Do ICP-MS based methods fulfill the EU monitoring requirements for the determination of elements in our environment?

Undoubtedly, the most important advance in the environmental regulatory monitoring of elements of the last decade is the widespread introduction of ICP-mass spectrometry (ICP-MS) due to standards developed by the European Committee for Standardization. The versatility of ICP-MS units as a tool for the determination of major, minor and trace elements (Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Mo, Na, Ni, P, Pb, Sb, Se, Sn, Ti, V and Zn) in surface water, groundwater, river sediment, topsoil, subsoil, fine particulates and atmospheric deposition is illustrated in this paper. Ranges of background concentrations for major, minor and trace elements obtained from a regional case study (Flanders, Belgium) are summarized for all of these environmental compartments and discussed in the context of a harmonized implementation of European regulatory monitoring requirements. The results were derived from monitoring programs in support of EU environmental quality directives and were based on a selection of (non-polluted) background locations. Because of the availability of ICP-MS instruments nowadays, it can be argued that the main hindrance for meeting the European environmental monitoring requirements is no longer the technical feasibility of analysis at these concentration levels, but rather (i) potential contamination during sampling and analysis, (ii) too limited implementation of quality control programs, validating the routinely applied methods (including sampling and low level verification) and (iii) lack of harmonization in reporting of the chemical environmental status between the individual member states.

Methodology for setup and data processing of mobile air quality measurements to assess the spatial variability of concentrations in urban environments.

A case study is presented to illustrate a methodology for mobile monitoring in urban environments. A dataset of UFP, PM2.5 and BC concentrations was collected. We showed that repeated mobile measurements could give insight in spatial variability of pollutants at different micro-environments in a city. Streets of contrasting traffic intensity showed increased concentrations by a factor 2-3 for UFP and BC and by <10% for PM2.5. The first quartile (P25) of the mobile measurements at an urban background zone seems to be good estimate of the urban background concentration. The local component of the pollutant concentrations was determined by background correction. The use of background correction reduced the number of runs needed to obtain representative results. The results presented, are a first attempt to establish a methodology for setup and data processing of mobile air quality measurements to assess the spatial variability of concentrations in urban environments.

The Aeroflex: a bicycle for mobile air quality measurements.

Fixed air quality stations have limitations when used to assess people's real life exposure to air pollutants. Their spatial coverage is too limited to capture the spatial variability in, e.g., an urban or industrial environment. Complementary mobile air quality measurements can be used as an additional tool to fill this void. In this publication we present the Aeroflex, a bicycle for mobile air quality monitoring. The Aeroflex is equipped with compact air quality measurement devices to monitor ultrafine particle number counts, particulate mass and black carbon concentrations at a high resolution (up to 1 second). Each measurement is automatically linked to its geographical location and time of acquisition using GPS and Internet time. Furthermore, the Aeroflex is equipped with automated data transmission, data pre-processing and data visualization. The Aeroflex is designed with adaptability, reliability and user friendliness in mind. Over the past years, the Aeroflex has been successfully used for high resolution air quality mapping, exposure assessment and hot spot identification. 

Wintertime spatio-temporal variation of ultrafine particles in a Belgian city.

Simultaneous measurements of ultrafine particles (UFPs) were carried out at four sampling locations situated within a 1 km(2) grid area in a Belgian city, Borgerhout (Antwerp). All sampling sites had different orientation and height of buildings and dissimilar levels of anthropogenic activities (mainly traffic volume). The aims were to investigate: (i) the spatio-temporal variation of UFP within the area, (ii) the effect of wind direction with respect to the volume of traffic on UFP levels, and (iii) the spatial representativeness of the official monitoring station situated in the study area. All sampling sites followed similar diurnal patterns of UFP variation, but effects of local traffic emissions were evident. Wind direction also had a profound influence on UFP concentrations at certain sites. The results indicated a clear influence of local weather conditions and the more dominant effect of traffic volumes. Our analysis indicated that the regional air quality monitoring station represented the other sampling sites in the study area reasonably well; temporal patterns were found to be comparable though the absolute average concentrations showed differences of up to 35%.

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.

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.