Receptor modeling for analyzing PCDD/F and dioxin-like PCB sources in Hong Kong

A total of 96 ambient air samples were collected from January 2004 to December 2004 for the investigation of dioxins (polychlorinated dibenzo-para-dioxins and polychlorinated dibenzofurans [PCDD/Fs]) and dioxin-like profile for polychlorinated biphenyls (PCBs) in the atmosphere of Hong Kong. Two-day back-trajectories were obtained using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model from National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory. Receptor models – potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) – were built based on the measured PCDD/Fs and dioxin-like PCBs total toxic equivalent (TEQ) concentrations. Both models were modified in this study so as to integrate the information obtained from three sampling sites in Hong Kong. The PSCF modeling resolved two main PCDD/F and dioxin-like PCB polluting paths from Mainland China. In line with previous studies, the northerly path around the Pearl River Delta might be one of the pollution sources of Hong Kong air. On the other hand, the receptor models also indicated another potential northeasterly source from Yangtze River Delta, which was seldom mentioned as the source region of Hong Kong air. Results from the CWT modeling suggested that the most toxic air mass affecting Hong Kong is probably attributable to the northeast path rather than the north path.     

Evaluation of Three Air Dispersion Models: ISCST2, ISCLT2, and Screen2 for Mercury Emissions in an Urban Area

The goal of this paper is to compare and evaluate the performance of three air quality regulatory models for mercury releases. The models include Industrial Source Complex Short Term model (ISCST2), Industrial Source Complex Long Term model (ISCLT2), and SCREEN2. The evaluation is conducted in multiple point source urban environment using meteorological data, emission inventory and monitoring data for eight stations for the year 1990 to 1992. The performance of the models is evaluated using eight statistical parameters. The comparison of models results for both quarterly and annual averaging periods shows that ISCST2 predictions qualitatively match the observed concentrations; whereas SCREEN2 predicts highest concentrations and ISCLT2 the lowest concentrations. The summary of statistical analysis obtained by using three different methods of observed concentration (Co) and predicted concentrations (Cp) comparison show that the ISCST2 has a better overall performance than ISCLT2 and SCREEN2 models. However, none of the models met the criteria for a reasonable model. Summaries of 95% confidence limits on normalize mean square error (NMSE), geometric mean variance (VG) and geometric mean bias (MG) for each and among model indicate that of the three models, ISCST2 has the best overall performance indicators. Improved model performance may be achieved by incorporating different types of mercury forms into emission rate and air dispersion calculations.     

Inverse Modeling for Aquatic Source and Transport Parameters Identification and its Application to Fukushima Nuclear Accident

Inverse modeling technique based on nonlinear least square regression method (LSRM) is developed for the identification of aquatic source and transport parameters. Instantaneous line source release model in two-dimensional domain and continuous point source release model in three-dimensional domain are used for the purpose. Case studies have been carried out for both types of releases to illustrate their application. Error analysis has been carried out to identify the maximum error that can be tolerated in the input concentration data used in the inverse model and to specify the minimum number of sampling points to generate such input data. The LSRM is compared with the well-established correlation coefficient optimization method for instantaneous line source release model, and good comparison is observed between them. The LSRM is used to quantitatively estimate the releases of different radionuclides into the Pacific Ocean which has resulted due to the discharge of highly radioactive liquid effluent from the affected Daiichi Nuclear Power Station at Fukushima in Japan. The measured concentrations of these radionuclides in seawater samples collected from two sampling points near Fukushima are used for the estimation. The average release works out to be 1.09?×?10¹⁶ for ¹³¹I, 3.4?×?10¹⁵ Bq for ¹³⁴Cs, and 3.57?×?10¹⁵ Bq for ¹³⁷Cs. Very good agreement is observed between the releases estimated in this study and those estimated by other different agencies.     

Monitoring and dispersion modelling of emissions from the fluidised bed combustion of poultry litter

Gaseous emissions from the fluidised bed combustion of chickenlitter were monitored and recorded. Emission data was used tocreate a dispersion model for a proposed site on a poultry farmin Limerick, Ireland. Variables within the combustion unit notonly influenced combustion but also emission levels ofpollutants such as SO₂ and NO_x. CO emissions decreased withuse of the correct ratio between fluidising and secondary air,the staging of secondary air and the degree of turbulence withwhich the secondary air is introduced. Dispersion modelling ofactual combustion at a proposed poultry unit predicted thatground level concentrations for the set of emissions data wouldbe below the limits and guidelines set by air quality standards.This was true for both and line source. Line sourceconcentration levels were less than those for point source.     

Assessing the Relative Importance of Spatial Variability in Emissions Versus Landscape Properties in Fate Models for Environmental Exposure Assessment of Chemicals

Multimedia mass balance models differ in their treatment of spatial resolution from single boxes representing an entire region to multiple interconnected boxes with varying landscape properties and emission intensities. Here, model experiments were conducted to determine the relative importance of these two main factors that cause spatial variation in environmental chemical concentrations: spatial patterns in emission intensities and spatial differences in environmental conditions. In the model, experiments emissions were always to the air compartment. It was concluded that variation in emissions is in most cases the dominant source of variation in environmental concentrations. It was found, however, that variability in environmental conditions can strongly influence predicted concentrations in some cases, if the receptor compartments of interest are soil or water—for water concentrations particularly if a chemical has a high octanol–air partition coefficient (K _oa). This information will help to determine the required level of spatial detail that suffices for a specific regulatory purpose.     

A statistical F test for the natural attenuation of contaminants in groundwater

Natural attenuation (NA) is a catchall explanation for the overall decay and slowed movement of the contaminants in the subsurface. One direct support to NA is to demonstrate that contaminant concentrations from monitoring wells located near the source are decreasing over time. The decrease is summarily expressed in terms of an apparent half-life that is determinedfrom the line best fitting the observed log-transformed concentration data and time. This simple (time-only) decay modelassumes other factors are invariant, and so is flawed when complicating factors – such as a fluctuating water table – are present. A history of the water-table fluctuation can track changes in important NA factors like recharge, groundwater flow direction and velocity, as well as other non-NA factors like volume of water in and purged from the well before a sample is collected. When the trend in the concentrations is better associated with the water table rising or falling, any conclusionabout degradation rate may be premature. We develop simple regressions to predict contaminant concentration (c) by two line models: one involving time (c c(t)), and another involving groundwater elevation (c c(z)). We develop a third model that includesboth factors (c c(t, z)). Using an F-test to compare the fits to the models, we determine which modelis statistically better in explaining the observed concentrations. We applied the test to sites where benzene degradation rates had previously been estimated. The F-testcan be used to determine the suitability of applying non-parametric statistics, like the Mann-Kendall, to the concentration data, because the result from the F-test canindicate instability of the contaminant plume that may bemasked when the water table fluctuates.     

General plume dispersion model (GPDM) for point source emission

Gaussian-based dispersion models are widely used to estimate local pollution levels. The accuracy of such models depends on stability classification schemes as well as plume rise equations. A general plume dispersion model (GPDM) for a point source emission, based on Gaussian plume dispersion equation, was developed. The program complex was developed using Java and Visual basic tools. It has the flexibility of using five kinds of stability classification schemes, i.e., Lapse Rate, Pasquill–Gifford (PG), Turner, σ–θ and Richardson number. It also has the option of using two types of plume rise formulations – Briggs and Holland’s. The model, applicable for both rural and urban roughness conditions, uses meteorological and emission data as its input parameters, and calculates concentrations of pollutant at the center of each cell in a predefined grid area with respect to the given source location. Its performance was tested by comparing with 4-h average field data of continuous releases of SO₂ from Dadri thermal power plant (Uttar Pradesh, India). Results showed that the Turner scheme used with Holland’s equation gives the best outcome having a degree of agreement (d) of 0.522.     

Modeling trihalomethane formation for Jabal Amman water supply in Jordan

A mathematical model that expresses Total trihalomethane (TTHM) concentration in terms of initial chlorine concentration, total organic carbon, bromide ion concentration, contact time, and pH is developed for Zai water treatment plant which supplies water to Jabal Amman. The developed mathematical model is for constant temperature of 20°C. To adjust model calculated TTHM concentrations for temperatures other than 20°C, another mathematical model that expresses TTHM growth rate as function of temperature is also developed. To test the ability of the two developed models in predicting TTHM concentrations throughout water supplies, a sampling program that aimed at measuring TTHM concentrations in addition to the predictors in the two developed mathematical models namely; chlorine concentration, bromide ion concentration, total organic carbon, temperature and pH throughout Jabal Amman water supply was conducted. The two developed mathematical models and WaterCad, which was used to determine water age, were used to predict TTHM concentrations throughout Jabal Amman water supply. Predicted TTHM concentrations were compared to actual TTHM concentrations measured during the sampling program. Results showed that there is good agreement between measured and, calculated TTHM concentrations, which means that the method presented in this paper, can be used to obtain good estimates of TTHM concentrations throughout networks.     

Multipoint source method in air pollution modelling of cold start emission

The paper presents a new method of air pollution modelling on a micro scale. For estimation of concentration of car exhaust pollutants, each car is treated as an instantaneous moving emission source. This approach enables us to model time and spatial changes of emission, especially during cold and cool start of an engine. These stages of engine work are a source of significant pollution concentration in urban areas. In this work, two models are proposed: one for the estimation of emission after cold start of the engine and another for the prediction of pollutant concentration. The first model (defined for individual exhaust gas pollutants) enables us to calculate the emission as a function of time after the cold or cool start, ambient temperature and average speed of motion. This model uses the HBEFA database. The second mathematical model is developed in order to calculate the pollutant dispersion and concentrations. The finite volume method is applied to discretise the set of partial differential equations describing wind flow and pollutant dispersion in the domain considered. Models presented in this paper can be called short-term models on a small spatial scale. The results of numerical simulation of pollutant emission and dispersion are also presented.     

Measurement and Interpretation of Concentrations of Urban Atmospheric Organic Compounds

The presence of volatile organic compounds (VOCs) from traffic and other sources in urban areas is a cause for concern about public health. Canister, chemical derivatisation, particulate sampling and adsorption sampling techniques were used to measure VOC concentrations of a wide range of compounds (C6-C40) during a four day campaign in south London with subsequent laboratory analysis of the samples. Compounds quantified included alkanes, mono- and poly-nuclear aromatic hydrocarbons. Also the first sequential measurements of carbonyl compounds (C1-C8) in a UK urban area are presented. Results from canister and adsorption sampling methods are compared. A comparison of the results with other urban data is presented and the temporal variations in VOC concentrations were interpreted with reference to the prevalent wind speeds and directions. The CALINE4 line source dispersion model was generally successful in reproducing the daytime 12 hour average concentrations of selected VOCs.     

Modelling the Size Separated Particulate Matter (SSPM10) from Vehicular Exhaust at Traffic Intersections in Mumbai

The study was carried out to predict the size separated particulate matter below 10 microm size (SSPM10) from vehicular exhausts at traffic intersections using modified general finite line source model (GFLSM). Two air quality control regions (AQCRs) were selected in Mumbai City for this study. One was industrial area (AQCR1) containing the busy intersection, i.e. Marol link road, with the heavy inflow of two-three wheelers. And, the other was commercial busy district area (AQCR2) containing the busy intersection, i.e. Dadar circle, with a heavy traffic flow especially cars. The model was applied at both the traffic intersections. The data were collected for modelling study for three winter months in 1995 using cascade impactor of nine size ranges. The prediction results revealed that modified GFLSM underpredicted the SSPM10 concentrations for all the size ranges. However, showed considerable correlation between observed and predicted values for the size range below 4.7 microm at both the intersections. The relative high concentrations observed in the coarser range of 10-4.7 microm are attributed to the resuspension of the roadside particulate matter. Hence, the amount of underprediction was more for this range, which was due to the characteristics of model that does not take into account the factor for resuspension of roadside particulate matter caused by traffic movements. The model was also applied to predict the total particulate matter for downwind distances from the road intersection. The statistical evaluation of model was done, which indicated that the model's performance was good for the finer range of particles (below 4.7 microm) with r-square values of 0.49 and 0.57 found at both the intersections in AQCR1 and AQCR2, respectively. However, it is not unusual that the model uncertainty is likely to exist due to data input errors and stochastic fluctuations irrespective of the models accurateness. The statistical distribution model was therefore identified using Kolmogorov-Smirnov test. At both the intersections, SSPM10 concentration data were found lognormally distributed.     

Comparison of field-observed and model-predicted plume trends at fuel-contaminated sites: implications for natural attenuation rates

Subsequent to modeling of natural attenuation processes to predict contaminant trends and plume dynamics, monitoring data were used to evaluate the effectiveness of natural attenuation at reducing contaminant concentrations in groundwater at seven fuel-contaminated sites. Predicted and observed contaminant trends at seven sites were compared in order to empirically assess the accuracy of some fundamental model input parameters and assumptions. Most of the models developed for the study sites tended to overestimate plume migration distance, source persistence, and/or the time required for the benzene, toluene, ethyl benzene, and xylenes (BTEX) plumes to attenuate. Discrepancies between observed and predicted contaminant trends and plume behavior suggested that the influence of natural attenuation process may not have been accurately simulated. The conservatism of model simulations may be attributed to underestimation of natural source weathering rates, overestimation of the mass of contaminant present in the source area, and/or use of overly conservative first-order solute decay rates.     

Simulation of PM<Subscript>10</Subscript> concentration patterns for a 2010 traffic scenario in Bologna,Italy

Three state of the art traffic–emission–dispersion models dealing with particulate matter have been tested and validated over the Bologna metropolitan area with 2001 data and a future scenario has been developed in order to estimate expected PM concentrations in 2010. The modelling system is composed by a traffic model (VISUM) evaluating vehicle fluxes as a function of mobility demand and road network in the area, an emission model (Trefic) estimating pollutants emitted in atmosphere as a function of vehicle fluxes amount and composition and of environmental conditions and a dispersion model (ADMS) evaluating PM concentrations on the area, given the meteorological variables. The three models compose a cascade sequence and results of the previous one feed the next one. PM concentrations computed by the model suite for the town of Bologna, in northern Italy, for the reference period (January 2001) have been compared with air quality stations measurements suggesting the modelling system being especially suitable for evaluating traffic induced PM. Qualitative and quantitative changes in the circulating vehicle fleet have been supposed in order to obtain a realistic scenario for year 2010. Forecasted concentrations have been then compared with limits fixed by current EU legislation for particulate matter.     

基于LS-SVR、BP-ANN和MLR模型的PM10浓度预测

利用宁东能源化工基地PM10和气象监测数据,分别采用LS-SVR、BP-ANN和传统MLR模型预测PM10浓度变化。结果表明,较BP-ANN模型、MLR模型,LS-SVR模型能更好地刻画PM10浓度与各气象因素间的非线性相依关系,更准确地预测PM10浓度。     

Stochastic approaches for time series forecasting of boron: a case study of Western Turkey

In the present study, a seasonal and non-seasonal prediction of boron concentrations time series data for the period of 1996–2004 from Büyük Menderes river in western Turkey are addressed by means of linear stochastic models. The methodology presented here is to develop adequate linear stochastic models known as autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to predict boron content in the Büyük Menderes catchment. Initially, the Box–Whisker plots and Kendall’s tau test are used to identify the trends during the study period. The measurements locations do not show significant overall trend in boron concentrations, though marginal increasing and decreasing trends are observed for certain periods at some locations. ARIMA modeling approach involves the following three steps: model identification, parameter estimation, and diagnostic checking. In the model identification step, considering the autocorrelation function (ACF) and partial autocorrelation function (PACF) results of boron data series, different ARIMA models are identified. The model gives the minimum Akaike information criterion (AIC) is selected as the best-fit model. The parameter estimation step indicates that the estimated model parameters are significantly different from zero. The diagnostic check step is applied to the residuals of the selected ARIMA models and the results indicate that the residuals are independent, normally distributed, and homoscadastic. For the model validation purposes, the predicted results using the best ARIMA models are compared to the observed data. The predicted data show reasonably good agreement with the actual data. The comparison of the mean and variance of 3-year (2002–2004) observed data vs predicted data from the selected best models show that the boron model from ARIMA modeling approaches could be used in a safe manner since the predicted values from these models preserve the basic statistics of observed data in terms of mean. The ARIMA modeling approach is recommended for predicting boron concentration series of a river.     

Investigation of Building - Influenced Atmospheric Dispersion Using a Dual Source Technique

Dispersion of atmospheric contaminants in the vicinity of an isolated cubical model building was investigated in the field. A dual source/receptor technique was used in the experiments, which was proved to be very useful for the investigation of pollution dispersion. This experimental technique involved the simultaneous release of two different tracer gases from two different point sources, and the deployment of a FID (Flame Ionization Detector) co-located with a UVIC®(Ultra-Violet Ion Collector) detector. Both mean concentrations and concentration fluctuation statistics were examined. In this paper concentration fluctuation statistics are presented. The effect of the upwind source location on intermittency values and on the cumulative density function (cdf) is examined. The exact location of a source placed upwind of an obstacle has a very significant and complex effect on both mean concentrations and concentration fluctuations. As the lateral or vertical displacement between the two sources is increased, cross-correlation values between data taken simultaneously by two co-located detectors decrease rapidly.     

道路交通噪声预测声源简化研究

为了分析《环境影响评价技术导则声环境》(HJ 2.4—2009)中将道路声源简化为1条位于道路中心线处的线声源与按照车道数简化为多条线声源之间的误差,针对不同宽度的道路,推导了多条线声源与1条线声源在接收点噪声影响的误差计算公式,并基于Predictor-lima预测软件预测和现场噪声衰减规律实测进行了验证。研究结果表明,对于接收点到道路边缘的距离大于道路宽度的情况,可简化为1条线声源;对于接收点到道路边缘的距离小于道路宽度的情况,应按照车道数简化为多条线声源。     

大气颗粒物源解析受体模型应用研究及发展现状

通过大量文献资料调研对化学质量平衡模型、二重源解析技术、主因子分析、正矩阵因子分析法等目前应用较广泛的受体模型方法的原理、优缺点和应用现状进行了比较分析,对单颗粒源解析方法、有机物示踪技术和扩散与受体模型联用技术等受体模型新技术方法进行了评述。     

青岛市港口船舶大气污染排放清单的建立及应用

2002~2006年青岛市环保局与瑞典国际开发合作署合作开发了青岛市空气环境质量管理系统,建立青岛市海上交通源大气污染排放清单是其中的一项子专题,范围涉及青岛沿岸分布的港口,重点考虑船舶停泊港口及航线过程的大气污染物排放,划分了20条航线。建立的青岛市海上交通源大气污染排放清单在开发的基于GIS地理信息系统EnviMan复合源大气扩散模型中得到较好应用,实现了对沿海主要大气污染物排放量的空间模拟测算,解析出大气污染排放清单建立年度青岛市港口、航运排放的大气污染物对市区环境空气中的SO₂、NO_X浓度贡献分别约占8.0%、12.9%。