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1.
应用AERMOD模型,基于葫芦岛市2016年污染源排放清单和相关参数,模拟了葫芦岛市SO_2和NO_2的地面浓度,并与葫芦岛市4个大气环境监测站的对应资料进行对比验证。结果表明:SO_2和NO_2模拟的平均值均略小于监测值,造成这种差异的原因较多,但主要原因是模拟中所用的污染源排放清单还不够完善。而SO_2的监测和模拟结果的相关性比NO_2略好,其中SO_2总的相关系数的平均值为0.71,而NO_2为0.64;4个监测点位SO_2总的平均值的相对误差为-19.4%,4个监测点位NO_2总的平均值的相对误差为-25.6%。在SO_2的模拟结果中,冬季和春季监测和模拟结果的相关性相对较好,其中冬季监测和模拟结果的相关系数平均值为0.79;而NO_2的模拟结果中,冬季和秋季监测和模拟结果的相关性相对较好,其中冬季监测和模拟结果的相关系数平均值为0.69。  相似文献   

2.
为更好地表征当前广州城区和城郊大气颗粒物污染现状与差异及其与气象要素的关系,对2017年城郊站黄埔和城区站番禺的大气颗粒物(PM2.5和PM10)和气象观测数据进行了分析。结果表明:全年来看,城区和城郊PM2.5和PM10具有相似的质量浓度频率、月际变化和日变化;城区站的平均PM2.5质量浓度为39.3μg/m3,高于城郊站(35.3μg/m3);城区站PM10质量浓度为58.5μg/m3,低于城郊站(62.9μg/m3);ρ(PM2.5)/ρ(PM10)显示,相比城郊,城区的2次污染更严重,细粒子占比更高。风玫瑰图分析发现,静风或小风状态下,城区番禺的颗粒物污染程度要高于城区黄埔,本地排放对城区站的颗粒物污染,特别是细颗粒物污染的影响更为显著;城郊站颗粒物污染的形成也同时受本地排放和外源输送影响,主要的输送来源于西北上风向肇庆、佛山一带的污染排放,其对PM2.5的影响更为显著。  相似文献   

3.
秸秆焚烧对区域城市空气质量影响的模拟分析   总被引:2,自引:0,他引:2  
利用融合火点排放源、人为源和生物源的WRF-Chem(Weather Research and Forecasting Model coupled with Chemistry)模式,模拟2015年9月30日08:00(北京时间)起的72 h发生在淮河流域的一次农作物秸秆大面积露天焚烧过程,研究了农作物秸秆焚烧释放的气态污染物和颗粒物对区域城市空气质量的影响。通过有无火点两组试验分析了此次秸秆焚烧对流域内河南、山东、江苏和安徽四省83座城市CO、PM10(空气动力学当量直径小于等于10μm的颗粒物,即可吸入颗粒物)、PM2.5(空气动力学当量直径小于等于2.5μm的颗粒物,即细颗粒物)和O3浓度的定量影响,结果表明:(1)融合NCAR-FINN(Fire Inventory from NCAR)火点排放资料的WRF-Chem模式较好地再现了此次秸秆焚烧及火点烟羽扩散过程。同时结合EDGAR-HTAP(Emission Database for Global Atmospheric Research on Hemispheric Transport of Air Pollution)人为源和MEGAN(Model of Emission of Gases and Aerosols from Nature)生物源的WRF-FIRE(考虑火点排放试验)对流域内城市大气污染物的模拟效果较为理想,尤其对秸秆焚烧释放的污染物CO、PM10和PM2.5和产生的二次污染物O3浓度的模拟。(2)秸秆焚烧所释放的污染物造成流域内城市一次污染物CO、PM10和PM2.5浓度的增加,火点中心和下风向城市增幅最为明显,最大小时浓度增幅达到3倍标准差。气态污染物CO和相比PM10粒径更小的PM2.5可随风扩散至更远的地区,对城市浓度影响更大。(3)此外,秸秆焚烧也使得火点中心城市和下风向城市二次污染物O3浓度增加,但小时浓度增幅极值区分布在火点下风向烟羽末端太阳光照充足的地区,最大小时浓度增幅接近3倍标准差。秸秆焚烧对区域城市空气质量的影响存在明显的空间分布差异且对城市各大气污染成分的影响也不相同。  相似文献   

4.
利用地面细颗粒物(PM2.5)浓度和气象常规观测资料、地基 AERONET观测资料、GFED生物质燃烧排放清单和大气化学—天气耦合模式WRF-Chem,模拟研究了华北地区2014年10月气象要素和大气污染物的时空演变,重点关注北京10月7~11日的一次重霾事件及其天气形势、边界层气象特征、输送路径、PM2.5及其化学成分浓度变化等特征,以及秸秆燃烧对华北和北京地区细颗粒物浓度和地面短波辐射的影响。与观测资料的对比结果显示,模式可以很好地模拟北京地区地面气象要素和PM2.5质量浓度,考虑秸秆燃烧排放源可以明显改进北京PM2.5浓度模拟的准确性,但在重度污染情况下,模式总体上低估气溶胶光学厚度和高估地面短波辐射。10月7~11日北京地区重霾事件主要是不利气象条件下人为污染物累积和区域输送造成,也受到华北地区南部秸秆燃烧的影响。河南北部、河北南部和山东西部大面积秸秆燃烧释放的气态污染物和颗粒物在南风的作用下输送至北京,秸秆燃烧对北京地区地面PM2.5、有机碳(OC)、硝酸盐、铵盐、硫酸盐和黑碳(BC)的平均贡献率分别为24.6%、36.8%、23.2%、22.6%、7.1%和19.8%,秸秆燃烧产生的气溶胶可以导致北京地面平均短波辐射最大减小超过20 W m-2,约占总气溶胶导致地表短波辐射变化的24%。  相似文献   

5.
将INTEX-B排放源应用到空气质量模型Model3-CMAQ中,对中国地区对流层NO2的浓度分布进行了数值模拟,并与OMI卫星对流层NO2资料进行了对比和验证。结果表明:将INTEX-B排放源应用到Model3-CMAQ模式,模拟的NO2浓度在中国地区的分布、季节变化规律与卫星资料所得结果一致。敏感性试验表明,工业及电厂排放对NO2的浓度贡献最大,而交通排放的贡献相对较小,两种排放均主要集中在京津、长江三角洲等经济发达地区。  相似文献   

6.
通过对2015年1—12月上海崇明岛崇南地区颗粒物(PM_(2.5)、PM_(10))浓度的连续监测,研究了PM_(2.5)、PM_(10)在不同季节的动态变化特征及与其他因子(SO_2、NO_2、O_3)的相关性,分析了风向风速和降雨对颗粒物浓度的影响。结果表明:崇明岛PM_(2.5)和PM_(10)浓度的季节变化明显,呈现冬季的春季的秋季的夏季的的特征,冬季PM_(2.5)和PM_(10)小时浓度均值分别为0.058 mg/m~3和0.085 mg/m~3,夏季PM_(2.5)和PM_(10)均值分别为0.034 mg/m~3和0.054 mg/m~3。PM_(2.5)和PM_(10)浓度分别与SO_2浓度和NO_2浓度显著正相关,与O_3显著负相关。全年来看,在西南风向时PM_(2.5)和PM_(10)浓度较高,这主要受该方向上游吴淞工业区、宝钢、石洞口电厂、罗店工业区等工业排放影响;从高浓度颗粒物(PM_(2.5)质量浓度≥0.115 mg/m~3)来向看,北和西北风向时出现高浓度颗粒物的频率最高,这主要是受到我国北方采暖季大气颗粒物输送过程对崇明岛区域的脉冲式污染影响所致;PM_(2.5)、PM_(10)实时浓度与相应的风速呈显著负相关。降雨量大于5 mm或持续3 h及以上的连续降雨对大气颗粒物起到显著的湿清除作用,降雨后PM_(2.5)和PM_(10)质量浓度分别降低了68.0%和66.9%,降雨时和雨后PM_(2.5)浓度为0.025~0.033 mg/m~3,均低于我国环境空气PM_(2.5)的一级浓度限值。  相似文献   

7.
采用卫星监测的火点燃烧排放数据,利用区域化学传输模式WRF-Chem模拟分析了2017年5月华北地区细颗粒物(PM2.5)质量浓度分布,通过生物质燃烧排放源(华北区域以秸秆燃烧为主)开关的敏感性试验定量计算了燃烧排放对北京及其周边地区PM2.5质量浓度的影响。卫星监测结果显示,2017年5月华北地区有大量的秸秆焚烧现象,对该地区空气质量造成一定影响的燃烧天数为20 d,占全月总日数的65%左右。数值模拟结果表明:该地区秸秆燃烧排放导致PM2.5浓度升高的区域集中在华北平原农作物产区,其分布位置与卫星监测的火点分布吻合。秸秆燃烧导致这些地区PM2.5浓度月平均值上升幅度普遍超过3 μg/m~3,高值区超过了11 μg/m~3,上升比例可达10%以上;此外,来自华北平原及长三角地区的燃烧排放对北京(特别是东南部地区)污染物浓度的影响是不容忽视的,其中河南、山东、天津等地的秸秆燃烧在合适风场的作用下会严重影响北京,可导致丰台及通州等地PM2.5小时浓度上升超过17 μg/m~3,上升幅度超过40%。  相似文献   

8.
为深入了解晋城市颗粒物浓度时空分布特征,对晋城市2017年12月至2018年5月国控点、小型站和微型站PM2.5及PM10小时浓度数据进行收集整理,并进行空间插值分析和时间变化趋势分析及与气象监测数据的相关分析。结果表明:颗粒物浓度在冬、春季节具有明显差异,冬季PM10与PM2.5高值区主要位于东北部及东南小部分区域,春季PM10高值区位于城区南部区域,PM2.5高值区主要集中于城区。晋城市城区和郊区PM10与PM2.5月均浓度整体呈单峰型变化,PM10在4月份最高(157.54±5.67μg·m^-3),PM2.5在1月份最高(94.08±2.25μg·m^-3)。冬季PM2.5/PM10平均为0.57,春季平均为0.45。颗粒物小时浓度的变化呈现单峰单谷的型式,冬季PM10与PM2.5小时平均浓度最高值均出现在10时,春季均出现在09时。监测期间晋城市PM10与PM2.5的小时浓度值与相对湿度有较高的正相关性(p<0.01),与风速、风向有较高的负相关性(p<0.01),与温度和气压的相关性较低。冬季,东北至正南风向时,PM10与PM2.5的浓度普遍高于西北风向时的浓度,对晋城冬、春季国控点颗粒物浓度贡献率最高的风向风速为东南偏南风向,风速在1 m/s以内。  相似文献   

9.
利用人工神经网络(ANN)技术,基于气象条件、污染物排放变化和污染物浓度资料构建污染物浓度统计模型,在此基础上分析气象条件和污染物排放源排放变化对污染物浓度逐日变化和年际变化的影响。研究结果发现基于ANN建立的大气污染统计预报模型模拟NO_2浓度准确性较高,其次为SO2,PM10浓度准确性较低。ANN的输入参数更适合NO_2的模拟,SO2和PM10浓度的影响因子较为复杂。气象条件变化是NO_2浓度逐日变化的主要影响因子,污染物排放量变化是NO_2浓度年际变化的主要影响因子。因子分离法计算得到的气象条件、污染物排放及两者相互作用对NO_2浓度逐日变化的贡献率分别是57.9%、24.5%和17.6%,对NO_2浓度年际变化的贡献率分别是13.7%、73.3%和13%。  相似文献   

10.
邢军  孙颖  李德恒 《吉林气象》2012,(1):8-11,26
利用四平中韩沙尘暴监测站颗粒物监测仪器GRIMM180观测的2011年数浓度及ρ(PM10)、ρ(PM2.5)和ρ(PM1.0)数据及台站的常规气象观测资料,分析了该地区数浓度、质量浓度的变化特征及与气象条件的相关性。结果表明,PM2.5和PM10污染存在着明显的季节性变化,季节变化特征基本一致,表现为冬季>春季>秋季>夏季,冬季最重,夏季最轻;颗粒物质量浓度日变化呈现两峰特征,ρ(PM10)、ρ(PM2.5)和ρ(PM1.0)之间有很好的相关性,ρ(PM2.5)/ρ(PM10)的平均值为65.7%,ρ(PM1.0)/ρ(PM2.5)的平均值83.9%,ρ(PM1.0)/ρ(PM10)的平均值55.2%;四平地区年主导风向为SSW,颗粒物质量浓度变化受沙尘移动路径影响较大,采暖期间供热燃煤排放对空气质量有较大程度的影响,其中大风、浮尘等天气条件下颗粒物质量浓度值呈较大突变特性。  相似文献   

11.
In recent years, China has implemented several measures to improve air quality. The Beijing-Tianjin-Hebei(BTH)region is one area that has suffered from the most serious air pollution in China and has undergone huge changes in air quality in the past few years. How to scientifically assess these change processes remain the key issue in further improving the air quality over this region in the future. To evaluate the changes in major air pollutant emissions over this region, this paper employs ens...  相似文献   

12.
大气污染物排放清单是空气质量模拟和空气污染治理的重要依据.本研究比较分析了两套覆盖江苏省的2017年大气污染物排放清单,即分别由上海市环境科学研究院、江苏省环境科学研究院编制的"长三角清单"和"江苏省清单",并结合区域空气质量模型CMAQ评估不同清单对长三角地区2017年1、4、7、10月的空气质量模拟的影响.清单比较结果表明,除二氧化硫(SO2)以外,江苏省清单估算的各污染物排放量较长三角清单低.通过与观测数据比较,发现两套清单对SO2、氮氧化物(NOx)、臭氧(O3)和细颗粒物(PM2.5)的模型模拟性能均较好.江苏省清单与长三角清单两者的模拟结果空间分布接近,其中江苏省清单模拟的PM2.5和O3在长三角多数地区略低于长三角清单的模拟结果(1月O3除外).江苏省清单与长三角清单均能够用于空气质量模式模拟,可为江苏地区的细颗粒物和光化学烟雾污染的控制策略制定提供参考.  相似文献   

13.
In this paper, we evaluate the performance of several air quality models using the Pearl River Delta (PRD) region, including the Nested Air Quality Prediction Modeling System (NAQPMS), the Community Multiscale Air Quality (CMAQ) model, and the Comprehensive Air Quality Model with extensions (CAMx). All three model runs are based on the same meteorological fields generated by the Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5) and the same emission inventories. The emission data are processed by the Sparse Matrix Operator Kernel Emissions (SMOKE) model, with the inventories generated from the Transport and Chemical Evolution over the Pacific/Intercontinental Chemical Transport Experiment Phase B (TRACE-P/INTEX-B) and local emission inventory data. The results show that: (1) the meteorological simulation of the MM5 model is reasonable compared with the observations at the regional background and urban stations. (2) The models have different advantages at different stations. The CAMx model has the best performance for SO2 simulation, with the lowest mean normalized bias (MNB) and mean normalized error (MNE) at most of the Guangzhou stations, while the CMAQ model has the lowest normalized mean square error (NMSE) value for SO2 simulation at most of the other PRD urban stations. The NAQPMS model has the best performance in the NO2 simulation at most of the Guangzhou stations. (3) The model performance at the Guangzhou stations is better than that at the other stations, and the emissions may be underestimated in the other PRD cities. (4) The PM10 simulation has the best model measures of FAC2 (fraction of predictions within a factor of two of the observations) (average 53–56%) and NMSE (0.904–1.015), while the SO2 simulation has the best concentration distribution compared with the observations, according to the quantile–quantile (Q–Q) plots.  相似文献   

14.
以武汉市为研究区域,基于实地调查获得典型行业污染源活动水平,以大气污染物排放清单编制技术指南为参考,利用排放因子法建立2014年武汉市大气污染源排放清单,并结合经纬度、人口密度分布、土地利用类型、道路长度等数据将排放清单进行了3 km×3 km网格化处理.结果表明,2014年武汉市SO2、NOx、PM10、PM2.5、CO、BC、OC、VOCs和NH3排放量分别为10.3、17.0、16.3、7.1、63.1、0.6、0.4、19.8和1.6万t.固定燃烧源为SO2排放的主要来源,其贡献率约64%;移动源为NOx的主要来源,其贡献率约51%;颗粒物排放主要来源于扬尘源和工艺过程源;CO和VOCs主要来源于工艺过程源,BC和OC排放均以移动源和生物质燃烧源为主,NH3排放主要来自农业源.污染物排放主要集中在青山区至新洲区一带.  相似文献   

15.
The Scoping Plan for compliance with California Assembly Bill 32 (Global Warming Solutions Act of 2006; AB 32) proposes a substantial reduction in 2020 greenhouse gas (GHG) emissions from all economic sectors through energy efficiency, renewable energy, and other technological measures. Most of the AB 32 Scoping Plan measures will simultaneously reduce emissions of traditional criteria pollutants along with GHGs leading to a co-benefit of improved air quality in California. The present study quantifies the airborne particulate matter (PM2.5) co-benefits of AB 32 by comparing future air quality under a Business as Usual (BAU) scenario (without AB 32) to AB 32 implementation by sector. AB 32 measures were divided into five levels defined by sector as follows: 1) industrial sources, 2) electric utility and natural gas sources, 3) agricultural sources, 4) on-road mobile sources and 5) other mobile sources. Air quality throughout California was simulated using the UCD source-oriented air quality model during 12 days of severe air pollution and over 108 days of typical meteorology representing an annual average period in the year 2030 (10 years after the AB 32 adoption deadline). The net effect of all AB 32 measures reduced statewide primary PM and NOx emissions by ~1 % and ~15 %, respectively. Air quality simulations predict that these emissions reductions lower population-weighted PM2.5 concentrations by ~6 % for California. The South Coast Air Basin (SoCAB) experienced the greatest reductions in PM2.5 concentrations due to the AB 32 transportation measures while the San Joaquin Valley (SJV) experiences the smallest reductions or even slight increases in PM2.5 concentrations due to the AB 32 measures that called for increased use of dairy biogas for electricity generation. The ~6 % reduction in PM2.5 exposure associated with AB 32 predicted in the current study reduced air pollution mortality in California by 6.2 %, avoiding 880 (560–1100) premature deaths per year for the conditions in 2030. The monetary benefit from this avoided mortality was estimated at $5.4B/yr with a weighted average benefit per tonne of $35 k/tonne ($23 k/tonne–$45 k/tonne) of PM, NOx, SOx, and NH3 emissions reduction.  相似文献   

16.
This paper presents the application of a Monte-Carlo simulation for assessing the uncertainties of German 2005 emissions of particulate matter (PM10 & PM2.5) and aerosol precursors (SO2, NOx, NH3 and NMVOC) carried out in the PAREST (PArticle REduction STrategies) research project. For the uncertainty analysis the German Federal Environment Agency’s emission inventory was amended and integrated with a model on the disaggregation of energy balance data. A series of algorithms was developed in order to make efficient and pragmatic use of available literature and expert judgement data for uncertainties of emission model input data. The inventories for PM10 (95 %-confidence interval: ?16 %/+23 %), PM2.5 (?15 %/+19 %) and NOx (?10 %/+23 %) appear most uncertain, while the inventories for SO2 (?9 %/+9 %), NMVOC (?10 %/+12 %) and NH3 (?13 %/+13 %) show a higher accuracy. The source categories adding the most relevant contributions to overall uncertainty vary across the pollutants and comprise agriculture, mobile machinery in agriculture and forestry, construction sites, small businesses/carpentries, cigarette smoke and fireworks, road traffic, solvent use and stationary combustion. The PAREST results on relative uncertainties have been quoted in the German Informative Inventory Reports since 2012. A comparison shows that the PAREST results for Germany are within the range of (for NH3: close below) other European countries’ results on air pollutant inventory uncertainties as reported in the 2013 Informative Inventory Reports.  相似文献   

17.
北京秋季一次典型大气污染过程多站点分析   总被引:3,自引:1,他引:2  
多站点多种大气污染物的同步在线观测对深入剖析大气污染的成因和演变机制有重要意义。以龙潭湖、北京325 m塔、双清路和阳坊4监测站点实时NOx、SO2、O3、PM2.5和PM10浓度观测数据为基础,介绍了北京地区2010年10月3~11日发生的一次典型污染过程。不同污染物在污染过程中变化特征不一致,表现为NOx、SO2、O3浓度有明显日变化,而PM浓度升高后一直维持在高值,日变化幅度很小。通过分析不同站点、相同污染物之间的相关性和变异系数发现,4站点间一次污染物NO和SO2空间浓度差别大,变异系数分别为77%和70%,相关系数低于0.44;而二次污染物NO2、PM2.5、O3空间浓度差别较小,变异系数分别为34%、36%和29%,相关系数均超过0.54。结合中尺度气象模式研究发现,该污染过程中,850 hPa高空持续的西南暖平流造成华北地区显著平流逆温,与近地层辐射逆温共同作用,使北京地区混合层高度维持在1200 m以下。低混合层高度和低风速限制了大气垂直和水平扩散,造成北京地区近地层污染物累积,形成重度污染。  相似文献   

18.
Aerosols consist of organic and inorganic species, and the composition and concentration of these species depends on their sources, chemical transformation and sinks. In this study an assessment of major inorganic ions determined in three aerosol particle size ranges collected for 1 year at Welgegund in South Africa was conducted. SO42? and ammonium (NH4+) dominated the PM1 size fraction, while SO42? and nitrate (NO3) dominated the PM1–2.5 and PM2.5–10 size fractions. SO42? had the highest contribution in the two smaller size fractions, while NO3? had the highest contribution in the PM2.5–10 size fraction. SO42? and NO3? levels were attributed to the impacts of aged air masses passing over major anthropogenic source regions. Comparison of inorganic ion concentrations to levels thereof within a source region influencing Welgegund, indicated higher levels of most species within the source region. However, the comparative ratio of SO42? was significantly lower due to SO42? being formed distant from SO2 emissions and submicron SO42? having longer atmospheric residencies. The PM at Welgegund was determined to be acidic, mainly due to high concentrations of SO42?. PM1 and PM1–2.5 fractions revealed a seasonal pattern, with higher inorganic ion concentrations measured from May to September. Higher concentrations were attributed to decreased wet removal, more pronounced inversion layers trapping pollutants, and increases in household combustion and wild fires during winter. Back trajectory analysis also revealed higher concentrations of inorganic ionic species corresponding to air mass movements over anthropogenic source regions.  相似文献   

19.
RMAPS_Chem V1.0系统是基于WRF_Chem模式建立的服务于华北区域雾霾等污染预报业务的模式系统,该研究着重针对系统中污染排放清单不确定性带来的SO2浓度预报偏差较大问题,采用EnKF源反演和误差统计订正相结合的方法对排放清单进行了改进,形成了一套优化后的华北区域SO2排放清单。通过输入初始清单和优化清单对2017年10月进行模拟,并与华北地区616个地面环境监测站观测值进行对比,结果表明:EnKF源反演结合误差统计订正的排放清单优化方法适用于SO2排放清单的改进,有效降低了清单系统性偏差,针对主要区域及重点城市的检验显示模拟结果接近观测值;排放清单优化后模拟误差显著降低,如河北南部、山东西部至北京一带模式预报均方根误差与归一化平均绝对误差明显下降,区域内站点模拟误差呈正态分布特征,误差分布范围、最大概率出现范围均明显变窄,且最大误差概率明显上升。  相似文献   

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