Fast-growing plant, giant reed (Arundo donax L.) has been gaining a lot of popularity in the phytoremediation of metal-polluted soils.  https://www.selleckchem.com/products/odq.html  However, information regarding the physiological background of tolerance and accumulation capacity of A. donax with respect to antimony (Sb), arsenic (As), and their co-contamination are very limited. Rooted stem cuttings were grown for 5 months in hydroponics exposed to Sb (10 mg L-1), As (10 mg L-1), and their combined toxicity (Sb 5 mg L-1 + As 5 mg L-1) wherein treatment without As/Sb served as control. Effect of these treatments on key photosynthetic parameters (rate of net photosynthesis, effective quantum yield of photosystem II, chlorophyll fluorescence, and photosynthetic pigments), phytoextraction ability of metalloids, nutrient uptake, root growth, and lignification were analyzed. Arsenic-containing treatments severely affected root morphology of A. donax compared to Sb/control and plants exposed to As showed intensive lignification already in young apical part of te the efficiency of phytoremediation when using this fast-growing and high biomass-producing plant species.Redesigning a supply chain network is an important strategic problem which affects network productivity, especially in varying environments. We propose a novel mathematical model for redesigning the network of a real company considering economic and social aspects. Strategic decisions of the model consist of opening new centers, selecting capacities from a set of discrete sizes, and closing or expanding capacities of existing centers during a planning horizon. Tactical decisions are involved with determination of product flows, facilities allocation, selection of fleet modes in terms of product types (i.e., frozen, chilled, dry, and ready meal) and fleet ownership types (i.e., self-owned or leased). The correlations and restrictions involved with multi-product supply chains, such as substitutability of products, the impossibility of transportation of some products together because of chemical effects or legal restrictions, and necessity of allocation of special fleets to some products because of specific holding conditions, are considered. Noting social responsibility aspect, an objective of this model is to minimize the maximum unsatisfied demand of added food banks to the network whose roles are feeding needy people. An interactive fuzzy programming approach is applied to solve the given bi-objective problem. Finally, useful managerial insights are derived from the results which show that more geographical diversity of facilities, using a new distribution strategy, and adding food banks as a new echelon can increase the productivity of the given network and makes it more responsible in terms of social responsibility.The viral RNA of SARS-Coronavirus-2 is known to be contaminating municipal wastewater. We aimed to assess if COVID-19 disease is spreading through wastewater. We studied the amount of viral RNA in raw sewage and the efficiency of the sewage treatment to remove the virus. Sewage water was collected before and after the activated sludge process three times during summer 2020 from three different sewage treatment plants. The sewage treatment was efficient in removing SARS-CoV-2 viral RNA. Each sewage treatment plant gathered wastewater from one hospital, of which COVID-19 admissions were used to describe the level of disease occurrence in the area. The presence of SARS-CoV-2 viral RNA-specific target genes (N1, N2, and E) was confirmed using RT-qPCR analysis. However, hospital admission did not correlate significantly with viral RNA. Moreover, viral RNA loads were relatively low, suggesting that sewage might preserve viral RNA in a hot climate only for a short time.In this work, hydrothermal leaching was applied to simulated soils (clay minerals vermiculite, montmorillonite, and kaolinite) and actual soils (Terunuma, Japan) to generate organic acids with the objective to develop an additive-free screening method for determination of Sr in soil. Stable strontium (SrCl2) was adsorbed onto soils for the study, and ten organic acids (citric, L(+)-tartaric, succinic, oxalic, pyruvic, formic, glycolic, lactic, acetic, and propionic) were evaluated for leaching Sr from simulated soils under hydrothermal conditions (120 °C to 200 °C) at concentrations up to 0.3 M. For strontium-adsorbed vermiculite (Sr-V), 0.1 M citric acid was found to be effective for leaching Sr at 150 °C and 1 h treatment time. Based on these results, the formation of organic acids from organic matter in Terunuma soil was studied. Hydrothermal treatment of Terunuma soil produced a maximum amount of organic acids at 200 °C and 0.5 h reaction time. To confirm the possibility for leaching of Sr from Terunuma soil, strontium-adsorbed Terunuma soil (Sr-S) was studied. For Sr-S, hydrothermal treatment at 200 °C for 0.5 h reaction time allowed 40% of the Sr to be leached at room temperature, thus demonstrating an additive-free method for screening of Sr in soil. The additive-free hydrothermal leaching method avoids calcination of solids in the first step of chemical analysis and has application to both routine monitoring of metals in soils and to emergency situations.Poverty eradication and environmental degradation are the two crucial challenges, and they are highly interlinked in the modern era. However, countries are still more emphasized in attaining poverty alleviation and alleviating environmental pollution which require enormous attention. Our study is a novel attempt to scrutinize the effect of poverty on carbon dioxide (CO2) emissions for India and China over the sample period 1987-2019. Findings attained from the ARDL model suggest that a rise in poverty contributes to growing CO2 emissions in India only in short run. Further, findings show that poverty is the principal source of pollution in the long term in India and China. Empirical results proposed focal policy implications in the light of sustainable development goals for India and China.Greenhouse gases are the major issues globally leading to climate change and increased pollution of the atmosphere. CO2 emissions have divergent effect to the environment that also causes the economic performance of any country. The main motive of this analysis was to expose the influence of CO2 emission on population growth, fossil fuel energy consumption, economic progress, and energy usage in Nepal by using time series data ranging from 1971 to 2019, and data stationarity was checked with the help of unit root tests. An autoregressive distributed lag (ARDL) method with cointegration test was employed to adjudicate the variable dynamics with short- and long-run evidence. Furthermore, variable causality was tested through the Granger causality test. Study findings show that during long-run analysis that fossil fuel energy consumption and energy utilization has constructive affinity with carbon dioxide emission that exposed the p-values (0.0000) and (0.1065) correspondingly, while population growth and economic progress uncovered an inimical relation to CO2 emission.