Temporal variations of atmospheric aerosol in four European urban areas

Purpose

The concentrations of PM₁₀ mass, PM_2.5 mass and particle number were continuously measured for 18 months in urban background locations across Europe to determine the spatial and temporal variability of particulate matter.

Methods

Daily PM₁₀ and PM_2.5 samples were continuously collected from October 2002 to April 2004 in background areas in Helsinki, Athens, Amsterdam and Birmingham. Particle mass was determined using analytical microbalances with precision of 1 ??g. Pre- and post-reflectance measurements were taken using smoke-stain reflectometers. One-minute measurements of particle number were obtained using condensation particle counters.

Results

The 18-month mean PM₁₀ and PM_2.5 mass concentrations ranged from 15.4 ??g/m³ in Helsinki to 56.7 ??g/m³ in Athens and from 9.0 ??g/m³ in Helsinki to 25.0 ??g/m³ in Athens, respectively. Particle number concentrations ranged from 10,091 part/cm³ in Helsinki to 24,180 part/cm³ in Athens with highest levels being measured in winter. Fine particles accounted for more than 60% of PM₁₀ with the exception of Athens where PM_2.5 comprised 43% of PM₁₀. Higher PM mass and number concentrations were measured in winter as compared to summer in all urban areas at a significance level p?Conclusions Significant quantitative and qualitative differences for particle mass across the four urban areas in Europe were observed. These were due to strong local and regional characteristics of particulate pollution sources which contribute to the heterogeneity of health responses. In addition, these findings also bear on the ability of different countries to comply with existing directives and the effectiveness of mitigation policies.     

Analysis of cloud and precipitation chemistry at Whiteface Mountain,NY

Federal and state programs over the past two decades have resulted in the reduction of emissions of precursors of acid rain. Concomitant with these changes, measured concentrations of acidity in precipitation and in watersheds have shown a downward trend or improvement. However, another pathway for these precursors is through cloud and fog events that often tend to occur at high-elevation regions affecting the fauna and flora as well. In this study we report on long-term measurements of cloud water and precipitation chemistry made from 1994 onwards at a high-elevation location, Whiteface Mountain NY, in the northeastern United States. Trends and inter-relationship between the ions were examined along with ambient SO₂ measurements and Adirondack lakes chemistry data.     

A comparison of mesh-adaptive LES with wind tunnel data for flow past buildings: Mean flows and velocity fluctuations

In this paper we address two important aspects of micro-scale urban airflow model evaluation: (a) the identification of key flow features as dictated by the physics of the problem and as captured by the simulations, and (b) the comparison of important model output parameters (mean flows and fluctuations) with experimental data. A series of mesh-adaptive large eddy simulations (LES) was carried out for the study of air flows within two intersecting street canyons with varying building configurations. The novelty of the approach lies in the combination of LES with mesh adaptivity, which allows a variable-filter length and the implementation of an anisotropic eddy-viscosity model. Both coarse and fine-mesh simulations were carried out, using single and parallel-processor systems respectively. The simulations showed clearly that the expected flow patterns such as the street canyon recirculation and the street-mouth vortices, as well as the exchange of air flow at the street intersections, can readily be captured by the mesh-adaptive LES.In addition, the detailed comparisons of mean flows and fluctuations of the resolved velocity field with the measured data showed that the simulation results agreed well with the patterns and trends of the wind tunnel measurements. In most cases the finer-mesh simulations improved considerably the accuracy of the mean flows, especially for the symmetrical configuration. The improvement in the predicted fluctuations was less obvious, with several detector locations underpredicting the measured values, although the overall comparison was also satisfactory. The typical errors for the mean flows for all three building configurations were less than 30%, whilst for the velocity fluctuations less that 40%. Both the simulated means flows and turbulence levels were generally more accurate in the streets parallel to the wind (streamwise direction) than in the streets normal to the wind.     

Prediction of the Fate and Transport Processes of Atrazine in a Reservoir

The fate and transport processes of a toxic chemical such as atrazine, an herbicide, in a reservoir are significantly influenced by hydrodynamic regimes of the reservoir. The two-dimensional (2D) laterally-integrated hydrodynamics and mass transport model, CE-QUAL-W2, was enhanced by incorporating a submodel for toxic contaminants and applied to Saylorville Reservoir, Iowa. The submodel describes the physical, chemical, and biological processes and predicts unsteady vertical and longitudinal distributions of a toxic chemical. The simulation results from the enhanced 2D reservoir model were validated by measured temperatures and atrazine concentrations in the reservoir. Although a strong thermal stratification was not identified from both observed and predicted water temperatures, the spatial variation of atrazine concentrations was largely affected by seasonal flow circulation patterns in the reservoir. In particular, the results showed the effect of flow circulation on spatial distribution of atrazine during summer months as the river flow formed an underflow within the reservoir and resulted in greater concentrations near the surface of the reservoir. Atrazine concentrations in the reservoir peaked around the end of May and early June. A good agreement between predicted and observed times and magnitudes of peak concentrations was obtained. The use of time-variable decay rates of atrazine led to more accurate prediction of atrazine concentrations, while the use of a constant half-life (60 days) over the entire period resulted in a 40% overestimation of peak concentrations. The results provide a better understanding of the fate and transport of atrazine in the reservoir and information useful in the development of reservoir operation strategies with respect to timing, amount, and depth of withdrawal.     

In vitro methane removal by volcanic pumice soil biofilter columns over one year

Soil methane (CH(4)) biofilters, containing CH(4)-oxidizing bacteria (methanotrophs), are a promising technology for mitigating greenhouse gas emissions. However, little is known about long-term biofilter performance. In this study, volcanic pumice topsoils (0-10 cm) and subsoils (10-50 cm) were tested for their ability to oxidize a range of CH(4) fluxes over 1 yr. The soils were sampled from an 8-yr-old and a 2-yr-old grassed landfill cover and from a nearby undisturbed pasture away from the influence of CH(4) generated by the decomposing refuse. Methane was passed through the soils in laboratory chambers with fluxes ranging from 0.5 g to 24 g CH(4) m(-3) h(-1). All topsoils efficiently oxidized CH(4). The undisturbed pasture topsoil exhibited the highest removal efficiency (24 g CH(4) m(-3) h(-1)), indicating rapid activation of the methanotroph population to the high CH(4) fluxes. The subsoils were less efficient at oxidizing CH(4) than the topsoils, achieving a maximum rate oxidation rate of 7 g CH(4) m(-3) h(-1). The topsoils exhibited higher porosities; moisture contents; surface areas; and total C, N, and available-P concentrations than the subsoils, suggesting that these characteristics strongly influence growth and activity of the CH(4)-oxidizing bacteria. Soil pH values and available-P levels gradually declined during the trial, indicating a need to monitor chemical parameters closely so that adjustments can be made when necessary. However, other key soil physicochemical parameters (moisture, total C, total N) increased over the course of the trial. This study showed that the selected topsoils were capable of continually sustaining high CH(4) removal rates over 1 yr, which is encouraging for the development of biofilters as a low-maintenance greenhouse gas mitigation technology.     

Phosphorus fertilizer and grazing management effects on phosphorus in runoff from dairy pastures

Fertilizer phosphorus (P) and grazing-related factors can influence runoff P concentrations from grazed pastures. To investigate these effects, we monitored the concentrations of P in surface runoff from grazed dairy pasture plots (50 x 25 m) treated with four fertilizer P rates (0, 20, 40, and 80 kg ha(-1) yr(-1)) for 3.5 yr at Camden, New South Wales. Total P concentrations in runoff were high (0.86-11.13 mg L(-1)) even from the control plot (average 1.94 mg L(-1)). Phosphorus fertilizer significantly (P < 0.001) increased runoff P concentrations (average runoff P concentrations from the P(20), P(40), and P(80) treatments were 2.78, 3.32, and 5.57 mg L(-1), respectively). However, the magnitude of the effect of P fertilizer varied between runoff events (P < 0.01). Further analysis revealed the combined effects on runoff P concentration of P rate, P rate x number of applications (P < 0.001), P rate x time since fertilizer (P < 0.001), dung P (P < 0.001), time since grazing (P < 0.05), and pasture biomass (P < 0.001). A conceptual model of the sources of P in runoff comprising three components is proposed to explain the mobilization of P in runoff and to identify strategies to reduce runoff P concentrations. Our data suggest that the principal strategy for minimizing runoff P concentrations from grazed dairy pastures should be the maintenance of soil P at or near the agronomic optimum by the use of appropriate rates of P fertilizer.     

Characterizing Storm Hydrograph Rise and Fall Dynamics With Stream Stage Data1

Abstract: Storm‐flow transients (i.e., hydrograph rise and fall dynamics) may represent an important aspect of understanding streamflow dynamics. However, little is known about how temporal resolution of transient data and climate variability may color these potential indicators of hydrologic pattern or condition. Warm‐season stream stage and rainfall were monitored continuously (5 min) during the 2002 water year in eight tributaries of the Little Miami River (Ohio), which drain 17‐58 km² catchments. Rise rates generated using 5‐min data were different than those generated with mean daily data [calculated with the Indicators of Hydrologic Alteration (IHA) software], though fall rates were similar for fine and coarse temporal data. This result suggests that data with low temporal resolution may not be adequate to fully represent the dynamics of storm rise rates. Conversely, fall rates based on daily stage data (via IHA) were similar to those based on the 5‐min data, and so daily mean data may be appropriate for characterizing fall rates. We next analyzed the possible correlations between rainfall variability and storm‐flow stage dynamics. We derived rise and recession rates from storm stage hydrographs by assuming exponential rise and decay of a runoff peak. We found that raw rise rates (R_raw) were correlated with both the maximum rainfall rate and the time to the centroid of a rain event. We subsequently removed the trend based on these rainfall characteristics, which yielded new representations of rise rates abbreviated as R_rate and R_tcent, respectively, and that had lower variability than the uncorrected (raw) data. Fall rates were found to be independent of rainfall characteristics. Due to the predominant influence of stream hydrology upon aquatic biota and nutrient fluxes, our work suggests that these stage data analysis protocols can refine or otherwise reduce variability in these indices by accounting for relevant factors such as rainfall forcing. These protocols for derivation of transient indices should be tested for their potential to improve correlations between stream hydrology and temporally aligned biotic data and dissolved nutrient fluxes in streams.     

Analysis of the air pollution climate at a background site in the Po valley

The Po valley in northern Italy is renowned for its high air pollutant concentrations. Measurements of air pollutants from a background site in Modena, a town of 200 thousand inhabitants within the Po valley, are analysed. These comprise hourly data for CO, NO, NO(2), NO(x), and O(3), and daily gravimetric equivalent data for PM(10) from 1998-2010. The data are analysed in terms of long-term trends, annual, weekly and diurnal cycles, and auto-correlation and cross-correlation functions. CO, NO and NO(2) exhibit a strongly traffic-related pattern, with daily peaks at morning and evening rush hour and lower concentrations over the weekend. Ozone shows an annual cycle with a peak in July due to local production; notwithstanding the diurnal cycle dominated by titration by nitrogen oxide, the decreasing long term trend in NO concentration did not affect the long term trend in O(3), whose mean concentration remained steady over the sampling period. PM(10) shows a strong seasonality with higher concentration in winter and lower concentration in summer and spring. Both PM(10) and ozone show a marked weekly cycle in summer and winter respectively. Regressions of PM(10) upon NO(x) show a consistently greater intercept in winter, representing higher secondary PM(10) in the cooler months of the year. There is a seasonal pattern in primary PM(10) to NO(x) ratios, with lower values in winter and higher values in summer, but the reasons are unclear.     

A Multiple Criteria Decision Analysis Model Based on ELECTRE TRI-C for Erosion Risk Assessment in Agricultural Areas

This paper deals with a real-world decision-aiding problem for zoning the risk of erosion, total suspended solids emissions, and ecological consequences of their transfers towards the streams. One of these consequences is the decrease of fishes into the streams in agricultural watersheds, because of the clogging of spawning areas. Given the multiple criteria nature of the problem, the originality of our research is to adapt a new decision-aiding sorting method, ELECTRE TRI-C, for identifying risk zones in rural areas, where measures must be taken. The developed model was applied in a small watershed (Low Normandy, France) where the objective was to assess the most appropriate intervention for protecting the reproduction habitat of the salmonid fishes. Agricultural parcels were evaluated on multiple criteria for grouping them into four risk categories, which are related to risk levels as well as priorities on the improvement works. The decision-aiding sorting model is co-constructed, within a constructive approach, through an interaction process between decision-aiding analysts, environmental experts, and local actors for improving transparency and communication on the results. This model is linked with a geographical information system (GIS) for assessing a set of criteria and the visualization of the farming parcels along with their type of intervention they should be submitted to best practices. The assignment results were validated by the environmental experts. These results have a strong impact on the agricultural practices of the farmers into the watersheds. The model proposed in this paper can be considered as a useful decision aid tool in any regions for implementing public agricultural and environmental policies for protecting the ecological areas.