The development of effects-based air quality management regimes

This paper considers the evolution of attempts to control and manage air pollution, principally but not exclusively focussing upon the challenge of managing air pollution in urban environments. The development and implementation of a range of air pollution control measures are considered. Initially the measures implemented primarily addressed point sources, a small number of fuel types and a limited number of pollutants. The adequacy of such a source-control approach is assessed within the context of a changing and challenging air pollution climate. An assessment of air quality management in the United Kingdom over a 50-year timeframe exemplifies the range of issues and challenges in contemporary air quality management. The need for new approaches is explored and the development and implementation of an effects-based, risk management system for air quality regulation is evaluated.     

Particle size distribution of airborne Aspergillus fumigatus spores emitted from compost using membrane filtration

Information on the particle size distribution of bioaerosols emitted from open air composting operations is valuable in evaluating potential health impacts and is a requirement for improved dispersion simulation modelling. The membrane filter method was used to study the particle size distribution of Aspergillus fumigatus spores in air 50 m downwind of a green waste compost screening operation at a commercial facility. The highest concentrations (approximately 8 × 10⁴ CFU m⁻³) of culturable spores were found on filters with pore diameters in the range 1–2 μm which suggests that the majority of spores are emitted as single cells. The findings were compared to published data collected using an Andersen sampler. Results were significantly correlated (p < 0.01) indicating that the two methods are directly comparable across all particles sizes for Aspergillus spores.     

Biomass consumption and CO2, CO and main hydrocarbon gas emissions in an Amazonian forest clearing fire

Biomass consumption and CO₂, CO and hydrocarbon gas emissions in an Amazonian forest clearing fire are presented and discussed. The experiment was conducted in the arc of deforestation, near the city of Alta Floresta, state of Mato Grosso, Brazil. The average carbon content of dry biomass was 48% and the estimated average moisture content of fresh biomass was 42% on wet weight basis. The fresh biomass and the amount of carbon on the ground before burning were estimated as 528 t ha^?1 and 147 t ha^?1, respectively. The overall biomass consumption for the experiment was estimated as 23.9%. A series of experiment in the same region resulted in average efficiency of 40% for areas of same size and 50% for larger areas. The lower efficiency obtained in the burn reported here occurred possibly due to rain before the experiment. Excess mixing ratios were measured for CO₂, CO, CH₄, C₂–C₃ aliphatic hydrocarbons, and PM_2.5. Excess mixing ratios of CH₄ and C₂–C₃ hydrocarbons were linearly correlated with those of CO. The average emission factors of CO₂, CO, CH₄, NMHC, and PM_2.5 were 1,599, 111.3, 9.2, 5.6, and 4.8 g kg^?1 of burned dry biomass, respectively. One hectare of burned forest released about 117,000 kg of CO₂, 8100 kg of CO, 675 kg of CH₄, 407 kg of NMHC and 354 kg of PM_2.5.     

Predicting bioremediation of hydrocarbons: Laboratory to field scale

There are strong drivers to increasingly adopt bioremediation as an effective technique for risk reduction of hydrocarbon impacted soils. Researchers often rely solely on chemical data to assess bioremediation efficiently, without making use of the numerous biological techniques for assessing microbial performance. Where used, laboratory experiments must be effectively extrapolated to the field scale. The aim of this research was to test laboratory derived data and move to the field scale. In this research, the remediation of over thirty hydrocarbon sites was studied in the laboratory using a range of analytical techniques. At elevated concentrations, the rate of degradation was best described by respiration and the total hydrocarbon concentration in soil. The number of bacterial degraders and heterotrophs as well as quantification of the bioavailable fraction allowed an estimation of how bioremediation would progress. The response of microbial biosensors proved a useful predictor of bioremediation in the absence of other microbial data. Field-scale trials on average took three times as long to reach the same endpoint as the laboratory trial. It is essential that practitioners justify the nature and frequency of sampling when managing remediation projects and estimations can be made using laboratory derived data. The value of bioremediation will be realised when those that practice the technology can offer transparent lines of evidence to explain their decisions.     

Surface ozone background in the United States: Canadian and Mexican pollution influences

We use a global chemical transport model (GEOS-Chem) with 1° × 1° horizontal resolution to quantify the effects of anthropogenic emissions from Canada, Mexico, and outside North America on daily maximum 8-hour average ozone concentrations in US surface air. Simulations for summer 2001 indicate mean North American and US background concentrations of 26 ± 8 ppb and 30 ± 8 ppb, as obtained by eliminating anthropogenic emissions in North America vs. in the US only. The US background never exceeds 60 ppb in the model. The Canadian and Mexican pollution enhancement averages 3 ± 4 ppb in the US in summer but can be occasionally much higher in downwind regions of the northeast and southwest, peaking at 33 ppb in upstate New York (on a day with 75 ppb total ozone) and 18 ppb in southern California (on a day with 68 ppb total ozone). The model is successful in reproducing the observed variability of ozone in these regions, including the occurrence and magnitude of high-ozone episodes influenced by transboundary pollution. We find that exceedances of the 75 ppb US air quality standard in eastern Michigan, western New York, New Jersey, and southern California are often associated with Canadian and Mexican pollution enhancements in excess of 10 ppb. Sensitivity simulations with 2020 emission projections suggest that Canadian pollution influence in the Northeast US will become comparable in magnitude to that from domestic power plants.     

Ultrafine particles near a major roadway in Raleigh,North Carolina: Downwind attenuation and correlation with traffic-related pollutants

Ultrafine particles (UFPs, diameter < 100 nm) and co-emitted pollutants from traffic are a potential health threat to nearby populations. During summertime in Raleigh, North Carolina, UFPs were simultaneously measured upwind and downwind of a major roadway using a spatial matrix of five portable industrial hygiene samplers (measuring total counts of 20–1000 nm particles). While the upper sampling range of the portable samplers extends past the defined “ultrafine” upper limit (100 nm), the 20–1000 nm number counts had high correlation (Pearson R = 0.7–0.9) with UFPs (10–70 nm) measured by a co-located research-grade analyzer and thus appear to be driven by the ultrafine range. Highest UFP concentrations were observed during weekday morning work commutes, with levels at 20 m downwind from the road nearly fivefold higher than at an upwind station. A strong downwind spatial gradient was observed, linearly approximated over the first 100 m as an 8% drop in UFP counts per 10 m distance. This result agreed well with UFP spatial gradients estimated from past studies (ranging 5–12% drop per 10 m). Linear regression of other vehicle-related air pollutants measured in near real-time (10-min averages) against UFPs yielded moderate to high correlation with benzene (R² = 0.76), toluene (R² = 0.49), carbon monoxide (R² = 0.74), nitric oxide (R² = 0.80), and black carbon (R² = 0.65). Overall, these results support the notion that near-road levels of UFPs are heavily influenced by traffic emissions and correlate with other vehicle-produced pollutants, including certain air toxics.     

Hydrocarbon emissions speciation in diesel and biodiesel exhausts

Diesel engine emissions are composed of a long list of organic compounds, ranging from C₂ to C₁₂₊, and coming from the hydrocarbons partially oxidized in combustion or produced by pyrolisis. Many of these are considered as ozone precursors in the atmosphere, since they can interact with nitrogen oxides to produce ozone under atmospheric conditions in the presence of sunlight. In addition to problematic ozone production, Brookes, P., and Duncan, M. [1971. Carcinogenic hydrocarbons and human cells in culture. Nature.] and Heywood, J. [1988. Internal Combustion Engine Fundamentals.Mc Graw-Hill, ISBN 0-07-1000499-8.] determined that the polycyclic aromatic hydrocarbons present in exhaust gases are dangerous to human health, being highly carcinogenic.The aim of this study was to identify by means of gas chromatography the amount of each hydrocarbon species present in the exhaust gases of diesel engines operating with different biodiesel blends. The levels of reactive and non-reactive hydrocarbons present in diesel engine exhaust gases powered by different biodiesel fuel blends were also analyzed.Detailed speciation revealed a drastic change in the nature and quantity of semi-volatile compounds when biodiesel fuels are employed, the most affected being the aromatic compounds. Both aromatic and oxygenated aromatic compounds were found in biodiesel exhaust. Finally, the conservation of species for off-side analysis and the possible influence of engine operating conditions on the chemical characterization of the semi-volatile compound phase are discussed.The use of oxygenated fuel blends shows a reduction in the Engine-Out emissions of total hydrocarbons. But the potential of the hydrocarbon emissions is more dependent on the compositions of these hydrocarbons in the Engine-Out, to the quantity; a large percent of hydrocarbons existing in the exhaust, when biodiesel blends are used, are partially burned hydrocarbons, and are interesting as they have the maximum reactivity, but with the use of pure biodiesel and diesel, the most hydrocarbons are from unburned fuel and they have a less reactivity. The best composition in the fuel, for the control of the hydrocarbon emissions reactivity, needs to be a fuel with high-saturated fatty acid content.     

Impact of large scale circulation on European summer surface ozone and consequences for modelling forecast

In this study, we investigate the benefit for European ozone simulation of using day-to-day varying chemical boundary conditions produced by a global chemical weather forecast platform instead of climatological monthly means at the frontiers of a regional model. We performed two simulations over Europe using the regional (0.5 × 0.5°) CHIMERE CTM forced by global scale simulations based on the LMDz-INCA CTM. For summer 2005, ozone differences exceeding 20 ppb can be punctually found between these two simulations in the borders of the domain. The mean of the differences ranges between 0 and 3 ppb beyond 15° of the frontiers of the regional model.Correlations with ground-based ozone measurements at more than 400 stations are slightly increased by the use of daily boundary conditions. The simulation of the temporal variability is significantly enhanced in particular for the daily means and daily maxima. As expected, the gain is higher at the borders of the regional domain.The change of percentile distribution shows that the net impact of high temporal resolution boundary conditions is not of major concern for surface ozone peaks which are mainly due to local photochemistry. The use of daily boundary conditions is however necessary to correctly simulate concentrations in the 20–35 ppb range which are of crucial interest for human and vegetation exposure effects.     

Spatiotemporal modelling of ozone distribution in the State of California

This paper is concerned with the spatiotemporal mapping of monthly 8-h average ozone (O₃) concentrations over California during a 15-years period. The basic methodology of our analysis is based on the spatiotemporal random field (S/TRF) theory. We use a S/TRF decomposition model with a dominant seasonal O₃ component that may change significantly from site to site. O₃ seasonal patterns are estimated and separated from stochastic fluctuations. By means of Bayesian Maximum Entropy (BME) analysis, physically meaningful and sufficiently detailed space–time maps of the seasonal O₃ patterns are generated across space and time. During the summer and winter months the seasonal O₃ concentration maps exhibit clear and progressively changing geographical patterns over time, suggesting the existence of relationships in accordance with the typical physiographic and climatologic features of California. BME mapping accuracy can be superior to that of other techniques commonly used by EPA; its framework can rigorously assimilate useful data sources that were previously unaccounted for; the generated maps offer valuable assessments of the spatiotemporal O₃ patterns that can be helpful in the identification of physical mechanisms and their interrelations, the design of human exposure and population health models, and in risk assessment. As they focus on the seasonal patterns, the maps are not contingent on short-time and locally prevalent weather conditions, which are of no interest in a global and non-forecasting framework. Moreover, the maps offer valuable insight about the space–time O₃ concentration patterns and are, thus, helpful for disentangling the influence of explanatory factors or even for identifying some influential ones that could have been otherwise overlooked.