Publications by authors named "Dakang Wang"
Formaldehyde (HCHO) is a key player in photochemical processes and serves as a crucial precursor in the formation of hydroxyl radicals and ozone (O). While satellite observations can offer extensive spatiotemporal distributions of HCHO at both global and regional scales, the reliability of these satellite-derived HCHO measurements remains uncertain. In this study, we generated a five-year (June 2018-May 2023) Level 3 HCHO dataset, by applying spatial averaging technique to the TROPOspheric Monitoring Instrument (TROPOMI) Level 2 data.
View Article and Find Full Text PDFMonitoring the spatiotemporal distribution of formaldehyde (HCHO) is crucial for reducing volatile organic compounds (VOCs) emissions, and the long-term evolution of socio-natural sources contributions to tropospheric HCHO over China is still unclear. We propose an oversampling algorithm for quantitatively tracking the evolution of uncertainty, which lowers the uncertainty of the original Level 2 OMI HCHO data (50 % -105 %) to 0-50 %, and then we examine the evolution of contributions from various emissions sources applying multi-scale correlation. We found that the high formaldehyde vertical column densities (VCD) caused by human activities in eastern China are crossing the Hu Huanyong Line, which was formerly used to demarcate the population distribution.
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- In early 2020, ship emissions around Southern China significantly decreased due to two main factors: reduced shipping activity from COVID-19 and the enforcement of low-sulfur fuel regulations.
- Ship emissions of nitrogen oxides (NO), sulfur oxides (SO), and primary particulate matter (PM) fell by 19%, 71%, and 58%, respectively, compared to the same time in 2019.
- The reduction in ship emissions led to a 16-18% drop in surface NO levels, but correspondingly caused a 3.8-4.9% increase in surface ozone levels, highlighting the need to address both ship and land-based emissions for better air quality.
Article Synopsis
- Soil moisture content (SMC) is crucial for geoscience research and can be retrieved using artificial neural networks (ANN) with remote sensing data.
- The study developed a sparse sample exploitation (SSE) method to address sample scarcity caused by cloud cover and faulty measuring instruments, effectively increasing sample availability for ANN training from 264 to 635.
- New optimized parameters, including elevation as a key factor, were introduced to enhance the feature description and improve retrieval accuracy of SMC using Sentinel-1 SAR and Landsat-8 images in eastern Austria.
Satellite HCHO data are widely used as a reliable proxy of non-methane volatile organic compounds (NMVOCs) to constrain underlying emissions and chemistry. Here, we examine global significant changes in HCHO columns at the early stage of the COVID-19 pandemic (January-April 2020) compared with the same period in 2019 with observations from the TROPOspheric Monitoring Instrument (TROPOMI). HCHO columns decline (11.
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