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

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.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2025-09-26
DOI
https://doi.org/10.1038/s41597-025-05618-0
Primary Topic
Impact of Light on Environment and Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Qiaoxuan Li, Menglin Dai, Gang Liu, Kun Sun et al.
Scientific Data
Impact of Light on Environment and Health
article

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

Qiaoxuan Li, Menglin Dai, Gang Liu, Kun Sun, Srinivasa Raghavendra Bhuvan Gummidi, Wu Chen, Zuoqi Chen, Qiance Liu, Hongwei Guo, Bailang Yu, Jinchao Song
article en

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.

Scientific DataVol. 12(1)
Quanzhou Normal University (CN), University of Southern Denmark (DK), Peking University (CN), University of Michigan (US), East China Normal University (CN), Fuzhou University (CN)
Openalex Percentile: Top 75%
Impact of Light on Environment and Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.