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.     

Indoor air pollution levels in public buildings in Thailand and exposure assessment

Levels of pollutants including PM2.5 and PM2.5 composition (black carbon and water soluble ions), SO(2), NO(2), CO, CO(2), and BTEX (benzene, toluene, ethylbenzene, xylene) were monitored for indoor and outdoor air at a university campus and a shopping center, both located in the Northern suburb of Bangkok. Sampling was done during December 2005-February 2006 on both weekdays and weekends. At the university, indoor monitoring was done in two different air conditioned classrooms which shows the I/O ratios for all pollutants to be below 0.5-0.8 during the weekends. However, on weekdays the ratios for CO(2) and most detected BTEX were above 1.0. The concept of classroom occupancy was defined using a function of the student number in a lecture hour and the number of lecture hours per day. Classroom 2, which had a higher occupancy than classroom 1, was characterized by higher concentrations of most pollutants. PM2.5 was an exception and was higher in classroom 1 (37 microg/m(3), weekdays) as compared to classroom 2 (26 microg/m(3), weekdays) which was likely linked to the dust resuspension from the carpeted floor in the former. Monitoring was also done in the shopping mall at three different sites. Indoor pollutants levels and the I/O ratios at the shopping mall were higher than at the university. Levels of all pollutants measured at the car park, except for toluene and CO(2), were the highest. I/O ratios of the pollutants at the mall were above 1.0, which indicates the relatively higher influence of the indoor sources. However, the black carbon content in PM2.5 outdoor is higher than indoor, which suggest the important contribution from outdoor combustion sources such as the traffic. Major sources of outdoor air pollution in the areas were briefly discussed. Exposure modeling was applied using the time activity and measured pollutant concentrations to assess the exposure of different groups of people in the study areas. High exposure to PM2.5, especially for the people working in the mall, should be of health effect concern.     

Analysis of the air pollution climate at a background site in the Po valley

The Po valley in northern Italy is renowned for its high air pollutant concentrations. Measurements of air pollutants from a background site in Modena, a town of 200 thousand inhabitants within the Po valley, are analysed. These comprise hourly data for CO, NO, NO(2), NO(x), and O(3), and daily gravimetric equivalent data for PM(10) from 1998-2010. The data are analysed in terms of long-term trends, annual, weekly and diurnal cycles, and auto-correlation and cross-correlation functions. CO, NO and NO(2) exhibit a strongly traffic-related pattern, with daily peaks at morning and evening rush hour and lower concentrations over the weekend. Ozone shows an annual cycle with a peak in July due to local production; notwithstanding the diurnal cycle dominated by titration by nitrogen oxide, the decreasing long term trend in NO concentration did not affect the long term trend in O(3), whose mean concentration remained steady over the sampling period. PM(10) shows a strong seasonality with higher concentration in winter and lower concentration in summer and spring. Both PM(10) and ozone show a marked weekly cycle in summer and winter respectively. Regressions of PM(10) upon NO(x) show a consistently greater intercept in winter, representing higher secondary PM(10) in the cooler months of the year. There is a seasonal pattern in primary PM(10) to NO(x) ratios, with lower values in winter and higher values in summer, but the reasons are unclear.     

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.     

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.     

Temporal and spatial variations of the quality of ambient air in the Kingdom of Bahrain during 2007

The main objective of the present investigation is to study the temporal and spatial variations of the quality of ambient air in the Kingdom of Bahrain. The non-parametric Kruskal-Wallis (KW) test showed significant spatial variations and interactions of spatial-temporal among five mobile monitoring stations for 11 air pollutants. The Mann Whitney (MW) test demonstrated the seasonality of spring over winter for the PM(10), PM(2.5), NO(2), CO and p-xylene, the seasonality of winter over spring for O(3), and no significant seasonal variation for NH(3), benzene, SO(2), toluene and H(2)S. It is concluded that emissions from automobile exhaust, industrial and developmental projects are responsible for the spatial air pollution, and that air temperature is the controlling factor for the seasonal variations.     

睢宁地区大气PM_(2.5)及气态污染物季节性变化特征

根据2014年全年实时在线观测数据,分析了徐州睢宁地区大气细颗粒物(PM_(2.5))和气态污染物(包括SO_2、CO、NO_x、O_3)质量浓度的季节性变化特征。结合后向轨迹模型,分析不同气团对该地区大气污染浓度的影响。PM_(2.5)与O_3值在夏季最低,呈显著相关,表明夏季PM_(2.5)主要受控于本地大气光化学活性。在冬季,除O_3外,PM_(2.5)、SO_2、CO、NO_x值最高,且大气颗粒物主要以细粒子为主。O_3在春季最高,并与远程传输的气团且经过我国东部污染源密集地区相对应。高浓度的PM_(2.5)主要与冬季缓慢移动的气团相对应,这可能将PM_(2.5)及其气态前体物传输至该地区进而加重大气污染程度。     

不同模式版本对长三角区域大气污染物模拟结果对比评估

选取2015年1、4、7、10月(分别代表冬、春、夏、秋4季),应用CMAQv4.7.1和CMAQv5.1模式模拟长三角区域的空气质量,对比了NO2、SO2、O3、PM2.54个常规污染物的模拟结果,表明CMAQv5.1对NO2、SO2和PM2.5的模拟效果优于CMAQv4.7.1,而CMAQv4.7.1的O3模拟效果优于CMAQv5.1;CMAQv5.1的NO2模拟值更接近地面观测值,比起不同版本的化学机制对NO2模拟效果的影响,NO2的模拟偏差受排放高估的影响更大;2个版本SO2的模拟值差距较小,且都与地面观测值之间差异较小;CMAQv5.1 PM2.5的模拟值比CMAQv4.7.1更接近观测值,气溶胶模块机制的更新(例如新增细分的PM2.5模式物种和部分二次有机气溶胶生成机制的改进等)对PM2.5模拟效果的改善显著;CMAQv5.1的O3模拟值比CMAQv4.7.1高,CMAQv5.1的O3模拟值在O3观测值的高值时段更接近观测值,而CMAQv4.7.1的O3模拟值在低值时段更接近观测值,CMAQv5.1在日最大8小时平均(MDA8)O3观测浓度超标日的O3模拟效果相比CMAQv4.7.1有一定程度的改善,但在非超标日模拟效果变差,CMAQv5.1的O3模拟效果总体相比CMAQv4.7.1并未得到有效提升。提出,未来针对低值时段和低值区域的O3模拟机制的改进将进一步提升O3模拟效果。     

Spatial variability of air pollutants in the city of Taranto, Italy and its potential impact on exposure assessment

Epidemiological studies typically use monitored air pollution data from a single station or as averaged data from several stations to estimate population exposure. In industrialized urban areas, this approach may present critical issues due to the spatial complexities of air pollutants which are emitted by different sources. This study focused on the city of Taranto, which is one of the most highly industrialized cities in southern Italy. Epidemiological studies have revealed several critical situations in this area, in terms of mortality excess and short-term health effects of air pollution. The aims of this paper are to study the variability of air pollutants in the city of Taranto and to interpret the results in relation to the applicability of the data in assessing population exposure. Meteorological and pollution data (SO2, NO2, PM10), measured simultaneously and continuously during the period 2006–2010 in five air quality stations, were analyzed. Relative and absolute spatial concentration variations were investigated by means of statistical indexes. Results show significant differences among stations. The highest correlation between stations was observed for PM10 concentrations, while critical values were found for NO2. The worst values were observed for the SO2 series. The high values of 90th percentile of differences between pairs of monitoring sites for the three pollutants index suggest that mean concentrations differ by large amounts from site to site. The overall analysis supports the hypothesis that various parts of the city are differently affected by the different emission sources, depending on meteorological conditions. In particular, analysis revealed that the influence of the industrial site may be primarily identified with the series of SO2 data which exhibit higher mean concentration values and positive correlations with wind intensity when the monitoring station is downwind from the industrial site. Results suggest evaluating the population exposure to air pollutants in industrialized cities by taking into account the possible zones of influence of different emission sources. More research is needed to identify an indicator, which ought to be a synthesis of several pollutants, and take into account the meteorological variables.     

Air quality of Prague: traffic as a main pollution source

Political and economical transition in the Central and Eastern Europe at the end of eighties significantly influenced all aspects of life as well as technological infrastructure. Collapse of outdated energy demanding industry and adoption of environmental legislation resulted in seeming improvements of urban environmental quality. Hand in hand with modernization the newly adopted regulations also helped to phase out low quality coal frequently used for domestic heating. However, at the same time, the number of vehicles registered in the city increased. The two processes interestingly acted as parallel but antagonistic forces. To interpret the trends in urban air quality of Prague, Czech capital, monthly averages of PM(10), SO(2), NO(2), NO, O(3) and CO concentrations from the national network of automated monitoring stations were analyzed together with long term trends in fuel consumption and number of vehicles registered in Prague within a period of 1992-2005. The results showed that concentrations of SO(2) (a pollutant strongly related to fossil fuel burning) dropped significantly during the period of concern. Similarly NO(X) and PM(10) concentrations decreased significantly in the first half of the nineties (as a result of solid fuel use drop), but remained rather stable or increased after 2000, presumably reflecting rapid increase of traffic density. In conclusion, infrastructural changes in early nineties had a strong positive effect on Prague air quality namely in the first half of the period studied, nevertheless, the current trend in concentrations of automotive exhaust related pollutants (such as PM(10), NO(X)) needs adoption of stricter measures.     

Air pollution exposure monitoring and estimating. Part I. Integrated air quality monitoring system

This paper presents an integrated exposure monitoring system, based on an expansion of existing air quality monitoring systems using dispersion modelling. The system allows: (1) identifying geographical areas whose inhabitants are most exposed to ambient pollution; (2) identifying how many people in an area are exposed to concentrations of pollution exceeding air quality guidelines; (3) describing the exposure of population subgroups (e.g. children); (4) planning pollution abatement measures and quantifying their effects; (5) establishing risk assessment and management programs, and (6) investigating the short- and long-term effects of both pollutants and pollution sources on public health. The effect of pollution is rarely very large and in order to discover it, exposure estimation must provide data that reflects both spatial and temporal variations. Estimates of pollution exposure are obtained using an integrated approach that combines results of measurements from monitoring programs with dispersion calculations. These values can serve as estimates for individual short-term or long-term exposure. The grouped data allows the expression of ambient pollution concentrations as the spatial distribution of estimates such as the mean or 98th percentile of such compounds as SO2, O3, NO2, PM10 and PM2.5. This integrated approach has been combined into a single software package, AirQUIS.     

Differences between weekend and weekday ozone levels over rural and urban sites in Southern Italy

Air quality data from a network of 11 monitoring stations in the Apulia region of southern Italy during the summer of 2005 reveal a high frequency of ozone law limit violations. Since ozone is a secondary pollutant, air quality control strategies aimed at reducing ozone concentration are not immediate. Herein, we analyse weekly changes in concentration levels of ozone (O(3)), nitrogen oxides (NO(x)), carbon monoxide (CO), and volatile organic compounds (VOCs), and evaluate how the differences in primary emissions cause changes in the production of ozone. The comparison between weekend and weekday levels of O(3) and its precursors are direct evidence for the existence of the "ozone weekend effect." This effect was observed at all stations with a considerable variation in the overall ozone magnitude, including both traffic stations and non-traffic stations. Data from VOC measurements at traffic stations primarily indicated elevated levels of benzene, toluene, and xylenes (BTX); all of these substances showed an overall decrease over the weekend. A single station indicated levels of non-methane hydrocarbon (NMHC) and PM10, both of which did not demonstrate any weekly cycle. Analysis of weekly and diurnal cycles of O(3), NO(x), CO, NMHC, and PM10 indicates that higher weekend ozone levels result from a reduction in the emission of nitrogen oxides on weekends in VOC-sensitive regimes. This indicates that a reduction in VOC and NO(x) levels would be more effective than NO(x) reduction alone. Our results underscore the need for improved and more efficient VOC measurements.     

平顶山市大气PM10、PM2.5 污染调查

于2003年12月-2004年11月对平顶山市城区大气PM10、PM2.5污染进行了调查.结果表明,2004年大气PM10、PM2.5质量浓度分别为0.031 mg/m3～0.862 mg/m3、0.019 mg/m3～0.438 mg/m3;年均值分别为0.174 mg/m3、0.114 mg/m3,超标0.74倍、6.60倍.PM10、PM2.5污染的季节变化趋势是以冬季、春季高,秋季次之,夏季最低,细颗粒(PM2.5)约占PM10 65%;As、Pb、Cd、S、Zn、Cu、Mn、Ca等元素是颗粒物中主要污染元素,易在PM2.5中富集.平顶山市大气颗粒物污染的主要来源有煤炭燃烧、汽车尾气、城市基础建设和有色金属冶炼行业.     

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。     

Characterization and diurnal variation of size-resolved inorganic water-soluble ions at a rural background site

Water-soluble inorganic ions in aerosol samples have been studied. The sample collection took place during summer in 2003 at a European background site which is operating within the framework of the European Monitoring and Evaluation Program. Gent type PM10 stacked filter unit (SFU) samplers were operated in parallel on a day and night basis to collect particles in separate coarse (2.0-10 microm) and fine (<2.0 microm) size fractions. Particulate masses were measured gravimetrically; the filters from one of the SFU samplers were analyzed by particle-induced X-ray emission spectrometry (PIXE) and instrumental neutron activation analysis (INAA). Filters from the other SFU sampler were analyzed by ion chromatography (IC) for major inorganic anions (MSA-, NO2(-), NO3(-), Cl-, Br-, SO4(2-), oxalate) and cations (Na+, K+, NH4(+), Mg2+, Ca2+). The water-soluble inorganic ions measured were responsible for 44% and 16% of the total fine and coarse particulate mass, respectively. In the fine size fraction, the main ionic components were SO4(2-) and NH4(+) accounting for about 90% of fine ionic mass. In the coarse fraction the main ionic components were Ca2+ and NO3(-), followed by SO4(2-). Significant day and night difference in the mass concentrations was observed only for fine NO3(-). The molar ratios of fine NH4(+) to SO4(2-) indicated their complete neutralization to (NH4)2SO4. According to the cation-to-anion ratios the coarse particles were alkaline, while the fine particles were slightly acidic or neutral. By comparing the corresponding concentrations obtained from PIXE/INAA and IC, we determined the water-extractable part of the individual species. We also investigated the effect of long-range transported air masses on the local air concentrations, and we found that the air quality of this background monitoring station was affected by regional pollution sources.     

CO and NO2 pollution in a long two-way traffic road tunnel: investigation of NO2/NOx ratio and modelling of NO2 concentration

The CO, NO and NO2 concentrations, visibility and air flow velocity were measured using continuous analysers in a long Norwegian road tunnel (7.5 km) with traffic in both directions in April 1994 and 1995. The traffic density was monitored at the same time. The NO2 concentration exceeded Norwegian air quality limits for road tunnels 17% of the time in 1994. The traffic through the tunnel decreased from 1994 to 1995, and the mean NO2 concentration was reduced from 0.73 to 0.22 ppm. The ventilation fan control, based on the CO concentration only, was unsatisfactory and the air flow was sometimes low for hours. Models for NO2 concentration based on CO concentration and absolute air flow velocity were developed and tested. The NO2/NOx ratio showed an increase for NOx levels above 2 ppm; a likely explanation for this phenomenon is NO oxidation by O2. Exposure to high NO2 concentrations may represent a health risk for people with respiratory and cardiac diseases. In long road tunnels with two-way traffic, this study indicates that ventilation fan control based on CO concentration should be adjusted for changes in vehicle CO emission and should be supplemented by air flow monitoring to limit the NO2 concentration.     

天津市基于新标准的空气质量预报模型效果评估

利用2015年环境空气质量监测数据,对天津市OPAQ空气质量统计预报模型预测效果进行验证评估。结果表明,模型对天津市AQI和PM_(2.5)、PM_(10)、O_3、NO——2的预测结果与实测结果具有较好的趋势一致性,且预测时间越临近,拟合度越好,24 h预报的相关系数r全部达到0.8以上。对PM_(2.5)的预报性能明显优于PM_(10)、O_3和NO_2,PM_(2.5)平均值预测略呈正偏差,但重污染预测值偏低约15%;O_3和NO_2预测值呈明显负偏差,O_3峰值预测不足,NO_2预测值整体偏低,均以24 h预报趋势性最好,但负偏差最为突出。     

南通市冬季PM2.5中水溶性离子污染特征

根据南通市2016和2017年冬季大气多参数站自动监测PM2.5数据和在线离子色谱分析仪Marga监测的PM2.5中水溶性离子数据,分析了南通市冬季PM2.5中水溶性离子污染特征。结果表明,南通市2016和2017年冬季,ρ(PM2.5)分别为58和54μg/m 3,均高出其年均值(14μg/m^3);ρ(水溶性离子)总占ρ(PM2.5)百分比分别为74.5%和74.3%;二次离子ρ(NO3^-、SO4^2-和NH4^+)占ρ(PM2.5)百分比分别为66.8%和66.6%;各水溶性离子占比大小依次为:NO3^-、SO4^2-、NH4^+、Cl^-、K^+、Na^+、Ca^2+、Mg^2+。对ρ(NO3^-)/ρ(SO 4^2-)分析表明,移动源已经成为南通市冬季的主要污染源,且呈逐年增强趋势。对氯氧化率和硫氧化率的分析表明,南通市冬季存在较明显的二次污染,SO2的转化程度大于NO2。除Na^+和Mg^2+外,其他离子与PM2.5均呈显著相关性,NO3^-、SO4^2-与NH4^+之间的相关系数最高,Cl^-与除Na^+外的所有阳离子均呈显著相关性。     

Chemical characteristics of aerosols and trace gas distribution over North and Central India

A field campaign on aerosol chemical properties and trace gases measurements was carried out along the Delhi-Hyderabad-Delhi road corridor (spanning about 3,200 km) in India, during February 1-29, 2004. Aerosol particles were collected on quartz and cellulose filters using high volume (PM(10)) sampler at various locations along the route (i.e., urban, semi-urban, rural, and forest areas) and have been characterized for major cations (Na(+), Ca(2+), Mg(2+), K(+), and NH (4) (+)), anions (Cl(-), NO (3)(-), and SO (4)(2-)), and heavy metals (Cu, Cd, Fe, Zn, Mn, and Pb). Simultaneously, we measured NO(2) and SO(2) gases. These species show large spatial and temporal variations. The ambient PM(10) concentration has been observed to be the highest (55 ± 4 μg m(-3)) near semi-urban areas followed by forest areas (48 ± 2 μg m(-3)) and in rural areas (44 ± 22 μg m(-3)). The concentrations of NO( x ) (NO(2)+NO) and SO(2) ranged from 16 to 69 μg m(-3) and 4 to 11 μg m(-3), respectively. Among anions, NO(3)(-) and SO(4) (2-) are the major constituents of PM(10). The urban and semi-urban sites showed enhanced concentrations of Fe, Zn, Mn, Cd, and Pb. This study provide information about atmospheric concentrations of various species in the northern to central India, which may be important for policy makers to better understand the air quality of the region.     

2014-2018年南京PM2.5中碳组分污染特征分析

利用在线高分辨率仪器对2014-2018年南京市PM2.5中有机碳(OC)、元素碳(EC)进行了连续监测,结果表明:离线分析法与在线分析法对OC、EC的测定结果具有很好的线性相关性,离线分析的EC、OC浓度高于在线自动监测值;2014-2018年南京OC与EC的平均质量浓度分别为(6. 38±3. 91)μg/m^3和(3. 12±1. 76)μg/m^3,整体呈下降趋势,冬季OC与EC均较高,夏季两者质量浓度较低。OC和EC均呈现夜间高、白天低的日变化规律,OC与EC第一个峰值均出现在08:00左右,OC第二个峰值出现在20:00前后;夏季OC与EC相关性最低,冬季最高,NO2、CO与OC、EC的相关性总体高于SO2,表明燃料燃烧对碳气溶胶有一定贡献,但没有交通源的贡献显著,夏季O3与OC呈现一定程度的正相关性。利用最小相关系数法(MRS)计算大气OC中一次有机碳(POC)和二次有机碳(SOC),结果显示OC中以POC为主,但SOC呈逐年上升趋势,2018年SOC质量浓度达1. 96μg/m3,在OC中占比达31. 9%,后续颗粒物污染治理的重点可能应关注VOCs。