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.     

The impact of ambient ozone on mountain spruce forests in the Czech Republic as indicated by malondialdehyde

Malondialdehyde (MDA), a product of lipid peroxidation and biomarker of oxidative stress, is measured over the long term in spruce Picea abies needles under real conditions in three Czech mountain border areas. The trends presented collate the MDA content in spruce needles with ambient ozone, temperature and precipitation as casual, and defoliation as a subsequent factor for the period 1994-2006. We have found the overall decreasing trends in MDA and defoliation. The highest MDA and defoliation are recorded in the Jizerske, the lowest in the Krusne hory Mts. Out of the examined variables the MDA is predicted best by mean temperature in vegetation season, median of O₃ concentrations and AOT40; these three variables account for 34% of MDA1 and 36% of MDA2 variability. Our hypothesis that higher ambient O₃ exposure results in higher MDA contents in P. abies needles under real conditions has not been approved.     

How life history contributes to stress response in the Manila clam <Emphasis Type="Italic">Ruditapes philippinarum</Emphasis>

Introduction  

Within the last decade, numerous studies have investigated the role of environmental history on tolerance to stress of many organisms. This study aims to assess if Manila clams Ruditapes philippinarum may react differently to cadmium exposure and trematode parasite infection (Himasthla elongata) depending on their origin and environmental history in Arcachon Bay (France).     

Comparison of land-use regression models between Great Britain and the Netherlands

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO₂ and PM_10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL).Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country.A common model for GB and NL explained NO₂ concentrations well (adjusted R² 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction.The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models.     

Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.     

The impact of infield biomass burning on PM levels and its chemical composition

In the South of Italy, it is common for farmers to burn pruning waste from olive trees in spring. In order to evaluate the impact of the biomass burning source on the physical and chemical characteristics of the particulate matter (PM) emitted by these fires, a PM monitoring campaign was carried out in an olive grove. Daily PM10 samples were collected for 1 week, when there were no open fires, and when biomass was being burned, and at two different distances from the fires. Moreover, an optical particle counter and a polycyclic aromatic hydrocarbon (PAH) analyzer were used to measure the high time-resolved dimensional distribution of particles emitted and total PAHs concentrations, respectively. Chemical analysis of PM10 samples identified organic and inorganic components such as PAHs, ions, elements, and carbonaceous fractions (OC, EC). Analysis of the collected data showed the usefulness of organic and inorganic tracer species and of PAH diagnostic ratios for interpreting the impact of biomass fires on PM levels and on its chemical composition. Finally, high time-resolved monitoring of particle numbers and PAH concentrations was performed before, during, and after biomass burning, and these concentrations were seen to be very dependent on factors such as weather conditions, combustion efficiency, and temperature (smoldering versus flaming conditions), and moisture content of the wood burned.     

Indoor air quality (IAQ) assessment in a multistorey shopping mall by high-spatial-resolution monitoring of volatile organic compounds (VOC)

In order to assess indoor air quality (IAQ), two 1-week monitoring campaigns of volatile organic compounds (VOC) were performed in different areas of a multistorey shopping mall. High-spatial-resolution monitoring was conducted at 32 indoor sites located in two storehouses and in different departments of a supermarket. At the same time, VOC concentrations were monitored in the mall and parking lot area as well as outdoors. VOC were sampled at 48-h periods using diffusive samplers suitable for thermal desorption. The samples were then analyzed with gas chromatography–mass spectrometry (GC–MS). The data analysis and chromatic maps indicated that the two storehouses had the highest VOC concentrations consisting principally of terpenes. These higher TVOC concentrations could be a result of the low efficiency of the air exchange and intake systems, as well as the large quantity of articles stored in these small spaces. Instead, inside the supermarket, the food department was the most critical area for VOC concentrations. To identify potential emission sources in this department, a continuous VOC analyzer was used. The findings indicated that the highest total VOC concentrations were present during cleaning activities and that these activities were carried out frequently in the food department. The study highlights the importance of conducting both high-spatial-resolution monitoring and high-temporal-resolution monitoring. The former was able to identify critical issues in environments with a complex emission scenario while the latter was useful in interpreting the dynamics of each emission source.