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A review of satellite remote sensing for pollution control and carbon reduction in China

Year: 2026
Type: article
Abstract: • Systematically summarizing the role of satellite remote sensing for pollution control and carbon reduction in China. • Identifying critical scientific and practical challenges. • Proposing actionable recommendations. Mitigating pollutants and greenhouse gas (GHG) emissions is a core strategic imperative for China, necessitating integrated technological solutions. Satellite remote sensing (SRS) has emerged as a pivotal tool for environmental monitoring, enhancing our understanding of pollutants and GHG emissions from space and supports policy-making. Here we summarize the recent research advances regarding the role of SRS in monitoring pollutants and GHG emissions in China, focusing on three key applications: 1) pollutant emission tracking, 2) carbon emission quantification, and 3) synergistic monitoring of pollution-carbon interactions. Current analysis identifies substantial progress achieved over the past decades, but critical limitations remain. From a scientific perspective, both ground observation networks and professional sensors are lacking for improving retrieval accuracy. Moreover, artificial intelligence (AI)-based data-mining theory is inadequate. From a practical perspective, high-resolution satellite provides insufficient coverage for nationwide carbon monitoring and data deficiencies hinders intelligent monitoring systems. To address these challenges, we provide the following strategic priorities: 1) establishing integrated Space-Air-Ground observation systems, 2) accelerating the deployment of next-generation monitoring satellites and developing related retrieval algorithms, and 3) developing AI-based monitoring systems through multisource data integration. This review enhances the understanding of SRS applications and provides directions for future research aimed at mitigating pollutant and GHG emissions, thereby supporting China’s dual carbon goals and sustainable development worldwide.
Language: English
Open Access status: gold
Estimated APC paid: $3,550
OpenAlex ID: W7124946213
FWCI:
Cites: 103
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