Characteristics of dioxin emissions at startup and shutdown of MSW incinerators

Dioxin concentrations from municipal waste incinerators in Japan and elsewhere often show low concentrations that comply with legal limits (in this paper, the term "dioxin" designates WHO-TEQ: PCDD/Fs+dioxin-like PCB). However, such data is usually generated under normal steady state operational conditions, and there has been little investigation of releases occurring during startup and shutdown. It is important, therefore, to ascertain quantitatively emissions in an unsteady state (startup and shutdown) in order to correctly evaluate the relationship between emissions from a facility and the surrounding environment. The present study aimed to examine dioxin emissions of a continuously operated incinerator at startup and shutdown, and estimating the time period of greatest emission, and the processes causing dioxin generation. The startup process was divided into five stages and the shutdown into two; at each stage, dioxins in the flue gas were measured at the boiler outlet and the stack. From the concentration of dioxins and the flue gas volume at each stage, the amount of dioxins at startup and shutdown were calculated, and these were compared with that under steady state conditions. Dioxin concentration at the stack under steady state conditions was a very low level, while those at startup and shutdown were higher. In the case where dioxin concentration under a steady state is a low level like in this study, it is indicated that the total annual dioxin emission from a facility could be attributed to the startup periods.     

Sampling Airborne Solids in a Duct Following a 90° Bend

Present standardized methods (ASME Power Test Code 27, Western Precipitation Bulletin 50, etc.) of stack sampling usually stress sampling under conditions of steady flow (no variation with time) in order to obtain data representative of the source emissions. On many occasions these standardized methods are applied when the velocity and/or the mass flow rate of pollutants do vary with time, thus impairing the accuracy of the sampling results. In addition, it is difficult to evaluate any inaccuracy of the sampling data. This paper classifies these two source variables into four categories and suggests basic sampling approaches for each type of source condition. Several standardized procedures are evaluated and classified according to the source conditions to which the procedure is applicable. The intent of this paper is to show the most accurate sampling approach for each source condition and thus serve as a guide when planning source sampling programs.     

Simulation of atmospheric PAH emissions from diesel engines

Simulation of atmospheric PAH emissions in a typical European passenger car diesel engine at steady conditions or under a certification cycle is made using in-house software. It is based on neural fitting of experimental data from eight different fuels tested under five operating steady conditions (reproducing modes of the European transient urban/extraurban certification cycle). The software allows the determination of PAH emissions as a function of the fuel composition parameters (aromatic content, cetane index, gross heat power, nitrogen and sulphur content) and operation conditions (torque and engine speed). The mathematical model reproduces experimental data with a maximum error of 20%. This tool is very useful, since changes in parameters can be made without experimental cost and the trend in modifications in PAH emissions is immediately obvious.     

Quantifying trace gas emissions from composite landscapes: A mass-budget approach with aircraft measurements

Quantifying trace gas emissions and the influence of surface exchange processes on the atmosphere is a necessary step towards the control of global greenhouse gas emissions and reliability of air quality models. This paper proposes a procedure based on the mass balance method and implemented on highly resolved aircraft data. It allows one to estimate surface exchanges on areas of several km² and heterogeneous features exploiting the characteristics of convective boundary layer during steady state conditions that permit the estimation of emission/absorption terms as functions of advective fluxes only. A nonparametric approach is adopted and the fluxes on the surface of a virtual box surrounding the area of interest are reconstructed on the basis of scalar densities and wind vectors using Shepard functions. Two different techniques are also proposed to face lack of data on the top surface of the box. The method has been applied to experimental data coming from measurement campaigns on two different sites. It provides realistic estimates of the CO₂ emission/absorption in the considered areas that are in good agreement with CO₂ fluxes evaluated by Airborne Eddy Covariance and confirm the suitability of the proposed approach for the assessment of turbulent exchange of trace gases by composite landscapes. Uncertainties on the estimated emissions due to both propagation of the experimental error and interpolation have been quantified by bootstrap analysis as 6%.     

Innovative approach for estimating fugitive gaseous fluxes using computed tomography and remote optical sensing techniques.

This paper presents a new approach to quantify emissions from fugitive gaseous air pollution sources. The authors combine Computed Tomography (CT) with Path-Integrated Optical Remote Sensing (PI-ORS) concentration data in a new field beam geometry. Path-integrated concentrations are sampled in a vertical plane downwind from the source along several radial beam paths. An innovative CT technique, which applies the Smooth Basis Function Minimization method to the beam data in conjunction with measured wind data, is used to estimate the total flux from the fugitive source. The authors conducted a synthetic data study to evaluate the proposed methodology under different meteorological conditions, beam geometry configurations, and simulated measurement errors. The measurement errors were simulated based on data collected with an Open-Path Fourier Transform Infra-Red system. This approach was found to be robust for the simulated errors and for a wide range of fluctuating wind directions. In the very sparse beam geometry examined (eight beam paths), successful emission rates were retrieved over a 70 degrees range of wind directions under extremely large measurement error conditions.     

Evaluation of low wind modeling approaches for two tall-stack databases

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO₂ monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO₂ monitors within 10 km of the Dakota Gasification Company’s plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO₂ monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the overprediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.

Implications: AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the overprediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.     

Innovative Approach for Estimating Fugitive Gaseous Fluxes Using Computed Tomography and Remote Optical Sensing Techniques

ABSTRACT

This paper presents a new approach to quantify emissions from fugitive gaseous air pollution sources. The authors combine Computed Tomography (CT) with Path-Integrated Optical Remote Sensing (PI-ORS) concentration data in a new field beam geometry. Path-integrated concentrations are sampled in a vertical plane downwind from the source along several radial beam paths. An innovative CT technique, which applies the Smooth Basis Function Minimization method to the beam data in conjunction with measured wind data, is used to estimate the total flux from the fugitive source. The authors conducted a synthetic data study to evaluate the proposed methodology under different meteorological conditions, beam geometry configurations, and simulated measurement errors. The measurement errors were simulated based on data collected with an Open-Path Fourier Transform Infra-Red system. This approach was found to be robust for the simulated errors and for a wide range of fluctuating wind directions. In the very sparse beam geometry examined (eight beam paths), successful emission rates were retrieved over a 70° range of wind directions under extremely large measurement error conditions.     

冬季沈阳市典型源排放PM10浓度分布模拟分析

选取沈阳市7个典型的大气污染源2006年12月～2007年2月的PM10排放浓度资料,利用CALPUFF对PM10浓度月平均分布做模拟分析。模拟结果分析表明：冬季月平均PM10浓度分布的范围与风场、地形有直接的关系。地势平坦、风速大时,污染物扩散范围大,污染物浓度小;地势不平、风速小时,污染物扩散范围小,污染物浓度大。1月份是沈阳市冬季月平均大气污染最严重的月份,污染物分布主要集中在市区的北部、东部和南部地区,东部地区大气污染最为严重。     

Relating meteorological variables and trends in motor vehicle emissions to monthly urban carbon monoxide concentrations

A model which quantifies the relationship between the monthly time series for CO emissions, the monthly time series in ambient CO concentration, and meteorologically driven dispersion was developed. Fifteen cities representing a wide range of geographical and climatic conditions were selected. An eight-year time series (1984–1991 inclusive) of monthly averaged data were examined in each city. A new method of handling missing ambient concentration values which is designed to calculate city-wide average concentrations that follow the trend seen at individual monitor sites is presented. This method is general and can be used in other applications involving missing data. The model uses emissions estimates along with two meteorological variables (wind speed and mixing height) to estimate monthly averages of ambient air pollution concentrations. The model is shown to have a wide range of applicability; it works equally well for a wide range of cities that have very different temporal CO distributions. The model is suited for assessing long-term trends in ambient air pollutants and can also be used for estimating seasonal variations in concentration, estimation of trends in emissions, and for filling in gaps in the ambient concentration record.     

Measurement, analysis, and modeling of fine particulate matter in eastern North Carolina

An analysis of fine particulate data in eastern North Carolina was conducted to investigate the impact of the hog industry and its emissions of ammonia into the atmosphere. The fine particulate data are simulated using ISORROPIA, an equilibrium thermodynamic model that simulates the gas and aerosol equilibrium of inorganic atmospheric species. The observational data analyses show that the major constituents of fine particulate matter (PM2.5) are organic carbon, elemental carbon, sulfate, nitrate, and ammonium. The observed PM2.5 concentration is positively correlated with temperature but anticorrelated with wind speed. The correlation between PM2.5 and wind direction at some locations suggests an impact of ammonia emissions from hog facilities on PM2.5 formation. The modeled results are in good agreement with observations, with slightly better agreement at urban sites than at rural sites. The predicted total inorganic particulate matter (PM) concentrations are within 5% of the observed values under conditions with median initial total PM species concentrations, median relative humidity (RH), and median temperature. Ambient conditions with high PM precursor concentrations, low temperature, and high RH appear to favor the formation of secondary PM.     

Numerical simulation of flow and dispersion around an isolated cubical building: The effect of the atmospheric stratification

The aim of this work is to investigate atmospheric flow and dispersion of contaminants in the vicinity of single buildings under different stability conditions. The mathematical model used is based on the solution of equations of conservation of mass, linear momentum and energy with the use of a non-standard κ–? turbulence model. The modifications proposed in the κ–? model are the inclusion of the Kato and Launder correction in the production of turbulent kinetic energy and the use of a modified wall function. Results are presented of numerical simulations of dispersion around a cubical obstacle, under neutral, stable and unstable atmospheric conditions. Experimental data from wind tunnel and field trials obtained by previous authors are used to validate the numerical results. The numerical simulation results show a reasonable level of agreement with field and wind tunnel concentration data. The deviation between model results and field experimental data is of the same order as the deviation between field and wind tunnel data.     

Unsteady characteristics of the dispersion process in the vicinity of a pig barn. Wind tunnel experiments and comparison with field data

Two complementary methods, field experiments and physical modelling in a wind tunnel, have been used to investigate the dispersion of tracer-gas released from the ventilation system of a pig barn, under near-neutral stability conditions. In both cases, concentration fluctuations were measured and the deduced statistical results were compared. The choice of data processing applied to the time series of concentration was motivated by special issues in the assessment of odour annoyances: “where, how often, how long and how strong does it smell?” These features were described by the mean concentration distribution, the intermittency factor, the persistence and the 90-percentile. The good agreement between field and wind tunnel data confirmed the ability to replicate in wind tunnel the unsteady properties of a dispersion process, if the unsteady turbulent behaviour of the atmospheric boundary layer was properly modelled.A parametrical study of the influence on the dispersion process of the ratio between the exhaust velocity from the stack and the wind speed was then performed in wind tunnel. The fundamental outcome was that the near-field dispersion process under neutral stability conditions, despite the strong influence of the building wake, was for the most part driven by the meandering behaviour of the plume and not so much by the diffusion process.This study was also focused on the influence of the averaging time on the statistical results. The scatter generated by using dimensionless averaging times 200<T_a^*<400 (used during field experiments) instead of T_a^*→∞ (averaging time to ensure reproducible statistic results) was quantified in the wind tunnel. A degree of representativity of the results obtained from short-term samples, compared to fully converged statistical results was therefore assessed.     

Assessing the representativeness of monitoring data from an urban intersection site in central London,UK

The wind flow field around urban street-building configurations has an important influence on the microscale pollutant dispersion from road traffic, affecting overall dilution and creating localised spatial variations of pollutant concentration. As a result, the “representativeness” of air quality measurements made at different urban monitoring sites can be strongly dependent on the interaction of the local wind flow field with the street-building geometry surrounding the monitor. The present study is an initial attempt to develop a method for appraising the significance of air quality measurements from urban monitoring sites, using a general application computational fluid dynamics (CFD) code to simulate small-scale flow and dispersion patterns around real urban building configurations. The main focus of the work was to evaluate routine CO monitoring data collected by Westminster City Council at an intersection of street canyons at Marylebone Road, Central London. Many monitors in the UK are purposely situated at urban canyon intersections, which are thought to be local “hot spots” of pollutant emissions, however very limited information exists in the literature on the flow and dispersion patterns associated with them. With the use of simple CFD simulations and the analysis of available monitoring data, it was possible to gain insights into the effect of wind direction on the small-scale dispersion patterns at the chosen intersection, and how that can influence the data captured by a monitor. It was found that a change in wind direction could result in an increase or decrease of monitored CO concentration of up to 80%, for a given level of traffic emissions and meteorological conditions. Understanding and de-coupling the local effect of wind direction from monitoring data using the methods presented in this work could prove a useful new tool for urban monitoring data interpretation.     

A methodology to urban air quality assessment during large time periods of winter using computational fluid dynamic models

The representativeness of point measurements in urban areas is limited due to the strong heterogeneity of the atmospheric flows in cities. To get information on air quality in the gaps between measurement points, and have a 3D field of pollutant concentration, Computational Fluid Dynamic (CFD) models can be used. However, unsteady simulations during time periods of the order of months, often required for regulatory purposes, are not possible for computational reasons. The main objective of this study is to develop a methodology to evaluate the air quality in a real urban area during large time periods by means of steady CFD simulations. One steady simulation for each inlet wind direction was performed and factors like the number of cars inside each street, the length of streets and the wind speed and direction were taken into account to compute the pollutant concentration. This approach is only valid in winter time when the pollutant concentrations are less affected by atmospheric chemistry. A model based on the steady-state Reynolds-Averaged Navier–Stokes equations (RANS) and standard k-? turbulence model was used to simulate a set of 16 different inlet wind directions over a real urban area (downtown Pamplona, Spain). The temporal series of NO_x and PM₁₀ and the spatial differences in pollutant concentration of NO₂ and BTEX obtained were in agreement with experimental data. Inside urban canopy, an important influence of urban boundary layer dynamics on the pollutant concentration patterns was observed. Large concentration differences between different zones of the same square were found. This showed that concentration levels measured by an automatic monitoring station depend on its location in the street or square, and a modelling methodology like this is useful to complement the experimental information. On the other hand, this methodology can also be applied to evaluate abatement strategies by redistributing traffic emissions.     

Uncertainties in predicted ozone concentrations due to input uncertainties for the UAM-V photochemical grid model applied to the July 1995 OTAG domain

The photochemical grid model, UAM-V, has been used by regulatory agencies to make decisions concerning emissions controls, based on studies of the July 1995 ozone episode in the eastern US. The current research concerns the effect of the uncertainties in UAM-V input variables (emissions, initial and boundary conditions, meteorological variables, and chemical reactions) on the uncertainties in UAM-V ozone predictions. Uncertainties of 128 input variables have been estimated and most range from about 20% to a factor of two. 100 Monte Carlo runs, each with new resampled values of each of the 128 input variables, have been made for given sets of median emissions assumptions. Emphasis is on the maximum hourly-averaged ozone concentration during the 12–14 July 1995 period. The distribution function of the 100 Monte Carlo predicted domain-wide maximum ozone concentrations is consistently close to log-normal with a 95% uncertainty range extending over plus and minus a factor of about 1.6 from the median. Uncertainties in ozone predictions are found to be most strongly correlated with uncertainties in the NO₂ photolysis rate. Also important are wind speed and direction, relative humidity, cloud cover, and biogenic VOC emissions. Differences in median predicted maximum ozone concentrations for three alternate emissions control assumptions were investigated, with the result that (1) the suggested year-2007 emissions changes would likely be effective in reducing concentrations from those for the year-1995 actual emissions, that (2) an additional 50% NO_x emissions reductions would likely be effective in further reducing concentrations, and that (3) an additional 50% VOC emission reductions may not be effective in further reducing concentrations.     

Continuous carbon dioxide measurements in a rural area in the upper Spanish plateau

Continuous carbon dioxide (CO2) measurements over the period 2004-2005 for a rural area in the upper Spanish plateau were examined to characterize the influence of sources and sinks. The diurnal pattern and the annual cycle are presented. The baseline CO2 levels over the time frames researched are determined so as to achieve a more accurate verification of the ambient conditions when uptake is deployed at the site. The results reveal a mean concentration of 384.2 ppm, with 9.8-ppm variability. The mean maximum concentration levels at night, 4:00 a.m. Greenwich Mean Time (GMT), are 390.7 ppm, mainly when atmospheric stability increased. Moreover, mean CO2 levels increase in spring, peaking in May at 388.5 ppm. Concentrations then decline in summer and again increase in autumn, reaching a similar mean value in December. The results also show consistency with vegetation and crop growth, as well as the influence of meteorological conditions, soil features, and human activity in the area. Minimum and maximum CO2 concentrations present a similar but opposite variation, 4.4 ppm x yr(-1), with values decreasing in the latter. Diurnal variation is more pronounced during the growing season and higher in 2004, partly because of abundant rainfall. The lower daily amplitudes in the remaining months are attributed to the reduction in plant and soil respiration processes. The influence of wind on CO2 concentrations has enabled us to identify the contribution of emissions from the cities of Valladolid and Palencia. An increase in mean CO2 concentrations was observed in the, east-southeast, southeast, south-southeast, and south sectors for the former city, and north and east for the latter. The ratio of CO2 increase in the wind sectors influenced by these sources yielded a factor of 1.2 with respect to the relationship between the populations of the two cities.     

Modelling local and synoptic scale influences on ozone concentrations in a topographically complex region of Southern Italy

A modelling study with the on-line coupled Eulerian chemical-weather model WRF/Chem for the Southern Italian region around Cosenza (Calabria) was conducted to identify the influences of synoptic scale meteorology, local scale wind systems and local emissions on ozone concentrations in this orographically complex region. Four periods of 5–7 days were chosen, one from each season, which had wind pattern characteristics representative of typical local climatological conditions, in order to study the local versus non-local impacts on ozone transport and formation. To account for the complex terrain, the horizontal resolution of the smallest modelling domain was 3 km. Model results were compared with measurements to demonstrate the capability of the model to reproduce ozone concentrations in the region. The comparison was favourable with a mean bias of ?1.1 ppb. The importance of local emissions on ozone formation and destruction was identified with the use of three different emission scenarios. Generally the influence of regional emissions on the average ozone concentration was small. However during periods when mountain-sea wind systems were well developed and synoptic scale winds were weak, the influence of local emissions from the urban area was at its greatest. The maximum influence of local emissions on ozone concentrations was 18 ppb.     

Characterization of near-road pollutant gradients using path-integrated optical remote sensing

Understanding motor vehicle emissions, near-roadway pollutant dispersion, and their potential impact to near-roadway populations is an area of growing environmental interest. As part of ongoing U.S. Environmental Protection Agency research in this area, a field study was conducted near Interstate 440 (I-440) in Raleigh, NC, in July and August of 2006. This paper presents a subset of measurements from the study focusing on nitric oxide (NO) concentrations near the roadway. Measurements of NO in this study were facilitated by the use of a novel path-integrated optical remote sensing technique called deep ultraviolet differential optical absorption spectroscopy (DUV-DOAS). This paper reviews the development and application of this measurement system. Time-resolved near-road NO concentrations are analyzed in conjunction with wind and traffic data to provide a picture of emissions and near-road dispersion for the study. Results show peak NO concentrations in the 150 ppb range during weekday morning rush hours with winds from the road accompanied by significantly lower afternoon and weekend concentrations. Traffic volume and wind direction are shown to be primary determinants of NO concentrations with turbulent diffusion and meandering accounting for significant near-road concentrations in off-wind conditions. The enhanced source capture performance of the open-path configuration allowed for robust comparisons of measured concentrations with a composite variable of traffic intensity coupled with wind transport (R2 = 0.84) as well as investigations on the influence of wind direction on NO dilution near the roadway. The benefits of path-integrated measurements for assessing line source impacts and evaluating models is presented. The advantages of NO as a tracer compound, compared with nitrogen dioxide, for investigations of mobile source emissions and initial dispersion under crosswind conditions are also discussed.     

冬季沈阳市典型源排放PM_(10)浓度分布模拟分析

选取沈阳市7个典型的大气污染源2006年12月~2007年2月的PM10排放浓度资料,利用CALPUFF对PM10浓度月平均分布做模拟分析。模拟结果分析表明:冬季月平均PM10浓度分布的范围与风场、地形有直接的关系。地势平坦、风速大时,污染物扩散范围大,污染物浓度小;地势不平、风速小时,污染物扩散范围小,污染物浓度大。1月份是沈阳市冬季月平均大气污染最严重的月份,污染物分布主要集中在市区的北部、东部和南部地区,东部地区大气污染最为严重。     

Improvements to standard methodologies for the analytical determination of metals in stationary-source emissions samples

Deficiencies with the current European reference method for the analysis using inductively couple plasma-mass spectrometry of metals in samples from stationary emissions sources are presented based on experimental data obtained from real samples. The effect of these deficiencies on the quality and accuracy of data is highlighted with biases of up to 40% being observed in real samples. Suggestions to improve the performance of the standard method are presented. In particular, the beneficial effect of using a drift correction procedure to account for the decrease in instrument sensitivity observed during an analytical measurement series is demonstrated. It is shown that this corrective procedure results in substantial improvements to the accuracy of data produced.