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1.
Long-term variations and trends of atmospheric aerosols in the East Asian region were analyzed by using aerosol optical depth (AOD or τ), and ångström exponent (AE or α) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2010. The increased emission of anthropogenic fine aerosols in east China resulted in the high AOD in this region during summer. The steady increasing emission of anthropogenic fine aerosols caused an increasing trend of AOD in east China, and the large-scale transport of sandstorms and smoke plume caused by forest fires affected intense inter-annual variations of AOD in the East Asian region. While in the central part of South Korea, located in the lee side of the East Asian continent, AE tended to rise to a level higher than in east China, the ground-based mass concentrations continued to decline. A noticeable decrease of PM10 mass concentration in spring and winter in central Korea is most likely attributable to decreases in sandstorms in the source region of East Asia. However, the ratio of PM2.5 mass concentration to PM10 increases overall with a high level in summer. Aerosol types were classified into dust, smoke plume, and sulphate by using satellite data over Cheongwon in central Korea. The columnar AOD, with different aerosol types, was compared with the ground-based mass concentrations at Cheongwon, and the relatively high level of the correlations presented between PM2.5 and AOD produced in sulphate. Growth and increases of fine hygroscopic aerosols generated as gas-to-particle conversion particularly in summer contribute to increases of columnar AOD in the East Asian region.  相似文献   

2.
Aerosols in the atmosphere not only degrade visibility, but are also detrimental to human health and transportation. In order to develop a method to estimate PM_(2.5) mass concentration from the widely measured visibility, a field campaign was conducted in Southwest China in January 2019. Visibility, ambient relative humidity(RH), PM_(2.5) mass concentrations and scattering coefficients of dry particles were measured. During the campaign, two pollution episodes, i.e., from 4-9 January and from 10-16 January, were encountered. Each of the two episodes could be divided into two periods. High aerosol hygroscopicity was found during the first period, when RH was higher than 80% at most of the time, and sometimes even approached 100%. The second period experienced a relatively dry but more polluted condition and aerosol hygroscopicity was lower than that during the first period. An empirical relationship between PM_(2.5) mass concentration and visibility(ambient aerosol extinction) under different RH conditions could thus be established. Based on the empirical relationship,PM_(2.5) mass concentration could be well estimated from visibility and RH. This method will be useful for remote sensing of PM_(2.5) mass concentration.  相似文献   

3.
A better knowledge of aerosol properties is of great significance for elucidating the complex mechanisms behind frequently occurring haze pollution events. In this study, we examine the temporal and spatial variations in both PM_1 and its major chemical constituents using three-year field measurements that were collected in six representative regions in China between 2012 and 2014. Our results show that both PM_1 and its chemical compositions varied significantly in space and time, with high PM_1 loadings mainly observed in the winter. By comparing chemical constituents between clean and polluted episodes, we find that the elevated PM_1 mass concentration during pollution events should be largely attributable to significant increases in organic matter(OM) and inorganic aerosols like sulfate, nitrate, and ammonium(SNA),indicative of the critical role of primary emissions and secondary aerosols in elevating PM_1 pollution levels. The ratios of PM_1/PM_(2.5) are found to be generally high in Shanghai and Guangzhou, while relatively low ratios are seen in Xi'an and Chengdu, indicating anthropogenic emissions were more likely to accumulate in forms of finer particles. With respect to the relative importance of chemical components and meteorological factors quantified via statistical modeling practices, we find that primary emissions and secondary aerosols were the two leading factors contributing to PM_1 variations, though meteorological factors also played important roles in regulating the dispersion of atmospheric PM.  相似文献   

4.
Meteorological conditions, particularly the vertical wind field structure, have a direct influence on the PM2.5 concentrations over the Pearl River Delta (PRD). In October 2012, an exceptional air pollution event occurred in the PRD, and a high concentration of PM2.5 was registered at some stations. During days with PM2.5 air pollution, the wind speed was less than 3 m s-1 at the surface, and the vertical wind field featured a weak wind layer (WWL) with a thickness of approximately 1000 m. The mean atmospheric boundary layer height was less than 500 m during pollution days, but it was greater than 1400 m during non-pollution days. A strong negative correlation was detected between the PM2.5 concentration and the ventilation index (VI). The VI was less than 2000 m2 s?1 during PM2.5 air pollution days. Because of the weak wind, sea–land breezes occurred frequently, the recirculation factor (RF) values were small at a height of 800 m during pollution days, and the zones with the lowest RF values always occurred between the heights of 300 and 600 m. The RF values during PM2.5 pollution days were approximately 0.4 to 0.6 below a height of 800 m, reducing the transportation capacity of the wind field to only 40% to 60%. The RF and wind profile characteristics indicated that sea–land breezes were highly important in the accumulation of PM2.5 air pollution in the PRD. The sea breezes may transport pollutants back inland and may result in the peak PM2.5 concentrations at night.  相似文献   

5.
This paper examined the decadal mean, seasonal cycle, and interannual variations of mean and extreme temperatures using daily temperature and relative humidity data from 589 stations over eastern China and South Korea between 1996–2005. The results show that the decadal mean Tm (mean daily mean temperature) and the TNn (minimum daily minimum temperature) increase from north to south; the opposite spatial gradient is found in the DTR (diurnal temperature range); the value of the DTR over South Korea is in- b...  相似文献   

6.
Observational data from the Roshydromet hydrometeorological stations for 1978–2017, global meteorological network, and objective analysis and reanalysis (NOAA) are used to study the interannual variability of sea surface temperature and air temperature in the coastal and marine areas of the Okhotsk, Japan, Yellow, East China, and South China seas at the modern stage of the warming. Based on the EOF, cluster, and correlation analysis, the spatiotemporal pattern of temperature variations is analyzed and the zoning of sea areas according to the features of modern climate change is performed. The possible cause-and-effect relationships between these changes and the variations in wind components and climate indices are investigated. The studies revealed, specified, and quantified the modern trends and regional features of interannual variability of thermal conditions in the distinguished areas.  相似文献   

7.
In this study, interdecadal and interannual variations of the South Asian high (SAH) and the western Pacific subtropical high (WPSH), as well as their relationships with the summer climate over Asian and Pacific regions, are addressed. The variations of SAH and WPSH are objectively measured by the first singular value decomposition (SVD) mode of geopotential heights at the 100- and 500-hPa levels. The first SVD mode of summertime 100- and 500-hPa geopotential heights represents well the relationship between the variations of SAH and WPSH. Both SAH and WPSH exhibit large interannual variability and experienced an apparent long-term change in 1987. The WPSH intensifies and extends westward when SAH intensifies and extends eastward, and vice versa. The India?CBurma trough weakens when WPSH intensifies. The changes in SAH and WPSH at various levels are linked to broad-scale increases in tropical tropospheric temperature and geopotential height. When SAH and WPSH strengthen, monsoon flow becomes weaker over eastern Asia. In the meantime, precipitation decreases over eastern South China Sea, Philippines, the Philippine Sea and northeastern Asia, but increases over China, Korea, Japan and the ocean domain east of Japan. Similar features are mostly found on both interdecadal and interannual timescales, but are more evident on interannual timescale.  相似文献   

8.
秦卓凡  廖宏  陈磊  朱佳  钱静 《大气科学》2021,45(6):1273-1291
汾渭平原因其封闭的地形条件以及煤炭为主的能源结构,大气污染问题一直存在,并于2018年被列入大气污染防控的重点区域。文章利用2015年以来PM10、PM2.5、SO2、NO2、CO、O3质量浓度的观测数据和空气质量指数(Air Quality Index,简称AQI),分析了汾渭平原AQI及大气污染物质量浓度的时空分布特征;使用多元线性回归模型研究了气象条件对冬季PM2.5和夏季O3浓度日最大8 h滑动平均值(MDA8_O3)日变化和年际变化的影响。研究发现,汾渭平原的空气质量在2015~2017年间逐年变差,在2018~2019年有所好转,污染较重的城市为西安、渭南、咸阳、临汾、运城、三门峡、洛阳,集中在汾河平原与渭河平原交界处。汾渭平原的首要大气污染物多为PM2.5、PM10或O3,三者占比之和约90%。重污染时期主要集中在天气条件不利及污染物排放量大的冬季供暖期,但夏季O3浓度的升高趋势使得汾渭平原夏季污染情况越来越严重。影响汾渭平原冬季PM2.5浓度和夏季MDA8_O3日变化最主要的气象要素都是2 m高度气温(简称T2M),相对贡献分别是45.5%、35.3%,都表现为正相关;第二主要的气象要素都是2 m相对湿度(简称RH2M),相对贡献分别是41.5%(正相关)、25.4%(负相关)。影响汾渭平原冬季PM2.5浓度年际变化最主要的2个气象要素是T2M和RH2M,其相对贡献分别为43.6%、31.9%,且都呈正相关,2015~2019年汾渭平原冬季气象条件的变化会导致PM2.5浓度上升,部分削弱了人为减排导致的下降趋势(?8.3 μg m?3 a?1)。影响汾渭平原夏季MDA8_O3年际变化最主要的2个气象要素是T2M(正相关)和850 hPa风速(WS850,负相关),其相对贡献分别为71.7%、16.3%。2015~2019年汾渭平原夏季气象条件的变化导致O3污染呈上升趋势(1.2 μg m?3 a?1),但O3污染的总上升趋势(8.7 μg m?3 a?1)中,人为排放变化的贡献更大(7.5 μg m?3 a?1)。本研究表明,汾渭平原大气污染形势严峻,其颗粒物污染问题尚未解决,还面临着新的臭氧污染的挑战,汾渭平原内的11个地级市分属陕西、山西、河南三省管辖,三省交界处又是重污染区域,所以需要三省联合防治防控,协同改善汾渭平原的空气质量。  相似文献   

9.
利用MODIS火点、土地类型、植被覆盖、生物质载荷和排放因子等数据产品,开发了露天生物质燃烧排放模型,并将其嵌入空气质量模式WRF-CUACE,通过敏感性试验定量评估了露天生物质燃烧对中国地面PM2.5浓度的影响。研究设计了3种模拟方案,比较模式评估结果发现修订后的方案能更好地模拟PM2.5浓度。结果表明:2014年10月露天生物质燃烧主要集中在我国东北、华南和西南地区,其对PM2.5月平均浓度的贡献达30~60 μg·m-3,局地甚至超过100 μg·m-3;华北、华东和华南地区生物质燃烧对PM2.5月平均浓度的贡献达5~20 μg·m-3。从相对贡献看,东北大部分地区生物质燃烧对地面PM2.5浓度的贡献超过50%,华南地区达20%~50%,西南局部地区甚至超过60%;华北、华中以及华东地区相对较低,平均相对贡献达10%~20%。生物质燃烧越严重的地区,其产生的PM2.5中二次气溶胶的贡献占比越小,反之亦然。  相似文献   

10.
利用2010年南沙气象探测基地灰霾观测资料,采用灰霾数值预报系统对不同天气型灰霾过程进行数值模拟,研究珠三角地区空气污染的主要控制因子和主要污染成分及不同天气系统影响下各种排放源对珠三角地区的污染贡献。结果表明:灰霾数值预报模式模拟值与实测值趋势基本一致,除个别极值外,模拟结果能较好和定性的反应珠三角地区各污染物浓度变化,是适合珠三角地区的灰霾数值预报系统。在易出现灰霾月的变性高压入海型和不易出现灰霾月的热带气旋外围下沉气流控制时,各污染物浓度均较高,特别是PM10、PM2.5、元素碳EC(Elemental Carbon)、有机碳OC(Organic Carbon)和CO浓度尤其明显。在易出现灰霾月冷空气南下时和不易出现灰霾月无明显天气系统影响时,元素碳EC、有机碳OC和CO浓度较低,其他污染物浓度接近零。无论是否出现灰霾,相对于空气中的其他污染物,元素碳EC、有机碳OC和CO浓度均较高,说明在珠三角地区碳污染较重。  相似文献   

11.
秦皇岛地处河北省东北部,是环渤海重要的港口城市,在近几年京津冀地区减排效果较好的情况下,于2019年1月出现了多次持续细颗粒物(PM2.5)污染过程。因此本文利用耦合了数值源解析模块ISAM(Integrated Source Apportionment Method)的区域空气质量模式RAMS-CMAQ(Regional Atmospheric Modeling System–Community Multiscale Air Quality),对2019年1月秦皇岛地区PM2.5进行模拟,并将PM2.5质量浓度高于(低于)75 μg m-3的时段划分为污染(清洁)时段,分别探讨了两个时段本地排放源对秦皇岛市PM2.5质量浓度的贡献情况,并且进一步探讨了秦皇岛各区县及外地排放源对秦皇岛市4个国控环境监测站点(第一关站、北戴河站、市监测站、建设大厦站)PM2.5质量浓度的区域传输特征。结果表明,秦皇岛地区PM2.5质量浓度整体呈“南高北低”式分布。清洁时段,PM2.5质量浓度受本地贡献较大,青龙县、卢龙县大部分地区贡献为40%~50%,海港区、抚宁区、北戴河区、第一关区及昌黎县大部分地区贡献在60%以上;4个国控环境监测站点受跨界输送贡献占34.7%~41.6%。污染时段,秦皇岛市本地贡献相对于清洁时段整体下降10%左右,当地大气污染受到跨界区域传输影响增加;而在4个国控站中,北戴河站、第一关站受到跨界输送贡献分别下降1.0%和2.3%;市监测站、建设大厦站受到跨界输送贡献分别上升2.9%和2.0%。  相似文献   

12.
A total of 11 PM2.5 samples were collected from October 2003 to October 2004 at 8 sampling sites in Beijing city. The PM2.5 concentrations are all above the PM2.5 pollution standard (65 μg m^-3) established by Environmental Protection Agency, USA (USEPA) in 1997 except for the Ming Tombs site. PM2.5 concentrations in winter are much higher than in summer. The 16 Polycyclic aromatic hydrocarbons (PAHs) listed as priority pollutants by USEPA in PM2.5 were completely identified and quantified by high performance liquid chromatography (HPLC) with variable wavelength detector (VWD) and fluorescence detector (FLD) employed. The PM2.5 concentrations indicate that the pollution situation is still serious in Beijing. The sum of 16 PAHs concentrations ranged from 22.17 to 5366 ng m^-3. The concentrations of the heavier molecular weight PAHs have a different pollution trend from the lower PAHs. Seasonal variations were mainly attributed to the difference in coal combustion emission and meteorological conditions. The source apportionment analysis suggests that PAHs from PM2.5 in Beijing city mainly come from coal combustion and vehicle exhaust emission. New measures about restricting coal combustion and vehicle exhaust must be established as soon as possible to improve the air pollution situation in Beijing city.  相似文献   

13.
通过国务院“大气十条”等严格的大气污染治理措施的实施,近年来我国空气质量得到全面改善。对大气污染治理效果开展科学分析研究,可为后续空气质量持续改善、污染科学精准治理提供有效科技支撑。由于气象条件是影响污染物浓度分布的重要因素,治理效果分析的一个重要问题是区分气象条件和减排措施对污染物浓度变化的具体贡献。本文利用京津冀地区13个城市2013~2018年86个监测站点逐日PM2.5浓度以及欧洲中期气象预报中心(ECMWF)气象再分析资料,采用KZ(Kolmogorov–Zurbenko)滤波分析PM2.5浓度观测序列的时频特性,将其分解为短期天气影响分量、中期季节变化分量以及长期趋势分量3个部分,针对分解浓度序列建立气象因子回归模型,实现定量评估气象和减排对治理效果的具体贡献。在研究时间段内,京津冀地区13个城市PM2.5浓度的长期分量显著下降(22.2%~58.0%),其中邢台市下降幅度最大(58.0%)。整体分析表明,气象条件和排放源均有利于大气污染的改善,但减排措施是空气质量显著改善的决定性原因,具体贡献为气象条件的影响占18.5%,排放源的影响占81.5%。逐城分析表明,唐山市的气象条件最有利于PM2.5浓度的减小(29.2%),而衡水市的减排措施最有利于PM2.5浓度的减小(92.0%)。  相似文献   

14.
南京市气溶胶PM2.5一次来源解析   总被引:14,自引:4,他引:10  
在南京大学鼓楼校区(市区)和南京信息工程大学(郊区)校园,分季采集PM2.5及其主要排放源的颗粒样品,在南京大学现代分析测试中心用X-荧光分析法分析样品中的化学元素,应用化学元素平衡法(CMB)计算了各主要源对PM2.5的贡献。结果表明对市区扬尘和建筑尘是PM2.5最主要的贡献源,贡献率合计约70%;燃煤尘和冶炼尘仅为约15%。对郊区扬尘和煤烟尘是PM2.5的最主要贡献源,平均贡献率分别为50%和22.4%,建筑尘的平均贡献率为8.3%,冶炼尘的贡献小于8%。这些结果可为治理气溶胶细颗粒源提供决策依据。  相似文献   

15.
The interannual variations of the sea level at the coastal stations of the Sea of Japan and of the water discharge through the Korea (Tsushima) Strait are studied. It is demonstrated that the interannual variations of the water discharge through this strait are determined by the water discharge of the Oyashio (in the subarctic Pacific) and the Kuroshio (in the East China Sea) currents and by the zonal wind stress component over the Sea of Japan in winter period. It is revealed that the variations in the East China Sea water transport through the Korea (Tsushima) Strait cause the interannual variations of the dissolved oxygen content in intermediate (500 m) and deep (1000 m and more, σθ = 27.35) waters of the Sea of Japan.  相似文献   

16.
In this work, the influence of South Asian biomass burning emissions on O3 and PM2.5 concentrations over the Tibetan Plateau (TP) is investigated by using the regional climate chemistry transport model WRF-Chem. The simulation is validated by comparing meteorological fields and pollutant concentrations against in situ observations and gridded datasets, providing a clear perspective on the spatiotemporal variations of O3 and PM2.5 concentrations across the Indian subcontinent, including the Tibetan Plateau. Further sensitivity simulations and analyses show that emissions from South Asian biomass burning mainly affect local O3 concentrations. For example, contribution ratios were up to 20% in the Indo-Gangetic Plain during the pre-monsoon season but below 1% over the TP throughout the year 2016. In contrast, South Asian biomass burning emissions contributed more than 60% of PM2.5 concentration over the TP during the pre-monsoon season via significant contribution of primary PM2.5 components (black carbon and organic carbon) in western India that were lofted to the TP by westerly winds. Therefore, it is suggested that cutting emissions from South Asian biomass burning is necessary to alleviate aerosol pollution over the TP, especially during the pre-monsoon season.  相似文献   

17.
Sandstorms in the desert and loess regions of north China and Mongolia, as well as the associated dustfall episodes on the Korean Peninsula, were monitored in 2005. The ground mass concentrations of PM10 and PM2.5 were analyzed during dustfall episodes at Cheongwon, in central south Korea, based on synoptic features at surface, 850 hPa and 500 hPa levels. A total of seven dustfall episodes lasting eleven days were observed and the mass concentration ratios of PM2.5 and PM10 during dustfall episodes were classified into a severe dustfall episode (SDE) and a moderate dustfall episode (MDE) depending upon two synoptic features. The main synoptic feature was for SDEs, which occurred frequently under a surface anticyclone and cyclone located in the west and east of the Korean Peninsula with large amplitude trough at 500 hPa over the northern Korean Peninsula. The sandstorms at the source headed directly to Korea via a strong N-NW wind without passing through any large cities or industrial areas of east China. The PM10 mass concentration sharply increased during the SDEs; however, the fine aerosol fraction of PM2.5 levels was relatively low with 13.6% of the mass concentration. In a synoptic feature for MDEs, a slow moving cyclone headed to Korea via the industrial areas of northeastern China under a small amplitude trough at a 500 hPa level. A weak anticyclone was also located over China. MDEs showed low mass concentrations of coarse PM10 particles and large fraction of fine PM2.5 particles at 46.3%.  相似文献   

18.
利用2016年12月至2017年5月海南省3个地级市(三沙市永兴岛、三亚、海口)监测的PM2.5、PM10数据,对比分析其污染特征。结果表明:相较于海口、三亚,永兴岛空气质量最好,细粒子污染程度最轻且PM2.5、PM10质量浓度日变化最平稳,其主要原因是人类生产活动对空气质量的影响不大。进一步通过分析3个站点的PM2.5质量浓度与近地面气象要素(相对湿度、月总降水量、能见度)发现,永兴岛PM2.5质量浓度与能见度整体呈负相关,永兴岛在不同风速、风向上的PM2.5质量浓度最小,三亚次之,海口最大。永兴岛PM2.5的大值区主要出现在东北风向上,其他方向上的气流则相对比较清洁,且在静风或者微风条件下,永兴岛的初始PM2.5质量浓度比较低。通过每天逐6 h的72 h后向轨迹分析发现,冬季、夏季风影响期间,永兴岛分别受来源于西太平洋、南海的海洋性气流影响,这与永兴岛的空气质量有直接关系。  相似文献   

19.
东亚冬季风综合指数及其表达的东亚冬季风年际变化特征   总被引:19,自引:4,他引:15  
贺圣平  王会军 《大气科学》2012,36(3):523-538
本文通过多变量经验正交函数展开 (multivariate EOF, 简称 MV-EOF) 研究了东亚冬季风各系统成员的协同关系, 再运用单变量EOF定义单个系统的强度系数。从而给出能够反映东亚冬季风各主要特征及其年际变化、同时包含西伯利亚高压、东亚大槽和纬向风经向切变信息的强度指数 (EAWMII)。分析表明, 这个新指数EAWMII能够很好地反映东亚冬季风在20世纪80年代中期的减弱信号, 并且与大气环流场以及东亚冬季表面温度的变化均显著相关, 能够在很大程度上表征东亚冬季风的综合特征。此外, EAWMII与北极涛动 (Arctic Oscillation, 简称AO) 指数、北太平洋涛动 (North Pacific Oscillation, 简称NPO) 指数和Nio3.4指数相关显著。分析还表明AO和NPO影响东亚冬季气候的区域有所不同: AO主要影响欧亚大陆中、高纬、我国东北以及日本北部等地区, NPO则主要影响华南、华东、朝鲜、韩国以及日本中南部及其附近海域。并且, AO很可能可以通过影响NPO进而影响东亚冬季风。  相似文献   

20.
为了解邢台沙河市冬季大气污染特征,选取2017年12月至2018年2月沙河市区3个省控站点(司法局、市政府、宣传中心)的逐时监测数据,分析了沙河市主要污染物的时空分布特征和潜在源区。污染物浓度特征分析表明:整个冬季司法局、市政府和宣传中心站点的细颗粒物(PM2.5)平均浓度分别为118.0 μg/m3、121 μg/m3和135 μg/m3。在大气自然活动和人为污染排放的共同作用下,PM10、PM2.5、SO2、NO2和CO均有明显的日变化特征。整个冬季沙河市的ρ(PM2.5)/ρ(PM10)、ρ(SO2)/ρ(NO2)均值分别为0.57和1.05(ρ为各物质的浓度)。且随着污染加重,ρ(PM2.5)/ρ(PM10)、ρ(SO2)/ρ(NO2)均明显升高,表明燃煤贡献增加;污染物空间分布特征分析表明:位于3个站点东北处的玻璃企业产生的污染物可能对监测站点造成了一定影响。污染物空间差异分析表明,区域污染范围越大、强度越高,大气污染的空间差异性越小;潜在源分析表明:沙河市PM2.5的强潜在源区分布在其周边区域,随着PM2.5浓度增加,强潜在源区呈缩小趋势。沙河市东南部的本地源对PM2.5浓度有主要贡献,而此处正是玻璃企业的聚集地。  相似文献   

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