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Simulation of average monthly ozone exposure concentrations in China: A temporal and spatial estimation method
Zhirui Fan1, Binghu Huang1, Chao Peng2
1College of Oceanography and Space Informatics, China University of Petroleum, Qingdao, 266580, China.
Environmental Research
|May 19, 2021
Summary
Accurate ozone exposure mapping in China is improved by combining ground monitoring station data with remote sensing data. This hybrid approach enhances health assessments and regional planning by providing refined ozone concentration data, especially in areas lacking monitoring stations.
Area of Science:
- Environmental Science
- Atmospheric Chemistry
- Geostatistics
Background:
- Ozone exposure poses health risks, necessitating precise concentration data.
- Existing monitoring stations (MS) provide urban-centric data, limiting coverage in areas with scarce MS.
Purpose of the Study:
- To improve the accuracy of simulating average monthly ozone exposure concentrations in monitor-free areas of China.
- To develop a refined ozone exposure concentration map by integrating ground-based and remote sensing data.
Main Methods:
- Utilized space-time geostatistical kriging interpolation with a composite space/time mean trend model (CSTM).
- Combined accurate but sparse monitoring station (MS) data with comprehensive remote sensing (RS) data.
- Determined a distance threshold (175 km) to optimally fuse MS and RS data for improved accuracy.
Main Results:
- Developed a refined ozone exposure concentration interpolation map for mainland China.
- Identified that ozone exposure concentration is highest in northern, eastern, and parts of central China.
- Demonstrated that fusing MS and RS data through a distance threshold enhances estimation accuracy.
Conclusions:
- Remote sensing (RS) data effectively characterizes ground ozone exposure when combined with monitoring station (MS) data.
- The refined ozone exposure map provides valuable insights for public health and regional economic development in China.
