A semi-empirical model for urban PM10 concentrations,and its evaluation against data from an urban measurement network

We have developed a model for evaluating the mass-based concentrations of urban particulate matter. The basic model assumption is that local vehicular traffic is responsible for a substantial fraction of the street-level concentrations of both PM₁₀ and NO_x, either due to primary emissions or resuspension from street surfaces. The modelling system utilises the data from an air quality monitoring network in the Helsinki Metropolitan Area. We have determined linear relationships between the measured urban PM₁₀ data against those of NO_x in various urban surroundings, based on continuously measured hourly concentration values. The data was obtained from two stations in central Helsinki and one suburban station in the Helsinki Metropolitan Area during a period of 3 yr, from 1996 to 1998. The model also includes a treatment of the regional background concentrations, and resuspended particulate matter. The model performance was evaluated against the measured PM₁₀ data from the above-mentioned three stations and from two other stations, using data that was measured in 1999. We used two alternative model versions, one based on separate correlation parameters (PM₁₀ vs. NO_x) for each station, and another based on parameters averaged over the stations considered. We analysed the agreement between the measured and predicted hourly concentration time series, utilising the values of the fractional bias (FB) and the so-called index of agreement (IA). As expected, the model predicts relatively well the yearly mean concentrations of PM₁₀: the FB values range from −0.05 to +0.09. Model performance is also relatively good when predicting the yearly mean values that are classified separately for each hour of the day: the corresponding IA values range from 0.85 to 0.96. However, model performance is substantially worse in predicting the hourly time series of the year: the IA values using the station-specific parameters range from 0.46 to 0.65. The model was applied in evaluating the yearly average spatial concentration distribution of PM₁₀ in central Helsinki, based on the corresponding modelled NO_x concentrations. With re-evaluation of a few parameters that can be determined empirically, the model could be evaluated, and most probably applied, in other urban areas as well.     

Interpretation of air quality in relation to monitoring station's surroundings

This study explores the appropriateness of the locality of air monitoring stations which are meant to indicate air quality in the area. Daily variations in NO₂ and PM₁₀ concentrations at 14 monitoring stations in Hong Kong are examined. The daily variations in NO₂ at a number of background monitoring stations exhibit patterns similar to variations in traffic volume while variations in PM₁₀ concentration exhibit less discernible pattern. Principal component analysis (PCA) and cluster analysis (CA) are applied to analyse NO₂ and PM₁₀ measurements between January 2001 and December 2005. The results show that NO₂ concentrations at background stations within the urban area are highly influenced by vehicle emissions. The effect vehicle emission has on NO₂ at stations within new towns is smaller. CA results also show that variations in PM₁₀ concentrations are distinguished by the area the station is located in. PCA results show that there are two principal components (PC's) associated with variations in roadside concentration of PM₁₀. The strong influence of roadside emissions towards concentrations of NO₂ and PM₁₀ at a number of urban background stations may be due to their close proximity to busy roadways and the high density of surrounding tall buildings, which creates an enclosure that hinders dispersion of roadside emissions and results in air pollution behaviour that reflects variation in traffic.     

Codependencies of Reactive Air Toxic and Criteria Pollutants on Emission Reductions

Abstract

It is important to understand the effects of emission controls on concentrations of ozone, fine particulate matter (PM_2.5), and hazardous air pollutants (HAPs) simultaneously, to evaluate the full range of health, ecosystem, and economic effects. Until recently, the capability to simultaneously evaluate interrelated atmospheric pollutants (“one atmosphere” analysis) was unavailable to air quality managers. In this work, we use an air quality model to examine the potential effect of three emission reductions on concentrations of ozone, PM_2.5, and four important HAPs (formaldehyde, acetaldehyde, acrolein, and benzene) over a domain centered on Philadelphia for 12-day episodes in July and January 2001. Although NO_x controls are predicted to benefit PM_2.5 concentrations and sometimes benefit ozone, they have only a small effect on formaldehyde, slightly increase acetaldehyde and acrolein, and have no effect on benzene in the July episode. Concentrations of all pollutants except benzene increase slightly with NO_x controls in the January simulation. Volatile organic compound controls alone are found to have a small effect on ozone and PM_2.5, a less than linear effect on decreasing aldehydes, and an approximately linear effect on acrolein and benzene in summer, but a slightly larger than linear effect on aldehydes and acrolein in winter. These simulations indicate the difficulty in assessing how toxic air pollutants might respond to emission reductions aimed at decreasing criteria pollutants such as ozone and PM_2.5.     

Air pollution “holiday effect” resulting from the Chinese New Year

Our study was an attempt to conduct a comprehensive and systematical examination of the holiday effect, defined as the difference in air pollutant concentrations between holiday and non-holiday periods. This holiday effect can be applied to other countries with similar national or cultural holidays. Hourly and daily surface measurements of six major air pollutants from thirteen air quality monitoring stations of the Taiwan Environmental Protection Administration during the Chinese New Year (CNY) and non-Chinese New Year (NCNY) periods were used. We documented evidence of a “holiday effect”, where air pollutant concentrations were significantly different between holidays (CNY) and non-holidays (NCNY), in the Taipei metropolitan area over the past thirteen years (1994–2006).The concentrations of NO_x, CO, NMHC, SO₂ and PM₁₀ were lower in the CNY than in the NCNY period, while the variation in the concentration of O₃ was reversed, which was mainly due to the NO titration effect. Similar differences in these six air pollutants between the CNY and NCNY periods were also found in the diurnal cycle and in the interannual variation. For the diurnal cycle, a common traffic-related double-peak variation was observed in the NCNY period, but not in the CNY period. Impacts of dust storms were also observed, especially on SO₂ and PM₁₀ in the CNY period. In the 13-year period of 1994–2006, decreasing trends of NO_x and CO in the NCNY period implied a possible reduction of local emissions. Increasing trends of SO₂ and PM₁₀ in the CNY period, on the other hand, indicated a possible enhancement of long-range transport. These two mechanisms weakened the holiday effect.     

An assessment of the impact of climate change on air quality at two UK sites

Possible effects of climate change on air quality are studied for two urban sites in the UK, London and Glasgow. Hourly meteorological data were obtained from climate simulations for two periods representing the current climate and a plausible late 21st century climate. Of the meteorological quantities relevant to air quality, significant changes were found in temperature, specific humidity, wind speed, wind direction, cloud cover, solar radiation, surface sensible heat flux and precipitation. Using these data, dispersion estimates were made for a variety of single sources and some significant changes in environmental impact were found in the future climate. In addition, estimates for future background concentrations of NO_x, NO₂, ozone and PM₁₀ upwind of London and Glasgow were made using the meteorological data in a statistical model. These showed falls in NO_x and increases in ozone for London, while a fall in NO₂ was the largest percentage change for Glasgow. Other changes were small. With these background estimates, annual-average concentrations of NO_x, NO₂, ozone and PM₁₀ were estimated within the two urban areas. For London, results averaged over a number of sites showed a fall in NO_x and a rise in ozone, but only small changes in NO₂ and PM₁₀. For Glasgow, the changes in all four chemical species were small. Large-scale background ozone values from a global chemical transport model are also presented. These show a decrease in background ozone due to climate change. To assess the net impact of both large scale and local processes will require models which treat all relevant scales.     

Evaluation of the effect of long-range transport of air pollutants on coastal atmospheric monitoring sites in and around Taiwan

Long-range transport of pollution outflow from Asian mainland has been noticed and expected to play a significant role in Pacific background. Since 1993 the Taiwanese Environmental Protection Administration (TEPA) is conducting ground-based observations of various particulate and gaseous pollutants at 74 monitoring stations in Taiwan. One of these stations, Heng-Chun at the south coast of Taiwan can be considered as a background station with only negligible amounts of local pollution, and another one, Wan-Li at the north coast, predominantly receives air that has not passed over Taiwan, so that background air can be analysed by means of sectorisation. In this work, the sectorised 13-year time series of measurements of CO, SO₂, O₃, NO_x and PM₁₀, from the Wan-Li station are presen and compared to data from the Heng-Chun station and another TEPA background station off the coast of mainland China, Ma-Zu. The CO and O₃ measurements are also compared to data from the Yonaguni station, a Pacific island site, part of the Global Atmospheric Watch (GAW) network.The similarity of the sectorised data from the Wan-Li station with the data of the other station indicates that atmospheric measurements from the Wan-Li site can be used to make inferences about trends in western Pacific background air pollution and the effect of long-range transport of pollutants. The measurement time series from 1993 to 2006 do not indicate a significant trend in the monthly mean O₃ concentrations in accordance with other research about ozone in tropical latitudes. An increasing trend in CO concentrations of 2.8% per annum is observed between 1999 and 2006 for long-range transport to northern Taiwan, and a doubling of the SO₂ and NO_x concentrations observed at the Wan-Li and Heng-Chun sites within the period 2001–2006. SO₂ concentrations are found to quadruple at Ma-Zu within the same period. The data suggest that pollution from the Asian mainland enhances significantly the background air pollution over the Pacific.     

Long-term trends of primary and secondary pollutant concentrations in Switzerland and their response to emission controls and economic changes

A detrending technique is developed for short-term and yearly variations in order to identify long-term trends in primary and secondary pollutants. In this approach, seasonal and weekly variations are removed by using a mean year; the residual meteorological short-term variation is removed by using a multiple linear regression model. This methodology is employed to detrend ozone (O₃), NO_x, VOC and CO concentrations in Switzerland. We show that primary pollutants (NO_x,VOC and CO) at urban and sub-urban stations show a downward trend over the last decade which correlates well with the reductions in the estimated Swiss emissions. In spite of these large decreases achieved in precursor emissions, summer peak ozone concentrations do not show any statistically significant trend over the last decade. Application of this method to ozone concentrations measured at the Jungfraujoch (3580 m a.s.l.) also shows no trend over the last 10 years. Detrended summer ozone correlates well with European Union gross national product and industrial production growth rates. These results suggest that if substantial reductions in summer peak ozone in Switzerland are desired, emissions reduction strategies must be part of control program involving a much larger region.     

Measurements and analyses of nitrogen oxides and ozone in the yard and on the roof of a street-canyon in Suzhou

The concentrations of air pollutants such as nitrogen oxides and ozone characterised by very fast chemical reactions can significantly vary within urban street-canyon due to the short distances between sources and receptor. With the primary objective to analyse this issue, NO, NO₂, NO_x, O₃, BTX, and wind flow field were continuously measured for 1 week at two heights (a street-level yard and a 25-m-high rooftop) in an urban canyon in Suzhou (China). The yard ozone concentrations were found to be up to six times lower than on the roof. Different frequency distributions (FD), dynamical and chemical processes of the pollutant variations from yard to roof are discussed to explain the findings. The predominant factors for the dissimilar pollutant vertical diffusion at the two measurement locations were associated to dissimilar fluid-dynamic and heterogeneous removal effects that likely induced dissimilar ozone chemical processes relative to NO_x and BTX precursors.     

Assessment of ambient air quality in the port of Naples

Two experimental monitoring campaigns were carried out in 2012 to investigate the air quality in the port of Naples, the most important in southern Italy for traffic of passengers and one of the most important for goods. Therefore, it represents an important air pollution source located close to the city of Naples. The concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and BTEX (benzene, toluene, ethylbenzene, and xylenes) in the air were measured at 15 points inside the Naples port area through the use of passive samplers. In addition, a mobile laboratory was positioned in a fixed point inside the port area to measure continuous concentration of pollutants together with particulate matter, ambient parameters, and wind direction and intensity. The pollution levels monitored were compared with those observed in the urban area of Naples and in other Mediterranean ports. Even though the observation time was limited, measured concentrations were also compared with limit values established by European legislation. All the measured pollutants were below the limits with the exception of nitrogen dioxide: its average concentration during the exposition time exceeded the yearly limit value. A spatial analysis of data, according to the measured wind direction and intensity, provided information about the effects that ship emissions have on ambient air quality in the port area. The main evidence indicates that ship emissions influence sulfur dioxide concentration more than any other pollutants analyzed.

Implications: Two monitoring campaigns were carried out to measure BTEX, SO₂, NO₂, and PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) air concentrations in the port of Naples. NO₂ hourly average and PM₁₀ daily average comply with European legislative standards. Spatial variation of pollutants long the axis corresponding to the prevailing wind direction seems to indicate a certain influence of ship emissions for SO₂. For NO₂ and PM₁₀, a correlation between concentrations in the harbor and those measured by the air quality monitoring stations sited in the urban area of Naples was observed, indicating a possible contribution of the near road traffic to the air pollution in the port of Naples.     

Harbour of Ravenna: The contribution of harbour traffic to air quality

Ravenna is one of the main Italian ports and has assumed a leadership position in Italy for some products and markets. The commercial harbour and the adjacent industrial area are very important for the economic system of Ravenna but, at the same time, they are highly critical areas.In particular, on average 8000 ships per year pass through the harbour of Ravenna, influencing air quality in harbour environment.The paper originates from a study about the contribution of different sources of air pollution in Ravenna and its aim is to evaluate the maritime traffic contribution to the air quality in the port area and to determine the suitability of an urban air quality model to support the air quality management in Ravenna. NO_x and PM are selected as modelled pollutants.The study is made up of two parts. The first deals with the evaluation of annual emission of PM₁₀ and NO_x coming from ships through a standard European methodology while in the second we simulated the diffusion of these pollutants in the whole area. In order to evaluate the capability of the model to treat maritime traffic emissions, we compared hour-by-hour simulated concentrations with data collected by a fixed monitoring station located near the Candiano Canal.NO_x concentrations obtained by short- and long-term simulations show a good match with the values measured by the fixed monitoring station, located in the centre of harbour area, and these results are also supported by FA2 performance index.Instead the omission of the secondary particulate and the contribution of other sources of particulate matter in the port area are probably the most important causes of the PM₁₀ underestimation.The worse results obtained according to the performance indexes indicate the need to consider the formation and transport of secondary particulate matter in order to obtain more reliable predictions.     

Air quality in Yanbu,Saudi Arabia

Yanbu, on the Red Sea, is an affluent Saudi Arabian industrial city of modest size. Substantial effort has been spent to balance environmental quality, especially air pollution, and industrial development. We have analyzed six years of observations of criteria pollutants O₃, SO₂, particles (PM_2.5 and PM₁₀) and the known ozone precursors—volatile organic compounds (VOCs) and nitrogen oxides (NO_x). The results suggest frequent VOC-limited conditions in which ozone concentrations increase with decreasing NO_x and with increasing VOCs when NO_x is plentiful. For the remaining circumstances ozone has a complex non-linear relationship with the VOCs. The interactions between these factors at Yanbu cause measurable impacts on air pollution including the weekend effect in which ozone concentrations stay the same or even increase despite significantly lower emissions of the precursors on the weekends. Air pollution was lower during the Eids (al-Fitr and al-Adha), Ramadan and the Hajj periods. During Ramadan, there were substantial night time emissions as the cycle everyday living is almost reversed between night and day. The exceedances of air pollution standards were evaluated using criteria from the U.S. Environmental Protection Agency (EPA), World Health Organization (WHO), the Saudi Presidency of Meteorology and Environment (PME) and the Royal Commission Environmental Regulations (RCER). The latter are stricter standards set just for Yanbu and Jubail. For the fine particles (PM_2.5), an analysis of the winds showed a major impact from desert dust. This effect had to be taken into account but still left many occasions when standards were exceeded. Fewer exceedances were found for SO₂, and fewer still for ozone. The paper presents a comprehensive view of air quality at this isolated desert urban environment.

Implications: Frequent VOC-limited conditions are found at Yanbu in Saudi Arabia that increase ozone pollution if NO_x is are reduced. In this desert environment, increased nightlife produces the highest levels of VOCs and NO_x at night rather than the day. The effects increase during Ramadan. Fine particles peak twice a day—the morning peak is caused by traffic and increases with decreasing wind, potentially representing health concerns, but the larger afternoon peak is caused by the wind, and it increases with increasing wind speeds. These features suggest that exposure to pollutants must be redefined for such an environment.     

Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations

Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to optimize the ANN models to achieve the most accurate hourly prediction for a case study (city of Tehran), and to examine a methodology to analyze uncertainties based on ANN and Monte Carlo simulations (MCS). In the current study, the ANNs were constructed to predict criteria pollutants of nitrogen oxides (NO_x), nitrogen dioxide (NO₂), nitrogen monoxide (NO), ozone (O₃), carbon monoxide (CO), and particulate matter with aerodynamic diameter of less than 10 μm (PM₁₀) in Tehran based on the data collected at a monitoring station in the densely populated central area of the city. The best combination of input variables was comprehensively investigated taking into account the predictability of meteorological input variables and the study of model performance, correlation coefficients, and spectral analysis. Among numerous meteorological variables, wind speed, air temperature, relative humidity and wind direction were chosen as input variables for the ANN models. The complex nature of pollutant source conditions was reflected through the use of hour of the day and month of the year as input variables and the development of different models for each day of the week. After that, ANN models were constructed and validated, and a methodology of computing prediction intervals (PI) and probability of exceeding air quality thresholds was developed by combining ANNs and MCSs based on Latin Hypercube Sampling (LHS). The results showed that proper ANN models can be used as reliable metamodels for the prediction of hourly air pollutants in urban environments. High correlations were obtained with R ² of more than 0.82 between modeled and observed hourly pollutant levels for CO, NO_x, NO₂, NO, and PM₁₀. However, predicted O₃ levels were less accurate. The combined use of ANNs and MCSs seems very promising in analyzing air pollution prediction uncertainties. Replacing deterministic predictions with probabilistic PIs can enhance the reliability of ANN models and provide a means of quantifying prediction uncertainties.     

Trend analysis of urban NO2 concentrations and the importance of direct NO2 emissions versus ozone/NOx equilibrium

The annual air quality standard of NO₂ is often exceeded in urban areas near heavy traffic locations. Despite significant decrease of NO_x emissions in 1986–2005 in the industrial and harbour area near Rotterdam, NO₂ concentrations at the urban background remain at the same level since the end of the nineties. Trend analysis of monitoring data revealed that the ozone/NO_x equilibrium is a more important factor than increasing direct NO₂ emissions by traffic. The latter has recently been identified as an additional NO₂ source due to the introduction of oxy-catalytic converters in diesel vehicles and the growing number of diesel vehicles. However, in Rotterdam over the period 1986–2005 direct NO₂ emissions by road traffic only increased 3–4%. Due to the importance of the ozone/NO_x equilibrium, it is concluded that local NO_x emissions in Rotterdam need substantial reduction to achieve lower NO₂ urban background levels. This is a relatively costly abatement strategy and, therefore, a “hotspot” approach aiming at reducing NO_x emissions by local traffic measures is more effective to meet European air quality standards.     

Long term changes in nitrogen oxides and volatile organic compounds in Toronto and the challenges facing local ozone control

Ground level ozone represents a significant air quality concern in Toronto, Canada, where the national 65 ppb 8-h standard is repeatedly exceeded during the summer. Here we present an analysis of nitrogen dioxide (NO₂), ozone (O₃), and volatile organic compound (VOC) data from federal and provincial governmental monitoring sites from 2000 to 2007. We show that summertime VOC reactivity and ambient concentrations of NO₂ have decreased over this period of time by up to 40% across Toronto and the surrounding region. This has not resulted in significant summertime ozone reductions, and in some urban areas, it appears to be increasing. We discuss the competing effects of decreased ozone titration leading to an increase in O₃, and decreased local ozone production, both caused by significant decreases in NO_x concentrations. In addition, by using local meteorological data, we show that annual variability in summer ozone correlates strongly with maximum daily temperatures, and we explore the effect of atmospheric transport from the southwest which has a significant influence on early morning levels before local production begins. A mathematical model of instantaneous ozone production is presented which suggests that, given the observed decreases in NO_x and VOC reactivity, we would not expect a significant change in local ozone production under photochemically relevant conditions. These results are discussed in the context of Toronto's recent commitment to cutting local smog-causing pollutants by 20% by 2012.     

Controls on hourly variations in urban background air pollutant concentrations

Average 21st century concentrations of urban air pollutants linked to cardiorespiratory disease are not declining, and commonly exceed legal limits. Even below such limits, health effects are being observed and may be related to transient daytime peaks in pollutant concentrations. With this in mind, we analyse >52,000 hourly urban background readings of PM₁₀ and pollutant gases throughout 2007 at a European town with legal annual average concentrations of common pollutants, but with a documented air pollution-related cardiorespiratory health problem, and demonstrate the hourly variations in PM₁₀, SO₂, NO_x, CO and O₃. Back-trajectory analysis was applied to track the arrival of exotic PM₁₀ intrusions, the main controls on air pollutants were identified, and the typical hourly pattern on ambient concentrations during 2007 was profiled. Emphasis was placed on “worst case” data (>90th percentile), when health effects are likely to be greatest. The data show marked daytime variations in pollutants result from rush-hour traffic-related pollution spikes, midday industrial SO₂ maxima, and afternoon O₃ peaks. African dust intrusions enhance PM₁₀ levels at whatever hour, whereas European PM incursions produce pronounced evening peaks due to their transport direction (across an industrial traffic corridor). Transient peak profiling moves us closer to the reality of personal outdoor exposure to inhalable pollutants in a given urban area. We argue that such an approach to monitoring data potentially offers more to air pollution health effect studies than using only 24 h or annual averages.     

Effects of Instrument Precision and Spatial Variability on the Assessment of the Temporal Variation of Ambient Air Pollution in Atlanta,Georgia

Abstract

Data from the U.S. Environmental Protection Agency Air Quality System, the Southeastern Aerosol Research and Characterization database, and the Assessment of Spatial Aerosol Composition in Atlanta database for 1999 through 2002 have been used to characterize error associated with instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, GA. These data are being used in time series epidemiologic studies in which associations of acute respiratory and cardiovascular health outcomes and daily ambient air pollutant levels are assessed. Modified semivariograms are used to quantify the effects of instrument precision and spatial variability on the assessment of daily metrics of ambient gaseous pollutants (SO₂, CO, NO_x, and O₃) and fine particulate matter ([PM_2.5] PM_2.5 mass, sulfate, nitrate, ammonium, elemental carbon [EC], and organic carbon [OC]). Variation because of instrument imprecision represented 7–40% of the temporal variation in the daily pollutant measures and was largest for the PM_2.5 EC and OC. Spatial variability was greatest for primary pollutants (SO₂, CO, NO_x, and EC). Population–weighted variation in daily ambient air pollutant levels because of both instrument imprecision and spatial variability ranged from 20% of the temporal variation for O₃ to 70% of the temporal variation for SO₂ and EC. Wind rose plots, corrected for diurnal and seasonal pattern effects, are used to demonstrate the impacts of local sources on monitoring station data. The results presented are being used to quantify the impacts of instrument precision and spatial variability on the assessment of health effects of ambient air pollution in Atlanta and are relevant to the interpretation of results from time series health studies that use data from fixed monitors.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.     

Air pollution characteristics associated with mesoscale atmospheric patterns in northwest continental Europe

An impact related daily air quality index (DAQx), calculated for 15 air quality monitoring stations (traffic, background, and industry) in Belgium, France, Germany and Luxembourg, was compared to mesoscale atmospheric patterns between 2001 and 2007. Meteorological conditions were described by the Hess and Brezowsky synoptic weather classification system and gridded data of the EU FP6 ENSEMBLES project of total precipitation and mean surface temperature. DAQx values indicate sufficient to poor air quality in the urban area of Brussels and at urban traffic stations, as well as satisfactory air quality at the background stations. The air quality index refers to more than 90% to the presence of high PM₁₀, O₃ and NO₂ concentrations. SO₂ and CO play only a minor role. The investigation of weather regimes indicates that zonal and mixed cyclonic circulation regimes are associated with better air quality than meridional and anticyclonic weather regimes. In general, weather regimes with high daily precipitation lead to better air quality than dryer air masses because of lower contribution of PM₁₀ to the air quality index. A trend analysis of weather regimes from 1978 to 2007 shows significant (α = 0.05) positive trends for weather classes associated with lower PM₁₀ concentrations. The results of a case study at a German station examining the relationship between PM₁₀ concentrations and local meteorological quantities (wind speed and precipitation) confirm the results of the regional analysis.     

Modeling the intra-urban variability of outdoor traffic pollution in Oslo,Norway—A GA2LEN project

Traffic is a major source of air pollutants in urban environments, and exposure to these pollutants may be associated with adverse health effects. However, inconsistencies in observational epidemiological studies may be caused by differential measurement errors in various approaches in assessing exposure.We aimed to evaluate a simple method for assessing outdoor air pollutant concentrations in Oslo, Norway, through a land-use regression method.Samples of nitrogen oxides (NO_x) were collected in two different weeks using Ogawa passive diffusion samplers simultaneously at 80 locations across Oslo. Independent variables used in subsequent regression models as predictors of the pollutants were derived using the Arc 9 geographic information system (GIS) software. Indicators of land use, traffic, population density, and physical geography were tested.The final regression model yielded an adjusted coefficient of determination (R²) of 0.77 for nitrogen dioxide (NO₂), 0.66 for nitric oxide (NO), and 0.73 for NO_x.The results suggest that a good predictive exposure model can be derived from this approach, which can be used to estimate long-term small-area variation in concentrations for individual exposure assessment in epidemiological studies in a highly cost-effective way. These small-area variations in traffic pollution are important since they may have associations with health effects.     

Retrospective assessment of air quality management practices in Taiwan

In 1995, Taiwan's Environmental Protection Administration (EPA/TW) instituted a policy of levying emission taxes on polluters in order to combat the rampant national issue of pollution. Since that time, pollution control strategies, tightening exhaust emission standards for industry, improvements in fuel quality, and new stricter vehicle emission standards, etc., have been implemented. This study evaluates the effectiveness of these measures and examines the improvement of Taiwan's air quality. In this paper, we conduct a detailed analysis of change in the concentrations of pollutants (SO₂, NO_x and particulate matter [PM]) between two three-year periods (from 1996 to1998 and from 2000 to 2002). The pollution levels were generally lower in the latter period. Concentrations at 14 EPA/TW stations in central Taiwan were simulated and source apportionment analyses in three of Central Taiwan's largest cities were conducted using a trajectory transfer-coefficient air quality model. Correlation coefficients (r) between simulations and observations for the monthly means of the concentrations of SO₂, NO_x, PM_2.5 and PM₁₀ during the study periods at the 14 stations are 0.56, 0.63, 0.70 and 0.31, respectively. The sulfur control policy greatly reduced SO₂ concentration island-wide, a stringent emission standard put into place for gasoline vehicles reduced NO_x concentration along highways, and an emissions tax placed on construction sites, as well as a regular program for road-dust sweeping, reduced primary particulate matter. Among all of the pollution abatement policies implemented, the most effective method for reducing PM_2.5 concentrations in the three largest cities involved the reduction of fine ammonium sulfate aerosols from point sources (56–63% of net PM_2.5 reduction). The next largest reduction was attributed to a diminishment in primary PM_2.5 emanating from point sources (27–56% of net PM_2.5 reduction). Secondary particulate matter, especially sulfate, was reduced from distances up to 150 km leeward of major pollution point sources such as Taichung Power Plant.