Stereoscopic Remote Sensing of Air Pollutants: Emission, Formation, and Transport

Dear Colleagues,

In recent years, with the development of multi-platform remote sensing technologies such as satellite-based, airborne-based, ground-based, and ship-based sensing, the three-dimensional stereoscopic monitoring of air pollutants has been realized, providing a unique perspective for the analysis of the whole process of pollutant emission, transport, reaction, and deposition. Many of these emerging technologies are exciting and may inspire the scientific community, including geostationary satellites for trace gas observation, ground-based horizontal scanning, the development of a vertical multi-axis differential absorption spectrometer, trace gas monitoring lidar, and other optical methods. Combining these multiple observation techniques, multi-perspective three-dimensional observation can be performed at various scales, such as the meter-scale and kilometer-scale for regional or global coverage. With the help of chemical models or Lagrangian trajectory analysis, we are able to achieve source appointment and the characterization of air pollution, and provide further guidance for air quality policies.

Therefore, we are launching a new Special Issue, entitled "Stereoscopic remote sensing of air pollutants: emission, formation and transport", and welcome contributions addressing the following topics:

• The pinpoint and characterization of air pollution emissions.
• Process of air pollution.
• Source analysis of pollutants.
• Local and regional transport processes of pollutants.
• New techniques and algorithms for atmospheric remote sensing.
• New atmospheric physical and chemical models.
• Health risk of air pollutants.

Dr. Chengxin Zhang
Dr. Chi Li
Dr. Chengzhi Xing
Guest Editors

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• satellite remote sensing
• ground-based remote sensing
• atmospheric pollutants
• source analysis
• greenhouse gases

Title: Recent developments in satellite remote sensing for air pollution surveillance in support of Sustainable Development Goals
Authors: Dimitris Stratoulias; Narissara Nuthammachot; Racha Dejchanchaiwong; Perapong Tekasakul; Gregory R. Carmichael
Affiliation: Air Pollution and Health Effect Research Center, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand
Abstract: Air pollution is an integral part of climatic, environmental and socioeconomic current affairs and a cross-cutting component of certain United Nations Sustainable Development Goals (SDG). Hence, reliable information on air pollution and related exposures is a crucial element for tracking and evaluating the efficacy of policy interventions. At the same time, Earth observation is steadily gaining confidence as a data source in the calculation of various SDG indicators. The current paper focuses on the potential usability of modern satellite remote sensing in the context of the SDGs relevant to air quality. We introduce the socioeconomic importance of air quality and discuss the current uptake of geospatial information. The latest developments in Earth Observation galvanize the availability of finer spatial, temporal and radiometric resolution products with increased global coverage, long-term stability and coherence in measurements. Leveraging on the latest operational satellite technology available and primarily the Sentinel-5P and GEMS missions, we demonstrate two potential operational applications of quantifying air pollution at city and at regional scales. Based on the two examples and by discussing the near-future anticipated geospatial capabilities, we showcase and advocate that the potential of remote sensing as a, complementary to ground station networks, source of air pollution information is gaining confidence and as such can be an invaluable tool in quantifying global air pollution and a source for deriving robust population exposure estimates due to ambient air pollution.

Title: Analysis of the spatiotemporal distribution, sources, and impact on atmospheric oxidation of reactive nitrogen oxides in the North China Plain agricultural regions in summer
Authors: Shaocong Wei; Qianqian Hong; Wei Tan; Jian Chen; Tianhao Li; Xiaohan Wang; Jingkai Xue; Jiale Fang; Chao Liu; Aimon Tanvir; Chengzhi Xing; Cheng Liu
Affiliation: Wuxi University
Abstract: The lack of vertical observation of reactive nitrogen oxides in agricultural areas has posed a significant challenge in fully understanding their sources and impacts on atmospheric oxidation. Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations were conducted in the agricultural regions of the North China Plain (NCP) to measure the vertical distributions of aerosols, nitrogen dioxide (NO2), and nitrous acid (HONO). This study aimed at revealing the spatiotemporal distribution, sources, and environmental effects of reactive nitrogen oxides in the NCP agricultural areas. Our findings indicated that the vertical profiles of aerosols and NO2 exhibited a Gaussian shape, with distinct peak times occurring between 8:00-10:00 and 16:00-18:00. HONO reached its maximum concentration near the surface around 8:00 in the morning and decreased exponentially with altitude. After sunrise, the concentration of HONO rapidly decreased due to photolysis. Additionally, the potential source contribution function (PSCF) was used to evaluate the potential sources of air pollutants. The results indicated that the main potential pollution sources of aerosols were located in the southern part of Hebei, Shanxi, Shandong, and Jiangsu provinces, while the potential pollution sources of NO2 were concentrated in the Beijing-Tianjin-Hebei region. Above 500 meters, heterogeneous reactions of NO2 on aerosol surfaces were identified as important sources of HONO, rather than direct emissions. Furthermore, we discussed the production rate of hydroxyl radicals (OH) from HONO photolysis. It was found that the production rate of OH from HONO photolysis decreased with altitude, with peaks occurring in the morning and evening. This pattern was consistent with the variations in HONO concentration, indicating that HONO was the main contributor to OH production in the agricultural regions of the North China Plain. This study provides a new perspective on the sources of active nitrogen in agricultural regions and their contribution to atmospheric oxidation capacity from a three-dimensional perspective.

Title: Geometric Factor Correction Algorithm Based on Temperature and Humidity Profile Lidar
Authors: Bowen Zhang; Guangqiang Fan; Tianshu Zhang
Affiliation: Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences
Abstract: Due to the influence of geometric factors, the temperature and humidity profile lidar's near-field signal was warped when sensing the air environment. In order to perform geometric factor correction on near-field signals, this article proposed different correction solutions for the Mie and Raman scattering channels. The Mie scattering channel used the Raman method to invert the aerosol backscatter coefficient and correct the extinction coefficient in the transition zone. The geometric factor was the ratio of the measured signal to the forward computed vibration Raman scattering signal. The aerosol optical characteristics were reversed using the corrected echo signal, and the US standard atmospheric model was added to the missing signal in the blind zone reflecting the aerosol evolution process. The stability and dependability of the proposed algorithm were confirmed by the consistency between the visibility provided by the Environmental Protection Agency and the visibility acquired via lidar inversion. The near-field humidity data was supplemented by the interpolation method in the Raman scattering channel to reflect the water vapor transfer process in the temporal dimension; The measured transmittance curve of the filter, the theoretical normalized spectrum, and the sounding data were used to compute the delay geometric factor. The temperature was reversed and the near-field signal distortion issue was resolved by applying the corrected quotient. The proposed algorithm exhibited robustness and universality, enhancing the system's detection accuracy compared to the meteorological gradient tower and the constantly recorded temperature and humidity inversion data. It was essential to monitor the atmospheric environment of the urban canopy layer.