Air quality has recently been a huge concern as it directly affects people’s lives. An air quality level assessment and prediction system is essential to keep track of air quality. Therefore, developing an efficient air quality assessment and prediction system has become one of the most important concerns. In the present work air quality level of Surat city, India is assessed and predicted for the period from 2020 to 2023 using the Autoregressive integrated moving average (ARIMA) model. Experimental results show that the ARIMA model outperforms the other models. According to the findings, the maximum quantity of SO2 and NO2 present in the air in 2020 is 37 mm and 18 mm, respectively, with a maximum of 27 mm and 31 mm in 2021. Thus, we can observe that even though SO2 has reduced a bit, the amount of NO2 has increased, thus degrading the quality of air.

The present study evaluated lead biosorption by Enterobacter cloacae WW1 isolated from tannery wastewaters under different initial Pb2+ concentrations, biomass concentrations, and contact times. The results showed that at an initial Pb2+ concentration of 80 mg.L-1, the optimal conditions for living cells were a biomass concentration of 7 g.L-1 and a contact time of 120 min. For non-living cells, biomass was a biomass concentration of 4 g.L-1 and contact time of 45 min, which provided removal efficiencies of 92.03 ± 0.10% and 99.51 ± 0.01%, respectively. The maximum biosorption capacity obtained for non-living cells using an initial Pb2+ concentration of 640 mg.L-1 was 76.65 ± 0.05 mg.g-1. The equilibrium data followed the Langmuir and Freundlich models for living cells, and the data for non-living cell biosorbents fit the Langmuir model. The biosorption kinetics for living and non-living cells fit well with a pseudo-second-order kinetic equation. SEM-EDX analysis clearly showed the morphology and presence of Pb2+ particles on non-living cell surfaces after biosorption. In addition, the results revealed that functional groups such as hydroxyl, amino, carboxyl, amide, and phosphate groups on the bacterial cell surface detected by FTIR were associated with the binding of Pb2+ ions. The results indicated that E. cloacae WW1, a lead-resistant bacterium, can be used as an alternative biosorbent for lead removal from wastewater.

Heating, Ventilating, and Air Conditioning (HVAC) is a system to condition indoor air by cooling or heating to achieve thermal comfort for a human being. The HVAC system operates based on the refrigeration cycle, where heat is dissipated from the condensing unit in the warm air arrangement. This represents an ironic foundation of heat that might be recovered for further schemes or applications. In this paper, experimental work was developed to validate the proposed heat recovery system using heated air released from the condenser unit of the HVAC system as a source for the air dryer for the drying rack. Four different output parameters are to be observed in this research: the dry-bulb temperature of the air exit from the condenser unit, the dry-bulb temperature of the air inflowing the dryer, and the drying time and the relative humidity of the air leaving the dryer. These experimental works were conducted using a domestic application of a 1.0 hp air conditioning (AC) system with R-22 refrigerant gas and based on the following factors: The three-variant mass of wet clothes, the three-stage of mechanical fan speed for releasing warm air from the condenser, and the effect of variable ambient or surrounding air dry-bulb temperature were studied. A physical prototype of the dryer was constructed for proof-of-concept purposes. The experimental output was then analyzed to obtain precision and accurate data. To determine the system behavior, a refrigeration cycle analysis was conducted. It has been shown that an AC system of 1.0 hp can cover wet clothes drying of weights 1950 g, 4255 g, and 6350 g at 55, 80, and 110 min with a constant air velocity of 0.34 m-3.s-1 in an ambient temperature of 33°C. The significant contribution of this research is the proposed heat-recovery-based air dryer system with the capability to increase the Coefficient of Performance (COP) of the AC unit from 2.36 to 2.70. Hence, the energy-saving was received using the heat-recovered-based air dryer instead of a commercial electric air dryer system that uses high power consumption from their heater element.

The goal of this study was to examine the water quality for drinking and domestic purposes in the Korba coalfield region of Chhattisgarh, India. The Korba Coalfield region has seen the collection of fifteen groundwater samples from different places. The content of eight metals was determined using ICP-MS instruments: aluminum (Al), barium (Ba), cadmium (Cd), iron (Fe), magnesium (Mn), lead (Pb), nickel (Ni), and zinc (Zn). Spatial distribution maps were produced using GIS software to make it simple to understand the groundwater’s quality. The groundwater samples were collected during the pre-monsoon season and the amount of Al, Ba, Cd, Fe, Mn, Pb, Ni, and Zn exceeded the ideal drinking water standards in a few sites. The elevated metal concentrations in the study region’s groundwater could be hazardous to the quality of water. The HPI value based on mean concentration was calculated to be 21.64, which is significantly lower than the reference pollutant index score of 100. The HPI calculation revealed that 73.33% of groundwater samples had low HPI values, 6.67% had medium HPI values, and the remaining 20% had high HPI values. The correlation between heavy metals and HPI was calculated; HPI is positively correlated with Fe (r > 0.9471), Pb (r > 0.9666), and Zn (r > 0.9634), indicating that these elements contribute significantly more to heavy metal concentration in the various samples examined than the other selected elements. The box plot seems to be a graphical representation of the outcomes of the different parameter concentrations which show the mean, maximum, and minimum metal values. The cluster analysis was performed and it was classified into two clusters. Cluster-1 comprises 14 members (93.33%) of the water samples examined and is distinguished by relatively low Ba (<700 μg.L-1), pH, TDS, Al, Fe, Cd, Mn, Pb, and Zn concentrations. Cluster-II is made up of 1 member (6.67%), which is primarily made up of groundwater samples (GW-10) taken in the KCF region, India. High values of HPI are found in the eastern portion of Chhattisgarh’s KCF region, reflecting the spatial distribution of metals. Heavy metal leaching from open-pit mining and transit routes was observed to have contaminated groundwater in the eastern section of the research region.

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.