P. Sivakumar , R. Saravanane , S. Mohan , B. Sankar
{"title":"生物炭在含牛粪、食物垃圾和稻草的厌氧沼气池中作为甲烷强化催化剂的实验和统计研究","authors":"P. Sivakumar , R. Saravanane , S. Mohan , B. Sankar","doi":"10.1016/j.clwas.2025.100388","DOIUrl":null,"url":null,"abstract":"<div><div>There is a growing interest in meeting the rising energy demand from a more sustainable source. Biomass energy has the potential to act as a sustainable and environmentally friendly alternative to fossil fuels and help achieve net-zero emissions in the near future. This study proposes an economically feasible method to enhance biogas efficiency by co-digesting cow dung (CD), food waste (FW), rice straw (RS), with the addition of Coconut husk Bio-Char (BC). The present research aims to study the variation in the biogas yield from biochar addition by monitoring the alteration in the influential parameters such as pH, temperature, total solids (TS), volatile solids (VS), volatile fatty acids (VFA), and carbon to nitrogen ratio (C/N). The biochar addition stabilized both pH and temperature due to its intrinsic properties by transforming intermediates like H<sub>2</sub>S and CO<sub>2</sub>. It also significantly increased the VFA accumulation and degradation attributed to the buffering ability of the biochar. The methane yield of blends with biochar was significantly higher than that of the blends without biochar. The mixture CD 30: FW 50:RS 20 containing biochar showed a peak methane yield of 165.08 mL. The statistical model developed using response surface methodology (RSM) predicted the methane yield with an accuracy of 99.07 % and a statistical significance level of 0.05. The accuracy of the RSM model was validated by comparing it with the existing Gompertz kinetic model. The performance evaluation error metrics, Coefficient of Correlation (R), and Root Mean Square Error (RMSE) results were observed to be 0.966, 0.925, and 62.89 mL/gVS, 87.24 mL/gVS for RSM model and Gompertz model, indicating the superior performance of the RSM model developed in this study.</div></div>","PeriodicalId":100256,"journal":{"name":"Cleaner Waste Systems","volume":"12 ","pages":"Article 100388"},"PeriodicalIF":3.9000,"publicationDate":"2025-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Biochar as a catalyst for methane enhancement in anaerobic digestor containing cow dung, food waste, and rice straw: An experimental and statistical study\",\"authors\":\"P. Sivakumar , R. Saravanane , S. Mohan , B. Sankar\",\"doi\":\"10.1016/j.clwas.2025.100388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>There is a growing interest in meeting the rising energy demand from a more sustainable source. Biomass energy has the potential to act as a sustainable and environmentally friendly alternative to fossil fuels and help achieve net-zero emissions in the near future. This study proposes an economically feasible method to enhance biogas efficiency by co-digesting cow dung (CD), food waste (FW), rice straw (RS), with the addition of Coconut husk Bio-Char (BC). The present research aims to study the variation in the biogas yield from biochar addition by monitoring the alteration in the influential parameters such as pH, temperature, total solids (TS), volatile solids (VS), volatile fatty acids (VFA), and carbon to nitrogen ratio (C/N). The biochar addition stabilized both pH and temperature due to its intrinsic properties by transforming intermediates like H<sub>2</sub>S and CO<sub>2</sub>. It also significantly increased the VFA accumulation and degradation attributed to the buffering ability of the biochar. The methane yield of blends with biochar was significantly higher than that of the blends without biochar. The mixture CD 30: FW 50:RS 20 containing biochar showed a peak methane yield of 165.08 mL. The statistical model developed using response surface methodology (RSM) predicted the methane yield with an accuracy of 99.07 % and a statistical significance level of 0.05. The accuracy of the RSM model was validated by comparing it with the existing Gompertz kinetic model. The performance evaluation error metrics, Coefficient of Correlation (R), and Root Mean Square Error (RMSE) results were observed to be 0.966, 0.925, and 62.89 mL/gVS, 87.24 mL/gVS for RSM model and Gompertz model, indicating the superior performance of the RSM model developed in this study.</div></div>\",\"PeriodicalId\":100256,\"journal\":{\"name\":\"Cleaner Waste Systems\",\"volume\":\"12 \",\"pages\":\"Article 100388\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cleaner Waste Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772912525001861\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cleaner Waste Systems","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772912525001861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Biochar as a catalyst for methane enhancement in anaerobic digestor containing cow dung, food waste, and rice straw: An experimental and statistical study
There is a growing interest in meeting the rising energy demand from a more sustainable source. Biomass energy has the potential to act as a sustainable and environmentally friendly alternative to fossil fuels and help achieve net-zero emissions in the near future. This study proposes an economically feasible method to enhance biogas efficiency by co-digesting cow dung (CD), food waste (FW), rice straw (RS), with the addition of Coconut husk Bio-Char (BC). The present research aims to study the variation in the biogas yield from biochar addition by monitoring the alteration in the influential parameters such as pH, temperature, total solids (TS), volatile solids (VS), volatile fatty acids (VFA), and carbon to nitrogen ratio (C/N). The biochar addition stabilized both pH and temperature due to its intrinsic properties by transforming intermediates like H2S and CO2. It also significantly increased the VFA accumulation and degradation attributed to the buffering ability of the biochar. The methane yield of blends with biochar was significantly higher than that of the blends without biochar. The mixture CD 30: FW 50:RS 20 containing biochar showed a peak methane yield of 165.08 mL. The statistical model developed using response surface methodology (RSM) predicted the methane yield with an accuracy of 99.07 % and a statistical significance level of 0.05. The accuracy of the RSM model was validated by comparing it with the existing Gompertz kinetic model. The performance evaluation error metrics, Coefficient of Correlation (R), and Root Mean Square Error (RMSE) results were observed to be 0.966, 0.925, and 62.89 mL/gVS, 87.24 mL/gVS for RSM model and Gompertz model, indicating the superior performance of the RSM model developed in this study.