【摘要】：隨著我國(guó)經(jīng)濟(jì)的高速發(fā)展,工業(yè)生產(chǎn)、汽車(chē)尾氣、化石燃料燃燒等帶來(lái)的大氣污染日益嚴(yán)重,極端霧霾、極寒、短時(shí)強(qiáng)降水、閃電等災(zāi)害天氣也頻頻發(fā)生,這些現(xiàn)象已嚴(yán)重影響到人們的正常工作與生活。氣溶膠是研究氣候變化與大氣污染的重要參數(shù),也是進(jìn)行定量遙感必需獲得的參數(shù),其參數(shù)反演精度、物化性質(zhì)以及空間分布一直是大氣污染和氣候變化研究中的熱點(diǎn),也是我們了解最薄弱的部分。因此,借助多源衛(wèi)星數(shù)據(jù),結(jié)合地基觀(guān)測(cè)數(shù)據(jù),進(jìn)行氣溶膠參數(shù)遙感定量反演、大氣氣溶膠特性及空間分布的精確探測(cè)具有重要科學(xué)價(jià)值。論文主要研究了如下內(nèi)容:首先,基于邊界層氣溶膠垂直廓線(xiàn)分布的訂正方案,提出了一種全新的基于CALIPSO衛(wèi)星數(shù)據(jù)的氣溶膠光學(xué)厚度(AOD)定量反演算法。利用地面資料對(duì)AOD反演結(jié)果進(jìn)行驗(yàn)證,并分析其可能的誤差源。結(jié)果表明:濾云處理后反演得到的CALIPSO AOD值普遍低于地基觀(guān)測(cè)站的AOD值,而訂正后的CALIPSO AOD值與地基觀(guān)測(cè)的AOD值相比,除個(gè)別站(龍鳳山)外,其他站的擬合斜率和相關(guān)系數(shù)都有提高,訂正效果較好;CALIPSO衛(wèi)星與地面站的相互位置對(duì)驗(yàn)證結(jié)果會(huì)有影響,其中類(lèi)型2的擬合結(jié)果好于其他類(lèi)型的擬合結(jié)果;不同相對(duì)濕度對(duì)地基、衛(wèi)星AOD有一定影響,總而言之,不管是CALIPSO AOD還是訂正后的CALIPSO AOD(corrected),擬合斜率和擬合系數(shù)都隨相對(duì)濕度的增加而減小。其次,利用長(zhǎng)時(shí)間序列的MODIS數(shù)據(jù)探討了江西地區(qū)AOD空間變化特征,同時(shí)利用CALIPSO/CALIOP VFM數(shù)據(jù),計(jì)算了氣溶膠、不同子類(lèi)型氣溶膠和云的垂直概率分布和MPH(最大似然高度)。發(fā)現(xiàn),江西地區(qū)AOD水平分布由南向北逐漸遞增。其中,九江、南昌地區(qū)達(dá)到最高。垂直方向上,氣溶膠主要累積在1~3.5km,云和氣溶膠的混合狀態(tài)出現(xiàn)概率大于分離狀態(tài)。在2~4km垂直高度上,春季污染沙塵出現(xiàn)的概率最高,冬季次之,夏季與秋季相當(dāng)。而煙塵氣溶膠夏季出現(xiàn)的概率最高,春、冬季相當(dāng),秋季次之。最后,針對(duì)北京地區(qū)一次極端霧霾事件,通過(guò)利用地面和衛(wèi)星觀(guān)測(cè)數(shù)據(jù),結(jié)合氣象條件,采用后向軌跡模式來(lái)分析霧霾形成過(guò)程和氣溶膠光學(xué)特性,并探討可能的污染來(lái)源。結(jié)果表明:高的相對(duì)濕度、差的擴(kuò)散條件(低風(fēng)速和穩(wěn)定的大氣層)和在高排放與氣溶膠吸濕增長(zhǎng)條件下氣溶膠二次轉(zhuǎn)化是這次重霾事件發(fā)生的主要原因。霧霾期間,AOD500nm日均值為1.15,水氣(CWV)的日均值為0.42cm。Angstrom指數(shù),細(xì)粒子模態(tài)的日均值分別為1.19和0.81,這表明細(xì)小的氣溶膠顆粒在大氣中含量較多,成為霾期間大氣消光的主要貢獻(xiàn)者。衛(wèi)星觀(guān)測(cè)顯示,霧霾期間北京地區(qū)有一層明顯的氣溶膠層集中在地面上層2km內(nèi),氣溶膠類(lèi)型主要由混合污染氣溶膠組成。
[Abstract]:With the rapid economic development of our country, the air pollution brought by industrial production, automobile exhaust gas and fossil fuel combustion is becoming increasingly serious. Extreme haze, extreme cold, short term heavy precipitation, lightning and other disaster weather also occur frequently. These phenomena have seriously affected people's normal work and life. Aerosol is not only an important parameter to study climate change and atmospheric pollution, but also a necessary parameter for quantitative remote sensing. The inversion accuracy, physicochemical properties and spatial distribution of aerosol are always hot spots in the research of atmospheric pollution and climate change. It is also the weakest part we know. Therefore, with the help of multi-source satellite data and ground-based observation data, the remote sensing quantitative inversion of aerosol parameters and the accurate detection of atmospheric aerosol characteristics and spatial distribution are of great scientific value. The main contents of this paper are as follows: firstly, a new (AOD) quantitative inversion algorithm of aerosol optical thickness based on CALIPSO satellite data is proposed based on the revised scheme of boundary layer aerosol vertical profile distribution. The AOD inversion results are verified by ground data, and the possible error sources are analyzed. The results show that the CALIPSO AOD obtained by cloud filtering inversion is generally lower than the AOD value of the ground-based observation station, and the revised CALIPSO AOD value is compared with the AOD value of the ground-based observation, except for the individual stations (Longfeng Mountain). The slope of fitting and correlation coefficient of other stations are improved, and the effect of correction is better. The mutual position of CALIPSO satellite and earth station will affect the verification results, and the fitting results of type 2 are better than those of other types. The satellite AOD is affected by different relative humidity. In a word, both the CALIPSO AOD and the revised CALIPSO AOD (corrected), fitting slope and fitting coefficient decrease with the increase of relative humidity. Secondly, using the MODIS data of long time series, the spatial variation characteristics of AOD in Jiangxi are discussed, and the vertical probability distribution and MPH (maximum likelihood height) of aerosols, different subtypes of aerosols and clouds are calculated by using CALIPSO/CALIOP VFM data. It is found that the horizontal distribution of AOD in Jiangxi is increasing gradually from south to north. Among them, Jiujiang, Nanchang area reached the highest. In the vertical direction, the aerosol mainly accumulates at 1 ~ 3.5km, and the probability of the mixed state of cloud and aerosol is greater than that of the separation state. In the vertical height of 2~4km, the probability of contaminated dust in spring is the highest, followed by winter, and the same in summer and autumn. The probability of soot aerosol appeared in summer was the highest, spring and winter were the same, and autumn was the second. Finally, in the light of an extreme haze event in Beijing, the formation process of haze and the optical properties of aerosol are analyzed by using ground and satellite observation data and meteorological conditions, and the possible sources of pollution are discussed. The results show that high relative humidity, poor diffusion conditions (low wind speed and stable atmosphere) and secondary aerosol conversion are the main causes of this heavy haze event. During haze, the daily average value of AOD500nm is 1.15, the daily average value of water (CWV) is 0.42cm.Angstrom exponent, the daily average value of fine particle mode is 1.19 and 0.81, respectively, which indicates that the fine aerosol particles are more in the atmosphere. To become a major contributor to atmospheric extinction during haze. Satellite observations show that there is an obvious aerosol layer in Beijing during haze, which is mainly composed of mixed polluted aerosols (2km).
【學(xué)位授予單位】：江西理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：X513;X87

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