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.

Fixed air quality monitoring stations generally monitor the air quality in developing countries. However, this practice, in addition to being costly, inherently contains drawbacks associated with the inability to capture the spatial distribution of air pollutants. Against this limitation, it is necessary to employ flexible and dynamic monitoring techniques that are fundamental and influential in comprehending the spatial distribution of pollutants. Because of this, in recent times, the application of GIS as a monitoring technique has proved to be more efficient than using fixed monitoring stations. Therefore, to this end, the current study mapped the spatial distribution of PM10 and NO2 pollutants in Cape Town CBD using the GIS technique. Subsequently, the GIS monitoring technique revealed that both pollutants had high spatial distribution between 2017 and 2018, irrespective of the season. Furthermore, high exposure concentrations of PM10 were generally observed across the CBD in contrast to NO2 exposure levels, which were relatively low. To contextualize the findings, compared with other studies, the current research discovered that spatial distribution of air pollution is associated with meteorological conditions, such as wind speed and temperature, that traditional techniques of monitoring exposure can’t capture.

Current research explains the comparison of linear and nonlinear regression methods for finding the optimal isotherm study using experimental data for the adsorption of BG on multi-walled carbon nanotubes MWCNTs. BG dye maximum adsorption onto MWCNTs occurred at pH 2 and 35°C, with the apparent equilibrium reached after 15 min. In this study, five error functions were used: ERRS, Hybrid, Chi-square (χ2), ARE, and EABS. The values of error functions suggest that the Langmuir Linear type 3 is a suitable isotherm to describe the adsorption of BG on MWCNTs. The results showed that the Langmuir isotherm is a fit good isotherm to describe the adsorption process. The coefficient of non-determination (K2) showed Hybrid, and ERRS were the preferable error functions used to predict the fit of linear and nonlinear isotherm models. Compared with other studies, MWCNTs can be used as a low-cost adsorbent with low contact time for the removal of BG dye from an aqueous solution.

This article is a systematic review of the decarbonization of the building sector in Morocco. It explores the different approaches and technologies used to reduce greenhouse gas emissions and achieve decarbonization targets in this sector. The article examines the policies and regulations in place in Morocco to encourage decarbonization of the building sector, as well as the initiatives taken by key actors to reduce carbon emissions in their buildings. It also reviews sustainable building technologies and renewable energy systems currently used in the country. The systematic review concludes that while Morocco has put in place policies and regulations to encourage the decarbonization of the building sector, there is still much to be done to achieve the ambitious decarbonization targets set by the country. The authors of the article recommend greater investment in sustainable building technologies and renewable energies, as well as increased collaboration between public and private sector actors to accelerate the transition to low-carbon buildings.

Regional geochemical mapping was carried out in Bilaspur and Korba Districts of Chhattisgarh, and stream sediments/slope wash, soil, and water samples were analyzed for concentration of heavy metals. The study contributes to understanding heavy metals contamination of sediments, soils, and water due to anthropogenic activity, mainly in agriculture-based rural areas. The study reveals that high geochemical anomalies observed for heavy metals like Ni, Cr, As, and Zn in sediments and soil samples are due to the extensive uses of phosphatic fertilizer and soil amendments in the form of poultry and swine manure. Water quality assessment of major streams in the study areas shows that the water is suitable for domestic and agricultural uses. Correlation analysis reveals that the chemical weathering of rock-forming minerals doesn’t control the surface water chemistry of the study area and is also an anthropogenic source of sodium in water. This study also shows the importance of the country’s geochemical mapping database, which will have much broader applications than conventional mineral exploration and geological mapping.

The impact of global warming is climate change which affects elements of society. This condition causes a decrease in the level of community welfare and increases the level of community vulnerability. Some climate change impacts are floods, droughts, landslides, and shoreline changes. In this study, we will focus on landslides. Landslides are among the most dangerous natural disasters that often occur in mountainous areas, especially during the rainy season. Various factors influence events involving landslides. This study aims to utilize GIS to identify landslide-prone areas in Padang. The method used in this study is the Zuidam and Concelado criteria overlay method for the level of landslide hazard and the broken method (jenks). The natural break (jenks) classification method reduces within-class variation and maximizes between-class variation. This study shows that the level of landslide vulnerability in Padang City is low, with a total area of 288854.38173 ha with a percentage of 42.21%. We need to consider more factors and experiment with training and validating data in more detail to gain insight into the physical contributions of the factors to landslide occurrences.

ABS was the first surfactant used in detergent formulations, but because its molecular structure is branched, it is difficult to decompose biologically, making ABS a toxic compound for the environment. This study aims to remove MBAS surfactant, using a combination of phytoremediation and filtration methods to remove surfactant (MBAS) Chemical Oxygen Demand (COD) from detergent wastewater by optimizing operating factors such as pH, contact time, plant type, and filter media. Water lettuce (Pistia stratiotes) and water hyacinth (Eichhornia crassipes) were selected as plant species and silica-activated carbon was used as filter media. Water lettuce and hyacinth were grown in a 10-liter reactor with detergent wastewater samples for 6 and 12 days. Filter media are placed in the reactor in use, and aeration is done. The efficiency for reducing COD was 81.73%, and the efficiency for surfactant was 99.42% for each experiment, which was thought to be because of plant adsorption and filtering processes. The water lettuce (Pistia stratiotes) plant had the maximum adsorption capability for all the qualities evaluated, with a surfactant content in the roots of 27543.24 (mg/kg MBAS), compared to the water hyacinth plant, which only absorbed 2597.95 (mg/kg MBAS).

In this study, three promising yeast isolates were isolated from the sap of the Indian date palm tree (Phoenix sylvestris) and characterized by biochemical tests and 18S rRNA gene sequencing. They were confirmed as Saccharomyces cerevisiae and were designated as strains PYS-1, PYS-2, and PYS-3. These confirmed strains were used for the preparation of bioinoculants. Bioinoculant was prepared and applied to wheat crops, and the effect of Bioinoculant. Statistical analysis is carried out using analysis of variance (ANOVA), and it is found that the absorbance of chlorophyll, protein, and Indole Acetic Acid (IAA) content is significantly increased. The treatment of bioinoculant showed that crops significantly increased chlorophyll, protein, and IAA content. Further, we applied bioinoculant on the soil and measured the soil’s humus content before and after the treatment of bioinoculant. Then, a paired t-test was applied to check the effectiveness of the treatment, and it was found to significantly increase humus content in the soil. The use of bioinoculants is an economically feasible and eco-friendly method.

This study investigated the water quality and the organic pollution level of rivers in Cotabato City, specifically the Rio Grande de Mindanao, Matampay, Esteros, and Tamontaka rivers. The physicochemical characteristics of water in these rivers were determined in the laboratory, and the level of organic pollution was determined using Palmer’s algal pollution index. Water quality assessment showed that the dissolved oxygen (DO) in Matampay River and the biological oxygen demand (BOD) in Esteros River exceed the minimum standard set by the Department of Environment and Natural Resources (DENR) for water quality in class C rivers. Results also showed that there were thirty (30) algal genera belonging to twelve (12) classes were observed in Cotabato City rivers. Algal genera belonging to Chlorophyceae and Bacillariophyceae were found to be the most abundant in these rivers. Using Palmer’s algal pollution index, the Rio Grande de Mindanao showed a probability of high organic pollution, while the rest of the rivers indicated a lack of organic pollution. For a more thorough assessment of the Cotabato City rivers, it is advisable to consider more comprehensive measures, such as extending the sampling duration and expanding the number of sampling stations.

Countries all over the world are paying attention to the growth of the new energy vehicle industry and implementing various subsidy policies to stimulate industry development to enhance the new energy vehicle industry’s innovative capability. This study uses a network DEA model to analyze China’s new energy vehicle industry’s technological innovation capability, decomposing it into two stages: technology development and innovation transformation, and calculating the innovation capability level of China’s new energy vehicle industry from 2012 to 2017. The findings show that due to a disconnect between the efficiency of the technology development stage and the efficiency of the innovation transformation stage, innovation technology cannot serve business operations, resulting in China’s new energy vehicle industry’s overall low level of innovation capability. Based on this, an IT3SLS analysis of the factors influencing innovation capability and phase-by-phase efficiency reveals that while China’s new energy vehicle industry’s subsidy policy has historically failed to significantly improve innovation capability, there is a complementary/substitution effect between labor input, corporate capital, and government subsidies. Based on the findings of this study, important policy recommendations are made to further develop the technological capabilities of the new energy vehicle industry in the context of China’s present new energy policy.