Parsimonious estimation of hourly surface ozone concentration across China during 2015-2020.
Wenxiu ZhangDi LiuHanqin TianNaiqing PanRuqi YangWenhan TangJia YangFei LuBuddhi DayanandaHan MeiSiyuan WangHao ShiPublished in: Scientific data (2024)
Surface ozone is an important air pollutant detrimental to human health and vegetation productivity, particularly in China. However, high resolution surface ozone concentration data is still lacking, largely hindering accurate assessment of associated environmental impacts. Here, we collected hourly ground ozone observations (over 6 million records), remote sensing products, meteorological data, and social-economic information, and applied recurrent neural networks to map hourly surface ozone data (HrSOD) at a 0.1° × 0.1° resolution across China during 2015-2020. The coefficient of determination (R 2 ) values in sample-based, site-based, and by-year cross-validations were 0.72, 0.65 and 0.71, respectively, with the root mean square error (RMSE) values being 11.71 ppb (mean = 30.89 ppb), 12.81 ppb (mean = 30.96 ppb) and 11.14 ppb (mean = 31.26 ppb). Moreover, it exhibits high spatiotemporal consistency with ground-level observations at different time scales (diurnal, seasonal, annual), and at various spatial levels (individual sites and regional scales). Meanwhile, the HrSOD provides critical information for fine-resolution assessment of surface ozone impacts on environmental and human benefits.
Keyphrases
- human health
- particulate matter
- hydrogen peroxide
- high resolution
- climate change
- risk assessment
- air pollution
- electronic health record
- neural network
- big data
- healthcare
- endothelial cells
- mass spectrometry
- mental health
- single molecule
- data analysis
- magnetic resonance
- artificial intelligence
- molecularly imprinted
- pluripotent stem cells
- contrast enhanced