Sample biochemical methane potential from the digestion of domestic mixed sewage sludge in batch tests

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Abstract

Biochemical methane potential (BMP) is a standard test to assess the biogas (including methane) production from the anaerobic digestion of any organic waste. In many anaerobic digestions of sewage sludge, the inoculum to substrate ratio and mixing were variable to take into consideration for efficient performance. However, the organic content in sewage sludge varied due to the composition of the raw wastewater being treated and the treatment condition. This study is focused on the methane production from the digestion of domestic mixed sewage sludge in the batch reactor at different organic contents. Biochemical methane potential (BMP) was conducted at the inoculum to substrate ratio (I/S) ratio of 2:0, each with different organic content. On the termination day of the BMP assay, the sample from each BMP reactor was tested for pH, and alkalinity to determine the status of the anaerobic process. Results showed that the anaerobic process was stable since the pH remained in the pH range which is suitable for the anaerobic process to take place. The anaerobic process was also confirmed stabled as indicated by low value (< 0.3) of intermediate alkalinity to partial alkalinity ratio (IA/PA). The ultimate methane yield was 588.3 ml CH4/g VS at the organic content of 0.52 and 1244.5 ml CH4/g VS at the organic content of 0.68 respectively. For the organic content of 0.68, the maximum methane production rate constant was 13.97 mL CH4/g VS /hr. For the case of lower organic content, the maximum methane production rate constant was 6.41 mL CH4/g VS /hr. However, the lag phase of the methane yield curve for both organic content was less than one (1) day, showing the good biodegradability of domestic mixed sewage sludge.

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APA

Seswoya, R., & Karim, A. T. A. (2017). Sample biochemical methane potential from the digestion of domestic mixed sewage sludge in batch tests. International Journal on Advanced Science, Engineering and Information Technology, 7(2), 431–437. https://doi.org/10.18517/ijaseit.7.2.2094

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