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Healthcare Waste, Pandemic Covid-19: A Case of India
2021
Dinesh Kumar, Sukesh Trikha | Ranju Anthony
The present pandemic, while causing economic slowdown and global panic, also generated healthcare waste in unprecedented amounts across the globe, due to mass screenings/diagnosing/treatment. This paper aims to explore the prospects of the current and future challenges with respect to the risk to human health due to environmental contamination with the healthcare waste generated as a result of and caused by the Covid-19 pandemic in the Indian context. Peer-reviewed literature with respect to healthcare waste generation during the pandemic, its burden, challenges, and policies promulgated during the pandemic and their implications for the future was searched on various databases like PubMed, Google Scholar, and Science Direct and reviewed. Many research studies and international reports have demonstrated that the quantity of biomedical waste has increased in the times of the Covid-19 pandemic across the globe. Additionally, the danger of general waste getting contaminated has also multiplied, in part due to increased quarantine facilities and home quarantines, along with hospitals managing Covid-19 patients and also due to inadequate segregation at the point of generation of such waste, which is a major concern in itself. The occupational exposure of this increased waste to hospital and municipal waste collection workers has also increased, though World Health Organization (WHO) declines having any evidence of transmission of coronavirus while handling healthcare waste. Enough policies existed before the pandemic and few newer guidelines are also issued to address various additional aspects, which are to be implemented to manage the healthcare waste, minimize threats to the environment and human health. Cleaner, greener waste management facilities, the inclusion of bio-disaster in disaster management, the social impact of waste management policies, and waste reduction are to be prioritized.
اظهر المزيد [+] اقل [-]Optimization of Chlorella Culture Conditions with Response Surface Methodology to Increase Biomass
2021
R. Kanimozhi, D. Arvind Prasath, R. Dhandapani | Santhosh Sigamani
Microalgae is gaining popularity as a major ingredient in nutrition supplements. To mass cultivate, it is imperative to improve the biomass yield hence optimization of cultures conditions becomes paramount. In this work, an attempt has been made to optimize the microalgal production using response surface methodology (RSM) and validate further the optimized parameters. The optimum conditions for the cultivation of Chlorella sp. KPU016 under optimized nutrient conditions were pH 8.2, the light intensity of 3100 lx, glycerol 1.44 g.L-1 (under pre-set conditions of 12 h lighting, the temperature at 27±1°C. With these RSM-driven optimum conditions, the yield of microalgal biomass achieved was 282.50 mg.L-1. For larger-scale microalgal harvesting, the validated optimal conditions can be inferred as the best for enhanced microalgal production. The isolate was partially sequenced and submitted to the NCBI database and the GenBank accession number is MZ348364.
اظهر المزيد [+] اقل [-]Application of Remote Sensing and GIS Techniques for the Analysis of Lake Water Fluctuations: A Case Study of Ugii Lake, Mongolia
2021
Amgalan Magsar, Toru Matsumoto, Altanbold Enkhbold | Nandintsetseg Nyam-Osor
Ugii Lake is a freshwater lake located in the steppe region of Mongolia and is an important breeding and staging area for a wide variety of waterfowl. Remote sensing and geographic information system techniques were used to estimate fluctuations in the surface area and water balance of Ugii Lake. To estimate the changes in lake water balance, lake water fluctuations should be analyzed using the most accurate methods. A different water extraction technique was applied, and the results were compared with field surveys conducted in May, July, and September 2020. The lake surface area using both NDWI and MNDWI-1 showed a strong, positive correlation (R=0.93, R=0.94, p < 0.01) with the water level of Ugii Lake. A topographic map of Ugii Lake was provided by the project (P2018-3568) conducted in August 2019 and used to estimate the volume of Ugii Lake in ArcGIS 10.1. This result was consistent with that of a previous study by JICA in 2005. Finally, the water balance of Ugii Lake was estimated, and the results proved that the influence of both surface and groundwater on Ugii Lake are valuable parameters, which are completely dependent on hydrological regime changes mostly due to local climate change in steppe regions. This study provides valuable insight into the most suitable water extraction methods for lakes in semi-arid steppe regions in Mongolia.
اظهر المزيد [+] اقل [-]Hydrochemistry and Application of GIS in Groundwater Quality in Nagalapura Taluk, Bellary District, Karnataka, India
2021
Maradi Sangrama Nayaka, T. Suresh, S. Manjappa | B. Suresh
The assessment of groundwater quality is essential for the conservation of natural resources. Hence, this study aims to assess the hydrochemistry of groundwater in and around the Nagalapura Taluk in Bellary district, Karnataka, India. The groundwater quality variables are mapped using a Geographic Information System (GIS). For the hypothesis, the mean value of ten groundwater quality variables was obtained from 50 bore well samples (2016-2018). To assess the lead ions and type of water, the USSL, SAR, and Na% were measured. Ionic ratio and Gibbs graphs were used to demonstrate the chemical reactions in the water samples. ArcGIS was used for spatial analysis of the quality variables. The results showed the order of Cl- > SO42- > HCO3- with water types Na+-Cl- and Cl-, and the order of Na+ > Mg++ > Ca++ > K+ with Na+ and Mg++ as the dominant anion and cation, respectively. The hydrochemistry of groundwater is determined by the geological structure in 64 percent of the water samples examined. The Wilcox diagram shows that no-alkali exposure to the crops is expected. Forty one samples (82%) fit within the C3-S1 group; this category is fit for irrigational needs. Only 01 and 03 samples showed maximum SAR during two seasons like pre-monsoon and post-monsoon periods. The maps showed that groundwater in the selected sites is usually of higher quality, whereas the presence of dolomite indicates a reduction in water quality.
اظهر المزيد [+] اقل [-]Comparative Life Cycle Assessment Analysis of Sewage Sludge Recycling Systems in China
2021
Jiawen Zhang | Toru Matsumoto
With the acceleration of economic development and urbanization in China, sewage sludge generation has sharply increased. To maximize energy regeneration and resource recovery, it is crucial to analyze the environmental impact and sustainability of different sewage sludge recycling systems based on life cycle assessment. This study analyzed four sewage sludge recycling systems in China through life cycle assessment using the ReCipe method, namely aerobic composting, anaerobic digestion and biomass utilization, incineration, and heat utilization and using for building materials. In particular, the key pollution processes and pollutants in sewage sludge recycling systems were analyzed. The results demonstrated that aerobic composting is the most environmentally optimal scenario for reducing emissions and energy consumption. The lowest environmental impact and operating costs were achieved by making bricks and using them as building materials; this was the optimal scenario for sludge treatment and recycling. In contrast, incineration and heat utilization had the highest impact on health and marine toxicity. Anaerobic digestion and biomass utilization had the highest impact on climate change, terrestrial acidification, photochemical oxidant formation, and particulate matter formation. In the future, policy designers should prioritize building material creation for sludge treatment and recycling.
اظهر المزيد [+] اقل [-]Study of Some Indicators of Environmental Pollution of Surface Soilfor the City of Touggourt (Southeast Algeria)
2021
A. Benarabi, M. S. Nili | A. Douadi
Soil is contaminated with various potentially harmful metals (PTMs). Therefore, the adequate protection of soil from contamination is imperative, as the soil is regarded as the primary cradle for living and environmental balance. Accordingly, the purpose of this study was to assess the contamination level by PTMs in Touggourt city, where soil samples have been collected randomly from 18 sites. These sites included manufacturing companies and institutions belonging to the industrial region of Touggourt city. The concentrations of six PTMs - zinc (Zn), iron (Fe), cobalt (Co), copper (Cu), lead (Pb) and manganese (Mn) were assessed using the atomic absorption spectrophotometer (AAS) instrument as well as the application of the modern pollution indices such as CF (Contamination Factor), PLI (Pollution Load Index) and EF (Enrichment Factor). The highest values of contamination factor (CF) for Zn, Fe, Co, Cu, and Pb were 0.605, 1.605, 0.277, 0.05, 0.438, and 0.01, respectively, and the highest value of pollution load index (PLI) was 0.139, while the results of enrichment factor (EF) for the Zn, Mn, Co, Cu and Pb metals were 2.608, 0.060, 0.740, 0.122, and 2.358, respectively. According to these pollution indices, the results of this study have indicated that human effects or industrial wastes and traffic, in particular, were the sources of heavy metal contaminating the studied region.
اظهر المزيد [+] اقل [-]GIS-Based Surface Runoff Modeling Using Empirical Technique For A River Basin In South India
2021
B. Prabhu Dass Batvari | K. Nagamani
Precipitation is the primary source of fresh water in the world. Surface runoff will happen when the amount of rainfall is greater than the soil’s infiltration capacity. In most water resource applications, runoff is the most important hydrological variable. Aside from these rainfall characteristics, there are a number of catchment-specific elements that have a direct impact on runoff amount and volume. This research focuses on estimating surface runoff over the lower Vellar basin, a river basin in the southern part of India, by integrating Soil Conservation Service-Curve Number (SCS-CN) method with GIS. This technique is one of the most common methods used by hydrologists for estimating surface runoff. Curve Number (CN) is an index established by the Natural Resource Conservation Service (NRCS) to denote the potential for stormwater runoff. The nature of the watershed is explored first by creating land use and land cover pattern followed by the preparation of slope, drainage, and location maps. The area taken for this study is the lower Vellar basin situated in the Cuddalore District of Tamil Nadu, India. The curve number is analyzed using the rainfall data of 15 years (2001-2015) and the runoff is being calculated. The watershed pattern of the study area is also explored being analyzed and executed. Preservation of the runoff water is also discussed.
اظهر المزيد [+] اقل [-]FAIRCHAIN project overview
2021
Gésan-Guiziou, Geneviève
Recognition of Image-Based Plant Leaf Diseases Using Deep Learning Classification Models
2021
Sakshi Takkar, Anuj Kakran, Veerpal Kaur, Manik Rakhra, Manish Sharma, Pargin Bangotra | Neha Verma
Plant diseases are spread by a variety of pests, weeds, and pathogens and may have a devastating effect on agriculture, if not handled in a timely manner. Farmers face umpteen challenges from a proper water supply, untimely rain, storage facilities, and several plant diseases. Crops disease is the primary threat and it causes enormous loss to farmers in terms of production and finance. Identifying the disease from several hectares of agricultural land is a very difficult practice even with the presence of modern technology. Accurate and rapid illness prediction for early illness treatment to crops minimizes economical loss to the individual and further proves to be productive for healthy crops. Many studies use modern deep learning approaches to improve the accuracy and performance of object detection and identification systems. The suggested method notifies farmers of different agricultural illnesses, prompting them to take further essential precautions before the disease spreads to the whole agricultural field. The primary objective of this study is to detect the illnesses as soon as they begin to spread on the leaves of the plants. Super-Resolution Convolutional Neural Network (SRCNN) and Bicubic models are employed in the system to identify healthy and diseased leaves with an accuracy of 99.175 % and 99.156 % respectively.
اظهر المزيد [+] اقل [-]Toxicity, Monitoring, and Biodegradation of Cypermethrin Insecticide:A Review
2021
Ramandeep Kaur | Joginder Singh
Cypermethrin insecticide is widely used to prevent and control pest and crop diseases though, its residues have caused significant damage to the environment and living organisms. Microbial remediation becomes a popular approach to counter the toxicity of cypermethrin in both aquatic as well as terrestrial life. Cypermethrin can be effectively degraded to nontoxic compounds by bacterial and fungal strains. Various bacterial and fungal strains such as Ochrobactrum lupini DG-S-01, Bacillus sp. strain SG2, Azoarcus indigens strain HZ5, Streptomyces aureus strain HP-S-01, and Aspergillus oryzae M-4 are used for the cypermethrin degradation. Extensive usage of cypermethrin has caused problems such as surface water contamination, reduced fertility of the soil, detrimental effects on soil microbiota and non-targeted species. Due to environmental concerns associated with the cypermethrin in groundwater and food products, there is a crucial need to develop economical, rapid, and reliable techniques that can be used for field applications. An in-depth understanding of cypermethrin is explored in this review paper and possible solutions to mitigate its environmental toxicity are suggested.
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