Evidence map›Paper›PMID 41760679›Full record

ArticleScientific data2026

China material stocks and flows account for 2019-2023.

Jiayun Huang, Guochun Huang, Lulu Song, Wei-Qiang Chen

Abstract read
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Jiayun HuangState Key Laboratory of Regional and Urban Ecology, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen, Fujian Province, 361021, P. R. China.
Guochun HuangState Key Laboratory of Regional and Urban Ecology, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen, Fujian Province, 361021, P. R. China.
Lulu SongState Key Laboratory of Regional and Urban Ecology, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen, Fujian Province, 361021, P. R. China. llsong@iue.ac.cn.
Wei-Qiang ChenState Key Laboratory of Regional and Urban Ecology, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen, Fujian Province, 361021, P. R. China. wqchen@iue.ac.cn.

Funding

External Cooperation Program of Fujian Science and Technology Department 2023I0036Natural Science Foundation of China 42471316Natural Science Foundation of Fujian 2024J010043
6 · The paper itself

Abstract

China is the world's largest consumer of bulk materials, and the accumulation of material stocks and flows plays a critical role in shaping its socioeconomic metabolism and environmental sustainability. Detailed and up-to-date provincial-level data on material stocks and flows are therefore essential for understanding resource use and supporting regional sustainability transitions. This study presents the most recent update of the Provincial Material Stocks and Flows Database (PMSFD), extending our previous dataset for 1978-2018 to cover the years 1978-2023. The PMSFD provides consistent time-series data for 31 provinces and 13 bulk material categories across five key end-use sectors, compiled using a bottom-up material flow analysis framework that integrates official statistics and standardized estimation methods. Compared with the earlier version, the updated PMSFD captures the recent slowdown in material accumulation and reveals the regional heterogeneity. The data can be applied to studies on material metabolism, resource efficiency, circular economy strategies, and embodied carbon emissions accounting, as well as to inform regional and national sustainability policymaking in China.

Identifiers

PMID41760679
PMCPMC13065793

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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.