The Chambal river, subjected to industrial and sewage pollution, was studied with reference to the benthic fauna. Twenty seven taxa of benthic fauna of four main groups were observed at the stretch of the river: Oligochaeta, Diptera, Mollusca and Insecta (“others”). It was noted that the pollution input zone shows less fauna. The analysis of various physicochemical parameters showed an increase in pollution where domestic and industrial effluent were added. Changes in the benthic community have been explained with the help of the Diversity Index. The species diversity values showed a decrease from the prepollution point to the effluent discharge channel with an increase at the posteffluent point, indicating it to be a recovery zone. The coefficient of correlation was assessed between different physicochemical and different groups of benthic fauna. 相似文献
Environmental Chemistry Letters - In the context of climate change, most of the actual dihydrogen production is not sustainable with about 96% of the 60 million tons of dihydrogen produced annually... 相似文献
Environmental Science and Pollution Research - Photovoltaic (PV) panels are one of the most important solar energy sources used to convert the sun’s radiation falling on them into electrical... 相似文献
Microplastic pollution is becoming a major issue for human health due to the recent discovery of microplastics in most ecosystems. Here, we review the sources, formation, occurrence, toxicity and remediation methods of microplastics. We distinguish ocean-based and land-based sources of microplastics. Microplastics have been found in biological samples such as faeces, sputum, saliva, blood and placenta. Cancer, intestinal, pulmonary, cardiovascular, infectious and inflammatory diseases are induced or mediated by microplastics. Microplastic exposure during pregnancy and maternal period is also discussed. Remediation methods include coagulation, membrane bioreactors, sand filtration, adsorption, photocatalytic degradation, electrocoagulation and magnetic separation. Control strategies comprise reducing plastic usage, behavioural change, and using biodegradable plastics. Global plastic production has risen dramatically over the past 70 years to reach 359 million tonnes. China is the world's top producer, contributing 17.5% to global production, while Turkey generates the most plastic waste in the Mediterranean region, at 144 tonnes per day. Microplastics comprise 75% of marine waste, with land-based sources responsible for 80–90% of pollution, while ocean-based sources account for only 10–20%. Microplastics induce toxic effects on humans and animals, such as cytotoxicity, immune response, oxidative stress, barrier attributes, and genotoxicity, even at minimal dosages of 10 μg/mL. Ingestion of microplastics by marine animals results in alterations in gastrointestinal tract physiology, immune system depression, oxidative stress, cytotoxicity, differential gene expression, and growth inhibition. Furthermore, bioaccumulation of microplastics in the tissues of aquatic organisms can have adverse effects on the aquatic ecosystem, with potential transmission of microplastics to humans and birds. Changing individual behaviours and governmental actions, such as implementing bans, taxes, or pricing on plastic carrier bags, has significantly reduced plastic consumption to 8–85% in various countries worldwide. The microplastic minimisation approach follows an upside-down pyramid, starting with prevention, followed by reducing, reusing, recycling, recovering, and ending with disposal as the least preferable option.
Traditional fertilizers are highly inefficient, with a major loss of nutrients and associated pollution. Alternatively, biochar loaded with phosphorous is a sustainable fertilizer that improves soil structure, stores carbon in soils, and provides plant nutrients in the long run, yet most biochars are not optimal because mechanisms ruling biochar properties are poorly known. This issue can be solved by recent developments in machine learning and computational chemistry. Here we review phosphorus-loaded biochar with emphasis on computational chemistry, machine learning, organic acids, drawbacks of classical fertilizers, biochar production, phosphorus loading, and mechanisms of phosphorous release. Modeling techniques allow for deciphering the influence of individual variables on biochar, employing various supervised learning models tailored to different biochar types. Computational chemistry provides knowledge on factors that control phosphorus binding, e.g., the type of phosphorus compound, soil constituents, mineral surfaces, binding motifs, water, solution pH, and redox potential. Phosphorus release from biochar is controlled by coexisting anions, pH, adsorbent dosage, initial phosphorus concentration, and temperature. Pyrolysis temperatures below 600 °C enhance functional group retention, while temperatures below 450 °C increase plant-available phosphorus. Lower pH values promote phosphorus release, while higher pH values hinder it. Physical modifications, such as increasing surface area and pore volume, can maximize the adsorption capacity of phosphorus-loaded biochar. Furthermore, the type of organic acid affects phosphorus release, with low molecular weight organic acids being advantageous for soil utilization. Lastly, biochar-based fertilizers release nutrients 2–4 times slower than conventional fertilizers.
