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Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing
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Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 18964

Special Issue Editors

Dr. Xin Yang

E-Mail Website
Guest Editor
College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
Interests: remote sensing of air pollution; aerosol-radiation-cloud-precipitation Interaction; aerosols and air quality
Prof. Dr. Kai Qin

E-Mail Website
Guest Editor
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Interests: aerosol; trace gases; remote sensing; lidar
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Simone Lolli

E-Mail Website
Guest Editor
CNR-IMAA, Contrada S. Loja, 85050 Tito Scalo, PZ, Italy
Interests: radiative transfer; aerosols; lidar; image fusion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Atmospheric pollution, especially fine particulate matter, profoundly affects environmental systems and human health. Atmospheric pollution monitoring is a vital step toward understanding what the essential process of the potential impact is. Apart from in situ measurements, space-borne remote sensing instruments can periodically observe air pollutants, e.g., atmospheric aerosols. Therefore, many emerging approaches of remote sensing associated with the network of ground-based measurements are highly expected to monitor, estimate, and even predict the concentration of air pollutants. Furthermore, they are applied to analyze and estimate the potential effect on global or regional environments and public health.

This Special Issue entitled “Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing” will collect and integrate current accomplishments and future advancements of advanced remote sensing of air pollution. Community members are sincerely invited to submit contributions related to elements of air pollution in providing a comprehensive request for impact assessments on public health and climate changes. Both comprehensive reviews and research articles on atmospheric pollution monitoring are welcomed. The topics of this issue consist of (but are not limited to):

  • PM 2.5 concentration estimation and prediction;
  • aerosol–radiation–cloud–precipitation interaction;
  • Optical properties modeling of air pollutants;
  • Advanced deep learning approaches for air pollution monitoring.

Dr. Xin Yang
Prof. Dr. Kai Qin
Dr. Simone Lolli
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • PM 2.5
  • air pollution
  • human activity
  • solar radiation
  • aerosol optical depth
  • atmospheric composition

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Published Papers (8 papers)

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Research

31 pages, 9525 KiB  
Article
Absorbing Aerosol Optical Properties and Radiative Effects on Near-Surface Photochemistry in East Asia
by Huimin Chen, Bingliang Zhuang, Jane Liu, Yinan Zhou, Yaxin Hu, Yang Chen, Yiman Gao, Wen Wei, Huijuan Lin, Shu Li, Tijian Wang, Min Xie and Mengmeng Li
Remote Sens. 2023, 15(11), 2779; https://doi.org/10.3390/rs15112779 - 26 May 2023
Cited by 4 | Viewed by 1724
Abstract
Absorbing aerosols have significant influences on tropospheric photochemistry and regional climate change. Here, the direct radiative effects of absorbing aerosols at the major AERONET sites in East Asia and corresponding impacts on near-surface photochemical processes were quantified by employing a radiation transfer model. [...] Read more.
Absorbing aerosols have significant influences on tropospheric photochemistry and regional climate change. Here, the direct radiative effects of absorbing aerosols at the major AERONET sites in East Asia and corresponding impacts on near-surface photochemical processes were quantified by employing a radiation transfer model. The average annual aerosol optical depth (AOD) of sites in China, Korea, and Japan was 1.15, 1.02 and 0.94, respectively, and the corresponding proportion of absorbing aerosol optical depth (AAOD) was 8.61%, 6.69%, and 6.49%, respectively. The influence of absorbing aerosol on ultraviolet (UV) radiation mainly focused on UV-A band (315–400 nm). Under the influence of such radiative effect, the annual mean near-surface J[NO2] (J[O1D]) of sites in China, Korea, and Japan decreased by 16.95% (22.42%), 9.61% (13.55%), and 9.63% (13.79%), respectively. In Beijing–Tianjin–Hebei (BTH) and Yangtze River Delta (YRD) region, the annual average AOD was 1.48 and 1.29, and the AAOD was 0.14 and 0.13, respectively. The UV radiative forcing caused by aerosols dominated by black carbon (BC-dominated aerosols) on the surface was −3.19 and −2.98 W m−2, respectively, accounting for about 40% of the total aerosol radiative forcing, indicating that the reduction efficiency of BC-dominated aerosols on solar radiation was higher than that of other types of aerosols. The annual mean J[NO2] (J[O1D]) decreased by 14.90% (20.53%) and 13.71% (18.20%) due to the BC-dominated aerosols. The daily maximum photolysis rate usually occurred near noon due to the diurnal variation of solar zenith angle and, thus, the daily average photolysis rate decreased by 2–3% higher than that average during 10:00–14:00. Full article
(This article belongs to the Special Issue Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing)
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24 pages, 7506 KiB  
Article
A New Algorithm of Atmospheric Boundary Layer Height Determined from Polarization Lidar
by Bisen Han, Tian Zhou, Xiaowen Zhou, Shuya Fang, Jianping Huang, Qing He, Zhongwei Huang and Minzhong Wang
Remote Sens. 2022, 14(21), 5436; https://doi.org/10.3390/rs14215436 - 28 Oct 2022
Cited by 5 | Viewed by 2709
Abstract
Accurately determining the atmospheric boundary layer height (ABLH) is needed when one is addressing the air quality-related issues in highly urbanized areas, as well as when one is investigating issues that are related to the emission and transport of dust aerosols over the [...] Read more.
Accurately determining the atmospheric boundary layer height (ABLH) is needed when one is addressing the air quality-related issues in highly urbanized areas, as well as when one is investigating issues that are related to the emission and transport of dust aerosols over the source region. In this study, we propose a new ABLH retrieval method, which is named ADEILP (ABLH that is determined by polarization lidar); it is based on the short-term polarized lidar observation that took place during the intensive field campaign in July 2021 in Tazhong, the hinterland of Taklimakan Desert. Furthermore, we conducted comparisons between the ABLH that was identified using a radiosonde (ABLHsonde), the ABLH that was identified by ERA5 (ABLHERA5) and the ABHL that was identified by ADELIP (ABLHADELIP), and we discussed the implications of the dust events. The ADELIP method boasts remarkable advancements in two parts: (1) the lidar volume linear depolarization ratio (VLDR) that represented the aerosol type was adopted, which is very effective in distinguishing between the different types of boundary layers (e.g., mixing layer and residual layer); (2) the idea of breaking up the entire layer into sub-layers was applied on the basis of the continues wavelet transform (CWT) method, which is favorable when one is considering the effect of fine stratification in an aerosol layer. By combining the appropriate height limitations, these factors ensured that there was good robustness of the ADELIP method, thereby enabling it to deal with complex boundary layer structures. The comparisons revealed that ABLHADELIP shows good consistency with ABLHsonde and ABLHERA5 for non-dust events. Nevertheless, the ADELIP method overestimated the stable boundary layer and underestimated the heights of the mixing layer. The dust events seem to be a possible reason for the great difference between ABLHERA5 and ABLHsonde. Thus, it is worth suggesting that the influence that is caused by the differences of the vertical profile in the ERA5 product should be carefully considered when the issues on dust events are involved. Overall, these findings support the climatological analysis of the atmosphere boundary layer and the vertical distribution characteristics of aerosols over typical climatic zones. Full article
(This article belongs to the Special Issue Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing)
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22 pages, 6673 KiB  
Article
Evaluation of IMERG Precipitation Products in the Southeast Costal Urban Region of China
by Ning Lu
Remote Sens. 2022, 14(19), 4947; https://doi.org/10.3390/rs14194947 - 3 Oct 2022
Cited by 5 | Viewed by 1743
Abstract
The intensification of extreme precipitation has aggravated urban flood disasters, which makes timely and reliable precipitation information urgently needed. As the high-quality and widely used satellite precipitation products, Integrated Multi-satellitE Retrievals for GPM (IMERG), have not been well investigated in coastal urban agglomerations [...] Read more.
The intensification of extreme precipitation has aggravated urban flood disasters, which makes timely and reliable precipitation information urgently needed. As the high-quality and widely used satellite precipitation products, Integrated Multi-satellitE Retrievals for GPM (IMERG), have not been well investigated in coastal urban agglomerations where damages from precipitation-related disasters are more severe. With precipitation measurements from local high-density gauge stations, this study evaluates three IMERG runs (IMERG ER, IMERG LR, and IMERG FR) in the southeast coastal urban region of China. The evaluation shows that the three IMERG products severely overestimate weak precipitation and underestimate heavy precipitation. Among the three runs, the post-corrected IMERG FR does not show a substantial improvement compared to the near-real-time IMERG ER and IMERG LR. The performance of IMERG varies depending on the precipitation pattern and intensity, with the best estimation ability occurring in the coastal urban region in summer and in the northern forests in winter. Due to the year-round urban effect on precipitation variability, IMERG cannot detect precipitation events well in the central high-density urban areas, and has its best detection ability on cultivated lands in summer and forests in winter. Within the urban agglomeration, IMERG shows a poorer performance in areas with higher urbanization levels. Thus, the IMERG products for coastal urban areas need considerable improvements, such as regionalized segmental corrections based on precipitation intensity and the adjustment of short-duration estimates by daily or sub-daily precipitation measurements. Full article
(This article belongs to the Special Issue Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing)
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21 pages, 5700 KiB  
Article
Investigation of Aerosol Types and Vertical Distributions Using Polarization Raman Lidar over Vipava Valley
by Longlong Wang, Marija Bervida Mačak, Samo Stanič, Klemen Bergant, Asta Gregorič, Luka Drinovec, Griša Močnik, Zhenping Yin, Yang Yi, Detlef Müller and Xuan Wang
Remote Sens. 2022, 14(14), 3482; https://doi.org/10.3390/rs14143482 - 20 Jul 2022
Cited by 10 | Viewed by 2191
Abstract
Aerosol direct radiative forcing is strongly dependent on aerosol distributions and aerosol types. A detailed understanding of such information is still missing at the Alpine region, which currently undergoes amplified climate warming. Our goal was to study the vertical variability of aerosol types [...] Read more.
Aerosol direct radiative forcing is strongly dependent on aerosol distributions and aerosol types. A detailed understanding of such information is still missing at the Alpine region, which currently undergoes amplified climate warming. Our goal was to study the vertical variability of aerosol types within and above the Vipava valley (45.87°N, 13.90°E, 125 m a.s.l.) to reveal the vertical impact of each particular aerosol type on this region, a representative complex terrain in the Alpine region which often suffers from air pollution in the wintertime. This investigation was performed using the entire dataset of a dual-wavelength polarization Raman lidar system, which covers 33 nights from September to December 2017. The lidar provides measurements from midnight to early morning (typically from 00:00 to 06:00 CET) to provide aerosol-type dependent properties, which include particle linear depolarization ratio, lidar ratio at 355 nm and the aerosol backscatter Ångström exponent between 355 nm and 1064 nm. These aerosol properties were compared with similar studies, and the aerosol types were identified by the measured aerosol optical properties. Primary anthropogenic aerosols within the valley are mainly emitted from two sources: individual domestic heating systems, which mostly use biomass fuel, and traffic emissions. Natural aerosols, such as mineral dust and sea salt, are mostly transported over large distances. A mixture of two or more aerosol types was generally found. The aerosol characterization and statistical properties of vertical aerosol distributions were performed up to 3 km. Full article
(This article belongs to the Special Issue Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing)
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16 pages, 8411 KiB  
Article
Analysis of PM2.5 Variations Based on Observed, Satellite-Derived, and Population-Weighted Concentrations
by Xin Fang, Shenxin Li, Liwei Xiong and Bin Zou
Remote Sens. 2022, 14(14), 3381; https://doi.org/10.3390/rs14143381 - 14 Jul 2022
Cited by 6 | Viewed by 1914
Abstract
Fine particulate matter (PM2.5), which can cause adverse human health effects, has been proven as the first air pollutant in China. In situ observations with ground-level monitoring and satellite-based concentrations have been used to analyze the variations in PM2.5. [...] Read more.
Fine particulate matter (PM2.5), which can cause adverse human health effects, has been proven as the first air pollutant in China. In situ observations with ground-level monitoring and satellite-based concentrations have been used to analyze the variations in PM2.5. However, variation analyses based on these two kinds of measurement have mainly focused on the concentration itself and ignored the effects on the population. Therefore, this study not only investigated these two kinds of measurements, but also performed weighted population analyses to study the variations in PM2.5. Firstly, daily models of timely structure adaptive modeling (TSAM) were constructed to simulate satellite-derived PM2.5 levels from January 2013 to December 2016. Secondly, population-weighted concentrations were calculated based on TSAM-derived PM2.5 surfaces. Finally, observed, TSAM-derived, and population-weighted concentrations were used to analyze the variations in PM2.5. The results showed the different importance of various input parameters; AOD had the highest rank. Additionally, TSAM models demonstrated good performance, fitting R ranging from 0.86 to 0.91, and validating R from 0.82 to 0.89. According to the air quality standard in China, TSAM-derived PM2.5 showed that the increase in area lower than Level II was 29.03% and the increase in population was only 14.81%. This indicates that the air quality exhibited an overall improvement in spatial perspective, but some areas with high population density showed a relatively low improvement due to uneven distributions in China. The population-weighted PM2.5 concentration could better represent the health threats of air pollutants compared with in situ observations. Full article
(This article belongs to the Special Issue Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing)
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18 pages, 5600 KiB  
Article
Influence of Spatial Resolution on Satellite-Based PM2.5 Estimation: Implications for Health Assessment
by Heming Bai, Yuli Shi, Myeongsu Seong, Wenkang Gao and Yuanhui Li
Remote Sens. 2022, 14(12), 2933; https://doi.org/10.3390/rs14122933 - 19 Jun 2022
Cited by 8 | Viewed by 2340
Abstract
Satellite-based PM2.5 estimation has been widely used to assess health impact associated with PM2.5 exposure and might be affected by spatial resolutions of satellite input data, e.g., aerosol optical depth (AOD). Here, based on Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD [...] Read more.
Satellite-based PM2.5 estimation has been widely used to assess health impact associated with PM2.5 exposure and might be affected by spatial resolutions of satellite input data, e.g., aerosol optical depth (AOD). Here, based on Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD in 2020 over the Yangtze River Delta (YRD) and three PM2.5 retrieval models, i.e., the mixed effects model (ME), the land-use regression model (LUR) and the Random Forest model (RF), we compare these model performances at different spatial resolutions (1, 3, 5 and 10 km). The PM2.5 estimations are further used to investigate the impact of spatial resolution on health assessment. Our cross-validated results show that the model performance is not sensitive to spatial resolution change for the ME and LUR models. By contrast, the RF model can create a more accurate PM2.5 prediction with a finer AOD spatial resolution. Additionally, we find that annual population-weighted mean (PWM) PM2.5 concentration and attributable mortality strongly depend on spatial resolution, with larger values estimated from coarser resolution. Specifically, compared to PWM PM2.5 at 1 km resolution, the estimation at 10 km resolution increases by 7.8%, 22.9%, and 9.7% for ME, LUR, and RF models, respectively. The corresponding increases in mortality are 7.3%, 18.3%, and 8.4%. Our results also show that PWM PM2.5 at 10 km resolution from the three models fails to meet the national air quality standard, whereas the estimations at 1, 3 and 5 km resolutions generally meet the standard. These findings suggest that satellite-based health assessment should consider the spatial resolution effect. Full article
(This article belongs to the Special Issue Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing)
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16 pages, 6099 KiB  
Article
Vertical Profile of Ozone Derived from Combined MLS and TES Satellite Observations
by Jingwen Liu, Sihui Wang, Qiangqiang Yuan, Feng Zhang and Liye Zhu
Remote Sens. 2022, 14(7), 1588; https://doi.org/10.3390/rs14071588 - 25 Mar 2022
Cited by 7 | Viewed by 2465
Abstract
Ozone is one of the most important gases in the atmosphere as it plays different roles based on the levels it presents. The ozone layer in the stratosphere protects life on Earth by absorbing ultraviolet (UV) radiance while harming life at ground-level. In [...] Read more.
Ozone is one of the most important gases in the atmosphere as it plays different roles based on the levels it presents. The ozone layer in the stratosphere protects life on Earth by absorbing ultraviolet (UV) radiance while harming life at ground-level. In order to better understand the source of ozone pollution, transport of ozone, stratosphere-troposphere exchange of ozone, it is necessary to estimate the vertical profile of ozone. In this study, we derive the vertical ozone profile throughout the troposphere to the stratosphere by combing ozone retrievals from MLS (Microwave Limb Sounder) and TES (Tropospheric Emission Spectrometer). The combination algorithm is based on the MLS and TES retrieved vertical profiles of ozone, and averaging kernels of MLS, which represent the vertical sensitivity of the instrument. The combination algorithm was applied to the pairs of MLS and TES over the globe in 2007 as examples. The combined vertical profiles were compared with ozonesonde observations for validation, which indicate that the combined products extract information from MLS and TES have less biases than that of MLS or TES alone in general in both stratosphere and troposphere under certain quantitative criteria. Full article
(This article belongs to the Special Issue Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing)
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16 pages, 3648 KiB  
Article
CALIOP-Based Quantification of Central Asian Dust Transport
by Ying Han, Tianhe Wang, Ruiqi Tan, Jingyi Tang, Chengyun Wang, Shanjuan He, Yuanzhu Dong, Zhongwei Huang and Jianrong Bi
Remote Sens. 2022, 14(6), 1416; https://doi.org/10.3390/rs14061416 - 15 Mar 2022
Cited by 11 | Viewed by 2458
Abstract
Central Asia is one of the most important sources of mineral saline dust worldwide. A comprehensive understanding of Central Asian dust transport is essential for evaluating its impacts on human health, ecological safety, weather and climate. This study first puts forward an observation-based [...] Read more.
Central Asia is one of the most important sources of mineral saline dust worldwide. A comprehensive understanding of Central Asian dust transport is essential for evaluating its impacts on human health, ecological safety, weather and climate. This study first puts forward an observation-based climatology of Central Asian dust transport flux by using the 3-D dust detection of Cloud-Aerosol LiDAR with Orthogonal Polarization (CALIOP). The seasonal difference of transport flux and downstream contribution are evaluated and compared with those of the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Central Asian dust can be transported not only southward in summer under the effect of the South Asian summer monsoon, but also eastward in other seasons under the control of the westerly jet. Additionally, the transport of Central Asian dust across the Pamir Plateau to the Tibetan Plateau is also non-negligible, especially during spring (with a transport flux rate of 150 kg m−1 day−1). The annual CALIOP-based downstream contribution of Central Asian dust to South Asian (164.01 Tg) is 2.1 times that to East Asia (78.36 Tg). This can be attributed to the blocking effect of the higher terrain between Central and East Asia. Additionally, the downstream contributions to South and East Asia from MERRA-2 are only 0.36 and 0.84 times that of CALIOP, respectively. This difference implies the overestimation of the wet and dry depositions of the model, especially in the low latitude zone. The quantification of the Central Asian dust transport allows a better understanding of the Central Asian dust cycle, and supports the calibration/validation of aerosol-related modules of regional and global climate models. Full article
(This article belongs to the Special Issue Observation and Impact Evaluation of Atmospheric Pollution by Remote Sensing)
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