Palsas and peat plateaus occur in various environmental conditions, but their driving environmental factors have not been examined across the Northern Hemisphere with harmonized datasets. Such comparisons can deepen our understanding of these landforms and their response to climate change. We conducted a comparative study between four regions: Hudson Bay, Iceland, Northern Fennoscandia, and Western Siberia by integrating landform observations and geospatial data into a MaxEnt model. Climate and hydrological conditions were identified as primary, yet regionally divergent, factors affecting palsa and peat plateau occurrence. Suitable conditions for these landforms entail specific temperature ranges (500-1500 thawing degree days, 500-4000 freezing degree days), around 300 mm of rainfall, and high soil moisture accumulation potential. Iceland's conditions, in particular, differ due to higher precipitation, a narrower temperature range, and the significance of soil organic carbon content. The annual thermal balance is a critical factor in understanding the occurrence of permafrost peatlands and should be considered when comparing different regions. We conclude that palsas and peat plateaus share similar topographic conditions but occupy varying soil conditions and climatic niches across the Northern Hemisphere. These findings have implications for understanding the climatic sensitivity of permafrost peatlands and identifying potential greenhouse gas emitters.

Environmental changes, such as climate warming and higher herbivory pressure, are altering the carbon balance of Arctic ecosystems; yet, how these drivers modify the carbon balance among different habitats remains uncertain. This hampers our ability to predict changes in the carbon sink strength of tundra ecosystems. We investigated how spring goose grubbing and summer warming-two key environmental-change drivers in the Arctic-alter CO2 fluxes in three tundra habitats varying in soil moisture and plant-community composition. In a full-factorial experiment in high-Arctic Svalbard, we simulated grubbing and warming over two years and determined summer net ecosystem exchange (NEE) alongside its components: gross ecosystem productivity (GEP) and ecosystem respiration (ER). After two years, we found net CO2 uptake to be suppressed by both drivers depending on habitat. CO2 uptake was reduced by warming in mesic habitats, by warming and grubbing in moist habitats, and by grubbing in wet habitats. In mesic habitats, warming stimulated ER (+75%) more than GEP (+30%), leading to a 7.5-fold increase in their CO2 source strength. In moist habitats, grubbing decreased GEP and ER by similar to 55%, while warming increased them by similar to 35%, with no changes in summer-long NEE. Nevertheless, grubbing offset peak summer CO2 uptake and warming led to a twofold increase in late summer CO2 source strength. In wet habitats, grubbing reduced GEP (-40%) more than ER (-30%), weakening their CO2 sink strength by 70%. One-year CO2-flux responses were similar to two-year responses, and the effect of simulated grubbing was consistent with that of natural grubbing. CO2-flux rates were positively related to aboveground net primary productivity and temperature. Net ecosystem CO2 uptake started occurring above similar to 70% soil moisture content, primarily due to a decline in ER. Herein, we reveal that key environmental-change drivers-goose grubbing by decreasing GEP more than ER and warming by enhancing ER more than GEP-consistently suppress net tundra CO2 uptake, although their relative strength differs among habitats. By identifying how and where grubbing and higher temperatures alter CO2 fluxes across the heterogeneous Arctic landscape, our results have implications for predicting the tundra carbon balance under increasing numbers of geese in a warmer Arctic.

The negative effects of PM2.5 concentration in urban development are becoming more and more prominent. Bernaola-Galvan Segmentation Algorithm (BGSA) and wavelet analysis are powerful tools for processing non-linear and non-stationary signals. First, we use BGSA that reveals there are 41 mutation points in the PM2.5 concentration in Guiyang. Then, we reveal the multi-scale evolution of PM2.5 concentration in Guiyang by wavelet analysis. In the first part, we performed one-dimensional continuous wavelet transform (CWT) on the eight monitoring points in the study area, and the results showed that they have obviously similar multi-scale evolution characteristics, with a high-energy and significant oscillation period of 190-512 days. Next, the wavelet transform coherence (WTC) reveals the mutual relationship between the PM2.5 concentration and the atmospheric pollutants and meteorological factors. PM2.5 concentration variation is closely linked to that of PM10 concentration. But, it is not to be ignored that the increase in the SO2 and NO2 concentrations will cause the PM2.5 concentration to rise on different scales. Lastly, the variation of the PM2.5 concentration can be better explained by the combination of multiple factors (2-4) using the multiple-wavelet coherence (MWC). Under the combination of the two factors, the average temperature (Avgtem) and relative humidity (ReH) have the highest AWC and PASC. In the case of the combination of four factors, CO-Avgtem-Wind-ReH plays the largest role in determining PM2.5 concentration.

Soil freeze-thaw cycles play a critical role in ecosystem, hydrological and biogeochemical processes, and climate. The Tibetan Plateau (TP) has the largest area of frozen soil that undergoes freeze-thaw cycles in the low-mid latitudes. Evidence suggests ongoing changes in seasonal freeze-thaw cycles during the past several decades on the TP. However, the status of diurnal freeze-thaw cycles (DFTC) of shallow soil and their response to climate change largely remain unknown. In this study, using in-situ observations, the latest reanalysis, machine learning, and physics-based modeling, we conducted a comprehensive assessment of the spatiotemporal variations of DFTC and their response to climate change in the upper Brahmaputra (UB) basin. About 24 +/- 8% of the basin is subjected to DFTC with a mean frequency of 87 +/- 55 days during 1980-2018. The area and frequency of DFTC show small long-term changes during 1980-2018. Air temperature impacts on the frequency of DFTC changes center mainly around the freezing point (0 degrees C). The spatial variations in the response of DFTC to air temperature can primarily be explained by three factors: precipitation (30.4%), snow depth (22.6%) and seasonal warming/cooling rates (14.9%). Both rainfall and snow events reduce diurnal fluctuations of soil temperature, subsequently reducing DFTC frequency, primarily by decreasing daytime temperature through evaporation-cooling and albedo-cooling effects, respectively. These results provide an in-depth understanding of diurnal soil freeze-thaw status and its response to climate change. Freeze-thaw transitions of terrestrial landscapes are a common phenomenon in cold regions. The seasonal and diurnal freeze-thaw cycles (DFTC) of shallow soil exhibit substantial differences in response to climate. Understanding of the spatiotemporal patterns of DFTC and their response to climate change remains limited over the Tibetan Plateau (TP), which is characterized by the largest areas of freeze-thaw terrain in the mid- and low-latitudes of the world. We found the frequency and area of DFTC show a slight increase trend in a significantly warming climate in upper Brahmaputra (UB) basin, the largest river basin of the TP. The variation of DFTC depends on climatic conditions, with soils near the freezing point (0 degrees C) being more susceptible to changes in DFTC. Precipitation, snow depth and seasonal warming/cooling rates are the top three factors influencing the response of DFTC to air temperature changes. Snowfall plays a more important role in the temporal variability of DFTC frequency than rainfall. The number of diurnal freeze-thaw cycles (DFTC) in shallow soil increase slightly during the period 1980-2018 in the upper Brahmaputra (UB) basin Air temperature effects on the changes in DFTC frequency center on the freezing point Snowfall plays a more important role in the temporal variability of DFTC than rainfall

Global warming has shown an Arctic amplification effect in recent decades, leading to pronounced changes in pan-Arctic soil surface temperature (SST). SST plays a direct role in energy exchange between soil and atmosphere and serves as an indicator of the land-atmosphere energy balance. Remote sensing land surface temperature (LST) data is able to indicate near-surface temperature, but influences from environment factors, such as vegetation and snow, can introduce biases between LST and SST. In this study, the importances of five environment factors (vegetation, snow, surface soil composition, topography, and solar radiation) to monthly mean SST estimation from MODIS LST in pan-Arctic were analyzed. Then a method for pan-Arctic monthly mean SST estimation from MODIS LST by incorporating these environment factors and monthly-based modeling based on random forest (RF) algorithm was proposed. The results reveal that all the selected environment factors contribute to monthly-based modeling, with vegetation exerting the greatest importance from May to October and snow in March and April. The root mean square error (RMSE) of pan-Arctic monthly SST estimated by the proposed method from 2003 to 2022 ranges from 0.89 to 1.88 degrees C, which is a 42.95---53.35 % reduction compared to the widely used season-based multivariate linear regression (MLR) models based solely on LST (RMSE between 1.56 and 4.03 degrees C). The accuracy is notably improved in areas with lower and no vegetation (grassy woodlands, grasslands, permanent wetlands, and barrens) in the cold season (September to the following April), and in higher vegetation (forests) areas in the warm season (May to August). The proposed method can contribute to producing high-precision monthly mean SST data from LST, estimating permafrost extent and active layer thickness, and understanding the land-atmosphere energy balance in pan-Arctic.

Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth's status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth's surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements.

Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought-induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi-day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short-term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability. This research explores how climate change could impact the water stress experienced by black spruce and tamarack trees in the western boreal forest of Canada. We focused on a key measure called tree water deficit to understand if the trees were under stress due to insufficient water. We examined how tree water deficit relates to environmental factors such as temperature, sunlight, and soil moisture. The findings revealed that, on a daily basis, factors like sunlight and temperature cause trees to release more water into the air. However, over longer periods (days to weeks), the amount of water in the soil becomes crucial, suggesting that trees might face water stress during dry spells. So, while trees could grow more on hotter, sunnier days, they could also experience water stress and reduced growth if the soil becomes too dry for an extended period. This study helps us grasp how various factors interact to influence tree water stress in the boreal forest, providing insights important for managing these ecosystems in a changing climate. A novel approach to determine environmental controls of tree water deficit across time scales with wavelet analysis and Granger causality Soil moisture emerges as a significant control of tree water deficit in boreal trees at longer scales (multi-days) Daily productivity gains with warming will be mitigated by decreased soil water availability in longer periods of tree water deficit

The current water environment carrying capacity assessment method has a single assessment index and does not constrain the scope of assessment. It is not possible to adaptively assess the water environment carrying capacity layer by layer. In order to solve this problem, in this paper. we propose an adaptive assessment method of urban water environment carrying capacity based on water quality target constraints. This method constructs a new evaluation index system for water environment carrying capacity, which takes water resources and environment, water pollution control, and economic carrying capacity as the criteria, and takes water quality status, pollution discharge, technology management. economic development, and social development as the constraint target layer, and takes the total wastewater discharge, industrial water consumption, and urbanization level as the constraint index layer. Two methods of structural entropy weight and mean square error decision are introduced to realize the adaptive joint weight assignment evaluation of the reference layer and the target layer. Through experimental analysis, the assessed area has a good water environment carrying capacity and foundation, and the overall water environment carrying capacity of the study area from 2016 to 2019 was on the rise.

Seasonally frozen ground (SFG) significantly contributes to global carbon sinks. Global warming and anthropogenic-induced disturbances threaten the carbon storage capacity of SFG. Challenges in evaluating the SFG carbon storage potential include the lack of understanding of the control mechanisms of soil organic carbon (SOC) variations and timely spatial estimates of SOC. In this study, we investigated SOC stocks in SFG in the Tibet Autonomous Region, China, in 2020 and 2021. We employed partial least squares structural equation modeling (PLS-SEM) to explore the effect of complex processes (interacting roles of climate, plant physiology and phenology, freeze-thaw cycle, soil environment, and C inputs) on SOC and mapped SOC stocks in the topmost 30 cm. We identified four causal pathways: (1) an indirect pathway representing the effect of climate on plant physiology and phenology through changes in freeze-thaw cycles and soil environment, (2) an indirect pathway representing the effect of climate on C inputs through changes in freeze-thaw cycles, soil environment and plant physiology and phenology, (3) an indirect pathway representing the effect of climate on freeze-thaw cycles, and (4) an indirect pathway representing the effect of climate on the soil environment through changes in freeze--thaw cycles. C inputs exerted the greatest control on SOC. The effect of these factors decreased with increasing soil depth. We used PLS-SEM to generate maps of SOC stocks in SFG at a 500 m resolution with a moderate accuracy. The estimated mean SOC stocks in the 0-30 cm layer reached 6.87 kg m(-2), with a 95% confidence interval ranging from 6.2 to 7.5 kg m(-2). Our results indicated that it is critical to consider the depth dependence of the direct and indirect effects of environmental factors when assessing the control mechanisms of SOC vari-ations. In this work, we also demonstrated that spatially explicit SOC estimates based on timely investigations are important for assessing C stocks against the background of considerable environmental changes across the Ti-betan Plateau.

Introduction: More than 16% of the total electricity used worldwide is met by hydropower, having local to regional environmental consequences. With positive indicators that energy is becoming more broadly available and sustainable, the world is moving closer to achieving Sustainable Development Goal 7 (SDG 7). Pakistan became the first nation to include the Sustainable Development Goals (SDGs) in its national development strategy.Methodology: The current study sought to investigate the structural limits of Environmental Impact Assessment (EIA) guidelines for hydropower development in Pakistan. The study included the document review of the EIA reports about hydropower projects in Pakistan, scientific questionnaires from decision-makers, and public consultation.Results and Discussion: The document evaluates that an adequate mechanism is available, and donors like the Asian Development Bank and World Bank observe the implementation process of EIA in Pakistan. However, a comprehensive analysis of the EIA system found several things that could be improved, not only in the institutional framework but also in actual implementation and practices. More than 20% of respondent decision-makers disagreed with the compliance of the current Institutional Framework with EIA guidelines, and 25% think that the existing guidelines followed in Pakistan are not aligned with international standards and practices for Hydropower in actual practice. EIA has a limited impact on decision-making due to insufficient technical and financial resources.Recommendations: There should be a think tank with experts who can meet the needs of present and future epochs. The public should be communicated with and educated about EIA. For better efficiency, the officers and decision-makers should be trained internationally, i.e., the Water and Power Development Authority (WAPDA).