This study assessed the hazard indicators of common chemical and organic fertilizers widely available in the markets of Najaf Governorate, Iraq. The concentrations of natural radionuclides were measured in thirteen types of fertilizers by Gamma spectrum using NaI(Tl) (3*3) detector. The average radioactivity of the nuclides 226Ra, 232Th, and 40K was (48.91, 37.04, and 702.4675) Bq.kg-1, respectively, for (Di-Aluminum Phosphate) the chemical fertilizers of the type (DAP) and the (nitrogen, phosphorus, and potassium) chemical fertilizers of the type (NPK) the average radioactivity of the nuclides 226Ra, 232Th, and 40K were (35.78, 42.356 and 1519.653) Bq.kg-1, respectively, while the average radioactivity of the organic fertilizers (Orga.) were 55.153, 23.148 and 1451.258 for the three studied nuclei. As for the average values for radium equivalent were 155.967, 213.363, and 200.0023 (Bq.kg-1) for (DAP), (NPK) and organic fertilizers, respectively. The values of the external severity index (Hex), gamma radiation hazard index (Iγ), and representative alpha index (Iα) were within the permissible limits determined by the UNCEAR 2000. The highest value of total annual effective dose equivalent(TAED) was 1.468 mSv.y-1, the lowest value was 0.302 mSv.y-1, and the mean values were 0.722 mSv.y-1. In contrast, the highest value for annual gonadal dose equivalent(AGED) was 1392.527 μSv.y-1, the lowest value was 275.361 μSv.y-1, and the average values for all models were 672.135 μSv.y-1. The Excess Lifetime Cancer Risk (ELCR), the highest value was 4.039 × 10-3, the lowest value was 0.833× 10-3, and the average value was 1.988× 10-3 for all fertilizers. The Pearson correlation between radioactive variables and cluster analysis was recognized for the three types of fertilizer samples despite it not being widely accepted. The study can be considered preliminary data for subsequent studies.

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.

In this paper, greywater samples are collected from the kitchens of different types of buildings (residential and commercial) located in different districts within the city of Jeddah, Saudi Arabia. The collected samples are analyzed and compared with the potable water from the same region. The parameters investigated are pH, conductivity, total solids (TS), total dissolved solids (TDS), total suspended solids (TSS), total hardness, temporary hardness, permanent hardness, alkalinity, chloride, and biochemical oxygen demand (BOD). It was found that the amount of total suspended solids is very high in the greywater samples. It shows the presence of both temporary and permanent hardness. Their alkalinity values are greater than hardness. It may be due to the number, lifestyle, age of the occupants, presence of children, and social and cultural behavior of residents. The concentration of BOD level is very low, which shows that the greywater samples have lower concentrations of organic compounds. Design details of the greywater treatment plant are suggested based on the results of the analysis. This includes a screening chamber, grit chamber, settling tank, and filtration unit. The treated greywater is recommended for reuse for gardening, landscaping, and toilet flushing purposes.

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.

To become the fastest-growing large economy in the world, India has set a target growth rate of 9%, reaching an economy of $5 trillion by 2024-25. It is an immense challenge to meet the growth target and keep the CO2 emissions under control. The present paper aims to discover the determinants for explaining CO2 emissions in India by conducting a complete decomposition analysis, where the residuals are fully distributed to the determinants for the country from 1990-2018. The analysis reveals that the biggest contributor to the rise in CO2 emissions in India is the expansion of the economy (scale effect). The intensity of CO2 and the change in the composition of the economy, which nearly move in tandem, also contribute to the rise in CO2 emissions, although more slowly. A declining energy intensity of the Indian economy is responsible for a considerable reduction in CO2 emissions. As a typical result for an upcoming economy, this paper did not find evidence for an environmental Kuznets curve. This implies that continued economic growth will lead to increased CO2 emissions.

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.

Rice milling involves shelling and polishing paddy grains to produce rice- both raw and parboiled. Parboiled rice production requires a massive quantity of freshwater for soaking, which, in turn, generates a large amount of wastewater. If this wastewater is not properly ameliorated, it can cause tremendous troubles of surface water pollution, land pollution, and, ultimately, groundwater pollution. Therefore, proper treatment of polluted water from rice mills (PWRM) as per the effluent discharge norms is necessary to protect the surface and subsurface water resources for sustainable development. There are two methods for remediating rice mill wastewater- physicochemical and biological. The biological methods produce comparatively less sludge and are cost-effective. Moreover, these processes are capable of retrieving green energy in the form of biomethane, biohydrogen, and bioelectricity to augment bio-fuel production, aiming to meet the ever-increasing fuel demands caused by rapid industrialization, motorization, and urbanization. The focus on green energy production is gaining momentum day by day due to the adverse effects of conventional energy derived from fossil fuel combustion in terms of enhanced Air Pollution Index (API) in the ambient atmosphere. In this paper, anaerobic biodegradation, phytoremediation, phyco-remediation, and microbial fuel cell techniques adopted by various researchers for remediating the polluted water from rice mills have been well addressed and critically discussed. The pros and cons of these biological methods have been well addressed to assess the socio-technoeconomic feasibility of each method.

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.

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.