NO2 and SO2dispersion modeling and relative roles of emission sources over Map Ta Phut industrial area,Thailand

Map Ta Phut industrial area (MA) is the largest industrial complex in Thailand. There has been concern about many air pollutants over this area. Air quality management for the area is known to be difficult, due to lack of understanding of how emissions from different sources or sectors (e.g., industrial, power plant, transportation, and residential) contribute to air quality degradation in the area. In this study, a dispersion study of NO₂ and SO₂ was conducted using the AERMOD model. The area-specific emission inventories of NO_x and SO₂ were prepared, including both stack and nonstack sources, and divided into 11 emission groups. Annual simulations were performed for the year 2006. Modeled concentrations were evaluated with observations. Underestimation of both pollutants was found, and stack emission estimates were scaled to improve the modeled results before quantifying relative roles of individual emission groups to ambient concentration over four selected impacted areas (two are residential and the others are highly industrialized). Two concentration measures (i.e., annual average area-wide concentration or AC, and area-wide robust highest concentration or AR) were used to aggregately represent mean and high-end concentrations for each individual area, respectively. For AC-NO₂, on-road mobile emissions were found to be the largest contributor in the two residential areas (36–38% of total AC-NO₂), while petrochemical-industry emissions play the most important role in the two industrialized areas (34–51%). For AR-NO₂, biomass burning has the most influence in all impacted areas (>90%) except for one residential area where on-road mobile is the largest (75%). For AC-SO₂, the petrochemical industry contributes most in all impacted areas (38–56%). For AR-SO₂, the results vary. Since the petrochemical industry was often identified as the major contributor despite not being the largest emitter, air quality workers should pay special attention to this emission group when managing air quality for the MA.

Implications: Effective air quality management in Map Ta Phut Industrial Area, Thailand requires better understanding of how emissions from various sources contribute to the degradation of ambient air quality. Based on the dispersion study here, petrochemical industry was generally identified as the major contributor to ambient NO₂ and SO₂. By accounting for all stack and non-stack sources, on-road mobile emissions were found to be important in some particular areas.     

Characterisation for some emission sources in CMB calculation for Mae Moh area, Thailand

Particulate samples of agricultural waste burning, straw burning, forest leaf burning, heavy duty truck emission, paved road dust, soil, agricultural soil, coal, electrostatic precipitator ash, and emission from stack power plant were collected from the Mae Moh area. Chemical compositions of sampling filters were analysed to determine the particulate matter source profiles. The analysis included ICP-MS for elemental compositions, ion chromatography for water soluble ions and CHNS/O for carbon species. In all biomass burning profiles organic carbon (OC) was higher during smouldering phase, while elemental carbon (EC) was higher during flaming phase. Results relating to biomass emission during flaming stage showed increase in K⁺. Organic and elemental carbons were the most abundant in biomass burning and truck exhaust. The abundance of EC was much lower, and the abundance of OC was much higher in biomass burning relative to truck exhaust emission. Al, K, Mg, Ca, and Fe were presented with high abundance in road dust, soil, coal, fly ash and stack samples. The differences in chemical compositions were not sufficient to distinguish geological material and fugitive dust sources. Fly ash profile differed from the others since OC and EC were not detected. Na and Zn were most abundant in stack samples. These findings served as a starting point for source contribution study. For future application of source apportionment using the CMB modelling technique, these source profiles should be appropriately grouped and selected to generate reliable outcomes.     

Simulating industrial emissions using atmospheric dispersion modeling system: model performance and source emission factors

In this paper, the Gaussian Atmospheric Dispersion Modeling System (ADMS4) was coupled with field observations of surface meteorology and concentrations of several air quality indicators (nitrogen oxides (NOx), carbon monoxide (CO), fine particulate matter (PM10) and sulfur dioxide (SO2)) to test the applicability of source emission factors set by the European Environment Agency (EEA) and the United States Environmental Protection Agency (USEPA) at an industrial complex. Best emission factors and data groupings based on receptor location, type of terrain and wind speed, were relied upon to examine model performance using statistical analyses of simulated and observed data. The model performance was deemed satisfactory for several scenarios when receptors were located at downwind sites with index of agreement 'd' values reaching 0.58, fractional bias 'FB' and geometric mean bias 'MG' values approaching 0 and 1, respectively, and normalized mean square error 'NMSE' values as low as 2.17. However, median ratios of predicted to observed concentrations 'Cp/Co' at variable downstream distances were 0.01, 0.36, 0.76 and 0.19 for NOx, CO, PM10 and SO2, respectively, and the fraction of predictions within a factor of two of observations 'FAC2' values were lower than 0.5, indicating that the model could not adequately replicate all observed variations in emittant concentrations. Also, the model was found to be significantly sensitive to the input emission factor bringing into light the deficiency in regulatory compliance modeling which often uses internationally reported emission factors without testing their applicability.     

Odor emission rate estimation of indoor industrial sources using a modified inverse modeling method

Odor emission rates are commonly measured in the laboratory or occasionally estimated with inverse modeling techniques. A modified inverse modeling approach is used to estimate source emission rates inside of a postdigestion centrifuge building of a water reclamation plant. Conventionally, inverse modeling methods divide an indoor environment in zones on the basis of structural design and estimate source emission rates using models that assume homogeneous distribution of agent concentrations within a zone and experimentally determined link functions to simulate airflows among zones. The modified approach segregates zones as a function of agent distribution rather than building design and identifies near and far fields. Near-field agent concentrations do not satisfy the assumption of homogeneous odor concentrations; far-field concentrations satisfy this assumption and are the only ones used to estimate emission rates. The predictive ability of the modified inverse modeling approach was validated with measured emission rate values; the difference between corresponding estimated and measured odor emission rates is not statistically significant. Similarly, the difference between measured and estimated hydrogen sulfide emission rates is also not statistically significant. The modified inverse modeling approach is easy to perform because it uses odor and odorant field measurements instead of complex chamber emission rate measurements.     

Project MISTT: Mesoscale plume modeling of the dispersion,transformation and ground removal of SO2

A diagnostic β-mesoscale (25–250 km) plume model is developed using an existing steadystate model as a building block. This quasi-steady. Lagrangian model incorporates the diurnal variability of the planetary boundary layer (PBL) structure and of the parameters governing the chemical conversion and ground removal of SO₂. The vertical inhomogeneity of atmospheric dispersion is simulated by the use of an assumed height- and stability-dependent profile of the eddy diffusion coefficient. Two important dimensionless system parameters are identified which govern pollutant dilution and ground removal. Model inputs are derived from Project MISTT aircraft data and the ground monitoring data of the St. Louis Regional Air Pollution Study (RAPS). On 9 and 18 July 1976, the plume of the 2400 MW, coal-fired Labadie power plant near St. Louis was sampled from aircraft out to 300 km. Model application is considered specifically for the data of these two days and corresponding quantitative information about the dispersion, transformation and ground removal of SO₂ is extracted. The results show that peak daytime SO₂ conversion rates reached 1.8 and 3.0% h⁻¹ on 9 and 18 July, respectively; the corresponding peak dry deposition velocities were between 1.5 and 2.0cms⁻¹. The model is used to investigate the effects of source height, time of SO₂ release and eddy diffusion on the overall sulfur budget of the plume. The mid- and late-afternoon plumes appear to have the highest potential for long range transport and sulfate formation. Ground removal is strongly influenced by the profile of vertical eddy diffusion in the surface layer and much less by the profile shape and magnitude higher up.     

Sensitivity of Native Desert Vegetation To SO2 and to SO2 and NO2 Combined

Interest in air pollution injury to native vegetation has been generated with the construction and planned construction of large coal-fired power plants near the coal reserves in the southwest desert areas of the United States. Since information on the effects of SO₂ on these native species was not available in the literature, fumigation studies were conducted with portable chambers placed over native species in the field with SO₂ and SO₂ + NO₂. Pollutant concentrations were measured and controlled with instruments located in a mobile laboratory. Each fumigation was of two hours duration and the concentration ranged from 0.5 to 11 ppm SO₂ and from 0.1 to 5 ppm NO₂. Concentrations of SO₂ above 2 ppm were required to cause injury to all but a few of the 87 species studied. Many of the native desert species proved to be highly resistant to injury from these gases.     

焦化行业SO2排放现状及减排潜力分析

随着钢铁工业的高速发展,高温炼焦已成为中国煤炭资源利用的重要途径之一,与此同时焦化行业SO2排放污染问题越来越引起人们的关注.2007年,全国焦炭产量总计335.53 Mt,其中机械化焦炉产量达305.37 Mt,约占全国焦炭产量的91.01%,焦化行业SO2排放量达181.19 kt.在参考国家制定的焦化行业未来产业...     

Two-days ahead prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the urban area of Palermo,Italy

Artificial neural networks are functional alternative techniques in modelling the intricate vehicular exhaust emission dispersion phenomenon. Pollutant predictions are notoriously complex when using either deterministic or stochastic models, which explains why this model was developed using a neural network. Neural networks have the ability to learn about non-linear relationships between the used variables. In this paper a recurrent neural network (Elman model) based forecaster for the prediction of daily maximum concentrations of SO₂, O₃, PM10, NO₂, CO in the city of Palermo is proposed. The effectiveness of the presented forecaster was tested using a time series recorded between 1 January 2003 to 31 December 2004 in eight monitoring stations in urban area of Palermo (Italy). Experimental trials show that the developed and tuned model is appropriate, giving small values of root mean square error (RMSE) , mean absolute error (MAE) and mean square error (MSE). In addition, the related correlation coefficient ranges from 0.72 to 0.97 for each forecasted pollutant, underlying a small difference between the forecasted and the measured values. The above results make the proposed forecaster a powerful tool for pollution management systems.     

UV Fourier transform measurements of tropospheric O3, NO2, SO2, benzene, and toluene.

Using the differential optical absorption spectroscopy (DOAS) technique and a Fourier transform spectrometer, NO2, SO2, O3, benzene. and toluene were measured during three measurement campaigns held in Brussels in 1995, 1996, and 1997. The O3 concentrations could be explained as the results of the local photochemistry and the dynamical properties of the mixing layer. NO2 concentrations were anti-correlated to the O3 concentrations, as expected. SO2 also showed a pronounced dependence on car traffic. Average benzene and toluene concentrations were, respectively 1.7 ppb and between 4.4 and 6.6 pbb, but high values of toluene up to 98.8 ppb were observed. SO2 concentrations and to a lesser extent, those of NO2 and 03, were dependent on the wind direction. Ozone in Brussels has been found to be influenced by the meteorological conditions prevailing in central Europe. Comparisons with other measurements have shown that 03 and SO2 data are in general in good agreement, but our NO2 concentrations seem to be generally higher.     

Carbon catalysis in the aqueous oxidation of SO2 by NO2 and air

Sulfur Dioxide and an oxidant gas — air or NO₂ — were bubbled through aqueous suspensions of both washed and unwashed carbon black as well as through samples of wash water, which contained whatever soluble species were originally present on the carbon, and high-purity water. The sulfate yields obtained showed the washed and unwashed carbon to be equally catalytic for the oxidation of SO₂ to sulfate by both oxidants whereas little sulfate was generated in either the wash water or high-purity water in the absence of carbon. These results indicate that the sulfate yields produced in aqueous suspensions of the carbon studied are due to catalysis by the carbon particles rather than by soluble species dissolved from them.     

Source profiles for industrial, mobile, and area sources in the Big Bend Regional Aerosol Visibility and Observational study

Representative PM2.5 and PM10 source emissions were sampled in Texas during the Big Bend Regional Aerosol Visibility and Observa (BRAVO) study. Chemical source profiles for elements, ions, and carbon fractions of 145 samples are reported for paved and unpaved road dust, soil dust, motor vehicle exhaust, vegetative burning, four coal-fired power stations, an oil refinery catalytic cracker, two cement kilns, and residential meat cooking. Several samples were taken from each emitter and source type, and these were averaged by source type, and in source subgroups based on commonality of chemical composition. The standard deviation represents the variability of the chemical mass fractions. BRAVO profiles differed in some respects from profiles measured elsewhere. High calcium abundances in geological dust, high selenium abundances in coal-fired power stations, and high antimony abundances in oil refinery catalytic cracker emissions were found. Abundances of eight thermally evolved carbon fractions [Atmos. Environ. 28 (15) (1994) 2493] differ among combustion sources, and a Monte Carlo simulation demonstrates that these differences are sufficient to differentiate among several carbon-emitters.     

Demonstration of a global modeling methodology to determine the relative importance of local and long-distance sources

A global three-dimensional (3D) transport–dispersion model was used to simulate Krypton-85 (⁸⁵Kr) background concentrations at five sampling locations along the US east coast during 1982–1983. The samplers were established to monitor the ⁸⁵Kr plume downwind of the Savannah river plant (SRP), a nuclear fuel reprocessing facility. The samplers were located 300–1000 km downwind of the SRP. In the original analyses of the measurements, a constant background concentration, representing an upper-limit and different for each sampling station, was subtracted from the measurements to obtain the part of the measurement representing the SRP plume. The use of a 3D global model, which includes all major ⁸⁵Kr sources worldwide, was able to reproduce the day-to-day concentration background variations at the sampling locations with correlation coefficients of 0.36–0.46. These 3D model background predictions, without including the nearby SRP source, were then subtracted from the measured concentrations at each sampler, the result representing the portion of the measurement that can be attributed to emissions from the SRP. The revised plume estimates were a factor of 1.3–2.4 times higher than from the old method using a constant background subtraction. The greatest differences in the SRP plume estimates occurred at the most distant sampling stations.     

Adjoint inverse modeling of NOx emissions over eastern China using satellite observations of NO2 vertical column densities

A four-dimensional variational data assimilation system for optimization of NO_x emissions (RC4-NO_x) was developed. A parameterized NO_x chemistry scheme was introduced into the RC4-NO_x system, and key parameters such as chemical production and loss terms of NO_x were calculated in advance using the Community Multiscale Air Quality (CMAQ) modeling system. RC4-NO_x was applied to optimize NO_x emissions over eastern China (EC) in July 1996, 1999, and 2002 using Global Ozone Monitoring Experiment (GOME) satellite observations of NO₂ vertical column densities (VCDs) and a priori emissions from the Regional Emission Inventory in Asia (REAS). After assimilation, RC4-NO_x generally reproduced the spatial distribution, regional averaged values, and time evolution of GOME NO₂ VCDs. Over EC, a priori emissions were reduced by 20% in 1996 and by 8% in 1999, whereas a posteriori emissions were almost the same as a priori emissions in 2002. A priori emissions in the Beijing region were reduced by optimization over the whole simulation period. A posteriori emissions over the Yangtze Delta were larger than a priori emissions in 2002, although they were smaller in both 1996 and 1999. As in other areas, a priori emissions over the North China Plain were reduced in 1996; but those over the eastern part of the plain were increased in 1999, and the area of increased emissions moved slightly westward in 2002. In each region, the growth rates of a posteriori emissions during both 1996–1999 and 1999–2002 became generally larger than those of a priori emissions, and the trends of a posteriori emissions became similar to those of GOME NO₂ VCDs. Our inverse modeling analysis indicates that the rate of increase of NO_x emissions over EC from 1996 to 2002 was much larger for a posteriori emissions (49%) than for a priori emissions (19%).     

Simultaneous removal of NO and SO2 by high-temperature fluidized zero-valent iron processes

A new approach to simultaneously remove nitrogen monoxide (NO) and sulfur dioxide (SO2) by zero valent iron (ZVI) was investigated. Three different parameters, temperature, flux, and ZVI dosage, were tested in fluidized ZVI column studies containing 500 ppmv of NO and SO2, respectively. Under the ZVI dosage of 0.5 g at flux of 0.6 L/cm2 x min for temperature 573 K, there is neither NO nor SO2 reduction. For 623 K and 673 K, complete removal for NO and > 90% removal for SO2 were achieved. For temperatures of 723 K and 773 K, 100% removal was achieved for both NO and SO2. The amounts of NO or SO2 reduction (as milligrams of NO or SO2 per gram ZVI) increased as temperature increased, and linearities were observed with both correlation coefficients > 0.97. Compared with NO, SO2 had earlier breakthrough because of a slower diffusion rate and less reactivity but higher mass reduction because of a higher molecular weight for SO2 (64 g/mol for SO2 and 30 g/mol for NO). At same temperature, both NO and SO2 reductions (as milligrams of NO or SO2 per gram of ZVI) were constant regardless of either flux or ZVI dosage variation, but breakthrough time was affected by both flux and ZVI dosage. A parameter weight of ZVI/flux (W/F) was developed to represent these two parameters at the same time to assess the breakthrough time of NO and SO2. Higher breakthrough time was achieved for higher W/F value. Moreover, interestingly, longer breakthrough time and more NO and SO2 mass reduction were achieved for combined NO and SO2 than individual NO or SO2 treated by ZVI, and both oxidation and reduction reactions occurred instead of a reduction reaction only. Chemical reactions among ZVI/NO, ZVI/ SO2, and ZVI/NO/SO2 were also proposed and verified by X-ray diffraction analyses.     

Effects of NO2 and SO2 on selective catalytic reduction of nitrogen oxides by ammonia

The selective catalytic reduction (SCR) characteristics of NO and NO(2) over V(2)O(5)-WO(3)-MnO(2)/TiO(2) catalyst using ammonia as a reducing agent have been determined in a fixed-bed reactor at 200-400 degrees C. The presence of NO(2) enhances the SCR activity at lower temperatures and the optimum ratio of NO(2)/NO(x) is found to be 0.5. During the SCR reactions, there are some side reactions occurred such as ammonia oxidation and N(2)O formation. At higher temperatures, the selective catalytic oxidation of ammonia and the nitrous oxide formation compete with the SCR reactions. The denitrification (DeNO(x)) conversion decreases at lower temperatures but it increases at higher temperatures with increasing SO(2) concentration. The presence of SO(2) in the feeds inhibits N(2)O formation.     

Application of air pollution dispersion modeling for source-contribution assessment and model performance evaluation at integrated industrial estate-Pantnagar

Source-contribution assessment of ambient NO₂ concentration was performed at Pantnagar, India through simulation of two urban mathematical dispersive models namely Gaussian Finite Line Source Model (GFLSM) and Industrial Source Complex Model (ISCST-3) and model performances were evaluated. Principal approaches were development of comprehensive emission inventory, monitoring of traffic density and regional air quality and conclusively simulation of urban dispersive models. Initially, 18 industries were found responsible for emission of 39.11 kg/h of NO₂ through 43 elevated stacks. Further, vehicular emission potential in terms of NO₂ was computed as 7.1 kg/h. Air quality monitoring delineates an annual average NO₂ concentration of 32.6 μg/m³. Finally, GFLSM and ISCST-3 were simulated in conjunction with developed emission inventories and existing meteorological conditions. Models simulation indicated that contribution of NO₂ from industrial and vehicular source was in a range of 45-70% and 9-39%, respectively. Further, statistical analysis revealed satisfactory model performance with an aggregate accuracy of 61.9%.     

Simultaneous absorption of NO and SO2 into hexamminecobalt(II)/iodide solution

An innovative catalyst system has been developed to simultaneously remove NO and SO2 from combustion flue gas. Such catalyst system may be introduced to the scrubbing solution using ammonia solution to accomplish sequential absorption and catalytic oxidation of both NO and SO2 in the same reactor. When the catalyst system is utilized for removing NO and SO2 from the flue gas, Co(NH3)(6)2+ ions act as the catalyst and I- as the co-catalyst. Dissolved oxygen, in equilibrium with the residual oxygen in the flue gas, is the oxidant. The overall removal process is further enhanced by UV irradiation at 365 nm. More than 95% of NO is removed at a feed concentration of 250-900 ppm, and nearly 100% of SO2 is removed at a feed concentration of 800-2500 ppm. The sulfur dioxide co-existing in the flue gas is beneficial to NO absorption into hexamminecobalt(II)/iodide solution. NO and SO2 can be converted to ammonium sulfate and ammonium nitrate that can be used as fertilizer materials. The process described here demonstrates the feasibility of removing SO2 and NO simultaneously only by retrofitting the existing wet ammonia flue-gas-desulfurization (FGD) scrubbers.     

Coupling of the Weather Research and Forecasting Model with AERMOD for pollutant dispersion modeling. A case study for PM10 dispersion over Pune,India

The prediction of spatial variation of the concentration of a pollutant governed by various sources and sinks is a complex problem. Gaussian air pollutant dispersion models such as AERMOD of the United States Environmental Protection Agency (USEPA) can be used for this purpose. AERMOD requires steady and horizontally homogeneous hourly surface and upper air meteorological observations. However, observations with such frequency are not easily available for most locations in India. To overcome this limitation, the planetary boundary layer and surface layer parameters required by AERMOD were computed using the Weather Research and Forecasting (WRF) Model (version 2.1.1) developed by the National Center for Atmospheric Research (NCAR). We have developed a preprocessor for offline coupling of WRF with AERMOD. Using this system, the dispersion of respirable particulate matter (RSPM/PM10) over Pune, India has been simulated. Data from the emissions inventory development and field-monitoring campaign (13–17 April 2005) conducted under the Pune Air Quality Management Program of the Ministry of Environment and Forests (MoEF), India and USEPA, have been used to drive and validate AERMOD. Comparison between the simulated and observed temperature and wind fields shows that WRF is capable of generating reliable meteorological inputs for AERMOD. The comparison of observed and simulated concentrations of PM10 shows that the model generally underestimates the concentrations over the city. However, data from this single case study would not be sufficient to conclude on suitability of regionally averaged meteorological parameters for driving Gaussian models like AERMOD and additional simulations with different WRF parameterizations along with an improved pollutant source data will be required for enhancing the reliability of the WRF–AERMOD modeling system.     

Effects of air filtration at small SO2 and NO2 concentrations on the yield of barley

Two cultivars of Igri and Gerbel winter barley Horteum vulgare L. were grown in open-top chambers in filtered and unfiltered air at a site with approximately 10 nl litre(-1) SO2 and 12 nl litre(-1) NO2 (seasonal mean). The experiment ran for three consecutive seasons 1982-1983, 1983-1984, 1984-1985, and significant effects of filtration were observed for each crop. In years 1982-1983 and 1984-1985, the crops in unfiltered air yielded larger grain dry matter, 9% in 1982-1983, and 8% in 1984-1985. For both crops, the differences were statistically significant at the 5% level. Differences were also observed for the remaining above-ground dry matter, and these were consistent in direction in each year but statistically significant only in 1984-1985. In both growing seasons (1982-1983 and 1984-1985), there were no major pest infestations and no long-term water stress or photochemical ozone episodes. In the remaining experiment (1983-1984) similar air concentrations of SO2 and NO2 produced effects of the opposite sign to those observed in 1982-1983 and 1984-1985. Significant reductions in grain yield (13%) were obtained in unfiltered air. The only major environmental difference for the 1983-1984 crop was a notable dry period in May and June 1984 with marked water stress in the crop, requiring irrigation. These results suggest that the relationship between yield and pollutant concentration may be confounded by additional stresses, many of which are a common component of the growing season for major crops.     

Comparison and development of dynamic flux chambers to determine odorous compound emission rates from area sources

Two dynamic flux chambers for direct measurement of odorous compound emissions from quiescent liquid surfaces were investigated under simulated conditions in the laboratory. Initially, a flux chamber built according to the model recommended by French standard NF X 43-104 was studied. This chamber was used in two different ways. The first led to a lack of precision concerning emissions rates from the sampled liquid surface, whereas the second led to an overestimation of the measurements. The second part of the study was devoted to an improved dynamic flux chamber, built according to the feedback from the results obtained using the normalised sampling system. Laboratory tests showed good accuracy and precision. This work underlines the importance of the aerodynamic performances of a dynamic sampling system.