The emission factors (EFs) and source profiles of polycyclic aromatic hydrocarbons (PAHs) in particulate matter (PM10 and PM2.5) from the prebaked anode industry were studied to fill the knowledge gap and provide data for emission inventory and source resolution. In 2018, three prebaked anode plants were selected in Central China, each having one calcining chimney as well as one baking chimney, and then 92 samples were collected from the stack gas of the six chimneys. The results of the study are as follows. (1) PM10 and PM2.5 from the prebaked anode industry contained 37-42% water-soluble ions, 16-20% elements, 11-17% organic carbon, and 9.2-14% elemental carbon. (2) The EFs for PAHs of PM10 and PM2.5 were 1146.1 ± 899.7 and 866.2 ± 1179.8 mg/(t aluminum produced), respectively. The EF for BaP was seven times lower than that given by the European Environment Agency (EEA), whereas those of BbF, BkF, and IcdP were 2-13 times higher than those given by the EEA. (3) Seven diagnostic ratios for PAHs, including Ant/(Ant+Phe), Flua/(Flua+Pyr), BaA/(BaA + Chr), IcdP/(IcdP+BghiP), Flu/(Flu+Pyr), Phe/Ant and BaA/Chr were discussed. Just by diagnostic ratio, it is hard to precisely distinguish between calcining and baking in prebaked industry. (4) The toxic equivalence of PMs in the baking stack gas in the prebaked anode industry was five times higher than that in the calcining stack gas, and PM2.5 showed higher potential toxicity risk than PM10. V.Grasslands across the world are being degraded due to the impacts of overgrazing and climate change. However, the influences of grassland degradation on carbon (C), nitrogen (N), and phosphorus (P) dynamics and stoichiometry in soil ecosystems are not well studied, especially at high elevations where ongoing climate change is most pronounced. Ecological stoichiometry facilitates understanding the biogeochemical cycles of multiple elements by studying their balance in ecological systems. This study sought to assess the responses of these soil elements to grassland degradation in the Qinghai Lake watershed on the Qinghai-Tibet Plateau (QTP), which has an average elevation of >4000 m and is experiencing serious grassland degradation due to its sensitivity and vulnerability to external disturbances. Substituting space for time, we quantified normalized difference vegetation index to gauge grassland degradation. C, N, and P concentrations and their molar ratios in soil and in soil microbial biomass were also measured. The results showed that grassland degradation decreased the concentrations of C and N, as well as the ratios of CP and NP in soil. The soil became relatively more P rich and thus N limitation is anticipated to be more apparent with grassland degradation. Moreover, C, N, and P concentrations in soil microbial biomass decreased with increased grassland degradation. CNP ratios of soil microbial biomass were highly constrained, suggesting that soil microorganisms exhibited a strong homeostatic behavior, while the variations of microbial biomass CNP ratios suggest changes in microbial activities and community structure. Overall, our study revealed that grassland degradation differentially affects soil C, N, and P, leading to decreased CN and NP in soil, as well as decreased C, N, and P concentrations in soil microbial biomass. This study provides insights from a stoichiometric perspective into microbial and biogeochemical responses of grassland ecosystems as they undergo degradation on the QTP. The paper focuses on analysis of long-term changes of aerosol optical depth (AOD) over Iran. It describes contributions of dominant aerosol in the aerosol load over Iran covering the period 1980-2018. For this purpose, a long-term AOD dataset from the reanalysis-based Modern Era Retrospective Analysis for Research and Applications (MERRA-2), the satellite-based Moderate Resolution Imaging Spectroradiometer (the new version of MODIS/Terra and Aqua) as well as a new AOD product (MERRA-2 MODIS merged) were used. The ground-based AOD measurements of the five Aerosol Robotic Network (AERONET) sites used for validation demonstrated better consistency of the MERRA-2 MODIS merged (MMM) product. Analysis of these datasets demonstrated high AOD in the southwest of Iran because of the proximity to the major source areas of natural mineral dust in spring and summer. In contrast, low AOD was mostly observed along the high elevation lands in the northern and western highlands.  https://www.selleckchem.com/products/ve-822.html  The trend analysis of AODs revealed differences between the AOD datasets, but agree on the positive trends over southwestern Iran and negative trend in northern Iran. Classification of major aerosol types indicated that the clean marine and mixed aerosols were the dominant aerosol types during the cold and hot seasons, respectively, and the increase of desert dust around 2010 was another obvious result in spring and summer. Our results indicate that the variation in dust aerosol has a key role in determining the AOD long-term changes in Iran which has contributed in regional climate change and environmental evolutions. V.Excess nitrate in drinking water is a human health concern, especially for young children. Public drinking water systems in violation of the 10 mg nitrate-N/L maximum contaminant level (MCL) must be reported in EPA's Safe Drinking Water Information System (SDWIS). We used SDWIS data with random forest modeling to examine the drivers of nitrate violations across the conterminous U.S. and to predict where public water systems are at risk of exceeding the nitrate MCL. As explanatory variables, we used land cover, nitrogen inputs, soil/hydrogeology, and climate variables. While we looked at the role of nitrate treatment in separate analyses, we did not include treatment as a factor in the final models, due to incomplete information in SDWIS. For groundwater (GW) systems, a classification model correctly classified 79% of catchments in violation and a regression model explained 43% of the variation in nitrate concentrations above the MCL. The most important variables in the GW classification model were % cropland, protect drinking water.