本文關(guān)鍵詞：四川省不同類型森林區(qū)域大氣顆粒物化學(xué)組成的研究　出處：《四川農(nóng)業(yè)大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： PM_(2.5) 森林地區(qū) OC EC酸度 AIM-Ⅳ

【摘要】：研究選擇于2010～2012年夏季,在四川白馬泉風(fēng)景區(qū)(以下簡稱：白馬泉)、攀枝花蘇鐵國家級自然保護區(qū)(以下簡稱：攀枝花)、貢嘎山國家級自然保護區(qū)(以下簡稱：貢嘎山)和臥龍國家級自然保護區(qū)(以下簡稱：臥龍)四個森林地區(qū)采集12小時(分為日間PM2.5和夜間PM2.5)和24小時PM2.5樣本以及24小時TSP樣本。本文重點探討PM2.5質(zhì)量濃度及其成分變化規(guī)律。研究結(jié)果顯示,24小時PM2.5平均質(zhì)量濃度在白馬泉、攀枝花、貢嘎山和臥龍分別為72.42、104.9、20.55和29.19μg/m3。本研究運用離子色譜儀分析了PM2.5和TSP中12種水溶性離子,其中,以S042-和NH4+這兩種水溶性離子濃度最高,并且這兩種水溶性離子呈現(xiàn)出良好的線性關(guān)系。二次無機氣溶膠以SO42-、NO3-和NH4+三種離子為主,同時也是水溶性離子最主要成分。24小時PM2.5中的SNA (SO42-、NO3-和NH4+)在白馬泉、攀枝花、貢嘎山和臥龍平均濃度分別為16.34、18.22、4.43和8.89 μg/m3,與OC的濃度比較接近,而OC的濃度則分別為15.86、20.81、3.11和9.33μg/m3。OC和EC相關(guān)性顯示,總體上攀枝花的相關(guān)性相對好一些,而其他地區(qū)的相關(guān)性均較差,即攀枝花地區(qū)OC和EC有一個較明顯的共同污染源,而其他三個地區(qū)則沒有。四個森林地區(qū)中PM2.5和TSP質(zhì)量濃度總體上隨著溫度的升高而上升,但是隨著相對濕度的提升而降低。OC、SO42-和NH4+作為PM2.5中含量最高、最主要的三種成分,其變化規(guī)律與PM2.5的變化規(guī)律基本一致。研究還參照美國EPA顆粒物中酸度測定方法對顆粒物中強酸性H+濃度進行測定,白馬泉、攀枝花、貢嘎山和臥龍24小時PM2.5中強酸性H+濃度分別為6.26、2.9E-04、11.11和10.04 nmol/m3,明顯高于由H+-NH4+-Na+-SO42--NO3--Cl--H2O-T-NH3-H2C2O4等參數(shù)組成的AIM-IV熱力學(xué)模型計算出來的四個地區(qū)24小時PM2.5中原位酸氫離子濃度(白馬泉、攀枝花、貢嘎山和臥龍原位酸氫離子濃度分別是0.028、1.4E-05、7.7E-04和0.0027 nmol/m3)。白馬泉、攀枝花、貢嘎山和臥龍24小時PM2.5中原位酸pH(pHIS)分別是3.77、3.69、4.01和3.91,高于其他森林地區(qū)的有關(guān)報道,主要是由于大氣中高濃度氨氣的存在。此外,草酸還可以輕微增強原位酸度。通過IBM SPSS 21.0對PM25原位酸pH建立線性回歸預(yù)測模型,得到24小時PM2.5原位酸pH預(yù)測模型表達式：pHIS=-0.038T+0.011RH+0.094NS+0.096RC/A+0.038NH3+0.051H2C2O4+13.715,R2= 0.775(n=42,p0.001)。四個森林地區(qū)中任意兩個森林地區(qū)的發(fā)散系數(shù)均在0.3以上,表明任意兩個森林地區(qū)不存在很明顯的共同污染源。運用IBM SPSS 21.0對顆粒物進行主成分分析,結(jié)果表明白馬泉污染物主要來源于地殼揚塵和生物質(zhì)燃燒等一次排放和長距離傳輸過來的老化氣溶膠。攀枝花的污染物來源則主要是本地貢獻的,主要包括老化的氣溶膠和生物質(zhì)燃燒。貢嘎山的污染物來源主要有地殼揚塵與生物質(zhì)燃燒等構(gòu)成的一次排放物,以及當(dāng)?shù)厣傻暮烷L距離傳輸過來的老化氣溶膠。臥龍的污染物更多的是一次排放的,包括地表揚塵和生物質(zhì)燃燒等,由于臥龍較低的光合有效輻射而使得有機氣溶膠老化程度較低。四個地區(qū)中NO3-/SO42-質(zhì)量比均較小,遠小于1,說明這四個森林地區(qū)中污染物以固定源排放為主。通過主成分分析得到白馬泉、攀枝花、貢嘎山和臥龍四個森林地區(qū)PM2.5中有機物(OM)與OC比值分別是2.3、2.3、2.4和1.3,最后的質(zhì)量閉合結(jié)果顯示,OM和EC對顆粒物質(zhì)量貢獻率為38.0～49.3和2.0～5.7%,SNA (SO42-, NH4+和N03-)對白馬泉、攀枝花、貢嘎山和臥龍PM的貢獻率分別是23.0、17.4、22.1和30.5%,土壤揚塵也是重要的污染物來源之一,對白馬泉、攀枝花、貢嘎山和臥龍的貢獻率分別是6.3、17.0、10.4和19.1%。進行質(zhì)量重建得到四個森林地區(qū)的顆粒物質(zhì)量占實際稱量得到的顆粒物質(zhì)量的百分比為75.9-102.0%。
[Abstract]:Study on the 2010 ~ 2012 Summer in Sichuan Baima spring scenic area (hereinafter referred to as: Bai Maquan), Panzhihua cycad National Nature Reserve (hereinafter referred to as Panzhihua), Gongga Mountain National Nature Reserve (hereinafter referred to as Gongga mountain) and the Wolong National Nature Reserve (hereinafter referred to as: Wolong four) a forest area collected 12 hours (divided into day and night PM2.5 PM2.5) and PM2.5 in 24 hours and 24 hours of sample TSP sample. This paper focuses on the variation of the concentration and composition of PM2.5. The results showed that the 24 hour average PM2.5 concentration in the white horse springs, Panzhihua, Gongga mountain and Wolong were 72.42104.9,20.55 and 29.19 g/m3. this research uses the ion chromatography analysis of 12 kinds of water-soluble ions, PM2.5 and TSP in the S042- and NH4+ of these two kinds of water soluble ion concentration was the highest, and the two kinds of water soluble ions showed good There is a good linear relationship. The two inorganic aerosol with SO42-, NO3- and NH4+ three kinds of ions, but also the main component of water soluble ions in PM2.5 SNA.24 hours (SO42-, NO3- and NH4+) in Panzhihua, Gongga mountain and Baima spring, Wolong average concentration were 16.34,18.22,4.43 and 8.89 g/m3, close to with the concentration of OC, whereas the concentration of OC were 15.86,20.81,3.11 and 9.33 g/m3.OC and EC correlation on the whole of Panzhihua is relatively good, and the correlation between other areas are poor, namely Panzhihua area OC and EC have an obvious common pollution source, while the other three areas are not four. A forest area in PM2.5 and TSP concentration generally increase with the temperature rising, but with the relative humidity enhance and reduce.OC, SO42- and NH4+ as PM2.5 was the highest, three major ingredients, its changes Consistent with the changing rules of PM2.5. The study also refer to particles of strong acidic H+ concentrations were measured, acidity determination method of American EPA particles in white springs, Panzhihua, Gongga mountain and Wolong 24 hours PM2.5 strong acidic H+ concentration were 6.26,2.9E-04,11.11 and 10.04 nmol/m3, significantly higher than that of AIM-IV thermodynamic model composed of H+-NH4+-Na+-SO42--NO3--Cl--H2O-T-NH3-H2C2O4 parameter calculation out of the four regions in 24 hours of PM2.5 acid in the concentration of hydrogen ions (white horse springs, Panzhihua, Gongga mountain and Wolong in situ acid hydrogen ion concentration were 0.028,1.4E-05,7.7E-04 and 0.0027 nmol/m3). The white horse springs, Panzhihua, Gongga mountain and Wolong 24 hours PM2.5 in situ acid pH (pHIS) is 3.77,3.69,4.01 and 3.91 respectively, higher than that of the reports of other forest regions, mainly due to the high concentration of ammonia in the atmosphere. In addition, oxalic acid can also increase slightly In situ strong acidity. By IBM SPSS 21 on PM25 in situ acid pH establish linear regression model, get 24 hours of in situ PM2.5 acid pH prediction model expressions: pHIS=-0.038T+0.011RH+0.094NS+0.096RC/A+0.038NH3+0.051H2C2O4+13.715, R2= 0.775 (n=42, p0.001). The coefficient of divergence of two forest area of any four forest area was more than 0.3, showed obvious common the pollution source does not exist two forest area. The use of IBM SPSS 21 on arbitrary particles for principal component analysis, the results showed that Ma Quan pollution mainly comes from the crustal dust and biomass burning emissions and a long distance transmission over aging aerosols. Panzhihua is the main source of pollutants is the local contribution, including aging aerosol and biomass burning in Gongga mountain. The main sources of the pollutant has a row of crust dust and biomass burning. The object, and the generation of local and long distance transmission over aging aerosols. Wolong is more of a pollutant emissions, including surface dust and biomass burning, because of Wolong's low photosynthetically active radiation and the organic aerosol aging degree is low. The four regions are smaller than the NO3-/SO42- quality. Far less than 1, indicating that four forest area pollutants in stationary source emissions. Through principal component analysis to get the white horse springs, Panzhihua, organic matter in Gongga mountain and Wolong four forest area in PM2.5 (OM) and the ratio of OC is 2.3,2.3,2.4 and 1.3 respectively, the quality of the final results of the closed display, OM and EC on particles mass contribution rate is 38 ~ 49.3 and 2 ~ 5.7%, SNA (SO42-, NH4+ and N03-) white horse springs, Panzhihua, Gongga mountain and Wolong PM contribution rate is 23.0,17.4,22.1 and 30.5% respectively, soil dust is an important pollutant source One of the contribution rates to the white horse spring, Panzhihua, Gongga mountain and Wolong were 6.3,17.0,10.4 and 19.1%. respectively, and the quality of particulate matter in four forest areas was accounted for 75.9-102.0%..

【學(xué)位授予單位】：四川農(nóng)業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：X513

【相似文獻】

相關(guān)期刊論文 前10條

1 江剛;新的研究報告確認(rèn)大氣顆粒物與健康的關(guān)系[J];中國環(huán)境科學(xué);2000年06期

2 江英;大氣顆粒物中的鉑族金屬[J];中國環(huán)境科學(xué);2002年01期

3 王婉,劉咸德,狄一安,趙立蔚,郭冬發(fā),魯毅強;天津市大氣顆粒物鉛的同位素豐度比測定[J];環(huán)境化學(xué);2002年06期

4 江剛;大氣顆粒物上的農(nóng)藥[J];中國環(huán)境科學(xué);2003年04期

5 ;大氣顆粒物源解析技術(shù)[J];中國環(huán)保產(chǎn)業(yè);2004年07期

6 賀斌;撫順市大氣顆粒物組成成分特征研究[J];黑龍江環(huán)境通報;2004年03期

7 王蔭淞,李愛國,魏侖,張元勛,李德義,裘惠源,李燕,張桂林,謝亞寧,張靜,張元茂,山祖慈;用X射線吸收近邊結(jié)構(gòu)譜研究大氣顆粒物中元素的種態(tài)[J];核技術(shù);2004年11期

8 謝云霞,羅文峰,李后強;大氣顆粒物的分形特征[J];世界科技研究與發(fā)展;2004年06期

9 賀斌,張志軍;大氣顆粒物組分解析[J];遼寧城鄉(xiāng)環(huán)境科技;2005年01期

10 朱光華;;大氣顆粒物采樣膜本底值的研究[J];過程工程學(xué)報;2006年S2期

相關(guān)會議論文 前10條

1 張普;周來東;王治淵;;成都市城區(qū)大氣顆粒物估計背景值研究[A];成都市科技年會分會場——世界現(xiàn)代田園城市空氣環(huán)境污染防治學(xué)術(shù)交流會論文集[C];2010年

2 白志鵬;;大氣顆粒物環(huán)境基準(zhǔn)研究歷程與展望[A];第十屆全國氣溶膠會議暨第六屆海峽兩岸氣溶膠技術(shù)研討會摘要集[C];2009年

3 何翔;錢楓;李\，

本文編號：1411372