A dataset of trace gases in the Yellow River Basin based on Sentinel-5P (2018–2024)

<p indent="0mm">This study systematically develops a spatiotemporal distribution dataset (YRB-S5P-TGD) of four trace gases (CH<sub>4</sub>, HCHO, NO<sub>2</sub>, and CO) in the Yellow River Basin from 2018 to 2024, based on ESA Sentinel-5P satellite L2 offline data streams and GEE L3 standardized datasets. The dataset integrates the high-frequency global coverage advantage of S5P satellites with the cloud computing capabilities of the GEE platform. The study adopts a standardized processing workflow: (1) Data screening and quality control: Offline data streams are prioritized, with low-confidence observations filtered using quality flags; (2) Spatiotemporal aggregation and resampling: Monthly/annual mean vertical column concentrations are calculated, and the original resolution is upscaled to a <sc>1 km</sc> grid using bilinear resampling; (3) Regional cropping and standardized output: GeoTIFF-format datasets are generated based on the Yellow River Basin boundary to ensure compatibility with mainstream GIS analysis requirements. By implementing rigorous and unified quality control standards, the dataset effectively avoids biases potentially introduced during reprocessing, supporting multi-scale analyses ranging from monthly variations to interannual trends. This dataset constitutes a valuable supplement to the systematic observation data of trace gases in the Yellow River Basin. Its high spatiotemporal resolution delivers critical data support for research such as precise source apportionment of regional air pollution and greenhouse gas flux estimation.

Authors

Publication Details

Journal
China Scientific Data
Published
2025-11-24
DOI
https://doi.org/10.11922/11-6035.csd.2025.0067.zh
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
0.00
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article

A dataset of trace gases in the Yellow River Basin based on Sentinel-5P (2018–2024)

Lian Yang, Ji Min Liang, Kai Feng, Shengcai Cao
China Scientific Data
Marine and coastal ecosystems
article

A dataset of trace gases in the Yellow River Basin based on Sentinel-5P (2018–2024)

Lian Yang, Ji Min Liang, Kai Feng, Shengcai Cao
article en

Abstract

<p indent="0mm">This study systematically develops a spatiotemporal distribution dataset (YRB-S5P-TGD) of four trace gases (CH<sub>4</sub>, HCHO, NO<sub>2</sub>, and CO) in the Yellow River Basin from 2018 to 2024, based on ESA Sentinel-5P satellite L2 offline data streams and GEE L3 standardized datasets. The dataset integrates the high-frequency global coverage advantage of S5P satellites with the cloud computing capabilities of the GEE platform. The study adopts a standardized processing workflow: (1) Data screening and quality control: Offline data streams are prioritized, with low-confidence observations filtered using quality flags; (2) Spatiotemporal aggregation and resampling: Monthly/annual mean vertical column concentrations are calculated, and the original resolution is upscaled to a <sc>1 km</sc> grid using bilinear resampling; (3) Regional cropping and standardized output: GeoTIFF-format datasets are generated based on the Yellow River Basin boundary to ensure compatibility with mainstream GIS analysis requirements. By implementing rigorous and unified quality control standards, the dataset effectively avoids biases potentially introduced during reprocessing, supporting multi-scale analyses ranging from monthly variations to interannual trends. This dataset constitutes a valuable supplement to the systematic observation data of trace gases in the Yellow River Basin. Its high spatiotemporal resolution delivers critical data support for research such as precise source apportionment of regional air pollution and greenhouse gas flux estimation.

China Scientific DataVol. 10(4)
Openalex Percentile: Top 62%
Marine and coastal ecosystems
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