华北地区一次重污染天气的气象变化过程分析

利用大气环境监测数据、常规气象观测资料、探空数据以及HYSPLIT后向轨迹模式对2014年2月20—26日发生在华北区域的一次大面积重污染天气进行综合分析。利用风云卫星观测资料直观展示了污染的生成、消散状况。结果表明,在此次重污染天气过程中,华北地区主要城市均观测到高浓度的PM_(2.5),其中北京、石家庄PM_(2.5)小时浓度均值分别为286.1、371.2μg/m~3。该次污染与天气过程关系密切,平稳的高空环流形势、华北地面弱低压为污染天气的发生、发展提供了有利的气象条件。地面的静风或小风天气以及近地逆温的出现有利于污染的维持。后向轨迹分析表明,此次污染过程区域性明显,南部、西南部周边地区的污染物外源性输入对研究的主要城市有显著影响。     

基于RAMS-CMAQ模拟的2019年初威海市大气污染反弹成因研究

威海市是山东省东部最典型的沿海城市,也是中国、日本、韩国大气污染相互传输影响的重要通道.虽然威海市大气质量已连续4年达标,但其污染仍时有反弹.2019年1-2月威海市大气N02和PM2.5浓度反弹率分别达48.5％和35.O％,明显高于山东省内陆地区和京津冀地区平均水平.通过对同期空气质量例行监测数据和气象资料统计分析...     

大连海域溢油应急预报信息系统及其应用

在国外溢油应争信息系统基础上针对大连海域的特点研究开发了先进实用的“大连海域溢油模拟信息系统”，综合了三维溢油扩散模型、应急反应模型、以及电子海图、地理信息系统（GIS）、数据库等技术。不但能够快速准确地预测模拟并可视化显示海上溢油的漂移扩散、性质变化，还可以同时显示环境敏感区和应急人员设备分布等相关信息。经实际益油案例应用表明，系统的预测模拟结果与现场实验情况完全相符，可用效地提高对海上溢油污染事故的应急决策效率。     

用气流输送轨迹分析上海,重庆,贵阳的酸雨特点及其比较

用降雨时的气流输送轨迹,分析了上海、重庆和贵阳三地的酸雨特点和成因。研究表明,重庆和贵阳的酸雨,主要是受局地污染源的影响,远距离外来污染影响不大;但贵阳在静止锋天气时的酸雨,可能也受远处输送来的外来污染的影响。上海地区的酸雨,除受局地污染源的影响外,还受远处外来污染的影响。     

The influence of forest fires on CO, HCN, C2H6, and C2H2 over northern Japan measured by infrared solar spectroscopy

Total column abundances of CO, HCN, C₂H₆, and C₂H₂ have been retrieved from infrared solar spectra observed at Moshiri (44.4°N) and Rikubetsu (43.5°N) in northern Japan from 1997 to 2005. The spectra were recorded with high spectral resolution ground-based Fourier transform infrared (FTIR) spectrometers and total column abundances were calculated by SFIT1 version 1.09e. Deviations of these species relative to their seasonal mean values (ΔCO, ΔHCN, ΔC₂H₆, and ΔC₂H₂) were derived, which showed short-time enhancements in 1998, 2002, and 2003. Good correlations among ΔCO, ΔHCN, ΔC₂H₆, and ΔC₂H₂ in a few months of each year were seen. Since the number of forest fires in Siberia had large enhancements in 1998, 2002, and 2003, trajectory analyses were performed in order to assess the influence of forest fires and it was confirmed that air masses passing over the location of burning points in Siberia reached Moshiri and Rikubetsu. This paper shows that enhancements of these species were driven by biomass burning in Siberia.     

帕米尔高原东部PM10输送路径及潜在源分析

基于HYSPLIT后向轨迹模式和NCEP的GDAS数据（2019年3月~2020年2月）,对抵达帕米尔高原东部的48h后向气团轨迹按季节聚类,其PM₁₀和PM_2.5年均值分别为（29.4±16.4）,（9.3±5.1）μg/m³,大气颗粒物以PM₁₀为主,结合同期PM₁₀浓度数据,分析不同路径对帕米尔高原东部PM₁₀聚集的贡献,并利用潜在源贡献因子法（PSCF）和浓度权重轨迹法（CWT）,揭示研究期间帕米尔高原东部不同季节PM₁₀的潜在源分布及其贡献水平.结果表明：帕米尔高原东部PM₁₀输送路径的季节特征明显,春季来自中亚的西风气流对应PM₁₀高值,夏季来自中国新疆西部的气流也对应较高PM₁₀值,秋季各轨迹对应PM₁₀值相当,冬季来自南亚方向气流对应PM₁₀高值.PM₁₀春季贡献源区主要位于中国新疆西部、阿富汗东北部、巴基斯坦东北部、塔吉克斯坦中部及东部地区,夏季主要位于中国新疆西部喀什与和田北部地区,秋季主要位于土库曼斯坦东部、乌兹别克斯坦东南部、巴基斯坦北部、阿富汗北部与塔吉克斯坦南部接壤地区,冬季主要位于巴基斯坦东北部、印度北部以及阿富汗北部.     

Temporal variations and source apportionment of volatile organic compounds at an urban site in Shijiazhuang, China

Shijiazhuang, the city with the worst air quality in China, is suffering from severe ozone pollution in summer. As the key precursors of ozone generation, it is necessary to control the Volatile Organic Compounds (VOCs) pollution. To have a better understanding of the pollution status and source contribution, the concentrations of 117 ambient VOCs were analyzed from April to August 2018 in an urban site in Shijiazhuang. Results showed that the monthly average concentration of total VOCs was 66.27 ppbv, in which, the oxygenated VOCs (37.89%), alkanes (33.89%), and halogenated hydrocarbons (13.31%) were the main composite on. Eight major sources were identified using Positive Matrix Factorization modeling with an accurate VOCs emission inventory as inter-complementary methods revealed that the petrochemical industry (26.24%), other industrial sources (15.19%), and traffic source (12.24%) were the major sources for ambient VOCs in Shijiazhuang. The spatial distributions of major industrial activities emissions were identified by using geographic information statistics system, which illustrated the VOCs was mainly from the north and southeast of Shijiazhuang. The inverse trajectory analysis using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and Potential Source Contribution Function (PSCF) clearly demonstrated the features of pollutant transport to Shijiazhuang. These findings can provide references for local governments regarding control strategies to reduce VOCs emissions.     

川南自贡市大气颗粒物污染特征及传输路径与潜在源分析

川南自贡市大气颗粒物污染比较严重, 2015～2018年PM_(10)和PM_(2.5)平均浓度分别为(95.42±9.53)μg·m~(-3)和(65.95±6.98)μg·m~(-3),并有明显的下降趋势,冬季PM_(10)和PM_(2.5)浓度远高于其它季节, 1月平均浓度最高,分别为(138.08±52.29)μg·m~(-3)和(108.50±18.05)μg·m~(-3),夏季平均浓度最低.PM_(2.5)与PM_(10)的平均比值为69.12%,冬季比值约为夏季的1.17倍,空气污染以PM_(2.5)为主.采用拉格朗日混合单粒子轨迹模型(HYSPLIT)和全球资料同化系统的GDAS气象数据,对自贡市细颗粒物(PM_(2.5))浓度和逐日72 h后向轨迹进行计算和聚类研究,利用潜在源贡献分析法(PSCF)和浓度权重轨迹分析法(CWT),探讨不同季节影响自贡市PM_(2.5)浓度的潜在源区以及不同源区的污染贡献.结果表明,自贡市近地面四季多受东南风、偏西风和西北风控制,高浓度PM_(2.5)多出现在0～2 m·s~(-1)的低风速区;不同季节、不同输送路径对自贡PM_(2.5)污染影响的差异显著,春季主要受到来自偏西和偏北方向短距离输送气流的影响,夏季污染轨迹主要来自短距离输送的东南气流,秋季主要受来自资阳,经遂宁、重庆和内江的短距离输送气流的影响,冬季除受到资阳、遂宁和内江等周边城市的影响外,还受到来自西藏中部的远距离输送气流影响;除夏季外,自贡市潜在源区主要位于重庆西部与川南交界区域,冬季的主要贡献区范围最广、贡献程度最大,夏季潜在源区范围最小且贡献程度最弱.     

长江三角洲地区大气污染过程分析

针对2015年和2016年12月2个月的4次污染过程,利用中分辨率成像光谱仪（MODIS）Terra卫星的气溶胶光学厚度（AOD）,Angstrom波长指数（AE）气溶胶数据,并结合PM_2.5和PM₁₀的浓度以及比值变化分析,发现以PM_2.5为代表的人为因素产生的细颗粒物是造成研究地区污染发生的重要因素.并且利用MODIS火点数据以及美国海军气溶胶分析与预测系统（NAAPS）模拟分析污染物成分,发现2015年12月12~16日和19~27日2次污染都以人为因素产生的细粒子污染物为主,沙尘以及生物质燃烧产生的烟粒对研究地区影响较小.2016年12月6~10日和15~18日2次污染过程产生的原因不同,利用潜在源贡献因子分析法（PSCF）分析发现6~10日污染天气的产生主要是由西北方向含有大量沙尘粒子气流以及南方生物质燃烧产生的大量烟粒共同输送到研究地区,加之研究地区大量人为污染细粒子的产生,导致了此次混合型污染天气发生.15~18日污染过程与2015年2次污染过程相似,主要原因都在于人为因素产生的细颗粒污染物的影响,沙尘以及烟粒对污染过程起到了加剧的作用.     

ASSESSMENT OF POTENTIAL ATMOSPHERIC TRANSPORT AND DEPOSITION PATTERNS DUE TO RUSSIAN PACIFIC FLEET OPERATIONS

A probabilistic analysis of atmospheric transport and deposition patterns from two nuclear risk sites-Kamchatka and Vladivostok-situated in the Russian Far East to countries and geographical regions of interest (Japan, China, North and South Koreas, territories of the Russian Far East, State of Alaska, and Aleutian Chain Islands, US) was performed. The main questions addressed were the following: Which geographical territories are at the highest risk from hypothetical releases at these sites? What are the probabilities for radionuclide atmospheric transport and deposition on different neighboring countries in case of accidents at the sites? For analysis, several research tools developed within the Arctic Risk Project were applied: (1) isentropic trajectory model to calculate a multiyear dataset of 5-day forward trajectories that originated over the site locations at various altitudes; (2) DERMA long-range transport model to simulate 5-day atmospheric transport, dispersion, and deposition of 137Cs for 1-day release (at the rate of 10(10) Bq/s); and (3) a set of statistical methods (including exploratory, cluster, and probability fields analyses) for evaluation of trajectory and dispersion modeling results. The possible impact (on annual, seasonal, and monthly basis) of selected risk sites on neighboring geographical regions is evaluated using a set of various indicators. For trajectory modeling, the indicators examined are: (1) atmospheric transport pathways, (2) airflow probability fields, (3) fast transport probability fields, (4) maximum possible impact zone, (5) maximum reaching distance, and (6) typical transport time fields. For dispersion modeling, the indicators examined are: (1) time integrated air concentration, (2) dry deposition, and (3) wet deposition. It was found for both sites that within the boundary layer the westerly flows are dominant throughout the year (more than 60% of the time), increasing with altitude of free troposphere up to 85% of the time. For the Kamchatka site, the US regions are at the highest risk with the average times of atmospheric transport ranging from 3 to 5.1 days and depositions of 10(-1) Bq/m2 and lower. For the Vladivostok site, the northern China and Japan regions are at the highest risk with the average times of atmospheric transport of 0.5 and 1.6 days, respectively, and depositions ranging from 10(0) to 10(+2) Bq/m2. The areas of maximum potentially impacted zones are 30 x 10(4) km2 and 25 x 10(4) km2 for the Kamchatka and Vladivostok sites, respectively.