PBL 發展和山谷風環流對泰北生質燃燒霾害日夜變化的影響

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：1

、訪客IP：18.116.239.195

姓名

阿彌陀(Amit Bhujel) 查詢紙本館藏

畢業系所

大氣科學學系

論文名稱

PBL 發展和山谷風環流對泰北生質燃燒霾害日夜變化的影響
(Effects of PBL Development and Mountain-Valley Circulation on Diurnal Variation of Biomass Burning Haze in Northern Thailand)

相關論文

★ 鹿林山背景站大氣輻射及氣膠輻射驅動力之研究	★ 中南半島生質燃燒氣膠濃度分布之年際變化與其對區域環境衝擊研究
★ 中壢地區光達消光散射比之長期分析與污染物關聯性研究	★ 臺灣大氣背景PM2.5質量濃度之推估
★ 雲林斗六PM2.5濃度變化與氣膠光學特性及氣象條件之關聯性研究	★ Mapping Surface Solar Radiation with Satellite Data over Taiwan
★ 開發適用於大氣邊界層觀測的無人機系統	★ 利用AERONET資料解析中南半島地區氣膠種類及成分
★ 氣膠對臺灣北部暖雲微物理和毛雨的影響	★ Characteristics and Corrections of Thermal Offset for Secondary Standard Pyranometers
★ 氣膠對臺灣中部平原夏季降水日變化之影響	★ 中南半島生質燃燒氣膠傳送動力機制及區域氣候反饋
★ 2019年春季泰國北部無人機觀測實驗: 邊界層特徵與氣膠垂直分布之研究	★ Investigating hygroscopic cloud-seeding effects in liquid-water clouds in northern Taiwan: in-situ measurements and model simulation
★ 整合無人機與光達觀測解析斗六地區空污事件之演變過程	★ 氣膠光學及微物理反演法開發：以鹿林山大氣背景站應用為例

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 (2025-6-1以後開放)

摘要(中)

春季生質燃燒為眾所周知的東南亞細懸浮微粒(PM2.5)主要污染源。為了解泰國北部(清邁省)生質燃燒好發期間 (2019 年春季) ，生質燃燒氣膠於不同地形、時間與空間的分布情形，本研究利用低成本 PM2.5 微型感器系統 (Aerobox)、氣膠遙測觀測網 (AERONET) 網絡進行監測，部署於泰北山區的三個地點：山頂測站 (Doi Ang Khang) 、山谷小鎮 (Fang)和山腳大城市 (Chiang Mai) ，並配合方縣 (Fang)部屬光達(mini-MPL) 監測氣膠垂直分布，再透過 (1) 線性回歸、 (2) 多元線性相關和 (3) 隨機森林機器學習算法，校正 Aerobox 的觀測數據。
結果顯示三個測站PM2.5日平均值趨勢相似，而PM2.5與火點日平均並不一致。因地面PM2.5日變化受邊界層 (PBL)發展與地形影響，使PM2.5於日出後隨PBL逐漸增加而減少，而午後 PBL 高度下降後PM2.5隨之上升，直到入夜後 PM2.5濃度將恢復為夜間值，此變化發生的確切時間和規模因地點而異。地表 PM2.5 的日均值與 AOD 具有中等到高度的相關性，而小時值相關性受日夜變化影響，相關性較低。各站PM2.5與AERONET AOD小時相關係數分別為0.59 (Chiang Mai) 、0.51 (Fang)、0.45 (Doi Ang Khang) ，各站PM2.5與衛星 AOD小時相關係數分別為在 0.39 (Chiang Mai) 、 0.46 (Fang)、 0.27 (Doi Ang Khang) 。 AERONET AOD與衛星AOD具高度相關性。光達觀測結果表示，山谷PBL累積氣膠導致 AOD 達到峰值，當PBL在早晨上升時，周圍山脈高度以下的污染物傳送，伴隨殘留污染物被夾帶到PBL中。結合氣象條件對氣膠空間分布的分析表示，山谷環流對氣膠在夜間山谷積累和日間擴散扮演重要角色，氣膠在夜間流入導致埃指數 (AE)增加，而日間氣膠的粒徑大小取決於氣膠吸濕增長效應，相對濕度的晝夜循環由空氣溫度決定。總結本研究分析結果，復雜地形區域地面 PM2.5 和垂直柱狀氣膠變化差異可能很大，而低成本微型感測器可為複雜地形內空品提供可靠的參考依據。

摘要(英)

Emission from biomass burning has been known to be a major source of particulate matter (including PM2.5; cut sizes ≤ 2.5 μm) in southeast Asia that peaks during the spring season. This study aims to understand the diurnal pattern of temporal and vertical dispersion of aerosols across varying terrain of Chiang Mai province of Thailand during the peak biomass burning period – spring season, 2019. For this purpose, the low-cost PM2.5 sensor system, Aerobox, and ambient weather stations were deployed at three sites: Doi Ang Khang located at the hilltop, Fang valley with a medium-sized town, and Chiang Mai valley containing a large city. Each of these sites were co-located with Cimel sunphotometer of NASA’s AERONET network. The vertical profile of aerosol loading was obtained by the mini-MPL and UAV-mounted Aeromount deployed at Fang valley. Three methods – simple linear regression, multiple linear correlation, and random forest machine learning algorithm – were tested to correct data from Aerobox. This study shows that widespread haze is formed that travels back and forth throughout the Chiang Mai province. The meteorological parameters showed clear diurnal variation throughout most of the period and the PM2.5 and AOD followed the pattern. The daily average of surface PM2.5 had a moderate to high correlation with AOD while the correlation of hourly averaged data was lower and was biased by the time of day. The diurnal variation of biomass-burning aerosols in the valleys of northern Thailand was observed to be governed by a combination of factors like the complex terrain, metrological condition, PBL development and mountain-valley circulation. The nocturnal air quality in the valley was observed to be poor with a secondary peak in PM2.5 during the midnight as a combined result of low PBL height, stable atmosphere, closed terrain and katabatic flow. The influx of aerosols at night increased quantity of finer-sized aerosols despite high humidity while at day, the size of aerosols was governed by the diurnal cycle of air temperature. The vertical profile of NRB showed that the nocturnal boundary layer height was shallow with residual layer on top of it which splits into two parts. The upper residual layer was observed to get dispersed and transported away while the lower layer got mixed back into the morning-time boundary layer. A combination of shallow mixing height, re-mixing of residual layer into the valley and day-time emission of aerosols seem to have contributed to the peak PM2.5 concentration during the morning in the valleys. In the afternoon, a sudden rise in mixing layer height was observed due to the vertical coupling between mountain atmospheric boundary layer which allows aerosols to get mixed up to higher altitude where it can be carried away by prevalent wind. Along with that, the day-time circulation also aided the reduction of aerosols in the valley. This study showcases how a
network of low-cost instruments can be integrated with conventional measurement approaches to understand air-quality variation in complex terrains.

關鍵字(中)

★ 邊界層(PBL)
★ 山谷風環流
★ 微型微脈衝光達
★ 低成本微型感測器
★ 氣膠光學厚度

關鍵字(英)

★ Aerosol optical depth
★ Low-cost PM2.5 measurement
★ PBL
★ Mountain-valley breeze
★ Diurnal pattern

論文目次

Abstract i
摘要 iii
Acknowledgement iv
Table of Contents vi
List of Figures viii
List of Tables xii
List of Abbreviations xiii
Explanation of Symbols xv
Chapter 1: Introduction 1
1.1 Objectives 4
1.2 Scope and Limitations 4
Chapter 2: Literature Review 5
2.1 Mountain-Valley Circulation 5
2.1.1 Basic Mountain-Valley Circulation: 5
2.1.2 Interaction of Valley Circulation with PBL and Mountain Wave: 8
2.2 AERONET 10
2.2.1 Classification of Aerosols Based on AERONET Data 10
2.2.2 Applications of AERONET Data 11
Chapter 3: Data and Methodology 14
3.1 Site Description 14
3.2 Instrument and Data Description 16
3.2.1 Aerobox: Low-cost PM2.5 Sensor with Meteorological Sensors 19
3.2.2 Ground-based Remote Sensing of Aerosol Optical Depth (AOD) 21
3.2.3 Satellite-based Remote Sensing of AOD and Fire Data 22
3.2.4 Measurement of Vertical Distribution of Aerosols 23
Chapter 4: Results and Discussions 26
4.1 Spatiotemporal Variation of PM2.5, AOD and Fire count 26
4.2 Diurnal Variation of AOD and PM2.5 31
4.3 Correlation of PM2.5 with AOD 34
4.4 Vertical Variation of Aerosols 40
4.4.1 Comparison PBL Height Obtained from Lidar and In-situ Measurement 40
4.4.2 Diurnal Cycle on a Normal Day 41
4.4.3 Diurnal Variation of Aerosols on a Day with Stable Synoptic Condition 42
4.5 Influence of Meteorology on the Development of Biomass-Burning Smoke Plumes 45
4.5.1 Overview of Meteorological Condition 45
4.5.2 Influence of Meteorology on Pollution Development 58
Chapter 5: Validation of MAIAC Smoke Plume Injection Height 70
5.1 Comparison with Lidar Measurement 71
5.2 Comparison with UAV Measurement 74
Chapter 6: Conclusion 76
Chapter 7: Recommendation for Future Works 78
Chapter 8: References 79

參考文獻

Abel, S. J., Highwood, E. J., Haywood, J. M., & Stringer, M. A. (2005). The direct radiative effect of biomass burning aerosols over southern Africa. Atmospheric Chemistry and Physics, 5(7), 1999–2018. https://doi.org/10.5194/ACP-5-1999-2005
Adler, B., & Kalthoff, N. (2014). Multi-scale Transport Processes Observed in the Boundary Layer over a Mountainous Island. Boundary-Layer Meteorology, 153(3), 515–537. https://doi.org/10.1007/S10546-014-9957-8/FIGURES/10
Alfano, B., Barretta, L., Giudice, A. del, de Vito, S., Francia, G. di, Esposito, E., Formisano, F., Massera, E., Miglietta, M. L., & Polichetti, T. (2020). A Review of Low-Cost Particulate Matter Sensors from the Developers’ Perspectives. Sensors (Basel, Switzerland), 20(23), 1–56. https://doi.org/10.3390/S20236819
Anoruo, C. M. (2020). Validation of OMI seasonal and spatio-temporal variations in aerosol-cloud interactions over Banizoumbou using AERONET data. Journal of Atmospheric and Solar-Terrestrial Physics, 211, 105457. https://doi.org/10.1016/J.JASTP.2020.105457
Barreto, Á., Cuevas, E., Granados-Muñoz, M. J., Alados-Arboledas, L., Romero, P. M., Gröbner, J., Kouremeti, N., Almansa, A. F., Stone, T., Toledano, C., Román, R., Sorokin, M., Holben, B., Canini, M., & Yela, M. (2016). The new sun-sky-lunar Cimel CE318-T multiband photometer – A comprehensive performance evaluation. Atmospheric Measurement Techniques, 9(2), 631–654. https://doi.org/10.5194/AMT-9-631-2016
Berkoff, T. A., Sorokin, M., Stone, T., Eck, T. F., Hoff, R., Welton, E., & Holben, B. (2011). Nocturnal Aerosol Optical Depth Measurements with a Small-Aperture Automated Photometer Using the Moon as a Light Source. Journal of Atmospheric and Oceanic Technology, 28(10), 1297–1306. https://doi.org/10.1175/JTECH-D-10-05036.1
Boucher, O. (2015). Atmospheric Aerosols. Springer Netherlands. https://doi.org/10.1007/978-94-017-9649-1
Bright, J. M., & Gueymard, C. A. (2019). Climate-specific and global validation of MODIS Aqua and Terra aerosol optical depth at 452 AERONET stations. Solar Energy, 183, 594–605. https://doi.org/10.1016/J.SOLENER.2019.03.043
Bulot, F. M. J., Johnston, S. J., Basford, P. J., Easton, N. H. C., Apetroaie-Cristea, M., Foster, G. L., Morris, A. K. R., Cox, S. J., & Loxham, M. (2019). Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment. Scientific Reports 2019 9:1, 9(1), 1–13. https://doi.org/10.1038/s41598-019-43716-3
Burg, B. R., Ruch, P., Paredes, S., & Michel, B. (2015). Placement and efficiency effects on radiative forcing of solar installations. AIP Conference Proceedings, 1679(1), 090001. https://doi.org/10.1063/1.4931546
Burg, B. R., Ruch, P., Paredes, S., & Michel, B. (2017). Effects of radiative forcing of building integrated photovoltaic systems in different urban climates. Solar Energy, 147, 399–405. https://doi.org/10.1016/J.SOLENER.2017.03.004
Calinoiu, D., Paulescu, M., Ionel, I., Stefu, N., Pop, N., Boata, R., Pacurar, A., Gravila, P., Paulescu, E., & Trif-Tordai, G. (2013). Influence of aerosols pollution on the amount of collectable solar energy. Energy Conversion and Management, 70, 76–82. https://doi.org/10.1016/J.ENCONMAN.2013.02.012
Campbell, J. R., Hlavka, D. L., Welton, E. J., Flynn, C. J., Turner, D. D., Spinhirne, J. D., Scott, V. S. I., & Hwang, I. H. (2002). Full-time, eye-safe cloud and aerosol lidar observation at atmospheric radiation measurement program sites: Instruments and data processing. Journals.Ametsoc.Org, 19(4), 431–442. https://doi.org/https://doi.org/10.1175/1520-0426(2002)019<0431:FTESCA>2.0.CO;2
Castell, N., Dauge, F. R., Schneider, P., Vogt, M., Lerner, U., Fishbain, B., Broday, D., & Bartonova, A. (2017). Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates? Environment International, 99, 293–302. https://doi.org/10.1016/j.envint.2016.12.007
Chen, Q. X., Han, X. L., Gu, Y., Yuan, Y., Jiang, J. H., Yang, X. B., Liou, K. N., & Tan, H. P. (2022). Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land. Atmospheric Research, 265, 105810. https://doi.org/10.1016/J.ATMOSRES.2021.105810
Cheng, F. Y., Yang, Z. M., Ou-Yang, C. F., & Ngan, F. (2013). A numerical study of the dependence of long-range transport of CO to a mountain station in Taiwan on synoptic weather patterns during the Southeast Asia biomass-burning season. Atmospheric Environment, 78, 277–290. https://doi.org/10.1016/j.atmosenv.2013.03.020
di Antonio, A., Popoola, O. A. M., Ouyang, B., Saffell, J., & Jones, R. L. (2018). Developing a Relative Humidity Correction for Low-Cost Sensors Measuring Ambient Particulate Matter. Sensors 2018, Vol. 18, Page 2790, 18(9), 2790. https://doi.org/10.3390/S18092790
Drame, M., Ould Bilal, B., Camara, M., Sambou, V., & Gaye, A. (2012). Impacts of aerosols on available solar energy at Mbour, Senegal. Journal of Renewable and Sustainable Energy, 4(1), 013105. https://doi.org/10.1063/1.3682078
Eck, T. F., Holben, B. N., Reid, J. S., Sinyuk, A., Hyer, E. J., O’Neill, N. T., Shaw, G. E., Castle, J. R. vande, Chapin, F. S., Dubovik, O., Smirnov, A., Vermote, E., Schafer, J. S., Giles, D., Slutsker, I., Sorokine, M., & Newcomb, W. W. (2009). Optical properties of boreal region biomass burning aerosols in central Alaska and seasonal variation of aerosol optical depth at an Arctic coastal site. Journal of Geophysical Research. Vol.114: D11201, 114, 11201. https://doi.org/10.102912008jdoi0870
Gautam, R., Hsu, N. C., Eck, T. F., Holben, B. N., Janjai, S., Jantarach, T., Tsay, S. C., & Lau, W. K. (2013). Characterization of aerosols over the Indochina peninsula from satellite-surface observations during biomass burning pre-monsoon season. Atmospheric Environment, 78, 51–59. https://doi.org/10.1016/j.atmosenv.2012.05.038
Giles, D. M., Holben, B. N., Eck, T. F., Sinyuk, A., Smirnov, A., Slutsker, I., Dickerson, R. R., Thompson, A. M., & Schafer, J. S. (2012). An analysis of AERONET aerosol absorption properties and classifications representative of aerosol source regions. Journal of Geophysical Research: Atmospheres, 117(D17), 17203. https://doi.org/10.1029/2012JD018127
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. v., & Lyapustin, A. I. (2019). Advancements in the Aerosol Robotic Network (AERONET) Version 3 database - Automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements. Atmospheric Measurement Techniques, 12(1), 169–209. https://doi.org/10.5194/AMT-12-169-2019
He, M., Kuerbanjiang, N., & Dhaniyala, S. (2019). Performance characteristics of the low-cost Plantower PMS optical sensor. Https://Doi.Org/10.1080/02786826.2019.1696015, 54(2), 232–241. https://doi.org/10.1080/02786826.2019.1696015
Ho, T. K. (1995). Random decision forests. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 1, 278–282. https://doi.org/10.1109/ICDAR.1995.598994
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer, A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F., Jankowiak, I., & Smirnov, A. (1998). AERONET—A Federated Instrument Network and Data Archive for Aerosol Characterization. Remote Sensing of Environment, 66(1), 1–16. https://doi.org/10.1016/S0034-4257(98)00031-5
Hsu, N. C., Jeong, M. J., Bettenhausen, C., Sayer, A. M., Hansell, R., Seftor, C. S., Huang, J., & Tsay, S. C. (2013). Enhanced Deep Blue aerosol retrieval algorithm: The second generation. Journal of Geophysical Research Atmospheres, 118(16), 9296–9315. https://doi.org/10.1002/jgrd.50712
Hsu, N. C., Lee, J., Sayer, A. M., Kim, W., Bettenhausen, C., & Tsay, S. C. (2019). VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long-Term Aerosol Data Records. Journal of Geophysical Research: Atmospheres, 124(7), 4026–4053. https://doi.org/10.1029/2018JD029688
Hsu, N. C., Tsay, S. C., King, M. D., & Herman, J. R. (2004). Aerosol properties over bright-reflecting source regions. IEEE Transactions on Geoscience and Remote Sensing, 42(3), 557–569. https://doi.org/10.1109/TGRS.2004.824067
Hsu, N. C., Tsay, S. C., King, M. D., & Herman, J. R. (2006). Deep Blue retrievals of Asian aerosol properties during ACE-Asia. IEEE Transactions on Geoscience and Remote Sensing, 44(11), 3180–3195. https://doi.org/10.1109/TGRS.2006.879540
Justice, C. O., Giglio, L., Korontzi, S., Owens, J., Morisette, J. T., Roy, D., Descloitres, J., Alleaume, S., Petitcolin, F., & Kaufman, Y. (2002). The MODIS fire products. Remote Sensing of Environment, 83(1–2), 244–262. https://doi.org/10.1016/S0034-4257(02)00076-7
Kalthoff, N., Adler, B., & Bischoff-Gauss, I. (2020). Spatio-temporal Structure of the Boundary Layer under the Impact of Mountain Waves. Meteorologische Zeitschrift, 29(5), 409–424. https://doi.org/10.1127/METZ/2020/1033
Karagulian, F., Barbiere, M., Kotsev, A., Spinelle, L., Gerboles, M., Lagler, F., Redon, N., Crunaire, S., & Borowiak, A. (2019). Review of the performance of low-cost sensors for air quality monitoring. In Atmosphere (Vol. 10, Issue 9). MDPI AG. https://doi.org/10.3390/atmos10090506
Karaoghlanian, N., Noureddine, B., Saliba, N., Shihadeh, A., & Lakkis, I. (2022). Low cost air quality sensors “PurpleAir” calibration and inter-calibration dataset in the context of Beirut, Lebanon. Data in Brief, 41, 108008. https://doi.org/10.1016/J.DIB.2022.108008
Kaufman, Y. J., Wald, A. E., Remer, L. A., Gao, B. C., Li, R. R., & Flynn, L. (1997). MODIS 2.1-μm channel - correlation with visible reflectance for use in remote sensing of aerosol. IEEE Transactions on Geoscience and Remote Sensing, 35(5), 1286–1298. https://doi.org/10.1109/36.628795
Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., & Hsu, N. C. (2013). The Collection 6 MODIS aerosol products over land and ocean. Atmospheric Measurement Techniques, 6(11), 2989–3034. https://doi.org/10.5194/amt-6-2989-2013
Levy, R. C., Remer, L. A., Mattoo, S., Vermote, E. F., & Kaufman, Y. J. (2007). Second-generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance. Journal of Geophysical Research Atmospheres, 112(13). https://doi.org/10.1029/2006JD007811
Lin, C. A., Zhang, Y., Heath, G., Henze, D. K., Sengupta, M., & Lu, C. H. (2023). Improvement of aerosol optical depth data for localized solar resource assessment. Solar Energy, 249, 457–466. https://doi.org/10.1016/J.SOLENER.2022.11.047
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/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. Te, 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/10.1016/J.ATMOSENV.2013.04.066
Liousse, C., Devaux, C., Dulac, F., & Cachier, H. (1995). Aging of savanna biomass burning aerosols: Consequences on their optical properties. Journal of Atmospheric Chemistry 1995 22:1, 22(1), 1–17. https://doi.org/10.1007/BF00708178
Ludwig, F. L., Horel, J., & Whiteman, C. D. (2004). Using EOF analysis to identify important surface wind patterns in mountain valleys. Journals.Ametsoc.Org, 43, 969–983. https://doi.org/https://doi.org/10.1175/1520-0450(2004)043<0969:UEATII>2.0.CO;2
Lyapustin, A., & Wang, Y. (2018). MCD19A2 MODIS/Terra+Aqua Land Aerosol Optical Depth Daily L2G Global 1km SIN Grid V006 [Data set]. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MODIS/MCD19A2.006
Madhavan, B. L., He, Y., Wu, Y., Gross, B., Moshary, F., & Ahmed, S. (2012). Development of a Ground Based Remote Sensing Approach for Direct Evaluation of Aerosol-Cloud Interaction. Atmosphere 2012, Vol. 3, Pages 468-494, 3(4), 468–494. https://doi.org/10.3390/ATMOS3040468
Masoom, A., Kosmopoulos, P., Bansal, A., Gkikas, A., Proestakis, E., Kazadzis, S., & Amiridis, V. (2021). Forecasting dust impact on solar energy using remote sensing and modeling techniques. Solar Energy, 228, 317–332. https://doi.org/10.1016/J.SOLENER.2021.09.033
Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou. (2021). IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. https://www.ipcc.ch/report/ar6/wg1/#FullReport
MPLNET Product Information. (n.d.). Retrieved March 2, 2023, from https://mplnet.gsfc.nasa.gov/product-info/
Nemet, G. F. (2009). Net radiative forcing from widespread deployment of photovoltaics. Environmental Science and Technology, 43(6), 2173–2178. https://doi.org/10.1021/ES801747C/SUPPL_FILE/ES801747C_SI_001.PDF
Pani, S. K., Wang, S. H., Lin, N. H., Chantara, S., Lee, C. te, & Thepnuan, D. (2020). Black carbon over an urban atmosphere in northern peninsular Southeast Asia: Characteristics, source apportionment, and associated health risks. Environmental Pollution, 259, 113871. https://doi.org/10.1016/J.ENVPOL.2019.113871
Pani, S. K., Wang, S. H., Lin, N. H., Lee, C. te, Tsay, S. C., Holben, B. N., Janjai, S., Hsiao, T. C., Chuang, M. T., & Chantara, S. (2016). Radiative effect of springtime biomass-burning aerosols over northern indochina during 7-SEAS/BASELInE 2013 campaign. Aerosol and Air Quality Research, 16(11), 2802–2817. https://doi.org/10.4209/aaqr.2016.03.0130
Pilinis, C., Charalampidis, P. E., Mihalopoulos, N., & Pandis, S. N. (2014). Contribution of particulate water to the measured aerosol optical properties of aged aerosol. Atmospheric Environment, 82, 144–153. https://doi.org/10.1016/J.ATMOSENV.2013.10.024
Punsompong, P., Pani, S. K., Wang, S. H., & Bich Pham, T. T. (2021). Assessment of biomass-burning types and transport over Thailand and the associated health risks. Atmospheric Environment, 247, 118176. https://doi.org/10.1016/J.ATMOSENV.2020.118176
Sato, M., Hansen, J., Koch, D., Lacis, A., Ruedy, R., Dubovik, O., Holben, B., Chin, M., & Novakov, T. (2003). Global atmospheric black carbon inferred from AERONET. Proceedings of the National Academy of Sciences of the United States of America, 100(11), 6319–6324. https://doi.org/10.1073/PNAS.0731897100/SUPPL_FILE/1897FIG7.PDF
She, L., Zhang, H. K., Li, Z., de Leeuw, G., & Huang, B. (2020). Himawari-8 Aerosol Optical Depth (AOD) Retrieval Using a Deep Neural Network Trained Using AERONET Observations. Remote Sensing 2020, Vol. 12, Page 4125, 12(24), 4125. https://doi.org/10.3390/RS12244125
Solanki, R., Macatangay, R., Sakulsupich, V., Sonkaew, T., & Mahapatra, P. S. (2019). Mixing Layer Height Retrievals From MiniMPL Measurements in the Chiang Mai Valley: Implications for Particulate Matter Pollution. Frontiers in Earth Science, 7, 308. https://doi.org/10.3389/FEART.2019.00308/BIBTEX
Stavroulas, I., Grivas, G., Michalopoulos, P., Liakakou, E., Bougiatioti, A., Kalkavouras, P., Fameli, K. M., Hatzianastassiou, N., Mihalopoulos, N., & Gerasopoulos, E. (2020). Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece. Atmosphere 2020, Vol. 11, Page 926, 11(9), 926. https://doi.org/10.3390/ATMOS11090926
Stewart, J. Q., Whiteman, C. D., W. James Steenburgh, & Bian, X. (2002). A climatological study of thermally driven wind systems of the US Intermountain West. Journals.Ametsoc.Org, 699–708. https://doi.org/https://doi.org/10.1175/1520-0477(2002)083<0699:ACSOTD>2.3.CO;2
Streets, D. G., Yarber, K. F., Woo, J. H., & Carmichael, G. R. (2003). Biomass burning in Asia: Annual and seasonal estimates and atmospheric emissions. Global Biogeochemical Cycles, 17(4). https://doi.org/10.1029/2003gb002040
Stull, R. B. (1988). Geographic Effects. An Introduction to Boundary Layer Meteorology, 587–618. https://doi.org/10.1007/978-94-009-3027-8_14
Tsay, S. C., Hsu, N. C., Lau, W. K. M., Li, C., Gabriel, P. M., Ji, Q., Holben, B. N., Judd Welton, E., Nguyen, A. X., Janjai, S., Lin, N. H., Reid, J. S., Boonjawat, J., Howell, S. G., Huebert, B. J., Fu, J. S., Hansell, R. A., Sayer, A. M., Gautam, R., … Pantina, P. (2013). From BASE-ASIA toward 7-SEAS: A satellite-surface perspective of boreal spring biomass-burning aerosols and clouds in Southeast Asia. Atmospheric Environment, 78, 20–34. https://doi.org/10.1016/j.atmosenv.2012.12.013
Tsay, S. C., Maring, H. B., Lin, N. H., Buntoung, S., Chantara, S., Chuang, H. C., Gabriel, P. M., Goodloe, C. S., Holben, B. N., Hsiao, T. C., Christina Hsu, N., Janjai, S., Lau, W. K. M., Lee, C. te, Lee, J., Loftus, A. M., Nguyen, A. X., Nguyen, C. M., Pani, S. K., … 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(11), 2581–2602. https://doi.org/10.4209/aaqr.2016.08.0350
Tsay, S.-C., Maring, H. B., Lin, N.-H., Buntoung, S., Chantara, S., Chuang, H.-C., Gabriel, P. M., Goodloe, C. S., Holben, B. N., Hsiao, T.-C., Hsu, N. C., Janjai, S., Lau, W. K. M., Lee, C.-T., Lee, J., Loftus, A. M., Nguyen, A. X., Nguyen, C. M., Pani, S. K., … 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
Varble, A., Nesbitt, S., Salio, P., Zipser, E., van den Heever, S., McFarquhar, G., Kollias, P., Kreidenweis, S., DeMott, P., Jensen, M., Houze, Jr. , R., Rasmussen, K., Leung, R., Romps, D., Gochis, D., Avila, E., & Williams, C. (2017). Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Preliminary Science Plan. Journal of Geophysical Research: Atmospheres, 126(12). https://doi.org/10.1029/2021JD034722
Wang, S. H., Tsay, S. C., Lin, N. H., Chang, S. C., Li, C., Welton, E. J., Holben, B. N., Hsu, N. C., Lau, W. K. M., Lolli, S., Kuo, C. C., Chia, H. P., Chiu, C. Y., Lin, C. C., Bell, S. W., Ji, Q., Hansell, R. A., Sheu, G. R., Chi, K. H., & Peng, C. M. (2013). Origin, transport, and vertical distribution of atmospheric pollutants over the northern South China Sea during the 7-SEAS/Dongsha Experiment. Atmospheric Environment, 78, 124–133. https://doi.org/10.1016/j.atmosenv.2012.11.013
Wang, S. H., Welton, E. J., Holben, B. N., Tsay, S. C., Lin, N. H., Giles, D., Stewart, S. A., Janjai, S., Nguyen, X. A., Hsiao, T. C., Chen, W. N., Lin, T. H., Buntoung, S., Chantara, S., & Wiriya, W. (2015). Vertical distribution and columnar optical properties of springtime biomass- burning aerosols over Northern Indochina during 2014 7-SEAS Campaign. Aerosol and Air Quality Research, 15(5), 2037–2050. https://doi.org/10.4209/aaqr.2015.05.0310
Welton, E. J., & Campbell, J. R. (2002). Micropulse lidar signals: Uncertainty analysis. Journals.Ametsoc.Org, 19(12), 2089–2094. https://journals.ametsoc.org/view/journals/atot/19/12/1520-0426_2002_019_2089_mlsua_2_0_co_2.xml?tab_body=fulltext-display
Welton, E. J., Campbell, J. R., Spinhirne, J. D., & III, V. S. S. (2001). Global monitoring of clouds and aerosols using a network of micropulse lidar systems. Https://Doi.Org/10.1117/12.417040, 4153, 151–158. https://doi.org/10.1117/12.417040
Whiteman, C. (2000). Mountain meteorology: fundamentals and applications. https://books.google.com/books?hl=en&lr=&id=Mz_7qLK5hQcC&oi=fnd&pg=PA3&dq=C.+David+Whiteman,+C.D.,+Mountain+Meteorology:+Fundamentals+and+Applications.+Oxford+University+Press,+2000,+355+pp.&ots=6Y7jyzpQVi&sig=nnfQevAa9YwJ0016vQ0sym39428
World Health Organization. Regional Office for Europe. (2000). Air quality guidelines for Europe (2nd edition). World Health Organization. Regional Office for Europe. https://apps.who.int/iris/handle/10665/107335
Worldometers.info. (2023a, April 18). Population of South-Eastern Asia - Worldometer. https://www.worldometers.info/world-population/south-eastern-asia-population/
Worldometers.info. (2023b, April 18). Population of Southern Asia - Worldometer. https://www.worldometers.info/world-population/southern-asia-population/
Xiao, C. wei, Li, P., & Feng, Z. ming. (2018). Re-delineating mountainous areas with three topographic parameters in Mainland Southeast Asia using ASTER global digital elevation model data. Journal of Mountain Science, 15(8), 1728–1740. https://doi.org/10.1007/S11629-017-4746-8/METRICS
Xing, Y. F., Xu, Y. H., Shi, M. H., & Lian, Y. X. (2016). The impact of PM2.5 on the human respiratory system. Journal of Thoracic Disease, 8(1), E69–E74. https://doi.org/10.3978/J.ISSN.2072-1439.2016.01.19
Yin, S., Wang, X., Zhang, X., Guo, M., Miura, M., & Xiao, Y. (2019). Influence of biomass burning on local air pollution in mainland Southeast Asia from 2001 to 2016. Environmental Pollution, 254. https://doi.org/10.1016/j.envpol.2019.07.117
Zhou, Y., & Zheng, H. (2016). Digital universal particle concentration sensor PMS5003 series data manual. https://aqicn.org/air/sensor/spec/pms5003-english-v2.3.pdf

指導教授

王聖翔(Sheng-Hsiang Wang)

審核日期

2023-6-8

推文