System dynamics-based prediction of municipal solid waste generation in high-cold and high-altitude area: The case of Lhasa, Tibet

被引:3
|
作者
Liu, Hongbo [1 ]
Zhang, Qinxiao [1 ]
Xue, Zhuyuan [1 ]
Zhuang, Xinying [2 ]
Li, Jiacong [1 ]
机构
[1] Tianjin Univ, Sch Environm Sci & Engn, Tianjin 300354, Peoples R China
[2] Liupanshui Normal Univ, Sch Chem & Mat Engn, Liupanshui, Peoples R China
关键词
System dynamics; municipal solid waste; prediction; high-cold and high-altitude area; Lhasa; reduction; classification; MULTIVARIABLE REGRESSION-ANALYSIS; MATERIAL FLOW-ANALYSIS; LANDFILL; ISLAND; CHINA;
D O I
10.1177/0734242X221084077
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The ecological environment in high-cold and high-altitude area is fragile and sensitive, which raise higher claim for municipal solid waste (MSW) management. In the high-cold and high-altitude area, there are problems, such as the mismatch between the actual amount of MSW generated and the scale of transportation and treatment facilities, and the inefficiency of MSW management. In terms of MSW forecasting methods, it is also difficult to forecast due to the lack of data. This study is the first to propose a system dynamics-based method for predicting the amount of MSW generated in high-cold and high-altitude area, and apply it to Lhasa. The research results show that the total amount of MSW generated in Lhasa is small, but the growth rate is fast. Through dynamic simulation, it is found that the synergistic consideration of gross domestic product (GDP) growth rate, urban construction policy and tourism development policy can significantly reduce the growth trend (14% emission reduction in 2030). In addition, strengthening supervision and restraint, publicity and education in high-cold and high-altitude area can produce better waste sorting effects, minimise the pressure on treatment facilities, and improve resource utilisation. Finally, the policy implications are suggested, for example, in the process of MSW management, the impact of economy, urbanisation, tourism and so on, should be taken into account and comprehensively adjusted. It is anticipated that this model and policy implications can be applied to other high-cold and high-altitude cities to provide data support and policy reference for the whole-process management of MSW.
引用
收藏
页码:1555 / 1567
页数:13
相关论文
共 14 条
  • [11] Machine learning tool-based prediction and forecasting of municipal solid waste generation rate: a case study in Guwahati, Assam, India
    T. Singh
    R. V. S. Uppaluri
    International Journal of Environmental Science and Technology, 2023, 20 : 12207 - 12230
  • [12] Forecasting municipal solid plastic waste generation and management policy using system dynamics: a case study of Khulna City in Bangladesh
    Rafizul, Islam M.
    Kraft, Eckhard
    Haupt, Thomas
    Rafew, S. M.
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2024, 196 (06)
  • [13] Urban Spatial Decision Support System for Municipal Solid Waste Management of Nagpur Urban Area Using High-Resolution Satellite Data and Geographic Information System
    Katpatal, Yashwant B.
    Rao, B. V. S. Rama
    JOURNAL OF URBAN PLANNING AND DEVELOPMENT-ASCE, 2011, 137 (01): : 65 - 76
  • [14] Prediction of municipal solid waste generation and analysis of dominant variables in rapidly developing cities based on machine learning - a case study of China
    Zhao, Ying
    Tao, Zhe
    Li, Ying
    Sun, Huige
    Tang, Jingrui
    Wang, Qianya
    Guo, Liang
    Song, Weiwei
    Li, Bailian Larry
    WASTE MANAGEMENT & RESEARCH, 2024, 42 (06) : 476 - 484