作者：赵锐, 赵丽萍, 陈静芳, 刘婕, 李敏

作者单位：西南交通大学地球科学与环境工程学院，四川 成都 611756

关键词：垃圾渗滤液;结垢;预测;BP神经网络;HDPE管材

摘要：

垃圾渗滤液含有大量复杂的有害成分，在集输过程中极易引起管道结垢，增加处理处置设施运营成本和环境风险。该研究设计将高密度聚乙烯(HDPE)管材浸置于模拟渗滤液中开展结垢实验，通过称重、FTIR、SEM、XRD等表征手段，考察HDPE管材在渗滤液中的结垢特征及垢物组成，以实验数据为基础，利用BP神经网络驱动构建结垢预测模型，分析影响结垢的主要水质因素。结果表明：ρ(Ca²⁺)是影响结垢的关键因素，其次为ρ(腐殖质)、 ρ(COD)、pH值、ρ(NaHCO₃)和ρ(Cl^–)；垢物的主要成分是CaCO₃，结垢过程是CaCO₃沉淀与腐殖质络合物等共同粘附沉积的结果；所建模型的预测结果与实验结果的平均相对误差为11.7%，具有较好的预测渗滤液集输管道结垢的应用潜力，可为渗滤液集输系统堵塞防治提供决策参考。

Pipe scaling prediction based on BP neural network for landfill leachate transport
ZHAO Rui, ZHAO Liping, CHEN Jingfang, LIU Jie, LI Min
Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
Abstract: Leachate contains a large number of complex harmful components, which is easy to cause pipe scaling during the transport process, increasing the cost of disposal facilities and environmental risks. In this study, high-density polyethylene (HDPE) pipe samples were immersed in simulated leachate to carry out a scaling experiment. The scale composition and scaling characteristics in the leachate were investigated through characterizations of weighing, FTIR, SEM, and XRD. Based on the experimental data, the scaling prediction model is constructed by BP neural network method, and the main factors of leachate quality affecting scaling were analyzed. The results show that the ρ(Ca²⁺) is the key factor affecting scaling, followed by ρ(humus), ρ(COD), pH value, ρ(NaHCO₃), and ρ(Cl^–). The main component of the scale is the CaCO₃ crystal, and its precipitation adheres to the humus complex to form the scale. The relative error between the scaling prediction results of the model and the experimental results is 11.7%, indicating that it has a good application potential to predict the leachate transportation pipe scaling, and is expected to provide a decision-making tool for the prevention and control of blockage of leachate collection and transportation system.
Keywords: leachate;scaling;prediction;BP neural network;HDPE pipe materials
2022, 48(7):1-7  收稿日期: 2022-04-11;收到修改稿日期: 2022-05-27
基金项目: 国家重点研发计划专项(2019YFC1905600)；国家自然科学基金项目(41571520)；四川省青年科技创新团队资助(2022JDTD0005)；四川循环经济研究中心课题 (XHJJ-2002，XHJJ-2005)；中央高校基本科研业务费专项资金 (2682021ZTPY088)
作者简介: 赵锐（1983-），男，四川南充市人，教授，博士，主要从事环境系统工程研究
参考文献
[1] LUO H W, ZENG Y F, CHENG Y, et al. Recent advances in municipal landfill leachate: A review focusing on its characteristics, treatment, and toxicity assessment[J]. Science of the Total Environment, 2020, 703: 135468
[2] ZHAO R, WANG X Q, CHEN X L, et al. Impacts of different aged landfill leachate on PVC corrosion[J]. Environmental Science and Pollution Research, 2019, 26(18): 18256-18266
[3] 郭希, 李佳, 陈弹霓. 垃圾渗滤液输送系统堵塞的研究进展[J]. 广东化工, 2019, 46(6): 142-143
[4] XIA Y, ZHANG H, PHOUNGTHONG K, et al. Leaching characteristics of calcium-based compounds in MSWI Residues: From the viewpoint of clogging risk[J]. Waste Management, 2015, 42: 93-100
[5] LI Z Z, XUE Q, LIU L, et al. Precipitates in landfill leachate mediated by dissolved organic matters[J]. Journal of Hazardous Materials, 2015, 287: 278-286
[6] CORSINO S F, CAPODICI M, DANIELE D T, et al. Assessment of landfill leachate biodegradability and treatability by means of allochthonous and autochthonous biomasses[J]. New Biotechnology, 2020, 55: 91-97
[7] SACKEY L N A, VLADIMIR K, GESTEL C A M. Ecotoxicological effects on Lemna minor and Daphnia magna of leachates from differently aged landfills of Ghana[J]. Science of the Total Environment, 2020, 698: 134295
[8] FLEMING I R, ROWE R K. Laboratory studies of clogging of landfill leachate collection and drainage systems[J]. Canadian Geotechnical Journal, 2004, 41(1): 134-153
[9] RITTMANN B E, BANASZAK J E, COOKE A, et al. Biogeochemical evaluation of mechanisms controlling CaCO₃(s) precipitation in landfill leachate-collection systems[J]. Journal of Environmental Engineering, 2003, 129(8): 723-730
[10] 李敏, 赵锐, 杨天学, 等. 不同填埋年龄期垃圾渗滤液对HDPE管材结垢影响[J]. 环境科学研究, 2021, 34(5): 1148-1156
[11] 满瑞林, 白鸽玲, 陈石. 垃圾填埋渗沥液输送管道结垢物剖析[J]. 环保科技, 2002, 8(2): 4-7
[12] 王小倩. 垃圾渗滤液输运管道结垢腐蚀研究进展[J]. 风景名胜, 2019(1): 267, 276
[13] 冯凌宇. 垃圾渗滤液阻垢预处理技术的研究进展[J]. 净水技术, 2021, 40(3): 48-52
[14] LI Z Z. Modeling precipitate-dominant clogging for landfill leachate with NICA-Donnan theory[J]. Journal of Hazardous Materials, 2014, 274: 413-419
[15] SHAHA B N, MEEROFF D E, KOHN K, et al. Effect of electronic water treatment system on calcium carbonate scale formation in landfill leachate collection piping[J]. Journal of Environmental Engineering, 2019, 145(9): 04019052
[16] XIE M J, LI Z S, ZHAO J L, et al. A prognostics method based on back propagation neural network for corroded pipelines[J]. Micromachines, 2021, 12(12): 1568
[17] 生活垃圾卫生填埋处理技术规范: GB50869—2013[S]. 北京: 中国建筑工业出版社, 2013.
[18] 孙巧萍, 段翠九, 任丽梅, 等. 渗沥液浓缩液对设备的结垢腐蚀研究[J]. 环境卫生工程, 2017, 25(6): 58-59
[19] 王前. 焚烧炉渣混填对渗滤液导排系统土工布生物结垢影响及机理研究[D]. 北京: 北京大学, 2021.
[20] 史谦. 厌氧发生器UBF+膜生物反应器+超滤+纳滤+反渗透工艺在生活垃圾焚烧发电厂渗滤液处理中的应用[J]. 中国建材科技, 2018, 10(9): 150-152
[21] 康广凤, 宁海丽, 左华. MBR+膜分离技术处理生活垃圾焚烧厂渗滤液工程研究[J]. 环境保护科学, 2018, 44(6): 90-95
[22] 曾武, 邹卫东, 陈清, 等. 芬顿组合工艺处理垃圾焚烧电厂渗滤液处理厂反渗透浓缩液的中试研究[J]. 广东化工, 2018, 45(7): 205-206
[23] 花发奇, 唐湘姬. 生活垃圾焚烧发电厂渗滤液处理工程实例[J]. 中国新技术新产品, 2018(17): 38-39
[24] 陈春俊, 杨露, 何智颖, 等. ARIMA-BP神经网络高速列车隧道压力波预测模型研究[J]. 中国测试, 2021, 47(10): 80-86
[25] 王岩. 深度神经网络的归一化技术研究[D]. 南京: 南京邮电大学, 2019.
[26] 王晓辉, 刘静蕾, 边会娟, 等. 基于改进BP神经网络的室内环境热舒适度预测与分析[J]. 控制工程, 2021, 28(7): 1437-1445
[27] 廖连莹, 左言言, 周翔, 等. 基于GA-BP的混合动力汽车匀速工况声品质预测模型[J]. 中国测试, 2019, 45(5): 128-133
[28] PETER L B, MARTIN A. Neural network learning: theoretical foundations[M]. New York: Cambridge University Press, 1999: 112-345.
[29] 蒋华义, 蔡航航, 梁爱国, 等. 碱对镀锌铁表面CaCO₃污垢生长特性的影响机理研究[J]. 化工学报, 2019, 70(1): 170-178
[30] 向杰鹏. 蒸发工艺处理危险废物填埋场渗滤液中pH值的优化研究[J]. 广东化工, 2021, 48(15): 152-153
[31] HERZ A, MALAYERI M R, MüLLER-STEINHAGEN H. Fouling of roughened stainless steel surfaces during convective heat transfer to aqueous solutions[J]. Energy Conversion and Management, 2008, 49(11): 3381-3386
[32] CHO D W, KWON G, HAN J, et al. Influence of humic acid on the long-term performance of direct contact membrane distillation[J]. Energy & Environment, 2019, 30(1): 109-120
[33] VANGULCK J F, ROWE R K. Evolution of clog formation with time in columns permeated with synthetic landfill leachate[J]. Journal of Contaminant Hydrology, 2004, 75: 115-139
[34] MANNING D A. Carbonates and oxalates in sediments and landfill: monitors of death and decay in natural and artificial systems[J]. Journal of the Geological Society, 2000, 157(1): 229-238
[35] MALIVA R G, MISSIMER T M, LEO K C, et al. Unusual calcite stromatolites and pisoids from a landfill leachate collection system[J]. Geology, 2000, 28(10): 931-934