Audrius Dėdelė

Development of Land Use Regression Models for Particle Composition in Twenty Study Areas in Europe

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM2.5) explaining on average between 67 and 79% of the concentration variance (R(2)) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R(2) ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R(2) under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE.

The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network

In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations.

The influence of proximity to city parks and major roads on the development of arterial hypertension

Aims: The aim of this study was to examine the relation between residential distance from major roads and city parks and the development of arterial hypertension. Methods: In this study, we used data of the population included in the MONICA survey (Lithuania). In total, 739 participants without arterial hypertension were selected for the present study. Poisson regression with robust variance estimation was used to evaluate the associations between distances from a major road and a city park expressed as categorical variables and the incidence of arterial hypertension, adjusting for individual risk factors. Results: For persons living at a distance of 151–300 m and > 300 m from city parks, relative risks were 1.49 (95% CI 1.03–2.15) and 1.51 (95% CI 1.10–2.07) respectively, as compared to a ≤ 150 m distance from city parks. For persons living further than 200 m away from a major road, the relative risk for the residential distance from city parks > 150 m was 2.36 (p = 0.029) times higher, as compared to a ≤ 150 m distance from city parks. We found that an increased risk of arterial hypertension was associated with the distance from a city park > 350 m and the distance to a major road < 200 m (RR = 1.48, 95% CI 1.03–2.12) as compared to living ≤ 350 m to a city park and ≥ 200 m away from a major road. Conclusions: An increase in the incidence of arterial hypertension was associated with a shorter distance to a major road and a greater distance to a city park. The effect modification of a shorter distance to a major road on the association between a greater distance to city parks and the incidence of arterial hypertension was identified.