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Since 2003, Quito, the Capital of Ecuador, has implemented an air quality monitoring system that records hourly urban background concentrations of CO, NOx, NO2, O3, PM2.5, PM10 and SO2, as well as meteorological data. However, currently no modelling system for forecasting or estimating hourly concentrations of air pollution at background level for Quito has been implemented. This study evaluates the application of the UBM model, developed by Aarhus University, for calculating pollutant levels at the location of six monitoring stations. Air pollution is estimated based on emissions inventories, regional background and meteorological data for year 2009. Emissions are scaled, using calibration factors, to ensure computed concentrations fit with observed values based on the analysis of emissions inventories produced in Quito and other cities in Latin-American. Output values from the UBM model are graphically and statistically evaluated against measurements. Results show that, for Quito, the UBM model successfully estimates the hourly concentrations for CO, NO2, NOx, O3 and PM2.5. These findings confirm the applicability of UBM to model air pollution at urban background level in Quito. Best performance of UBM is achieved when using meteorological data retrieved from the corresponding location of simulation, although satisfactory results are obtained when the modelling for all locations is conducted applying meteorological data derived from only one location. Applying emissions and calibration factors from year 2009 with corresponding meteorology data from 2008 and 2010, the UBM model shows similar performance as for the year 2009. Unsatisfactory results for estimating SO2 concentrations suggest that the emissions data must be revised.

Background: Air pollution is suspected to cause lung cancer. The purpose was to investigate whether the concentration of nitrogen oxides (NOx) at the residence, used as an indicator of air pollution from traffic, is associated with risk for lung cancer. Methods: We identified 679 lung cancer cases in the Danish Cancer Registry from the members of three prospective cohorts and selected a comparison group of 3,481 persons from the same cohorts in a case-cohort design. Residential addresses from January 1, 1971, were traced in the Central Population Registry. The NOx concentration at each address was calculated by dispersion models, and the time-weighted average concentration for all addresses was calculated for each person. We used Cox models to estimate incidence rate ratios after adjustment for smoking (status, duration, and intensity), educational level, body mass index, and alcohol consumption. Results: The incidence rate ratios for lung cancer were 1.30 [95% confidence interval (95% CI), 1.07-1.57] and 1.45 (95% CI, 1.12-1.88) for NOx concentrations of 30 to 72 and >72 μg/m3, respectively, when compared with Conclusion: The study showed a modest association between air pollution from traffic and the risk for lung cancer. Impact: This study points at traffic as a source of carcinogenic air pollution and stresses the importance of strategies for reduction of population exposure to traffic-related air pollution. Cancer Epidemiol Biomarkers Prev; 19(5); 1284–91. ©2010 AACR.

Modelling of ambient particle number concentrations (PNC) has been implemented in the Danish air quality modelling system DEHM/UBM/AirGIS and evaluated with long-term measurements. We implemented particle dynamical processes in the regional scale model DEHM using the M7 aerosol dynamics module (presented in the accompanying article by Frohn et al., 2021), and we developed models for PNC at the local scale (UBM) and street scale (OSPM), in a first approximation without including the particle dynamics as presented in this article. Outdoor concentration estimates are provided at the front door of all residential address locations in Denmark for the past 40 years (1979–2018) with a spatial resolution of 1 km × 1 km taking all emission sectors in Denmark into account and additionally at the street location, with significant traffic (>500 vehicles/day). We evaluated our model with up to 18-year long measurement time series of particle number size distributions (PNSD) at Danish street, urban and rural background stations. Two particle size ranges were used for evaluation: PNC >10 (count of particles with diameter larger than 10 nm) and PNC 30_250 (diameter range 30–250 nm), in order to exclude nucleation events from the measurements and to obtain a consistent long-term measured time series. When comparing our model estimates with PNC 30_250 measurements, we obtain Pearson correlation coefficients (R p) in the range 0.39–0.95 depending on station location (street, urban background, rural) and averaging time (hour, day, month, year). The highest correlations were found for yearly averages at a monitoring station located at a street with dense traffic (R p = 0.95) whereas shorter time averages and comparisons with monitoring stations at urban and rural background locations provided lower correlations. The model performance for PNC in terms of correlation coefficients with respect to measurements is comparable to the performance for other pollutants such as NO X, PM 2.5 and better than the performance for PM 10. The model generally overestimated the observed concentrations, Normalized Mean Bias (NMB) was in the range 6%–190% compared to PNC >10 and 90%–290% compared to PNC 30_250. These relatively high NMBs are probably caused by uncertainties in the modelling process, especially the estimation of particle number emissions, which largely determine the ambient concentrations of PNC. Furthermore, uncertainties might as well originate from the complexity of modelling particle dynamical processes accurately and the great challenges in performing long-term PNC measurements. The presented model can estimate PNC at all Danish addresses over the last 40 years with a 1-h time resolution. The data seem to provide a good indication of the relative differences in PNC at Danish addresses.

BACKGROUND. Previous studies have shown associations between air pollution and risk for lung cancer. OBJECTIVE. To investigate whether traffic and the concentration of nitrogen oxides (NOx) at the residence are associated with risk for lung cancer. METHODS. We identified 592 lung cancer cases in the Danish Cancer Registry among 52 970 members of the Diet Cancer and Health cohort and traced residential addresses from 1 January 1971 in the Central Population Registry. We calculated the NOx concentration at each address by dispersion models, and calculated the time-weighted average concentration for all addresses for each person. We used Cox models to estimate incidence rate ratios (IRRs) after adjustment for smoking (status, duration and intensity), environmental tobacco smoke, length of school attendance, occupation and dietary intake of fruit. RESULTS. For the highest compared with the lowest quartile of NOx concentration at the residence we found an IRR for lung cancer of 1.30 (95% confidence interval (CI): 1.05-1.61) and the IRR for lung cancer in association with living within 50 m of a major road (> 10 000 vehicles per day) was 1.21 (95% CI: 0.95-1.55). The results showed tendencies of stronger associations among non-smokers, among those with a relatively low fruit intake and among those with a longer school attendance; only length of school attendance modified the effect significantly. CONCLUSIONS. This study supports that risk for lung cancer is associated with different markers of air pollution from traffic near the residence.

Three years of aerosol measurements from four European cities were analysed to identify and quantify the parameters influencing the particle number size distribution (NSD) at different measurement sites (Copenhagen, Helsinki, Leipzig, London). A ‘triple-site’ approach was established with data from a roadside, an urban background and a rural measurement station, which was available for each city. The NSD measurements were conducted over a diameter size range of 8–700 nm. The average annual total number concentrations varied between 1700 cm−3 (Finnish rural site) and 23,000 particles cm−³ (London roadside). Highest variability on the diurnal course was found for the roadside sites and on the seasonal course for the rural sites. A first identification of the influencing parameters was found using correlation analysis. The most dominating factors were then quantified using a multiple linear regression approach documenting the highest influence for daytime (45%) followed by wind direction (18%), season (12%), wind speed (11%), temperature (8%) and solar radiation (6%), on average. The variation of influence between the different cities is analysed and discussed. Subsequently NSDs were modelled using the regression approach in order to verify how well the parameters are capable of ‘explaining’ the actual NSD, showing best performance for roadside NSD with correlation coefficients between 0.65 and 0.8 and limited performance for the rural sites (0.5–0.6).

Background and aims: Vehicle engine exhaust includes ultrafine particles with a large surface area and containing absorbed polycyclic aromatic hydrocarbons, transition metals and other substances. ...

DCE – Nationalt Center for Miljø og Energi, Aarhus Universitet har for Frederiksberg Kommune udarbejdet en kortlægning af luftforurening (Jensen et al., 2020a) og et virkemiddelkatalog for forbedring af luftkvaliteten (Jensen et al., 2020b). De to rapporter indgår som fagligt baggrundsmateriale for Frederiksberg Kommunes egen formulering af en luftforureningsstrategi - STRATEGI FOR REN LUFT – 2030, som blev udgivet i august 2021 (Frederiksberg Kommune, 2021). Artiklen beskriver kortlægningen af luftforureningen i Frederiksberg Kommune og dens helbredsmæssige konsekvenser. Kortlægningen indeholder en luftkvalitetsvurdering med geografisk beskrivelse af luftkvaliteten; en kildeopgørelse, som beskriver emissionen fordelt på kilder, og kildernes bidrag til luftkvaliteten; samt luftforureningens helbredseffekter og tilhørende samfundsmæssige omkostninger (eksterne omkostninger). Endvidere præsenteres et virkemiddelkatalog for reduktion af luftforurening i Frederiksberg Kommune med fokus på kommunale virkemidler inden for trafik, og en konsekvensvurdering af virkemidlerne. Virkemidler beskrives inden for indsatsområderne: By- og trafikplanlægning, elektrificering af transport, økonomiske virkemidler og regulering af transport, samt ikke-kildebaserede virkemidlers rensning af miljøet. Væsentlige lokale kilder til luftforurening er trafik og brændeovne, hvor denne artiklen alene omhandler trafik., Proceedings from the Annual Transport Conference at Aalborg University, Vol. 28 No. 1 (2021): Proceedings from the Annual Transport Conference at Aalborg University

The Operational Street Pollution Model (OSPM®) has been widely applied in the air pollution community for more than two decades. In the presented work some of the parameterisations used by OSPM have been revised and tested against several street datasets. We present an air pollution "screening" calculation in which OSPM, in combination with the urban background model UBM, was applied for all address locations in Denmark along major roads and results (annual means for NO2, PM10 and PM2.5) are presented on an interactive map on the internet.

Traffic is one of the major sources of harmful airborne particles worldwide. To relate exposure to adverse health effects it is important to determine the deposition probability of the inhaled particles in the human respiratory tract. The size-dependent deposition of 12-580 nm particles was measured with a novel setup in 9 healthy subjects breathing by mouth on the windward side of a busy street in Copenhagen, Denmark. The aerosol was characterized both at the curbside and, to obtain the background concentration, at rooftop level. Particle hygroscopicity, a key parameter affecting respiratory tract deposition, was also measured at the same time of exposure. The total deposition fraction of the curbside particles in the range 12-580 nm was 0.60 by number, 0.29 by surface area, and 0.23 by mass. The deposition fractions of the "traffic exhaust" contribution, calculated as the hydrophobic fraction of the curbside particles, was 0.68, 0.35, and 0.28 by number, surface area, and mass, respectively. The deposited amount of traffic exhaust particles was 16 times higher by number and 3 times higher by surface area compared to the deposition of residential biofuel combustion particles investigated previously (equal inhaled mass concentrations). This was because the traffic exhaust particles had both a higher deposition probability and a higher number and surface area concentration per unit mass. To validate the results, the respiratory tract deposition was estimated by using the well-established ICRP model. Predictions were in agreement with experimental results when the effects of particle hygroscopicity were considered in the model.

International audience; 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 2003/2004. 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.