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Extensive attention device capability strain along with sticking in order to prophylaxis suggestions.
(3) The cooling effects of UGS in daytime SUHI were highly dependent on the background climate (cold > temperate > arid). (4) The nighttime SUHI could be effectively offset when UGSFs were greater than 0.48, 0.82, 0.97, 0.95 in NAAC, NAGL, YZ, and UQ. This article highlights the different feedback of urban green space to UHII and supports green infrastructure intervention as an effective means of reducing urban heat stress at urban agglomeration scales.Environmental molecular markers can be used to understand the sources, transport, and fate of pollutants. Furthermore, they can also be applied to assess the influences of anthropogenic activities and elucidate urbanization from different perspectives. In this study, the potential of linear alkylbenzenes (LABs) and polycyclic aromatic hydrocarbons (PAHs) as chemical indicators of urbanization was examined first. Overall, the concentrations of LABs and PAHs ranged from 5.49-148 ng/g (mean 15.6, median 9.33) and 3.61-4878 ng/g (mean 181, median 71.3), respectively. Owing to the different sources and input methods of these two substances in soil, the area-weighted median values for LABs were more suitable to assess the magnitude of contamination on the administrative scale. For PAHs, the average values were more practical. LAB (consumption-induced pollutants) and PAH (production-induced pollutants) concentrations exhibited good correlations with some indices for residential daily life and industrialization, which indicated that soil can be utilized to reveal multidimensional urbanization-environment relationships. Two different patterns, the inverted U-shaped pattern and the upward pattern, were employed to simulate the environment-urbanization relationships in Shenzhen, China, which indicated that raising the standard of living or industrialization had created different soil pollution. The environmental quality demand was more difficult to meet by changing the energy structure than by improving infrastructure.Accurate prediction of any type of natural hazard is a challenging task. Of all the various hazards, drought prediction is challenging as it lacks a universal definition and is getting adverse with climate change impacting drought events both spatially and temporally. The problem becomes more complex as drought occurrence is dependent on a multitude of factors ranging from hydro-meteorological to climatic variables. A paradigm shift happened in this field when it was found that the inclusion of climatic variables in the data-driven prediction model improves the accuracy. However, this understanding has been primarily using statistical metrics used to measure the model accuracy. The present work tries to explore this finding using an explainable artificial intelligence (XAI) model. The explainable deep learning model development and comparative analysis were performed using known understandings drawn from physical-based models. The work also tries to explore how the model achieves specific results at different spatio-temporal intervals, enabling us to understand the local interactions among the predictors for different drought conditions and drought periods. The drought index used in the study is Standard Precipitation Index (SPI) at 12 month scales applied for five different regions in New South Wales, Australia, with the explainable algorithm being SHapley Additive exPlanations (SHAP). The conclusions drawn from SHAP plots depict the importance of climatic variables at a monthly scale and varying ranges of annual scale. We observe that the results obtained from SHAP align with the physical model interpretations, thus suggesting the need to add climatic variables as predictors in the prediction model.The growing social awareness of environmental protection entails that the assumptions of the sustainable development idea are being implemented in various economic sectors at an increasingly fast pace. One of them is the power industry, the sustainable development of which is now becoming a priority in economic policy for many countries. The paper refers to this issue by developing methodology for both studying and assessing the level of sustainable energy development in the Central and Eastern European Countries. The study involved 21 indicators characterizing the sustainable energy development of these countries in the areas of energy, environmental, economic, and social security for 2008 and 2018. When considering the complexity of the subject matter and the wide scope of the research, four methods of multi-criteria data analysis (TOPSIS, VIKOR, MOORA and COPRAS) were used. For each of them, based on the adopted criteria, synthetic indicators were determined, which allowed for the assessment of the level of sustainable energy development in the CEE countries. Weights for the adopted indicators were identified based on the Shanon's Entropy method. Afterwards, an unambiguous assessment of the level of sustainable energy development of the CEE countries was performed. The results showed that in 2008 and 2018, the best ranking position was held by Latvia and Croatia, and the worst ranking position was held by Poland and Bulgaria. The method of multidimensional scaling made it possible to determine the positions of studied countries on scatter plots in two-dimensional space, which showed differences between individual CEE countries. All in all, the applied methods allowed for a considerably broad assessment of the level of sustainable energy development of the CEE countries.This study examines the spectral properties and source characteristics of absorbing aerosols (BC Black Carbon; BrC Brown Carbon, based on aethalometer measurements) in the urban background of Athens during December 2016-February 2017. Using common assumptions regarding the spectral dependence of absorption due to BC (AAEBC = 1) and biomass burning (AAEbb = 2), and calculating an optimal AAEff value for the dataset (1.18), the total spectral absorption was decomposed into five components, corresponding to absorption of BC and BrC from fossil-fuel (ff) combustion and biomass burning (bb), and to secondary BrC estimated using the BC-tracer minimum R-squared (MRS) method. Substantial differences in the contribution of various components to the total absorption were found between day and night, due to differences in emissions and meteorological dynamics, while BrC and biomass burning aerosols presented higher contributions at shorter wavelengths. At 370 nm, the absorption due to BCff contributed 36.3% on average, ant implications for radiative transfer models.Data on long-chain chlorinated paraffins (LCCPs) is extremely sparse, despite their use and emission are increasing with the phasing out of short-chain chlorinated paraffins (SCCPs). In this study, we analyzed chlorinated paraffins (CPs) in foodstuff samples (551 pooled samples, 93 items) divided into eight categories collected from Jinan, Shandong Province of China, by atmospheric-pressure chemical ionization quadrupole time-of-flight mass spectrometry (APCI-qToF-MS), to investigate the occurrence, contamination patterns and homologue patterns of LCCPs in foodstuff commonly consumed in traditional Chinese diet. Inflammation inhibitor LCCP intake through diet was estimated as well. LCCPs were detected in all pooled samples with geometric mean (GM) concentrations ranging from 1.8 to 21.9 ng/g wet weight (ng/g ww), contributing to 9-28% of the total CP mass in the studied foodstuff categories. The contamination patterns of LCCPs differed from SCCPs and medium-chain chlorinated paraffins (MCCPs), as reflected by the patterns of mass distribution, and by the lack of correlations between LCCP and S/MCCP concentrations in various foodstuff categories. The homologue profiles of LCCPs were extremely complex and diverse, with frequent detection of C30-36Cl2-15 very-long-chain chlorinated paraffin (vLCCP) congeners. The homologue profiles of eggs stood out for their high abundance of C18-22Cl9-13 LCCP congeners. LCCPs contributed 6.0-25.2% (8.9% for median estimation) to the estimated dietary intake (EDI) for total CPs through diet based on estimations using different percentiles of CP concentrations. The median estimate of dietary LCCP intake for adults in Jinan was 287.9 ng/kg_bw/day, reaching ~10- to 100-fold of that in Sweden and Canada. Considering the continuing production, use and emission of LCCPs, as well as the similar toxicity effects induced by LCCPs as SCCPs and MCCPs, attention should be paid to the health risk posed by LCCPs, or all CPs as a class of contaminants.The diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection requires the detection of viral RNA by reverse transcription-polymerase chain reaction (RT-qPCR) performed mainly using nasopharyngeal swabs. However, this procedure requires separate analysis per each individual, performed in advanced centralized laboratory facilities with specialized medical personnel. In this study, an alternative approach termed "solid waste-based surveillance (SWBS)" was explored, in order to investigate SARS-CoV-2 infection in small communities through the indirect sampling of saliva left on waste. Sampling was performed at 20 different sites in Italy during the second peak of COVID-19. Three swabs were positive for SARS-CoV-2 using a published RT-qPCR protocol targeting the non-structural protein 14 region, and the viral load ranged 4.8 × 103-4.0 × 106 genome copies/swab. Amino acid substitutions already reported in SARS-CoV-2 sequences circulating in Italy (A222V and P521S) were detected in two positive samples. These findings confirmed the effectiveness of SWBS for non-invasive and dynamic SARS-CoV-2 surveillance.Marine pollution is an increasingly dangerous problem, affecting people across the world. Japan's decision on 13 April 2021 to discharge nuclear wastewater into the sea has aroused the close attention of interest-related countries. To resolve conflicts among various countries and achieve the harmonious development of the marine and economic environment, we employ the static game, the rank-dependent expected utility (RDEU) game, and the sequential game to comprehensively analyze the equilibrium strategies of discharge country and interest-related countries under different situations. Our analysis reveals that in the static game and sequential game where interest-related countries make decisions first, the discharge behavior of the discharge country should be restricted from the perspective of the internal and external benefits of the discharge country. In addition, when integrating changes in emotion into the game, it can be found that the most expected emotional state to prevent the discharge country from discharging nuclear wastewater for interest-related countries is to remain pessimistic. Overall, this study provides important implications for inter-state relations and environmental protection.Coal gasification coarse slag (CGCS) is solid waste generated during coal gasification. The mainly treatment method of CGCS is storage and landfill, which causes severe environmental pollution and waste of land resources. Sodium silicate can be synthesized using CGCS after impurities are removed for the high content of amorphous silica. In this work, a novel method of acid activation depolymerization-dilute alkali dissociation is proposed to synthesize high-modulus, low-impurity sodium silicate using CGCS under mild conditions. In the acid activation depolymerization process, the content of impurities such as CaO and Fe2O3 can be reduced from over 30% to below 3%. SiO2 composition can be enriched from 35.75% to 60.60%. The SiOAl bond is broken, the coordination structures of Q4(2Al) and Q4(3Al) are depolymerized, and the reactive Q4(0Al) and Q3(0Al) coordination structures of amorphous silica are formed. Numerous defects appear in the aluminosilicate structure, exposing a large number of active SiOH bonds. Efficient desilicated ratio is increased from 7.
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