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1.
秸秆焚烧导致湖北中东部一次严重霾天气过程的分析   总被引:1,自引:0,他引:1  
利用地面气象要素、火点信息及污染物资料,研究了2014年6月12~13日湖北省中东部地区一次重度霾天气的成因及污染特征。结果表明:导致此次霾天气的主要原因是安徽省北部大面积秸秆焚烧所形成污染气团受偏东北气流输送的影响,12日在湖北中东部形成了两条"带状"的能见度低值区,最低能见度仅为2.1 km。秸秆焚烧污染物输送气流由北向南影响湖北,主要作用于孝感—武汉—咸宁一带,3个地区细颗粒物(PM2.5)峰值浓度均超过了600μg/m3,且武汉和孝感的PM2.5与PM10质量浓度比值在12日增加到0.76和0.77,并出现了0.96和0.93的最大值,随着污染气团的传输,其中PM2.5所占比例会出现明显下降。SO2质量浓度的变化特征不显著,NO2质量浓度在污染物质量浓度达到峰值前1~3 h达到峰值,而CO是秸秆焚烧产生的主要污染气体,其质量浓度变化与PM2.5和PM10呈正相关关系,相关系数分别为0.66和0.67。风矢量和分析表明:6月12日湖北省中东部存在明显的东北来向气流输送,污染物的输送是该时段霾天气发生的主要影响因子,而6月13日湖北省东北边界处的输送气流已经明显减弱消失,东南部风矢量和异常偏小导致的污染物堆积是该地区污染持续的主要原因。  相似文献   

2.
2009年秋季南京地区一次持续性灰霾天气过程研究   总被引:10,自引:3,他引:7  
高岑  王体健  吴建军  费启  曹璐 《气象科学》2012,32(3):246-252
2009年10月14—27日,南京地区发生了一次持续性的灰霾天气过程。利用气象观测资料和污染物浓度监测资料,结合焚烧点监测、后向气流轨迹模拟,分析了颗粒物和气态污染物的浓度演变特征、气象要素特征及产生持续灰霾天气的可能原因。研究表明,该次过程中绝大部分时间能见度低于10 km,空气污染指数最大时达到195。地面PM2.5质量浓度有显著增长,在26日达到最大值为0.782 mg/m3。NO2质量浓度日均值在24日和27日超过了环境空气质量二级标准,其含量分别为0.094和0.099 mg/m3,对应NOx质量浓度分别为0.105和0.108 mg/m3。SO2质量浓度在22日达到峰值,最大值为0.161 mg/m3,平均值为0.083 mg/m3,低于环境空气质量二级标准。分析显示:近半个月内南京地区天气形势稳定,处于持续温度偏高、干燥无雨的状态,非常有利于灰霾天气的发生。卫星监测发现24、25、26日江淮之间中部均有火点,其中24日有50个着火点,25日增加为85个,26日减少为38个,表明有秸秆焚烧现象存在。从后向气流轨迹分析来看,在秸秆焚烧最为严重的3 d内,南京地区主要受到来自东到东北方向气流的影响,有利于秸秆焚烧形成的污染物经气流输送影响南京,造成严重灰霾天气。  相似文献   

3.
利用常规气象观测资料和NCEP再分析资料对2013年12月1—8日常州地区一次持续性严重霾天气过程进行了综合分析。结果表明:常州地区此次持续性霾天气过程中高纬地区高层环流较平直,低层为弱西南暖湿气流,冷空气势力较弱;2013年11月30日常州地区位于地面"L"型高压顶部,偏西风对常州上游地区污染物的输送和12月1日清晨出现的逆温层,导致扩散条件较差是此次霾过程爆发的主要原因;持续的地面均压场控制和频繁出现的逆温层为霾提供了维持机制,12月9日的强冷空气造成了此次霾过程消散。持续性霾天气过程期间,温度露点差减小,相对湿度增大,风力减小,多为偏西偏南风,且近地面多为弱的上升运动,为霾的维持提供了稳定的层结和充足的水汽。常州地区此次霾天气过程的主要污染物为颗粒物(PM2.5、PM10),部分SO_2、NO_2及O_3等污染物通过协同转化作用生成颗粒物,导致霾粒子浓度剧增是此次霾过程爆发的重要内因;后向轨迹模式的模拟结果也表明常州上游地区污染物的输送对此次霾过程亦有贡献。  相似文献   

4.
文章利用呼和浩特市2006—2009年环境监测点监测的SO2、NO2和PM10平均浓度资料进行统计分析,得到:(1)呼和浩特市SO2日平均浓度在0.017~0.188mg·m-3之间,超标率为4.0%,NO2在0.026~0.081mg·m-3之间,未超过国家二级标准,PM10在0.036~0.332mg·m-3之间,超标率达到6.5%;(2)污染物浓度最小的月份是7月、8月,最大的月份是1月和12月;(3)近年呼和浩特污染物浓度总体呈下降趋势。  相似文献   

5.
北京一次持续霾天气过程气象特征分析   总被引:6,自引:0,他引:6       下载免费PDF全文
2013年1月10-14日,北京平原地区出现了水平能见度在2 km以下、以PM2.5为首要污染物、空气质量持续5 d维持在重度以上污染水平的霾天气。综合分析此次霾天气过程的天气形势、北京地区常规和加密气象资料以及城郊连续观测的PM2.5浓度资料。结果表明:此霾过程期间,北京高空以平直纬向环流为主,受西北偏西气流控制,没有明显冷空气南下影响北京地区,地面多为不利于污染物扩散和稀释的弱气压场;大气层结稳定、风速小(日平均风速小于2 m·s-1)、相对湿度较大(日平均相对湿度在70 %以上)、逆温频率高强度大,边界层内污染物的水平和垂直扩散能力差;北京城区及南部的京津冀地区人类活动排放污染物强度大,在相对稳定和高湿的天气背景下,受地形和城市局地环流的影响,北京本地污染物累积和区域污染物输送以及PM2.5细粒子在高湿条件下的物理化学转化等过程共同作用造成此次北京城区及平原地区污染物浓度快速增长并持续偏高,高浓度PM2.5对大气消光有显著影响,造成低能见度和持续霾天气。  相似文献   

6.
京津冀地区霾成因机制研究进展与展望   总被引:9,自引:3,他引:6  
为满足当前对京津冀地区霾研究和控制的迫切要求,本文梳理了近年来京津冀地区霾的长期变化特征、天气学特征、污染物来源等相关研究成果,发现:从2000年以后,京津冀地区的霾日数呈现出了下降趋势;北京细颗粒物(PM2.5)质量浓度也在总体上呈现下降的趋势,但2013年年均质量浓度仍高达89.5μg m–3,约为我国空气质量标准的3倍(35μg m–3),京津冀空气污染的形势依然严峻;近年来京津冀地区的霾污染事件频发可以归因为不利天气条件与大量污染物人为排放的共同作用;大量的研究表明,区域输送对京津冀地区霾事件的形成和维持有不可忽视的影响;京津冀地区的大气污染不再局限于一时一地,针对重污染天气的预警以及应急控制应该以区域预报为基础实现区域联动;京津冀地区独特的地理环境条件加上城市群的快速发展,形成的局地大气环流也会对局地的污染过程产生重大的影响;大气边界层内气象要素的变化对重污染发生具有显著贡献。京津冀地区的污染控制需要城市群的联动应对治理。  相似文献   

7.
利用南京市2002—2006年大气监测资料,分析了南京市大气中SO2、NO2、PM10年变化趋势及月季规律,评价了南京市空气质量状况。结果表明:5a来,SO2质量浓度呈显著上升趋势,NO2质量浓度缓慢上升,PM10质量浓度明显下降;南京市首要污染物是PM10,SO2、NO2污染较轻;3种污染物质量浓度均以夏季最低。进一步研究不同气象条件下污染物质量浓度发现,污染物质量浓度与风速反相关,且东南风时浓度最高;降水对污染物有清除作用;雾、霾天气下污染加剧;气象能见度与PM10、NO2的质量浓度反相关;污染物有明显的"周末效应",周末质量浓度值较低。  相似文献   

8.
魏玉香  童尧青  银燕  陈魁   《大气科学学报》2009,32(3):451-457
利用南京市2002—2006年大气监测资料,分析了南京市大气中SO2、NO2、PM10年变化趋势及月季规律,评价了南京市空气质量状况。结果表明:5a来,SO2质量浓度呈显著上升趋势,NO2质量浓度缓慢上升,PM10质量浓度明显下降;南京市首要污染物是PM10,SO2、NO2污染较轻;3种污染物质量浓度均以夏季最低。进一步研究不同气象条件下污染物质量浓度发现,污染物质量浓度与风速反相关,且东南风时浓度最高;降水对污染物有清除作用;雾、霾天气下污染加剧;气象能见度与PM10、NO2的质量浓度反相关;污染物有明显的"周末效应",周末质量浓度值较低。  相似文献   

9.
利用长株潭地区地面空气质量监测资料、常规地面气象资料及NCEP再分析资料和MODIS火点监测资料,结合HYSPLIT4后向轨迹模式,对2014年10月1718日长株潭地区一次严重霾天气过程的空气污染特征和成因进行综合分析。研究表明,长株潭地区此次严重霾天气污染事件的主要污染物为PM2.5,安徽南部和江西西北部地区秸秆焚烧产生的颗粒物,经高空偏东北气流引导输送到长株潭地区,是这次大范围烟霾天气的主要来源。长株潭地区西部高空槽区宽广,槽前西南气流较为强盛,地面受均压场控制,水平风速弱,为严重霾污染天气的维持提供了有利的环流条件。中低层逆温和大气底层湿度的增加,使污染物粒子不断累积;近地面连续静(小)风和风向的频繁转变,不利于污染物粒子的水平扩散;中下层弱的下沉气流、较低的混合层高度有利于污染物的垂直累积,为此次重度霾污染天气的发展、加强提供了有利的气象条件。  相似文献   

10.
利用1961—2012年江苏省69个地面气象站观测资料和2012年苏州市大气气溶胶观测资料,在对霾日进行判识和筛选的基础上,分析江苏省霾日的时空变化特征及霾与气象条件和污染物的关系。结果表明:1961—2012年江苏省各站年总霾日数均呈上升趋势,85%的台站呈极显著上升趋势;江苏省年平均霾日数呈显著上升趋势,其中2011—2012年呈急剧上升趋势;1980年前霾日的空间分布差异不明显,1980年后,沿江和苏南地区为霾的高发区,东部沿海大部地区霾日较少。霾天气主要发生在冬季和春季,以12月和1月发生最多。降水少和风速小有利于霾天气的发生;除SO2外,PM10、PM2.5和NO2等污染物浓度随着霾等级的增加而增大,其中PM2.5浓度增大明显。  相似文献   

11.
The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.  相似文献   

12.
Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.  相似文献   

13.
Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d.  相似文献   

14.
Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region.  相似文献   

15.
正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.  相似文献   

16.
正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on  相似文献   

17.
Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.  相似文献   

18.
正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted  相似文献   

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20.
《大气和海洋科学快报》2014,(5):F0003-F0003
AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.  相似文献   

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