北京郊区夏季PM2.5和黑碳气溶胶的观测资料分析

城市近郊常受到城区污染物扩散和输送的影响,2010年7月21日至8月6日利用β射线颗粒物连续监测仪和黑碳仪对北京西北郊区PM25和黑碳气溶胶（BC）进行了连续观测。结果表明,北京西北郊区夏季PM25和BC的质量浓度分别是(13316±8164)、(289±162) μg/m3。受明显的山谷风的影响,来自观测点东南方的城区的气流使PM25和BC浓度升高,来自观测点西北方向的风则使PM25和BC浓度降低。受局地排放、区域输送和气象条件的共同影响,郊区的PM25和BC浓度表现出明显日变化特征,二者浓度在上午、傍晚和夜间显著上升。     

乌鲁木齐大气黑碳气溶胶浓度变化特征及影响因素分析

利用乌鲁木齐大气成分观测站2009年11月—2010年2月(2009年冬季)黑碳气溶胶(BC)质量浓度观测资料,同时结合该站观测的PM数据以及国内外其它地区的BC观测结果,分析了该地区黑碳气溶胶的变化特征及影响因素。结果表明:(1)BC日平均浓度为12.442±5.407μg.m-3,其变化范围为2.685~26.691μg.m-3。BC质量浓度与API指数的变化趋势基本一致,相关系数为0.660。(2)BC浓度的日变化具有明显的双峰值特征,其峰值区主要出现在上午和夜间,谷值区出现在凌晨和下午。逐日分布具有2~3 d到数天不等的急剧上升的变化,与天气过程活动周期基本吻合。(3)周一至周四BC平均浓度呈总体降低趋势,周五开始逐渐增加,总体的变化幅度不大,工作日和周末差别较小。(4)BC小时平均浓度出现频数符合对数正态分布,冬季本底浓度为6.146μg.m-3。(5)BC与PM10,PM2.5,PM1.0日平均浓度在0.001水平上均呈正相关,线性相关系数分别为0.526,0.538和0.548;BC在PM10,PM2.5,PM1.0中分别约占6.8%,8.2%和9.2%,表明BC是PM的重要组成部分。(6)乌鲁木齐城市冬季BC气溶胶浓度高于国内外部分城市,明显高于较为洁净的边远地区,远高于瓦里关本底站及南极观测的结果。     

北京地区夏末秋初气象要素对PM2.5污染的影响

利用北京宝联站及北京上甸子大气本底站2006-2008年的7-9月PM2.5连续观测资料以及北京市观象台的探空数据、海淀气象站的风廓线雷达和降水量等资料,对北京地区夏末秋初PM2.5的质量浓度特征及其与气象要素的关系进行了统计分析.结果表明:城区站各月平均PM2.5质量浓度明显高于郊区站,高空偏南气流的输送是造成城区及本底地区出现细颗粒物污染的主要原因.从地面风速来看,城区当北风和南风分别达到2m·s-1和3.5 m·s-1以上时能起到扩散作用;郊区在低风速的北风条件下也能起到扩散和稀释作用,而南风基本上对郊区的颗粒物无扩散作用.PM2.5质量浓度在降水前后的清除量与降水量、初始质量浓度均呈正相关关系,城区及郊区的云下清除过程更多取决于降水前污染物的浓度,降水量作用较弱.当混合层高度突破1500 m时,垂直扩散对污染物的稀释扩散效果明显.     

上海市区和郊区黑碳气溶胶的观测对比

为了探讨上海市区和郊区黑碳气溶胶质量浓度、分布以及来源和输送等特征,利用上海浦东 (市区) 和东滩 (郊区河口湿地)2007年12月—2008年11月的黑碳气溶胶小时平均质量浓度数据,对比分析了两地黑碳气溶胶浓度在不同时间尺度上的变化特征以及气象要素对黑碳质量浓度的影响。结果表明:观测期间浦东和东滩两地黑碳气溶胶小时质量浓度平均值分别为3.8 μg·m-3,1.7 μg·m-3。两地黑碳气溶胶浓度具有类似的季节变化特征,均为冬季较高、夏季较低;同时浦东黑碳气溶胶浓度日变化呈现出明显的双峰结构,并具有显著的周末效应,体现了局地人为源排放的影响。受源排放影响为主的市区与受输送影响为主的郊区,黑碳气溶胶浓度在不同风向上与风速的关系表现出不同特征。     

广州城区和城郊大气颗粒物污染现状及来源分析

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。     

2007年春季广州城区黑碳气溶胶污染特征的初步研究

2007年4月利用黑碳仪（Aethalometer）、颗粒物在线观测仪（TEOM1400a）和现时天气现象传感器（PWD22）获得了大气细粒子中每5 min黑碳气溶胶（BC）浓度以及每30 min PM2.5浓度及大气能见度观测数据。结果发现：黑碳日均值浓度为7.4±2.9 μg·m－3,变化范围分别为2.1～11.6 μg·m－3。PM2.5日均值浓度为77.4±35.9 μg·m－3,浓度变化范围分别为29.6～183.3 μg·m－3。黑碳小时浓度变化具有2个明显的峰值,主要与机动车尾气排放密切相关。黑碳浓度与PM2.5浓度呈正相关,与大气能见度呈负相关,相关系数为分别为0.707和－0.529,表明黑碳是PM2.5中的重要组成部分,对大气能见度的影响较显著。     

一次雾霾天气过程的污染影响因子分析

利用常规天气资料、自动气象站资料、观象台风廓线雷达资料及污染资料,分析了2005年11月2-5日发生在北京的一次持续雾霾天气过程中中低空扰动、山谷风以及城市热岛对PM10浓度的影响。结果表明:PM10对中低空的扰动很敏感,且扰动越靠近地面,层次越厚,污染指数下降越明显;城区PM10浓度明显高于清洁对照站定陵,但北京地方性山谷风对城郊浓度日变化有明显影响,当谷风加强时,定陵站浓度接近城区并有可能高于城区浓度,谷风有对城区重污染向郊区输送的作用;雾霾天气下热岛效应显著,热岛对PM10浓度的影响相对气象条件和人类活动的影响来说很小。     

晋城市冬、春季PM2.5和PM10污染水平时空分布及其与气象因子的关系

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。     

秸秆燃烧对北京秋季气溶胶浓度和短波辐射影响的模拟研究

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%。     

山东一次PM2.5污染过程的模拟特征

利用Weather Research and Forecasting/Chemistry(WRF/Chem)空气质量模式模拟研究了山东地区2014年2月21~26日期间的中度细颗粒物(PM2.5)污染过程,并从模拟结果评估、分布及演变特征、与气象条件的关系等方面分析了PM2.5的模拟特征。模拟研究结果表明,山东PM2.5积聚期间多为弱的偏南风控制,消散阶段受西北风控制,当北京—天津—河北(京津冀)一带同时存在更为严重的PM2.5污染时,西北冷空气的平流输送使得山东部分地区的PM2.5浓度在完全削弱前又出现了一个高峰值。污染期间山东全省平均PM2.5的模拟浓度为125μg m~(-3),伴随着地面3.0 m/s的低风速、370 m低边界层高度和70%左右的相对湿度,其中PM2.5的模拟值受边界层高度的影响最大。整个污染期间全省平均PM2.5模拟值高于监测值10%左右,但是对于局部站点300μg m~(-3)及以上的观测峰值,模式模拟结果明显偏低。模拟效果的评估结果是:山东南部最好、然后是山东半岛,山东中部、西北部地区较差。     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

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.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

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.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

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.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

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.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

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     

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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     

A Brief Introduction to Marine Meteorological Science Experiment Base at Bohe Town,Maoming City,Guangdong Province

<正>With the support of specialized funds for national science institutions,the Guangzhou Institute of Tropical and Marine Meteorology,China Meteorological Administration set up in October 2008 an experiment base for marine meteorology and a number of observation systems for the coastal boundary layer,air-sea flux,marine environmental elements,and basic meteorological elements at Bohe town,Maoming city,Guangdong province,in the northern part of the South China Sea.     

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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.     

Information for Authors

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.