results can aid more robust planning and decision-making.
Journal resources
Environmental Publications
- Environmental Research Communications
- Environmental Research Letters
- Environmental Research: Climate
- Environmental Research: Ecology
- Environmental Research: Energy
- Environmental Research: Food Systems
- Environmental Research: Health
- Environmental Research: Infrastructure and Sustainability
- Environmental Research: Water
Journal information
- 2018-present
Environmental Research Communications
doi: 10.1088/issn.2515-7620
Online ISSN: 2515-7620