During the Kharif season of 2022-2023 at Lovely Professional University, Jalandhar, Punjab, a field experiment was conducted to investigate the “Effect of soil and foliar application of humic acid and brassinolide on morpho-physiological and yield parameters of Black gram (Vigna mungo).” The experiment was designed using a Randomised Block Design (RBD) with three replications and eight treatments. Compared to the other treatments, RDF + humic acid 0.1% + brassinolide 0.1ppm (foliar application) was the optimal treatment for most morphological and yield parameters. Plant height (cm), number of primary branches per plant, number of secondary branches per plant, dry matter accumulation (g), chlorophyll Index (SPAD), and leaf area (cm2) were highest under T7- RDF + humic acid 0.1%+brassinolide 0.1ppm (foliar applied) conditions. Minimum phenological observations were recorded for soil and foliar applications of brassinolide, including days to first flowering, days to 50 percent flowering, and days to pod initiation. Number of pods /plant, pod length(cm), pod weight (g), no. of seeds /pod, test weight (g), seed yield (q/ha), stover yield (q/ha), and harvest index (%) were significantly influenced by the T7 and recorded higher values. The increased seed yield may be attributable to plants treated with growth regulators remaining physiologically more active to accumulate sufficient food reserves for developing blossoms and seeds.

This study aims to analyze the association between the share of agriculture in GDP and changes in climatic variables, notably per capita CO2 emissions and temperature change, using time series data of India, Bangladesh, and Nepal for the period 1961-2018. The ARDL bounds testing method was applied to analyze the relationships among the research variables for both short-term and long-term. The results revealed that in the long run, per capita CO2 emissions and temperature change have no statistically significant relationship with India and Nepal’s share of agriculture in GDP. However, temperature change has demonstrated a positive and statistically significant relationship with the share of agriculture in Bangladesh’s GDP. Temperature change has a significant and adverse impact on the share of agriculture in India’s GDP in the short run, whereas CO2 has no significant effect. In the short run, CO2 shows a positive and significant connection with the share of agriculture in Bangladesh’s GDP. Still, temperature change is negatively and significantly associated with the proportion of agriculture in the nation’s GDP. Different lag values of both CO2 and temperature change have significant relationships with the share of GDP in agriculture in the short run in Nepal. As agriculture is a key source of GDP for all three countries, it is vital to implement suitable policies and make plans and strategies to mitigate climate change’s harmful consequences in agriculture.

This study aims to determine how vulnerable groundwater in Khartoum is to contamination. For this purpose, the DRASTIC Index idea was used. A descriptive cross-sectional analytical analysis is designed in this study. A total of 279 boreholes were sampled from a total of 1015 boreholes (27.5 percent). The following criteria were utilized to define the DRASTIC Index: depth, net recharge, aquifer media, soil texture, terrain, video media, and soil conductivity. Standard bacteriological test methodologies were used for groundwater. The biological data from the 279 boreholes revealed that total coliform, thermo-tolerant coliform, and E. coli were found in 34.4 percent, 18.6 percent, and 0.36 percent of the boreholes, respectively. Bacteriological contamination is common in Sharge Elnile, although only a few cases have been reported in Khartoum. According to the study, the bulk of boreholes in Khartoum State were built without any criteria. Many sources of contamination were discovered within a radius of less than 120 meters, which was deemed to violate Khartoum State’s Environmental Health Law of 2002. For this reason, bacteriological contamination is common in Sharge Elnile, although only a few cases have been reported in Khartoum.

It is extremely difficult to clean up accidental oil spills in water since conventional oil sorbents absorb much more water in addition to the oil. Alternatively, cleanup techniques might lead to secondary contamination. This study examines and measures the oil absorption capacities of two hydrophobic natural fibers: water hyacinth (Eichhornia crassipes) and lotus (Nelumbo nucifera). At the laboratory scale, the absorption of engine oil, vegetable oil, and diesel oils onto various dry biomass materials, including water hyacinth and lotus with different particle sizes (BSS-44, BSS-60, BSS-100, BSS-120, BSS-160, and BSS-200), was investigated. Water hyacinth shows a higher absorption efficiency for all samples as compared to the lotus.

Leather manufacturing processes raw hides and skins into various finished leather products, generating huge amounts of untanned and untanned leather solid wastes (LSWs). The present study investigates the LSWs generation, characterization, and management practices of the Sheba leather industry in Ethiopia. Results revealed that LSWs are categorized as non-chrome solid waste, including de-dusted salt, raw trimming, hairs, fleshing waste, pickle trimming, and splitting wastes. Chrome-based wastes include chrome shaving waste, crust leather trimming waste, buffing dust waste, finished leather trimming waste, etc. Further, solid wastes were characterized for the physico-chemical parameters viz. moisture (31.5%), ash content (7.3%), pH (5.7), carbon content (14.7%), nitrogen content (0.3%), chromium content (2%), calorific value (20,107 kJ.kg-1), VOCs (75.1%) and carbon to nitrogen ratio (52:1). Results obtained suggested various sustainable technological options for the effective LSWs management to preserve environment.

This first-of-its-kind study systematically assesses the abundance and characteristics of Microplastics (MPs) in different categories of informal open drains (nallas) carrying different liquid waste streams from different functional areas of an Indian city. Such drains are part of the informal urban drainage system that carries wastewater, stormwater, industrial effluent, and rural runoff. Logistical and locational limitations of traditional wastewater (WW) sampling methods severely limit their application in open drains. To overcome sampling challenges owing to complex geography, vast drainage network spread across different functional areas of the entire city, and local challenges, appropriately modified sampling strategies were adopted to collect samples from 35 open WW drains (small/local, intermediatory, and large). MPs (50μm-5mm) were present in a bucket, and net samples obtained from all 35 WW drains. The average MP concentration in WW drains was 4.20 ± 1.40 particles/L (bucket samples) and 5.19 ± 1.32 particles/L (net samples). A declining trend of MPs abundance was observed from larger to smaller drains, confirming that smaller and intermediatory drains (carrying WW from different functional areas of the city) are discharging their MP loads into larger drains. Intermixing different WW streams (municipal WW, stormwater surface runoff, agricultural runoff, and industrial WW) increases MP levels in drains. The local riverine ecosystem is being put at risk by a daily MPs load of 12.6 x 108 particles discharged from 9 larger drains into the local river Kharun. To protect the riverine ecosystem, controlling the high daily MPs load from such drains is important. Diversion of WW drains through constructed wetlands built near river banks can be a cost-effective solution. Because the entire Indian subcontinent and parts of Africa rely mainly on such drains having similar characteristics and local conditions, the findings of this study reflect the status and pattern of MPs pollution in informal drains of the entire Indian subcontinent and can be used by stakeholders and governments to take mitigative and preventive measures to manage the MPs pollution and protect the local riverine ecosystem.

We develop an economic model to derive the conditions under which individuals will invest in human capital and move on to adopt sustainable technology instead of natural resource-intensive technology. For this purpose, we extend the overlapping generation model developed by Ikefuji & Horii as our analytical framework. Unlike Ikefuji & Horii who developed an overlapping generation model (OLG) in the context of local pollution, the authors adopted it in the context of renewable natural resources. To do this, we have introduced the production sector that relies on natural resource-intensive technology. This research extends beyond the Ikefuji & Horii model by assuming that an individual derives utility by investing in his child’s education apart from utility derived from consumption when young and adult. Human capital accumulation enables individuals to participate in human capital-intensive production, which produces output through sustainable production technology. As the main result of our theoretical analysis, we find that more educated individual is less dependent on the natural resource endowment for earning their income. We also find that sustainable consumption growth requires that individuals assign a certain positive weight to investment in their child’s education. A long-run steady-state equilibrium level of human capital accumulation is higher and higher than the weight assigned by the parents to the child’s education. In this overlapping generation’s economy, sustainable consumption growth requires that individuals assign a certain weight or give some importance to human capital accumulation. This follows from the fact that the long-run steady-state value of the income earned by an individual depends positively on the expenditure on education.

This research was conducted in the waters of Malili River, East Luwu Regency, with 4 observation points in Malili River East Luwu Regency, namely: (a) Southeast Sulawesi Sub Das (Point 1) namely Pongkeru village bridge, Coordinate point 12126.69’8°” E; (b) Larona Sub Das Karebbe basin bridge (Point 2), Coordinate point 12115.09’9°” E; (c) The meeting point of Larona sub-dash and Pongkeru sub-dash (Point 3), coordinate point 12159.64’8°” E; (d) Upper Malili River, Malili village, Malili bridge (Point 4), Coordinate point 12147.20’5°” E. Metal concentration and distribution were analyzed descriptively with the help of images (maps), graphs, and tables. Differences in Pb, Cd, and Hg metal concentrations in sediments between point locations were tested using analysis of variance (ANOVA) through the SPSS version 22 program. The relation between grain size, organic matter, and Pb, Cd, and Hg metal concentrations was tested using linear correlation. The results showed that the sediment content of Pb and Cd metal concentrations at each point location did not exceed NOAA (1999) quality standards. In the sediment, Hg metal concentration exceeds the quality standards of NOAA (1999) at each point, namely point 1. Pongkeru 0.590 μg.g-1, point 2. Karebbe 0.229 μg.g-1, point 3. Kawasule 0.514 μg.g-1 and point 4. Malili 0.358 μg.g-1. The relation between sediment size and Pb, Cd, and Hg metal concentrations at each point location has a weak correlation. The relation does not significantly affect the content of heavy metals in the sediment. It may be due to other factors, such as the source of heavy metal pollutants in each different point location. The relation between organic matter and the concentration of Pb, Cd, and Hg metals at each point location has a weak correlation. The relation does not significantly affect the content of heavy metals in the sediment because it may be due to other factors, such as different sources of heavy metal pollutants in each point location.

Lipases are utilized in biodiesel production utilizing various types of substrates. The use of lipase in bioenergy production aims to reduce energy crises and environmental pollution. Lipase-producing indigenous bacteria Bacillus licheniformis (Accession no. OP56979) and Bacillus rugosus (Accession no. OP56980) were isolated from various oil-contaminated sites. The isolated potential lipolytic bacteria were screened for maximum lipase production. Then, the bacteria showing the highest lipolytic activity were subjected to identification using the 16s rRNA technique while other isolated were identified biochemically. Lipase [LipBL-WII(c)] from Bacillus licheniformis having the highest lipolytic activity expressed various characteristics. Characterization of crude LipBL-WII(c) expressed that it showed stability in a wide range of pH (4 to 10) with optimum lipolytic activity observed at pH 8. It was then found to be active at a temperature range from 20°C to 80°C with optimal at 50°C. Lipase activity was also stimulated in metal ions such as Ca+1, Mg2+, and Zn2+ the most. Furthermore, LipBL-WII(c) retained lipolytic activity in the presence of various organic solvents and surfactants. The kinetic parameters (Km and Vmax) for LipBL-WII(c) were ascertained using Lineweaver- Burk plot. LipBL-WII(c) showed a potential for biodiesel production using olive oil as a source. Lipase gave 84% yield of biodiesel production from olive oil. Thus, it could be employed as a potential candidate for green biodiesel production using oil sources.

In this study, waste tires were used to develop activated carbon for the adsorption of Cr(VI) from aqueous solutions, and an artificial neural network (ANN) model was applied to predict the adsorption efficiency of waste-tire activated carbon (WTAC). SEM and FTIR were used to characterize the developed WTAC. A three-layer ANN with different training algorithms and hidden layers with different numbers of neurons was developed using 79 data sets gathered from batch adsorption experiments with different initial Cr(VI) ion concentrations, contact periods, temperatures, and doses. Conjugate gradient backpropagation of Powell-Beale restarts (traincgb) was found to be the best training algorithm among all the training algorithms, with an RMSE of 5.894 and an R2 of 0.985. The ANN topology had 4, 8, and 4 neurons in the input, hidden, and output layers. The correlation coefficient of the ANN models of Cr(VI) ion adsorption efficiency is 0.977.