四川省不同类型森林区域大气颗粒物化学组成的研究

发布时间：2018-01-11 21:47

本文关键词：四川省不同类型森林区域大气颗粒物化学组成的研究　出处：《四川农业大学》2015年硕士论文　论文类型：学位论文

更多相关文章： PM_(2.5) 森林地区 OC EC酸度 AIM-Ⅳ

【摘要】：研究选择于2010～2012年夏季,在四川白马泉风景区(以下简称：白马泉)、攀枝花苏铁国家级自然保护区(以下简称：攀枝花)、贡嘎山国家级自然保护区(以下简称：贡嘎山)和卧龙国家级自然保护区(以下简称：卧龙)四个森林地区采集12小时(分为日间PM2.5和夜间PM2.5)和24小时PM2.5样本以及24小时TSP样本。本文重点探讨PM2.5质量浓度及其成分变化规律。研究结果显示,24小时PM2.5平均质量浓度在白马泉、攀枝花、贡嘎山和卧龙分别为72.42、104.9、20.55和29.19μg/m3。本研究运用离子色谱仪分析了PM2.5和TSP中12种水溶性离子,其中,以S042-和NH4+这两种水溶性离子浓度最高,并且这两种水溶性离子呈现出良好的线性关系。二次无机气溶胶以SO42-、NO3-和NH4+三种离子为主,同时也是水溶性离子最主要成分。24小时PM2.5中的SNA (SO42-、NO3-和NH4+)在白马泉、攀枝花、贡嘎山和卧龙平均浓度分别为16.34、18.22、4.43和8.89 μg/m3,与OC的浓度比较接近,而OC的浓度则分别为15.86、20.81、3.11和9.33μg/m3。OC和EC相关性显示,总体上攀枝花的相关性相对好一些,而其他地区的相关性均较差,即攀枝花地区OC和EC有一个较明显的共同污染源,而其他三个地区则没有。四个森林地区中PM2.5和TSP质量浓度总体上随着温度的升高而上升,但是随着相对湿度的提升而降低。OC、SO42-和NH4+作为PM2.5中含量最高、最主要的三种成分,其变化规律与PM2.5的变化规律基本一致。研究还参照美国EPA颗粒物中酸度测定方法对颗粒物中强酸性H+浓度进行测定,白马泉、攀枝花、贡嘎山和卧龙24小时PM2.5中强酸性H+浓度分别为6.26、2.9E-04、11.11和10.04 nmol/m3,明显高于由H+-NH4+-Na+-SO42--NO3--Cl--H2O-T-NH3-H2C2O4等参数组成的AIM-IV热力学模型计算出来的四个地区24小时PM2.5中原位酸氢离子浓度(白马泉、攀枝花、贡嘎山和卧龙原位酸氢离子浓度分别是0.028、1.4E-05、7.7E-04和0.0027 nmol/m3)。白马泉、攀枝花、贡嘎山和卧龙24小时PM2.5中原位酸pH(pHIS)分别是3.77、3.69、4.01和3.91,高于其他森林地区的有关报道,主要是由于大气中高浓度氨气的存在。此外,草酸还可以轻微增强原位酸度。通过IBM SPSS 21.0对PM25原位酸pH建立线性回归预测模型,得到24小时PM2.5原位酸pH预测模型表达式：pHIS=-0.038T+0.011RH+0.094NS+0.096RC/A+0.038NH3+0.051H2C2O4+13.715,R2= 0.775(n=42,p0.001)。四个森林地区中任意两个森林地区的发散系数均在0.3以上,表明任意两个森林地区不存在很明显的共同污染源。运用IBM SPSS 21.0对颗粒物进行主成分分析,结果表明白马泉污染物主要来源于地壳扬尘和生物质燃烧等一次排放和长距离传输过来的老化气溶胶。攀枝花的污染物来源则主要是本地贡献的,主要包括老化的气溶胶和生物质燃烧。贡嘎山的污染物来源主要有地壳扬尘与生物质燃烧等构成的一次排放物,以及当地生成的和长距离传输过来的老化气溶胶。卧龙的污染物更多的是一次排放的,包括地表扬尘和生物质燃烧等,由于卧龙较低的光合有效辐射而使得有机气溶胶老化程度较低。四个地区中NO3-/SO42-质量比均较小,远小于1,说明这四个森林地区中污染物以固定源排放为主。通过主成分分析得到白马泉、攀枝花、贡嘎山和卧龙四个森林地区PM2.5中有机物(OM)与OC比值分别是2.3、2.3、2.4和1.3,最后的质量闭合结果显示,OM和EC对颗粒物质量贡献率为38.0～49.3和2.0～5.7%,SNA (SO42-, NH4+和N03-)对白马泉、攀枝花、贡嘎山和卧龙PM的贡献率分别是23.0、17.4、22.1和30.5%,土壤扬尘也是重要的污染物来源之一,对白马泉、攀枝花、贡嘎山和卧龙的贡献率分别是6.3、17.0、10.4和19.1%。进行质量重建得到四个森林地区的颗粒物质量占实际称量得到的颗粒物质量的百分比为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%..

【学位授予单位】：四川农业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X513

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