Clean-soil Air Water最新文献

Surface water quality assessment is very important to establish a proper water quality surveillance database for better water resources management. This study was conducted to investigate the surface water quality status of Kalpani stream in District Mardan, northern Pakistan. For this purpose, various physicochemical and biological parameters were assessed during summer and winter seasons, like pH, turbidity, total dissolved solids (TDS), electrical conductivity (EC), chloride, calcium, total hardness, sulfate, nitrate, and E. coli bacteria. In addition, multivariate statistical analyses were performed, including one-way ANOVA, correlation matrix, and principal component analysis. Results revealed that lowest pH recorded in winter was 6.6 in the SP1 sampling point, and the highest was 8.2 in SP3, which showed alkaline characteristics throughout the study period at all three sites in both seasons. Water quality was relatively turbid in winter with a 2.02 NTU in SP1, possibly due to low water flow rate as compared to the summer. Also, NO₃⁻ and SO₄²⁻ concentrations were high during winter, recorded at 74.49 and 105.15 mg/L at SP3, respectively as compared to summer. Dilution could be one of reasons for such variations during winter and summer. The E. coli ranges 240–2000 and 73–2450 CFU/100 mL during winter and summer seasons, respectively at SP3 demonstrated enormous microbial contamination from untreated sewage and agriculture runoff. The correlation matrix revealed various physicochemical parameter pairs during winter with positive correlations, and during summer a negative correlation. Findings suggested that proper surface water quality monitoring strategies and sewage treatment measures must be established.

Converting saline water into freshwater using renewable energy resources is crucial to address global shortages of freshwater. This study aims to investigate the freshwater productivity of a single-slope solar still (SSS) operating with solar energy, one of the renewable energy sources. The main motivation of this study is to evaluate the experimental, theoretical, and economic performance of the solar still under climate conditions that have not been sufficiently studied before. Experimental analyses were conducted under the climatic conditions of Tunceli, a city located in the Eastern Anatolia Region of Türkiye. In addition, a comprehensive theoretical analysis was carried out using energy equations, and the experimental and theoretical results were compared with each other. Finally, the economic feasibility of the system was evaluated through a cost analysis. The SSS's experimental and theoretical productivity were found to be 1883.9 and 2458.7 g/m²/day, respectively. The experimental thermal efficiency for this still was 15.1%, whereas the theoretical thermal efficiency was 19.7%. It was concluded that the theoretical productivity and efficiency values were close to the experimental values and the difference between them originated from the assumptions of theoretical calculations. The cost of water distilled by the single-slope solar distillation unit was found to be $0.077/kg, and the payback period was found to be 9 months.

A random sample of soil from Famagusta, Cyprus, was used in the study to examine the effects of treated and untreated irrigation wastewater on the physicochemical parameters of the soil. Soil samples of various textures (sand, clay, and silt) were collected at a depth of 20 cm and mixed with treated (TWW) and untreated wastewater (UWW). Parameters, such as trace metals, pH, electrical conductivity (EC), cations, and anions, were analyzed for all samples. Pollution indices, such as geo-accumulation index (I_geo), enrichment factor (EF), and metal contamination index (MCI), were utilized to assess the level of soil pollution caused by irrigation wastewater. The results reveal that TWW and UWW were higher in trace metals than the background sample, whereas the results of pollution indices indicate geo-I_geo revealed the order Cu > Zn > Ni > Cr > Ti as heavily contaminated (3 < I_geo4) for Cu (UWW–SC), and EF shows a descending order of metal as Cu < Zn < Ni < Ti. For factor analysis, Al, Ti, Mn, Ni, Cu, Cr, and Zn had a higher factor loading (>0.5), implying that the concentration of the elements during wastewater treatment significantly affects quality, characteristics, and variability of the soils. The K-means cluster showed final cluster centers with Zn having the highest mean clusters of 0.41 and 2.02 for clusters 1 and 2, respectively. The result also indicated that there were positive (direct) and negative (inverse) relationships from covariance analysis. According to the study, reusing treated or untreated municipal wastewater for agricultural irrigation unquestionably improves the qualities of soil as a medium for the growth of living things.

The accurate apportionment of pollution sources is crucial for effective river water quality management. In this study, we analyzed the water quality status of Qingyi River and identified and quantified potential sources affecting water quality changes. Although the APCS-MLR model is widely used for source apportionment, its high sensitivity to outliers and reliance on linear assumptions limit its accuracy in rivers with unstable water quality dynamics, often resulting in a high proportion of unidentified sources. To address this gap, this study introduces an approach that integrates the feature importance of random forest (RF) to optimize the APCS-MLR model, enhancing its ability to capture nonlinear relationships, handle outliers, and improve source quantification. This approach was applied to the Qingyi River, which has good overall water quality but exhibits spatial variability and instability in some parameters. The results demonstrated the validity of our method: the coefficient of determination (R²) of the optimized model increased from 0.617 to 0.695, indicating a superior goodness-of-fit. Concurrently, the average contribution rate of unidentified sources decreased from 38.54% to 16.97%, confirming the model's enhanced ability to resolve pollution sources. The final apportionment ranked the sources as industrial sewage (48.73%), natural factors (17.69%), unidentified sources (16.97%), agricultural runoff (10.06%), and landfill leachate (6.55%). These findings provide a more reliable basis for crafting targeted protection strategies for the Qingyi River. Meanwhile, this study offers a novel and insightful methodology for advancing source apportionment techniques in the field of water environment research.

In this study, bituminous coal was activated with sulfuric acid (H₂SO₄) under relatively low temperatures (30°C–60°C), yielding an adsorbent material referred to as chemically activated carbon (CAC). Additionally, another adsorbent material, referred to as physically activated carbon (PAC), was prepared from the same coal through steam activation at 800°C. The physicochemical properties of both adsorbents were examined using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR) and Brunauer–Emmett–Teller (BET) analysis. The results showed that H₂SO₄ activation at low temperature did not markedly increase surface area but significantly changed pore structures and surface functional groups. Although CAC exhibited a lower surface area than PAC, its phenol adsorption performance was notably high. In batch adsorption experiments, the removal efficiencies of bituminous coal, CAC and PAC were 7%, 80.3%, and 99.2%, respectively. FT-IR analysis indicated that hydrogen bonds between phenol molecules and surface functional groups were effective in the adsorption. Kinetic studies revealed that phenol adsorption onto CAC followed a pseudo-second-order kinetic model, implying that adsorption rate is controlled by chemical interaction between phenol molecules and active sites on the CAC surface, rather than mass transfer or diffusion. Moreover, CAC was reusable and maintained over 88% phenol removal efficiency up to the third cycle. Overall, low temperature acid activation procedure can be considered an energy-efficient method for developing an adsorbent that provides high phenol removal from bituminous coal and can be a practical alternative to conventional high temperature steam activation. However, further optimization is required to match the performance of physical activation.

Heavy metal contamination in soil is a global environmental issue with serious ecological and human health implications. This research article focuses on assessing the extent and risk of heavy metal contamination in soils surrounding three major cement factories: ACC (Barmana), UltraTech (Baga), and Ambuja (Darlaghat), located in the industrially active districts of Bilaspur and Solan in Himachal Pradesh, India. The primary aim of this study was to quantify concentrations of selected heavy metals, including iron, chromium, cobalt, copper, lead, arsenic, manganese, cadmium, mercury, nickel, and zinc; identify their spatial distribution; and evaluate associated ecological risks. Soil samples (n = 34) were collected from multiple directions (North, East, South, and West) and distances (3, 6, and 12 km) around each factory and analyzed, using inductively coupled plasma optical emission spectroscopy (ICP-OES). This study uniquely integrates the Contamination Factor (C_f), Geoaccumulation Index (I_geo), and Potential Ecological Risk Index (RI) for a comprehensive evaluation. The results reveal alarming levels of cadmium (Cd) and mercury (Hg), with peak concentrations of 17.2 and 99.7 mg/kg, respectively, followed by Cr, As, and Ni, significantly exceeding permissible limits. These findings highlight localized pollution hotspots and the role of cement manufacturing emissions and raw material usage as major contributors. This study underscores the urgent need for pollution mitigation strategies and provides valuable insights for policymakers, environmental managers, and public health stakeholders in protecting soil resources and community well-being.