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.     

Assessing Spatial Variability of Ambient Nitrogen Dioxide in Montréal,Canada, with a Land-Use Regression Model

Abstract

The purpose of this study was to derive a land-use regression model to estimate on a geographical basis ambient concentrations of nitrogen dioxide (NO₂) in Montréal, Quebec, Canada. These estimates of concentrations of NO₂ will be subsequently used to assess exposure in epidemiologic studies on the health effects of traffic-related air pollution. In May 2003, NO₂ was measured for 14 consecutive days at 67 sites across the city using Ogawa passive diffusion samplers. Concentrations ranged from 4.9 to 21.2 ppb (median 11.8 ppb). Linear regression analysis was used to assess the association between logarithmic concentrations of NO₂ and land-use variables derived using the ESRI Arc 8 geographic information system. In univariate analyses, NO₂ was negatively associated with the area of open space and positively associated with traffic count on nearest highway, the length of highways within any radius from 100 to 750 m, the length of major roads within 750 m, and population density within 2000 m. Industrial land-use and the length of minor roads showed no association with NO₂. In multiple regression analyses, distance from the nearest highway, traffic count on the nearest highway, length of highways and major roads within 100 m, and population density showed significant associations with NO₂; the best-fitting regression model had a R² of 0.54. These analyses confirm the value of land-use regression modeling to assign exposures in large-scale epidemiologic studies.     

Comparison of the performances of land use regression modelling and dispersion modelling in estimating small-scale variations in long-term air pollution concentrations in a Dutch urban area

The performance of a Land Use Regression (LUR) model and a dispersion model (URBIS – URBis Information System) was compared in a Dutch urban area. For the Rijnmond area, i.e. Rotterdam and surroundings, nitrogen dioxide (NO₂) concentrations for 2001 were estimated for nearly 70 000 centroids of a regular grid of 100 × 100 m.A LUR model based upon measurements carried out on 44 sites from the Dutch national monitoring network and upon Geographic Information System (GIS) predictor variables including traffic intensity, industry, population and residential land use was developed. Interpolation of regional background concentration measurements was used to obtain the regional background. The URBIS system was used to estimate NO₂ concentrations using dispersion modelling. URBIS includes the CAR model (Calculation of Air pollution from Road traffic) to calculate concentrations of air pollutants near urban roads and Gaussian plume models to calculate air pollution levels near motorways and industrial sources. Background concentrations were accounted for using 1 × 1 km maps derived from monitoring and model calculations.Moderate agreement was found between the URBIS and LUR in calculating NO₂ concentrations (R = 0.55). The predictions agreed well for the central part of the concentration distribution but differed substantially for the highest and lowest concentrations. The URBIS dispersion model performed better than the LUR model (R = 0.77 versus R = 0.47 respectively) in the comparison between measured and calculated concentrations on 18 validation sites. Differences can be understood because of the use of different regional background concentrations, inclusion of rather coarse land use category industry as a predictor variable in the LUR model and different treatment of conversion of NO to NO₂.Moderate agreement was found between a dispersion model and a land use regression model in calculating annual average NO₂ concentrations in an area with multiple sources. The dispersion model explained concentrations at validation sites better.     

Biomonitoring of traffic-related nitrogen oxides in the Maurienne valley (Savoie, France), using purple moor grass growth parameters and leaf N/N ratio

Effects of traffic-related nitrogenous emissions on purple moor grass (Molinia caerulea (L.) Moench) transplants, used here as a new biomonitoring species, were assessed along 500 m long transects orthogonal to roads located in two open areas in the Maurienne valley (French Alps). Leaves were sampled during summer 2004 and 2005 for total N-content and ¹⁵N-abundance determination while nitrogen oxides (NO and NO₂) concentrations were determined using passive diffusion samplers. A significant and negative correlation was observed between plant total N-content, and ¹⁵N-abundance and the logarithm of the distance to the road axis. The strongest decreases in plant N parameters were observed between 15 and 100 m from road axis. They were equivalent to background levels at a distance of about 800 m from the roads. In addition, motor vehicle pollution significantly affected vegetation at road edge, as was established from the relationship between leaf ¹⁵N-abundance, total N-content and road traffic densities.     

Estimated long-term outdoor air pollution concentrations in a cohort study

Several recent studies associated long-term exposure to air pollution with increased mortality. An ongoing cohort study, the Netherlands Cohort Study on Diet and Cancer (NLCS), was used to study the association between long-term exposure to traffic-related air pollution and mortality. Following on a previous exposure assessment study in the NLCS, we improved the exposure assessment methods.Long-term exposure to nitrogen dioxide (NO₂), nitrogen oxide (NO), black smoke (BS), and sulphur dioxide (SO₂) was estimated. Exposure at each home address (N=21 868) was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in a national monitoring network. Regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables were used to estimate the urban component. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and on the nearest major road, and the sum of traffic intensity in a buffer of 100 m around each home address were assessed. Further, a quantitative estimate of the local component was estimated.The regression models to estimate the urban component explained 67%, 46%, 49% and 35% of the variances of NO₂, NO, BS, and SO₂ concentrations, respectively. Overall regression models which incorporated the regional, urban and local component explained 84%, 44%, 59% and 56% of the variability in concentrations for NO₂, NO, BS and SO₂, respectively.We were able to develop an exposure assessment model using GIS methods and traffic intensities that explained a large part of the variations in outdoor air pollution concentrations.     

Ultrafine particles near a major roadway in Raleigh,North Carolina: Downwind attenuation and correlation with traffic-related pollutants

Ultrafine particles (UFPs, diameter < 100 nm) and co-emitted pollutants from traffic are a potential health threat to nearby populations. During summertime in Raleigh, North Carolina, UFPs were simultaneously measured upwind and downwind of a major roadway using a spatial matrix of five portable industrial hygiene samplers (measuring total counts of 20–1000 nm particles). While the upper sampling range of the portable samplers extends past the defined “ultrafine” upper limit (100 nm), the 20–1000 nm number counts had high correlation (Pearson R = 0.7–0.9) with UFPs (10–70 nm) measured by a co-located research-grade analyzer and thus appear to be driven by the ultrafine range. Highest UFP concentrations were observed during weekday morning work commutes, with levels at 20 m downwind from the road nearly fivefold higher than at an upwind station. A strong downwind spatial gradient was observed, linearly approximated over the first 100 m as an 8% drop in UFP counts per 10 m distance. This result agreed well with UFP spatial gradients estimated from past studies (ranging 5–12% drop per 10 m). Linear regression of other vehicle-related air pollutants measured in near real-time (10-min averages) against UFPs yielded moderate to high correlation with benzene (R² = 0.76), toluene (R² = 0.49), carbon monoxide (R² = 0.74), nitric oxide (R² = 0.80), and black carbon (R² = 0.65). Overall, these results support the notion that near-road levels of UFPs are heavily influenced by traffic emissions and correlate with other vehicle-produced pollutants, including certain air toxics.     

The effects of congestions tax on air quality and health

The “Stockholm Trial” involved a road pricing system to improve the air quality and reduce traffic congestion. The test period of the trial was January 3–July 31, 2006. Vehicles travelling into and out of the charge cordon were charged for every passage during weekdays. The amount due varied during the day and was highest during rush hours (20 SEK = 2.2 EUR, maximum 60 SEK per day). Based on measured and modelled changes in road traffic it was estimated that this system resulted in a 15% reduction in total road use within the charged cordon. Total traffic emissions in this area of NO_x and PM10 fell by 8.5% and 13%, respectively. Air quality dispersion modelling was applied to assess the effect of the emission reductions on ambient concentrations and population exposure. For the situations with and without the trial, meteorological conditions and other emissions than from road traffic were kept the same. The calculations show that, with a permanent congestion tax system like the Stockholm Trial, the annual average NO_x concentrations would be lower by up to 12% along the most densely trafficked streets. PM10 concentrations would be up to 7% lower. The limit values for both PM10 and NO₂ would still be exceeded along the most densely trafficked streets. The total population exposure of NO_x in Greater Stockholm (35 × 35 km with 1.44 million people) is estimated to decrease with a rather modest 0.23 μg m^?3. However, based on a long-term epidemiological study, that found an increased mortality risk of 8% per 10 μg m^?3 NO_x, it is estimated that 27 premature deaths would be avoided every year. According to life-table analysis this would correspond to 206 years of life gained over 10 years per 100 000 people following the trial if the effects on exposures would persist. The effect on mortality is attributed to road traffic emissions (likely vehicle exhaust particles); NO_x is merely regarded as an indicator of traffic exposure. This is only the tip of the ice-berg since reductions are expected in both respiratory and cardiovascular morbidity. This study demonstrates the importance of not only assessing the effects on air quality limit values, but also to make quantitative estimates of health impacts, in order to justify actions to reduce air pollution.     

石家庄市道路交通环境NO_x污染水平及ARMA模型预测

选择石家庄市区代表性路段作为研究对象,对其交通环境空气中NOx的污染水平进行现状监测。基于Matlab软件建立拟合模型,对下一时期的NOx污染趋势进行预测。结果表明,石家庄市交通环境中NOx小时浓度介于0.047~0.237 mg/m3之间,呈早晚高,且下午明显低于上午的日变化规律;NOx日均浓度介于0.076~0.211 mg/m3之间,其浓度与车流量呈明显的正相关性。利用matlab软件建立的ARMA模型能够较好地预测道路交通环境空气中NOx的浓度变化趋势。     

Comparison of land-use regression models between Great Britain and the Netherlands

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO₂ and PM_10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL).Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country.A common model for GB and NL explained NO₂ concentrations well (adjusted R² 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction.The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models.     

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.     

Relating indoor NO2 levels to infant personal exposures

We report here the results of a field survey of personal nitrogen dioxide exposure (PNO₂) of infants and simultaneous indoor NO₂ levels from various points throughout the infants' homes. Personal nitrogen dioxide levels can be predicted by average room NO₂ concentrations when appropriately weighted by infant presence in the room. Bedroom NO₂ concentration alone presents an alternative predictor which is more suitable for use in large scale surveys. Because of the typical infant's peculiar time-location patterns, they receive most of their NO₂ exposures in bedrooms (65 %)and living rooms (32 %), while the kitchen (5 %) and outdoor environments (> 2%)contribute only a small fraction of daily exposure. Average NO₂ exposure during cooking periods can be predicted using passive samplers placed directly over stoves and hours of stove use time.     

A prediction-based approach to modelling temporal and spatial variability of traffic-related air pollution in Montreal, Canada

Concentrations of traffic-related air pollution can be highly variable at the local scale and can have substantial seasonal variability. This study was designed to provide estimates of intra-urban concentrations of ambient nitrogen dioxide (NO₂) in Montreal, Canada, that would be used subsequently in health studies of chronic diseases and long-term exposures to traffic-related air pollution. We measured concentrations of NO₂ at 133 locations in Montreal with passive diffusion samplers in three seasons during 2005 and 2006. We then used land use regression, a proven statistical prediction method for describing spatial patterns of air pollution, to develop separate estimates of spatial variability across the city by regressing NO₂ against available land-use variables in each of these three periods. We also developed a “pooled” model across these sampling periods to provide an estimate of an annual average. Our modelling strategy was to develop a predictive model that maximized the model R². This strategy is different from other strategies whose goal is to identify causal relationships between predictors and concentrations of NO₂.Observed concentrations of NO₂ ranged from 2.6 ppb to 31.5 ppb, with mean values of 12.6 ppb in December 2005, 14.0 ppb in May 2006, and 8.9 ppb in August 2006. The greatest variability was observed during May. Concentrations of NO₂ were highest downtown and near major highways, and they were lowest in the western part of the city. Our pooled model explained approximately 80% of the variability in concentrations of NO₂. Although there were differences in concentrations of NO₂ between the three sampling periods, we found that the spatial variability did not vary significantly across the three sampling periods and that the pooled model was representative of mean annual spatial patterns.     

Nitrogen dioxide distribution in street canyons

Weekly average NO₂ concentrations have been measured at over 40 locations within two canyonlike streets in central London, using passive diffusion tube samplers. A steady decline in concentrations with height is found, levels being close to local background at about 20 m. There is a rapid decline over the first 10–15 m horizontally from the centre of the road and concentrations are close to local background at a distance of 30 m. Concentrations are 10–15% higher close to traffic lights than they are 60 m upstream. Possible reasons for this are discussed. The results provide valuable information to assist in the selection of sites for chemiluminescence monitors, which are required to check compliance with the new European Council air quality standard for NO₂.     

Recent trends and projections of primary NO2 emissions in Europe

An assessment of recent trends in primary NO₂ emissions has been carried out for ten case study locations across the European Union. Estimates of the percentage of NO_x from road traffic emitted as primary NO₂ (f-NO₂) have been derived for 1995, 2000 and 2005 by combining the results of a literature survey of primary NO₂ emission factors for different vehicle types and technologies with an emission inventory. Estimates of f-NO₂ have also been derived from ambient monitoring data at roadside sites in each case study location using a model.The results of the analysis of trends show that f-NO₂ has increased in recent years and that the rate of increase has been greatest since 2000. f-NO₂ has increased from 8.6% in 2000 to 12.4% in 2004 as an average across the monitoring sites and from an average of 6.3% in 2000 to 10.6% in 2005 as an average of the emission inventory based calculations for the case study countries. f-NO₂ is predicted to increase further to an average of 19.6% in 2010 and 32.0% in 2020 as a result of the further penetration of exhaust after treatment technologies for diesel vehicles in the fleets. This increase is expected to be offset by the large reduction in NO_x emissions over this period, resulting in an increase in NO₂ emissions from road traffic to 2015, followed by a decline to close to 2004 levels by 2020. Estimates of future ambient NO₂ concentrations have also been calculated for the roadside monitoring sites included in the study. At 29 out of 45 of these sites the annual mean NO₂ limit value is predicted to be exceeded in 2010. At 22 of these sites, the annual mean concentration is expected to remain above the limit value until 2020 and beyond.     

A composite receptor and dispersion model approach for estimation of effective emission factors for vehicles

It is difficult to estimate vehicular emission factors at traffic junctions for use in dispersion modelling studies. Firstly, because the vehicles are in various modes of operation and secondly, it is difficult to delineate the effects of other contributing sources, mainly the effects of road dust and deposited constituents, which are very prominent at traffic junctions in India. Factor analysis-multiple regression (FA-MR), a receptor modelling technique has been used in this study for apportioning the contributing sources. The measurement data consist of one year's temporal variation of suspended particulate matter (SPM), analysed for its trace metal constituents, and two gaseous components NO₂ and SO₂ at two traffic junctions in Mumbai (India). FA-MR apportioned 40% of the observed SPM to road dust and 15% to vehicular sources. Of the total Pb observed in the SPM, FA-MR apportioned 60% to vehicular sources and 20% to road dust. The field-observed vehicular counts, meteorological parameters and road geometry were used in California line source dispersion model to estimate the effective vehicular emission factor for Pb at one traffic junction. This derived emission factor was used to predict the Pb concentration at second (independent observation) traffic junction. The result was found to be more satisfactory than using default emission factors obtained from literature. Similarly, effective vehicular emission factor for NO₂ was also evaluated for one site and tested for predicting concentrations at the other site.     

Modelling and assessing trends in traffic-related emissions using a generalised additive modelling approach

A generalised additive modelling (GAM) approach is used to model daily concentrations of nitrogen oxides (NO_X), nitrogen dioxide (NO₂), carbon monoxide (CO), benzene and 1,3-butadiene at a busy street canyon location in central London. The models were developed for the period July 1998–June 2005 using appropriate meteorological and road traffic covariates. For all models, the complex and localised wind-flow patterns resulting from the street canyon location of the monitoring site, which can be difficult to model deterministically, have a large influence on the model predictions. It is shown that GAMs built using simple covariates explain a large amount of the daily variation for these pollutants (mean r²=0.86). It is found that concentrations of benzene and 1,3-butadiene have declined in line with detailed calculations of emissions trends, with some evidence to suggest that reductions in benzene have been greater than estimated reductions in emissions. Although measured concentrations of NO_X have declined from 1998 to 2005, much of the decline appears to be associated with reductions in overall traffic and meteorological factors rather than reduced emissions of NO_X. Unadjusted NO_X trends show a 28.6% reduction (95% confidence interval from 21.2% to 35.8%) from 1998 to 2005, whereas meteorologically adjusted trends show a 19.3% decline (95% confidence interval from 14.8% to 23.5%) over this period. Analysis shows that there were a higher number of occasions in the early part of the time series that led to strong recirculation of exhaust emissions and higher NO_X concentrations at this location, thus affecting observed trends in concentration.     

Characteristics of re-suspended road dust and its impact on the atmospheric environment in Beijing

A sampling campaign of re-suspended road dust samples from 53 sites that could cover basically the entire Beijing, soil samples from the source regions of dust storm in August 2003, and aerosol samples from three representative sites in Beijing from December 2001 to September 2003, was carried out to investigate the characteristics of re-suspended road dust and its impact on the atmospheric environment. Ca, S, Cu, Zn, Ni, Pb, and Cd were far higher than its crustal abundances and Ca²⁺, SO₄²⁻, Cl⁻, K⁺, Na⁺, NO₃⁻ were major ions in re-suspended road dust. Al, Ti, Sc, Co, and Mg in re-suspended road dust were mainly originated from crustal source, while Cu, Zn, Ni, and Pb were mainly derived from traffic emissions and coal burning, and Fe, Mn, and Cd were mainly from industrial emissions, coal combustion and oil burning. Ca²⁺ and SO₄²⁻ mainly came from construction activities, construction materials and secondary gas-particle conversions, Cl⁻ and Na⁺ were derived from industrial wastewater disposal and chemical industrial emissions, and NO₃⁻ and K⁺ were from vehicle emissions, photochemical reactions of NO_X, biomass and vegetable burning. The contribution of mineral aerosol from inside Beijing to the total mineral aerosols was ∼30% in spring of 2002, ∼70% in summer of 2002, ∼80% in autumn of 2003, ∼20% in PM₁₀ and ∼50% in PM_2.5, in winter of 2002. The pollution levels of the major pollution species, Ca, S, Cu, Zn, Ni, Pb, Fe, Mn, and Cd in re-suspended road dust reached ∼76%, ∼87%, ∼75%, ∼80%, ∼82%, ∼90%, ∼45%, ∼51%, and ∼94%, respectively. Re-suspended road dust from the traffic and construction activities was one of the major sources of pollution aerosols in Beijing.     

Investigations of emissions and heterogeneous formation of HONO in a road traffic tunnel

Simultaneous measurements of nitrous acid (HONO) and nitrogen dioxide (NO₂) using a differential optical absorption spectroscopy system, nitrogen oxide (NO) by an in situ chemiluminescence analyser and carbon dioxide (CO₂) by a gas chromatographic technique were carried out in the Wuppertal Kiesbergtunnel. At high traffic density HONO concentrations of up to 45 ppbV were observed. However, at low traffic density unexpectedly high HONO concentrations of up to 10 ppbV were measured caused by heterogeneous HONO formation on the tunnel walls. In addition to the tunnel campaigns, emission measurements of HONO, NO₂, NO and CO₂ from different single vehicles (a truck, a diesel and a gasoline passenger car) were also performed. For the correction of the HONO emission data, the heterogeneous HONO formation on the tunnel walls was quantified by two different approaches (a) in different NO₂ emission experiments in the tunnel without traffic and (b) on tunnel wall residue in the laboratory. The HONO concentration corrected for heterogeneous formation on the tunnel walls, in relation to the CO₂ concentration can be used to estimate the amount of HONO, which is directly emitted from the vehicle fleet. From the measured data, emission ratios (e.g. HONO/NO_x) and emission indices (e.g. mg HONO kg⁻¹ fuel) were calculated. The calculated emission index of 88±18 mg HONO kg⁻¹ fuel allows an estimation of the HONO emission rates from traffic into the atmosphere. Furthermore, the heterogeneous formation of HONO from NO₂ on freshly emitted exhaust particles is discussed.     

Spatial Differences in Outdoor PM10 Mass and Aerosol Composition in Mexico City

Abstract

Twenty-five MiniVol samplers were operated throughout the Mexico City metropolitan region from February 22 through March 22, 1997, to evaluate the variability of PM₁₀ concentrations and composition. The highest PM₁₀ concentrations were found in neighborhoods with unpaved or dirty roads, and elements related to crustal material were the main cause of differences from nearby (<200 m) monitors that were not adjacent to the roadbed. SO₄ ^2?concentrations were homogeneous across the city. SO₄ ^2?measured at the city boundaries was about two-thirds of the concentrations measured within the urbanized area, indicating that most SO₄ ^2? is of regional origin. Elemental carbon (EC) and organic carbon (OC) concentrations were highly variable, with higher concentrations in areas that had high diesel traffic and older vehicles. Spatial correlations among PM₁₀ concentrations were high, even though absolute concentrations were variable, indicating a common effect of meteorology on the concentration or dispersion of local emissions.