Calendar Event Details

Zhanqing Li

Affiliation: University of Maryland, College Park
Event Date: Tuesday, April 16, 2019

Location: G133, B33
Time: 11:00 AM

New Approaches in Estimating Surface Air Pollution Indices by Remote Sensing and Understanding Aerosol-PBL Interactions

Aerosol optical depth (AOD) and its fine fraction, particulate matter (PM) of diameter less than 2.5mm (PM2.5) and planetary boundary layer (PBL) height are frequently referred to concerning air quality. We have developed a suite of novel approaches to estimate these quantities in order to maximize the extraction of pertinent information from remote sensing data acquired both from space and on the ground:

1. Aerosol optical depth. AOD retrieved from such well-known sensors as MODIS and MISR has been widely used. These products were developed for global applications that aren’t optimized for any local applications. A major source of error originates from a lack of information on aerosol type/properties. Taking advantage of local measurements of aerosol and surface observations and the resulting “more dynamic” climatology, AOD retrieval can be improved considerably (Wei et al., 2019a,b,c).

2. Fine-mode fraction. While several global AOD products have been widely employed, but few have sound quality in their fine-coarse fraction, if available at all, due to large uncertainties. The root of this limitation also stem from lack, or insufficient use of local aerosol properties. We have developed an algorithm that can fuse aerosol size information conveyed in ground-based observations to improve the estimation of fine-mode fraction (Yan et al., 2017a, 2017b, 2018, 2019).

3. Aerosol vertical distribution and interactions with PBL. Given the total column loading of aerosol, PM2.5 at surface is dictated by the vertical distribution of aerosol (Li et al., 2017). Since the majority of aerosols are confined to the planetary boundary layer (PBL), the height of PBL (PBLH) matters very much, and so are wind and topography (Su et al., 2018), especially under the condition of heavy loading of absorbing aerosol leading to a feedback between aerosol and PBL (Li et al. 2017; Dong et al., 2017). Lidar-based remote sensing of PBLH assumes well mixed PBL that co-varies with thermodynamics-driven PBL. This assumption may be violated to incur additional errors. To remedy this, we are developing an new method that can improve the PBLH estimation and improving understanding of the PBL-aerosol interaction.

Application of the above methods requires an integrated approach by fusing a large array of measurements made by space-borne active (CALIPSO) and passive (MODIS, MISR) sensors, surface meteorological and radiosonde data, and AERONET data. The integral approach is expected to reduce the overall errors in estimating several air pollution indices considerably.

Related recent publications:

Chen, J., Z. Li, M. Lv, Y. Wang, W. Wang1 , Y. Zhang, H. Wang, X. Yan, Y. Sun, and M. Cribb, (2019), Aerosol hygroscopic growth, contributing factors and impact on haze events in a severely polluted region in northern China, Atmos. Chem. Phys., 19, 1–16, https://doi.org/10.5194/acp-19-1-2019

Dong, Z., Z. Li, X. Yu, M. Cribb, X. Li, and J. Dai, 2017, Opposite Long-term Trends in Aerosols between Low and High Altitudes: A Testimony to the Aerosol-PBL Feedback, Atmos. Chem. & Phy., 17, 7997-8009, doi:10.5194/acp-2017-2.

Li, Z. et al., 2017: Aerosols and boundary-layer interactions and impact on air quality, Natl. Sci. Rev., 4, 810-833, doi:10.1093/nsr/nwx117.

Lv, M., D. Liu, Z. Li, et al. (2017), Hygroscopic growth of atmospheric aerosol particles based on lidar, radiosonde, and in situ measurements: case studies from the Xinzhou field campaign, J. Quant. Spectrosc. Radiat. Transf., 188, 60–70, doi:10.1016/j.jqsrt.2015.12.029.

Su, T., Z. Li, R. Kahn, 2018, Relationships between the planetary boundary layer height and surface pollutants derived from lidar observations over China, Atmos. Chem. Phy. 18, 15921-15935, https://doi.org/10.5194/acp-18-15921-2018.

Su, T., Z. Li, R. Kahn, 2019, A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability, Rem. Sens. Environ., under revision.

Wei, J., Z. Li, et al., (2019). A regionally robust high-spatial-resolution aerosol retrieval algorithm for MODIS images over Eastern China. IEEE Transactions on Geoscience and Remote Sensing, doi:10.1109/TGRS.2019.2892813

Wei, J., Li, Z., Peng, Y., Sun, L. (2019), MODIS Collection 6.1 aerosol optical depth products over land and ocean: validation and comparison. Atmospheric Environment, 201,428-440.

Wei, J., Z. Li, et al., Estimating the 1-km-resolution PM_2.5 concentrations across China using the space-time random forest approach, Rem. Sens. Environ., under revision.

Yan, X., Li, Z., et al. (2017a). An improved algorithm for retrieving the fine-mode fraction of aerosol optical thickness, part 1: Algorithm development. Rem. Sens. Environ, 192, 87-97.

Yan, X., Z. Li, et al., 2019: An improved algorithm for retrieving the fine-mode fraction of aerosol optical thickness. Part 2: Application and validation in Asia, Rem. Sens. Environ., in press.

Posted or updated: Tuesday, April 9, 2019

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