Evaluation of the Industrial Source Complex short-term model in a large-scale multiple source region for different stability classes

The original Industrial Source Complex Model (ISCST, 90346) and its latest version, the ISCST2 (92090), are evaluated for the 1- and 24-hour averaging periods, using six statistical parameters. The confidence limits on two parameters were obtained using the bootstrap, jacknife, seductive, and robust resampling techniques. Evaluation is conducted in a multiple point source environment and in all the different stability categories, using a year of meteorological data, emission inventory of the Lucas County, in Toledo, Ohio, and monitoring data from two nearby stations for the year 1987. This was representative of a real time situation in which the ISCST is generally applied for regulatory work. The sensitivity analysis shows that the ISC is a poor performing model in the 1-h and 24-h averaging period, neutral and stable categories, and modifications to it are necessary in order to improve its performance. Its performance changes depending on the chosen paired values. A better relative performance is observed in the unstable category relative to the neutral and stable categories. Improved model performance may be achieved by applying modifications to the physics on which the model is based.     

Aerosols concentration in the Candiota area applying different gravimetric methods of sampling and numeric modelling

The main purpose of the present work is to study the concentration of atmospheric particles in the Candiota region, in the state of Rio Grande do Sul, where the Presidente Médici coal power plant is located. Aerosol samples were collected at the studied locations between December 2000 and December 2001 during 24 h periods at 15 day intervals using HV PM10 and dichotomous samplers. Then, the values obtained with the ISCST (Industrial Source Complex Term) model, with the HV PM10 sampler at all studied stations, and with the dichotomous sampler at the 8 de Agosto station were compared with each other. The results show that the values for the model had been underestimated in relation to the HV PM10 data for the studied stations, but agreed with the values obtained with the dichotomous sampler.     

Integrated assessment of brick kiln emission impacts on air quality

This paper presents monitoring results of daily brick kiln stack emission and the derived emission factors. Emission of individual air pollutant varied significantly during a firing batch (7 days) and between kilns. Average emission factors per 1,000 bricks were 6.35–12.3 kg of CO, 0.52–5.9 kg of SO₂ and 0.64–1.4 kg of particulate matter (PM). PM emission size distribution in the stack plume was determined using a modified cascade impactor. Obtained emission factors and PM size distribution data were used in simulation study using the Industrial Source Complex Short-Term (ISCST3) dispersion model. The model performance was successfully evaluated for the local conditions using the simultaneous ambient monitoring data in 2006 and 2007. SO₂ was the most critical pollutant, exceeding the hourly National Ambient Air Quality Standards over 63 km² out of the 100-km² modelled domain in the base case. Impacts of different emission scenarios on the ambient air quality (SO₂, PM, CO, PM dry deposition flux) were assessed.     

Emissions of SO2, NO x and particulates from a pipe manufacturing plant and prediction of impact on air quality

Integrated pipe manufacturing industry is operation intensive and has significant air pollution potential especially when it is equipped with a captive power production facility. Emissions of SO₂, NO _x , and particulate matter (PM) were estimated from the stationary sources in a state-of-the-art pipe manufacturing plant in India. Major air polluting units like blast furnace, ductile iron spun pipe facility, and captive power production facility were selected for stack gas monitoring. Subsequently, ambient air quality modeling was undertaken to predict ground-level concentrations of the selected air pollutants using Industrial Source Complex (ISC 3) model. Emissions of SO₂, NO _x , and particulate matter from the stationary sources in selected facilities ranged from 0.02 to 16.5, 0.03 to 93.3, and 0.09 to 48.3 kg h^???1, respectively. Concentration of SO₂ and NO _x in stack gas of 1,180-kVA (1 KW = 1.25 kVA) diesel generator exceeded the upper safe limits prescribed by the State Pollution Control Board, while concentrations of the same from all other units were within the prescribed limits. Particulate emission was highest from the barrel grinding operation, where grinding of the manufactured pipes is undertaken for giving the final shape. Particulate emission was also high from dedusting operation where coal dust is handled. Air quality modeling indicated that maximum possible ground-level concentration of PM, SO₂, and NO _x were to the tune of 13, 3, and 18 μg/m³, respectively, which are within the prescribed limits for ambient air given by the Central Pollution Control Board.     

The Impact of Road Traffic in Madrid Community by Using a Nested Gaussian-Mesoscale Air Quality Model (GAMA)

In this contribution we show the integration of a mesoscale air quality model OPANA with the ISCST3 Gaussian model (EPA) in order to analyze the impact of different emission sources and particularly the traffic emission into the different gridboxes which define the OPANA Eulerian structure. The application is done over the Madrid (Spain) regional area with 80 × 100 km and gridboxes of about 5 km. Thousands of Gaussian runs over interested gridboxes are executed in order to simulate the traffic emissions from each gridbox. Each mobile unit is represented by a Gaussian point emitter. Input meteorological variables for the ISCST3 are taken from the OPANA mesoscale air quality model. Results shows that it is possible to model the impact of traffic emissions over each gridbox. A short comparison with air quality monitoring in each gridbox is also shown.     

Mercury emission and dispersion models from soils contaminated by cinnabar mining and metallurgy

The laboratory flux measurement system (LFMS) and dispersion models were used to investigate the kinetics of mercury emission flux (MEF) from contaminated soils. Representative soil samples with respect to total Hg concentration (26-9770 μg g(-1)) surrounding a decommissioned mercury-mining area (Las Cuevas Mine), and a former mercury smelter (Cerco Metalúrgico de Almadenejos), in the Almadén mercury mining district (South Central Spain), were collected. Altogether, 14 samples were analyzed to determine the variation in mercury emission flux (MEF) versus distance from the sources, regulating two major environmental parameters comprising soil temperature and solar radiation. In addition, the fraction of the water-soluble mercury in these samples was determined in order to assess how MEF from soil is related to the mercury in the aqueous soil phase. Measured MEFs ranged from less than 140 to over 10,000 ng m(-2) h(-1), with the highest emissions from contaminated soils adjacent to point sources. A significant decrease of MEF was then observed with increasing distance from these sites. Strong positive effects of both temperature and solar radiation on MEF was observed. Moreover, MEF was found to occur more easily in soils with higher proportions of soluble mercury compared to soils where cinnabar prevails. Based on the calculated Hg emission rates and with the support of geographical information system (GIS) tools and ISC AERMOD software, dispersion models for atmospheric mercury were implemented. In this way, the gaseous mercury plume generated by the soil-originated emissions at different seasons was modeled. Modeling efforts revealed that much higher emissions and larger mercury plumes are generated in dry and warm periods (summer), while the plume is smaller and associated with lower concentrations of atmospheric mercury during colder periods with higher wind activity (fall). Based on the calculated emissions and the model implementation, yearly emissions from the "Cerco Metalúrgico de Almadenejos" decommissioned metallurgical precinct were estimated at 16.4 kg Hg y(-1), with significant differences between seasons.     

Indoor air pollution by 2-ethyl-1-hexanol in non-domestic buildings in Nagoya, Japan

2-Ethyl-1-hexanol is a possibly causative chemical in sick building symptoms, although 2-ethyl-1-hexanol has received little attention as a hazardous substance in studies on indoor air pollution. Airborne 2-ethyl-1-hexanol concentrations were measured from 2002 to 2004 in 99 rooms of 42 non-domestic buildings in Nagoya, Japan. The diffusive sampling method is effective for the measurement of a low level of 2-ethyl-1-hexanol in indoor air. The geometric mean (geometric standard deviation) of 2-ethyl-1-hexanol concentrations was 16.5 (5.4) microg m(-3) in indoor air and 1.9 (2.2) microg m(-3) in outdoor air. The maximum concentration of 2-ethyl-1-hexanol in indoor air and outdoor air was 2709 microg m(-3) and 12.4 microg m(-3), respectively. Fewer rooms in a small number of new buildings showed high concentrations of 2-ethyl-1-hexanol, while low concentrations were observed in many rooms of these buildings as well as the other new buildings. The room-to-room concentrations of 2-ethyl-1-hexanol in each building exhibited a wide variation. The geometric mean of the 2-ethyl-1-hexanol concentrations was significantly higher for indoor air than for outdoor air (p < 0.01). The correlation of the 2-ethyl-1-hexanol concentrations between indoor and outdoor air was not significant. Mechanical ventilation was effective in the temporary reduction of indoor 2-ethyl-1-hexanol level. These results suggest that the predominant source of 2-ethyl-1-hexanol was indoor areas.     

Empirical evaluation of spatial and non-spatial European-scale multimedia fate models: results and implications for chemical risk assessment

Multimedia environmental fate models are commonly-applied tools for assessing the fate and distribution of contaminants in the environment. Owing to the large number of chemicals in use and the paucity of monitoring data, such models are often adopted as part of decision-support systems for chemical risk assessment. The purpose of this study was to evaluate the performance of three multimedia environmental fate models (spatially- and non-spatially-explicit) at a European scale. The assessment was conducted for four polycyclic aromatic hydrocarbons (PAHs) and hexachlorobenzene (HCB) and compared predicted and median observed concentrations using monitoring data collected for air, water, sediments and soils. Model performance in the air compartment was reasonable for all models included in the evaluation exercise as predicted concentrations were typically within a factor of 3 of the median observed concentrations. Furthermore, there was good correspondence between predictions and observations in regions that had elevated median observed concentrations for both spatially-explicit models. On the other hand, all three models consistently underestimated median observed concentrations in sediment and soil by 1-3 orders of magnitude. Although regions with elevated median observed concentrations in these environmental media were broadly identified by the spatially-explicit models, the magnitude of the discrepancy between predicted and median observed concentrations is of concern in the context of chemical risk assessment. These results were discussed in terms of factors influencing model performance such as the steady-state assumption, inaccuracies in emission estimates and the representativeness of monitoring data.     

Seasonal variations of heavy metal contamination in river Gomti of Lucknow city region

The present study deals with the seasonal variations in the concentrations of heavy metals namely chromium, lead and mercury by using spectrophotometric methods. The water samples were collected at regular intervals from five selected sites of river Gomti in the pre-monsoon period (months of February-May) and the post monsoon period (months of October-January). The concentrations of chromium (VI) and mercury (II) were determined by using Genesys-10 UV-VIS Spectrophotometer while lead (II) concentrations were determined using Atomic Absorption Spectrophotometer, Perkin-Elmer 5000 model. The concentrations of all the three metals were found to be higher in the pre-monsoon period than in the post-monsoon period. The statistical analysis of the data was discussed in both the seasons in terms of mean, standard deviation and coefficient of variation.     

Validation of two air quality models for Indian mining conditions

All major mining activity particularly opencast mining contributes to the problem of suspended particulate matter (SPM)directly or indirectly. Therefore, assessment and prediction are required to prevent and minimize the deterioration of SPM due tovarious opencast mining operations. Determination of emission rate of SPM for these activities and validation of air quality models are the first and foremost concern. In view of the above, the study was taken up for determination of emission rate for SPMto calculate emission rate of various opencast mining activitiesand validation of commonly used two air quality models for Indianmining conditions. To achieve the objectives, eight coal and three iron ore mining sites were selected to generate site specific emission data by considering type of mining, method of working, geographical location, accessibility and above all resource availability. The study covers various mining activitiesand locations including drilling, overburden loading and unloading, coal/mineral loading and unloading, coal handling orscreening plant, exposed overburden dump, stock yard, workshop, exposed pit surface, transport road and haul road. Validation of the study was carried out through Fugitive Dust Model (FDM) and Point, Area and Line sources model (PAL2) by assigning the measured emission rate for each mining activity, meteorologicaldata and other details of the respective mine as an input to the models. Both the models were run separately for the same set ofinput data for each mine to get the predicted SPM concentrationat three receptor locations for each mine. The receptor locationswere selected such a way that at the same places the actual filedmeasurement were carried out for SPM concentration. Statisticalanalysis was carried out to assess the performance of the modelsbased on a set measured and predicted SPM concentration data. The value of coefficient of correlation for PAL2 and FDM was calculated to be 0.990-0.994 and 0.966-0.997, respectively, which shows a fairly good agreement between measured and predicted values of SPM concentration. The average index of agreement values for PAL2 and FDM was found to be 0.665 and0.752, respectively, which represents that the prediction by PAL2 and FDM models are accurate by 66.5 and 75.2%, respectively. These indicate that FDM model is more suited for Indian mining conditions.