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低 HS 浓度沼气脱硫生物滴滤塔特性:性能与模型分析。

Characteristics of low HS concentration biogas desulfurization using a biotrickling filter: Performance and modeling analysis.

机构信息

School of Municipal and Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Key Laboratory of Northwest Water Resources, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an 710055, China.

School of Municipal and Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Key Laboratory of Northwest Water Resources, Environment and Ecology, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an 710055, China.

出版信息

Bioresour Technol. 2019 May;280:143-150. doi: 10.1016/j.biortech.2019.02.007. Epub 2019 Feb 2.

Abstract

This study investigated the characteristics of low HS concentration biogas biodesulfurization using a lab-scale biotrickling filter (BTF). The influence of operational parameters on HS removal efficiency and HS distributions in packed bed was evaluated by establishing a counter-current one-dimensional multi-layer BTF model and statistical analysis of the simulation results. The overall biodesulfurization efficiency of counter-current BTF on treating low HS concentration was 92.27 ± 10.30%. The HS distribution of the BTF packed bed could be predicted by the calibrated BTF model. The influence of the operational parameters on the HS distribution of the packed bed was following the sequence of pH > empty bed retention time (EBRT) > gas-to-liquid flow ratio (G/L). The biogas biodesulfurization process was strongly related to the sulphide affinity constant. Moreover, a high substrate concentration of the SOB could further accelerate the biodesulfurization process of the biogas with low HS concentration.

摘要

本研究采用实验室规模的生物滴滤塔(BTF),考察了低 HS 浓度沼气生物脱硫的特点。通过建立逆流一维多层 BTF 模型并对模拟结果进行统计分析,评估了操作参数对 HS 去除效率和填充床中 HS 分布的影响。逆流 BTF 处理低 HS 浓度沼气的整体生物脱硫效率为 92.27±10.30%。BTF 模型可以预测 BTF 填充床中 HS 的分布。操作参数对填充床中 HS 分布的影响顺序为 pH 值>空床停留时间(EBRT)>气液比(G/L)。沼气生物脱硫过程与硫亲和常数密切相关。此外,较高的 SOB 基质浓度可以进一步加速低 HS 浓度沼气的生物脱硫过程。

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