Application of a stochastic, Weibull probability generator for replacing missing data on ambient concentrations of gaseous pollutants

A stochastic, three-parameter, Weibull frequency distribution, probability generator was tested by using theoretical data. Subsequently, it was applied to replace missing values of hourly atmospheric concentrations of trace gases that were continuously monitored at three study sites, for 2 years. The results were highly accurate and realistic. The cumulative means and the medians calculated by the Weibull method were intermediate between corresponding values calculated by uniform substitution of missing values with 'zero' or with half of the minimum detection limit of the appropriate measurement instrument used. Furthermore, the Weibull method allowed the replacement of as many as 100 missing values on either side of a measured data sub-set, without altering the overall characteristics of the true frequency distribution of the entire data set.     

Estimating net changes in life-cycle emissions from adoption of emerging civil infrastructure technologies

There is a net emissions change when adopting new materials for use in civil infrastructure design. To evaluate the total net emissions change, one must consider changes in manufacture and associated life-cycle emissions, as well as changes in the quantity of material required. In addition, in principle one should also consider any differences in costs of the two designs because cost savings can be applied to other economic activities with associated environmental impacts. In this paper, a method is presented that combines these considerations to permit an evaluation of the net change in emissions when considering the adoption of emerging technologies/materials for civil infrastructure. The method factors in data on differences between a standard and new material for civil infrastructure, material requirements as specified in designs using both materials, and price information. The life-cycle assessment approach known as economic input-output life-cycle assessment (EIO-LCA) is utilized. A brief background on EIO-LCA is provided because its use is central to the method. The methodology is demonstrated with analysis of a switch from carbon steel to high-performance steel in military bridge design. The results are compared with a simplistic analysis that accounts for the weight reduction afforded by use of the high-performance steel but assuming no differences in manufacture.     

Functional models for colloid retention in porous media at the triple line

Spectral confocal microscope visualizations of microsphere movement in unsaturated porous media showed that attachment at the Air Water Solid (AWS) interface was an important retention mechanism. These visualizations can aid in resolving the functional form of retention rates of colloids at the AWS interface. In this study, soil adsorption isotherm equations were adapted by replacing the chemical concentration in the water as independent variable by the cumulative colloids passing by. In order of increasing number of fitted parameters, the functions tested were the Langmuir adsorption isotherm, the Logistic distribution, and the Weibull distribution. The functions were fitted against colloid concentrations obtained from time series of images acquired with a spectral confocal microscope for three experiments performed where either plain or carboxylated polystyrene latex microspheres were pulsed in a small flow chamber filled with cleaned quartz sand. Both moving and retained colloids were quantified over time. In fitting the models to the data, the agreement improved with increasing number of model parameters. The Weibull distribution gave overall the best fit. The logistic distribution did not fit the initial retention of microspheres well but otherwise the fit was good. The Langmuir isotherm only fitted the longest time series well. The results can be explained that initially when colloids are first introduced the rate of retention is low. Once colloids are at the AWS interface they act as anchor point for other colloids to attach and thereby increasing the retention rate as clusters form. Once the available attachment sites diminish, the retention rate decreases.     

一株高效广谱染料脱色菌脱色条件的优化

以模拟酸性大红3R染料废水为对象,在单因素实验基础上,选取温度、初始染料浓度、酵母粉浓度三因素为影响因子,以染料脱色率为响应值,利用Box-Behnken设计及响应面分析法研究了各因素对一株广谱型染料脱色菌株Enterobacter cloacae strain M3脱色效果的影响及各因素间交互作用,建立了二次多项式回归方程的预测模型,确定了菌株脱色酸性大红3R废水的优化条件。结果表明：回归方程极显著,拟合性好。最优脱色条件为温度36℃,染料浓度121.12 mg/L,酵母粉浓度1.99%,在此条件下,染料脱色率可达99.21%。经实验验证,实际值与模型预测值拟合良好,偏差仅为0.79%。     

Comparison of six particle size distribution models on the goodness-of-fit to particulate matter sampled from animal buildings

Lognormal distribution is often used as a default model for regression analysis of particle size distribution (PSD) data; however, its goodness-of-fit to particle matter (PM) sampled from animal buildings and its comparison to other PSD models have not been well examined. This study aimed to evaluate and to compare the goodness-of-fit of six PSD models to total suspended particulate matter (TSP) samples collected from 15 animal buildings. Four particle size analyzers were used for PSD measurement. The models' goodness-of-fit was evaluated based on adjusted R2, Akaike's information criterion (AIC), and mean squared error (MSE) values. Results showed that the models' approximation of measured PSDs differed with particle size analyzer. The lognormal distribution model offered overall good approximations to measured PSD data, but was inferior to the gamma and Weibull distribution models when applied to PSD data derived from the Horiba and Malvern analyzers. Single-variable models including the exponential, Khrgian-Mazin, and Chen's empirical models provided relatively poor approximations and, thus, were not recommended for future investigations. A further examination on model-predicted PSD parameters revealed that even the best-fit model of the six could significantly misestimate mean diameter median diameter; and variance. However, compared with other models, the best-fit model still offered the relatively best estimates of mean and median diameters, whereas the best predicted variances were given by the gamma distribution model.     

Cost-effective experimental design to support modeling of concentration-response functions

Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments.     

Online update of model state and parameters of a Monte Carlo atmospheric dispersion model by using ensemble Kalman filter

For an atmospheric dispersion model designed for the assessment of nuclear accident consequences, some uncertain model parameters, such as source term and weather conditions, may influence the reliability of model predictions. In this respect, good estimations of both model state and uncertain parameters are required. In this paper, an ensemble Kalman filter (EnKF) based method for simultaneous state and parameter estimation, using off-site radiation monitoring data, is presented. This method is based on a stochastic state space model, which resembles the parameter errors with stochastic quantities. Three imperfect parameters, including the source release rate, wind direction and turbulence intensity were perturbed simultaneously, and multiple parameter estimation were performed. Having been tested against both simulated and real radiation monitoring data, the method was found to be able to realistically reconstruct the real scene of dispersion, as well as the uncertain parameters. The estimated parameters given by EnKF nicely converge to the true values, and the method also tracks the temporal variation of those parameters.     

Experimental studies on particle impaction and bounce: effects of substrate design and material

This paper presents an experimental investigation of the effects of impaction substrate designs and material in reducing particle bounce and reentrainment. Particle collection without coating by using combinations of different impaction substrate designs and surface materials was conducted using a personal particle sampler (PPS) developed by the University of Southern California. The PPS operates at flow rate of 4 l min^-1 with a 50% cutpoint of approximately 0.9 μm in aerodynamic diameter. The laboratory results showed that the PPS collection efficiency for particles larger than 50% cutpoint is strikingly low (e.g., less than 50%) when an uncoated open cavity made of aluminum was used as an impaction substrate. The collection efficiency gradually increased when Teflon tape, Nuclepore, and glass fiber filters were used as impaction surfaces, respectively. Conical or partially enclosed cavity substrate designs increased collection efficiency of particles of 9 μm up to 80–90%. A conical cavity with glass fiber filter used as impaction surface was identified as the optimum configuration, resulting in a collection efficiency of 92% at Stokes numbers as high as 15.4 (corresponding to 9 μm in aerodynamic diameter). Particle losses were low (less than 10%) and relatively independent of particle size in any design with glass fiber filter. Losses seemed to increase slightly with particle size in all other configurations. Finally, outdoor PM₁ concentrations obtained with the PPS (in its optimum configuration) and a modified micro-orifice uniform deposit impactor (MOUDI) with coated impaction stages were in excellent agreement. The mean ratio of the PPS-to-MOUDI concentration was 1.13(±0.17) with a correlation coefficient R²=0.95. Results from this investigation can be readily applied to design particle bounce-free impaction substrates without the use of coating. This is a very important feature of impactors, especially when chemical analysis of the collected particulate matter is desirable.     

Phytotoxicity of low-weight carboxylic acids

Presence of low-weight carboxylic acids (LWCAs) can be the reason for phytotoxicity of green manures, treated bio-waste or digestates from biogas production applied to soils. As the phytotoxic concentrations of LWCA are poorly known, this work presents data on six acids (C(1)C(6): formic, acetic, propionic, butyric, valeric, and caproic). Phytotoxicity was measured in acute (72 or 120 h) and subchronic (21 d) assays for seed germination, seedling elongation, and plant growth for garden cress Lepidium sativum and ryegrass Lolium multiflorum. The dose-response relationship was modeled using Weibull model. Results showed a trend that toxicity of LWCA increases with the length of the carbon chain, formic acid (C(1)) being the least and caproic acid (C(6)) the most toxic. EC50 values in the acute seed germination of cress ranged between 1.9 and 4.2mM and for ryegrass between 1.8 and 6.4mM. In subchronic assays EC50 values for germination were in a range from 11 to 46mMkg(-1)dm for cress, and from 18 to 127 mM kg(-1) dm for ryegrass. EC50 values for early seedling growth of cress based on acute assays ranged from 0.7 to 2.3mM and that of ryegrass from 1.2 to 1.8mM. Range of EC50 values for shoot biomass of cress was between 8 and 40 mM kg(-1) dm and of ryegrass between 12 and 93 mM kg(-1) dm.     

Scientific Basis for the VOC Reactivity Issues Raised by Section 183(e) of the Clean Air Act Amendments of 1990

A methodology for determining regional ozone design values and the expected number of exceedances is described. The methodology was applied to data bases for one year or less from four U.S. urban areas: Houston, Los Angeles, Philadelphia, and St. Louis. The effects of reducing numbers of stations in a network were tested, and it was concluded that networks of nine or ten appropriately selected stations are adequate for estimating design values. Using the methodology described, the expected number of exceedances tends to be underestimated when using smaller networks; however, this appears to be an artifact of the conservative approach taken in developing the methodology.     

Characterization of urea SCR using Taguchi technique and computational methods

Use of biodiesel in diesel engine helps to reduce HC, CO, and smoke emissions due to their enormous oxygen content, whereas NOx emissions formed by Zeldovich mechanism shoot up. Implementation of Bharat Stage (BS) VI by April 2020 in India has created extreme pressure on automobile manufacturers to include after treatment technology in their systems. Selective catalytic reduction (SCR), a NOx control technology, is operated using aqueous urea solution as the reductant. There are several parameters that need to be monitored to enhance the NOx conversion efficiency of SCR retrofit. The uniformity index of ammonia, which determines the conversion efficiency, is greatly influenced by parameters like exhaust gas temperature, injection angle, injector position, mass flow rate, and SCR geometry. This paper considers two types of SCR design, namely SCR with and without mixer design and their impact on NOx reduction. The effect of mass flow rate on urea conversion in SCR design without mixer is 27%, but the impact is reduced greatly in SCR design with mixer with less than 2% variation. The UI resulting from different cases ranges from 0.59 to 0.83. Using Taguchi technique and CFD tool, the impact of parameters on both the SCR designs has been investigated and the optimum SCR design is reported.

     

Prediction of carbon monoxide acute air pollution episodes. Model formulation and first application in Lombardy

This paper describes a method to forecast the exceedance probability of a fixed threshold for a certain air pollutant concentration. This general approach has been applied in the case of carbon monoxide on 35 traffic monitoring stations in the Lombardy Region. The implemented model has been called FOREPOLL (Forecast Pollution).The model structure, consisting in three basic modules (the deterministic, the stochastic and the Bayesian one), has been thought to be adjustable to different stations of an air quality network and to various pollutants. Forepoll uses the last biennium data set of the station in exam (pollutants and micrometeorological parameters) as a moving learning time and also needs the forecasted synoptic weather type. In the first module the daily maxima of the hourly measured pollutant concentrations are checked in order to eliminate some known physical dependencies, such as the temperature dependence of the emissions. Then the data are divided into subgroups depending on the weather type and in each group fitted by a different Weibull distribution. To provide a first a priori exceedance probability, this distribution is daily rebuilt by taking into account the forecasted parameters. In the last module this probability is enhanced or reduced using simple, experience based, bayesian rules providing the a posteriori exceedance probability.Model validation trials have been carried out on a year of CO forecasted concentrations in different air quality stations; the first results are quite good particularly for the metropolitan areas, because the model seems to work better in case of stronger and more diffuse pollution.     

A semi-empirical model for urban PM10 concentrations,and its evaluation against data from an urban measurement network

We have developed a model for evaluating the mass-based concentrations of urban particulate matter. The basic model assumption is that local vehicular traffic is responsible for a substantial fraction of the street-level concentrations of both PM₁₀ and NO_x, either due to primary emissions or resuspension from street surfaces. The modelling system utilises the data from an air quality monitoring network in the Helsinki Metropolitan Area. We have determined linear relationships between the measured urban PM₁₀ data against those of NO_x in various urban surroundings, based on continuously measured hourly concentration values. The data was obtained from two stations in central Helsinki and one suburban station in the Helsinki Metropolitan Area during a period of 3 yr, from 1996 to 1998. The model also includes a treatment of the regional background concentrations, and resuspended particulate matter. The model performance was evaluated against the measured PM₁₀ data from the above-mentioned three stations and from two other stations, using data that was measured in 1999. We used two alternative model versions, one based on separate correlation parameters (PM₁₀ vs. NO_x) for each station, and another based on parameters averaged over the stations considered. We analysed the agreement between the measured and predicted hourly concentration time series, utilising the values of the fractional bias (FB) and the so-called index of agreement (IA). As expected, the model predicts relatively well the yearly mean concentrations of PM₁₀: the FB values range from −0.05 to +0.09. Model performance is also relatively good when predicting the yearly mean values that are classified separately for each hour of the day: the corresponding IA values range from 0.85 to 0.96. However, model performance is substantially worse in predicting the hourly time series of the year: the IA values using the station-specific parameters range from 0.46 to 0.65. The model was applied in evaluating the yearly average spatial concentration distribution of PM₁₀ in central Helsinki, based on the corresponding modelled NO_x concentrations. With re-evaluation of a few parameters that can be determined empirically, the model could be evaluated, and most probably applied, in other urban areas as well.     

Uncertainty assessment of contaminant plume length estimates in heterogeneous aquifers

The Virtual Aquifer approach is used in this study to assess the uncertainty involved in the estimation of contaminant plume lengths in heterogeneous aquifers. Contaminant plumes in heterogeneous two-dimensional conductivity fields and subject to first order and Michaelis-Menten (MM) degradation kinetics are investigated by the center line method. First order degradation rates and plume lengths are estimated from point information obtained along the plume center line. Results from a Monte-Carlo investigation show that the estimated rate constant is highly uncertain and biased towards overly high values. Uncertainty and bias amplify with increasing heterogeneity up to maximum values of one order of magnitude. Calculated plume lengths reflect this uncertainty and bias. On average, plume lengths are estimated to about 50% of the true plume length. When plumes subject to MM degradation kinetics are investigated by using a first order rate law, an additional error is introduced and uncertainty as well as bias increase, causing plume length estimates to be less than 40% of the true length. For plumes with MM degradation kinetics, therefore, a regression approach is used which allows the determination of the MM parameters from center line data. Rate parameters are overestimated by a factor of two on average, while plume length estimates are about 80% of the true length. Plume lengths calculated using the MM parameters are thus closer to the correct length, as compared to the first order approximation. This approach is therefore recommended if field data collected along the center line of a plume give evidence of MM kinetics.     

工艺参数对表面活性剂洗涤修复PAHs污染土壤的影响

采用土壤洗涤(soil-washing)技术,分别用TritonX-100和Tween-80为强化洗涤剂研究了搅拌强度、洗涤时间、表面活性剂浓度、液固比、温度和间歇搅拌6个工艺参数对PAHs污染土壤洗涤效果的影响。通过一系列烧杯搅拌实验得到最佳洗涤工艺参数。TritonX-100和Tween-80的最佳洗涤时间分别是30 min和60 min,其他工艺参数最佳条件均相同。分别是搅拌强度为250 r/min,表面活性剂浓度为5 g/L,液固比为10∶1,温度为室温和连续搅拌。在此最佳工艺参数条件下,污染土中PAHs的残留率<10%,基本上满足目标污染物的修复目标。应用表面活性剂强化洗涤技术修复PAHs污染土壤是合理和可行的。     

A Box-Behnken design for determining the optimum experimental condition of the fungicide (Vapam) sorption onto soil modified with perlite

In the present study, response surface methodology (RSM) based on the Box-Behnken design (BBD) was employed to investigate the effects of the different operating conditions on the removal of the fungicide (Vapam) onto soil modified with perlite using sorption process. The process parameters such as pH of the fungicide solution (2, 5 and 8), temperature (15, 25 and 35°C), shaking time (2, 13 and 24 h) and the percentage of perlite in the modified soil (0, 2 and 4 %) were investigated using a four-factor-three-level Box-Behnken design at an initial fungicide concentration of C(0) = 1.6 mg/L as a fixed input parameter. A second-order quadratic model suggested the optimum conditions to be as follows: fungicide solution pH of 3.57, temperature of 15°C, shaking time of 3.5 h and 4% of perlite in the modified soil which resulted in the improvement of Vapam sorption. Under optimum conditions, the fungicide (Vapam) removal was predicted 12.88 μg/g by BBD. The confirmatory experiments were conducted and the results revealed that the fungicide removal was 13.14 μg/g which indicated that the predicted and the observed values of response (Vapam removal) were in close agreement. Therefore, the soil modified with perlite holds good potential for Vapam sorption. This is the first report on fungicide Vapam sorption onto soil modified with perlite using statistical experimental design employing response surface methodology.     

Use of passive ambient ozone (O3) samplers in vegetation effects assessment

A stochastistic, Weibull probability model was developed and verified to simulate the underlying frequency distributions of hourly ozone (O3) concentrations (exposure dynamics) using the single, weekly mean values obtained from a passive (sodium nitrite absorbent) sampler. The simulation was based on the data derived from a co-located continuous monitor. Although at the moment the model output may be considered as being specific to the elevation and location of the study site, the results were extremely good. This effort for the approximation of the O3 exposure dynamics can be extended to other sites with similar data sets and in developing a generalized understanding of the stochastic O3 exposure-plant response relationships, conferring measurable benefits to the future use of passive O3 samplers, in the absence of continuous monitoring.     

Isomeric analysis of PCDD/PCDF in waste incinerator fly ash by GC-MS/MS

The development of an analytical method for the analysis of PCDD/PCDF in flyash using a bench analytical system comprising of a gas chromatograph fitted with an ion trap detector operated in the tandem MS mode is described. The optimum settings for the most important MS/MS parameters are given, including those for the less reported mono- to tri-chlorinated dioxin and furan congener groups. Flyash samples from three waste incineration plants representing a decommissioned 1970s plant design, an upgraded and still operating plant originally designed in the 1970s, and a modern 1990s design operating plant have been analysed for PCDD/PCDF. The flyash samples were analysed for PCDD/PCDF using the methods developed and the total PCDD/PCDF, I-TEQ values and isomeric profiles are reported. The flyash from the older decommissioned incinerator had very significantly higher concentrations of PCDD/PCDF compared to the modern incinerator flyash.     

Modeling biodegradation and kinetics of glyphosate by artificial neural network

An artificial neural network (ANN) model was developed to simulate the biodegradation of herbicide glyphosate [2-(Phosphonomethylamino) acetic acid] in a solution with varying parameters pH, inoculum size and initial glyphosate concentration. The predictive ability of ANN model was also compared with Monod model. The result showed that ANN model was able to accurately predict the experimental results. A low ratio of self-inhibition and half saturation constants of Haldane equations (< 8) exhibited the inhibitory effect of glyphosate on bacteria growth. The value of K(i)/K(s) increased when the mixed inoculum size was increased from 10(4) to 10(6) bacteria/mL. It was found that the percentage of glyphosate degradation reached a maximum value of 99% at an optimum pH 6-7 while for pH values higher than 9 or lower than 4, no degradation was observed.     

A Box-Behnken design for determining the optimum experimental condition of the fungicide (Vapam) sorption onto soil modified with perlite

In the present study, response surface methodology (RSM) based on the Box-Behnken design (BBD) was employed to investigate the effects of the different operating conditions on the removal of the fungicide (Vapam) onto soil modified with perlite using sorption process. The process parameters such as pH of the fungicide solution (2, 5 and 8), temperature (15, 25 and 35°C), shaking time (2, 13 and 24 h) and the percentage of perlite in the modified soil (0, 2 and 4 %) were investigated using a four-factor-three-level Box-Behnken design at an initial fungicide concentration of C₀ = 1.6 mg/L as a fixed input parameter. A second-order quadratic model suggested the optimum conditions to be as follows: fungicide solution pH of 3.57, temperature of 15°C, shaking time of 3.5 h and 4% of perlite in the modified soil which resulted in the improvement of Vapam sorption. Under optimum conditions, the fungicide (Vapam) removal was predicted 12.88 μg/g by BBD. The confirmatory experiments were conducted and the results revealed that the fungicide removal was 13.14 μg/g which indicated that the predicted and the observed values of response (Vapam removal) were in close agreement. Therefore, the soil modified with perlite holds good potential for Vapam sorption. This is the first report on fungicide Vapam sorption onto soil modified with perlite using statistical experimental design employing response surface methodology.