广州南沙区O3浓度变化及其与气象因子的关系

利用广州南沙区气象探测基地2010年O3浓度和常规气象观测资料,分析了O3浓度变化特征及其气象因子的关系。结果表明,广州南沙区2010年O3浓度最高时均值的最大值出现在8月,超标时数最多的是9月;O3浓度日变化呈单峰型分布,O3浓度日变化最大的季节是秋季,其次为夏季、春季、冬季;O3浓度呈现秋季>春季>夏季>冬季的变化特征。气温、相对湿度、日照时数和云量与O3浓度相关系数大,是影响南沙O3浓度的主要气象因子。秋季O3浓度高,O3主要以局地光化学反应生成为主;春季、夏季和冬季O3主要以外来源的输送为主。气团后向轨迹分析表明南沙区秋季气团主要来自污染的大陆地区,春季、夏季和冬季气团主要是来自东南沿海附近或较为清洁的南海。     

基于地面和卫星监测的长沙市冬季灰霾污染特征及成因研究

为探究长沙市冬季灰霾污染情况,基于2014年1月21日至2月9日地面和卫星监测数据,应用混合单粒子拉格朗日综合轨迹(HYSPLIT)模式和统计方法研究了长沙市冬季灰霾污染特征、来源和成因。结果表明,长沙市整体污染相对较重,特别是北部部分地区污染非常严重,而南部则相对较轻。污染前期空气质量开始下降,出现轻度污染;中期空气质量已达到重度污染和严重污染程度,PM_(2.5)和PM_(10)最高值均接近800μg/m~3;后期空气质量好转。经气流轨迹聚类后共划分为3类气流:东北、北以及西南,分别占总气流轨迹数的48.8%、34.3%和16.9%。长沙市灰霾污染的潜在源区主要位于山东中南部、河北南部、湖北以及广东、广西和湖南交汇处。结合气象要素发现,污染期风速较小,相对湿度增加,温度和气压降低,进一步加剧污染物堆积。因此,为了改善长沙市空气质量,不仅需对当地污染物排放进行控制,还需对污染物区域传输进行整合治理,实施长沙地区乃至跨区域大气联防联控策略。     

辽宁中部地区低能见度天气特征及与气象因素变化规律分析

利用1961—2010年辽宁中部地区16个气象站地面观测资料,采用趋势分析、不同标准期对比法和Mann-Kendall检验法,对辽宁中部地区因(轻)雾、霾引起的低能见度天气的时空分布特征及气象影响因子进行了分析。结果表明:辽宁中部地区低能见度日数整体呈增加趋势,且在2002年发生了突变,日数的增加主要发生在最近10年期间;低能见度天气逐月日数呈双峰双谷分布,夏季低能见度天气出现的最多,冬季次之,春季最少;低能见度天气的空间分布呈"两高两低"形势,与第1个标准气候期相比,最近30年标准气候期年平均低能见度天气日数增多了14 d;低能见度天气日数随着相对湿度的增大出现几率呈先增大后减小趋势;夏半年低能见度天气日数与降水量变化趋势一致,冬半年则相反;日均风速≤4.0m·s~(-1)、出现负变压时,对低能见度天气的形成更为有利。     

成都市大气颗粒物污染特征及与气象因子的关联性分析

利用成都市2013年6月至2014年5月的PM10和PM2.5浓度监测数据,分析大气颗粒物污染特征,并探讨其与气温、相对湿度、降雨、风向、风速等气象因子的关联性。结果表明:成都市大气PM2.5污染较严重;PM10和PM2.5浓度及超标率均表现为冬季秋季春季夏季,秋季和冬季为大气颗粒物污染高发期;PM2.5对PM10贡献显著;气温超过10℃时,PM10和PM2.5最高浓度大体随气温升高而降低;相对湿度为40%~80%时,PM10和PM2.5浓度随相对湿度增加而升高;相对湿度超过80%时,易发生降雨,PM10和PM2.5浓度降低;降雨对PM10的清除量高于PM2.5,但降雨后PM10和PM2.5浓度较快回升;PM10和PM2.5浓度在偏西风下高于其他风向;PM10主要受局地源影响,而PM2.5主要受西北方向上的外来源影响。     

辽宁省区域性空气污染的天气分型

应用2003-2004年主要污染物浓度和气象资料,对辽宁省全年的PM10产生的区域性3级空气污染进行环流分型,按污染源划分为冬季煤烟型、春季沙尘型和夏秋大雾型.其中冬季煤烟型又分为长白山高压地形槽型、高压内部均压场型、东北高压脊,西部倒槽型、蒙古高压前均压场、蒙古低压前均压场、高压内部小范围均压场型6个型;春季沙尘型分为东北低压型、南大风型和干冷锋北大风型;夏秋大雾型分为低压槽型和低压前均压场.上述类型几乎概括了近两年PM10 3级污染的所有个例,为大气环境质量预报、总量控制等提供依据.     

杭州市区大气能见度变化趋势及其与主要污染物相关性分析

利用2004-2006年地面气象观测资料和同期环境空气质量自动监测数据,分析了杭州市区大气能见度变化趋势及其与主要污染物的相关性.结果表明,杭州市区能见度的日分布特征为14时最好,8时最差;季节变化特征为夏季>春季>秋季>冬季,全年仅7月能见度超过10 km;SO2、NO2、PM10浓度均随能见度增高而逐渐降低;影响能见度的首要因子为相对湿度和PM2.5,能见度与PM2.5浓度具有较好的相关性.     

天津市大气能见度与空气污染物关系分析及控制措施

利用天津市1990—2004年大气能见度观测资料及天津市2002—2004年空气污染物监测数据,统计分析了天津市大气能见度变化特征及其与空气污染物的关系。结果表明,天津市20世纪90年代大气能见度处于波动下降趋势,2000—2003年大气能见度整体水平有所改善,到2004年空气质量迅速提高。统计数据说明,在非采暖季的春季,天津市大气能见度的下降与PM10浓度有较大相关性;在夏季,与相对湿度有较大相关性;在采暖季(冬季),与SO2和NOX等空气污染物浓度有密切关系。同时,提出改善城市大气能见度的4个措施:(1)制定长期的大气能见度控制策略;(2)合理改善能源结构;(3)加强城市裸露土地的治理;(4)城市交通采用清洁能源。     

天津冬季PM_(2.5)中水溶性无机离子污染特征研究

2015年12月3—21日对天津冬季 PM2.5进行了采样分析,重点分析了 Na~+、Mg~(2+)、NH_4~+ 、Ca~(2+)、K~+、Cl~-、SO_4~(2-) 、NO_3~-8种水溶性无机离子,结合风速、相对湿度、温度等气象资料,并利用主成分分析对水溶性无机离子来源进行了解析。结果表明,风速小、气温高和相对湿度大的天气条件以及冬季燃煤的人为原因是引起霾天的重要原因。采样期间PM_(2.5)平均质量浓度为104.22μg/m~3。霾天中,轻微霾天、轻度霾天、中度霾天、重度霾天的PM_(2.5)中总离子平均质量浓度分别为27.63、26.89、105.03、143.92μg/m~3,远高于非霾天的15.43μg/m~3。SO_4~(2-)是水溶性无机离子中含量最高的离子,约占总离子的1/3,SO_4~(2-)、NO_3~-、Cl~-和NH_4~+浓度之和占总离子的90%以上。随着霾程度加重,NH_4NO_3占比增加,(NH_4)_2SO_4占比减少。水溶性无机离子主要来源于海盐粒子、生物质燃烧、机动车尾气排放和燃煤等。     

北京市近12年空气污染变化特征及其与气象要素的相关性分析

以北京市近12年空气污染指数(API)为数据基础,首先分析了2001—2012年北京市API、污染等级、首要污染物的变化特征以及污染天数年度值、季度值、月值的变化特征;然后根据API转换得到PM10质量浓度,对其变化特征进行分析;最后采用相关系数法分析了北京市API、PM10质量浓度与气象因素的相关性。结果表明,北京市近12年空气污染天数有明显下降趋势,首要污染物主要为可吸入颗粒物;空气污染主要集中于春季,优良天气主要集中于夏季;PM10质量浓度年度最大值出现在2006年,季度最大、最小值分别出现在春、夏季,月值最大、最小值分别出现在3月和7月;气象因素与空气污染关系密切,气温、相对湿度、降雨量与污染天数和PM10质量浓度均呈显著负相关,而风速与污染天数和PM10质量浓度则呈显著正相关。     

基于MAX-DOAS的乌鲁木齐市NO_2时空变化

为研究乌鲁木齐市NO_2污染状况,了解其时空分布特征及其影响因素,基于多轴差分吸收光谱技术(MAXDOAS),利用2014年4月—2015年12月3个监测点和多次车载移动观测的数据,反演了乌鲁木齐对流层NO_2垂直柱浓度(VCD),并且结合气象和地形等因素进行了分析。结果表明:NO_2VCD由高到低的季节依次是冬季、春季、秋季和夏季,均值为10.84、7.78、5.98和3.56×1015molec·cm~(-2);由高到低的监测站依次是城区站、工业区站和郊区站,年均值为9.52、8.44和5.58×1015molec·cm~(-2);日变化上春冬两季呈U型,夏秋两季呈双峰型;NO_2空间分布由南到北呈明显的"两头低中间高",高值通常出现在市区高架桥附近;乌鲁木齐NO_2VCD与气象因子温度、风速、相对湿度、日照时数都有较好的相关性;乌鲁木齐夏季盛行西北风,顺势于地形利于市区污染物传输出去,冬季盛行东北风,而东面有博格达山阻挡致使风速较低,污染物滞留堆积浓度高。     

长沙地区雾霾特征及影响因子分析

根据长沙地区1970—2012年气象观测资料及环境监测数据,对近43年长沙雾霾特征及影响因子进行了分析。结果表明,长沙地区雾的年际变化具有显著的倒"U"型特征,霾整体上呈上升趋势;雾霾天气主要集中在秋冬季节,春夏季节较少;从空间分布来看,望城区(县)和宁乡县雾霾天气最多,浏阳市次之,长沙市区最少。在一次持续性雾霾天气过程中(10.2~10.12),相对湿度、PM2.5质量浓度与能见度呈现显著负相关,说明PM2.5质量浓度和相对湿度是雾霾天气形成的首要影响因子。     

Arctic haze and clouds observed by lidar during four winter seasons of 1993–1997, at Eureka,Canada

A Mie-scattering-polarized Haze Lidar was installed at Eureka, Canada (80°N, 86°W), in February 1993 and has been used to observe the arctic haze during winter seasons from 1993–94 to 1996–97. Although it is difficult to distinguish between the arctic haze and other scattering objects (mainly clouds) under the specific conditions, two methods were used to classify those objects into two groups. First the vertical profiles of the arctic haze and clouds were compared with meteorological data observed by a radiosonde, and the relations between the scattering and depolarization ratios and the meteorological data were investigated. Then, since the arctic haze had very stable layers, the time dependency of the correlation coefficient between the different vertical profiles for the arctic haze and clouds was investigated. After the scattering objects were classified into two groups (the arctic haze and the clouds), the scattering ratio, the depolarization ratio, and the occurrence probabilities of them were investigated statistically. The statistical results, from the observations over the last four winter seasons, indicate that the average values of the scattering and depolarization ratios of the arctic haze were respectively 1.27 and 1.34%. The average humidity over ice of the layer containing the arctic haze was 42±19% (cloud: 92±13%). The arctic haze was observed at altitudes less than 3 km frequently and at altitudes of 3–5 km occasionally.     

Causes of haze in the Columbia River Gorge

Visibility impairment in the Columbia River Gorge National Scenic Area is an area of concern. A field study conducted from July 2003 to February 2005 was followed by data analysis and receptor modeling to better understand the temporal and spatial patterns of haze and the sources contributing to the haze in the Columbia River Gorge in the states of Washington and Oregon. The nephelometer light scattering and surface meteorological data at eight sites along the gorge showed five distinct wind patterns, each with its characteristic diurnal and spatial patterns in light scattering by particles (bsp). In summer, winds were nearly always from west to east (upgorge) and showed decreasing bsp with distance into the gorge and a pronounced effect of the Portland, OR, metropolitan area on haze, especially in the western portions of the gorge. Winter often had winds from the east with very high levels of bsp, especially at the eastern gorge sites, with sources east of the gorge responsible for much of the haze. The major chemical components responsible for haze were organic carbon, sulfate, and nitrate. Positive matrix factorization (PMF) using chemically speciated Interagency Monitoring of Protected Visual Environments data indicated seven source factors in the western gorge and five factors in the eastern gorge. Organic mass is a large contributor to haze in the gorge in all seasons, with a peak in fall. The PMF analysis suggests that approximately half of the organic mass is biomass smoke, with mobile sources as the second largest contributor. PMF analysis showed nitrates (important in fall and winter) mainly attributed to a generic secondary nitrate factor, with the next largest contributor being oil combustion at Mt. Zion, WA and mobile sources at Wishram, WA. Sulfate is a significant contributor in all seasons, with peak sulfate concentrations in summer.     

Causes of Haze in the Columbia River Gorge

Abstract

Visibility impairment in the Columbia River Gorge National Scenic Area is an area of concern. A field study conducted from July 2003 to February 2005 was followed by data analysis and receptor modeling to better understand the temporal and spatial patterns of haze and the sources contributing to the haze in the Columbia River Gorge in the states of Washington and Oregon. The nephelometer light scattering and surface meteorological data at eight sites along the gorge showed five distinct wind patterns, each with its characteristic diurnal and spatial patterns in light scattering by particles (b_sp). In summer, winds were nearly always from west to east (upgorge) and showed decreasing b_sp with distance into the gorge and a pronounced effect of the Portland, OR, metropolitan area on haze, especially in the western portions of the gorge. Winter often had winds from the east with very high levels of b_sp, especially at the eastern gorge sites, with sources east of the gorge responsible for much of the haze. The major chemical components responsible for haze were organic carbon, sulfate, and nitrate. Positive matrix factorization (PMF) using chemically speciated Inter-agency Monitoring of Protected Visual Environments data indicated seven source factors in the western gorge and five factors in the eastern gorge. Organic mass is a large contributor to haze in the gorge in all seasons, with a peak in fall. The PMF analysis suggests that approximately half of the organic mass is biomass smoke, with mobile sources as the second largest contributor. PMF analysis showed nitrates (important in fall and winter) mainly attributed to a generic secondary nitrate factor, with the next largest contributor being oil combustion at Mt. Zion, WA and mobile sources at Wishram, WA. Sulfate is a significant contributor in all seasons, with peak sulfate concentrations in summer.     

Haze trends over the United States, 1980–1995

The patterns and trends of haze over the United States for the period of 1980–1995 are presented. Haze measurements are based on human visual range observations at 298 synoptic meteorological stations operated by the United States Weather Service. There was a significant (∼10%) decline in haziness over the 15-yr period. The reductions were evident throughout the eastern United States as well as over the hazy air basins of California. During the same period, in the eastern United States sulfur emissions also declined by about 10%. However, a causality for the reductions has not been established. This report is an update of an earlier survey of haze patterns and trends from 1950 to 1980.     

Modeling of potential power plant plume impacts on Dallas-Fort Worth visibility

During wintertime, haze episodes occur in the Dallas-Ft. Worth (DFW) urban area. Such episodes are characterized by substantial light scattering by particles and relatively low absorption, leading to so-called "white haze." The objective of this work was to assess whether reductions in the emissions of SO2 from specific coal-fired power plants located over 100 km from DFW could lead to a discernible change in the DFW white haze. To that end, the transport, dispersion, deposition, and chemistry of the plume of a major power plant were simulated using a reactive plume model (ROME). The realism of the plume model simulations was tested by comparing model calculations of plume concentrations with aircraft data of SF6 tracer concentrations and ozone concentrations. A second-order closure dispersion algorithm was shown to perform better than a first-order closure algorithm and the empirical Pasquill-Gifford-Turner algorithm. For plume impact assessment, three actual scenarios were simulated, two with clear-sky conditions and one with the presence of fog prior to the haze. The largest amount of sulfate formation was obtained for the fog episode. Therefore, a hypothetical scenario was constructed using the meteorological conditions of the fog episode with input data values adjusted to be more conducive to sulfate formation. The results of the simulations suggest that reductions in the power plant emissions lead to less than proportional reductions in sulfate concentrations in DFW for the fog scenario. Calculations of the associated effects on light scattering using Mie theory suggest that reduction in total (plume + ambient) light extinction of less than 13% would be obtained with a 44% reduction in emissions of SO2 from the modeled power plant.     

Air quality in Brunei Darussalam during the 1998 haze episode

Regional haze from biomass burning in SE Asia is a recurring air pollution phenomenon with a potential impact on the health of several hundred million people. Air quality data in Brunei Darussalam during the 1998 haze episode revealed that only particulate matter is a significant pollutant. The WHO guideline of 70 μg m⁻³ for PM₁₀ (24 h average) was exceeded on 54 days during the haze episode which lasted from 1 February to 30 April 1998. Concentrations of SO₂, NO₂, and O₃ were all below WHO guidelines and the 8 h guideline for CO was exceeded on only seven occasions. Average daily PM₁₀ concentrations were below 450 μg m⁻³ but concentrations greater than 600 μg m⁻³ persisted for several hours at a time and total exposure to such high concentrations could add up to several days over the course of a haze episode. Airborne particles exhibited diurnal variation, typically rising through the night to very high levels in the early morning and thereafter decreasing due largely to meteorological factors. The pollutant standards index (PSI), widely used to report urban air quality, may not be suitable for haze from forest fires as it does not take into account short-term exposure to extremely high particle concentrations of up to 1 mg m⁻³.     

Contributions to CO concentrations from biomass burning and traffic during haze episodes in Singapore

Prediction of ambient carbon monoxide (CO) due to haze in the presence of transportation sources at a busy expressway site in Singapore was made using street Canyon and Gaussian line source modules of a regional-scale Indic Airviro dispersion model for the haze episodes that occurred in the years 1994 and 1997. The fleet average emission factors for each vehicle category were estimated from US EPA MOBILE 5 A guidelines as a function of speed, vehicle deterioration rates and model years. One hour CO concentrations during the non-haze period for the year 1995 were first simulated and compared with measured readings to test the accuracy of the proposed approach. The calibrated model was then used to compute hourly CO values for the 1994 and 1997 haze episodes. The difference between the modeled CO values with and without haze provided CO contribution due to haze. An analysis of CO values estimated through modeling with experimental measurements made during haze periods confirmed this unique approach to establish concentration of CO due to haze in the presence of transportation sources.     

An anticyclonic point of view on low-level tropospheric long-range transport

Research on Arctic haze has provided an example when anticyclones may play a dominant role in carrying out low-level tropospheric long-range transport. This dominant role of anticyclones in transporting Arctic haze may be the result of the unique geographic and climatological situation existing during winter/spring in which both the huge Eurasian continent and the adjacent ice-covered Arctic Ocean tend to be regions where anticyclones form and exist over long periods of the winter and spring seasons. It is assumed that the seasonal variation of transport mechanisms provided by anticyclones is the primary cause for the seasonal variation of Arctic haze. Centers of anticyclones are the regions where air masses form and obtain their characteristics, both meteorological and chemical, due to the aerosols and gases released into the air. Transport within an air flow along the edges of quasi-stationary anticyclones will remain under stable atmospheric conditions, hence, dilution, lifting and removal of aerosols and gases will be less compared to a transport within the influence of a cyclonic pressure system. According to the concept of isentropic flow, anticyclones may dominate only low-level transport, whereas cyclones may be more important in controlling transport at upper tropospheric levels.     

Modeling of Potential Power Plant Plume Impacts on Dallas-Fort Worth Visibility

ABSTRACT

During wintertime, haze episodes occur in the Dallas-Ft. Worth (DFW) urban area. Such episodes are characterized by substantial light scattering by particles and relatively low absorption, leading to so-called “white haze.” The objective of this work was to assess whether reductions in the emissions of SO₂ from specific coal-fired power plants located over 100 km from DFW could lead to a discernible change in the DFW white haze. To that end, the transport, dispersion, deposition, and chemistry of the plume of a major power plant were simulated using a reactive plume model (ROME). The realism of the plume model simulations was tested by comparing model calculations of plume concentrations with aircraft data of SF₆ tracer concentrations and ozone concentrations. A second-order closure dispersion algorithm was shown to perform better than a first-order closure algorithm and the empirical Pasquill-Gifford-Turner algorithm. For plume impact assessment, three actual scenarios were simulated, two with clear-sky conditions and one with the presence of fog prior to the haze. The largest amount of sulfate formation was obtained for the fog episode. Therefore, a hypothetical scenario was constructed using the meteorological conditions of the fog episode with input data values adjusted to be more conducive to sulfate formation. The results of the simulations suggest that reductions in the power plant emissions lead to less than proportional reductions in sulfate concentrations in DFW for the fog scenario. Calculations of the associated effects on light scattering using Mie theory suggest that reduction in total (plume + ambient) light extinction of less than 13% would be obtained with a 44% reduction in emissions of SO₂ from the modeled power plant.