Aims/hypothesis
The aim of this study was to investigate whether air pollution from traffic at a residence is associated with mortality related to type 1 or type 2 diabetes.
Methods
We followed up ...52,061 participants in the Danish Diet, Cancer and Health cohort for diabetes-related mortality in the nationwide Register of Causes of Death, from baseline in 1993–1997 up to the end of 2009, and traced their residential addresses since 1971 in the Central Population Registry. We used dispersion-modelled concentration of nitrogen dioxide (NO
2
) since 1971 and amount of traffic at the baseline residence as indicators of traffic-related air pollution and used Cox regression models to estimate mortality-rate ratios (MRRs) with adjustment for potential confounders.
Results
Mean levels of NO
2
at the residence since 1971 were significantly associated with mortality from diabetes. Exposure above 19.4 μg/m
3
(upper quartile) was associated with a MRR of 2.15 (95% CI 1.21, 3.83) when compared with below 13.6 μg/m
3
(lower quartile), corresponding to an MRR of 1.31 (95% CI 0.98, 1.76) per 10 μg/m
3
NO
2
after adjustment for potential confounders.
Conclusions/interpretation
This study suggests that traffic-related air pollution is associated with mortality from diabetes. If confirmed, reduction in population exposure to traffic-related air pollution could be an additional strategy against the global public health burden of diabetes.
Non-exhaust traffic induced emissions are a major source of particle mass in most European countries. This is particularly important in Nordic and Alpine countries where winter time road traction ...maintenance occurs, e.g. salting and sanding, and where studded tyres are used. In this paper, Part 1, the road dust sub-model of a coupled road dust and surface moisture model (NORTRIP) is described. The model provides a generalised process based formulation of the non-exhaust emissions, with emphasis on the contribution of road wear, suspension, surface dust loading and the effect of road surface moisture (retention of wear particles and suspended emissions). The model is intended for use as a tool for air quality managers to help study the impact of mitigation measures and policies. We present a description of the road dust sub-model and apply the model to two sites in Stockholm and Copenhagen where seven years of data with surface moisture measurements are available. For the site in Stockholm, where studded tyres are in use, the model predicts the PM10 concentrations very well with correlations (R2) in the range of R2 = 0.76–0.91 for daily mean PM10. The model also reproduces well the impact of a reduction in studded tyres at this site. For the site in Copenhagen the correlation is lower, in the range 0.44–0.51. The addition of salt is described in the model and at both sites this leads to improved correlations due to additional salt emissions. For future use of the model a number of model parameters, e.g. wear factors and suspension rates, still need to be refined. The effect of sanding on PM10 emissions is also presented but more information will be required before this can be confidently applied for management applications.
•A coupled road dust and surface moisture model is presented and applied.•The surface moisture strongly determines the temporal variation of the road dust emissions.•The model predicts very well the temporal variation of suspended road dust emissions.•Time scales for suspension are significantly longer than previous estimates.•The model calculates the contribution of road salting to the emitted PM10 concentrations.
Non-exhaust traffic induced emissions are a major source of airborne particulate matter in most European countries. This is particularly important in Nordic and Alpine countries where winter time ...road traction maintenance occurs, e.g. salting and sanding, and where studded tyres are used. Though the total mass generated by wear sources is a key factor in non-exhaust emissions, these emissions are also strongly controlled by surface moisture conditions. In this paper, Part 2, the road surface moisture sub-model of a coupled road dust and surface moisture model (NORTRIP) is described. We present a description of the road surface moisture part of the model and apply the coupled model to seven sites in Stockholm, Oslo, Helsinki and Copenhagen over 18 separate periods, ranging from 3.5 to 24 months. At two sites surface moisture measurements are available and the moisture sub-model is compared directly to these observations. The model predicts the frequency of wet roads well at both sites, with an average fractional bias of −2.6%. The model is found to correctly predict the hourly surface state, wet or dry, 85% of the time. From the 18 periods modelled using the coupled model an average absolute fractional bias of 15% for PM10 concentrations was found. Similarly the model predicts the 90'th daily mean percentiles of PM10 with an average absolute bias of 19% and an average correlation (R2) of 0.49. When surface moisture is not included in the modelling then this average correlation is reduced to 0.16, demonstrating the importance of the surface moisture conditions. Tests have been carried out to assess the sensitivity of the model to model parameters and input data. The model provides a useful tool for air quality management and for improving our understanding of non-exhaust traffic emissions.
•A coupled road dust and surface moisture non-exhaust emission model is applied to seven sites over 18 different periods.•Surface moisture is shown to be the dominant cause of variability of the road dust emissions.•The model explains half the variability seen in roadside PM10 measurements.•Salt is found to have an impact on the surface moisture and on the variability of emissions.
This paper presents measurements of traffic-generated gas and particle pollution at two sites, one near a major highway and one near a busy urban street in Copenhagen, Denmark. Both sites were ...equipped for a 4-week period with a set of two measurement stations, one close to the kerbside and one background station. Measurements were carried out from March to April~2008, investigating NOx concentrations, submicrometer particle number size distribution (size range 10–700 nm), particle mass (PM2.5, PM10), and meteorological parameters. In this study we also estimate the emission factors for NOx, particle number and particle mass using measured traffic volume and dilution rate calculated by the Operational Street Pollution Model (WinOSPM). The mean concentrations of most of the measured pollutants are similar for the highway and the urban kerbside stations due to similar traffic density. The average concentrations of NOx are 142 μg m−3 and 136 μg m−3 for the highway and the urban kerbside stations, respectively. These values are about 5 times higher compared to the corresponding background values. The average particle number concentration is 24 900 particles cm−3 and 27 100 particles cm−3 for the highway and the urban kerbside stations, respectively, and these values exceed those measured at the background stations by a factor of 3 to 5. The temporal variation of the traffic contribution (difference of kerbside and background concentrations) is analysed for NOx, particle number and mass, and it follows the traffic pattern at the urban and the highway sites. Emission factors for particle number are found to be quite similar at both sites, (215±5) 1012 particles veh−1 km−1 for the highway and (187±3) 1012 particles veh−1 km−1 for the urban site. Heavy duty vehicles (HDVs) are found to emit about 20 times more particles than light duty vehicles (LDVs), which is in good agreement with other published studies. Emission factors are also determined for individual particle modes identified in the size spectra. Average fleet emission factors for PM2.5 at the highway and the urban site are 29 mg veh−1 km−1 and 46 mg veh−1 km−1, respectively. The estimated particle number and size spectra emission factors will provide valuable input for air quality and particle dispersion modelling near highways and in urban areas.
Objectives:To study the association between short-term exposure to ultrafine particles and morbidity in Copenhagen, Denmark.Methods:We studied the association between urban background levels of the ...total number concentration of particles (NCtot, 6–700 nm in diameter) measured at a single site (15 May 2001 to 31 December 2004) and hospital admissions due to cardiovascular (CVD) and respiratory disease (RD) in the elderly (age ⩾65 years), and due to asthma in children (age 5–18 years). We examined these associations in the presence of PM10, PM2.5 (particulate matter <10 and 2.5 µm in diameter, respectively) and ambient gasses. We utilised data on size distribution to calculate NCtot for four modes with median diameters 12, 23, 57 and 212 nm, and NC100 (number concentration of particles <100 nm in diameter) and examined their associations with health outcomes. We used a time series Poisson generalised additive model adjusted for overdispersion, season, day of the week, public holidays, school holidays, influenza, pollen and meteorology, with up to 5 days’ lagged exposure.Results and conclusions:The adverse health effects of particulate matter on CVD and RD hospital admissions in the elderly were mainly mediated by PM10 and accumulation mode particles with lack of effects for NC100. For paediatric asthma, accumulation mode particles, NC100 and nitrogen oxides (mainly from traffic related sources) were relevant, whereas PM10 appeared to have little effect. Our results suggest that particle volume/mass from long-range transported air pollution is relevant for CVD and RD admissions in the elderly, and possibly particle numbers from traffic sources for paediatric asthma.
Number fractions of externally mixed particles of four different sizes (30, 50, 80, and 150 nm in diameter) were measured using a Volatility Tandem DMA. The system was operated in a street canyon ...(Eisenbahnstrasse, EI) and at an urban background site (Institute for Tropospheric Research, IfT), both in the city of Leipzig, Germany as well as at a rural site (Melpitz (ME), a village near Leipzig). Intensive campaigns of 3–5 weeks each took place in summer 2003 as well as in winter 2003/04. The data set thus obtained provides mean number fractions of externally mixed soot particles of atmospheric aerosols in differently polluted areas and different seasons (e.g. at 80 nm on working days, 60% (EI), 22% (IfT), and 6% (ME) in summer and 26% (IfT), and 13% (ME) in winter). Furthermore, a new method is used to calculate the size distribution of these externally mixed soot particles from parallel number size distribution measurements. A decrease of the externally mixed soot fraction with decreasing urbanity and a diurnal variation linked to the daily traffic changes demonstrate, that the traffic emissions have a significant impact on the soot fraction in urban areas. This influence becomes less in rural areas, due to atmospheric mixing and transformation processes. For estimating the source strength of soot particles emitted by vehicles (veh), soot particle emission factors were calculated using the Operational Street Pollution Model (OSPM). The emission factor for an average vehicle was found to be (1.5±0.4)·1014 #(km·veh). The separation of the emission factor into passenger cars ((5.8±2)·1013} #(km·veh)) and trucks ((2.5±0.9)·1015 #(km·veh)) yielded in a 40-times higher emission factor for trucks compared to passenger cars.
There is limited evidence for the role of air pollution in the development and triggering of wheezing symptoms in young children. A study was undertaken to examine the effect of exposure to air ...pollution on wheezing symptoms in children under the age of 3 years with genetic susceptibility to asthma.
Daily recordings of symptoms were obtained for 205 children participating in the birth cohort study Copenhagen Prospective Study on Asthma in Children and living in Copenhagen for the first 3 years of life. Daily air pollution levels for particulate matter <10 microm in diameter (PM(10)) and the concentrations of ultrafine particles, nitrogen dioxide (NO(2)), nitrogen oxide (NO(x)) and carbon monoxide (CO) were available from a central background monitoring station in Copenhagen. The association between incident wheezing symptoms and air pollution on the concurrent and previous 4 days was estimated by a logistic regression model (generalised estimating equation) controlling for temperature, season, gender, age, exposure to smoking and paternal history of asthma.
Significant positive associations were found between concentrations of PM(10), NO(2), NO(x), CO and wheezing symptoms in infants (aged 0-1 year) with a delay of 3-4 days. Only the traffic-related gases (NO(2), NO(x)) showed significant effects throughout the 3 years of life, albeit attenuating after the age of 1 year.
Air pollution related to traffic is significantly associated with triggering of wheezing symptoms in the first 3 years of life.
The influence of residential wood-combustion on local air quality was studied during two periods in 2002 and 2003/04 in a small rural town with widespread use of wood combustion for heating. During ...one 6-week winter period, particle levels (PM
2.5) in the residential area were about 4
μg
m
−3 higher than at a nearby background site. This was comparable to the local traffic contribution observed at a busy street (about 70,000 vehicles per day) in the city of Copenhagen. The diurnal variation in the residential area showed increased particle levels (PM
2.5) in the evening and night as expected from local heating sources. Particle size distributions showed highest volume concentrations of particles with diameters of 400–500
nm, and the diurnal variation of particle volume was similar to PM
2.5. The particle measurements were supported by measurements of combustion gases in both the residential area and at a background site. Receptor modelling and source apportionment of the results confirmed that the most important sources to particles were long-range transport (both organic and inorganic compounds) and local heating (particularly organic compounds) in addition to regional traffic emissions. Local wood combustion sources affected especially the organic particle component.
Traffic pollution modelling and emission data Berkowicz, R.; Winther, M.; Ketzel, M.
Environmental modelling & software : with environment data news,
04/2006, Letnik:
21, Številka:
4
Journal Article
Recenzirano
Evaluation of traffic pollution in streets requires basically information on three main factors: traffic emissions, the meteorological conditions and the street surroundings. Dispersion models exist ...with various degree of sophistication, which are able to properly describe the dispersion conditions, and thus to predict the relationships between emissions and the concentration levels in the street. However, for real-world applications, the model calculations must be based on “true” emission data, and their estimation is not trivial. Significant uncertainty is still connected with emission data. Examining the relationships between model predictions and measurements with respect to the meteorological conditions and inter-relationships between different pollution components allows quantitative evaluation of the traffic emissions. This methodology is illustrated using the Danish Operational Street Pollution Model – OSPM, and time series of traffic related pollutants. Street level concentrations of NO
x
and CO are calculated using OSPM as the dispersion model and emission data estimated by the widely used COPERT methodology. Comparison with measurements shows significant underestimation of the pollution concentrations and especially the CO/NO
x
ratio. An alternative set of traffic emission factors, using a more simplified vehicle classification methodology, provides better agreement with the measured concentrations. Evaluation of these results provides some guidance on the necessary modifications of the “real-world” traffic emission factors.
We have slightly refined, evaluated and tested a mathematical model for predicting the vehicular suspension emissions of PM₁₀. The model describes particulate matter generated by the wear of road ...pavement, traction sand, and the processes that control the suspension of road dust particles into the air. However, the model does not address the emissions from the wear of vehicle components. The performance of this suspension emission model has been evaluated in combination with the street canyon dispersion model OSPM. We used data from a measurement campaign that was conducted in the street canyon Runeberg Street in Helsinki from 8 January to 2 May, 2004. The model reproduced fairly well the seasonal variation of the PM₁₀ concentrations, also during the time periods, when studded tyres and anti-skid treatments were commonly in use. For instance, the index of agreement (IA) was 0.83 for the time series of the hourly predicted and observed concentrations of PM₁₀. The predictions of the model were found to be sensitive to precipitation and street traction sanding. The main uncertainties in the predictions are probably caused by (i) the cleaning processes of the streets, which are currently not included in the model, (ii) the uncertainties in the estimation of the sanding days, and (iii) the uncertainties in the evaluation of precipitation. This study provides more confidence that this model could potentially be a valuable tool of assessment to evaluate and forecast the suspension PM₁₀ emissions worldwide. However, a further evaluation of the model is needed against other datasets in various vehicle fleet, speed and climatic conditions.
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