Evidence map›Paper›PMID 40210653›Full record

ArticleScientific data2025

A high resolution gridded dataset for takeaway packaging waste in China.

Pingda Lu, Ya Zhou, Qiuli Liu, Aiqun Guan, Zhifeng Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Pingda LuGuangdong Basic Research Center of Excellence for Ecological Security and Green Development, Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China.
Ya ZhouGuangdong Basic Research Center of Excellence for Ecological Security and Green Development, Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China. yazhou@gdut.edu.cn.ORCID http://orcid.org/0000-0002-1960-8900
Qiuli LiuGuangdong Basic Research Center of Excellence for Ecological Security and Green Development, Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China.
Aiqun GuanGuangdong Basic Research Center of Excellence for Ecological Security and Green Development, Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China.ORCID http://orcid.org/0009-0004-6176-7974
Zhifeng YangGuangdong Basic Research Center of Excellence for Ecological Security and Green Development, Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52170179National Natural Science Foundation of China (National Science Foundation of China) 52222007
6 · The paper itself

Abstract

The rapid growth of the takeaway industry has generated considerable takeaway packaging waste (TPW). Current research focuses on the environmental impacts from takeaway packaging at the regional or city level, which may offer limited implications for localized targeted policymaking. In this study, a high-resolution gridded dataset is provided for annual estimates of TPW in China at a grid resolution of 1 km × 1 km. Seven takeaway packaging categories and their usage probabilities are considered in the estimation, and the results are spatially distributed at the grid scale based on the geographic scope of takeaway delivery. The dataset reveals that a total of 366.66 kt of TPW were generated in China in 2018. The top 10% of grids with the highest TPW generation accounted for 64% of the national TPW. The TPW hotspots are typically located in commercial and residential areas. This dataset could promote effective management of TPW, and support strategies to reduce municipal solid waste in line with the "Zero-waste City" program.

Identifiers

PMID40210653
PMCPMC11985967

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.