Radiative Effects of Aerosols on the Environment in Taiwan

本研究著重在評估氣膠直接輻射效應對台灣大氣環境的影響。主要的研究方法包括：藉由氣膠物理、化學成份的實際觀測來瞭解氣膠的光學特性，同時估算其直接輻射效應；利用NCAR TUV輻射模式來評估氣膠對光化反應中光解係數的影響；利用一個一維模式，藉由預設氣膠光學特性與詳盡氣膠模式來估算氣膠的輻射效應及其對大氣邊界層參數的影響；以及針對長期氣象參數進行資料分析，尋找氣膠對台灣大氣環境的影響是否存在。料分析顯示夜間的顯著增溫導致夜間平均相對濕度大幅降低，遠較日間相對濕度之降低來的顯著，過去四十年夜間相對濕度的分佈明顯逐漸往較低濕度偏移，在都市區高於90%相對濕度發生時數的減少更是超過兩倍以上。除了三個離島與一高山測站（3.8 km），大部分的測站都可發現前述的變化趨勢，這樣的變化可能是導致台灣地區起霧頻率減少之主因。另外每日高低溫差的變化也主要發生在台灣陸地地區，顯示造成此溫度與濕度呈現日夜不對稱變化的原因主要是受局部地的效應或機制之影響，更精確的說，比濕的變化趨勢與局部地區之土地利用改變（如都市熱島效應）有關，而溫度變化趨勢除了受區域性乃至全球性效應的影響外，同時也受到局部地區土地利用改變的影響。由CIMEL 太陽輻射儀所觀測到的氣膠光學厚度（AOD）與光達（Lidar）在台北量測的消光係數剖面來估算氣膠的直接輻射效應，結果顯示其對地表、大氣層頂的輻射通量與大氣加熱率的影響不容忽視。台北地區的PM2.5與CIMEL AOD的關係遠較台南地區好，同時台北地區PM2.5與散光係數的關係性也不錯（R2 = 0.7）。氣膠含水量的估算對散光係數很重要。利用觀測成份與粒徑來估算氣膠混合狀態，結果顯示內混（internally mixed）與外混（externally mixed）兩種估算都與實際觀測的氣膠單次散射反照率（Single scattering albedo, SSA）有相當的差距。SSA的數值在台北於深夜達最高值約0.86至0.88，最低值同常在交通尖峰時段值約0.76至 0.79，SSA的大小主要受交通排放影響。粹散射氣膠於中午時段對光解係數影響較小（降低小於10%），但在早晨與傍晚則影響稍顯著（20%至50%與AOD大小有關），強輻射吸收的氣膠對光解係數的影響於整個白天都比散射性氣膠顯著，若AOD大於1.0，且SSA～0.8，則中午時段可減少50%以上，而早晨與傍晚則可達70%。此結果顯示在高AOD與低SSA時，氣膠對光解係數的削弱是很可觀的，未來大氣化學模式應該考慮此影響。用一維模式預設氣膠光學特性，結果顯示氣膠的SSA大小會影響地表、大氣層頂與大氣中輻射通量的收支情形，同時近地表的氣溫是升高或降低也與氣膠的光學特性有關。利用一維模式配合詳盡氣膠模式模擬顯示，不同大小的AOD與SSA會對大氣邊界層中的相關參數如溫度與邊界層高造成不同程度的影響，大量的強輻射吸收氣膠存在於大氣邊界層頂將使得大氣邊界層高度的發展明顯受限，大氣邊界層高度發展受限將可能使得大氣的垂直混合變差，容易導致空氣品質惡化。針對氣膠混合狀態的模擬顯示，內混假設對大氣的增溫最顯著，三種混合狀態的輻射效應估算在定性上與Jacobson (2000)的結果很類似。據本研究一維模式的模擬結果來看，氣膠的光學特性、垂直分佈與氣膠成份的混合狀態對氣膠直接輻射效應的估算很重要。同時目前詳盡氣膠模式只考慮少數成份如硫酸鹽、水及煤灰粒子，未來需包括更多氣膠化學成份進到一維模式，同時也需考慮氣膠與雲的交互作用機制與氣膠與光化學間的交互作用，如此才能更實際模擬氣膠的輻射效應及其對台灣大氣環境的影響。In this study we have made an evaluation of the direct radiative effects of aerosols on the environment of Taiwan by taking a multi-facet approach, including: investigating optical properties of aerosols in Taiwan, estimating their direct radiative forcing based on measurements of chemical and physical characteristics of aerosols, using NCAR TUV radiation model to evaluate the impact of aerosols on J-values associated with photochemistry, using a 1-D model with prescribed aerosol optical properties as well as detailed aerosol model to evaluate the radiative forcing of aerosols and their impacts on the atmospheric boundary layer, analyzing long-term changes of meteorological parameters and looking for possible impacts of aerosols.e find a long term trend of decreasing RH and that the trend is significantly larger in the nighttime than in daytime, apparently due to greater warming at night and in the early morning hours. Frequency distribution spectra of nighttime RH show a persistent shift toward lower values, whereas those of daytime exhibit little change over the last four decades. Such trends can be seen in most of the stations over Taiwan except for the three offshore island stations and one elevated station (3.8 km). The change in the frequency of occurrence is substantial for high RH values, reaching a factor of two reductions for RH greater than 90% in major urban centers. These changes are probably the main cause of a significant reduction of fog events over Taiwan. In addition, the change in the diurnal temperature range (DTR) is also primarily limited to Taiwan main island. Therefore, we believe that the “diurnally asymmetric” trends of humidity and temperature are mainly caused by factor(s) and/or process(es) within Taiwan, e.g., land use change or air pollutants emitted locally. More precisely, we concluded that the trend of relative humidity is mainly controlled by local effects associated with land-use change, whereas the trend of temperature is partly related to global/regional effects and partly due to local effects such as the urban heat island effect.ccording to the aerosol optical depth (AOD) measured by CIMEL sun-photometer and extinction coefficients retrieved by lidar in Taipei, the radiative impacts of aerosols on radiation fluxes at surface and the top of atmosphere (TOA) as well as atmospheric heating rates are significant. We found that coefficient of determination of PM2.5 vs. scattering coefficients in Taipei is quite high with R2 = 0.7. Good estimation of water content in aerosols is crucial to the scattering coefficients calculation. The absorption coefficient calculations based on either internally or externally mixed assumptions deviate significant from the direct measurements. Single scattering albedo (SSA) of aerosols in Taipei area usually peaks at midnight with values about 0.86 to 0.88 and lowest in traffic rush hours with values about 0.76 to 0.79. Value of SSA is a strong function of traffic emissions.ure scattering aerosols have less impact on J-values during the noon time period (less than 10% decrease) but have moderate impact in the early morning or late afternoon (20 to 50% decrease depending on AOD). For strong absorbing aerosols, the impact of aerosols on J-values is substantial both near noon time and at large solar zenith angles. The reduction in JNO2 can be more than 50% around noon time and 70% in the early morning or late afternoon for aerosol loading of AOD ~1.0 and SSA~0.8. These results revealed that the impact of aerosols on J values is significant especially for high AOD and low SSA conditions.adiative forcings at surface, atmosphere and TOA are strongly dependent on the value of SSA. Also, the perturbation to surface air temperature is critically dependent on optical properties of aerosols. Different values of SSA and AOD can result in different responses in parameters (e.g. temperature and PBL heights) of the atmospheric boundary layer. Light absorbing aerosols above the PBL height can strongly inhibit the growth of PBL height. Lowering the PBL height can inhibit the vertical mixing of pollutants and exacerbate air pollution in urban area. Internally mixed aerosols have the strongest warming effects on the atmosphere. Our estimate of radiative effects of the three types of mixing state of aerosols is qualitatively consistent with Jacobson (2000). ccording to our 1-D simulations, a detailed knowledge of optical properties, vertical distribution and mixing states of aerosols are critical to the correct evaluation of direct radiative forcing of aerosols. Moreover, current version of our aerosol composition model includes only sulfate, water and soot. More chemical species should be considered. In addition, more interaction processes of aerosols and clouds as well as aerosols and photochemistry should be incorporated into the 1-D model to obtain a more realistic evaluation of the radiative effects of aerosols on atmospheric environment.Approval IIedication IIIcknowledgments IVhinese Abstract Vnglish Abstract VIIontents Xist of Figures XIIIist of Tables XXIhapter 1. Introduction 1.1. Overview of aerosols 1.2. Direct and indirect effect of aerosols 3.3. Aerosol-cloud-climate interaction 7.4. Chemistry-climate interaction 9.5. Concluding remarks 11hapter 2. Data analysis 13.1. Changes in climate parameters observed in Taiwan 13.1.1. Introduction 14.1.2. Data 16.1.3. Result and discussion 18.1.4. Summary and implications 29hapter 3. Physical and chemical characteristics of aerosols in Taiwan 33.1. Changes in O3 and aerosols observed in Taiwan 33.2. Seasonality of MODIS AOD 39.3. Aerosol vertical profiles and their radiative forcing 40.3.1. AOD observed by CIMEL Sunphotometer 40.3.2. Aerosol extinction profiles from Lidar retrieval 41.4. Physical, chemical and optical characteristics of surface aerosols 42.4.1. Measurements and methodology 43.4.2. AOD vs. PM10 and PM2.5 concentrations 46.4.3. Surface optical properties vs. PM2.5 and CIMEL retrievals 47.4.4. Closure calculations based on averaged chemical compositions 50.4.5. Closure calculation based on in-situ chemical composition measurement 54.4.6. Diurnal variation of physical and chemical parameters of aerosols 56.5. Concluding remarks 57hapter 4. Aerosols impact on the photochemistry 59.1. Review 59.2. TUV radiation model 60.2.1. Introduction of TUV radiation model 60.2.2. Validation of TUV radiation model 60.3. Aerosols impact on J-values 61.4. Clouds and aerosols impact on J-values 63.5. Concluding remarks 64hapter 5. One dimensional photochemical aerosol model coupled with boundary layer processes 66.1. Introduction 66.2. Description of the 1-D composite model 67.2.1. 1-D atmospheric boundary layer model 68.2.2. 1-D photochemical model 69.2.3. Multi-bins and multi-components aerosol/cloud model 70.2.4. Optical modules 71.2.5. Setup of model simulation 73.3. Aerosol direct effect based on prescribed optical properties 73.3.1. Inclusions of aerosols and clouds 74.3.2. Aerosol impacts on radiation flux 74.3.3. Aerosol forcing impacts on surface air temperature 76.3.4. Cloud forcing impacts on surface air temperature 78.3.5. Aerosol and cloud forcing on surface temperature 78.3.6. Aerosol profiles on atmospheric heating rate 80.4. Aerosol radiative effect based on detailed aerosol model 81.4.1. Different initial size distribution 81.4.2. Different soot emission rates 83.4.3. Different vertical profiles of soot emission 86.4.4. Mixing states of aerosols 87.5. Concluding remarks 89hapter 6. Summary and conclusions 91.1. Research approaches 91.2. Major results 93.3. Future research topics 97eference 189ppendix A. List of acronym and symbols 203ppendix B. List of models 205ppendix C. List of refractive index 20