Michael Memmesheimer

Modal aerosol dynamics model for Europe: development and first applications

Abstract The Modal Aerosol Dynamics model for Europe (MADE) has been developed as an extension to mesoscale chemistry transport models to allow a more detailed treatment of aerosol effects in these models. Due to the complexity of the atmospheric aerosol system an approach has been chosen which is, on the one hand, fast enough for this application and, on the other, provides sufficient information on the particle size distribution. In MADE, which is developed from the regional particulate model (RPM) the particle size distribution of the submicrometer aerosol is represented by two overlapping lognormal modes. The chemical composition is currently treated in the sulfate–nitrate–ammonium and water system. Sources for aerosol particles are modelled through nucleation and emission. Coagulation, condensation, transport and deposition are considered as processes modifying the aerosol population in the atmosphere. Aerosol dynamics calculations are performed on-line within the chemistry-transport model. Process studies with a one-dimensional version of the model system are used to investigate the relative importance of the individual aerosol dynamic processes and the important links between between the gas and aerosol phase as well as meteorological parameters. Results from a first three-dimensional application of the fully coupled system of MADE and the European Air Pollution Dispersion model system (EURAD) are presented, showing the suitability of MADE as an aerosol dynamics model even within complex air quality models. The application of the new aerosol model provides information on particle number, size and surface area in addition to the chemical concentration fields, which can be used to study a variety of aerosol-related air pollution issues in subsequent studies.

Residential Exposure to Traffic Is Associated With Coronary Atherosclerosis

Background— Long-term exposure to fine-particulate-matter (PM2.5) air pollution may accelerate the development and progression of atherosclerosis. We investigated the associations of long-term residential exposure to traffic and fine particulate matter with the degree of coronary atherosclerosis. Methods and Results— We used baseline data on 4494 participants (age 45 to 74 years) from the German Heinz Nixdorf Recall Study, a population-based, prospective cohort study that started in 2000. To assess exposure differences, distances between residences and major roads were calculated, and annual fine particulate matter concentrations, derived from a small-scale dispersion model, were assigned to each address. The main outcome was coronary artery calcification (CAC) assessed by electron-beam computed tomography. We evaluated the association between air pollution and CAC with logistic and linear regression analyses, controlling for individual level risk factors of coronary atherosclerosis. Compared with participants living >200 m away from a major road, participants living within 50, 51 to 100, and 101 to 200 m had odds ratios of 1.63 (95% CI, 1.14 to 2.33), 1.34 (95% CI, 1.00 to 1.79), and 1.08 (95% CI, 0.85 to 1.39), respectively, for a high CAC (CAC above the age- and gender-specific 75th percentile). A reduction in the distance between the residence and a major road by half was associated with a 7.0% (95% CI, 0.1 to 14.4) higher CAC. Fine particulate matter exposure was associated with CAC only in subjects who had not been working full-time for at least 5 years. Conclusions— Long-term residential exposure to high traffic is associated with the degree of coronary atherosclerosis.

Chronic Residential Exposure to Particulate Matter Air Pollution and Systemic Inflammatory Markers

Background Long-term exposure to urban air pollution may accelerate atherogenesis, but mechanisms are still unclear. The induction of a low-grade systemic inflammatory state is a plausible mechanistic pathway. Objectives: We analyzed the association of residential long-term exposure to particulate matter (PM) and high traffic with systemic inflammatory markers. Methods We used baseline data from the German Heinz Nixdorf Recall Study, a population-based, prospective cohort study of 4,814 participants that started in 2000. Fine PM [aerodynamic diameter ≤ 2.5 μm (PM2.5)] exposure based on a small-scale dispersion and chemistry transport model was assigned to each home address. We calculated distances between residences and major roads. Long-term exposure to air pollution (annual PM2.5 and distance to high traffic) and concentration of inflammatory markers [high-sensitivity C-reactive protein (hs-CRP) and fibrinogen] on the day of the baseline visit were analyzed with sex-stratified multiple linear regression, controlling for individual-level risk factors. Results In the adjusted analysis, a cross-sectional exposure difference of 3.91 μg/m3 in PM2.5 (interdecile range) was associated with increases in hs-CRP of 23.9% [95% confidence interval (CI), 4.1 to 47.4%] and fibrinogen of 3.9% (95% CI, 0.3 to 7.7%) in men, whereas we found no association in women. Chronic traffic exposure was not associated with inflammatory markers. Short-term exposures to air pollutants and temperature did not influence the results markedly. Conclusions Our study indicates that long-term residential exposure to high levels of PM2.5 is associated with systemic inflammatory markers in men. This might provide a link between air pollution and coronary atherosclerosis.

Simulation of ozone intrusion caused by a tropopause fold and cut-off low

Abstract A tropopause fold and cut-off low developed over Europe at the end of April 1982 and enhanced the exchange of air between the stratosphere and troposphere. The episode has been simulated using the EURAD model which has been designed for long-range transport simulation for European conditions. Applying a linear relationship between potential vorticity and ozone, concentration fields of the tracer and their changes due to outflow of ozone-rich air from the stratosphere could be simulated. A considerable decrease of stratospheric ozone was also obtained. This indicates noticeable mixing of tropospheric air with reduced ozone content into the stratosphere during the episode. Strong downward fluxes more than an order of magnitude larger than normal when averaged over the model domain show up around levels close to the tropopause. Obviously, dynamical processes fovern teh ozone budget o the upper troposphere during the vigorous intrusion event. Drastic increases of ozone also occur in the lower troposphere but are probably underestimated since vertical mixing by clouds is not taken into account in the simulation experiments. It is intended to explore the interaction of ozone of stratospheric and tropospheric (anthropogenic) origin in further experiments.

The use of nested models for air pollution studies: an application of the EURAD model to a SANA episode

Abstract A multiple-nesting version of the European Acid Deposition Model (EURAD) has been developed in order to increase the horizontal resolution in a region of enhanced pollution, namely the former German Democratic Republic. This new technique allows the ability to simulate large-scale features together with the development of smaller-scale structures in the nested regions. This multiple-nesting approach was applied to a case that occurred in October 1990, the so-called SANA 1 episode. SANA is a German acronym that stands for “scientific program for the assessment of the air pollution situation in the former German Democratic Republic.” The SANA program was established to observe the rapid change in composition of air pollutants and their concentration levels over the eastern part of Germany due to political and economical changes. Thus, within the SANA program there is a unique chance to observe and control the effect of air quality strategies. Two nested areas are embedded in a coarse domain that co...

Simulation of the chernobyl radioactive cloud over Europe using the eurad model

Abstract The Eur opean A cid D eposition Model (EURAD) is used to investigate the long-range transport (LRT) and deposition of radioactive material in Europe during the first week after the Chernobyl accident. Emphasis is laid on using the model system in a forecast mode as possibly would be done shortly after such an event. Thus, meteorological fields are predicted with the PSU/NCAR mososcale model MM4. The multilayer Eulerian model CTM ( C hemistry T ransport Model ) is applied to compute transport and deposition of Cs-137 and I-131 using the predicted meteorological fields. However, the accident scenario was estimated using published data. The model results and performance are discussed by comparison with observations. It is demonstrated that the model can reproduce certain observed characteristics of the radioactive cloud, i.e. trends in surface air concentrations, arrival times and wet deposition patterns. This leads to the suggestion that the predictive capability of the EURAD-system has a relatively high level considering the fact that several simple approaches were used.

Analysis of a regional model (EURAD) near surface gas concentration predictions using observations from networks

SummaryThe three-dimensional long-range transport model EURAD has been applied to two episodes in 1986 to study the transport and transformation of air pollutants over Europe under different meteorological conditions. The spring episode is characterized by varying meteorological conditions over Europe and transport of pollutants is complex. The summer episode is suitable to study the enhanced formation of photooxidants as an almost stagnant high pressure system over central Europe favoured the accumulation of pollutants. Available observations from several monitoring networks in Europe are used to evaluate the near surface concentration predictions of the model. This is possible for the sulfur species, O3 and NO2 for the central part of the modelling domain. It is shown that O3 and NO2 trends in the western part of the model domain are estimated reasonably well. The strong bias for underpredicting NO2 in the eastern part of the domain reflects the quality of emission data for the two regions of the modelling area. Typically for regional scale Eulerian transport models when applied on larger grid sizes, EURAD overpredicts the observed minima and underpredicts the high observations. This is particularly true for O3 but also detectable in the sulfate comparisons. Several sensitivity simulations for both episodes were performed to test numerical algorithms, parameterizations or emission data. Results from these simulations clearly show the important role of cloud related processes during the spring time for the sulfur species. Further testing and assessment of cloud parameterizations and emission data for transport models is anticipated.

Residential exposure to urban air pollution, ankle-brachial index, and peripheral arterial disease.

Background: Long-term exposure to particulate air pollution has been associated with increased cardiovascular disease. Biologic pathways for this association are not fully understood. Methods: We examined the association of urban air pollution with atherosclerosis of the peripheral vascular bed, using baseline data (2000–2003) from 4348 participants in a population-based cohort study in the German Ruhr Area. Levels of annual fine particulate matter (PM2.5) exposure, derived from a dispersion and chemistry transport model, were assigned to the participants’ home addresses. Residential traffic exposure was assessed by the distance between residence and major roads (federal and state highways). Using multiple regression analyses and controlling for individual level risk factors, we examined the association of PM2.5 and traffic with the ankle–brachial index and prevalence of peripheral arterial disease, defined as an index of less than 0.9 or a history of treatment for peripheral artery disease. Results: Living within 101–200, 51–100, and 50 m of a major road was associated with an adjusted absolute decrease in ankle–brachial index of −0.015 (95% confidence interval [CI] = −0.030 to 0.0), −0.002 (−0.021 to 0.016) and –0.024 (−0.047 to −0.001), respectively. Stronger associations were seen in women, whereas no clear association was found in men. Individuals living within 50 m of a major road had an OR of 1.77 (1.01–2.1) for peripheral arterial disease compared with those living more than 200 m away. Associations with PM2.5 were inconsistent. Conclusions: This study adds to the evidence that long-term residential exposure to traffic is associated with atherosclerosis.

Evaluation studies with a regional chemical transport model (EURAD) using air quality data from the EMEP monitoring network

Abstract The EURAD model has been applied to simulate the transport and chemical transformations of atmospheric constituents over central Europe for a 3 week late winter episode in February/March 1982. The TADAP model (the European version of ADOM) carried out simulations for the same episode with the same emission data set but with different meteorological input. The episode is characterized by two typical European meteorological conditions: a relatively quiet blocking situation at the beginning of the episode is followed by rather disturbed conditions with frontal systems passing through central European. The evolution of the pollutant fields is markedly different during these two conditions. Evaluation studies with the focus on the sulfur species were performed using air quality data from the EMEP monitoring network for the comparison of model predictions with observations. The first simulation with predicted meteorology and the PHOXA emission data set revealed an underprediction of airborne sulfate and wet deposition, while SO 2 was overpredicted. A simulation with meteorological data created by a so-called nudging technique corrected the transport of SO 2 to remote regions and drastically improved the predictions of rainfall and subsequently the amount of wet deposition. However, the ambient sulfate aerosol concentrations were still underpredicted. As the same bias in sulfate was also observed for TADAP simulations of the same episode a hypothesis for the underprediction is a very low primary sulfate emission inherent in the emission database. By artificially increasing the primary sulfate emission to an obviously too high value, the underprediction of sulfate was changed into a strong overprediction for the major source regions and into a reasonable range as observed for the remote regions. An analysis of the precipitation amounts, the aqueous concentrations and the resulting wet deposition showed that during this episode the aqueous were precipitation limited.

Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies

BACKGROUND Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods. OBJECTIVES Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5. METHODS The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area. RESULTS The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5. CONCLUSIONS LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5.