Large-eddy simulation of pollution dispersion in an urban street canyon—Part I: comparison with field data

Large-eddy simulations (LESs) are applied to the problem of pollution dispersion within the urban canopy layer, specifically street canyons. The objective is to study the turbulence structure and hence the physical dispersion mechanisms of pollutants. LESs are implemented by incorporating the dynamic sub-grid scale stress model into the commercial computational fluids dynamics code CFX. To gain confidence in the approach, simulations are performed for a canyon-like geometry (roof garden) for which experimental measurements were also made. The experimental campaign consisted of using sonic anemometers to measure mean flow and turbulence intensities at a high sample rate of 60 Hz. Good agreement between simulations and experimental data are obtained. Real geometric features, such as non-uniform wall heights, result in a very much three-dimensional flow distribution. Comparisons with the k–ε model show that LESs are able to predict more accurately the turbulence statistics of the flow.     

Statistics of extreme values of air quality—a simulation study

Some of the existing National Ambient Air Quality Standards require the use of an extreme observed concentration in a year to determine compliance. Since observed extreme values tend to be not reliable, different statistical approaches for determining the extreme values have been used or suggested. However, none of these approaches properly take into account the effects of an underlying trend and the serial correlation of the air quality time series. By means of a time series simulation, these effects can be considered concurrently in estimating the extreme values.This paper reports the results of such a simulation for determining the statistics of the seven highest values (rank m = 1–7, m = 1 representing the highest value) using actual air quality data that contain both trends and autocorrelations. The result of this simulation shows that for a high-pollution season of 122 days, the commonly used asymptotic distributions overestimate the maximum (m = 1) values and underestimate their uncertainties. As one moves from m = 1 to m = 7, the over- and underestimations by the asymptotic distributions worsen (compared to the simulation result). These findings in logarithmic space are further enhanced when they are converted back to concentration space. The simulation using the oxidant data for Azusa, California further shows that the uncertainties associated with the estimates Of the extreme values are typically 20% of the values for m = 1 and 10% of the values for m = 7. Compared to the observed data, which is a single series for each year, the result based on the popular lognormal distribution consistently overpredicts the extreme values, by about 40% for the maximum values and about 20% for the seventh highest values.Our results illustrate the difficulty of estimating the extreme values of air quality time series with accuracy and confidence. However, the accuracy and confidence of the estimates improve as the rank moves away from the extreme. This result calls for the need for using a less extreme value in setting a sensible air quality standard. Of course, such a standard can be set without sacrificing its stringency.     

Application of the k–ε turbulence model to the high Reynolds number skimming flow field of an urban street canyon

A two-dimensional, steady, k–ε turbulence model was used to investigate the high Reynolds number skimming flow field of an urban street canyon. We describe the critical canyon width-to-height ratios that distinguish a cascade of vortex patterns that form in an urban street canyon. Details of the flow field are reported that includes the structure of the mean flow field, turbulent kinetic energy, turbulent length scale, turbulent eddy viscosity, and Reynolds stress for three typical different aspect ratios, W/H, of a street canyon. The consequences of vortex layering on vertical transport are explored.     

Can secondary organic aerosol formed in an atmospheric simulation chamber continuously age?

This work investigates the oxidative aging process of SOA derived from select aromatic (m-xylene) and biogenic (α-pinene) precursors within an environmental chamber. Simultaneous measurements of SOA hygroscopicity, volatility, particle density, and elemental chemical composition (C:O:H) reveal only slight particle aging for up to the first 16 h of formation. The chemical aging observed is consistent with SOA that is decreasing in volatility and increasing in O/C and hydrophilicity. Even after aging, the O/C (0.25 and 0.40 for α-pinene and m-xylene oxidation, respectively) was below the OOAI and OOAII ambient fractions measured by high-resolution aerosol mass spectra coupled with Positive Matrix Factorization (PMF). The rate of increase in O/C does not appear to be sufficient to achieve OOAI or OOAII levels of oxygenation within regular chamber experiment duration. No chemical aging was observed for SOA during dark α-pinene ozonolysis with a hydroxyl radical scavenger present. This finding is consistent with observations by other groups that SOA from this system is comprised of first generation products.     

Stochastic simulation of meteorological variability for long-range atmospheric transport—II. Long-term statistical models

Methods are developed for simulating meteorological inputs for statistical atmospheric transport models. Stochastic models are presented for the annual mean wind vector, the horizontal diffusion coefficient, the fraction of time it is raining, and the quantity of precipitation. The models are derived by aggregating the statistical models for short-term meteorological processes given in the companion paper of Small and Samson (Atmospheric Environment, 1989, 23, 2813–2824). Normal distributions are used for each variable. The normal distribution is derived directly for the mean wind vector based on the normality of short-term winds, and serves as an acceptable approximation for the other variables given their low interannual coefficient of variation. Correlation between variables is considered, including correlation between winds and precipitation, between the fraction of time it is raining and the total quantity of precipitation at a site, and between the annual precipitation quantity at multiple sites. Development and confirmation of the interannual distributions is supported by long-term meteorological data, including a nine-year backward trajectory record computed for a site in western Pennsylvania. Application of the method is demonstrated with a statistical atmospheric LRT model used to predict distributions of annual precipitation sulfates in eastern North America. Predicted interannual coefficients of variation of wet SO₄²⁻ concentrations range from about 10 to 15 per cent, similar to the level of interannual variation inferred from long-term data sets.     

A robust simulation–optimization modeling system for effluent trading—a case study of nonpoint source pollution control

In this study, a robust simulation–optimization modeling system (RSOMS) is developed for supporting agricultural nonpoint source (NPS) effluent trading planning. The RSOMS can enhance effluent trading through incorporation of a distributed simulation model and an optimization model within its framework. The modeling system not only can handle uncertainties expressed as probability density functions and interval values but also deal with the variability of the second-stage costs that are above the expected level as well as capture the notion of risk under high-variability situations. A case study is conducted for mitigating agricultural NPS pollution with an effluent trading program in Xiangxi watershed. Compared with non-trading policy, trading scheme can successfully mitigate agricultural NPS pollution with an increased system benefit. Through trading scheme, [213.7, 288.8]?×?10³ kg of TN and [11.8, 30.2]?×?10³ kg of TP emissions from cropped area can be cut down during the planning horizon. The results can help identify desired effluent trading schemes for water quality management with the tradeoff between the system benefit and reliability being balanced and risk aversion being considered.     

Removal of the emerging contaminant bisphenol A by an ureasil–PEO hybrid membrane: experimental study and molecular dynamic simulation

This work reports the use of a cross-linked ureasil–PEO hybrid matrix (designated PEO800) as an efficient adsorbent to retain the emerging contaminant bisphenol A (BPA) from an aqueous medium. The in-deep experimental and theoretical results provide information about the interactions between PEO800 and BPA. The in situ UV-vis spectroscopy data and the pseudo-first order, pseudo-second order, Elovich, and Morris–Webber intraparticle diffusion models allowed us to propose a three-step mechanism for the adsorption of BPA onto PEO800. The results indicate that the pseudo-first-order kinetic model effectively describes the adsorption of BPA onto PEO800. Differential scanning calorimetry (DSC) and Fourier transform infrared (FTIR) spectroscopy confirmed the interaction of PEO800 with BPA, showing an alteration in the chemical environment of the polymer ether oxygen atoms present in the hybrid matrix. The molecular dynamic simulation provides further evidence that the BPA molecules interact preferentially with PEO. The amount of desorbed BPA depended on the pH and solvent used in the assays. This work provides new opportunities for using the hydrophilic ureasil–PEO matrix which has demonstrated its abilities in being a fast and easy alternative to successfully removing organic contaminants from aqueous mediums and therefore having potential applications in water remediation.

Graphical abstract

     

SimPhy: a simulation game to lessen the impact of phytosanitaries on health and the environment—the case of Merja Zerga in Morocco

Diffuse phytosanitary pollution is a complex phenomenon to manage. Reducing this type of pollution is one of today’s key socio-economic and environmental challenges. At the regional level, few approaches enable the actors concerned to implement agricultural management strategies to reduce the use and impact of phytosanitary products. Our research problem focused on the consequences of intensive agriculture and, in particular, how to evaluate the impact of phytosanitary products on human health and the environment. In this article, we present the SimPhy simulation game which places the actors from a given region directly into a situation in which they manage farms whilst under pressure to reduce phytosanitaries (quantity and toxicity). The application focused on the Merja Zerga catchment area in Morocco. The region is dominated by intensive agriculture which is located upstream from a Ramsar-classified wetland area. The SimPhy simulation game is based on a decision support system-type tool. It allows us to anticipate the impact of regulations on farming systems. It also enables us to analyse the consequences of the actors’ strategies on farm economies, human health and the quality of ecosystems. Initial results from the SimPhy simulation game enabled the technicians from Agricultural Development Center (CDA) themselves to learn about managing agricultural production systems in a dynamic and interactive fashion. With the simulation game, it was possible to learn about the farmer's ability to adapt to new regulatory constraints, and the involved consequences for toxicity risks for human health and the environment.     

Use of 2–methoxyethyl ether and nitromethane as oxygenated additives for performance improvement and emission reduction of CI engine: experimental investigation and numerical simulation

Environmental Science and Pollution Research - Diesel engines are playing a vital responsibility in the field of automobile, agriculture, construction, and power generation. In the present world,...     

Dynamic flux chamber measurement of gaseous mercury emission fluxes over soils: Part 2—effect of flushing flow rate and verification of a two-resistance exchange interface simulation model

Both field and laboratory tests demonstrated that soil Hg emission fluxes measured by dynamic flux chamber (DFC) operations strongly depend on the flushing air flow rates used. The general trend is an increase in the fluxes with increasing flushing flow rates followed by an asymptotic approach to flux maximum at sufficiently high (optimum) flushing flow rates. This study indicates that the DFC measurements performed at low flushing flow rates can underestimate Hg emission fluxes over soils, especially Hg-enriched soils. High flushing flow rates therefore are recommended for accurate estimation of soil Hg emission fluxes by DFC operations. The dependence of DFC-measured soil Hg emission fluxes on flushing flow rate is a physical phenomenon inherent in DFC operations, regardless of DFC design and soil physical characteristics. Laboratory tests using DFCs over different soils confirmed the predictions of a two-resistance exchange interface model and demonstrated the capability of this model in quantitatively simulating Hg emissions from soils measured by DFC operations.