Prediction of the PCDD/F and dl-PCB 2005-WHO-TEQ content based on the contribution of six congeners: Toward a new screening approach for fish samples?

Current European Union regulation regarding polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans (PCDD/Fs) and dioxin-like polychlorinated biphenyls (dl-PCBs) in food and feed is based on Toxic Equivalent Quotient (TEQ) concept. For confirmatory purpose, the isotope-dilution method associated to a measurement by gas chromatography coupled with high resolution mass spectrometry is usually the method of choice for precisely measuring the 29 target congeners in three separated fractions. Time and cost related to these analyses are very significant. Various kinds of screening concepts can be considered. In the present study, we elaborated and validated a prediction model for the 2005 World Health Organization TEQ in fish, based on the measurement of 4 PCDD/F and 2 non-ortho dl-PCB congeners, potentially analyzable in a single extracted fraction by gas chromatography coupled with mass spectrometry. Large independent datasets have been used for model elaboration (n = 108) and validation (n = 363, n = 357 and n = 6).     

Modeling distributions of air pollutant concentrations—II. Estimation of one and two parameter statistical distributions

In Part I of this series Taylor, Jakeman and Simpson (1986, Atmospheric Environment, 20, 1781–1789) examined the problem of identifying the appropriate distributional form for air pollution concentration data. In this paper we examine the parameter estimation problem. Monte Carlo simulation is used to compare methods for fitting statistical distributions to such data where the distributional form is known. Three methods are investigated for estimating the parameters of the lognormal distribution, two methods for the exponential distribution, three methods for the γ-distribution and four methods for the Weibull distribution. For all distributions and for each method we examine the accuracy with which the upper percentiles of the distribution are evaluated as it is these percentiles which are referred to by air quality standards. For each distribution a simple empirical model, which yields approximations to the relative root mean square error of the percentile estimates against sample size and parameter values, is developed and demonstrated. Thus for each distributional model an estimate of the relative error associated with evaluating high pollutant levels may be readily determined.     

Validation of road vehicle and traffic emission models – A review and meta-analysis

Road transport is often the main source of air pollution in urban areas, and there is an increasing need to estimate its contribution precisely so that pollution-reduction measures (e.g. emission standards, scrapage programs, traffic management, ITS) are designed and implemented appropriately. This paper presents a meta-analysis of 50 studies dealing with the validation of various types of traffic emission model, including ‘average speed’, ‘traffic situation’, ‘traffic variable’, ‘cycle variable’, and ‘modal’ models. The validation studies employ measurements in tunnels, ambient concentration measurements, remote sensing, laboratory tests, and mass-balance techniques. One major finding of the analysis is that several models are only partially validated or not validated at all. The mean prediction errors are generally within a factor of 1.3 of the observed values for CO₂, within a factor of 2 for HC and NO_x, and within a factor of 3 for CO and PM, although differences as high as a factor of 5 have been reported. A positive mean prediction error for NO_x (i.e. overestimation) was established for all model types and practically all validation techniques. In the case of HC, model predictions have been moving from underestimation to overestimation since the 1980s. The large prediction error for PM may be associated with different PM definitions between models and observations (e.g. size, measurement principle, exhaust/non-exhaust contribution).Statistical analyses show that the mean prediction error is generally not significantly different (p < 0.05) when the data are categorised according to model type or validation technique. Thus, there is no conclusive evidence that demonstrates that more complex models systematically perform better in terms of prediction error than less complex models. In fact, less complex models appear to perform better for PM. Moreover, the choice of validation technique does not systematically affect the result, with the exception of a CO underprediction when the validation is based on ambient concentration measurements and inverse modelling. The analysis identified two vital elements currently lacking in traffic emissions modelling: 1) guidance on the allowable error margins for different applications/scales, and 2) estimates of prediction errors. It is recommended that current and future emission models incorporate the capability to quantify prediction errors, and that clear guidelines are developed internationally with respect to expected accuracy.     

Some Empirical Models for the Los Angeles Photochemical Smog Data

This paper presents (i) an empirico-mechanistic model which describes the dependence of CO, NO, NO₂, and O₃ on total hydrocarbons, traffic, wind speed, inversion base height, and solar radiation as well as the photochemical reactions associated with these pollutants; (ii) a detailed study of weather conditions when the instantaneous daily maximum O₃ exceeds the L.A. County alert level of 50 pphm; and (iii) regression models for the prediction of daily maximum O₃ values.     

Genotoxicity of sediment extracts of the Berre lagoon (France)

To evaluate the genotoxic risk that contaminated sediment could constitute for benthic organisms, three contaminated (VA, VC and VN) and one uncontaminated (RN) sediment samples were collected in the Berre lagoon (France). Potentially bioavailable contaminants in sediments were obtained using sediment extraction with synthetic seawater adjusted to pH 4 or pH 6, simulating the range of pH prevailing in the digestive tract of benthic organisms. The genotoxic activities of these extracts were evaluated by three short-term bioassays: the Salmonella mutagenicity test using the Salmonella typhimurium strain TA102, the alkaline comet assay and the micronucleus assay on the Chinese Hamster Ovary cells CHO-K1. Results of the Salmonella mutagenicity assay detected a mutagenic response for RN extract at pH 6, and for VA extract at pH 4. Results of the comet and micronucleus assays detected low genotoxic/clastogenic activities for VA and VC extracts at pH 6 and higher activities for RN, VA and VC extracts at pH 4. To identify if metals (Al, Fe, Mn, As, Cd, Co, Cr, Cu, Hg, Ni, Pb and Zn) were involved in these genotoxic activities, their concentrations were determined in the extracts, and their speciation was assessed by thermodynamic calculations. Results showed that extracts from sites VA, VC and VN generally presented the highest trace metal contents for both extractants, while the site RN presented lower trace metal contents but the highest Fe and Mn contents. Thermodynamic calculations indicated that Fe, Mn, As and in a lower extend Co, Ni and Zn were mainly present under free forms in extracts, and were consequently, more likely able to induce a genotoxic effect. Results globally showed no correspondence between free metal contents and genotoxic activities. They suggested that these positive results could be due to uncharacterized compounds, acting as direct genotoxic agents or enhancing the genotoxic properties of analyzed metals.     

Application of central composite face-centered design and response surface methodology for the optimization of electro-Fenton decolorization of Azure B dye

Purpose

The aim of this work was to improve the ability of electro-Fenton technique for the remediation of wastewater contaminated with synthetic dyes using a model azo dye such as Azure B.

Methods

Batch experiments were conducted to study the effects of main parameters, such as dye concentration, electrode surface area, treatment time, and voltage. In this study, central composite face-centered experimental design matrix and response surface methodology were applied to design the experiments and evaluate the interactive effects of the four studied parameters. A total of 30 experimental runs were set, and the kinetic data were analyzed using first- and second-order models.

Results

The experimental data fitted to the empirical second-order model of a suitable degree for the maximum decolorization of Azure B by electro-Fenton treatment. ANOVA analysis showed high coefficient of determination value (R ²?=?0.9835) and reasonable second-order regression prediction. Pareto analysis suggests that the variables, time, and voltage produce the largest effect on the decolorization rate.

Conclusion

Optimum conditions suggested by the second-order polynomial regression model for attaining maximum decolorization were dye concentration 4.83?mg/L, electrode surface area 15?cm², voltage 14.19?V, and treatment time of 34.58?min.     

Diffusion of an instantaneous cluster of particles in homogeneous turbulence

In this work we study the diffusion of instantaneous puffs vs the diffusion of continuous plumes. The model which we use is a Lagrangian model for the motion of N particles suggested by Kaplan and Dinar (1988, J. compt. Phys. 79, 317–335). This model is based on the approach of Richardson to the relative diffusion which states that the instantaneous relative velocity of particles is a function of their instantaneous separation. Results show that the diffusion of a puff is slower than that of a continuous source. We find that the puff evolves more slowly than in the analytic model of Lee and Stone (1983, Atmospheric Environment17, 2477–2481), since in their model diffusion is influenced only by the initial conditions. The effect of the source size on the diffusion rate is studied as well.     

The future monitoring capabilities of four network configurations in eastern Canada

The capability of deposition networks in eastern Canada to resolve regional trends has been examined by Blanchard et al. (1996, Atmospheric Environment 30, 2539–2549). This paper extends the earlier methods to permit evaluation of the need for specific individual sites, comparison of additional network configurations, and consideration of more regions. Parameter estimates for the statistical model are improved by using monthly instead of annual data. For the regions that we examined, eliminating all provincial sites in eastern Canada would cause an increase of 1 to 6 years in the time required for reaching a 90% probabiility of detecting the expected future trends. The elimination of certain key provincial sites may increase the uncertainties in the determination of deposition isopleths of particular interest, such as the 20 kg ha⁻¹ yr⁻¹ contours. The statistical techniques presented here are quite general and can be extended to statistical tests or estimators other than those illustrated here.     

The effect of precipitation on the vertical profiles of atmospheric ammonia: A modeling investigation

This paper describes theoretical calculations of atmospheric ammonia profiles during precipitation events. The PLUVIUS reactive storm model (Hales, 1982, Atmospheric Environment16,1775–1783) was used in a simplified form relevant to this specific system. Calculated NH₃ profiles for dry atmospheres were consistent with distributions previously reported in the literature. NH₃ profiles in the gas and cloud phases, following a simulated convective storm, showed large variations with height. These variations are strongly dependent on storm duration. In some cases, NH₃ gas concentrations were depleted by more than 50% by the precipitation scavenging process. Modeled NH₃ gas profiles regenerate slowly with time after storm termination.     

Ecotoxicity and biodegradability of antielectrostatic dicephalic cationic surfactants

Four series of dicephalic cationic surfactants, considered as new antielectrostatic agents have been investigated in order to establish their toxicity and biodegradability. Among them N,N-bis[3,3′-(dimethylamine)propyl]alkylamides, N,N-bis[3,3′-(dimethylamine)propyl]alkylamide dihydrochlorides, N,N-bis[3,3′-(trimethylammonio)propyl]alkylamide dibromides and N,N-bis[3,3′-(trimethylammonio)propyl]alkylamide dimethylsulphates with different hydrophobic chain length (n-C₉H₁₉ to n-C₁₅H₃₁) and type of counterion (chloride, bromide and methylsulfate) have been studied. The inhibitory effect against microorganisms has been examined using model gram-positive and gram-negative bacteria, and yeasts. None of the tested surfactants have shown antimicrobial activity against gram-negative bacteria (Escherichia coli, Pseudomonas putida) and yeasts (Saccharomyces cerevisiae, Rhodotorula glutinis) at a concentration below 1000 μg mL⁻¹, however some of them were moderately active against gram-positive bacteria (Staphylococcus aureus, Bacillus subtilis). The Microtox® test was successfully applied to measure EC₅₀ values of the studied dicephalic cationic surfactants. Their toxicity to Vibrio fischeri depended upon the alkanoyl chain length with the EC₅₀ values in a range of 2.6-980 mg L⁻¹. N,N-bis[3,3′-(dimethylamine)propyl]alkylamide dihydrochlorides 2a-b and N,N-bis[3,3′-(trimethylammonio)propyl]alkylamide dibromides 3a-b comprising n-decanoyl and n-dodecanoyl hydrophobic tails appeared to be the least toxic. Furthermore, the biodegradability under aerobic conditions of 2a-b, 3a-b was evaluated using OECD Method 301F. According to the obtained results 2a, 3a-3b can be considered as almost readily biodegradable and they are not expected to be persistent in the environment. Additionally, partial biodegradation was observed for 2b, indicating its possible biodegradation in wastewater treatment systems.     

Biosorption of arsenic from aqueous solution using dye waste

The purpose of this study is to examine on removal of arsenic from water by biosorption through potential application of herbal dye wastes. Four different flower dye residues (after extraction of natural dye) viz. Hibiscus rosasinensis, Rosa rosa, Tagetes erecta, and Canna indica were utilized successfully for the removal of arsenic from aqueous solution. Batch studies were carried out for various parameters viz. pH, sorbent dose, contact time, initial metal ion concentration, and temperature. Data were utilized for isothermal, kinetic, and thermodynamic studies. Scanning electron microscopy (SEM), energy-dispersive x-ray spectroscopy (EDAX), and Fourier transform infrared (FTIR) analyses of biomass were performed. The results showed that 1 g/100 ml for 5.0–5.5 h contact time at pH 6.0–7.5 with agitation rate 150 rpm provided 98, 96, 92, and 85 % maximum absorption of arsenic by R. rosa, H. rosasinensis, T. erecta, and C. indica, respectively, at initial concentration of 500 ppb. Data followed Langmuir isotherm showing sorption to be monolayer on heterogeneous surface of biosorbent. Negative values of ΔG° indicated spontaneous nature, whereas ΔH° indicates exothermic nature of system followed by pseudo-first-order adsorption kinetics. FTIR results showed apparent changes in functional group regions after metal chelation. SEM and EDAX analyses showed the changes in surface morphology of all test biosorbents. Herbal dye wastes, used as biosorbent, exhibited significant (85–98 %) removal of arsenic from aqueous solution. Hence, these biosorbents are cost-effective, easily available, eco-friendly, and comparatively more effective than other biosorbents already in use. These may be used to remove arsenic and other toxic metals from water.     

Prediction of dissolved oxygen concentration in hypoxic river systems using support vector machine: a case study of Wen-Rui Tang River,China

Accurate quantification of dissolved oxygen (DO) is critically important for managing water resources and controlling pollution. Artificial intelligence (AI) models have been successfully applied for modeling DO content in aquatic ecosystems with limited data. However, the efficacy of these AI models in predicting DO levels in the hypoxic river systems having multiple pollution sources and complicated pollutants behaviors is unclear. Given this dilemma, we developed a promising AI model, known as support vector machine (SVM), to predict the DO concentration in a hypoxic river in southeastern China. Four different calibration models, specifically, multiple linear regression, back propagation neural network, general regression neural network, and SVM, were established, and their prediction accuracy was systemically investigated and compared. A total of 11 hydro-chemical variables were used as model inputs. These variables were measured bimonthly at eight sampling sites along the rural-suburban-urban portion of Wen-Rui Tang River from 2004 to 2008. The performances of the established models were assessed through the mean square error (MSE), determination coefficient (R ²), and Nash-Sutcliffe (NS) model efficiency. The results indicated that the SVM model was superior to other models in predicting DO concentration in Wen-Rui Tang River. For SVM, the MSE, R ², and NS values for the testing subset were 0.9416 mg/L, 0.8646, and 0.8763, respectively. Sensitivity analysis showed that ammonium-nitrogen was the most significant input variable of the proposal SVM model. Overall, these results demonstrated that the proposed SVM model can efficiently predict water quality, especially for highly impaired and hypoxic river systems.     

An investigation of the formation of ambient NH4NO3 aerosol

The aerosol equilibrium formulation of Stelson and Seinfeld (1982a, b, Atmospheric Environment16, 983–992, 993–1000) is incorporated into the STEM-II transport/chemistry model and is evaluated against NH₃, HNO₃ and aerosol NH₄⁺ and NO₃⁻ measured at Nagano Prefecture, Japan on 29 and 30 July 1983. These results indicate that this modeling approach is useful in analyzing field data.     

Humidity effects on photochemical aerosol formation in the SO2-NO-C3H6-air system

In order to investigate the effects of humidity on the gas-phase oxidation of SO₂ in polluted air and on the subsequent aerosol formation process, photoirradiation experiments were carried out by means of a 4-m³ chamber, in which mixtures containing SO₂, NO and C₃H₆ with concentrations in the ppm range were exposed to simulated solar radiation in different relative humidity (r.h.) conditions. The total amount of oxidized SO₂ was quantified from the SO₄²⁻ yield determined by the chemical analysis of the aerosol product, and a part due to the oxidation by the OH radical was evaluated by estimating the OH concentration from the decay rate of C₃H₆. The remaining part was assigned to the oxidation by the Criegee intermediate, as it had a good correlation with the progress of the O₃ + C₃H₆ reaction. The contributions of the two oxidizing species to the total conversion and the oxidation rate of SO₂ were measured as functions of r.h. As a result, experimental evidence was obtained for the prediction of Calvert and Stockwell's (1983, Envir. Sci. Technol. 17, 428A–443A) simulation that the oxidation due to the Criegee intermediate was retarded by the increase in humidity. The OH contribution, on the other hand, was almost independent of r.h. It was observed consequently that the total oxidized amount of SO₂ considerably decreased as r.h. was higher.The humidity effect on the aerosol formation process was found to be more complicated than the effect on the gas-phase chemistry. The maximum rate of increase in the particle number concentration rose linearly with increasing r.h., but the number concentration itself measured at its maximum or at the end of the irradiation reached a ceiling value around r.h. = 30% and went down for higher r.h. The average panicle size in the final stage of the reaction showed a minimum around the same r.h. at which the number concentration was maximum. The H₂SO₄ concentration in the mist particles, however, decreased monotonically as r.h. got higher. It was suggested that these different responses against the increase in humidity resulted from the cooperation of several processes such as the H₂SO₄ monomer formation, the H₂O condensation, the particle coagulation, etc., which had different dependences on r.h.     

Emissions into the Atmosphere Due to the Ceramic Salt Glazing Process

The techniques of Principal Component Analysis (PCA) and subsequent regression analysis were used in an attempt to describe local and upwind chemical and physical factors which affect the variability of SO₄ ^–2 concentrations observed in a rural area of the northeastern U.S. The data used in the analyses included upwind and local O₃ concentrations, temperature, relative humidity and other climatological information, SO₂, and meteorological information associated with backward trajectories. The investigation identified five principal components, three major (eigenvalues >1) and two minor (eigenvalues < one), which accounted for 52% (r = 0.72) of the variability in the SO₄ ^–2 regression model. These components can be described as representing local and upwind photochemistry, droplet growth, SO₂ emissions, and air mass characteristics. The study also indicated that in future studies it will be necessary to a priori select air pollution and meteorological variables for measurement to potentially increase the sensitivity of this type of receptor model.     

Predicting personal exposure to airborne carbonyls using residential measurements and time/activity data

As a part of the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study, 48 h integrated residential indoor, outdoor, and personal exposure concentrations of 10 carbonyls were simultaneously measured in 234 homes selected from three US cities using the Passive Aldehydes and Ketones Samplers (PAKS). In this paper, we examine the feasibility of using residential indoor concentrations to predict personal exposures to carbonyls. Based on paired t-tests, the means of indoor concentrations were not different from those of personal exposure concentrations for eight out of the 10 measured carbonyls, indicating indoor carbonyls concentrations, in general, well predicted the central tendency of personal exposure concentrations. In a linear regression model, indoor concentrations explained 47%, 55%, and 65% of personal exposure variance for formaldehyde, acetaldehyde, and hexaldehyde, respectively. The predictability of indoor concentrations on cross-individual variability in personal exposure for the other carbonyls was poorer, explaining<20% of variance for acetone, acrolein, crotonaldehyde, and glyoxal. A factor analysis, coupled with multiple linear regression analyses, was also performed to examine the impact of human activities on personal exposure concentrations. It was found that activities related to driving a vehicle and performing yard work had significant impacts on personal exposures to a few carbonyls.     

Prediction of the adsorption capability onto activated carbon of a large data set of chemicals by local lazy regression method

Accurate quantitative structure–property relationship (QSPR) models based on a large data set containing a total of 3483 organic compounds were developed to predict chemicals’ adsorption capability onto activated carbon in gas phrase. Both global multiple linear regression (MLR) method and local lazy regression (LLR) method were used to develop QSPR models. The results proved that LLR has prediction accuracy 10% higher than that of MLR model. By applying LLR method we can predict the test set (787 compounds) with Q²_ext of 0.900 and root mean square error (RMSE) of 0.129. The accurate model based on this large data set could be useful to predict adsorption property of new compounds since such model covers a highly diverse structural space.     

Selection of an appropriate model to predict plume dispersion in coastal areas

In order to suggest a new methodology for selecting an appropriate dispersion model, various statistical measures having respective characteristics and recommended value ranges were integrated to produce a new single index by using fuzzy inference where eight statistical measures for various model results, including fractional bias (FB), normalized mean square error (NMSE), geometric bias mean (MG), geometric bias variance (VG), within a factor of two (FAC2), index of agreement (IOA), unpaired accuracy of the peak concentration (UAPC), and mean relative error (MRE), were taken as premise part variables. The new methodology using a single index was applied to the prediction of ground-level SO₂ concentration of 1-h average in coastal areas, where eight modeling combinations were organized with fumigation models, σ_y schemes for pre-fumigation, and modification schemes for σ_y during fumigation. As a result, the fumigation model of Lyons and Cole was found to have better predictability than the modified Gaussian model assuming that whole plume is immerged into the Thermal Internal Boundary Layer (TIBL). Again, a better scheme of σ_y (fumigation) was discerned. This approach, which employed the new integrated index, appears to be applicable to model evaluation or selection in various areas including complex coastal areas.     

A photochemical model for air quality assessment: Model description and verification

A hybrid Eulerian-Lagrangian, photochemical model has been developed for the assessment and prediction of the impact of large point sources on air quality. This simple model is based on solving the mass conservation equations which include chemical reaction terms in the cells of a two-dimensional crosswind plane which moves with the air parcel. Testing of the model is done in three ways. First, the chemistry is evaluated using results of smog chamber experiments simulating Melbourne's emissions and meteorological conditions. Second, the accuracy of the emissions inventory is tested using aircraft measurements. Finally the overall performance of the model is evaluated using monitoring station data. In general the model gives good agreement with the measurements, with the predictions for O₃ being somewhat better than those for NO₂. This result was also found in the three-dimensional study of McRae and Seinfeld (1983, Atmospheric Environment17, 501–522) for the Los Angeles area.