Similar, albeit weaker, impact was detected in the benzene and toluene concentrations. Sources outside the study area are responsible for most of the CO, PM1 and PM2.5 concentrations but during winter nights, characterised by strong atmospheric stability and low turbulence, their concentrations are elevated due to the local emissions. We developed a diagnostic statistical nonlinear model for the pollutant concentrations, which points to a stronger association of the atmospheric stability with the concentrations during stable conditions but turbulence dominating during convective conditions. Our findings explain the relatively low overall concentrations of locally emitted pollutants in the study area but warn of the potential for high concentrations during night-time in locations with comparable meteorological conditions.Climate change is a worldwide reality with significant effects on hydrological processes. It has already produce alterations in streamflow regime and is expected to continue in the future. To counteract the climate change impact, a better understanding of its effects is necessary. Hydrological models in combination with Indicators of Hydrologic Alteration (IHA) suppose an up-to-date approach to analyze in detail the impacts of climate change on rivers. In this study, the Soil and Water Assessment Tool (SWAT) model and Indicators of Hydrologic Alteration in Rivers (IAHRIS) software were successfully applied in Aracthos River basin, an agricultural watershed located in the north-western area of Greece. JQ1 Statistical indices showed an acceptable performance of the SWAT model in both calibration (R2 = 0.74, NSE = 0.54, PBIAS = 17.06%) and validation (R2 = 0.64, NSE = 0.36, PBIAS = 12.31%) periods on a daily basis. To assess the future hydrologic alteration due to climate change in Aracthos River basin, five Global Climate Models (GFDL-ESM2, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM and NorESM1-M) were selected and analyzed under two different emission scenarios (RCP 4.5 and RCP 8.5) for a long-term period (2070-2099). Results indicate that precipitation and flow is expected to be reduced and maximum and minimum temperature to be increased, compared to the historical period (1970-1999). IHA, obtained from IAHRIS software, revealed that flow regime can undergo a severe alteration, mainly on droughts that are expected to be more significant and longer. All these future hydrologic alterations could have negative consequences on the Aracthos River and its surroundings. The increase of droughts duration in combination with the reduction of flows and the alteration of seasonality can affect the resilience of riverine species and it can produce the loss of hydraulic and environmental diversity. Therefore, this study provides a useful tool for decision makers to develop strategies against the impact of climate change.Soil respiration is the largest carbon (C) flux from terrestrial ecosystems into the atmosphere. Accurate estimates of the magnitude and distribution of soil respiration are critically important to models of global C cycling and predictions of future climate change. One of the greatest challenges to accurate large-scale estimation of soil respiration is its great spatial heterogeneity at the site level. Our study explored how soil respiration varies in space and the drivers that lead to this variance in a natural subtropical evergreen broadleaf forest in Southern China. We conducted a two-year soil respiration measurement for 168 randomly selected sampling points in a 4 ha plot. We measured the spatial variance of soil respiration and tested its correlation to a variety of abiotic and biotic factors including topography, aboveground plant community structure, soil environmental factors, soil organic matter, and microbial community structure. We found that soil respiration was highly varied across the study plot, with a spatial variation coefficient (CV) of 32.75%. The structural equation modeling (SEM) analysis showed that elevation influenced tree species diversity, productivity, and soil water content, which in turn affected soil respiration via soil C content, clay content, fungalbacterial ratio, annual litterfall, and fine root biomass. 31% of the total spatial variation of soil respiration was accounted for in the SEM, mostly by elevation, soil C content, annual litterfall biomass, tree species diversity as estimated by the Simpson's index, and soil water content, with standardized total effects of 0.31, -0.31, 0.29, 0.19, and -0.18, respectively. Our data demonstrated that soil respiration was highly spatially varied at the fine scale, and was primarily regulated by factors of topography and plant community structure. More studies investigating the spatial variation of soil respiration are therefore needed to better understand and assess terrestrial ecosystem C cycling.The release of contaminants of emerging concern (CECs) into water bodies has aroused wide concern in recent years. Little information on the characteristics of CECs to pose potential risks even at low concentrations in urban water systems of Shanghai is available. This study investigated the occurrence and spatial distribution in source water, as well as the fates by drinking water treatment processes for organic compounds including 35 pesticides, 17 antibiotics, 7 microcystins (MCs), and 10 disinfection by-products (DBPs). The similar trends across seasons for COD and TOC, the indicators for organic pollutants, indicated that the water qualities in three targeted reservoirs were relatively stable. COD in the R3 reservoir inlet was 1.3-2.4 times greater than that in the R1 and R2 reservoirs, possibly resulting from the inflow of the Taipu River as a tributary. Pesticides, particularly methamidophos and metabolites, macrolide and sulfonamide antibiotics, particularly roxithromycin, were frequently detected in Shanghai source water inlets. Pesticide concentrations were 2.58-3.66 μg/L much higher than antibiotics (8.6-47.6 ng/L). The results showed that MCs (ng/L) and DBPs (haloacetic acids, HAAs μg/L; N-nitrosodimethylamine, NDMA ng/L) were found to be in low detection frequencies. It was found that 51.1-74.6% of organic matters in source water were composed of molecular weight (MW) less then 1 kDa. The removal rates for the part of MW less then 1 kDa were only 11.7-12.3% through the conventional treatment processes, compared with higher removal rates of 23.5-28.5% by advanced treatment processes. Pesticides, antibiotics and MCs can be significantly removed by six drinking water treatment plants.