【作者】 刘岩；

【导师】 张伟； 李莉；

【作者基本信息】 山东师范大学 ， 自然地理学， 2018， 硕士

【摘要】 VOCs是一系列碳氢化合物的总称,按来源不同,VOCs可分为人为源VOCs和植物源VOCs。从全球尺度来看,植物源VOCs排放量在整个VOCs排放占比达到90%以上,其排放量远超过人为源排放量。同时,在光化学反应过程中,植物源VOCs比人为源VOCs具有更强烈的化学反应活性,对臭氧生成的贡献不容忽视。植物源VOCs对对流层臭氧生成起着重要的角色,本文以遥感解译植被数据和MODIS数据为基础,利用Model of Emissions of Gases and Aerosols from Nature（MEGAN）模型对长三角地区2014年全年植物源VOCs的排放量、空间分布和时间变化进行了研究。在此基础上利用Weather Research and Forecasting（WRF）和Community Multi-scale Air Quality（CMAQ）模型模拟了长三角地区2014年7月植物源VOCs排放对该地区臭氧生成贡献的影响。长三角地区植物源VOCs排放对臭氧生成贡献影响方面,利用CMAQ模型,将臭氧模拟情景设为两种,情景一(S_a+b)即包括人为源又包括植物源,情景二（S_a）只有人为源排放。MEGAN模式输入数据主要包括叶面积指数（LAI:Leaf Area Index）、植被功能类型（PFT:Plant Function Type）、排放因子（EF:Emission Factor）和WRF模式所模拟的气象数据。研究结果表明,2014年长三角地区植物源VOCs排放量约为188.6万t,其中异戊二烯排放量约为70.4万t,占比约达37.33%;单萜烯排放量约为30.3万t,占比约达16.07%;其他VOCs排放量约为87.9万t,占比约达46.60%。相关研究表明,长三角地区2014年人为源VOCs排放量约为403万t,植物源VOCs排放约占到区域VOCs排放总量的32%。从时间变化上来看,在夏季（7、8、9月）长三角地区植物源VOCs排放达到最高值;最低值出现在冬季（1、2、12月）。从占比情况分析发现,夏季植物源VOCs排放约为60.9%,冬季植物源VOCs排放约为3.2%。植物源VOCs排放除了有明显的季节变化外,还有明显的昼夜排放日变化,由于中午高温和强烈的太阳辐射,植物源VOCs排放达到一天中最高值。异戊二烯夜间排放几乎为零,相反单萜烯和其他VOCs白天和夜晚都有排放,主要是因为光照对它们影响不大。从空间分布来看,长三角地区植物源VOCs排放总量南部高于北部。长三角地区各省份的年排放量统计结果显示,浙江省排放量约为84.2万t,占比约为44.6%;安徽省排放量约为76.0万t,占比约为40.3%;江苏省排放量约为27.2万t,占比约为14.4%;上海市排放量约为1.2万t,占比约为0.7%。长三角地区植物源VOCs排放空间分布与人为源VOCs排放空间分布相比,人为源VOCs主要集中分布在工业发展迅速和人类活动强烈的核心城市群地区。植物源VOCs排放主要集中分布在长三角南部地区,如浙江省及安徽省南部等植被覆盖较为密集地区。本文通过设置两种臭氧生成模拟情景,研究植物源VOCs排放对臭氧的生成贡献,该研究结果将对长三角地区臭氧污染问题具有重要意义。从植物源VOCs排放对不同城市站点臭氧生成贡献来看,对五个站点（上海普陀、南京草场门和山西路、杭州城厢镇及合肥明珠广场）的臭氧月均小时值、最大8h值和最大1h的生成贡献率分别为11±6.96%、12±7.76%和6.6±6.96%。长三角地区由植物源VOCs排放生成的臭氧月均小时浓度、最大8h浓度、最大1h浓度值最高约为15.12μg/m³、33.56μg/m³、55.35μg/m³,对臭氧的生成具有重要影响。就整个长三角地区来看,2014年7月由植物源VOCs排放生成的臭氧最高值区,主要出现在蚌埠市、铜陵市、合肥市、湖州市、南京市和浙江市,在模拟时间段内由植物源VOCs排放生成的臭氧最大1h浓度范围为23.22⁴3.04μg/m³。植物源VOCs排放对郊区和城区臭氧的生成贡献影响不同,郊区臭氧生成更容易受植物源VOCs排放的影响。研究结果将为长三角地区有关空气污染和臭氧污染问题治理提供科学依据。同时数据获取方面的不确定性及模式本身的不确定性问题,将是今后工作的研究方向。更多还原

【Abstract】 VOCs are the general name for a series of hydrocarbons.VOCs could be emitted from anthropogenic VOCs and biogenic VOCs.Biogenic VOCs emissions from vegetation were estimated to account for more than 90%of total VOCs emissions globally.Researches have shown that biogenic VOCs could lead to significant photochemical ozone formation,with its abundances and high chemical reactivity.Biogenic VOCs play an important role in the formation of tropospheric ozone.In the present work,biogenic emissions over the Yangtze River Delta（YRD）region for year 2014 were developed based on the interpretation of remote sensing image and MODIS data using the Model of MEGAN.Impact of biogenic VOCs emissions over the YRD region on ozone formation was investigated based on WRF–CMAQ modeling system for July 2014.To investigate the impact of biogenic emissions on ozone formation in the YRD region,two parallel CMAQ simulations were conducted with identical model configurations except the emissions:Scenario 1(S_a+b)included both anthropogenic and biogenic VOCs emissions while Scenario 2（S_a）only included anthropogenic emissions for the YRD region.Driving inputs for MEGAN include the leaf area index（LAI）,plant functional types（PFT）,emission factor,meteorology.The results show that annual biogenic VOCs emissions in the YRD estimated by MEGAN were 18.86×10⁵ton yr^-1 for year2014,of which isoprene（ISOP）,monoterpenes（MON）,and other VOCs account for7.04×10⁵（37.33%）,3.03×10⁵（16.07%）,and 8.79×10⁵ton yr^-1（46.60%）,respectively.Anthropogenic VOCs emissions in the YRD region were estimated to be40.3×10⁵ ton yr^-1.BVOCs emissions showed significant seasonal variations with highest emissions in summer（July,August,September）（60.9%）and lowest in winter（January,February,December）（3.2%）.In addition to the seasonal changes,biogenic VOCs emissions also exhibited diurnal variations.Biogenic VOCs emissions reach its peak value near local noon time due to high temperature and strong solar radiation.For isoprene,there are zero emissions during night time because isoprene emissions are light-dependent.In contrast,monoterpenes and other VOCs are being consistently emitted because they are not light-dependent.The southern of YRD emits more biogenic VOCs than the northern part.Annual emissions from Zhejiang（ZJ）,Anhui（AH）,Jiangsu（JS）provinces,and Shanghai（SH）were estimated to be 8.42×10⁵（44.6%）,7.60×10⁵（40.3%）,2.72×10⁵（14.4%）,and0.12×10⁵ton yr^-1（0.7%）,respectively.The results show that the spatial distribution of biogenic and anthropogenic VOCs emissions over the YRD region.Anthropogenic VOCs emissions were higher in Shanghai,Jiangsu and the eastern coastal areas of China,where there are more developed districts with high industrial activities and population.Biogenic VOCs emissions were higher in the southern YRD part（such as Zhejiang and the southern Anhui）than the northern part.The effects of biogenic VOCs on ozone concentrations were examined by comparing the results from the two scenarios.Findings from this work will provide important scientific support for the mitigation of ozone pollution in the YRD region.The impact of biogenic VOCs on ozone is mainly concentrated in the middle part of the YRD region,which is the downwind of the region in summer period.The daily average ozone values was calculated at national control points of Putuo,Caochangmen,Shanxi Road,Chengxiang town and Mingzhu square in YRD.The monthly average,maximum 8-h average and maximum 1-h ozone concentrations at 5urban sites contributed by biogenic VOCs emissions are 11±6.96%,12±7.76%,and6.6±6.96%,respectively in July 2014.The monthly average,maximum 8-h average and maximum 1-h ozone concentrations are over 15.12,33.56 and 55.35μg/m³ in YRD region,suggesting significant impact of biogenic VOCs emissions on ozone formation in the YRD region.Impact of biogenic emissions on ozone formation exhibited a strong spatial pattern:high contributions were observed in the middle YRD region,including Bengbu,Tongling,Hefei,Huzhou,Nanjing and Zhenjiang,with the maximum hourly ozone contribution of 23.22⁴3.04μg/m³ for July.The influence of biogenic VOCs on ozone formation in rural area is higher than urban area.The research is more reliability than traditional methods.The results can provide some scientific basis for some problems about air pollution and ozone pollution.The uncertainty of data acquisition and the uncertainty of the model itself will be the research direction of future work.更多还原