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1.
The insular suburban site of Castillo de Bellver was selected for the study of the variability of PM levels and composition in the Western Mediterranean Basin (WMB).Mean annual (in 2004) PM10 and PM2.5 levels at this site were 29 and 20 µg/m3, respectively. These levels may be regarded as relatively low when compared with other suburban insular locations in the Eastern Mediterranean Basin (EMB), but they are higher than those recorded at most of the European suburban sites, especially in Northern and Western Europe. Seasonal variability of PM levels at this site is governed by meteorology rather than local emissions, whereas the daily cycles are clearly defined by the anthropogenic emissions, mainly coming from the urban area of Palma de Mallorca and the harbour area of the same city.Concerning the aerosol composition at this site, the main PM constituent is the mineral matter (29% in PM10 and 16 % in PM2.5), more than 50% (in PM10) being attributable to African dust. The amount of secondary inorganic aerosols is also very high (27% in PM10 and 34% in PM2.5), with the predominance of fine ammonium sulphate, and in a less proportion fine ammonium nitrate (in winter) and coarse Ca and Na nitrate (with higher importance in summer). The carbonaceous particles, dominantly fine, account for 17% of PM10 and 25% of PM2.5. The elemental carbon/organic carbon (EC/OC) ratio reached a mean value of 0.17, similar to those observed at regional background sites in the WMB coast of Spain. The sea spray aerosols (mainly coarse) represented around 10% of PM10, and only 4% in PM2.5. Finally, the unaccounted fraction increased from 15% to 20% in PM2.5, being mostly attributed to water.The concentrations of trace elements in PM10 and PM2.5 were usually in the range to those observed in regional background sites in the Iberian Peninsula, with the exception of the typical tracers of road traffic such as Cu, Sb, Zn, Sn and Ba, which presented concentrations in the range of urban sites of Iberia. Other elements such as Cr, Zr, Hf and Co have been identified as the main tracers of the harbour contributions.  相似文献   

2.
Source identification of PM2.5 particles measured in Gwangju, Korea   总被引:1,自引:0,他引:1  
The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM2.5 particles were used for the analysis of carbonaceous species (organic (OC) and elemental carbon (EC)) using the thermal manganese dioxide oxidation (TMO) method, the investigation of seven ionic species using ion chromatography (IC), and the analysis of twenty-four metal species using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS). According to annual average PM2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM2.5 mass (21.5 μg m− 3), followed by secondary sulfate (14.6%), meat cooking (11.7%), secondary organic carbon (8.9%), secondary nitrate (7.6%), urban dust (5.5%), Asian dust (4.4%), biomass burning (2.8%), sea salt (2.7%), residual oil combustion (2.6%), gasoline vehicle exhaust (1.9%), automobile lead (0.5%), and components of unknown sources (3.4%). Seven PM2.5 sources including diesel vehicles (29.6%), secondary sulfate (17.4%), biomass burning (14.7%), secondary nitrate (12.6%), gasoline vehicles (12.4%), secondary organic carbon (5.8%) and Asian dust (1.9%) were identified from the UNMIX analysis. The annual average source apportionment results from the two models are compared and the reasons for differences are qualitatively discussed for better understanding of PM2.5 sources.Additionally, the impact of air mass pathways on the PM2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM2.5 collected during the four air mass patterns and two event periods were calculated with the CMB model and analyzed. Results of source apportionment revealed that the contribution of diesel traffic exhaust (47.0%) in stagnant conditions (S) was much higher than the average contribution of diesel vehicle exhaust (33.4%) during the sampling period. During Asian dust (AD) periods when the air mass passed over the Korean peninsula, Asian dust and secondary organic carbon accounted for 25.2 and 23.0% of the PM2.5 mass, respectively, whereas Asian dust contributed only 10.8% to the PM2.5 mass during the AD event when the air mass passed over the Yellow Sea. The contribution of biomass burning to the PM2.5 mass during the biomass burning (BB) event equaled 63.8%.  相似文献   

3.
气候变化引起的地面气溶胶浓度变化与区域空气质量密切相关。本文利用“国际大气化学—气候模式比较计划”(Atmospheric Chemistry and Climate Model Intercomparison Project, ACCMIP)中4个模式的试验数据分析了RCP8.5情景下2000~2100年气候变化对中国气溶胶浓度的影响。结果显示,在人为气溶胶排放固定在2000年、仅考虑气候变化的影响时,2000~2100年气候变化导致中国北部地区(31°N~45°N, 105°E~122°E)硫酸盐、有机碳和黑碳气溶胶分别增加28%、21%和9%,硝酸盐气溶胶在中国东部地区减少30%。气候变化对细颗粒物(PM2.5)浓度的影响有显著的季节变化特征,冬季PM2.5浓度在中国东部减少15%,这主要是由硝酸盐气溶胶在冬季的显著减少造成的;夏季PM2.5浓度在中国北部地区增加16%,而长江以南地区减少为9%,这可能与模式模拟的未来东亚夏季风环流的增强有关。  相似文献   

4.
春季中国东部气溶胶化学组成及其分布的模拟研究   总被引:2,自引:0,他引:2  
本文利用区域空气质量模式RAQMS(Regional Air Quality Model System),对2009年春季中国东部气溶胶主要化学成分及其分布进行了模拟研究。与泰山站观测资料的对比结果显示,模式能比较合理地反映气溶胶浓度的逐日变化特征。整体上,模式对无机盐气溶胶的模拟好,分别高估和低估黑碳和有机碳气溶胶浓度,其原因与排放源、二次有机气溶胶化学机制和模式分辨率的不确定性有关。模拟结果显示,春季气溶胶浓度高值主要集中于华北、四川东部、长江中下游等地区。受东南亚生物质燃烧和大气输送的影响,中国的云南和广西等地区有机碳浓度高于中国其他地区。中国西北部沙尘浓度较高,而且向东输送并影响到中国东部和南方部分地区。中国东部的华北、四川东部、长江中下游等地PM2.5(空气动力学直径在2.5微米以下的颗粒物)污染严重,4月平均PM2.5浓度超过了我国日平均PM2.5浓度限值。中国东部泰山站的观测和模拟结果都显示近地面硝酸盐浓度超过硫酸盐,中国北部对流层中硝酸盐的柱含量也大于硫酸盐,而在中国南部则相反,这一方面与春季中国云量 南多北少的分布特征以及云内液相化学反应有关,另一方面也与南北温差对气溶胶形成的影响有关。就整个中国东部而言,虽然硫酸盐的柱含量(46 Gg)仍大于硝酸盐(42 Gg),但比较接近,反映出我国氮氧化物排放迅速增加的趋势。春季中国地区对流层中PM10(空气动力学直径在10微米以下的颗粒物)及其化学成分柱含量分别为:990.8 Gg(PM10),52.6 Gg(硫酸盐),48.2 Gg(硝酸盐),32.1 Gg(铵盐),22.9 Gg(黑碳)和74.1 Gg(有机碳),有机碳(OC)中一次有机碳(POC)和二次有机碳(SOC)分别占60%和40%,中国东部PM10中人为气溶胶和沙尘分别占30%和70%,反映了春季沙尘对我国大气气溶胶的重要贡献。  相似文献   

5.
Epidemiological studies initially considered the impact of total solid particles on human health, but according to the acquired knowledge about the worse effect of smaller particles, those studies turned to consider the impact of PM10. However, for the last decade PM2.5 began to be more important, once as they are smaller they can penetrate deeper in the lungs, being possible their trapping in alveoli and worse effects on human health. Therefore, more information on PM2.5 should be provided namely concerning the levels and elemental composition. Considering the relevance of traffic on the emission of particles of small sizes, this work included the detailed characterization of PM10 and PM2.5, sampled at two sites directly influenced by traffic, as well as at two reference sites, aiming a further evaluation of the influence of PM10 and PM2.5 on public health. The specific objectives were to study the influence of traffic emission on PM10 and PM2.5 characteristics, considering concentration, size distribution and elemental composition. PM10 and PM2.5 samples were collected using low-volume samplers; the element analyses were performed by particle induced X-ray emission (PIXE). At the sites influenced by traffic emissions PM10 and PM2.5 concentrations were 7–9 and 6–7 times higher than at the background sites. The presence of 17 elements (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn and Pb) was determined in both PM fractions; particle metal contents were 3–44 and 3–27 times higher for PM10 and PM2.5, respectively, than at the backgrounds sites. The elements originated mostly from anthropogenic activities (S, K, V, Mn, Ni, Zn and Pb) were predominantly present in PM2.5, while the elements mostly originated from crust (Mg, Al, Si and Ca) predominantly occurred in PM2.5–10. The results also showed that in coastal areas sea salt spray is an important source of particles, influencing PM concentration and distributions (PM10 increased by 46%, PM2.5/PM10 decreased by 26%), as well as PM compositions (Cl in PM10 was 11 times higher).  相似文献   

6.
A set of daily PM10 (n = 281) samples collected from April 2001 to April 2002 at a rural site (Erdemli), located on the coast of the Eastern Mediterranean, were analyzed applying Mass Closure (MC), absolute principal factor analysis (APFA) and Positive Matrix Factorization (PMF) to determine source contributions. The results from the three techniques were compared to identify the similarities and differences in the sources and source contributions. Source apportionment analysis indicated that PM10 were mainly originated from natural sources (sea salt + crustal ≈ 60%) whilst secondary aerosols and residual oil burning accounted for approximately 20% and 10% of the total PM10 mass, respectively. Calculations for sulfate showed that on average 8% and 12% of its total concentration were originated from sea salt and biogenic emissions, respectively. However, the contribution by biogenic emissions may reach up to a maximum of ~ 40% in the summer. Potential Source Contribution Function (PSCF) analysis for identification of source regions showed that the Saharan desert was the main source area for crustal components. For secondary aerosol components the analysis revealed one source region, (i.e. the south-Eastern Black Sea), whereas for residual oil, Western Europe and the western Balkans areas were found to be the main source regions.  相似文献   

7.
不同降水强度对PM2.5的清除作用及影响因素   总被引:1,自引:0,他引:1       下载免费PDF全文
云和降水过程是大气污染物的重要清除途径,但由于降水过程和大气污染颗粒物本身的复杂性,目前降水过程对大气污染物的清除机制及影响因素有待深入研究。该文利用2014年3月—2016年7月在北京地区连续观测的PM2.5和降水数据,研究了不同降水强度对PM2.5的清除率,以及雨滴谱、风速和降水持续时间对PM2.5清除率的影响。研究表明:降水强度越大,对PM2.5清除效率越高。小雨、中雨和大雨对PM2.5清除率平均值分别为5.1%,38.5%和50.6%。小雨不但对PM2.5的清除率最低,而且对PM2.5的清除效果也存在很大差异,约50%的小雨个例中PM2.5质量浓度出现减小情况,而另外50%的小雨个例中,PM2.5质量浓度出现增加情况。在持续时间长或地面风速增大的情况下,小雨也表现出较高的清除率。在中雨和大雨情况下,PM2.5质量浓度均出现明显减小情况。但降水持续时间和风速对中雨和大雨的清除率影响较小,这是由于中雨和大雨一般在较短时间内即可清除大部分PM2.5,因此,对降水的持续时间和风速大小不敏感。  相似文献   

8.
This work attempts to characterize metallic elements associated with atmospheric particulate matter on a dry deposition plate, a TE-PUF high-volume air sampler and a universal air sampler. Dry deposition fluxes of particulates and concentrations of total suspended particulate, fine (PM2.5) and coarse (PM2.5–10) particulate matters were collected at Taichung harbor sampling sites from August 2004 to January 2005. Chemical analyses of metallic elements were made using a flame atomic absorption spectrophotometer coupled with hollow cathode lamps. Concentrations of metal elements in the forms of coarse particles and fine particles as well as the coarse/fine particulate ratios were presented. Statistical methods such as correlation analysis, principal component analysis and enrichment factor analysis were performed to compare the chemical components and identify possible emission sources at the sampling sites. Metallic elements of Cu, Zn, Pb, Cr, Ni and Mg had higher EFcrust ratios in winter and spring than in summer and autumn. Diurnal and nocturnal variations of metallic element concentrations in fine and coarse particles were also discussed.  相似文献   

9.
周涛  周青  张勇  张传江  李津  赵华  张茜茹 《气象科技》2022,50(4):574-583
本文综合利用2015—2020年地面气象观测资料、欧洲中心ERA5再分析资料及大气环境监测数据,分析了汾渭平原东部运城市污染物浓度的变化特征以及与天气形势和气象要素的关系。结果表明:①2015—2020年期间运城市PM2.5、PM10、SO2、NO2、CO 5种污染物年平均浓度呈下降趋势,而O3浓度呈上升趋势;②冬季和夏季空气质量相对较差,首要污染物分别是PM2.5和O3,边界层高度的变化与近地层风向风速、污染物浓度的关系密切,冬季(夏季)PM2.5(O3)污染较重时边界层高度较低(较高),以东北风(东南风)为主,风速偏小(偏大);③最后利用自组织映射神经网络(SOM)算法分别对冬夏925 hPa位势高度场进行天气分型并开展不同天气形势下污染物浓度与气象要素的变化对比研究,发现冬季污染时以静稳天气为主,低层弱东北风将污染物输送至运城市,而夏季O3污染较重时受热低压形势控制,利于O3前体物汇合,太阳辐射较强时O3浓度较高。  相似文献   

10.
In urban areas traffic is the major contributor to atmospheric particulate matter and exposure to these particles currently represents a serious risk to human health. The attention has been recently focused more on the particles of smaller sizes (PM2.5) which penetrate deeper in respiratory system causing severe health effects. Therefore, more information on PM2.5 should be provided, namely concerning morphological and chemical characterization. Aiming further evaluation of the impact of traffic emissions on public health, this work evaluated the influence of traffic on the chemical and morphological characteristics of PM10 and PM2.5, collected at one site influenced by traffic emissions and at one reference site. Chemical and morphological characteristics of 1,000 individual particles were determined by scanning electron microscopy combined with energy dispersive spectrometer (SEM–EDS). Cluster analysis (CA) was used to identify different types of particles that occurred in PM, aiming the identification of the respective emission sources. Traffic PM2.5 were dominated by particles composed of Fe oxides and alloys (67%) which were related to traffic emissions (this percentage was 3.7 times higher than at the background site); in PM2.5–10 the abundance of Fe oxides and alloys were 20% and 0% for the traffic and background sites, respectively. Background PM2.5 were mainly constituted by aluminum silicates (63%) related to natural sources (this percentage was 2.5 times higher than at the traffic site); the abundances of aluminum silicates in PM2.5–10 were 74% and 73% for traffic and background sites, respectively. It was concluded that traffic emissions were mainly present in PM2.5 (the percentage of particles associated to these emissions was 3.4 times higher than in PM2.5–10), while coarse particles were dominated by material of natural origin (the percentage of particles associated was 1.2 and 3.0 times higher than in PM2.5 for traffic and background sites, respectively). Previous results obtained by proton induced X-ray emission (PIXE) were consistent with SEM–EDS analysis that showed to be very useful to complement elemental analysis of different PM2.5 and PM2.5–10.  相似文献   

11.
The contribution of emissions from agricultural facilities is rapidly becoming a major concern for local and regional air quality. Characterization of particle properties such as physical size distribution and chemical composition can be valuable in understanding the processes contributing to emissions and ultimate fate of particulate matter from agricultural facilities. A measurement campaign was conducted at an Iowa, deep-pit, three-barn swine finishing facility to characterize near-source ambient particulate matter. Size-specific mass concentrations were determined using minivol samplers, with additional size distribution information obtain using optical particle counters. Particulate composition was determined via ion chromatographic analysis of the collected filters. A thermal-CO2 elemental/organic carbon analyzer measured particulate carbon. The chemical composition and size distribution of sub-micron particles were determined via real-time aerosol mass spectrometry. Primary particulate was not found to be a major emission from the examined facility, with filter-based impactor samples showing average near-source increases (~15–50 m) in ambient PM10 of 5.8 ± 2.9 μg m−3 above background levels. PM2.5 also showed contribution attributable to the facility (1.7 ± 1.1 μg m−3). Optical particle counter analysis of the numerical size distributions showed bimodal distributions for both the upwind and downwind conditions, with maximums around 2.5 μm and below the minimum quantified diameter of 0.3 μm. The distributions showed increased numbers of coarse particles (PM10) during periods when wind transport came from the barns, but the differences were not statistically significant at the 95% confidence level. The PM10 aerosols showed statistically increased concentrations of sulfate, nitrate, ammonium, calcium, organic carbon, and elemental carbon when the samplers were downwind from the pig barns. Organic carbon was the major constituent of the barn-impacted particulate matter in both sub-micron (54%) and coarse size (20%) ranges. The AMS PM1 chemical speciation showed similar species increases, with the exception of and Ca+2, the latter not quantified by the AMS.  相似文献   

12.
利用重庆地区能见度及温、压、湿、风等气象资料和大气颗粒物浓度数据,对重庆能见度特征及其影响因子进行分析,采用神经网络方法建立能见度预报模型,分析比较了引入PM2.5浓度因子对预报模型的影响效果。发现:重庆地区能见度分布呈现西低东高以及长江沿线较低的分布特征;雾发生时的平均能见度低于降水时能见度也远低于剔除雨、雾后的能见度,表明低能见度受大气中水汽影响更大;雾在冬季比例明显增加,使得平均能见度在冬季明显降低,而6月和10月降水增多是导致这两个月平均能见度出现明显降低的重要原因;能见度日变化呈现单峰型,雾和降水高发时段与平均能见度低值区重叠,是造成夜间能见度低的一个重要原因;大气湿度、温度及颗粒物浓度都是影响能见度的重要因子,当相对湿度小于70%时能见度随PM2.5增加明显降低,当相对湿度大于70%时PM2.5对能见度的影响降低;在能见度的客观预报模型中引入PM2.5浓度因子的预报效果好于不引入该因子的效果,特别是秋冬季的预报效果改善明显。  相似文献   

13.
针对受体模型对大气PM2.5中二次无机、有机气溶胶不能给出有效源贡献的问题,建立了一种基于污染源清单的化学质量平衡(Inventory-Chemical Mass Balance,I-CMB)颗粒物源解析受体模型,代入北京市近年的污染物排放数据进行了解析应用。结果表明,燃煤是北京大气PM2.5的最大来源(占比约28.06%),其余依次为机动车(19.73%)、扬尘(17.88%)、工业(16.50%)、餐饮(3.43%)、植物(3.40%)。相比于传统的化学质量平衡法(Chemical Mass Balance,CMB),I-CMB的源解析过程对源成分谱的要求较低、抗干扰性更强,计算结果均衡、详尽,比较适合我国当前大气PM2.5控制的需求。  相似文献   

14.
Shanghai is the largest industrial and commercial city in China, and its air quality has been deteriorating for several decades. However, there are scarce researches on the level and seasonal variation of fine particle (PM2.5) as well as the carbonaceous fractions when compared with other cities in China and around the world. In the present paper, abundance and seasonal characteristics of PM2.5, organic carbon (OC) and elemental carbon (EC) were studied at urban and suburban sites in Shanghai during four season-representative months in 2005–2006 year. PM2.5 samples were collected with high-vol samplers and analyzed for OC and EC using thermal-optical transmittance (TOT) protocol. Results showed that the annual average PM2.5 concentrations were 90.3–95.5 μg/m3 at both sites, while OC and EC were 14.7–17.4 μg/m3 and 2.8–3.0 μg/m3, respectively, with the OC/EC ratios of 5.0–5.6. The carbonaceous levels ranked by the order of Beijing > Guangzhou > Shanghai > Hong Kong. The carbonaceous aerosol accounted for  30% of the PM2.5 mass. On seasonal average, the highest OC and EC levels occurred during fall, and they were higher than the values in summer by a factor of 2. Strong correlations (r = 0.79–0.93) between OC and EC were found in the four seasons. Average level of secondary organic carbon (SOC) was 5.7–7.2 μg/m3, accounting for  30% of the total OC. Strong seasonal variation was observed for SOC with the highest value during fall, which was about two times the annual average.  相似文献   

15.
通过采集武汉市土壤风沙尘、建筑水泥尘、城市扬尘、餐饮源、生物质燃烧源、工业煤烟尘和电厂煤烟尘等7类源样品,并分析其碳组分、水溶性离子组分和无机元素组分,建立PM10和PM2.5源成分谱.研究表明,地壳元素Si、Ca、Al以及Fe等是土壤风沙尘的主要特征组分,其中Si是含量最高的成分,也是土壤风沙尘的标识组分.无组织建筑水泥尘中Si和Ca元素含量较高,将Ca元素作为无组织建筑水泥尘区别其他源类的重要元素,而有组织建筑水泥尘中OC、SO42-含量比无组织建筑水泥尘高.城市扬尘中Ca的含量相对较高,表明城市扬尘受到建筑水泥尘影响较多.生物质燃烧源成分谱中OC的含量远高于成分谱中其他组分,另外Cl-和K的平均含量也较高,K一般为生物质源的特征元素.  相似文献   

16.
面对日益严峻的大气污染形势,针对卫星气溶胶光学厚度(AOD)资料在灰霾数值预报领域的合理有效利用问题,使用WRF-Chem(WRF coupled with Chemistry)大气化学模式以及GSI(Gridpoint Statistical Interpolation)三维变分同化系统,利用MODIS和FY-3A/MERSI AOD资料,对一次灰霾天气过程进行了同化预报试验。试验结果显示,同化卫星AOD资料有效改善了模式初始场,MODIS和MERSI同化试验分别在AOD分析场的中心强度和空间分布各具优势,且对PM2.5和PM10的后续预报改进明显;从统计分析上看,同化试验的预报效果整体上好于控制试验,同化试验中PM2.5和PM10预报值的平均值、中值、平均偏差、均方根误差等指标均明显优于控制试验,且MODIS和MERSI同化试验分别在PM2.5和PM10预报统计结果中体现出了优势;卫星AOD资料同化能明显降低污染事件的空报率和漏报率,提高预报的TS评分和ETS评分。不同卫星AOD资料的差异对分析场中AOD的分布和强度产生了相应影响,进而影响了模式的灰霾预报效果;本次试验中,MODIS和MERSI AOD同化试验分别在PM2.5和PM10预报的评分上表现更佳。结果表明,卫星AOD资料同化对数值预报产生了积极的效果。   相似文献   

17.
对2002年1月1日-2002年12月31日日照市环境监测中心提供的PM10(可吸入颗粒物)日平均浓度资料和对应时段的日照市地面气象资料做了深入的分析,揭示了污染物PM10变化特征及其随气象要素的变化规律。同时分析了主要污染物PM10与地面风速、风向间的相关关系,发现日照市大于等于3级的PM10污染日均出现在1-4月,地面风速对污染物PM10浓度有一定影响,当地面风速超过5m/s时,3级及以上污染日很少出现,当地面风速超过6.5m/s时,随着风速的提高,污染物浓度呈下降趋势。污染物浓度呈明显的季节变化,冬、春季节明显高于夏、秋季节。  相似文献   

18.
Time-series of weekly total carbon(TC)concentrations of fine aerosol particles(PM2.5)in Beijing and Toronto were compared to investigate their respective levels and temporal patterns over two years from August 2001 through July 2003.In addition to this comparison,differences in the factors contributing to the observed concentrations and their temporal variations are discussed.Based upon past knowledge about the two megacities with highly contrasting air pollutant levels,it is not surprising that the average TC concentration in Beijing(31.5μg C m-3)was greater than that in Toronto by a factor of 8.3.Despite their large concentration differences,in both cities TC comprised a similarly large component of PM2.5.TC concentrations exhibited very different seasonal patterns between the two cities.In Beijing,TC experienced higher levels and greater weekly fluctuations in winter whereas in Toronto this behavior was seen in summer. As a result,the greatest gap in TC concentrations between Beijing and Toronto(by a factor of 12.7) occurred in winter,while the smallest gap(a factor of 4.6)was in summer.In Beijing,seasonal variations in the emissions probably played a greater role than meteorology in influencing the TC seasonality,while in Toronto during the warm months more than 80%of the hourly winds were recorded from the south,along with many potential anthropogenic sources for the days with high TC concentrations.This comparison of the differences provides insight into the major factors affecting carbonaceous aerosol in each city.  相似文献   

19.
Spokane, WA is prone to frequent particulate pollution episodes due to dust storms, biomass burning, and periods of stagnant meteorological conditions. Spokane is the location of a long-term study examining the association between health effects and chemical or physical constituents of particulate pollution. Positive matrix factorization (PMF) was used to deduce the sources of PM2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) at a residential site in Spokane from 1995 through 1997. A total of 16 elements in 945 daily PM2.5 samples were measured. The PMF results indicated that seven sources independently contribute to the observed PM2.5 mass: vegetative burning (44%), sulfate aerosol (19%), motor vehicle (11%), nitrate aerosol (9%), airborne soil (9%), chlorine-rich source (6%) and metal processing (3%). Conditional probability functions were computed using surface wind data and the PMF deduced mass contributions from each source and were used to identify local point sources. Concurrently measured carbon monoxide and nitrogen oxides were correlated with the PM2.5 from both motor vehicles and vegetative burning.  相似文献   

20.
侯梦玲  王宏  赵天良  车慧正 《大气科学》2017,41(6):1177-1190
本文利用GRAPES_CUACE大气化学模式对京津冀地区2015年12月重度雾霾过程进行了模拟和评估。京津冀地区能见度和PM2.5模拟值与观测值的对比表明:该模式能较好地模拟京津冀地区能见度和PM2.5的逐日变化情况,但模式存在对伴随着重污染发生的低能见度模拟偏高的问题。以12月5~10日的重度雾霾过程为重点,针对地面风速、边界层高度、相对湿度、PM2.5及其对能见度的影响进行了详细分析,研究结果表明:污染过程中大部分地区过程平均风速低于2 m s-1,边界层平均高度低于600 m,相对湿度较高。模式低能见度模拟偏高可能因为:(1)模式模拟重雾霾时段的PM2.5极大值浓度偏低。(2)模拟相对湿度存在系统性偏低的误差,这一误差对能见度的影响表现为两方面,一是相对湿度会通过影响可溶性气溶胶的吸湿增长过程影响气溶胶质量浓度,导致气溶胶消光系数的计算偏低;二是目前模式中采用的能见度的参数化公式考虑了相对湿度对气溶胶吸湿增长的影响,没有考虑雾滴的直接消光作用。  相似文献   

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