Evidence map›Paper›PMID 41006336›Full record

ArticleScientific data2025

A global dataset for steel aluminum and cement in-use stocks at 500 m gridded level 2000-2019.

Kun Sun, Qiaoxuan Li, Menglin Dai, Hongwei Guo, Qiance Liu, Jinchao Song, Zuoqi Chen, Srinivasa Raghavendra Bhuvan Gummidi, Wu Chen, Bailang Yu and 1 more

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

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

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

11 authors.

Kun SunSDU Life Cycle Engineering, Department of Green Technology, University of Southern Denmark, Odense, 5230, Denmark.ORCID http://orcid.org/0000-0003-1234-6781
Qiaoxuan LiSchool of Resources and Environmental Science, Quanzhou Normal University, Quanzhou, 362000, China.
Menglin DaiCollege of Urban and Environmental Sciences, Peking University, Beijing, 100871, China.ORCID http://orcid.org/0000-0002-1139-6325
Hongwei GuoCollege of Urban and Environmental Sciences, Peking University, Beijing, 100871, China.
Qiance LiuCollege of Urban and Environmental Sciences, Peking University, Beijing, 100871, China.ORCID http://orcid.org/0000-0003-0532-8550
Jinchao SongSchool for Environment and Sustainability, University of Michigan, Ann Arbor, MI, 48109, USA.
Zuoqi ChenKey Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou, 35002, China.
Srinivasa Raghavendra Bhuvan GummidiSDU Life Cycle Engineering, Department of Green Technology, University of Southern Denmark, Odense, 5230, Denmark.
Wu ChenSDU Life Cycle Engineering, Department of Green Technology, University of Southern Denmark, Odense, 5230, Denmark.
Bailang YuSchool of Geographic Sciences, East China Normal University, Shanghai, 200241, China. blyu@geo.ecnu.edu.cn.ORCID http://orcid.org/0000-0001-5628-0003
Gang LiuCollege of Urban and Environmental Sciences, Peking University, Beijing, 100871, China. gangliu@pku.edu.cn.ORCID http://orcid.org/0000-0002-7613-1985

Funding

Det Frie Forskningsråd (Danish Council for Independent Research) iBuildGreenNational Natural Science Foundation of China (National Science Foundation of China) 72334001, 71991484
6 · The paper itself

Abstract

The anthropogenic material in-use stocks accumulated in products, buildings, and infrastructure are essential for satisfying basic human demands and ensuring well-being. They drive global resource demand and environmental impacts while representing valuable resource reservoirs for potential recycling through urban mining. A high-resolution understanding of global material in-use stocks was achieved by integrating reconciled night-time light imageries with national stock data on primary construction materials, including steel, aluminum, and cement. The integration enabled the estimates of global stocks from 2000 to 2019 at a 500 × 500 m grid resolution. The updated dataset mitigated saturation and blooming effects in prior satellite data compared to previous datasets, offering refined temporal and geographical representations despite some regional variations. The refined results systematically elucidate the spatiotemporal dynamics of material accumulation worldwide, highlighting distribution discrepancies between and within cities. The comprehensive database serves as a helpful resource for supporting waste management, circular economy, spatial planning, urban sustainability, and climate change mitigation efforts across various geographical scales.

Identifiers

PMID41006336
PMCPMC12475013

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Registered trials

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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.