Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder characterized mainly by qualitative deficiencies in social communication skills, accompanied by repetitive and restricted behavior patterns. This study was conducted to investigate the associations between the risk of ASD development in children and exposure to trace elements (arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), lead (Pb), nickel (Ni), and zinc (Zn)). Two groups of children, including 44 ASD and 35 typically developing (TD) children, were selected, and their fasting urine samples were obtained. The concentration levels of trace elements were assayed using ICP-MS. The results showed that as compared to the TD group, the concentration levels of As (p = 0.002) and Pb (p < 0.001) and also Cr (p < 0.001), Cu (p = 0.001), and Ni (p < 0.001) were significantly higher among ASD children. In terms of gender, boys with ASD showed elevated levels of Cr, Cu, Ni, and Pb, whereas the urine levels of As, Cr, Cu, Ni, and Pb were markedly higher among girls when compared to the non-ASD children. Under the logistic regression model, the risk difference for As, Co, Cr, Cu, Ni, Pb, and Zn remained significant when adjustment was applied for age and gender confounders.

We expected to explore the associations of hearing loss and hearing thresholds at different frequencies with total and cause-specific mortality. In this study, 11,732 individuals derived from the National Health and Nutrition Examination Survey (NHANES) 1999–2012 were included. Data of death was extracted from the NHANES Public-Use Linked Mortality File through December 31, 2015. Cox proportional hazards models were used to explore the associations between hearing loss, hearing thresholds at different frequencies, and total or cause-specific mortality. A total of 1,253 deaths occurred with a median follow-up of 12.15 years. A significant positive dose-response relationship between hearing loss in speech frequency and total mortality was observed, and the HRs and 95% CIs were 1.16 (0.91, 1.47), 1.54 (1.19, 2.00), and 1.85 (1.36, 2.50), respectively, for mild, moderate, and severe speech-frequency hearing loss (SFHL) with a P ₜᵣₑₙd of 0.0003. In addition, moderate (HR: 1.90, 95% CI: 1.20–3.00) and greater (3.50, 1.38–8.86) SFHL significantly elevated risk of heart disease mortality. Moreover, hearing thresholds of >25 dB at 500, 1000, or 2000 Hz were significantly associated with elevated mortality from all causes (1.40, 1.17–1.68; 1.44, 1.20–1.73; and 1.33, 1.10–1.62, respectively) and heart disease (1.89, 1.08–3.34; 1.95, 1.21–3.16; and 1.89, 1.16–3.09, respectively). Hearing loss is associated with increased risks of total mortality and heart disease mortality, especially for hearing loss at speech frequency. Preventing or inhibiting the pathogenic factors of hearing loss is important for reducing the risk of death.

The feasibility of removal of chemical oxygen demand (COD) and ammonia nitrogen (NH₄⁺–N) from landfill leachate by an electrochemical assisted HClO/Fe²⁺ process is demonstrated for the first time. The performance of active chlorine generation at the anode was evaluated in Na₂SO₄/NaCl media, and a higher amount of active chlorine was produced at greater chloride concentration and higher current density. The probe experiments confirmed the coexistence of hydroxyl radical (•OH) and Fe(IV)-oxo complex (FeᴵⱽO²⁺) in the HClO/Fe²⁺ system. The influence of initial pH, Fe²⁺ concentration, and applied current density on COD and NH₄⁺–N abatement was elaborately investigated. The optimum pH was found to be 3.0, and the proper increase in Fe²⁺ dosage and current density resulted in higher COD removal due to the accelerated accumulation of •OH and FeᴵⱽO²⁺ in the bulk liquid phase, whereas, the NH₄⁺–N oxidation was significantly affected by the applied current density because of the effective active chlorine generation at higher current but was nearly independent of Fe²⁺ concentration. The reaction mechanism of electrochemical assisted HClO/Fe²⁺ treatment of landfill leachate was finally proposed. The powerful •OH and FeᴵⱽO²⁺, in concomitance with active chlorine and M(•OH), were responsible for COD abatement, and active chlorine played a key role in NH₄⁺–N oxidation. The proposed electrochemical assisted HClO/Fe²⁺ process is a promising alternative for the treatment of refractory landfill leachate.

Bioturbation is recognized as a deterministic process that sustains the physicochemical properties of the freshwater ecosystem. Irrigation, ventilation, and particle reworking activities made by biotic components on sediment beds influence the flow of nutrients and transport of particles in the sediment–water interface. Thus, the biogenic disturbances in sediment are acknowledged as pivotal mechanism nutrient cycling in the aquatic system. The macroinvertebrates of diverse taxonomic identity qualify as potent bioturbators due to their abundance and activities in the freshwater. Of particular relevance are the bioturbation activities by the sediment-dwelling biota, which introduce changes in both sediment and water profile. Multiple outcomes of the macroinvertebrate-mediated bioturbation are recognized in the form of modified sediment architecture, changed redox potential in the sediment–water interface, and elicited nutrient fluxes. The physical movement and physiological activities of benthic macroinvertebrates influence organic deposition in sediment and remobilize sediment-bound pollutants and heavy metals, as well as community composition of microbes. As ecosystem engineers, the benthic macroinvertebrates execute multiple functional roles through bioturbation that facilitate maintaining the freshwater as self-sustaining and self-stabilizing system. The likely consequences of bioturbation on the freshwater ecosystems facilitated by various macroinvertebrates — the ecosystem engineers. Among the macroinvertebrates, varied species of molluscs, insects, and annelids are the key facilitators for the movement of the nutrients and shaping of the sediment of the freshwater ecosystem.

The negative health effects of cement plant exposure are well-known in industrial settings, but they are less well-known among the general public who live near plants. The broad objective of the review was to provide a detailed systematic analysis of the global situation of the cement industry, including generation, pollution, impact on the natural ecosystem, technological and process improvements, sustainable models, the latest laws, challenges, needs, and ways forward. As an initial evaluation, a list of critical keywords was compiled, and a search of all accessible databases was conducted (i.e., Scopus, Web of Knowledge, Google Scholar). The manuscripts published in the journal between 2011 and 2021 were included. According to the findings, India is the second largest cement producer after China, with an installed capacity of 537 million tonnes and around 7.1 percent of the world’s production, up from 337.32 million tonnes in 2019. NOx, SOx, CO, CO₂, H₂S, VOCs, dioxins, furans, and particulate matter are all common air pollutants from cement manufacturing. Other sources of dust particles include quarrying, blasting, drilling, trucking, cement plants, fuel production, packaging, path cleaning, and slabs. Other methods of reduction play an important part in decreasing industrial emissions, resulting in lower carbon and more sustainable products. The decision-making trial, in conjunction with the DEMATEL evaluation laboratory and the analytical hierarchy process (AHP) technique, will aid in determining the priority of climate alteration and mitigation options. Furthermore, employing sustainable techniques and technology, switching to alternative fuels will save 12% of total CO₂ emissions by 2050.

This study gives a depiction of what are the general directions taken by international institutions so to tackle the current health emergency and the most pressing environmental issues, such as climate change and COVID-19 (Schaltegger, 2020; Adebayo et al., 2021).The role of companies is crucial under disruptive events, such as a crisis or, more in line with the present time, a pandemic, and the pursue of the shareholder value cannot be the essence and the only objective in doing business anymore, since also ESG (i.e., environmental, social, and governance) dynamics have to be taken in due consideration. Moreover, an adequate and effective corporate governance should lead to higher disclosure quality, which subsequently should help protect the entire planet and ecosystems as well. In this context, the principal role of accounting and corporate reporting activities should be oriented towards making emerge what is and what is not done by companies in their business operations, and the disclosure of financial information is currently deemed inappropriate for pursuing a sustainable growth in the medium and long run (Schaltegger, J Account Org Change 16:613–619, 2020; Kirikkaleli & Adebayo, Sustain Dev 29:583–594, 2020; Tettamanzi, Venturini & Murgolo Wider corporate reporting: La possibile evoluzione della Relazione sulla Gestione Bilancio e Revisione, IPSOA - Wolters Kluwer, Philadelphia, 2021). Thus, the objective of this study is to investigate what international and European institutions have planned to do in order to align corporate objectives with environmental and societal needs in the coming years (Biondi et al., Meditari Account Res 28:889–914, 2020; Songini L et al. Integrated reporting quality and BoD characteristics: an empirical analysis. J Manag Govern, 2021).As of today, our analysis finds that IFRS Foundation (at global level) and EFRAG (at European one) have been taking steps toward the aforementioned issues so to propose disclosure standards more in line with sustainability and environmental needed improvements. In fact, we tried to give a depiction of what are the actual and future strategies that both these institutions are going to put in place: this snapshot will give scientists, engineers, lawyers, and business people an overview of what should be like the corporate world of the near future, from a corporate reporting/accounting perspective (so to better understand what will be expected from companies of all the industries worldwide).

Municipal solid waste (MSW) management currently requires critical attention in ensuring the best principles of socio-economic attributes such as environmental protection, economic sustainability, and mitigation of human health problems. Numerous surveys on the waste management system reveal that approximately 90% of the MSW systems are improperly disposing the wastages in open dumps and landfills. Classifying the wastages into biodegradable and non-biodegradable helps converting them into usable energy and disposing properly. The advancements of effective computational approaches like artificial intelligence and image processing provide wide range of solutions for the present problem identified in MSW management. The computational approaches can be programmed to classify wastes that help to convert them into usable energy. Existing methods of waste classification in MSW remain unresolved due to poor accuracy and higher error rate. This paper presents an experimented effective computer vision–based MSW management solution with the help of the Internet of Things (IoT), and machine learning (ML) techniques namely regression, classification, clustering, and correlation rules for the perception of solid waste images. A ground-up built convolutional neural network (CNN) and CNN by the inception of ResNet V2 models trained through transfer learning for image classification. ResNet V2 supports training large datasets in deep neural networks to achieve improved accuracy and reduced error rate in identity mapping. In addition, batch normalization and mixed hybrid pooling techniques are incorporated in CNN to improve stability and yield state of art performance. The proposed model identifies the type of waste and classifies them as biodegradable or non-biodegradable to collect in respective waste bins precisely. Furthermore, observation of performance metrics, accuracy, and loss ensures the effective functions of the proposed model compared to other existing models. The proposed ResNet-based CNN performs waste classification with 19.08% higher accuracy and 34.97% lower loss than the performance metrics of other existing models.

One of the strategies for agricultural development is the optimal use of irrigation and drainage networks, which leads to higher productivity and economic benefits. In this regard, quantitative and qualitative studies of drainage water from networks are essential for efficient water management. In the present study, we develop a model using a system dynamics approach to simulate the cropping pattern of an irrigation and drainage network as well as the discharge and salinity of drainage water from network farms. We apply the Powell algorithm to optimize the economic profitability of cultivated crops by considering the salinity and discharge of drainage water from the fields. With three aims, i.e., (1) maximizing benefit–cost ratio, (2) minimizing drainage water salinity and discharge of network, and (3) economic and environmental considerations simultaneously, the optimization of cropping pattern within the Kosar irrigation and drainage network is performed. Results based on five consecutive years under different scenarios showed that some crops, such as watermelon, are not economically recommened for production due to high costs, water consumption, and low selling price causes environmental pollution. On the other hand, wheat, grain maize, silage maize, sorghum, and alfalfa have different conditions, and their production is suitable by considering all scenarios. By comparing with experimental data, we find that the proposed model is accurate to simulate and optimize the irrigation network and to detect its cropping pattern.

Both arsenic (As) and antimony (Sb) are primary environmental contaminants that often co-exist at contaminated sites. Though the microbial community compositions of As- and Sb-contaminated sites have been previously described, the changes in microbial community interactions and community functions remain elusive. In the current study, several key metabolic processes, such as As/Sb detoxification and carbon fixation, were enriched under heavily contaminated conditions. Furthermore, the identified keystone taxa, which are associated with the families Nitrosomonadaceae, Pedosphaeraceae, Halieaceae, and Latescibacterota, demonstrated positive correlations with As and Sb concentrations, indicating that they may be resistant to As and Sb toxicities. Accordingly, arsenic resistance–related functions, along with several functions such as carbon fixation, were found to be enriched in heavily contaminated sites. The current study elucidated the key microbial populations in As- and Sb-contaminated rice terraces and may provide useful information for remediation purposes.

The unprecedented increase in anthropogenic activities, coupled with the prevailing climatic conditions, has increased the aerosol load over East Africa (EA). Given this, the present study examined the trends in total, absorption, scattering, and total aerosol extinction optical depth (TAOD, AAOD, SAOD, and TAEOD) over EA, alongside trends in single scattering albedo (SSA). For this purpose, the AOD of different optical properties retrieved from multiple sensors and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) model between January 2001 to December 2019 were utilized to estimate trends and assess their statistical significance. The spatial patterns of seasonal mean AOD from the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor and MERRA-2 model were generally characterized with high (>0.35) and low (<0.2) AOD centers over EA observed during the local dry and wet seasons, respectively. Also, the spatial trend analysis revealed a general increase in TAOD, being positive and significant over the arid and semi-arid zones of the northeastern part of EA, which is majorly dominated by locally derived dust. The local dry (wet) months generally experienced positive (negative) trends in TAOD, associated with seasonal cycles of rainfall. High and significant positive trends in AAOD were dominated over the study domain, attributed to an increased amount of biomass burning, variations in soil moisture, and changes in the rainfall pattern. The trends in TAEOD showed a distinct pattern, except over some months that depicted significant increasing trends attributed to changes in climatic conditions and anthropogenic activities. At last, the study domain exhibited decreasing trends in SSA, signifying strong absorption of direct solar radiation resulting in a warming effect. The study revealed patterns of trends in aerosol optical properties and forms the basis for further research in aerosols over EA.