Road traffic impact on urban water quality: a step towards integrated traffic,air and stormwater modelling

Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.     

Ozone Formation in California's San Joaquin Valley: A Critical Assessment of Modeling and Data Needs

ABSTRACT

Data from the 1990 San Joaquin Valley Air Quality Study/ Atmospheric Utility Signatures, Predictions, and Experiments (SJVAQS/AUSPEX) field program in California's San Joaquin Valley (SJV) suggest that both urban and rural areas would have difficulty meeting an 8-hr average O₃ standard of 80 ppb. A conceptual model of O₃ formation and accumulation in the SJV is formulated based on the chemical, meteorological, and tracer data from SJVAQS/ AUSPEX. Two major phenomena appear to lead to high O₃ concentrations in the SJV: (1) transport of O₃ and precursors from upwind areas (primarily the San Francisco Bay Area, but also the Sacramento Valley) into the SJV, affecting the northern part of the valley, and (2) emissions of precursors, mixing, transport (including long-range transport), and atmospheric reactions within the SJV responsible for regional and urban-scale (e.g., downwind of Fresno and Bakersfield) distributions of O₃. Using this conceptual model, we then conduct a critical evaluation of the meteorological model and air quality model. Areas of model improvements and data needed to understand and properly simulate O₃ formation in the SJV are highlighted.     

Current Status of Air Quality Models for Particulate Matter

ABSTRACT

The current status of the mathematical modeling of atmospheric particulate matter (PM) is reviewed in this paper. Simulating PM requires treating various processes, including the formation of condensable species, the gas/ particle partitioning of condensable compounds, and in some cases, the evolution of the particle size distribution. The algorithms available to simulate these processes are reviewed and discussed. Eleven 3-dimensional (3-D) Eulerian air quality models for PM are reviewed in terms of their formulation and past applications. Results of past performance evaluations of 3-D Eulerian PM models are presented. Currently, 24-hr average PM_2.5 concentrations appear to be predicted within 50% for urban-scale domains. However, there are compensating errors among individual particulate species. The lowest errors tend to be associated with SO₄ ^2-, while NO₃ ^-, black carbon (BC), and organic carbon (OC) typically show larger errors due to uncertainties in emissions inventories and the prediction of the secondary OC fraction. Further improvements and performance evaluations are recommended.     

An Assessment of the Emissions Inventory Processing Systems EMS-2001 and SMOKE in Grid-Based Air Quality Models

Abstract

In the United States, emission processing models such as Emissions Modeling System-2001 (EMS-2001), Emissions Preprocessor System-Version 2.5 (EPS2.5), and the Sparse Matrix Operator Kernel Emissions (SMOKE) model are currently being used to generate gridded, hourly, speciated emission inputs for urban and regional-scale photochemical models from aggregated pollutant inventories. In this study, two models, EMS-2001 and SMOKE, were applied with their default internal data sets to process a common inventory database for a high ozone (O₃) episode over the eastern United States using the Carbon Bond IV (CB4) chemical speciation mechanism. A comparison of the emissions processed by these systems shows differences in all three of the major processing steps performed by the two models (i.e., in temporal allocation, spatial allocation, and chemical speciation). Results from a simulation with a photochemical model using these two sets of emissions indicate differences on the order of ±20 ppb in the predicted 1-hr daily maximum O₃ concentrations. It is therefore critical to develop and implement more common and synchronized temporal, spatial, and speciation cross-reference systems such that the processes within each emissions model converge toward reasonably similar results. This would also help to increase confidence in the validity of photochemical grid model results by reducing one aspect of modeling uncertainty.     

Demonstrating Attainment of the Air Quality Standards: Integration of Observations and Model Predictions into the Probabilistic Framework

ABSTRACT

This paper introduces an integrated observational-modeling approach to transform the deterministic nature of attainment demonstrations of the National Ambient Air Quality Standard (NAAQS) into the probabilistic framework. While the methods presented here can be used to address any air quality standard that is based on extreme values, this paper focuses on the application to the 1-hr and 8-hr NAAQS for ozone. Extreme value statistics and resampling techniques are applied to estimate the probability of exceeding the NAAQS for both 1-hr and 8-hr ozone concentrations. Within the integrated observation-modeling analysis approach, we show that the model-to-model differences in the predicted responses to emission reductions are smaller than the model-to-model differences in predicted absolute ozone concentrations. We illustrate that the emission reductions stemming from a real-world emission control strategy would substantially reduce the probability of exceeding the NAAQS over a large portion of the eastern United States, especially for the 8-hr average ozone concentrations.     

Application and Evaluation of Two Air Quality Models for Particulate Matter for a Southeastern U.S. Episode

Abstract

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29–July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O₃), particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 μm (PM₁₀) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O₃ and PM than CMAQ. Both models tend to predict O₃ values that are higher than those observed. For observed O₃ values above 60 ppb, O₃ performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O₃ values above 40 ppb.

Both models predict similar amounts of sulfate (SO₄ ^2?) and organic matter, and both predict SO₄ ^2? to be the largest contributor to PM_2.5. PMCAMx generally predicts higher amounts of ammonium (NH₄ ⁺), nitrate (NO₃ ^?), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO₃ ^?,NH₄ ⁺, and BC than observed, which degrades its performance. For PM₁₀ and PM_2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37–43% and –33–4% for CMAQ and 50–59% and 7–30% for PMCAMx. Both models predict the largest MNGEs for NO₃ ^? (98–104% for CMAQ, 138–338% for PMCAMx). The inaccurate NO₃ ^? predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.     

Modeling Atmospheric Mercury Deposition in the Vicinity of Power Plants

Abstract

Two mathematical models of the atmospheric fate and transport of mercury (Hg), an Eulerian grid–based model and a Gaussian plume model, are used to calculate the atmospheric deposition of Hg in the vicinity (i.e., within 50 km) of five coal–fired power plants. The former is applied using two different horizontal resolutions: coarse (84 km) and fine (16.7 km). More than 96% of the power plant Hg emissions are calculated with the plume model to be transported beyond 50 km from the plants. The grid–based model predicts a lower fraction to be transported beyond 50 km: >91% with a coarse resolution and >95% with a fine resolution. The contribution of the power plant emissions to total Hg deposition within a radius of 50 km from the plants is calculated to be <8% with the plume model, <14% with the Eulerian model with a coarse resolution, and <10% with the Eulerian model with a fine resolution. The Eulerian grid–based model predicts greater local impacts than the plume model because of artificially enhanced vertical dispersion; the former predicts about twice as much Hg deposition as the latter when the area considered is commensurate with the resolution of the grid–based model. If one compares the local impacts for an area that is significantly less than the grid–based model resolution, then the grid–based model may predict lower local deposition than the plume model, because two compensating errors affect the results obtained with the grid–based model: initial dilution of the power plant emissions within one or more grid cells and enhanced vertical mixing to the ground.     

Impact and cost of measures to reduce nutrient emissions from wastewater and storm water treatment in the German Elbe river basin

As a leading nutrient emitter, wastewater infrastructure harbors significant technical potentials to reduce the water-polluting emissions of phosphorus and nitrogen into the Elbe river basin. From the viewpoint of the central infrastructure, the effluent threshold value of urban wastewater treatment plants could be lowered further by advanced use of denitrification and membrane filtration, and storm water overflows of wastewater and contaminated rainwater from sewers could be treated in retention soil filters. In addition, small-scale wastewater treatment plants, infiltration and reducing or unsealing impervious surfaces could be used as decentralized elements of wastewater or storm water treatment. It can be shown that if the most advanced measures were applied in all wastewater-relevant areas, up to 60% of the phosphorus and 37% of the nitrogen emissions could be avoided. Alongside central wastewater treatment plants, small-scale treatment plants prove to be the most effective and cost-efficient option. To achieve an ecologically acceptable state of the Elbe, however, it may be necessary to employ more costly measures as well.     

Responses of a soil bacterium, Pseudomonas chlororaphis O6 to commercial metal oxide nanoparticles compared with responses to metal ions

The toxicity of commercially-available CuO and ZnO nanoparticles (NPs) to pathogenic bacteria was compared for a beneficial rhizosphere isolate, Pseudomonas chlororaphis O6. The NPs aggregated, released ions to different extents under the conditions used for bacterial exposure, and associated with bacterial cell surface. Bacterial surface charge was neutralized by NPs, dependent on pH. The CuO NPs were more toxic than the ZnO NPs. The negative surface charge on colloids of extracellular polymeric substances (EPS) was reduced by Cu ions but not by CuO NPs; the EPS protected cells from CuO NPs-toxicity. CuO NPs-toxicity was eliminated by a Cu ion chelator, suggesting that ion release was involved. Neither NPs released alkaline phosphatase from the cells’ periplasm, indicating minimal outer membrane damage. Accumulation of intracellular reactive oxygen species was correlated with CuO NPs lethality. Environmental deposition of NPs could create niches for ion release, with impacts on susceptible soil microbes.     

Photophysical and photochemical properties of the pharmaceutical compound salbutamol in aqueous solutions

Salbutamol is a potent β₂-adrenergic receptor agonist widely used in the treatment of bronchial asthma and chronic obstructive pulmonary disease. An increasing number of studies have detected salbutamol in natural water systems worldwide. Studies have shown that sunlight degrades salbutamol resulting in the formation of products; some showing higher toxicity to bacteria Vibrio fischeri than the parent compound. In this contribution, steady-state absorption and emission techniques, high-performance liquid chromatography, and transient absorption spectroscopy are used to investigate the photochemistry of salbutamol in aqueous buffer solutions at controlled pH values. Ground- and excited-state calculations that include solvent effects are performed to guide the interpretation of the experimental results. Salbutamol is sensitive to UVB light absorption in the pH range from 3 to 12, forming products that absorb light at longer wavelengths than the parent compound. Quantum yields of degradation reveal that the deprotonated species is 10-fold more photo-active than the protonated species. In line with this result, the fluorescence quantum yield of the protonated species is more than an order of magnitude higher than that of the deprotonated species. Transient absorption spectroscopy shows that population of the triplet state occurs with a rate constant of 7.1 × 10⁸ s⁻¹ in the protonated species, while a rate constant of 1.7 × 10¹⁰ s⁻¹ is measured for the deprotonated species. While degradation of the deprotonated species is not affected by the presence of molecular oxygen, a twofold increase in the photodegradation yield of the protonated species in air-saturated conditions is observed.