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Permafrost thaw increases active layer thickness, changes landscape hydrology and influences vegetation species composition. These changes alter belowground microbial and geochemical processes, affecting production, consumption and net emission rates of climate forcing trace gases. Net carbon dioxide (CO₂) and methane (CH₄) fluxes determine the radiative forcing contribution from these climate-sensitive ecosystems. Permafrost peatlands may be amosaic of dry frozen hummocks, semi-thawed or perched sphagnum dominated areas, wet permafrost-free sedge dominated sites and open water ponds. We revisited estimates of climate forcing made for 1970 and 2000 for Stordalen Mire in northern Sweden and found the trend of increasing forcing continued into 2014. The Mire continued to transition from dry permafrost to sedge and open water areas, increasing by 100% and 35%, respectively, over the 45-year period, causing the net radiative forcing of Stordalen Mire to shift from negative to positive. This trend is driven by transitioning vegetation community composition, improved estimates of annual CO₂ and CH₄ exchange and a 22% increase in the IPCC’s 100-year global warming potential (GWP_100) value for CH₄. These results indicate that discontinuous permafrost ecosystems, while still remaining a net overall sink of C, can become a positive feedback to climate change on decadal timescales. This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 2)’.

The rapid growth of roving mining camps has negatively influenced their surrounding environment. Although artisanal and small-scale gold mining (ASGM) is a major source of gold production, the mining activities and their activeness are not well revealed owing to their informal, illegal, and unregulated characteristics. This study characterizes the transformations of roving camp-type ASGM (R-C-ASGM) activities in Central of Katingan Regency, Central Kalimantan Province, Indonesia, from 2015 to 2021 using remotely sensed data, such as the time-series Sentinel-1 dataset. The results show that the growth of active R-C-ASGM sites was identified at the center of the Galangan mining region with expansions to the northwest part along the Kalanaman River, especially in 2021. Hence, these approaches identify the transformations of roving mining activities and their active or nonactive status even in tropical regions experiencing frequent heavy traffic rainstorms. They provide significant information on the socioenvironmental risks possibly caused at local and regional levels. Our results also inform the design of timely interventions suited to local conditions for strengthening environmental governance.

The environmental cycling of mercury (Hg) can be affected by natural and anthropogenic perturbations. Of particular concern is how these disruptions increase mobilization of Hg from sites and alter the formation of monomethylmercury (MeHg), a bioaccumulative form of Hg for humans and wildlife. The scientific community has made significant advances in recent years in understanding the processes contributing to the risk of MeHg in the environment. The objective of this paper is to synthesize the scientific understanding of how Hg cycling in the aquatic environment is influenced by landscape perturbations at the local scale, perturbations that include watershed loadings, deforestation, reservoir and wetland creation, rice production, urbanization, mining and industrial point source pollution, and remediation. We focus on the major challenges associated with each type of alteration, as well as management opportunities that could lessen both MeHg levels in biota and exposure to humans. For example, our understanding of approximate response times to changes in Hg inputs from various sources or landscape alterations could lead to policies that prioritize the avoidance of certain activities in the most vulnerable systems and sequestration of Hg in deep soil and sediment pools. The remediation of Hg pollution from historical mining and other industries is shifting towards in situ technologies that could be less disruptive and less costly than conventional approaches. Contemporary artisanal gold mining has well-documented impacts with respect to Hg; however, significant social and political challenges remain in implementing effective policies to minimize Hg use. Much remains to be learned as we strive towards the meaningful application of our understanding for stakeholders, including communities living near Hg-polluted sites, environmental policy makers, and scientists and engineers tasked with developing watershed management solutions. Site-specific assessments of MeHg exposure risk will require new methods to predict the impacts of anthropogenic perturbations and an understanding of the complexity of Hg cycling at the local scale.

This study investigates the land use and land cover (LULC) changes in Peshawar, Pakistan, from 2002 to 2022, and their relationship with local climate patterns. Utilizing a combination of remote sensing techniques, GIS analysis, and climate data, the research provides a comprehensive assessment of urban transformation in one of Pakistan’s major cities. Landsat imagery was used to classify and map LULC changes, while climate data were analyzed to identify temperature and precipitation trends. Results reveal significant urban expansion, with built-up areas increasing from 12% (154.4 km2) to 17% (213.6 km2) of the total land area over the study period. Contrary to initial expectations, vegetation cover showed a substantial increase from 57% (728.8 km2) to 70% (898.2 km2), while bare land decreased dramatically from 30% (384.1 km2) to 13% (162.6 km2). Water bodies remained relatively stable at approximately 1% of the area. Land Surface Temperature (LST) analysis shows a narrowing of the temperature range, with the maximum LST decreasing slightly from 34.39 °C to 33.66 °C and the minimum LST increasing from 27.71 °C to 29.12 °C between 2002 and 2022. Precipitation patterns exhibited a significant increasing trend, with maximum annual rainfall rising from 375.76 mm to 519.77 mm, representing a 38% increase. The study reveals a complex urban development pattern where expansion of built-up areas is accompanied by significant increases in vegetation cover. These findings underscore the need for adaptive urban planning strategies in Peshawar, emphasizing the importance of managing urban growth while preserving and enhancing green spaces. The study provides valuable insights for policymakers and urban planners, contributing to the development of sustainable and resilient urban environments in rapidly growing cities.

As an important application in remote sensing, landcover classification remains one of the most challenging tasks in very-high-resolution (VHR) image analysis. As the rapidly increasing number of Deep Learning (DL) based landcover methods and training strategies are claimed to be the state-of-the-art, the already fragmented technical landscape of landcover mapping methods has been further complicated. Although there exists a plethora of literature review work attempting to guide researchers in making an informed choice of landcover mapping methods, the articles either focus on the review of applications in a specific area or revolve around general deep learning models, which lack a systematic view of the ever advancing landcover mapping methods. In addition, issues related to training samples and model transferability have become more critical than ever in an era dominated by data-driven approaches, but these issues were addressed to a lesser extent in previous review articles regarding remote sensing classification. Therefore, in this paper, we present a systematic overview of existing methods by starting from learning methods and varying basic analysis units for landcover mapping tasks, to challenges and solutions on three aspects of scalability and transferability with a remote sensing classification focus including (1) sparsity and imbalance of data; (2) domain gaps across different geographical regions; and (3) multi-source and multi-view fusion. We discuss in detail each of these categorical methods and draw concluding remarks in these developments and recommend potential directions for the continued endeavor.

Landcover changes have altered the natural carbon cycle; however, most landcover studies focus on either forest conversion to agriculture or urban, rarely both. We present differences in dissolved organic carbon (DOC) concentrations and dissolved organic matter (DOM) molecular composition within Upper Mississippi River Basin low order streams and rivers draining one of three dominant landcovers (forest, agriculture, and urban). Streams draining forest and urban landcovers have greater DOC concentrations, likely driven by differences in carbon sourcing, microbial processing, and soil disturbance. Using Fourier transform-ion cyclotron resonance mass spectrometry, 24% of assigned molecular formulae are common across all landcovers. Relative abundances of N-,S- heteroatomic formulae (CHON, CHOS, CHONS) are higher for agricultural and urban streams, with agricultural stream DOM having more N-containing formulae compared to urban stream DOM, which has more S-containing formulae. Higher N-,S- heteroatomic formulae abundance, along with enrichment in aliphatic, N-aliphatic, and highly unsaturated and phenolic (low O/C) compound categories within agricultural and urban stream DOM are likely to result from increased anthropogenic inputs, autochthonous production, and microbial processing associated with agricultural and urban impacts. Reduced N-,S- heteroatomic formulae abundances in forested stream DOM, along with enrichments in condensed aromatics, polyphenolics, and highly unsaturated phenolic (high O/C) compound categories, likely reflect greater contributions from surrounding organic-rich forest soil and vegetation. Overall, landcover change from forested to agriculture lowers DOC concentrations and changes from forested to agriculture or urban increases autochthonous, and presumably more biolabile, DOM contributions with ramifications for stream biogeochemical cycling.

The rapid urbanization and industrialization along with the expansion of cities in developing countries like Bangladesh converting vegetation and bare land into built-up area that remarkably boost up the land surface temperature (LST). This study has been conducted for correlating and monitoring the changes of landuse–landcover change (LULC) and LST of rapidly expanding Chittagong metropolitan area from 1989 to 2018 utilizing four Landsat satellite images (TM, ETM+, OLI, and TIRS). The Present study combines the techniques of remote sensing and geographic information system (GIS) to find out the spatial variation of LST and identify its relationship with LULC. Supervised classification technique has been employed in ERDAS IMAGINE 14.0 software to retrieve LULC data. The images of the study area were categorized into four different classes namely vegetation, urban structures, bared lands and water bodies. LSTs were estimated using the single thermal infrared band of Landsat TM, ETM+, and the band 10 and 11 of the TIRS sensor’s image for the split-window algorithm method. Concerning the relationship between LULC and LST, it has been found that vegetation and water bodies shows lowest LST while bared lands and urban structures indicates highest LST. LULC analysis shows a dramatic increase in urban structures (from 20.83 to 58.93%), decrease in vegetation (from 56.54 to 20.24%) and bared lands (from 16.67 to 11.90%) and a further small increase in water bodies after the 80s, because of digging new ponds. LST in the study area has been increasing as high-temperature LU types have increased and low temperature LU types have decreased. Consequently, the mean annual temperature showed 6.5 °C increase, the minimum and maximum LST increased by 9 °C and 4 °C throughout the study period. The highest maximum and lowest minimum LST has found 40°C during the years of 2010 to 2018 and 15 °C in the year of 1989, respectively. The study will assist the decision-maker to understand the impacts of unplanned urbanization for future city planning and urban management.

This study undertook an assessment of 24 physiochemical parameters at over 1094 sites to compute the water quality index (WQI) across the upper and central Punjab regions of Pakistan. Prior to the WQI calculation, an analytical hierarchy process (AHP) was employed to assign specific weights to each water quality parameter. The categorization of WQI into distinct classes was achieved by constructing a pairwise matrix based on their relative importance utilizing Saaty’s scale. Additionally, the groundwater quality status for irrigation and drinking purposes across various zones in the study area was delineated through the integration of WQI and geostatistical methodologies. The findings revealed discernible heavy metal issues in the Lahore division, with emerging microbiological contamination across the entire study region, potentially attributed to untreated industrial effluent discharge and inadequately managed sewerage systems. The computed indices for the Lahore, Sargodha, and Rawalpindi divisions fell within the marginal to unfit categories, indicating water quality concerns. In contrast, the indices for other divisions were in the medium class, suggesting suitability for drinking purposes. Scenario analysis for developing mitigation strategies indicated that primary treatment before wastewater disposal could rehabilitate 9% of the study area, followed by secondary (35%) and tertiary (41%) treatments. Microbiological contamination (27%) emerged as the predominant challenge for water supply agencies. Given the current trajectory of water quality deterioration, access to potable water is poised to become a significant public concern. Consequently, government agencies are urged to implement appropriate measures to enhance overall groundwater quality for sustainable development.

Ecosystems provide a wide range of services crucial for human well-being and decision-making processes at various levels. This study analyzed the major land cover types of north-central Ethiopia and their impact on total and per-capita ecosystem service value (ESV). The ESV was estimated using the benefit-transfer method along the established global and local coefficient values for the periods 1973, 1986, 2001, 2016, and 2024. The findings show that agricultural lands continued to expand at a rate of 563.4 ha year −1 , at the expense of forests and grasslands. As a result, the total ESV of the study area declined from $101.4 to $61.03 million and $60.08–$43.69 million, respectively. The ESV per capita was also diminished by $152.4 (37.7%) and $257 (40.6%), respectively. However, land-cover improvement during the period 2001–2016 enhanced the total and per capita ESV in the study area. Therefore, potential future research may be required to develop a valid approach for assessing the robustness and sensitivity of value coefficients for the valuation of the ESV at the landscape level.

Cities are spatially expanding rapidly, leading to urban sprawl. This study aims to understand the nature of the urban expansion of Chennai city, located on India’s southeastern coast, by determining the urban growth pattern and identifying the urban sprawl areas. The urban growth pattern and sprawl areas between 1998 and 2019 are identified using remote sensing data through the delineation of the Urban Core Boundary (UCB). The urban areas were extracted from the Land Use Land Cover (LULC) classification using combined classification technique to delineate the UCB. All the findings were validated using ground truth information. LULC classification performed with an accuracy of more than 90 % for urban land cover revealed an increase in urban cover by 71.77% from 1998 to 2009 and 36.91 % from 2009 to 2019. The delineated UCB’s peripheral distance was measured from the city centre in an anticlockwise direction from 0˚ to 360˚ at every 10˚ interval. It is observed that the urban core boundary expanded to a maximum of 16.02 km along 240˚ and 11.93 km along 220˚ from the city centre, and the lands in the vicinity of the National Highway (NH 32), which is situated between these sectors, experienced maximum urban development. The study also pinpointed the sprawl areas during the study period, revealing that the urban sprawl occurs along the highways, around designated special economic zones, and industrial corridors.