Manipulating API and AOD data to distinguish transportation of aerosol at high altitude in Penang, Malaysia

8th International Symposium of the Digital Earth

地球科学;计算机科学

Tan, F.^1 ; Lim, H.S.^1 ; Abdullah, K.^1 ; Yoon, T.L.^1 ; Matjafri, M.Z.^1 ; Holben, B.^2

School of Physics, Universiti Sains Malaysia, Malaysia^1

NASA Goddard Space Flight Center, United States^2

关键词: Aerosol optical depths;    Air pollution index;    Air quality levels;    Back trajectory analysis;    Distribution patterns;    Ground truth data;    Numerical procedures;    Quantitative correlation;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/18/1/012082/pdf
DOI  :  10.1088/1755-1315/18/1/012082

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Air pollution index (API) is an index commonly used in Malaysia to determine the air quality level. It is a ground truth data measurement which is unable to unambiguously quantify air quality level at higher atmosphere. On the other hand, aerosol optical depth (AOD) from AERONET data obtained using sun photometer provides reading of the air quality for a column of atmosphere from ground surface. We first determine the quantitative correlation between the API and AOD data collected in Penang, Malaysia, between January-September, 2012, using two independent methods, one based on regression analysis and the other interpolation. Our purpose is to establish a systematic numerical procedure to determine whether aerosol transported in high altitude from other location has occurred. Two independent methods for establishing the quantitative relationship between the API and AOD data were used as a way to facilitate the verification of our approach. In our method, data from southwest monsoon period (August to September) were used as "calibration dataset" to establish the quantitative correlation between the AOD and API data. The established calibrated coefficients is then used to predict the AOD of other months, which are then compared against the data actually measured. Discrepancy between the predicted and measured AOD data can then be interpreted as an indication of whether the atmosphere at high altitude is polluted by aerosol transported from other location. If the predicted AOD is much larger than that measured, back trajectory analysis was applied to identify the aerosol transported source. This procedure is very helpful to investigate the aerosol transportation and distribution patterns during monsoon and non monsoon periods.