Studies have confirmed that adverse human health effects that are associated with exposure to air pollution may differ depending on other factors such as age, gender, environmental conditions, and socio-economic factors. This study was conducted to assess the association between ambient air pollution and cause-specific mortality in the three big cities in South Africa and to determine the susceptible groups thereof. Cause-specific mortality data for all ages and PM₁₀, NO₂, and SO₂ in Cape Town, Durban, and Johannesburg for the period from 1 January 2006 to 31 December 2010 were obtained. Statistical analyses were done to estimate the associations between air pollutants and cause-specific mortality. Susceptibility was therefore investigated in stratified analyses by sex and age (≥60 years) and environmental conditions (heat and cold) followed by models with interaction terms. Our estimates showed independent associations between these air pollutants, environmental conditions, and susceptible groups.

Since the last several decades, there has been a growing concern on the presence of endocrine-disrupting compounds (EDCs) in potable water due to their negative impacts on public health of mankind. As such, more and more EDCs have been regulated in many national drinking water quality standards. Given this situation, this work attempted to deliberately offer new insights into some remaining scientific challenges, i.e., (1) what should the allowable EDC concentration be in drinking water?; (2) should the main chlorinated byproducts of EDCs be regulated in potable water?; and (3) what concentration should be regulated for each chlorinated EDC? It is expected that these could help to better design the water quality regulations for EDCs.

We contribute to the renewable energy consumption-income (and growth) nexus literature by performing an empirical study on a worldwide panel database that, depending on data availability, covers between 146 and 161 countries for the period of 1960 to 2019 (59 years), enabling much more observations than most of the literature on the subject. The empirical methodology used accounts for cross-country dependency, heterogeneity and common effects amongst countries using a parsimonious specification that controls for traditional sources of income differences as well as institutional features of the countries. We also run an error correction model to check the impact of the share of the renewables on the income on the long run. Our results give support to the use of models that control for cross dependence giving a more accurate depiction of the renewable energy consumption-income nexus, showing either a negative or nonsignificant influence of the share of renewable energies consumption in the short run and a possible positive effect in the long run.

Given the context of the global energy shortage and the deterioration of the ecological environment, this paper uses industrial linkage as a starting point to deeply explore the energy consumption of different sectors and its transfer characteristics. First, a dual evaluation of energy consumption in various sectors is conducted from the perspectives of production and demand to realize an integrated analysis from the energy consumption perspective. Second, based on industrial linkage, the economic input-output life cycle assessment (EIO-LCA) model is used to quantify the net transfer of energy consumption and identify the transfer of energy consumption pressure embodied in economic activities by various sectors. Finally, the energy consumption of various sectors is decomposed, and the transfer flow of energy consumption is measured to accurately quantify the degree of linkage in the energy consumption of sectors. The results show that the current direct energy consumption intensity of various sectors in China is continuously decreasing, but this decrease is insufficient to reverse the upward trend in energy consumption demand. From the perspective of production and demand, non-energy industrial sector is a key sector for reducing energy consumption, and the intersectoral linkage between the subsectors caused by product trade flows has a greater impact on the level of direct and embodied energy consumption. Direct and embodied energy consumption in the same sector can be ranked quite differently, and their levels may not be equal. Energy sector is the main net outflow sector of energy consumption, and the level of its direct energy consumption is much higher than that of its embodied energy consumption. It is worth noting that the scale of embodied energy consumption in construction industry is much higher than the scale of direct energy consumption. Construction is the sector with the greatest net inflow of energy consumed and is the main driver of the energy consumption transfer of energy sector and non-energy industrial sector.

Awba reservoir serves the purpose of water supply in the University of Ibadan, Nigeria. Recent reports on pollution status have focused on toxicological implication of contaminants in this reservoir. But none is on genetic and systemic toxicity of the water in fish. We investigated cytogenotoxicity of Awba Dam water (ADW) on Clarias gariepinus using piscine micronucleus (MN) assay. Haematological and histopathological changes were also evaluated. Bi-monthly composite water samples were collected from the reservoir from July to October, 2018. The water was used to cultivate juvenile C. gariepinus in the laboratory for 1–4 months, and tap water was used as the negative control. Peripheral blood erythrocytes from the caudal veins of C. gariepinus were used for the monthly MN assessment. There was significant (p < 0.05) induction of MN and other erythrocyte nuclear abnormalities in C. gariepinus within the period of study. There were variations in the haematological indices and pathological alterations in sections of the gill, liver and kidney of C. gariepinus. The levels of some heavy metals in ADW were above standard permissible limits and might have contributed to the observed cytogenetic and systemic disruptions. These findings may be used by the concerned authorities to evolve management strategies for the reservoir’s health and biologic resources.

Polybrominated diphenyl ethers (PBDEs) are a class of persistent organic pollutants (POPs) used as flame retardants in the products utilized in day-to-day life. Their bioaccumulation, low volatility, and high persistence in the environment have led to their global spread even to remote and distant regions. The present study identifies gaps in the investigation of the neurotoxic potential of PBDEs, their effects on brain development, toxicokinetic, and their potential as a carcinogen. In India, to date, only human breast milk was assessed for levels of PBDEs, and it is suggested that other human tissues can also be explored. No data on the reproductive toxicity of PBDEs are reported from Indian cohorts. Long-range transport and deposition of PBDEs in colder regions necessitates monitoring of Himalayan regions in India. An inventory of PBDEs is required to be made for addressing the worrisome situation of the unregulated import of E-waste from the developed countries in India. The study also emphasizes providing guidelines for the articulation of policies regarding sound surveillance and management of PBDE production, consumption, and release in the Indian context. It is recommended that a separate cell for monitoring and follow-up of PBDEs should be established in India. Also, the development of better alternatives and environment-friendly remediation technologies for PBDEs is the need of the hour.

A reliable assessment of the aquifer contamination vulnerability is essential for the conservation and management of groundwater resources. In this study, a recent technique in artificial intelligence modeling and computational optimization algorithms have been adopted to enhance the groundwater contamination vulnerability assessment. The original DRASTIC model (ODM) suffers from the inherited subjectivity and a lack of robustness to assess the final aquifer vulnerability to nitrate contamination. To overcome the drawbacks of the ODM, and to maximize the accuracy of the final contamination vulnerability index, two levels of modeling strategy were proposed. The first modeling strategy used particle swarm optimization (PSO) and differential evolution (DE) algorithms to determine the effective weights of DRASTIC parameters and to produce new indices of ODVI-PSO and ODVI-DE based on the ODM formula. For strategy-2, a deep learning neural networks (DLNN) model used two indices resulting from strategy-1 as the input data. The adjusted vulnerability index in strategy-2 using the DLNN model showed more superior performance compared to the other index models when it was validated for nitrate values. Study results affirmed the capability of the DLNN model in strategy-2 to extract the further information from ODVI-PSO and ODVI-DE indices. This research concluded that strategy-2 provided higher accuracy for modeling the aquifer contamination vulnerability in the study area and established the efficient applicability for the aquifer contamination vulnerability modeling.

The rapidly changing population structure in South Asian countries is observed to be linked with growing social, economic, and environmental problems. Therefore, to enhance current wave of knowledge, this research investigated the effect of population structure on CO₂ emissions in some selected South Asian countries (Pakistan, India, Bangladesh, Nepal) over the period of 1990–2016. The results showed that age structure is associated with CO₂ emissions in the long run in Pakistan, India, Bangladesh, and Nepal. In addition, age structure drives more CO₂ emissions in India than in any other countries. People with age less than 15 years and people with age more than 65 years are responsible for increasing CO₂ emissions in India. On the other hand, in Pakistan, people of age less than 15 years are responsible for reduction of CO₂ emissions in the long run. In Nepal, age group of young people (less than 15 years) exerts negative effects on CO₂ emissions. The governments of these countries need to put serious attention toward age structure in order to improve air quality.

Three sampling campaigns were performed in the Lis River (Leiria, Portugal) in February of 2018, November of 2018, and May of 2019. River water and wastewater (influent and effluent) samples of two wastewater treatment plants were target of the study. A total of 25 samples were collected and 50 pesticides were monitored, including organochlorines, triazines, pyrethroids, and organophosphorus, among others. Most of the detected pesticides were insecticides and mainly organochlorines. Concentrations between 1.29 and 2134 ng/L were found. Aldrin, γ-HCH, and cypermethrin were detected in some samples in μg/L, being γ-HCH the pesticide most frequently detected with concentration in μg/L level. The pesticides with the highest detection frequency were (i) cypermethrin, HCB, methoxychlor, and ζ-HCH in river waters; (ii) isoproturon, cypermethrin, methoxychlor, pyrimethanil, γ-HCH, dieldrin, diuron, α-HCH, and α-endosulfan in effluents; and (iii) diuron and isoproturon in influents. The detection of the organochlorides and their degradation products is a consequence of their persistence in the environment, as their usage has long been prohibited in the European Union. Pesticides were grouped by their types in herbicides, insecticides, or fungicides and the detection and concentration for each type were discussed with the climatic conditions. Pesticide toxicity index was determined in the samples collected in the river.