Felix Deutsch

Mass and ionic composition of atmospheric fine particles over Belgium and their relation with gaseous air pollutants

Mass, major ionic components (MICs) of PM2.5, and related gaseous pollutants (SO2, NO(x), NH3, HNO2, and HNO3) were monitored over six locations of different anthropogenic influence (industrial, urban, suburban, and rural) in Belgium. SO4(2-), NO3-, NH4+, and Na+ were the primary ions of PM2.5 with averages diurnal concentrations ranging from 0.4-4.5, 0.3-7.6, 0.9-4.9, and 0.4-1.2 microg m(-3), respectively. MICs formed 39% of PM2.5 on an average, but it could reach up to 80-98%. The SO2, NO, NO2, HNO2, and HNO3 levels showed high seasonal and site-specific fluctuations. The NH3 levels were similar over all the sites (2-6 microg m(-3)), indicating its relation to the evenly distributed animal husbandry activities. The sulfur and nitrogen oxidation ratios for PM2.5 point towards a low-to-moderate formation of secondary sulfate and nitrate aerosols over five cities/towns, but their fairly intensive formation over the rural Wingene. Cluster analysis revealed the association of three groups of compounds in PM2.5: (i) NH4NO3, KNO3; (ii) Na2SO4; and (iii) MgCl2, CaCl2, MgF2, CaF2, corresponding to anthropogenic, sea-salt, and mixed (sea-salt + anthropogenic) aerosols, respectively. The neutralization and cation-to-anion ratios indicate that MICs of PM2.5 appeared mostly as (NH4)2SO4 and NH4NO3 salts. Sea-salt input was maximal during winter reaching up to 12% of PM2.5. The overall average Cl-loss for sea-salt particles of PM2.5 at the six sites varied between 69 and 96% with an average of 87%. Principal component analysis revealed vehicular emission, coal/wood burning and animal farming as the dominating sources for the ionic components of PM2.5.

Appraisal of measurement methods, chemical composition and sources of fine atmospheric particles over six different areas of Northern Belgium

Daily and seasonal variation in the total elemental, organic carbon (OC) and elemental carbon (EC) content and mass of PM(2.5) were studied at industrial, urban, suburban and agricultural/rural areas. Continuous (optical Dustscan, standard tapered element oscillating micro-balance (TEOM), TEOM with filter dynamics measurement system), semi-continuous (Partisol filter-sampling) and non-continuous (Dekati-impactor sampling and gravimetry) methods of PM(2.5) mass monitoring were critically evaluated. The average elemental fraction accounted for 2-6% of the PM(2.5) mass measured by gravimetry. Metals, like K, Mn, Fe, Cu, Zn and Pb were strongly inter-correlated, also frequently with non-metallic elements (P, S, Cl and/or Br) and EC/OC. A high OC/EC ratio (2-9) was generally observed. The total carbon content of PM(2.5) ranged between 3 and 77% (averages: 12-32%), peaking near industrial/heavy trafficked sites. Principal component analysis identified heavy oil burning, ferrous/non-ferrous industry and vehicular emissions as the main sources of metal pollution.

Optimization of the ion chromatographic quantification of airborne fluoride, acetate and formate in the Metropolitan Museum of Art, New York

Ion chromatographic (IC) methods have been compared in order to achieve an optimal separation of fluoride, acetate and formate under various elution conditions on two formerly introduced analytical columns (i and ii) and a novel one (iii): (i) an IonPac AS14 (250 mm × 4 mm I.D.), (ii) Allsep A-2 (150 mm × 4.6mm I.D.), and (iii) an IC SI-50 4E (250 mm (length) × 4mm (internal diameter - I.D.)). The IC conditions for the separation of the anions concerned were optimized on the IC SI-50 4E column. A near baseline separation of these anions was attained on the IonPac AS14, whereas the peaks of fluoride and acetate could not be resolved on the Allsep A-2. A baseline separation for the three anions was achieved on the IC SI-50 4E column, when applying an eluent mixture of 3.2 mmol/L Na(2)CO(3) and 1.0 mmol/L NaHCO(3) with a flow rate of 1.0 mL/min. The highest precision of 1.7, 3.0 and 2.8% and the best limits of detection (LODs) of 0.014, 0.22 and 0.17 mg/L for fluoride, acetate and formate, respectively, were obtained with the IC SI-50 4E column. Hence, this column was applied for the determination of the acetic and formic acid contents of air samples taken by means of passive gaseous sampling at the Metropolitan Museum of Art in New York, USA. Atmospheric concentrations of acetic and formic acid up to 1050 and 450 μg/m(3), respectively, were found in non-aerated showcases of the museum. In galleries and outdoors, rather low levels of acetic and formic acid were detected with average concentrations of 50 and 10 μg/m(3), respectively. The LOD data of acetate and formate on the IC SI-50 4E column correspond to around 0.5 μg/m(3) for both acetic and formic acid in air samples.

Modelling changes of aerosol compositions over Belgium and Europe

Seasonal changes in aerosol compositions over Belgium and Europe are simulated with an extended version of the EUROS model. EUROS is capable of modelling mass and chemical composition of aerosols in two size fractions (PM2.5 and PM10-2.5). The chemical composition is expressed in terms of seven components: ammonium, nitrate, sulphate, primary inorganic compounds, elementary carbon, primary organic compounds and Secondary Organic Compounds (SOA). A comparison of modelled and measured aerosol concentrations showed that modelled concentrations are generally consistent with observed concentrations. The chemical composition of the aerosol showed a strong dependence on the season. High aerosol concentrations during the summer were mainly due to high concentrations of the secondary components nitrate, ammonium, sulphate and SOA in the size fraction PM2.5. In contrast, during autumn and winter, increased PM-concentrations were mainly due to higher concentrations of primary components, especially in the size fraction PM10-2.5.

Air-quality modelling in the Lake Baikal region

In this paper, we assess the status of the air quality in the Lake Baikal region which is strongly influenced by the presence of anthropogenic pollution sources. We combined the local data, with global databases, remote sensing imagery and modelling tools. This approach allows to inventorise the air-polluting sources and to quantify the air-quality concentration levels in the Lake Baikal region to a reasonable level, despite the fact that local data are scarcely available. In the simulations, we focus on the month of July 2003, as for this period, validation data are available for a number of ground-based measurement stations within the Lake Baikal region.

Single-run ion chromatographic separation of inorganic and low-molecular-mass organic anions under isocratic elution: Application to environmental samples

For the isocratic ion chromatography (IC) separation of low-molecular-mass organic acids and inorganic anions three different anion-exchange columns were studied: IonPac AS14 (9 microm particle size), Allsep A-2 (7 microm particle size), and IC SI-50 4E (5 microm particle size). A complete baseline separation for all analyzed anions (i.e., F(-), acetate, formate, Cl(-), NO(2)(-), Br(-), NO(3)(-), HPO(4)(2-) and SO(4)(2-)) in one analytical cycle of shorter than 17 min was achieved on the IC SI-50 4E column, using an eluent mixture of 3.2mM Na(2)CO(3) and 1.0mM NaHCO(3) with a flow rate of 1.0 mL min(-1). On the IonPac AS14 column, it was possible to separate acetate from inorganic anions in one run (i.e., less than 9 min), but not formate, under the following conditions: 3.5mM Na(2)CO(3) plus 1.0mM NaHCO(3) with a flow rate of 1.2 mL min(-1). Therefore, it was necessary to adapt a second run with a 2.0mM Na(2)B(4)O(7) solution as an eluent under a flow rate of 0.8 mL min(-1) for the separation of organic ions, which considerably enlarged the analysis time. For the Allsep A-2 column, using an eluent mixture of 1.2mM Na(2)CO(3) plus 1.5mM NaHCO(3) with a flow rate of 1.6 mL min(-1), it was possible to separate almost all anions in one run within 25 min, except the fluoride-acetate critical pair. A Certified Multianion Standard Solution PRIMUS for IC was used for the validation of the analytical methods. The lowest RSDs (less than 1%) and the best LODs (0.02, 0.2, 0.16, 0.11, 0.06, 0.05, 0.04, 0.14 and 0.09 mg L(-1) for F(-), Ac(-), For(-), Cl(-), NO(2)(-), Br(-), NO(3)(-), HPO(4)(2-) and SO(4)(2-), respectively) were achieved using the IC SI-50 4E column. This column was applied for the separation of concerned ions in environmental precipitation samples such as snow, hail and rainwater.

Fine Atmospheric Particles from Agricultural Practices in Flanders: From Emissions to Health Effects and Limit Values

Agriculture can influence air quality via emissions of ammonia, soil dust and soot. These can be emitted into the atmosphere during farming practices, and contribute in different amounts to the total emissions and concentrations of air particulate matter (PM). The exact contribution of Flemish agricultural emissions to total air PM concentrations and to negative health effects are not well known. In this paper, agricultural emissions in Flanders and the processes leading to secondary PM are reviewed, together with their associated health effects. Agricultural ammonia emissions are a major contributor to local formation of secondary PM, and can increase above normal levels during some smog episodes. From a health perspective, secondary PM formed by ammonia is considered less important. Epidemiological studies suggest that combustion-related particles are the cause of negative health effects, although a reduction in ammonia emissions would reduce acidification and eutrophication of ecosystems. The World Health Organization currently considers PM2.5 as the best indicator for assessing human health effects. Setting an additional limit value for combustion-related particles would target potentially more harmful particles.

Making High Resolution Air Quality Maps for Flanders, Belgium

Using a combination of models, high resolution air quality maps for Flanders (Belgium) have been made. First of all, the Eulerian air quality model AURORA has simulated for a complete year the air pollutant concentrations over the region on a 3 × 3 km² resolution. These results are calibrated using the RIO-interpolation model on air quality station data. Thereafter, an extra simulation using the bi-Gaussian IFDM model is made on a resolution of 1 × 1 km², with a finer resolution (up to 25 m) close to the major roads. The nesting methodology of IFDM in AURORA is designed to avoid double counting of the roads. The results are highly detailed PM10, PM2.5, NO2 and EC maps for Flanders. Using station data and data from several measurement campaigns, the maps have been validated and it has been shown that the maps show indeed a highly detailed picture of the air quality in Flanders. These data will be used in assessing the air quality and human exposure to it in Flanders, and in assessing policy scenarios designed to improve the air quality.

A Statistical Approach for the Spatial Representativeness of Air Quality Monitoring Stations and the Relevance for Model Validation

A methodology is presented for the assessment of the spatial represent- tativeness of air pollution monitoring data. The methodology relies on a statistical approach that links air quality expectation values with land use characteristics. The relevance of this issue for model validation is addressed and the technique is illu- strated for the validation of BelEUROS model results.

The Effect of Wood Burning on Particulate Matter Concentrations in Flanders, Belgium

Since 2010, new estimations of the particulate matter emissions in Flanders have been made by using a tier-II approach. By means of a survey, the quantity of the wood by households, buildings (services sector), industry and agricultural sector consumption in Flanders has been estimated. A survey is necessary as not all consumed wood is purchased, e.g. some of the wood is sourced locally or waste wood is used. These surveys also provided data on the installation stock in Flanders, such as the type (fireplaces, pellet stoves, …) and age of the heating installation. Besides the wood consumption and use patterns, emission factors of particulate matter per type of wood and per type and age of heating installation were also updated based on international, recent literature on emission factors. Both new estimations resulted in an actualization of the particulate matter emissions of the residential wood burning in Flanders. Overall, the estimations were a factor 13 higher than the old estimations. This factor 13 is due to a factor 4 increase in the average emission factor and a factor of 3.4 in the wood consumption. As a result, heating in residential sector is estimated to be the most important emission source for primary particulate matter (37 % of all primary emissions) in Flanders. To confirm these results a comparison was carried out with the estimates of the contribution of wood burning to ambient PM10 concentrations based on measurements of levoglucosan. It was shown that about 10 % of the particulate matter concentrations in winter were due to wood burning, while in summer this amounted only 2–3 %. In the next step, a dispersion model has been used in order to check the consistency of both results. It is shown that the increased emissions are consistent with the measured particulate matter concentrations due to wood burning. Indeed, the increase in emissions by a factor 13 is needed to understand the high levoglucosan concentrations in ambient air in Flanders. Finally, the large changes that have been made to the Belgian SNAP-2 emission inventory due to the results of this study, raise questions about the homogeneity (both spatial and temporal) of the European emission inventory for this sector. Adjustments to this sector could possibly decrease the modelled PM-gap quite substantially.