PMID- 36121689
OWN - NLM
STAT- MEDLINE
DCOM- 20221207
LR  - 20221216
IS  - 2162-2906 (Electronic)
IS  - 1096-2247 (Linking)
VI  - 72
IP  - 12
DP  - 2022 Dec
TI  - Evaluation on production trend, compositions, and impact of plastic waste in 
      Chengdu, southwestern China.
PG  - 1454-1462
LID - 10.1080/10962247.2022.2126558 [doi]
AB  - 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 CO(2), 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.
FAU - Zhao, Xue
AU  - Zhao X
AUID- ORCID: 0000-0002-4700-0919
AD  - Sichuan Academy of Eco-Environmental Sciences, Chengdu, People's Republic of 
      China.
FAU - Yong, Yi
AU  - Yong Y
AD  - Sichuan Academy of Eco-Environmental Sciences, Chengdu, People's Republic of 
      China.
FAU - Du, Cheng-Song
AU  - Du CS
AD  - Chengdu Academy of Urban Environmental Management Science, Chengdu, People's 
      Republic of China.
FAU - Guo, Wei-Guang
AU  - Guo WG
AD  - Sichuan Academy of Eco-Environmental Sciences, Chengdu, People's Republic of 
      China.
FAU - Luo, Da-Peng
AU  - Luo DP
AD  - Sichuan Academy of Eco-Environmental Sciences, Chengdu, People's Republic of 
      China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20221026
PL  - United States
TA  - J Air Waste Manag Assoc
JT  - Journal of the Air & Waste Management Association (1995)
JID - 9503111
RN  - MLT3645I99 (bisphenol A)
RN  - 0 (Plastics)
RN  - 0 (Solid Waste)
RN  - 0 (Particulate Matter)
SB  - IM
MH  - Plastics
MH  - *Refuse Disposal/methods
MH  - Solid Waste/analysis
MH  - Waste Disposal Facilities
MH  - *Waste Management/methods
MH  - China
MH  - Particulate Matter
EDAT- 2022/09/20 06:00
MHDA- 2022/12/17 06:00
CRDT- 2022/09/19 11:53
PHST- 2022/09/20 06:00 [pubmed]
PHST- 2022/12/17 06:00 [medline]
PHST- 2022/09/19 11:53 [entrez]
AID - 10.1080/10962247.2022.2126558 [doi]
PST - ppublish
SO  - J Air Waste Manag Assoc. 2022 Dec;72(12):1454-1462. doi: 
      10.1080/10962247.2022.2126558. Epub 2022 Oct 26.