环境监测卫星Suomi NPP业务特性及生态环境监测应用

评价了2013年南京亚青会期间环境质量临时管控措施落实及绩效情况，分析了对改善空气质量产生的影响及存在的主要问题。结果表明：南京亚青会空气质量保障临时管控措施落实情况较好，空气质量保持良好。环比7月份，8月份减排SO2、NOx、颗粒物分别达到715，528与2 029 t。环比上年同期，2013年8月份SO2、NO2、PM10与PM2.5浓度分别下降22.2%，26.8%，18%与11.6%。企业停、限产优势在于能协同控制多种污染物，但成本较高，操作难度大；工地停工控制一次颗粒物非常有效，且易于操作。最后总结了亚青会保障存在的问题及成功经验，并提出青奥会空气质量保障对策建议。     

南京亚青会环境空气质量状况及原因分析

利用南京市空气质量监测结果，对2013年8月及亚青会期间空气质量状况进行评价与分析，并结合采取的临时管控措施及气象条件状况，分析空气质量变化的相关原因。结果表明，8月份南京市空气质量均达到良的等级，亚青会期间空气质量进一步改善，多项污染物浓度达到一级标准，且同比上年明显下降，这一方面与针对工业点源、机动车流动源及扬尘面源采取了临时管控措施，一定程度降低污染排放有关；另一方面与亚青会期间的气象条件有利于污染物扩散有关。     

南京亚青会环境空气质量状况及原因分析

利用南京市空气质量监测结果，对2013年8月及亚青会期间空气质量状况进行评价与分析，并结合采取的临时管控措施及气象条件状况，分析空气质量变化的相关原因。结果表明，8月份南京市空气质量均达到良的等级，亚青会期间空气质量进一步改善，多项污染物浓度达到一级标准，且同比上年明显下降，这一方面与针对工业点源、机动车流动源及扬尘面源采取了临时管控措施，一定程度降低污染排放有关；另一方面与亚青会期间的气象条件有利于污染物扩散有关。     

基于在线监测数据的青奥会废气重点污染源临时管控效果评估

简述了南京市废气重点污染源在线监测系统的组成和工作原理。根据2014年南京青奥会废气重点污染源环境临时管控要求,利用在线监控点位对7月份(青奥会前)和8月份(青奥会期间)重点废气污染源在线监测数据进行了统计分析。结果表明,青奥会期间南京市管控废气重点污染源的SO2和NOX排放量虽有个别企业出现增加,但整体排放量均有所降低,环境空气中SO2和NOX的平均值也有所降低,基本达到了临时管控要求。     

济南市空气污染现状及控制对策

利用2013年1—12月济南市大气监测数据,分析该市空气质量现状及时空分布特征,结果表明:2013年济南市空气主要污染物质量浓度均超过《环境空气质量标准》(GB 3095—2012)二级标准限值,空气污染严重时段为冬季采暖期,颗粒物污染严重区域为该市西部和西北部地区,SO2、NO2污染严重区为中心城区,并从点源、面源和移动源3个方面提出相应的污染防治对策。在SO2、NOx和工业烟粉尘分别减排22.5%、18.2%和31.4%的条件下,运用Models-3/CMAQ模型模拟计算得出:2015年1月和7月,济南市空气中SO2、NO2、PM10和PM2.5的质量浓度与2010年同期相比将分别降低23.9%和29.7%、11.4%和15.9%、21.9%和32.6%、13.5%和26.9%,空气质量得到明显改善。     

遂宁市2013年大气污染特征及成因

根据遂宁市近年的环境空气监测数据,系统研究了2013年大气污染特征和2007—2013年的变化趋势,分析了颗粒物的组成和主要来源,并与周边地区大气环境监测结果进行了横向比较。研究结果表明,2013年遂宁市环境空气质量达标率为88.1%,大气中SO2、NO2和PM10的年均质量浓度分别为31、30、94μg/m3,空气质量达到二级标准,但劣于往年水平,大气中首要污染物是PM10,夏季和秋季的空气质量明显优于冬季和春季;遂宁市空气质量的变化趋势与周边地区一致,呈现出一定的区域性污染特征,但明显优于周边地区;进一步从5个方面阐述了遂宁市2013年空气质量下降的原因;根据遂宁市大气污染现状,提出了大气防控措施和建议。     

2017年厦门金砖会晤期间PM2.5的化学特征及来源

为了探讨厦门金砖会晤期间的排放控制措施以及天气形势对大气颗粒物污染特征的影响,于2017年8月10日至9月10日对厦门气态污染物、细颗粒物(PM2.5)中的水溶性离子以及有机碳(OC)、元素碳(EC)等主要化学成分开展了高时间分辨率的在线监测。根据空气质量管控措施和天气形势将研究期分为6个阶段。管控前、管控期Ⅰ(非台风)和管控期Ⅱ(非台风) PM2.5质量浓度分别为(33. 12±9. 48)、(30. 30±17. 00)、(16. 01±4. 71)μg/m^3。管控期Ⅰ(台风)和管控期Ⅱ(台风) PM2.5质量浓度分别为(12. 40±3. 73)、(12. 45±3. 28)μg/m^3。结果表明:管控期Ⅰ(非台风)阶段受静稳天气的影响,管控效果削弱,PM2.5质量浓度下降幅度小;台风对颗粒物质量浓度下降的影响比管控更显著。管控初期,PM2.5中二次无机离子的质量浓度下降明显;台风对碳质组分质量浓度的影响不如无机组分显著。PMF源解析结果表明,二次无机源是PM2.5主要来源,随着管控措施的实行,扬尘源的贡献从21%降低到6%,而机动车源的贡献降幅不明显。台风期间SO4^2-、NO3^-、SO2、NO2以及硫酸盐氧化比值(SOR)均明显低于非台风期间,氮氧化比值(NOR)反而升高。台风和非台风期间NOR的日变化特征一致,NOR与阳离子的相关性分析结果表明,台风或高风速海风期间NOR与Na^+呈现很强的正相关性,说明海盐粒子可促进NO2非均相反应生成NO3-。     

南京及周边区域亚青期间大气监控预警走航观测研究

2013年8月,为了解亚青会期间南京及周边地区大气污染物的来源、时空分布和输送规律,江苏省环境监测中心联合中科院大气物理所等15家单位,开展了为期一个月的夏季联合观测,监测区域覆盖江苏沿江8市以及安徽部分地区。该次联合观测,江苏首次利用空气质量数值预报模式指导开展走航观测,实现了动静、水平与垂直相结合的立体式巡航观测,并初步揭示了现阶段江苏省大气污染主要特征,观测结果直接服务于亚青空气质量会商,为保障南京市空气质量提供技术支撑,同时为2014青奥会空气质量保障积累经验。     

大同市大气颗粒物浓度与水溶性离子季度分布特征

为研究大同市大气颗粒物质量浓度与水溶性离子组成特征,于2013年2、7、9、12月,分别对大同市及其对照点庞泉沟国家大气背景点进行了PM2.5及PM10的采样,通过超声萃取-IC法测定了样品中的9种水溶性离子,结果表明,大同市大气颗粒物污染1、4季度重于2、3季度,PM2.5季度均值全年均未超标,PM10仅第1季度超标1.4倍,污染状况总体良好,PM2.5与PM10相关系数R为0.75,说明大同市颗粒物污染有较为相近的来源,且不同季节均以粗颗粒物为主;大同市PM2.5中水溶性离子浓度分布为SO2-4、NO-3、NH+4Cl-、Ca2+K+、Na+F-、Mg2+,PM10中Ca2+浓度仅次于SO2-4、NO-3,控制扬尘将有效降低PM10的浓度;PM2.5及PM10中的9种水溶性离子在不同季度的浓度与颗粒物浓度分布规律类似,1、4季度较高,2、3季度较低;由阴阳离子平衡计算结果可知,相关性方程的斜率K为1.045,表明大同市大气颗粒物中阳离子相对亏损,大气细粒子组分偏酸性。NO-3与SO2-4浓度比值均小于1,大同市以硫酸型污染为主,大气中的SO2-4主要来源于人类活动排放。     

南京青奥会空气质量保障联合观测分析研究

2014年8月,为做好南京青奥会空气质量保障工作,江苏省环境监测中心联合中科院大气物理所、南京大学等36家单位,开展了为期一个月的空气质量保障联合观测,共获取监测数据5万多个,巡航观测里程超9 000 km,编制预报及分析报告87份,空气质量预报准确率达80%。结果表明,强力管控措施的实施,对缓解空气污染效果显著;通过联合团队观测方式,集中了产、学、研、用的技术优势和科研力量,带动了全省空气质量监测与分析能力的整体提升,为青奥会空气质量保障工作提供了强有力的技术支撑。     

吐鲁番市大气污染趋势及防治措施初探

通过对吐鲁番市城市环境质量三项大气主要污染物变化趋势进行调查分析，结果表明：吐鲁番市环境空气质量呈恶化趋势，大气污染物中PM10浓度呈上升趋势，SO 2呈略微上升趋势，NO2无显著变化。 PM10浓度在冬季采暖期和春秋季（4月）较高，为防治吐鲁番市空气质量变劣，急需采取积极有效的预防措施，切实保护好吐鲁番市人民赖以生存的空气环境。     

Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region.     

2015—2017年江苏省秋、冬季空气质量状况

采用2015—2017年秋、冬季江苏省环境空气质量监测数据,从空气质量优良(达标)率、首要污染物、主要污染物浓度分析空气质量现状及特点。结果表明,江苏省秋、冬季空气质量优良(达标)率在60%左右,其中沿海地区空气质量达标率最高(71.1%),西北地区达标率最差(52.2%)。污染日的首要污染物主要为PM 2.5,占比高达91.5%。ρ(PM2.5)/ρ(PM 10)存在地区差异,江苏西北地区扬尘源贡献较大,江苏南部地区的二次颗粒物贡献更明显。ρ(NO2)/ρ(SO2)逐年持续升高,表明大气污染类型从燃煤性污染转变为复合型污染。     

乌鲁木齐市采暖季空气质量变化趋势分析

为了定量评价乌鲁木齐市采暖季空气污染近五年的治理成效，给环境治理决策提供科学依据，运用回归分析方法，对乌鲁木齐市采暖季空气质量的浓度、级别和变化规律进行回归分析。分析结果表明，PM10、SO2、NO2三项污染物的浓度都有所下降，空气质量级别的污染天数呈现明显的月变化规律。乌鲁木齐市采暖季空气的重污染状况有所遏制，但SO2污染凸现，在下一步的治理工作中，加强尘污染治理的同时要加大对SO2的治理力度。     

Determination of O3, NO2, SO2, CO and PM10 measured in Belgrade urban area

O(3), NO(2), SO(2), CO and PM(10) concentrations, simultaneously determined for the first time in Belgrade urban area in the autumnal period of 2005, are presented. The obtained results display similar behaviour of SO(2), NO(2), CO, PM(10) opposite from that of O(3). The weekend effect was also investigated showing diminution of average daily concentrations of SO(2), NO(2), PM(10) and CO for 72, 40, 37 and 42% respectively, and increase of the average daily concentration of O(3) for 56%. Influence of meteorological conditions on observed concentration levels was studied, too. The observed influence of wind speed on the O(3) nightly concentration levels was analyzed pointing to the phenomena of O(3) transport during episodic measurements. To make an identification of possible pollution sources and analyse the influence of meteorological parameters on pollution levels, air back trajectories for high level concentrations episodes were calculated and analysed. A multivariate receptor modelling (Principal Component Analysis, Cluster Analysis) has been applied to a set of data in order to determine the contribution of different sources. It was found that the main principal components, extracted from the air pollution data, were related to gasoline combustion, oil combustion and ozone transport.     

Short-term variation in air quality associated with firework events: a case study

The effect of fireworks on air quality was assessed from the ambient concentrations of various air pollutants (SO2, NO2, PM10 and TSP) during Diwali festival in Hisar city (India), in November 1999. The extensive use of fireworks was found to be related to short-term variation in air quality. During the festival the concentration of SO2 was observed to be increased approximately 10-fold at few sites, whereas the concentrations of NO2, PM10 and TSP increased 2-3 times, compared to the data collected on a typical winter day in December 1999. The maximum NO2 concentration was observed a day after the festival. The diurnal pattern of the above pollutants showed a slight increase in the night. The levels of these pollutants observed during Diwali were found to be moderately high, which can be associated with serious health impacts.     

珠三角区域空气质量预报方法及预报效果评估

介绍了珠三角区域空气质量预报的"六步法"流程,并对2015年空气质量等级和首要污染物预报准确率进行评估研究。结果表明,2015年珠三角区域空气质量以优良为主,24 h等级预报准确率1月最高2月最低,平均准确率为87.6%;出现的首要污染物种类包括PM2.5,PM10,O3-8 h和NO2,预报准确率9月最高3月最低,平均准确率为72.7%。     

Air Quality and Monitoring Strategy in the Helsinki Metropolitan Area, Finland

The Helsinki Metropolitan Area Council (YTV) is responsible for air quality monitoring in the Helsinki area. Air quality has been monitored periodically since the late 1950s. An automatic SO2 monitoring network was constructed in 1975 and TSP measurements were added in 1978. Since then the network has been expanded and currently five automatic multicomponent stations form the basis of the network monitoring SO2, NO, NO2, CO, PM10 and O3 concentrations. Manual TSP and PM10 measurements are also conducted. Mobile monitoring units are also being used as well as special measurement campaigns. The effects of air pollution on nature are studied in bioindicator monitoring. An air quality index is used in order to inform the public of the current air quality situation. Changes in air quality are reflected in monitoring strategy. SO2 concentrations have decreased in the past two decades. Annual averages in 1995 were at or below 5 µg/m3. Traffic is the major source for pollutants even though catalytic converters have lowered traffic emissions somewhat. The highest annual average NO2 concentration at an urban site was 49 µg/m3 in 1995, and there has been no clear change in NO2 levels. There has been a decreasing trend in CO concentrations. Maximum annual TSP and PM10 averages in 1995 were 92 and 32 µg/m3, respectively. The highest average lead concentration was 0.01 µg/m3. Elevated concentrations are experienced from time to time. During the spring daily TSP and PM10 concentrations can go up to around 300 and 150 µg/m3, respectively. This is caused by resuspension mainly due to street sanding. Also a major winter NO2 episode occurred in December 1995. The highest hourly NO2 concentrations reached 400 µg/m3.