Abstract
The vertical distribution profiles of NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> are essential for understanding the mechanisms, detecting near-surface emissions, and tracking pollutant transportation at high altitude. However, most of the published NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> studies are based on the surface 2-D measurements. The ground-based 3-D remote-sensing stations were recently built to measure vertical distribution profiles of NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> . However, the stations were spatially sparse due to the high cost and could not make the measurements without sunlight. In this study, we first developed a multimodel fusion network (MF-net) based on the sparse vertical observations from the Jing-Jin-Ji region. We achieved the 3-D profile prediction of NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> in the range of 39.005–41.405N and 115.005–117.905E with 24-h coverage. The MF-net significantly surpassed the conventional WRF-CHEM model and provided a more accurate evaluation of the NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> transmission between Beijing and the neighboring cities. Besides, the MF-net covers the monitoring of NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> to the whole study area and extends the monitoring time to the entire day (24 h), making it serviceable for continuous spatial-temporal estimation of NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> and its transmission in pollution events. The MF-net provides more robust data support to formulate reasonable and effective pollution prevention and control measures.
Highlights
I N RECENT years, people have increasingly been concerned about air pollution with the development of urbanManuscript received September 23, 2020; revised January 3, 2021; accepted February 4, 2021
To compare the performance of the multimodal fusion network (MF-net) and the weather research and forecasting (WRF)-CHEM model, we systemically evaluated both methods on MAX-DOAS measurements and other testing data sets, such as the 2-D NO2 surface measurement from the China National Environmental Monitoring Center (CNEMC) sites
We conducted four experiments to show the superior performance of MF-net over the WRF-CHEM (Section IV-A) model
Summary
I N RECENT years, people have increasingly been concerned about air pollution with the development of urbanManuscript received September 23, 2020; revised January 3, 2021; accepted February 4, 2021. Qihou Hu is with the Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China. Haoran Liu is with the Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, China. NO2 is the precursor of secondary aerosols nitrate and has a significant impact on the formation and destruction of other air pollutants. It catalyzes the production of ozone (O3) in the troposphere and the removal of O3 in the stratospheric. The prevention and control of NO2 pollution are essential
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