中国科学引文数据库(CSCD)来源期刊
中国科技核心期刊
环境科学领域高质量科技期刊分级目录T2级期刊
RCCSE中国核心学术期刊
美国化学文摘社(CAS)数据库 收录期刊
日本JST China 收录期刊
世界期刊影响力指数(WJCI)报告 收录期刊

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

城镇生活垃圾产量预测模型综述

吴凡 牛冬杰

郑凯凯, 周振, 周圆, 王燕, 周建春, 李激. 城镇污水处理厂进水中地下水、河水及雨水混入比例研究[J]. 环境工程, 2020, 38(7): 75-80. doi: 10.13205/j.hjgc.202007012
引用本文: 吴凡, 牛冬杰. 城镇生活垃圾产量预测模型综述[J]. 环境工程, 2021, 39(4): 128-133. doi: 10.13205/j.hjgc.202104020
ZHENG Kai-kai, ZHOU Zhen, ZHOU Yuan, WANG Yan, ZHOU Jian-chun, LI Ji. A QUANTITIVE STUDY ON PROPORTION OF GROUNDWATER, RIVER WATER AND RAINWATER IN INFLUENT OF URBAN WASTEWATER TREATMENT PLANTS[J]. ENVIRONMENTAL ENGINEERING , 2020, 38(7): 75-80. doi: 10.13205/j.hjgc.202007012
Citation: WU Fan, NIU Dong-jie. REVIEW ON PREDICTIVE MODELS FOR MUNICIPAL SOLID WASTE PRODUCTION[J]. ENVIRONMENTAL ENGINEERING , 2021, 39(4): 128-133. doi: 10.13205/j.hjgc.202104020

城镇生活垃圾产量预测模型综述

doi: 10.13205/j.hjgc.202104020
基金项目: 

国家重点研发计划固废资源化重点专项"生活垃圾分类回收模式与智慧环卫关键设备"(2018YFC1900701)。

详细信息
    作者简介:

    吴凡(1996-),男,硕士研究生,主要研究方向为生活垃圾模型预测。1830574@tongji.edu.cn

    通讯作者:

    牛冬杰(1973-),女,副教授,硕士生导师,主要研究方向为固体废弃物处理与资源化利用。niudongjie@tongji.edu.cn

REVIEW ON PREDICTIVE MODELS FOR MUNICIPAL SOLID WASTE PRODUCTION

  • 摘要: 城镇生活垃圾产生情况的预测,对于城镇生活垃圾的规划和后续处置有实际参考意义。将已研究的模型进行梳理,将其分为适用于大范围预测的回归分析模型和适用于小范围精准预测的时间序列模型2大类,并对每一大类下各小类模型具体比较分析。并将城镇生活垃圾产生的影响因素分为地区整体因素、居民生活因素和其他因素3类,并对每一类因素的选取情况进行分别讨论;最后对预测过程中区域规模的选择、时间间隔的确定和输入变量的选择3个主要步骤提出参考意见,并对城镇生活垃圾产量预测模型目前尚存的问题进行总结。
  • [1] 张海龙, 李祥平, 齐剑英, 等. 华南某市生活垃圾组成特征分析[J]. 环境科学, 2015, 36(1):325-332.
    [2] 徐盼, 郑有飞, 吴荣军, 等. 我国城市生活垃圾的产生和处理现状分析[J]. 环境卫生工程, 2013, 21(6):13-15.
    [3] DUAN N, LI D, WANG P, et al. Comparative study of municipal solid waste disposal in three Chinese representative cities[J]. Journal of Cleaner Production, 2020, 254:120134.
    [4] KUMAR J S, SUBBAIAH K V, RAO P V V P. Prediction of municipal solid waste with RBF net work:a case study of Eluru, A. P, India[J]. International Journal of Innovation, Management and Technology, 2011, 2(3):238-243.
    [5] HANNAN M A, ABDULLA AL MAMUN M, Hussain A, et al. A review on technologies and their usage in solid waste monitoring and management systems:issues and challenges[J]. Waste Management, 2015, 43:509-523.
    [6] KORAI M S, MAHAR R B, UQAILI M A. The feasibility of municipal solid waste for energy generation and its existing management practices in Pakistan[J]. Renewable and Sustainable Energy Reviews, 2017, 72:338-353.
    [7] FU H Z, LI Z S, WANG R H. Estimating municipal solid waste generation by different activities and various resident groups in five provinces of China[J]. Waste Management, 2015, 41:3-11.
    [8] BEIGL P, LEBERSORGER S, SALHOFER S. Modelling municipal solid waste generation:a review[J]. Waste Management, 2008, 28(1):200-214.
    [9] KOLEKAR K A, HAZRA T, CHAKRABARTY S N. A review on prediction of municipal solid waste generation models[J]. Procedia Environmental Sciences, 2016, 35:238-244.
    [10] GHINEA C, DRAGOI E N, COMANITA E D, et al. Forecasting municipal solid waste generation using prognostic tools and regression analysis[J]. Journal of Environmental Management, 2016, 182:80-93.
    [11] 李海红, 巩雪松, 同帜. 多元线性回归预测模型在农村生活垃圾产量预测中的应用[J]. 西南农业学报, 2010, 23(4):1324-1328.
    [12] AZADI S, KARIMI-JASHNI A. Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate:a case study of Fars province, Iran[J]. Waste Management, 2016, 48:14-23.
    [13] ABDOLI M A, NEZHAD M F, SEDE R S, et al. Longterm forecasting of solid waste generation by the artificial neural networks[J]. Environmental Progress & Sustainable Energy, 2012, 31(4):628-636.
    [14] RIMAITYTE I, RUZGAS T, DENAFAS G, et al. Application and evaluation of forecasting methods for municipal solid waste generation in an Eastern-European city[J]. Waste Management Research, 2012, 30(1):89-98.
    [15] YANG Y, ZHANG J. A prediction on electronic waste resource with time series model[C]//2010 International Conference on Computer Application and System Modeling, 2010.
    [16] NAVARRO-ESBRI J, DIAMADOPOULOS E, GINESTAR D. Time series analysis and forecasting techniques for municipal solid waste management[J]. Resources, Conservation and Recycling, 2002, 35:201-214.
    [17] MARANDI F, FATEMI GHOMI S M T. Time series forecasting and analysis of municipal solid waste generation in Tehran city[C]//12th International Conference on Industrial Engineering, 2016.
    [18] HIMAN S, SAEED K, BAHARIN Bin A, et al. Application of artificial neural network in prediction of municipal solid waste generation[J]. World Applied Sciences Journal, 2012, 20:336-343.
    [19] NOORI R, KARBASSI A, SALMAN Sabahi M. Evaluation of PCA and Gamma test techniques on ANN operation for weekly solid waste prediction[J]. Journal of Environmental Management, 2010, 91(3):767-71.
    [20] KANNANGARA M, DUA R, AHMADI L, et al. Modeling and prediction of regional municipal solid waste generation and diversion in Canada using machine learning approaches[J]. Waste Management, 2018, 74:3-15.
    [21] VU H L, NG K T W, BOLINGBROKE D. Time-lagged effects of weekly climatic and socio-economic factors on ANN municipal yard waste prediction models[J]. Waste Management, 2019, 84:129-140.
    [22] 舒莹. 基于灰色预测模型的合肥市城市生活垃圾产量预测[J]. 环境科学与管理, 2007, 32(9):5-8.
    [23] 李银, 吴振家, 位瑞英. 基于灰色Verhulst模型预测韶关市生活垃圾产量[J]. 韶关学院学报, 2016,37(6):1-5.
    [24] INTHARATHIRAT R, ABDUL Salam P, KUMAR S, et al. Forecasting of municipal solid waste quantity in a developing country using multivariate grey models[J]. Waste Management, 2015, 39:3-14.
    [25] WEI Y, XUE Y, YIN J, et al. Prediction of municipal solid waste generation in china by multiple linear regression method[J]. International Journal of Computers and Applications, 2013, 35(3):13-22.
    [26] JALILI GHAZI M, NOORI R. Prediction of municipal solid waste generation by use of artificial neural network a case study of mashhad[J]. International Journal of Environmental Research, 2007, 2(1):13-22.
    [27] ABIDOYE L K, MAHDI F M, IDRIS M O, et al. ANN-derived equation and ITS application in the prediction of dielectric properties of pure and impure CO2[J]. Journal of Cleaner Production, 2018, 175:123-132.
    [28] MA J, DING Y, CHENG J C P, et al. A temporal-spatial interpolation and extrapolation method based on geographic Long Short-Term Memory neural network for PM2.5[J]. Journal of Cleaner Production, 2019, 237:1-11.
    [29] ANTANASIJEVIĆ D, POCAJT V, POPOVIĆ I, et al. The forecasting of municipal waste generation using artificial neural networks and sustainability indicators[J]. Sustainability Science, 2012, 8(1):37-46.
    [30] ABBASI M, El HANANDEH A. Forecasting municipal solid waste generation using artificial intelligence modelling approaches[J]. Waste Management, 2016, 56:13-22.
    [31] YOUNES M K, NOPIAH Z M, BASRI N E, et al. Landfill area estimation based on integrated waste disposal options and solid waste forecasting using modified ANFIS model[J]. Waste Management, 2016, 55:3-11.
    [32] 张旺. 基于Elman神经网络的城市生活垃圾清运量预测模型研究[D]. 武汉:湖北工业大学, 2017.
    [33] 郭华, 李佳美, 邱明杰, 等. 我国生活垃圾产量的多元线性回归预测分析[J]. 环境与发展, 2018(1):61-63.
    [34] 秦绪佳, 彭洁, 徐菲, 等. 基于RBF网络的城市垃圾产量预测及可视化[J]. 中国环境科学, 2018, 38(2):792-800.
    [35] CHEN H W, CHANG N B. Prediction analysis of solid waste generation based on grey fuzzy dynamic modeling[J]. Resources, Conservation and Recycling, 2000, 29:1-18.
    [36] ORIBE-GARCIA I, KAMARA-ESTEBAN O, MARTIN C, et al. Identification of influencing municipal characteristics regarding household waste generation and their forecasting ability in Biscay[J]. Waste Management, 2015, 39:26-34.
    [37] WU F, NIU D J, DAI S J, et al. New insights into regional differences of the predictions of municipal solid waste generation rates using artificial neural networks[J]. Waste Management, 2020, 107:182-190.
    [38] MONAVARI S M, OMRANI G A, KARBASSI A, et al. The effects of socioeconomic parameters on household solid-waste generation and composition in developing countries (a case study:Ahvaz, Iran)[J]. Environmental Monitoring and Assessment, 2012, 184(4):1841-1846.
    [39] BANDARA N J, HETTIARATCHI J P, WIRASINGHE S C, et al. Relation of waste generation and composition to socio-economic factors:a case study[J]. Environmental Monitoring and Assessment, 2007, 135(1/2/3):31-39.
    [40] AGUILAR-VIRGEN Q, TABOADA-GONZALEZ P, OJEDA-BENITEZ S. Seasonal analysis of the generation and composition of solid waste:potential use:a case study[J]. Environmental Monitoring Assessment, 2013, 185(6):4633-4645.
    [41] EDJABOU M E, JENSEN M B, GOTZE R, et al. Municipal solid waste composition:sampling methodology, statistical analyses, and case study evaluation[J]. Waste Management, 2015, 36:12-23.
    [42] DENAFAS G, RUZGAS T, MARTUZEVI AČG1 IUS D, et al. Seasonal variation of municipal solid waste generation and composition in four East European cities[J]. Resources, Conservation and Recycling, 2014, 89:22-30.
    [43] GIDARAKOS E, HAVAS G, NTZAMILIS P. Municipal solid waste composition determination supporting the integrated solid waste management system in the island of Crete[J]. Waste Management, 2006, 26(6):668-679.
    [44] NOORI R, ABDOLI M A, FAROKHNIA A, et al. Results uncertainty of solid waste generation forecasting by hybrid of wavelet transform-ANFIS and wavelet transform-neural network[J]. Expert Systems with Applications, 2009, 36(6):9991-9999.
    [45] SOTAMENOU J, DE JAEGER S, ROUSSEAU S. Drivers of legal and illegal solid waste disposal in the Global South:the case of households in Yaounde (Cameroon)[J]. Journal of Environmental Management, 2019, 240:321-330.
    [46] OJEDA-BENÍTEZ S, VEGA C A-D, MARQUEZ-MONTENEGRO M Y. Household solid waste characterization by family socioeconomic profile as unit of analysis[J]. Resources, Conservation and Recycling, 2008, 52(7):992-999.
    [47] KUMAR A, SAMADDER S R. An empirical model for prediction of household solid waste generation rate:a case study of Dhanbad, India[J]. Waste Management, 2017, 68:3-15.
    [48] NOORI R, KARBASSI A, MEHDIZADEH H, et al. A framework development for predicting the longitudinal dispersion coefficient in natural streams using an artificial neural network[J]. Environmental Progress & Sustainable Energy, 2011, 30(3):439-449.
    [49] POURREZA MOVAHED Z, KABIRI M, RANJBAR S, et al. Multi-objective optimization of life cycle assessment of integrated waste management based on genetic algorithms:a case study of Tehran[J]. Journal of Cleaner Production, 2020, 247:1-12.
    [50] NOORI R, ABDOLI M, JALILI GHAZIZADE M, et al. Comparison of ANN and PCA based multivariate linear regression applied to predict the weekly municipal solid waste generation in Tehran[J]. Iranian Journal of Public Health, 2009, 38(1):74-84.
  • 期刊类型引用(11)

    1. 何宽畅,冯诗洋,杨文剑,杨奎,尹征,何燕生,马金星. 基于合成电化学技术的水中污染物增值转化研究进展. 能源环境保护. 2025(01): 34-47 . 百度学术
    2. 赵霞,石诗义,毛杨,武桢寓. 城市污水处理厂的“水-能-碳”协调调度模型. 电网技术. 2024(05): 1918-1928 . 百度学术
    3. 涂倩倩,沈鹏飞,刘鸣燕,张梓璇,余波,杨凯. 城镇污水处理厂碳排放核算方法及特征. 净水技术. 2024(06): 52-62 . 百度学术
    4. 于翔,潘兴朋,王永乐. 浅析化工污水处理装置的改进创新措施和社会效益. 中国轮胎资源综合利用. 2024(12): 67-69 . 百度学术
    5. 李哲坤,张立秋,杜子文,封莉,刘永泽. 城市污泥不同处理处置工艺路线碳排放比较. 环境科学. 2023(02): 1181-1190 . 百度学术
    6. 任南琪,王旭. 城市水系统发展历程分析与趋势展望. 中国水利. 2023(07): 1-5 . 百度学术
    7. 纪义虎,左其亭,马军霞. 基于Tapio和LMDI模型的沁河流域碳排放与水资源利用脱钩关系分析. 水资源保护. 2023(04): 94-101 . 百度学术
    8. 谢琤琤,刘刚. 城市污水处理厂碳中和路径解析. 环境工程. 2023(09): 181-186 . 本站查看
    9. 蒲贵兵,王鹏,卫然. 基于城市生活污水系统全生命周期的直接碳减排路径研究. 环境科学与管理. 2023(10): 11-16 . 百度学术
    10. 张海亚,李思琦,黎明月,段亮,张洪伟,秦伟,赵立伟,刘鹏,吕云龙,王玉龙. 城镇污水处理厂碳排放现状及减污降碳协同增效路径探讨. 环境工程技术学报. 2023(06): 2053-2062 . 百度学术
    11. 李天昕,翁锐,徐新朋,程世昆,杨朕,李勇,李子富. 基于还田视角的人粪尿处理研究进展. 农业资源与环境学报. 2023(06): 1388-1399 . 百度学术

    其他类型引用(2)

  • 加载中
计量
  • 文章访问数:  512
  • HTML全文浏览量:  52
  • PDF下载量:  43
  • 被引次数: 13
出版历程
  • 收稿日期:  2020-04-26
  • 网络出版日期:  2021-07-21

目录

    /

    返回文章
    返回