污水管道危害性气体浓度分布模型扩展与验证

闫森, 丁艳萍, 郑才林, 廖邦友, 宋光顺, 陈军, 卢金锁. 污水管道危害性气体浓度分布模型扩展与验证[J]. 环境工程学报, 2019, 13(5): 1228-1236. doi: 10.12030/j.cjee.201901063
引用本文: 闫森, 丁艳萍, 郑才林, 廖邦友, 宋光顺, 陈军, 卢金锁. 污水管道危害性气体浓度分布模型扩展与验证[J]. 环境工程学报, 2019, 13(5): 1228-1236. doi: 10.12030/j.cjee.201901063
YAN Sen, DING Yanping, ZHENG Cailin, LIAO Bangyou, SONG Guangshun, CHEN Jun, LU Jinsuo. Extension and validation of the model of hazard gas concentration distribution in sewer[J]. Chinese Journal of Environmental Engineering, 2019, 13(5): 1228-1236. doi: 10.12030/j.cjee.201901063
Citation: YAN Sen, DING Yanping, ZHENG Cailin, LIAO Bangyou, SONG Guangshun, CHEN Jun, LU Jinsuo. Extension and validation of the model of hazard gas concentration distribution in sewer[J]. Chinese Journal of Environmental Engineering, 2019, 13(5): 1228-1236. doi: 10.12030/j.cjee.201901063

污水管道危害性气体浓度分布模型扩展与验证

  • 基金项目:

    国家自然科学基金资助项目51778523国家自然科学基金资助项目(51778523)

Extension and validation of the model of hazard gas concentration distribution in sewer

  • Fund Project:
  • 摘要: 污水管道危害气体分布模型的建立对管道的维护管理具有重要意义。以SewerX模型为基础,将硫酸盐还原作为产生CO的主要生化过程,并入污水管道总生化反应体系,扩展SewerX模型,建立了污水管道内CO、H2S、CH4的浓度分布应用模型。将其应用到某市长度为4 100 m污水管道,管道危害气体浓度模拟结果与实测结果比对发现,浓度变化趋势一致,相关系数达到0.99以上,表明扩展模型具有实际应用价值。在一定设计流量下,可选择不同污水管道水力参数,应用扩展模型分析表明,合理选择参数可降低污水管道危害气体浓度。研究为污水管道内危害性气体浓度的预测提供参考。
  • 加载中
  • [1] 方德琼. 山地城市污水管道中有害气体的检测及分布规律研究[D]. 重庆: 重庆大学, 2012.
    [2] PIKAAR I, SHARMA K R, HU S, et al. Reducing sewer corrosion through integrated urban water management[J]. Science, 2014, 345(6198): 812-814.
    [3] OJHA V K, DUTTA P, CHAUDHURI A. Identifying hazardousness of sewer pipeline gas mixture using classification methods: A comparative study[J]. Neural Computing & Applications, 2016, 28(6): 1-12.
    [4] JIANG G, KELLER J, BOND P L. Determining the long-term effects of H2S concentration, relative humidity and air temperature on concrete sewer corrosion[J]. Water Research, 2014, 65: 157-169.
    [5] GUISASOLA A, HAAS D D, KELLER J, et al. Methane formation in sewer systems[J]. Water Research, 2008, 42(6/7): 1421-1430.
    [6] 张远, 吕淑然, 杨凯, 等. 城市污水管道甲烷爆炸防控对策研究现状及展望[J]. 安全与环境工程, 2015, 22(5): 134-138.
    [7] NIELSEN A H, VOLLERTSEN J, JENSEN H S, et al. Aerobic and anaerobic transformations of sulfide in a sewer system: Field study and model simulations[J]. Water Environment Research, 2008, 80(1): 16-25.
    [8] 李怀正, 张璐璇, 汤霞, 等. 城市排水管道中硫化氢产气原因及影响因素分析[J]. 环境科学与管理, 2012, 37(4): 95-97.
    [9] CHAOSAKUL T, KOOTTATEP T, POLPRASERT C. A model for methane production in sewers[J]. Environmental Letters, 2014, 49(11): 1316-1321.
    [10] GUISASOLA A, SHARMA K R, KELLER J, et al. Development of a model for assessing methane formation in rising main sewers[J]. Water Research, 2009, 43(11): 2874-2884.
    [11] HVITVEDJACOBSEN T, VOLLERTSEN J, NIELSEN A H, et al. Sewer Processes: Microbial and Chemical Process Engineering of Sewer Networks[M]. USA:CRC Press, 2013.
    [12] MOHAMMAD K, EHSAN D. Optimal design of wastewater collection networks based on production rate of hydrogen sulfide[J]. Life Science Journal, 2015, 12(8): 73-77.
    [13] SHARMA K R, YUAN Z, DE H D, et al. Dynamics and dynamic modelling of H2S production in sewer systems[J]. Water Research, 2008, 42(10/11): 2527-2538.
    [14] FOLEY J, YUAN Z, LANT P. Dissolved methane in rising main sewer systems: Field measurements and simple model development for estimating greenhouse gas emissions[J]. Water Science & Technology, 2009, 60(11): 2963-2971.
    [15] LIU Y, NI B, SHARMA K, et al. Methane emission from sewers[J]. Science of the Total Environment, 2015, 524-525: 40-51.
    [16] FIRER D, FRIEDLER E, LAHAV O. Control of sulfide in sewer systems by dosage of iron salts: Comparison between theoretical and experimental results, and practical implications[J]. Science of the Total Environment, 2008, 392(1): 145-156.
    [17] NIELSEN A H, HVITVEDJACOBSEN T, VOLLERTSEN J. Kinetics and stoichiometry of sulfide oxidation by sewer biofilms[J]. Water Research, 2005, 39(17): 4119-4125.
    [18] CALABRò P S, MANNINA G, VIVIANI G. In sewer processes: Mathematical model development and sensitivity analysis[J]. Water Science & Technology, 2009, 60(1): 107-115.
    [19] DONCKELS B M R, KROLL S, DORPE M VAN, et al. Global sensitivity analysis of an in-sewer process model for the study of sulfide-induced corrosion of concrete[J]. Water Science & Technology, 2014, 69(3): 647-655.
    [20] VOLLERTSEN J, HVITVEDJACOBSEN T. Stoichiometric and kinetic model parameters for microbial transformations of suspended solids in combined sewer systems[J]. Water Research, 1999, 33(14): 3127-3141.
    [21] VOLLERTSEN J, REVILLA N, HVITVEDJACOBSEN T, et al. Modeling sulfides, pH and hydrogen sulfide gas in the sewers of San Francisco[J]. Water Environment Research, 2015, 87(11): 1980-1989.
  • 加载中
计量
  • 文章访问数:  2574
  • HTML全文浏览数:  2520
  • PDF下载数:  93
  • 施引文献:  0
出版历程
  • 刊出日期:  2019-06-03

污水管道危害性气体浓度分布模型扩展与验证

  • 1. 西安建筑科技大学,西北水资源与环境生态教育部重点实验室,西安 710055
  • 2. 西安建筑科技大学管理学院,西安 710055
  • 3. 安康市市政设施管理处,安康 725000
  • 4. 西安市政设计研究院有限公司,西安 710068
基金项目:

国家自然科学基金资助项目51778523国家自然科学基金资助项目(51778523)

摘要: 污水管道危害气体分布模型的建立对管道的维护管理具有重要意义。以SewerX模型为基础,将硫酸盐还原作为产生CO的主要生化过程,并入污水管道总生化反应体系,扩展SewerX模型,建立了污水管道内CO、H2S、CH4的浓度分布应用模型。将其应用到某市长度为4 100 m污水管道,管道危害气体浓度模拟结果与实测结果比对发现,浓度变化趋势一致,相关系数达到0.99以上,表明扩展模型具有实际应用价值。在一定设计流量下,可选择不同污水管道水力参数,应用扩展模型分析表明,合理选择参数可降低污水管道危害气体浓度。研究为污水管道内危害性气体浓度的预测提供参考。

English Abstract

参考文献 (21)

目录

/

返回文章
返回