Na Ma

Dr. Na Ma


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 August 2024 in Remote Sensing
Verified
Journal Article
Open access
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NMNa Ma
Na Ma
JWJie Wang
Jie Wang
CPChenglei Pei
Chenglei Pei
SYSipeng Yang
Sipeng Yang
TZTianshu Zhang
Tianshu Zhang
YXYiwei Xu
Yiwei Xu
Recently, in China, during the period of transition between spring and summer, the combination of sandstorms and ozone (O3) pollution has posed a significant challenge to the strategy of coordinated control of fine particulate matters (PM2.5) and O3. On the one hand, the dust invasion brings many primary aerosols and causes a large range of transboundary transport. On the other hand, the high concentration of aerosol causes a severe disturbance to the distribution of O3. Traditionally, high-resolution assessments of the spatial distribution of aerosols and O3 can be carried out using LiDAR technology. However, the negligence of the influence of aerosols in the process of O3 retrieval in traditional differential absorption lidar (DIAL) leads to an error in the accuracy of ozone concentration. Especially when dust transit occurs, the errors become bigger. In this study, a self-customized four-wavelength differential-absorption LiDAR system was used to synchronously obtain the accurate vertical distributions of ozone and high-concentration aerosol. The wavelength index of concentrated aerosol was inverted and applied to the differential equation framework for O3 calculation. This novel approach to retrieving the vertical profile of O3 was proposed and verified by applying it to a dust pollution event that occurred from April to May 2021 in Anyang City Henan Province, which is located in Northern China. It was found that the extinction coefficient of aerosol reached 2.5 km−1 during the dust period, and O3 was mainly distributed between 500 m and 1500 m. The O3 error exceeded over 10% arising from the high-concentration aerosol below 1.5 km during the dust storm event. By employing the inversion algorithm while considering the aerosol effects, the ozone concentration error was improved by over 10% compared with the error recorded without considering the aerosol influence especially in dust events. Through this study, it was found that the algorithm could effectively realize the synchronous and accurate inversion of high-concentration aerosols and O3 and can provide key technical support for air pollution control in China in the future.