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.     

Traffic pollution in a downtown site of Buenos Aires City

It has recently been recognized that air and noise pollution constitutes an extended problem over the densely populated city of Buenos Aires. Traffic emissions are of paramount concern, especially along narrow and main traffic arteries. In spite of these considerations, few systematic studies have been undertaken to evaluate the air quality in the metropolitan area of the city. In 1996, concentrations of carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂) and ozone (O₃) were simultaneously measured for the first time using a continuous monitoring station. This station was placed in a building at Belgrano Avenue, which is a heavy traffic street in the downtown area of the city (Bogo et al., Atmospheric Environment 33 (1999) 2587. In this work, we analyze the dependence of the measured primary pollutants, CO and the mixture of nitrogen oxides (NO_x), with meteorological conditions, traffic emissions and monitoring location. We compare the registered values with the results obtained from modeling the dispersion of the pollutants emitted from mobile and area sources. We also discuss the relevance of street canyon effects compared with background concentrations of these pollutants.     

Air quality measurements in urban green areas – a case study

The influence of traffic-induced pollutants (e.g. CO, NO, NO₂ and O₃) on the air quality of urban areas was investigated in the city of Essen, North Rhine-Westphalia (NRW), Germany. Twelve air hygiene profile measuring trips were made to analyse the trace gas distribution in the urban area with high spatial resolution and to compare the air hygiene situation of urban green areas with the overall situation of urban pollution. Seventeen measurements were made to determine the diurnal concentration courses within urban parks (summer conditions: 13 measurements, 530 30 min mean values, winter conditions: 4 measurements, 128 30 min mean values). The measurements were carried out during mainly calm wind and cloudless conditions between February 1995 and March 1996. It was possible to establish highly differentiated spatial concentration patterns within the urban area. These patterns were correlated with five general types of land use (motorway, main road, secondary road, residential area, green area) which were influenced to varying degrees by traffic emissions. Urban parks downwind from the main emission sources show the following typical temporal concentration courses: In summer rush-hour-dependent CO, NO and NO₂ maxima only occurred in the morning. A high NO₂/NO ratio was established during weather conditions with high global radiation intensities (K>800 W m⁻²), which may result in a high O₃ formation potential. Some of the values measured found in one of the parks investigated (Gruga Park, Essen, area: 0.7 km²), which were as high as 275 μg m⁻³ O₃ (30-min mean value) were significantly higher than the German air quality standard of 120 μg m⁻³ (30-min mean value, VDI Guideline 2310, 1996) which currently applies in Germany and about 20% above the maximum values measured on the same day by the network of the North Rhine–Westphalian State Environment Agency. In winter high CO and NO concentrations occur in the morning and during the afternoon rush-hour. The highest concentrations (CO=4.3 mg m⁻³, NO=368 μg m⁻³, 30-min mean values) coincide with the increase in the evening inversion. The maximum measured values for CO, NO and NO₂ do not, however, exceed the German air quality standards in winter and summer.     

Analysis of the air pollution climate at a central urban background site

Measurements of air pollutants from a background site in central London are analysed. These comprise hourly data for CO, NO, NO₂, O₃, SO₂ and PM₁₀ from 1996 to 2008 and particle number count from 2001 to 2008. The data are analysed in terms of long-term trends, annual, weekly and diurnal cycles, and autocorrelation and cross-correlation functions. CO, NO and NO₂ show a typical traffic-associated pattern with two daily peaks and lesser concentrations at the weekend. Particle number count and PM₁₀ show a similar cycle, but with smaller amplitude. Ozone has an annual cycle with a maximum in May, influenced by the spring maximum in background ozone, but the diurnal and weekly cycles are dominated by losses through reaction with nitric oxide. Particle number count shows a minimum corresponding with maximum air temperatures in August, whereas the CO, NO NO₂ and SO₂ show a minimum in June/July. There is a lower particle count to NO_x ratio at the background site compared to a central London kerbside site (Marylebone Road) and a seasonal pattern in particle count to NO_x and PM₁₀ ratios consistent with loss of nanoparticles by evaporation during atmospheric transport. Sulphur dioxide peaks in the morning in summer, but at midday in winter consistent with emissions from elevated sources mixing down from aloft as the diurnal mixed layer deepens. Implications for epidemiological studies of air quality and health are discussed. Sulphur dioxide, carbon monoxide, nitric oxide and nitrogen dioxide show clear downward trends over the measurement period, PM₁₀ declines initially before levels stabilised, and ozone concentrations increased.     

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.     

Assessment of nitrogen oxides and ground-level ozone behavior in a dense air quality station network: Case study in the Lesser Antilles Arc

ABSTRACT

This paper presents a study on ground-level ozone (O₃), nitrogen oxides (NO_x = NO + NO₂) concentrations, and their variabilities in the ambient air of three sites of a tropical archipelago that is moderately urbanized. Statistical analysis was performed on a quite complete (>80%) set of 5 years of measurements (2008–2012). There are few studies on those pollutants and their seasonal behavior in the Caribbean area, where pollution level and cities configuration are different from megacities. Analyses are focused on pollutant variations at the scale of the day, the week, and the seasons, using hourly data. The observations show that NO_x concentrations are more elevated during the wet season, whereas O₃ concentrations are higher in the dry season. Amplitudes of ozone cycles are strongly influenced by meteorological conditions (temperature, global radiation, and wind speed) and prevailing levels of NO_x. An ozone weekend effect is detected with the highest amplitude in the city, where anthropogenic activity is the lowest during the weekend. Due to the nature and the origin of pollutants, NO_x shows higher variability than O₃ in the time series. Our results evince the need for continuous measurements of volatile organic compounds (VOCs) in order to better quantify their contribution in O₃ formation in an insular context where numerous natural sources have been identified.

Implications: Statistical analyses of observed NO_x and O₃ concentrations for 5 years for a typical low industrialized site of the Caribbean area have been done. Air quality for those components is correct based on the standards of the World Health Orgaization, pollutant source spatial distributions, and level of industrialization. Observations show the same patterns as in megacities but also a strong impact of weather conditions and road traffic. Behaviors of O₃ cannot be fully explained without VOCs monitoring. Localization and type of AQS should be reconsidered to improve the accuracy of concentrations of the pollutant and better understand their behaviors.     

Exposure to hazardous air pollutants along Oba Akran road, Lagos-Nigeria

We measured toxic air pollutants along Oba Akran road in Lagos to evaluate pedestrian exposure. PM₁₀, CO, O₃, NO₂, SO₂, CH₄, noise, wind velocity and temperature were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM₁₀ (with an average of 274.6 μg m⁻³ for all samples) and CO (with an average of 19.27 ppm for all samples) was relatively high. CO is a traffic-related pollutant, so the influence of the local traffic emissions on CO levels is strong. The high concentration of the PM₁₀ measured at the three environments also suggests that the traffic is a major source of ultrafine particles. The overall average concentrations for the 72-day experimental period for SO₂, NO₂ and O₃ are 101.2, 62.5 and 0.32 ppb respectively, all of which are below the US national ambient air quality standards. Strong traffic impacts can be observed from the concentrations of some of these pollutants measured in these three environments. Most clear is a reflection of diesel truck traffic activity rich in black carbon concentrations. The diurnal variation of O₃ and NO₂ also showed that NO₂ was depleted by photochemically formed O₃ during the day and replenished at night as O₃ was destroyed. A multivariate statistical analysis (Principal Component Analysis, Factor Analysis) has been applied to a set of data in order to determine the contribution of different sources. It was found that the main principal components, extracted from the air pollution data, were related to gasoline combustion, oil combustion and ozone interactions.     

Partitioning, sources and variability of regional and local oxidant (OX = O3 + NO2) in a coastal rural area in the southwest of Iberian Peninsula

The purpose of this work is to investigate the behaviour and variability of oxidant levels (OX?=?NO₂?+?O₃), for the first time, in a rural coastal area in the southwest of the Iberian Peninsula, affected by several air masses types. Detailed database (built-up over the years 2008 to 2011, and containing around 500,000 data) from the Atmospheric Sounding Station “El Arenosillo” was used. The observed daily cycles of NO _x and OX were influenced by air masses coming from industrial and urban area. It can be seen that the concentration of OX is made up of a NO _x -independent ‘regional’ contribution (i.e. the O₃ background), and a linearly NO _x -dependent ‘local’ contribution from primary emissions, such as traffic. The local emission is very low in this area. Also, the regional contribution is similar to unpolluted sites and presents seasonal variation, being higher in May. However, our measurements showed that the proportion of OX in the form of NO₂ increases with the increase in NO _x concentration during the day. The higher proportion of NO₂ observed at night must be due to the conversion of NO to NO₂ by the NO?+?O₃ reaction. With regards to the source of the local NO _x -dependent contribution, it may be attributed to industrial emission, or the termolecular reaction 2NO?+?O₂?=?2NO₂, at high-NO _x levels and stagnant air during several days. Finally, we estimated the photolysis rate of NO₂, J _NO2, an important key atmospheric reaction coupled with ozone. We also present surface plots of annual variation of the daily mean NO _x and OX levels, which indicate that oxidants come from transport processes instead of local emissions associated as local photochemistry.     

A gas/aerosol air pollutants study over the urban area of Rome using a comprehensive chemical transport model

The aim of this study was to identify areas of potential relevant exposure to pollutants within Rome's urban core. To meet this goal, intensive field campaigns were conducted and simulations were performed, using the flexible air quality regional model (FARM), to study winter and summer pollution episodes. The simulations were performed using a complete emission inventory that included traffic flow model results of the Roman street network to better describe, with respect to the available diffuse national emission inventory, the hourly variation of traffic emissions in the city. The meteorological reconstruction was performed by means of both prognostic and diagnostic models by using experimental data collected during the field campaigns. To evaluate the capability of the FARM model to capture the main features of the selected episodes, a comparison of modelled results against observed air quality data for different pollutants was performed at urban and rural sites. FARM performed well in predicting ozone (O₃) and nitrogen dioxide (NO₂) concentrations, showing a good reproduction of both daily peaks and their diurnal variations. The model also showed a good capability to reproduce the magnitude of volatile alkane, aromatic and carbonyl compound concentrations. PM₁₀ model results revealed the tendency to under-predict the observed values. PM composition model results were compared with observed data, evidencing good results for elemental carbon (EC), nitrate (NO₃⁻) and ammonium (NH₄⁺), underestimation for sulphate (SO₄²⁻) and poor performance for organic matter (OM). The soil components of PM were found to be significantly under-predicted by the model, especially during Saharan dust episodes. Overall, the study results show large areas of high O₃ and PM₁₀ concentrations where levels of pollutants should be carefully monitored and population exposure evaluated.     

Ground level ozone concentrations and its association with NOx and meteorological parameters in Kathmandu valley, Nepal

This paper summarizes the results of a yearlong continuous measurements of gaseous pollutants, NO, NO₂, NO_x and O₃ in the ambient air at Kathmandu valley. Measured concentration of the pollutants in study area is a function of time. NO, NO₂ and O₃ peak occurred in succession in presence of sunlight. At the time of maximum O₃ concentration most of the NO_x are utilized. The diurnal cycle of ground level ozone concentrations, revealed mid-day peak with lower nocturnal concentrations and inverse relationship exists between O₃ and NO_x, which are evidences of photochemical O₃ formation. The observed ground level ozone during monsoon is slight lower than the pre-monsoon value. Further, lack of rainfall and higher temperature, solar radiation in the pre-monsoon have given rise to the gradual build up of ozone and it is lowest during winter. Ground level ozone concentrations measured during bandha (general strike) and weekend are 19% and 13% higher than those measured during weekdays. The most effective ozone abatement strategy for Kathmandu Valley may be control of NO_x emissions.     

Analysis of NO,NO2, O3 and NOx concentrations measured at a green area of Buenos Aires City during wintertime

We analyse the air quality data measured at a green area of Buenos Aires City (Argentina) during 38 days in winter. We study the relationships between ambient concentrations of nitric oxide (NO), nitrogen dioxide (NO₂), ozone (O₃) and nitrogen oxides (NO_x=NO+NO₂). The variation of the level of oxidant (OX=O₃+NO₂) with the NO_x is obtained. It can be seen that the level of OX at a given location is made up of two contributions: one independent and another dependent on the NO_x concentration. The first one can be considered as a regional contribution, equivalent to the background O₃ concentration and the second one as a local contribution that depends on the level of primary pollution. Local oxidant sources may include direct NO₂ emissions, the reaction of NO with O₂ at high-NO_x levels, and the emission of species that promote the conversion of NO to NO₂. The final category of emissions may include the nitrous acid (HONO) that is emitted directly in vehicle exhaust. Finally, we present a diurnal variation of the local as well as regional contributions and the dependence of the last one on wind direction.     

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.     

The effect of commuting microenvironment on commuter exposures to vehicular emission in Hong Kong

Vehicular exhaust emission has gradually become the major air pollution source in modern cities and traffic related exposure is found to contribute significantly to total human exposure level. A comprehensive survey was conducted from November 1995 to July 1996 in Hong Kong to assess the effect of traffic-induced air pollution inside different commuting microenvironments on commuter exposure. Microenvironmental monitoring is performed for six major public commuting modes (bus, light bus, MTR, railway, tram, ferry), plus private car and roadside pavement. Traffic-related pollutants, CO, NO_x, THC and O₃ were selected as the target pollutants. The results indicate that commuter exposure is highly influenced by the choice of commuting microenvironment. In general, the exposure level in decreasing order of measured pollutant level for respective commuting microenvironments are: private car, the group consisting light bus, bus, tram and pavement, MTR and train, and finally ferry. In private car, the CO level is several times higher than that in the other microenvironments with a trip averaged of 10.1 ppm and a maximum of 24.9 ppm. Factors such as the body position of the vehicle, intake point of the ventilation system, fuel used, ventilation, transport mode, road and driving conditions were used in the analysis. Inter-microenvironment, intra-microenvironment and temporal variation of CO concentrations were used as the major indicator. The low body position and low intake point of the ventilation system of the private car are believed to be the cause of higher intake of exhaust of other vehicles and thus result in high pollution level in this microenvironment. Compared with other metropolis around the world and the Hong Kong Air Quality Objectives (HKAQO), exposure levels of commuter to traffic-related air pollution in Hong Kong are relatively low for most pollutants measured. Only several cases of exceedence of HKAQO by NO₂ were recorded. The strong prevailing wind plus the channeling effect created by the harbor, the fuel used, the relative abundance of new cars and the successful implementation of the vehicle emission control program are factors that compensate the effect of the emission source strength and thus lead to low exposure levels.     

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.     

Assessment of traffic-related air pollution in the urban streets before and during the 2008 Beijing Olympic Games traffic control period

In order to investigate the air quality and the abatement of traffic-related pollution during the 2008 Olympic Games, we select 12 avenues in the urban area of Beijing to calculate the concentrations of PM₁₀, CO, NO₂ and O₃ before and during the Olympic traffic controlling days, with the OSPM model.Through comparing the modeled results with the measurement results on a representative street, the OSPM model is validated as sufficient to predict the average concentrations of these pollutants at street level, and also reflects their daily variations well, i.e. CO presents the similar double peaks as the traffic flow, PM₁₀ concentration is influenced by other sources. Meanwhile, the model predicts O₃ to stay less during the daytime and ascend in the night, just opposite to NO₂, which reveals the impact of photochemical reactions. In addition, the predicted concentrations on the windward side often exceed the leeward side, indicating the impact of the special street shape, as well as the wind.The comparison between the predicted street concentrations before and during the Olympic traffic control period shows that the overall on-road air quality was improved effectively, due to the 32.3% traffic flow reduction. The concentrations of PM₁₀, CO and NO₂ have reduced from 142.6 μg m⁻³, 3.02 mg m⁻³ and 118.7 μg m⁻³ to 102.0 μg m⁻³, 2.43 mg m⁻³ and 104.1 μg m⁻³. However, the different pollutants show diverse changes after the traffic control. PM₁₀ decreases most, and the reduction effect focusing on the first half-day even clears the morning peak, whereas CO and NO₂ have even reductions to minify the daily fluctuations on the whole. Opposite to the other pollutants, ozone shows an increase of concentration. The average reduction rate of PM₁₀, CO, NO₂ and O₃ are respectively 28%, 19.3%, 12.3% and −25.2%. Furthermore, the streets in east, west, south and north areas present different air quality improvements, probably induced by the varied background pollution in different regions around Beijing, along with the impact of wind force. This finding suggests the pollution control in the surrounding regions, not only in the urban area.     

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.     

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.     

Predicting residential indoor concentrations of nitrogen dioxide,fine particulate matter,and elemental carbon using questionnaire and geographic information system based data

Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system, and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households.As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3–4 day samples of nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) in 43 low SES residences across multiple seasons from 2003 to 2005. Elemental carbon (EC) concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally located ambient monitor.The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM_2.5 was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO₂ with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50 m buffer of a home and distance from a truck route as important contributors to indoor levels of NO₂ and EC, respectively. The Bayesian approach also highlighted the uncertanity in the models. We conclude that by utilizing public databases and focused questionnaire data we can identify important predictors of indoor concentrations for multiple air pollutants in a high-risk population.     

Determinants of perceived air pollution annoyance and association between annoyance scores and air pollution (PM2.5, NO2) concentrations in the European EXPOLIS study

Apart from its traditionally considered objective impacts on health, air pollution can also have perceived effects, such as annoyance. The psychological effects of air pollution may often be more important to well-being than the biophysical effects. Health effects of perceived annoyance from air pollution are so far unknown. More knowledge of air pollution annoyance levels, determinants and also associations with different air pollution components is needed. In the European air pollution exposure study, EXPOLIS, the air pollution annoyance as perceived at home, workplace and in traffic were surveyed among other study objectives. Overall 1736 randomly drawn 25–55-yr-old subjects participated in six cities (Athens, Basel, Milan, Oxford, Prague and Helsinki). Levels and predictors of individual perceived annoyances from air pollution were assessed. Instead of the usual air pollution concentrations at fixed monitoring sites, this paper compares the measured microenvironment concentrations and personal exposures of PM_2.5 and NO₂ to the perceived annoyance levels. A considerable proportion of the adults surveyed was annoyed by air pollution. Female gender, self-reported respiratory symptoms, downtown living and self-reported sensitivity to air pollution were directly associated with high air pollution annoyance score while in traffic, but smoking status, age or education level were not significantly associated. Population level annoyance averages correlated with the city average exposure levels of PM_2.5 and NO₂. A high correlation was observed between the personal 48-h PM_2.5 exposure and perceived annoyance at home as well as between the mean annoyance at work and both the average work indoor PM_2.5 and the personal work time PM_2.5 exposure. With the other significant determinants (gender, city code, home location) and home outdoor levels the model explained 14% (PM_2.5) and 19% (NO₂) of the variation in perceived air pollution annoyance in traffic. Compared to Helsinki, in Basel and Prague the adult participants were more annoyed by air pollution while in traffic even after taking the current home outdoor PM_2.5 and NO₂ levels into account.     

Major air pollutants in Bursa,Turkey: their levels,temporal changes,interactions, and sources

Bursa is one of the largest cities of Turkey and it hosts 17 organized industrial zones. Parallel to the increase in population, rapidly growing energy consumption, and increased numbers of transport vehicles have impacts on the air quality of the city. In this study, regularly calibrated automatic samplers were employed to get the levels of air pollution in Bursa. The concentrations of CH₄ and N-CH₄ as well as the major air pollutants including PM₁₀, PM_2.5, NO, NO₂, NO_x, SO₂, CO, and O₃, were determined for 2016 and 2017 calendar years. Their levels were 1641.62?±?718.25, 33.11?±?5.45, 42.10?±?10.09, 26.41?±?9.01, 19.47?±?16.51, 46.73?±?16.56, 66.23?±?32.265, 7.60?±?3.43, 659.397?±?192.73, and 51.92?±?25.63 µg/m³ for 2016, respectively. Except for O₃, seasonal concentrations were higher in winter and autumn for both years. O₃, CO, and SO₂ had never exceeded the limit values specified in the regulations yet PM₁₀, PM_2.5, and NO₂ had violated the limits in some days. The ratios of CO/NO_x, SO₂/NO_x, and PM_2.5/PM₁₀ were examined to characterize the emission sources. Generally, domestic and industrial emissions were dominated in the fall and winter seasons, yet traffic emissions were effective in spring and summer seasons. As a result of the correlation process between O_x and NO_x, it was concluded that the most important source of O_x concentrations in winter was NO_x and O₃ was in summer.