Heavy metals are discharged into the soil around us from various anthropogenic sources and also by the use of fertilizers, pesticides, pharmaceuticals, etc. In most cases, industrialization can be pointed to as the reason behind soil pollution. Contamination of soil leads to large-scale environmental degradation and health impacts. Many investigators have studied techniques for removing heavy metals from soil. Soil washing is an emerging area that can be implemented for this purpose. Studies were carried out in the controlled conditions of a laboratory environment to determine the suitability of soil-washing techniques for removing lead from polluted land. The results showing the influence of various parameters in soil washing, such as duration of washing, molar strength of the solution used, the weight ratio of soil to wash solution, etc., are presented in this paper. Batch studies were conducted to investigate the performance of chelating agents such as Na2EDTA, HCl, HNO3 and CaCl2 with regard to the removal of lead from artificially contaminated locally available soil. Based on the batch studies, it is observed that the strength of the washing solution, the proportion of soil and solution, the period of agitation, etc. influence the removal of contaminants. Based on the studies, it is concluded that, while recommending soil washing using chelating agents for remediating lead-contaminated soils, it is essential to identify the influencing parameters and determine the optimum conditions so that higher removal can be achieved without any adverse effect.

Based on the sand volume and sedimentation volume data for different particle size (PS) groups, the relationship between the annual scouring and silting amount of the Juliu River-Liujianfang section and the yearly sediment volume entering the downstream river channel was established. The critical values of sediment storage and release for the downstream river channel were obtained. It was found to decrease with an increase in the sediment particle size. The correlation coefficient between the annual scouring and silting amount of the Juliu River-Liujianfang section and the annual sediment volume entering the downstream river channel increased with the coarsening of sediment PS. It indicated that the sediment size was proportional to the sediment amount (SA) entering the river channel. As the sediment size increased, the deposition amount increased due to the variation of unit sediment amount. Based on the treatment and achievement of source areas with sediment sizes larger than 0.05 mm, it is significant to concentrate on treatment areas with sediment sizes larger than 0.10 mm.

This study seeks to understand the socio-economic and ecological impacts of the hydroelectric power projects along the upper basin of the river Teesta in Sikkim. This study estimates the non-market benefits of restoring the Teesta riverine ecosystem and evaluates the transferability of welfare estimates. This study is a first of its kind undertaken in the Teesta basin which uses a unique dataset of 830 households obtained from the affected regions of the river basin. During the study, nine villages adjacent to the river Teesta, dams, and powerhouses were identified and surveyed. Double bounded dichotomous choice questions were used to elicit willingness to pay (WTP). Both the logistic and normal distribution models were fitted and the results were mostly similar. The median WTP was INR 373.00 and the variables that described the rating on dams, ownership of property, monthly expenditure of the household, informal employment status, and satisfaction about the state of the river Teesta were among the significant variables in the model. The benefit function value transfer estimated was INR 232.00 with the percentage transfer error (PTE) of 61.9%.

Due to anthropogenic activities and the advancement of industries, metal contamination is growing globally. Aluminum toxicity is seriously endangering plants, animals, and humans by rapidly rising in soil and water. Even though some fungi can tolerate aluminum, researchers are interested in finding bacteria that are resistant to aluminum. The current state of knowledge on bacteria resistant to aluminum is extremely limited. In the present study, bacterial isolates from soil near a metal electroplating and automobile industry in Punjab, India, were isolated and then screened for high aluminum metal tolerance. The aluminum tolerant bacterial isolate was identified as Cedecea davisae M1, a member of the Enterobacteriaceae family, using morphological, biochemical, and 16srRNA gene sequence analyses. The spectroscopic results indicate that the strain may tolerate up to 150 ppm of aluminum. Antibiotic resistance of Cedecea davisae M1 was determined using disks on Luria agar plates, and the bacteria were found to be resistant to vancomycin, ampicillin, carbenicillin, and rifampicin. The findings of the study indicated that the strain might be able to remove aluminum toxicity from the environment, which needs to be further explored.

The water resource is an important guarantee of social and economic sustainable development. The improvement of water’s ecological carbon sequestration ability is a direct response to the goal of “double carbon”. Water quality directly affects its carbon sequestration capacity. So it is necessary to understand the water quality of rivers. In view of the fuzziness and uncertainty in water quality evaluation, this paper uses the cloud model to realize the qualitative to quantitative transformation of water quality in Wenyu River. By combining moment estimation theory with critic weight, AHM weight, and variable weight theory. A water quality evaluation method integrating a variable weight cloud model is constructed. And the temporal and spatial changes in water quality in Wenyu River are studied. The results show that the combined weights balance the influence of each index while retaining the advantages of subjective and objective weights. The results of the water quality evaluation are consistent with the practice, which verifies the feasibility and applicability of the method.

As China’s natural resource governance has turned to high-quality management, establishing reasonable and ecological land-use patterns is an effective means of promoting natural resource utilization and improving the quality of the ecological environment. Therefore, this study used ecological land as the expansion source to construct an ecological land-use pattern with the minimum cumulative resistance model in Haixing County, China, based on regional food security, ecological security, and construction land expansion patterns. This work also involved designing ecological corridors, radiation channels, strategic nodes, and other ecological components. The results demonstrate that (1) the ecological land source is 7976.93 hm2, accounting for 9.19% of the total area. It is mainly distributed in the southeast of the county, mainly in the river system and woodland; (2) the food security situation of Haixing County can be divided into four zones, most of which are agricultural adjustment areas, indicating that the ecological security of cultivated land in this area needs to be improved; (3) the ecological security level of Haixing County is divided into four areas, and the ideal safety zone accounts for the smallest area, indicating that the regional ecological situation is very unstable; (4) construction land expansion zone is divided into four parts. A suitable construction zone occupies the largest area and is mainly distributed around the current construction land; (5) the expansion of the ecological land-use pattern of Haixing County includes four zones, 15 ecological corridors, 12 radiation channels, and 35 strategic nodes, which is conducive to optimal land allocation from an ecological security perspective. This paper puts forward some suggestions for ecological protection and intensive urban development.

The area around Qinghai Lake is one of the most serious desertification areas on the Qinghai-Tibet Plateau. In this paper, combined with field investigation and indoor analysis, the classification and grading system of desertification around Qinghai Lake was established. On this basis, through remote sensing data processing and parameter inversion, the desertification monitoring index model was established. Based on the analysis of Landsat-5/TM remote sensing data from 1990 to 2020, the dynamic change characteristics of desertification land around Qinghai Lake in recent 30 years were obtained. The results show that the desertification area around Qinghai Lake was 1,359.62 km2, of which the light desertification land was the main one. The desertification spread in a belt around Qinghai Lake, concentrated in Ketu sandy area in the east, Ganzi River sandy area in the northeast, Bird Island sandy area in the northwest, and Langmashe sandy area in the southeast. From 1990 to 2000, the annual expansion rate of desertification around Qinghai Lake was 2.68%, the desertification spread rapidly, and light desertification land was the main part of desertification expansion. From 2000 to 2010, the annual expansion rate of desertification was only 0.83%, but severe desertification land and moderate desertification land developed more rapidly than in the previous period. From 2010 to 2020, the annual expansion rate of desertification was 2.66%, and the desertification was spreading rapidly, mainly with moderate desertification land and light desertification land. In the process of desertification land transfer around Qinghai Lake, the transfer of desertification land and non-desertification land was the main, accompanied by the mutual transformation of different levels of desertification land. The process of desertification around Qinghai Lake was essentially the result of natural and human factors. The special geographical location, climate changes, rodent damage, and human factors around Qinghai Lake were the main causes of desertification.

The characterization of non-point source pollution at the watershed scale difficult owing to its distributed nature combined with the lack of suitable measurements for validation. This study proposes the classification of land within a Mediterranean watershed according to its potential source of non-point pollution, considering interannual precipitation variability and dam regulation effects. For this purpose, the potential non-point pollution index (PNPI) developed by the Italian Environmental Protection Agency was modified to include annual local precipitation behavior, named local annual PNPI (APNPI). PNPI and APNPI were computed for the Guadalquivir River (Spain), which has a drainage surface of 57,500 km2 and is highly regulated by >60 reservoirs. The results reflect the vulnerability along the Guadalquivir River in terms of the spatially variable non-point pollutant nature of its contributing watersheds. The annual average nitrate concentration values on the southern side exceeded the average value on the northern side by almost five times and showed a statistically significant power fit with the PNPI, with an R2 of 0.65. Long-term available nitrate data (1981/82–2006/07) on a monthly scale at the outlets of some watersheds allowed us to rank priority pollutant source areas within the watershed. The power fits between the annual average nitrate loads and the APNPI (R2 = 0.51–0.99) were statistically significant, which validated the utility of adding the variability of precipitation at an annual scale as a dynamic factor in the index. The APNPI can constitute a simple dynamic classification index for assessing the relative risk of non-point source pollution across a large area, especially in data-scarce situations.

Recently, environment pollution around the globe has increased because of anthropogenic activities. As part of the biota, plants can assimilate the compounds present in air, water and soil and respond to changes in surround conditions, for that, they can be used as bioindicators of global pollution. However, urban plants' ability to monitor organic pollutants in air, soil, and water have not been profoundly studied yet. Anthropogenic contamination produced by five different types of pollutants [polycyclic aromatic hydrocarbons (PAHs), pharmaceuticals and personal care products (PPCPs), perfluoroalkyl substances (PFASs), pesticides and organophosphorus flame retardants (OPFRs)] has been studied in Riyadh and Abha areas (Saudi Arabia). In addition to the points in both cities, a control point located in the Asir National Park (close to Abha), which is little affected by human activity, was used. The 5 groups of contaminants were found with different but high detection frequencies from 85 % to 100 % in wild and ruderal plants. PAHs were detected in all the analyzed samples at the highest average sum of concentrations (ΣPAHs) 1486 ng·g−1 dry weight (d.w.). Statistically significant differences were obtained between Riyadh, Abha and the point located in the national park (p < 0.05). ΣPAHS in Riyadh >> ΣPAHs in Abha > ΣPAHs in the National Park. Values of the average sum of concentrations for the other groups of contaminants ΣPPCPs, ΣPFASs, Σpesticides and ΣOPFRs were 420.5, 171, 48 and 47 ng g−1 d.w., respectively. High values of PPCPs are due to the presence of salicylic acid. Differences in the average sum of each type of contaminant concentrations between cities were not statistically significant. The results of this assessment of wild and ruderal plants as bioindicators for 5 types of organic contaminants suggest that they can be used to monitor anthropogenic contaminants in the terrestrial environment.