河西走廊极端干旱区PM10质量浓度分布特征及其与气象要素关系研究

利用敦煌和酒泉2007—2011年的PM10质量浓度资料和风速、气温、相对湿度、气压、天气现象等相关气象要素资料，分析了河西走廊西部极端干旱区不同下垫面环境PM。0质量浓度的时空分布特征，结果表明，下垫面是沙地环境的敦煌PMl0质量浓度年平均值为128．9lμg·m-1，明显高于绿洲环境酒泉的76．1mg·m-1两站均是春季大于其他季节，尤以4月最为显著，敦煌和酒泉分别达到272．1lμg·m0和151lμg·m-2；PMl0质量浓度的不同分布特征与气象因素有密切的关系，尤其受沙尘天气的影响较大，其最大值可以反映沙尘天气的强度，非沙尘日PMl0质量浓度在不同下垫面条件下虽有一定相差，但空气质量状况均在“良”以上。两站PM10质量浓度日变化差异较大，敦煌四季的日变化特征均不特别显著，变化比较平稳，基本都呈单峰单谷型分布，最大值出现在17：00时左右，最小值出现在6：00左右；酒泉春、秋季日变化基本一致，呈单峰型，最大值出现在正午时段；夏季日变化规律性不明显，变化幅度比较平缓；冬季呈双峰双谷型，最大值和次大值分别出现在16：00和2：00左右，最小值和次小值分别出现在10：00和0：00左右。进一步分析发现，在沙尘日和非沙尘日PM10质量浓度明显不同，其对应的压、温、湿、风及能见度也有一定规律，沙尘日的日均风速和日最大风速大于非沙尘日，相对湿度、气压和能见度小于非沙尘日。两站的气温、气压、相对湿度、风速等气象要素与PM10质量浓度均有一定相关性，但PM10质量浓度的分布最终是受各要素综合影响的结果，敦煌和酒泉，PM值与PM10质量浓度日均值的相关性都很显著，相关系数分别为0．8961和0．9152，远高于其他各单气象要素与PM10质量浓度的相关性。两站沙尘日的昂M均值分别是非沙尘日2-3倍，因此气象影响指数能有效的区别沙尘日和非沙尘日。IPM的分布也能较好的反映PMl0质量浓度的分布，因此可用抽d来量化评价PM10质量浓度。

Concentration distribution characteristics of PM10 and the relation with meteorological element in extreme arid areas of the west part in Hexi Corridor

By making use of the PM10 mass concentration data as well as the related meteorological data such as wind speed, air temperature, relative humidity, barometric pressure and weather phenomena in Dunhuang and Jiuquan from 2007 to 2011, it is to analyze the spatial and temporal distribution characteristics of PM10 mass concentration in the extremely arid western region of Hexi Corridor different from the underlying surface environment. The results show that the annual average PM10 mass concentration value of Dunhuang whose underlying surface is desert is 128.9 ~tg＇m-3, which is significantly higher than that of Jiuquan with oasis environment whose value is 76.1 I.tg＇m3. The value of the two stations in spring are both greater than that in other seasons, especially in April when the values reach 272.1 ]xg＇m3 and 151 ixg＇m3 in Jiuquan and Dunhuang respectively. Different distribution characteristics of PM10 mass concentration is closely related with the meteorological elements, which can be influenced especially by the dust weather. The maximum value of it may reflect the intensity of dust. Although there are certain differences for PM10 mass concentration on non-dust days under different underlying surface conditions, the air mass conditions are always above ＂good＂. The diurnal variation difference of PM10 mass concentration in the two stations is huge. The diurnal variation of Dunhuang in the four seasons shows an indistinctive characteristic with stable variation basically distributed in single peak and single valley type, the maximum value of which appears in the afternoon at around 17：00 and the minimum value is in the early morning at around 6：00 o＇clock. The diurnal variation of Jiuquan in spring and autumn are basically consistent, showing the single peak type whose maximum value appears in the noon, while its diurnal variation in summer is almost irregular with rather stable amplitude of variation; In winter, it shows the double peak and double valley type with the maximum value and second maximum value appear at around 16：00 and 2：00 respectively and the minimum value and second minimum value appear at around 10：00 and 0：00 respectively. As can been seen by further analysis, the PM10 mass concentration on dust days and non-dust days is clearly different with its corresponding pressure, temperature, humidity, wind and visibility showing certain rules. The daily average wind speed and daily maximum wind speed on dust days are greater than that on non-dust days and are with smaller relative humidity, air pressure and visibility. The meteorological elements such as air temperature, barometric pressure, relative humidity and wind speed in the two stations are in certain correlation with PM10 mass concentration. However, the distribution of PM10 mass concentration is affected by comprehensive factors ultimately. The correlation of IVM value and daily average value of PM10 mass concentration both in Dunhuang and Jiuquan is significant with the relevant coefficients of 0.896 1 and 0.915 2, which are much higher than the correlation of other single meteorological elements and PMlo mass concentration. The average IpM value of the two stations on dust days are twice or three times the value on non-dust days. Therefore, the dust days and non-dust days can be distinguished effectively by the meteorological impact index. The distribution oflpM can reflect the distribution of PMlo mass concentration as well. Therefore, lVM Can be adopted to quantify and evaluate the PM10 mass concentration.