ABSTRACT
Based on statistical data from 2005 to 2019, we used the back propagation (BP) neural network model to predict the production amount of plastic waste in Chengdu. In addition to the amount of waste produced we wanted to achieve an understanding of its composition and environmental impacts. Compositions of plastic waste were analyzed by sampling. Particulate matter in the air and greenhouse gas emissions (GHGs) from plastic waste incineration, bisphenol A (BPA) from plastic waste landfills, were also evaluated. Results indicated that (a) economic development, urban construction level, and residents’ consumption were pusitively correlated to different degrees to plastic waste production; (b) the production of plastic waste in Chengdu in 2025 and 2030 will reach 865.3 and 931 kilotons (Kt), respectively; (c) high density polyethylene (HDPE) and polypropylene (PP) are the two main components of plastic waste in Chengdu and accounted for 40.17% and 24.96%, respectively; (d) different degrees of environmental impacts occurred during plastic waste incineration and landfill (taking 2019 as an example, the incineration of plastic waste in Chengdu produced between 2874.82 and 4711.73 tons of inhalable particulate matter (PM) and emitted between 725.4 and 867.4 Kt of CO2, and between 65.02 and 910.27 kg of bisphenol A (BPA) leached from sanitary landfills); (e) positive policies and measures from the beginning to the end-of-life of plastics should be carried out in the future, which would improve the level of plastic waste management in Chengdu and mitigate the side-impacts from plastic waste treatment and disposal.
Implications: The implications of this article are
Generation trends of plastic waste were revealed by a BP neural network model, which provided essential data for authorities to make decisions on waste management.
Influencing factors affecting plastic waste generation were analyzed, which will strongly support policy considerations regarding plastic waste control.
This investigation first explored and reported the compositions of plastic waste mixed with municipal solid waste (MSW), which yielded valuable information concerning plastic waste and details concerning the impacts of plastic waste disposal processes.
Those results of this investigation, being published here for the first time, will guide plastic waste management in Chengdu and could also provide useful information to other cities regarding that issue.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/10962247.2022.2126558
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Notes on contributors
Xue Zhao
Xue Zhao graduated from Chongqing University in 2017 and received doctor’s degree of Environmental Sciences and Engineering, then worked in Postdoctoral Workstation of CPI Yuanda Environmental Protection engineering Co., Ltd and School of environment, Tsinghua University, gained the postdoctoral certificate in 2020, and now is senior engineer for environmental engineering, work in Sichuan Academy of Eco-Environmental Sciences, and focus on the fields of waste management and utilization, emerging pollutants investigation and control etc.
Yi Yong
Yi Yong is the chief of the department of waste treatment technology, Sichuan Academy of Eco-Environmental Sciences, have been worked in Environment protection for more than 30 years.
Cheng-Song Du
Cheng-Song Du is senior engineer and work in Chengdu Academy of Urban Environmental Management Science.
Wei-Guang Guo
Wei-Guang Guo graduated from Peking University in and received master degree of Environmental Science, now is senior engineer and work in Sichuan Academy of Eco-Environmental Sciences.
Da-Peng Luo
Da-Peng Luo is engineer and work in Sichuan Academy of Eco-Environmental Sciences.