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Author: search.filters.author.Kumar, S.Subject: search.filters.subject.anaerobic digestion

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    Artificial neural network based modeling to evaluate methane yield from biogas in a laboratory-scale anaerobic bioreactor
    (Elsevier Ltd, 2016) Nair, V.V.; Dhar, H.; Kumar, S.; Thalla, A.K.; Mukherjee, S.; Wong, J.W.C.
    The performance of a laboratory-scale anaerobic bioreactor was investigated in the present study to determine methane (CH4) content in biogas yield from digestion of organic fraction of municipal solid waste (OFMSW). OFMSW consists of food waste, vegetable waste and yard trimming. An organic loading between 40 and 120 kg VS/m3 was applied in different runs of the bioreactor. The study was aimed to focus on the effects of various factors, such as pH, moisture content (MC), total volatile solids (TVS), volatile fatty acids (VFAs), and CH4 fraction on biogas production. OFMSW witnessed high CH4 yield as 346.65 L CH4/kg VS added. A target of 60–70% of CH4 fraction in biogas was set as an optimized condition. The experimental results were statistically optimized by application of ANN model using free forward back propagation in MATLAB environment. © 2016 Elsevier Ltd
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    Life cycle assessment of municipal solid waste management options for India
    (Elsevier Ltd, 2019) Khandelwal, H.; Thalla, A.K.; Kumar, S.; Kumar, R.
    Life Cycle Assessment (LCA) tool can be used for environmental assessment of Municipal Solid Waste Management (MSWM) system. The present study aims to evaluate the impact of MSWM system in Nagpur city, India under four different scenarios. i.e., composting combined with landfilling (S1), material recovery facility (MRF) & composting combined with landfilling (S2), MRF & anaerobic digestion (AD) combined with landfilling (S3) and MRF, AD & composting combined with landfilling (S4) using LCA tool. The sensitivity analysis was also performed for evaluating the influence of recycling rate of valuable resources in all the considered scenarios. The scenarios were compared using Gabi 8.5.0.79 model and CML-1A impact characterization method. S2 was found to have the least environmental impacts on global warming, human toxicity, eutrophication, and photochemical ozone creation potential categories. The sensitivity analysis indicated an inversely proportional relation between change in recycling rate and total environmental burdens. © 2019 Elsevier Ltd