大同地区典型沙尘天气过程近地层气象要素演变特征的对比分析

利用2009年3月-2010年3月大同国家基准气候站20m气象梯度塔的风向、风速、气温、相对湿度的观测资料及PM10质量浓度数据、气溶胶散射系数数据,分析大同地区典型沙尘天气过程近地层气象要素演变特征。结果表明,风速在沙尘暴、扬沙的发生、发展过程中均较大,浮尘较小。气温在沙尘暴期间受冷空气的影响迅速减小,而在扬沙和浮尘天气条件下温度的变化主要取决于长短波辐射的强弱和沙尘气溶胶的辐射强迫。相对湿度在沙尘暴期间基本上呈递增态势,结束后比发生前相对湿度增大,在扬沙和浮尘天气条件下,相对湿度与温度完全呈现出反相关关系,且相对湿度均较小。PM10质量浓度在沙尘暴、扬沙、浮尘天气条件下依次递减。沙尘暴期间气溶胶散射系数明显增大。     

2010年沙尘天气对巴彦浩特空气质量的影响

利用巴彦浩特2010年1月至2011年2月PM10、SO2、NO2的逐日监测数据和同一时期气象观测资料,分析巴彦浩特空气污染物特征及PM10浓度与沙尘天气之间的关系。分析结果表明:2010年春、夏、秋三季巴彦浩特的主要污染物是PM10,冬季主要污染物是SO2;沙尘天气是造成巴彦浩特PM10浓度变化的最重要因素;影响巴彦浩特空气质量的沙尘主要来源于其西北方向和西北偏北方向。建议有关部门在巴彦浩特西北地区搞好生态保护与建设,以减轻沙尘天气对巴彦浩特地区空气质量的影响。     

2007和2008年夏季北京奥运馆大气PM10与PM2.5质量浓度变化特征

为了监测北京奥运主场馆附近大气颗粒物的污染状况以及评估奥运污染源减排措施对北京大气颗粒物质量浓度变化的影响,利用颗粒物在线监测仪器TEOM于2007年和2008年夏季,在奥运主场馆附近的中国科学院遥感应用研究所办公楼楼顶对大气颗粒物PM₁₀和PM_2.5进行了连续同步观测。结果表明,2007年夏季监测点附近大气PM₁₀与PM_2.5质量浓度的平均值分别为153.9和71.2μg·m^-3,而2008年夏季PM₁₀与PM_2.5质量浓度的平均值分别为85.2和52.8μg·m^-3。与奥运前一年同时段相比,奥运时段大气PM₁₀和PM_2.5的质量浓度分别下降44.5%和25.1%。对比分析奥运前后的2次典型污染过程发现,空气相对湿度的增加和偏南气流输送的共同影响易造成大气颗粒物的累积增长,而降雨的湿清除作用和偏北气流则会使大气颗粒物浓度迅速降低。在相近的气象条件下,奥运前后的污染过程中,大气细粒子的日均增长速率分别为25.1和13.9μg·m^-3·d^-1,而大气粗粒子的日均增长速率分别为20.8和2.2μg·m^-3·d^-1,奥运时段污染累积过程中大气粗、细粒子的增长速率分别显著低于和略低于奥运前同时段污染过程中颗粒物的增长速率。污染源减排措施的实施是奥运期间大气颗粒物质量浓度降低的主要原因,从控制效果来看,奥运期间实施的污染源减排措施对大气粗粒子的控制效果明显好于大气细粒子。     

大同基准站PM10监测项目简析

本文首先介绍了PM10的基本概念以及对人体的危害和国际社会对其的重视程度,简单阐述了大同基准站PM10监测设备的基本原理,详细分析了PM10监测扬沙和烟尘等视程障碍天气的能力,用数据曲线清晰的展示出了PM10值在沙尘天气下的变化。同时详细分析了PM10值变化与能见度值的相互关系,通过分析提出了在一定的天气下可以参考PM10的值来判断能见度的观点。本文总结了PM10值与沙尘天气和能见度的关系。     

Vertical Observations and Analysis of PM2.5, O3, and NOx at Beijing and Tianjin from Towers during Summer and Autumn 2006

During the period between 18 August and 22 September 2006, an ultraviolet photometric O3 analyzer, a NO-NO2-NOx chemiluminescence analyzer, and a quartz micro-oscillating-scale particle concentration analyzer were simultaneously used for monitoring at three different heights each at Beijing (325-m tower) and Tianjin (255-m tower). These towers belong to the Institute of Atmospheric Physics (IAP) of the Chinese Academy of Sciences (CAS) and to the Tianjin Municipal Meteorological Bureau, respectively. These measurements were used to continuously measure the atmospheric O3 and NOx volume-by-volume concentrations and the PM2.5 mass concentration within a vertical gradient. When combined with meteorological data and information on the variation of vertical characteristics of the various atmospheric pollutants in the two cities, analysis shows that these two cities were seriously polluted by both PM2.5 and O3 during summer and autumn. The highest daily-average concentrations of PM2.5 near the ground in Beijing and Tianjin reached 183 μg m-3 and 165 μg m-3, respectively, while the O3 concentrations reached 52 ppb and 77 ppb, and NOx concentrations reached 48 ppb and 62 ppb for these two cities, respectively. The variations in the daily-average concentrations of PM2.5 between Beijing and Tianjin were demonstrated to be consistent over time. The concentrations of PM2.5 measured in Beijing were found to be higher than those in Tianjin. However, the overall O3 concentrations near the ground in Tianjin were higher than in Beijing. NOx concentrations in Tianjin were consistently lower than in Beijing. It was also found that PM2.5 pollution in Beijings atmosphere may also be affected by the pollutants originating in and delivered from Tianjin, and that Ti     

脱硝技术与天然气应用情景下京津冀地区空气质量模拟评估

针对京津冀地区主要大气污染物NOx（氮氧化物）和PM2.5（大气中粒径小于或等于2.5μm的颗粒物）,应用柴油车尾气净化技术及中小锅炉烟气脱硝技术,并根据2015年和2030年我国能源规划,设计3种技术应用情景,采用WRF-CAMx耦合模式,对京津冀地区大气中NOx和PM2.5进行了应用情景模拟。结果表明,单独应用柴油车尾气净化技术后（方案1）,北京、天津地区大气中的NOx浓度降低幅度达20%,河北地区降低5%;PM2.5的浓度降低幅度约10%;应用柴油车尾气净化技术和2015年能源规划情景（方案2）,京津冀地区大气中NOx和PM2.5浓度的降低幅度均超过20%;应用柴油车尾气净化技术和2030年能源规划情景（方案3）,该地区NOx浓度降低幅度与之相当,PM2.5浓度降低幅度超过30%。可见脱硝技术和清洁能源利用的有效性依赖于其应用比例。二次气粒转化的化学过程形成的硝酸盐、硫酸盐和铵盐对该地区空气中PM2.5浓度的贡献很大,冬、春、秋季硝酸盐最大贡献高达60%,夏、秋季硫酸盐最大贡献超过70%,铵盐四季最大贡献约25%。这说明PM2.5的主要前体物NOx、SO2、NH3、VOCs (Volatile Organic Compounds)、CO等均大幅度削减才能有效降低该地区空气中PM2.5浓度。     

Particle composition and size distributions in and around a deep-pit swine operation,Ames, IA

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. PM_2.5 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.     

Source identification of PM2.5 particles measured in Gwangju, Korea

The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM_2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM_2.5 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 PM_2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM_2.5 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 PM_2.5 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 PM_2.5 sources.Additionally, the impact of air mass pathways on the PM_2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM_2.5 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 PM_2.5 mass, respectively, whereas Asian dust contributed only 10.8% to the PM_2.5 mass during the AD event when the air mass passed over the Yellow Sea. The contribution of biomass burning to the PM_2.5 mass during the biomass burning (BB) event equaled 63.8%.     

Satellite and ground observations for large-scale air pollution transport in the Yellow Sea region

Large-scale air pollution transport (LSAPT) in the Yellow Sea region and their inflow onto the Korean Peninsula were observed through satellite images and ground measurements. LSAPT includes regional continental air-masses saturated with pollutants originating from China and subsequently landing on or passing through the Korean Peninsula. It is also possible to identify the distribution and transport patterns of LSAPT over the Yellow Sea. The ground concentrations for PM10, PM2.5 and CO measured at Cheongwon, located in the centre of south Korea, were compared with NOAA satellite images. Notably, the episodes observed of the LSAPT show a PM2.5 to PM10 ratio of 74% of the daily maximum concentrations. However, cases of duststorms were clearly distinguished by much higher PM10 concentrations and a ratio of 30% of PM2.5 to PM10 for daily maximum concentrations. For the episode on January 27, 2006, the inflow of a regionally polluted continental air-mass into the central and southwestern regions of the Korean Peninsula was observed sequentially at various ground observatories as well as by satellite. The north airflow dissipated the clouds over Mt. Halla on Jeju Island and further downwind, reducing air pollution and creating a von Kármán vortex.     

北京城区夏季污染建立、维持、消退的天气过程

利用北京城区污染观测站2006~2013年夏季可吸入颗粒物PM10逐日浓度检测资料,挑选所有PM10浓度大于150μg/m~3的个例,合成分析华北及北京地区风场变化情况,发现风速在污染当天变化不明显,南风与PM10的相关性普遍为正,污染当天各区南风增加较大,太行山一带甚至增长了5倍。南风异常可能会使河北、山东等地污染物向北京输送,造成北京大气污染。同时我们分析北京夏季空气污染时大气环流特征。在500 h Pa与200 h Pa,北京和内蒙古上空有显著的高压异常。在850 h Pa,环流场表现为东正西负的高度场异常,其中北京在正负异常分界线上。低层气压梯度异常会造成北京和以南地区南风异常。同时,我们发现北京污染天气伴随的高空环流异常具有准定常特征。在污染前4天,蒙古上空存在一个显著的高层高压异常。该高压异常增强并向南延伸,在污染当天控制北京和内蒙古。在污染消退期,该异常也逐渐消退。但在消退后第四天,北京和内蒙古上空依然受高压异常控制。这表明北京夏季污染和高空准定常环流异常有关。