Frequency of PPAR-γ, FTO and ABCC8 genetic variation in Pakistani cardiovascular smokers

Environmental Science and Pollution Research - Smoking is considered as one of the major reasons behind genetic variations in cardiometabolic disorders. However, effect of nicotine via smoking on...     

On-road emissions of CO, CO2 and NOX from four wheeler and emission estimates for Delhi

This study presents the emission factor of gaseous pollutants(CO, CO_2, and NO X) from on-road tailpipe measurement of 14 passenger cars of different types of fuel and vintage. The trolley equipped with stainless steel duct, vane probe velocity meter, flue gas analyzer, Nondispersive infra red(NDIR) CO_2 analyzer, temperature, and relative humidity(RH) sensors was connected to the vehicle using a towing system. Lower CO and higher NO X emissions were observed from new diesel cars(post 2010) compared to old cars(post 2005), which implied that new technological advancement in diesel fueled passenger cars to reduce CO emission is a successful venture,however, the use of turbo charger in diesel cars to achieve high temperature combustion might have resulted in increased NO X emissions. Based on the measured emission factors(g/kg), and fuel consumption(kg), the average and 95% confidence interval(CI) bound estimates of CO, CO_2,and NO X from four wheeler(4W) in Delhi for the year 2012 were 15.7(1.4–37.1), 6234(386–12,252),and 30.4(0.0–103) Gg/year, respectively. The contribution of diesel, gasoline and compressed natural gas(CNG) to total CO, CO_2 and NO X emissions were 7:84:9, 50:48:2 and 58:41:1respectively. The present work indicated that the age and the maintenance of vehicle both are important factors in emission assessment therefore, more systematic repetitive measurements covering wide range of vehicles of different age groups, engine capacity, and maintenance level is needed for refining the emission factors with CI.     

Biotechnology to convert carbon dioxide into biogas,bioethanol, bioplastic and succinic acid using algae,bacteria and yeast: a review

Environmental Chemistry Letters - Global warming is partly due to excessive carbon dioxide emissions, calling for methods to capture carbon dioxide for conversion into value-added...     

Chitosan-based beads as sustainable adsorbents for wastewater remediation: a review

Environmental Chemistry Letters - Water contamination is increasing worldwide, yet actual methods of water and wastewater treatment are limited, in particular by actual fossil-fuel derived...     

Essential oils and their bioactive compounds as eco-friendly novel green pesticides for management of storage insect pests: prospects and retrospects

Environmental Science and Pollution Research - The control of storage insect pests is largely based on synthetic pesticides. However, due to fast growing resistance in the targeted insects,...     

Chitosan Based Nanoformulation for Sustainable Agriculture with Special Reference to Abiotic Stress: A Review

Journal of Polymers and the Environment - Chitosan is a naturally occurring biological macromolecule and second most abundant polysaccharide next to cellulose, derived from deacetylation of chitin....     

Differential neuroprotective effect of curcuminoid formulations in aluminum chloride–induced Alzheimer’s disease

Environmental Science and Pollution Research - Alzheimer’s disease (AD) is a slowly progressive brain degenerative disorder which gradually impairs memory, thinking, and ability to perform...     

State-of-the-art applications of machine learning in the life cycle of solid waste management

● State-of-the-art applications of machine learning (ML) in solid waste (SW) is presented. ● Changes of research field over time, space, and hot topics were analyzed. ● Detailed application seniors of ML on the life cycle of SW were summarized. ● Perspectives towards future development of ML in the field of SW were discussed. Due to the superiority of machine learning (ML) data processing, it is widely used in research of solid waste (SW). This study analyzed the research and developmental progress of the applications of ML in the life cycle of SW. Statistical analyses were undertaken on the literature published between 1985 and 2021 in the Science Citation Index Expanded and Social Sciences Citation Index to provide an overview of the progress. Based on the articles considered, a rapid upward trend from 1985 to 2021 was found and international cooperatives were found to have strengthened. The three topics of ML, namely, SW categories, ML algorithms, and specific applications, as applied to the life cycle of SW were discussed. ML has been applied during the entire SW process, thereby affecting its life cycle. ML was used to predict the generation and characteristics of SW, optimize its collection and transportation, and model the processing of its energy utilization. Finally, the current challenges of applying ML to SW and future perspectives were discussed. The goal is to achieve high economic and environmental benefits and carbon reduction during the life cycle of SW. ML plays an important role in the modernization and intellectualization of SW management. It is hoped that this work would be helpful to provide a constructive overview towards the state-of-the-art development of SW disposal.     

The impact of mucormycosis (black fungus) on SARS-CoV-2-infected patients: at a glance

Environmental Science and Pollution Research - The emergence of various diseases during the COVID-19 pandemic made health workers more attentive, and one of the new pathogens is the black fungus...     

Waste to energy: a decision-making process for technology selection through characterization of waste,considering energy and emission in the city of Ahmedabad,India

Journal of Material Cycles and Waste Management - Municipal solid waste (MSW) disposal has become major issue for the city of Ahmedabad, India. Development, concentrated population and economic...