在東北季風盛行期間，從東亞長程傳輸的空氣污染物會影響多個下風處地點，包括臺灣。許多研究嘗試量化長程傳輸污染的比例及濃度，但受限於地面測站之分布及氣象預報模式的預測極限，對於較長時間尺度或較大的空間尺度的分析上具有一定的複雜度及困難性。相較之下，衛星具有長時間且大範圍觀測的優勢，故本研究提出結合衛星遙測的方法提供更全面的見解。首先應用一個根據測站資料建立的分類方法將2017年至2023年東北風期間的污染分成三種來源模式，進一步利用衛星的氣膠光學厚度、氣膠種類和PM2.5分析長程傳輸事件對臺灣的影響及分布，發現能有效地辨識出長程傳輸污染物的種類，同時結合軌跡模型提出境外污染的預警區域 (28-31°N, 121-125°E) 及閾值 (氣膠光學厚度大於1)。另外一方面，當長程境外傳輸事件影響臺灣地區時，臺灣西半部細懸浮微粒 (PM2.5) 相較於其他事件類型增加了25%，而沙塵氣膠的PM2.5濃度增加了約60%，是在境外污染影響下增加最為明顯的氣膠種類，可作為東北季風帶來的境外污染的指標。而人為污染氣膠的PM2.5在臺灣西北部的地區沒有增加的趨勢，反而集中在臺灣西南部，也就是尾流弱風區。該處的風速較弱，擴散條件會受到抑制。本研究提出的方法實現了對長程傳輸污染的長期分析，對氣膠的境外污染傳輸有了更明確的理解，進一步提高了長程境外污染事件預測的準確性，對於跨境合作的空氣污染控制政策具有重要參考價值。

Long-range transport (LRT) air pollution from East Asia, driven by the prevailing northeast monsoon can impact multiple downwind regions, including Taiwan. Numerous studies have attempted to quantify the contribution of LRT. However, analyzing longer time scales or larger spatial scales remains complex and challenging due to limitations in the spatial distribution of ground-based measurements and the prediction of simulation models. In contrast, satellite have the advantage of long-term and wide-area observations. Therefore, this study presents an approach that integrates satellite data to provide more comprehensive insights. Initially, an efficient method based on ground-based measurement was employed to classify particulate matter (PM2.5) source patterns into three types during northeast monsoon. Subsequently, satellite-based aerosol optical depth (AOD), aerosol types and PM2.5 data were used to analyze the impact and distribution of LRT on Taiwan. The results demonstrated that this approach effectively identifies the aerosol types of LRT. By integrating the trajectory model, it can propose a warning region (28-31°N, 121-125°E) and threshold (AOD greater than 1) for LRT. Other key findings include a 25% increase in PM2.5 concentration in western Taiwan during LRT events compared to other patterns. The PM2.5 concentration of dust type, in particular, increased most significantly by approximately 60%, serving as an indicator of LRT during the northeast monsoon. However, no increasing trend was observed in PM2.5 levels of anthropogenic pollutants (AP) in northwest Taiwan. Instead, the pollution is concentrated in southwestern Taiwan, a downwind region of northeast wind, which experiences weaker wind and poorer dispersion conditions. This research achieves long-term analysis of LRT and enhances understanding of aerosol type transport. Moreover, it improves the accuracy of forecasting LRT events and proves valuable for cross-border cooperation in air pollution control policies.

孫達旻. (2018). 同時輻射率定法在向日葵八號氣膠光學厚度反演之應用 國立中央大學]. 臺灣博碩士論文知識加值系統. 桃園縣. https://hdl.handle.net/11296/ftu762
張淵翔. (2017). 地球同步衛星（Himawari-8）在逐時大氣氣膠光學厚度之反演與分析 國立中央大學]. 臺灣博碩士論文知識加值系統. 桃園縣. https://hdl.handle.net/11296/2km6c9
Alexander, L., Allen, S., Bindoff, N., Breon, F.-M., Church, J., Cubasch, U., Emori, S., Forster, P., Friedlingstein, P., Gillett, N., Gregory, J., Hartmann, D., Jansen, E., Kirtman, B., Knutti, R., Kanikicharla, K., Lemke, P., Marotzke, J., Masson-Delmotte, V., & Xie, S.-P. (2013). Climate change 2013: The physical science basis, in contribution of Working Group I (WGI) to the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). In.
Chen, C.-C., Wang, Y.-R., Yeh, H.-Y., Lin, T.-H., Huang, C.-S., & Wu, C.-F. (2021). Estimating monthly PM2.5 concentrations from satellite remote sensing data, meteorological variables, and land use data using ensemble statistical modeling and a random forest approach. Environmental Pollution, 291, 118159. https://doi.org/https://doi.org/10.1016/j.envpol.2021.118159
Chen, T.-F., Chang, K.-H., & Lee, C.-H. (2019). Simulation and analysis of causes of a haze episode by combining CMAQ-IPR and brute force source sensitivity method. Atmospheric Environment, 218, 117006. https://doi.org/https://doi.org/10.1016/j.atmosenv.2019.117006
Chen, T.-F., Chang, K.-H., & Tsai, C.-Y. (2014). Modeling direct and indirect effect of long range transport on atmospheric PM2.5 levels. Atmospheric Environment, 89, 1–9. https://doi.org/10.1016/j.atmosenv.2014.01.065
Chuang, M.-T., Chiang, P.-C., Chan, C.-C., Wang, C.-F., Chang, E. E., & Lee, C.-T. (2008). The effects of synoptical weather pattern and complex terrain on the formation of aerosol events in the Greater Taipei area. The Science of the total environment, 399, 128-146. https://doi.org/10.1016/j.scitotenv.2008.01.051
Chuang, M.-T., Fu, J. S., Jang, C. J., Chan, C.-C., Ni, P.-C., & Lee, C.-t. (2008). Simulation of long-range transport aerosols from the Asian Continent to Taiwan by a southward Asian high-pressure system. The Science of the total environment, 406 1-2, 168-179.
Chuang, M.-T., Fu, J. S., Lee, C.-T., Lin, N.-H., Gao, Y., Wang, S.-H., Sheu, G.-R., Hsiao, T.-C., Wang, J.-L., Yen, M.-C., Lin, T.-H., & Thongboonchoo, N. (2016). The Simulation of Long-Range Transport of Biomass Burning Plume and Short-Range Transport of Anthropogenic Pollutants to a Mountain Observatory in East Asia during the 7-SEAS/2010 Dongsha Experiment. Aerosol and Air Quality Research, 16(11), 2933-2949. https://doi.org/10.4209/aaqr.2015.07.0440
Chuang, M.-T., Fu, J. S., Lin, N.-H., Lee, C.-T., Gao, Y., Wang, S.-H., Sheu, G.-R., Hsiao, T.-C., Wang, J.-L., Yen, M.-C., Lin, T.-H., Thongboonchoo, N., & Chen, W.-C. (2015). Simulating the transport and chemical evolution of biomass burning pollutants originating from Southeast Asia during 7-SEAS/2010 Dongsha experiment. Atmospheric Environment, 112, 294-305. https://doi.org/https://doi.org/10.1016/j.atmosenv.2015.04.055
Chuang, M. T., Lee, C. T., & Hsu, H. C. (2018). Quantifying PM(2.5) from long-range transport and local pollution in Taiwan during winter monsoon: An efficient estimation method. J Environ Manage, 227, 10-22. https://doi.org/10.1016/j.jenvman.2018.08.066
Chuang, M. T., Ooi, M. C. G., Lin, N. H., Fu, J. S., Lee, C. T., Wang, S. H., Yen, M. C., Kong, S. S. K., & Huang, W. S. (2020). Study on the impact of three Asian industrial regions on PM2.5 in Taiwan and the process analysis during transport. Atmos. Chem. Phys., 20(23), 14947-14967. https://doi.org/10.5194/acp-20-14947-2020
Dahari, N., Muda, K., Hussein, N., Latif, M. T., Khan, M., & Mohamad Khir, M. S. (2019). Long-Range Transport and Local Emission of Atmospheric PM2.5 in Southern Region of Peninsular Malaysia. IOP Conference Series: Materials Science and Engineering, 636, 012005. https://doi.org/10.1088/1757-899X/636/1/012005
Eck, T., Holben, B., Dubovik, O., Smirnov, A., Goloub, P., Chen, H., Chatenet, B., Gomes, L., Zhang, X. Y., Tsay, S. C., Ji, Q., Giles, D., & Slutsker, I. (2005). Columnar aerosol optical properties at AERONET sites in central Eastern Asia and aerosol transport to the tropical mid-Pacific. Journal of Geophysical Research, 110. https://doi.org/10.1029/2004JD005274
Fuller, R., Landrigan, P. J., Balakrishnan, K., Bathan, G., Bose-O'Reilly, S., Brauer, M., Caravanos, J., Chiles, T., Cohen, A., Corra, L., Cropper, M., Ferraro, G., Hanna, J., Hanrahan, D., Hu, H., Hunter, D., Janata, G., Kupka, R., Lanphear, B., . . . Yan, C. (2022). Pollution and health: a progress update. Lancet Planet Health, 6(6), e535-e547. https://doi.org/10.1016/s2542-5196(22)00090-0
Gao, N., Hopke, P. K., & N, W. R. (1996). Possible Sources for Some Trace Elements Found in Airborne Particles and Precipitation in Dorset, Ontario. J Air Waste Manag Assoc, 46(11), 1035-1047. https://doi.org/10.1080/10473289.1996.10467539
Hu, B., Zhao, X., Liu, H., Liu, Z., Song, T., Wang, Y., Tang, L., Xia, X., Tang, G., Ji, D., Wen, T., Wang, L., Sun, Y., & Xin, J. (2017). Quantification of the impact of aerosol on broadband solar radiation in North China. Scientific Reports, 7(1), 44851. https://doi.org/10.1038/srep44851
Hung, W.-T., Lu, C.-H., Wang, S.-H., Chen, S.-P., Tsai, F., & Chou, C. C. K. (2019). Investigation of long-range transported PM2.5 events over Northern Taiwan during 2005–2015 winter seasons. Atmospheric Environment, 217, 116920. https://doi.org/https://doi.org/10.1016/j.atmosenv.2019.116920
Junker, C., Wang, J.-L., & Lee, C.-T. (2009). Evaluation of the effect of long-range transport of air pollutants on coastal atmospheric monitoring sites in and around Taiwan. Atmospheric Environment, 43(21), 3374-3384. https://doi.org/https://doi.org/10.1016/j.atmosenv.2009.03.035
Kaufman, Y. J., Tanré, D., & Boucher, O. (2002). A satellite view of aerosols in the climate system. Nature, 419(6903), 215-223. https://doi.org/10.1038/nature01091
Lai, H.-C., Dai, Y.-T., Le, L.-P., Pan, B.-H., Lai, L.-W., & Hsiao, M.-C. (2023). Estimation the effect of accumulated long-range transported pollutants during a PM2.5 event in Taiwan. Atmospheric Pollution Research, 14(6), 101758. https://doi.org/https://doi.org/10.1016/j.apr.2023.101758
Lee, S., Kim, M., Kim, S.-Y., Lee, D.-W., Lee, H., Kim, J., Le, S., & Liu, Y. (2021). Assessment of long-range transboundary aerosols in Seoul, South Korea from Geostationary Ocean Color Imager (GOCI) and ground-based observations. Environmental Pollution, 269, 115924. https://doi.org/https://doi.org/10.1016/j.envpol.2020.115924
Levy, R., & Hsu, C. (2015). MODIS atmosphere L2 aerosol product. NASA MODIS adaptive processing system, 25.
Li, H., He, Q., & Liu, X. (2020). Identification of Long-Range Transport Pathways and Potential Source Regions of PM2.5 and PM10 at Akedala Station, Central Asia. Atmosphere, 11(11).
Li, T.-C., Yuan, C.-S., Huang, H.-C., Lee, C.-L., Wu, S.-P., & Tong, C. (2017). Clustered long-range transport routes and potential sources of PM2.5 and their chemical characteristics around the Taiwan Strait. Atmospheric Environment, 148, 152-166. https://doi.org/https://doi.org/10.1016/j.atmosenv.2016.10.010
Lin, C., Li, Y., Lau, A. K. H., Deng, X., Tse, T. K. T., Fung, J. C. H., Li, C., Li, Z., Lu, X., Zhang, X., & Yu, Q. (2016). Estimation of long-term population exposure to PM2.5 for dense urban areas using 1-km MODIS data. Remote Sensing of Environment, 179, 13-22. https://doi.org/https://doi.org/10.1016/j.rse.2016.03.023
Lin, C., Li, Y., Yuan, Z., Lau, A. K. H., Li, C., & Fung, J. C. H. (2015). Using satellite remote sensing data to estimate the high-resolution distribution of ground-level PM2.5. Remote Sensing of Environment, 156, 117-128. https://doi.org/https://doi.org/10.1016/j.rse.2014.09.015
Lin, C.-C., Chen, W.-N., Loftus, A. M., Lin, C.-Y., Fu, Y.-T., Peng, C.-M., & Yen, M.-C. (2017). Influences of the Long-Range Transport of Biomass-Burning Pollutants on Surface Air Quality during 7-SEAS Field Campaigns. Aerosol and Air Quality Research, 17(10), 2595-2607. https://doi.org/10.4209/aaqr.2017.08.0273
Lin, C.-Y., Chou, C. C. K., Wang, Z., Lung, S.-C., Lee, C.-T., Yuan, C.-S., Chen, W.-N., Chang, S.-Y., Hsu, S.-C., Chen, W.-C., & Liu, S. C. (2012). Impact of different transport mechanisms of Asian dust and anthropogenic pollutants to Taiwan. Atmospheric Environment, 60, 403-418. https://doi.org/https://doi.org/10.1016/j.atmosenv.2012.06.049
Lin, N.-H., Sayer, A. M., Wang, S.-H., Loftus, A. M., Hsiao, T.-C., Sheu, G.-R., Hsu, N. C., Tsay, S.-C., & Chantara, S. (2014). Interactions between biomass-burning aerosols and clouds over Southeast Asia: Current status, challenges, and perspectives. Environmental Pollution, 195, 292-307. https://doi.org/https://doi.org/10.1016/j.envpol.2014.06.036
Lin, N.-H., Tsay, S.-C., Maring, H. B., Yen, M.-C., Sheu, G.-R., Wang, S.-H., Chi, K. H., Chuang, M.-T., Ou-Yang, C.-F., Fu, J. S., Reid, J. S., Lee, C.-T., Wang, L.-C., Wang, J.-L., Hsu, C. N., Sayer, A. M., Holben, B. N., Chu, Y.-C., Nguyen, X. A., . . . Liu, G.-R. (2013). An overview of regional experiments on biomass burning aerosols and related pollutants in Southeast Asia: From BASE-ASIA and the Dongsha Experiment to 7-SEAS. Atmospheric Environment, 78, 1-19. https://doi.org/https://doi.org/10.1016/j.atmosenv.2013.04.066
Lin, T.-H., Tsay, S.-C., Lien, W.-H., Lin, N.-H., & Hsiao, T.-C. (2021). Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading. Remote Sensing, 13(8), 1544. https://www.mdpi.com/2072-4292/13/8/1544
Liu, T.-H., Tsai, F., Hsu, S.-C., Hsu, C.-W., Shiu, C.-J., Chen, W.-N., & Tu, J.-Y. (2009). Southeastward transport of Asian dust: Source, transport and its contributions to Taiwan. Atmospheric Environment, 43(2), 458-467. https://doi.org/https://doi.org/10.1016/j.atmosenv.2008.07.066
Manisalidis, I., Stavropoulou, E., Stavropoulos, A., & Bezirtzoglou, E. (2020). Environmental and Health Impacts of Air Pollution: A Review [Review]. Frontiers in Public Health, 8. https://doi.org/10.3389/fpubh.2020.00014
Molnár, P., Tang, L., Sjöberg, K., & Wichmann, J. (2017). Long-range transport clusters and positive matrix factorization source apportionment for investigating transboundary PM2.5 in Gothenburg, Sweden. Environ. Sci.: Processes Impacts, 19. https://doi.org/10.1039/C7EM00122C
Na, K., Sawant, A. A., Song, C., & Cocker, D. R. (2004). Primary and secondary carbonaceous species in the atmosphere of Western Riverside County, California. Atmospheric Environment, 38(9), 1345-1355. https://doi.org/https://doi.org/10.1016/j.atmosenv.2003.11.023
O'Doherty, S., Simmonds, P. G., Cunnold, D. M., Wang, H. J., Sturrock, G. A., Fraser, P. J., Ryall, D., Derwent, R. G., Weiss, R. F., Salameh, P., Miller, B. R., & Prinn, R. G. (2001). In situ chloroform measurements at Advanced Global Atmospheric Gases Experiment atmospheric research stations from 1994 to 1998. Journal of Geophysical Research: Atmospheres, 106(D17), 20429-20444. https://doi.org/https://doi.org/10.1029/2000JD900792
Owili, P. O., Lin, T.-H., Muga, M. A., & Lien, W.-H. (2020). Impacts of discriminated PM2.5 on global under-five and maternal mortality. Scientific Reports, 10(1), 17654. https://doi.org/10.1038/s41598-020-74437-7
Parkinson, C. L., Closs, J., & Greenstone, R. (2013). EOS Data Products Handbook.
Ramanathan, V., & Feng, Y. (2009). Air pollution, greenhouse gases and climate change: Global and regional perspectives. Atmospheric Environment, 43(1), 37-50. https://doi.org/https://doi.org/10.1016/j.atmosenv.2008.09.063
Sano, I., Mukai, M., Iguchi, N., & Mukai, S. (2010). Suspended particulate matter sampling at an urban AERONET site in Japan, part 2: relationship between column aerosol optical thickness and PM2.5 concentration. Journal of Applied Remote Sensing, 4, 043504-043504. https://doi.org/10.1117/1.3327930
Shi, Y., Matsunaga, T., Yamaguchi, Y., Li, Z., Gu, X., & Chen, X. (2018). Long-term trends and spatial patterns of satellite-retrieved PM2.5 concentrations in South and Southeast Asia from 1999 to 2014. Science of The Total Environment, 615, 177-186. https://doi.org/https://doi.org/10.1016/j.scitotenv.2017.09.241
Shimadera, H., Kojima, T., & Kondo, A. (2016). Evaluation of Air Quality Model Performance for Simulating Long-Range Transport and Local Pollution of PM2.5 in Japan. Advances in Meteorology, 2016(1), 5694251. https://doi.org/https://doi.org/10.1155/2016/5694251
Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J. B., Cohen, M. D., & Ngan, F. (2015). NOAA’s HYSPLIT Atmospheric Transport and Dispersion Modeling System. Bulletin of the American Meteorological Society, 96(12), 2059-2077. https://doi.org/https://doi.org/10.1175/BAMS-D-14-00110.1
Stohl, A. (1998). Computation, accuracy and applications of trajectories—A review and bibliography. Atmospheric Environment, 32, 947-966.
Su, S.-H., Chang, C.-W., & Chen, W.-T. (2020). The Temporal Evolution of PM2.5 Pollution Events in Taiwan: Clustering and the Association with Synoptic Weather. Atmosphere, 11, 1265. https://doi.org/10.3390/atmos11111265
Tsay, S.-C., Maring, H., Lin, N.-H., Buntoung, S., Chantara, S., Chuang, H.-C., Gabriel, P., Goodloe, C., Holben, B., Hsiao, T.-C., Hsu, N., Janjai, S., Lau, W., Lee, C.-T., Lee, J., Loftus, A., Anh, N., Nguyen, C., Pani, S., & Yen, M.-C. (2016). Satellite-Surface Perspectives of Air Quality and Aerosol-Cloud Effects on the Environment: An Overview of 7-SEAS/BASELInE. Aerosol and Air Quality Research, 16, 2581-2602. https://doi.org/10.4209/aaqr.2016.08.0350
van Donkelaar, A., Martin, R. V., Brauer, M., & Boys, B. L. (2015). Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter. Environ Health Perspect, 123(2), 135-143. https://doi.org/10.1289/ehp.1408646
van Donkelaar, A., Martin, R. V., Brauer, M., Hsu, N. C., Kahn, R. A., Levy, R. C., Lyapustin, A., Sayer, A. M., & Winker, D. M. (2016). Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors. Environmental Science & Technology, 50(7), 3762-3772. https://doi.org/10.1021/acs.est.5b05833
Wang, S.-H., Hung, W.-T., Chang, S.-C., & Yen, M.-C. (2015). Transport characteristics of Chinese haze over Northern Taiwan in winter, 2005-2014. Atmospheric Environment, 126. https://doi.org/10.1016/j.atmosenv.2015.11.043
Wang, X., Zhang, R., & Yu, W. (2019). The Effects of PM2.5 Concentrations and Relative Humidity on Atmospheric Visibility in Beijing. Journal of Geophysical Research: Atmospheres, 124(4), 2235-2259. https://doi.org/https://doi.org/10.1029/2018JD029269
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. https://doi.org/https://doi.org/10.1016/j.atmosenv.2018.12.004
Wei, X., Chang, N.-B., Bai, K., & Gao, W. (2020). Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives. Critical Reviews in Environmental Science and Technology, 50, 1640-1725. https://doi.org/10.1080/10643389.2019.1665944
Yoshida, M., Kikuchi, M., Nagao, T. M., Murakami, H., Nomaki, T., & Higurashi, A. (2018). Common Retrieval of Aerosol Properties for Imaging Satellite Sensors. Journal of the Meteorological Society of Japan. Ser. II, 96B, 193-209. https://doi.org/10.2151/jmsj.2018-039
Zhang, Y., Cai, Y.-J., Yu, F., Luo, G., & Chou, C. C. K. (2021). Seasonal Variations and Long-term Trend of Mineral Dust Aerosols over the Taiwan Region. Aerosol and Air Quality Research, 21(5), 200433. https://doi.org/10.4209/aaqr.2020.07.0433