Spatiotemporal characteristics of atmospheric CO2 under the influence of different industrial emission sources using lidar remote sensing in Nanping, China.

Atmospheric CO2 concentrations are predominantly regulated by multiple emission sources, with industrial emissions representing a critical anthropogenic driver that significantly influences temporal and spatial heterogeneity in regional CO2 patterns. This study investigated the spatiotemporal distribution of atmospheric CO2 in Pucheng and Nanping industrial parks, Nanping City, by conducting field experiments using two coherent differential absorption lidars from 1 August to 31 October 2024. Results showed that the spatial distributions of CO2 emissions within a 3 km radius were mapped, and the local diffusion processes were clarified. CO2 patterns varied differently in two industrial parks over the three-month period: Average CO2 concentrations in non-emission areas were 422.4 ppm in Pucheng and 408.7 ppm in Nanping, with the former experiencing higher and more variable carbon emissions; Correlation analysis indicated that synthetic leather factories in Pucheng contributed more to SO2 and NOx levels compared to the chemical plant in Nanping; In Pucheng, CO2 concentrations were transported from the north at ground-level wind speeds exceeding 4 m/s, while in Nanping, the concentrations dispersed gradually with increasing wind speeds; Forward trajectory simulations revealed that the peak-emission from Pucheng primarily affected southern Fujian, northeastern Jiangxi, and southern Anhui, while the peak-emission from Nanping influenced central and western Fujian and northeastern Jiangxi. Besides, emissions in both industrial parks were higher on weekdays and lower on weekends, reflecting changes in industrial activities. The study underscores the potential of lidar technology for providing detailed insights into CO2 distribution and the interactions between emissions, wind patterns, and carbon transport.

• Publication year

  2025

• Venue

  Journal of Environmental Science

• Publication date

  2025-03-01

• Fields of study

  Medicine, Environmental Science

• Identifiers
  DOI 10.1016/j.jes.2025.03.046PMID 41005906
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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