Development of Emission Factors for Polyamide Processing

ABSTRACT

Emission factors for selected volatile organic compounds (VOCs) and particulate material were developed during processing of commercial grades of polyamide 6, polyamide 66, and polyamide 66/6 resins. A small commercial-type extruder was used, and melt temperatures ranged from 475 to 550 °F. An emission factor was calculated for each substance measured and is reported as pounds released to the atmosphere per million pounds of polymer resin processed. Scaled to production volumes, these emission factors can be used by processors to estimate emission quantities from similar polyamide extrusion operations.     

Development of emission factors for polycarbonate processing

Emission factors for selected volatile organic compounds (VOCs) and particulate emissions were developed while processing eight commercial grades of polycarbonate (PC) and one grade of a PC/acrylonitrile-butadiene-styrene (ABS) blend. A small commercial-type extruder was used, and the extrusion temperature was held constant at 304 degrees C. An emission factor was calculated for each substance measured and is reported as pounds released to the atmosphere/million pounds of polymer resin processed [ppm (wt/wt)]. Scaled to production volumes, these emission factors can be used by processors to estimate emission quantities from similar PC processing operations.     

Development of Emission Factors for Polycarbonate Processing

Abstract

Emission factors for selected volatile organic compounds (VOCs) and particulate emissions were developed while processing eight commercial grades of polycarbonate (PC) and one grade of a PC/acrylonitrile-butadiene-styrene (ABS) blend. A small commercial-type extruder was used, and the extrusion temperature was held constant at 304 °C. An emission factor was calculated for each substance measured and is reported as pounds released to the atmosphere/million pounds of polymer resin processed [ppm (wt/wt)]. Scaled to production volumes, these emission factors can be used by processors to estimate emission quantities from similar PC processing operations.     

Determining the Costs of Air Pollution Control

A general procedure has been described that can be followed for estimating the cost of reducing air pollution emissions within a metropolitan region. The six step procedure examines emission inventories, regional trends, control trends, alternate control schemes, control costs, and optimum cost-effectiveness. The procedure is illustrated for one emission source in the Delaware Valley. By application of “feasible controls,” automobile emissions were shown to be reduced from 4.5 billion pounds per year in the Region during 1968 to 1.5 billion pounds in the year 2000. Annual control costs during the same period will increase from $30 million to over $300 million per year. This represents a cost increase from $15 per registered vehicle in 1968 to about $58 per vehicle per year in 2000. A method was illustrated for determining minimum cost to achieve any desired degree of emission reduction where alternate feasible control schemes are available. This method is especially useful where the allocation of scarce resources is involved. The general procedure is applicable to any number of pollutants and emission sources, and may be useful for calculations in any metropolitan area. The objectives of the present study are to apply this method to other sources within the Delaware Valley and to determine total regional costs for various levels of emission reduction. As one example of a practical application for this type of analysis, the economic impact of regulatory schemes can be evaluated on a cost-effectiveness basis     

Use of AERMOD to Determine a Hydrogen Sulfide Emission Factor for Swine Operations by Inverse Modeling

This study was conducted to determine both optimal settings applied to the plume dispersion model, AERMOD, and a scalable emission factor for accurately determining the spatial distribution of hydrogen sulfide concentrations in the vicinity of swine concentrated animal feeding operations (CAFOs). These operations emit hydrogen sulfide from both housing structures and waste lagoons. With ambient measurements made at 4 stations within 1 km of large swine CAFOs in Iowa, an inverse-modeling approach applied to AERMOD was used to determine hydrogen sulfide emission rates. CAFO buildings were treated as volume sources whereas nearby lagoons were modeled as area sources. The robust highest concentration (RHC), calculated for both measured and modeled concentrations, was used as the metric for adjusting the emission rate until the ratio of the two RHC levels was unity. Utilizing this approach, an average emission flux rate of 0.57 μg/m(2)-s was determined for swine CAFO lagoons. Using the average total animal weight (kg) of each CAFO, an average emission factor of 6.06 × 10(-7) μg/yr-m(2)-kg was calculated. From studies that measured either building or lagoon emission flux rates, building fluxes, on a floor area basis, were considered equal to lagoon flux rates. The emission factor was applied to all CAFOs surrounding the original 4 sites and surrounding an additional 6 sites in Iowa, producing an average modeled-to-measured RHC ratio of 1.24. When the emission factor was applied to AERMOD to simulate the spatial distribution of hydrogen sulfide around a hypothetical large swine CAFO (1M kg), concentrations 0.5 km from the CAFO were 35 ppb and dropped to 2 ppb within 6 km of the CAFO. These values compare to a level of 30 ppb that has been determined by the State of Iowa as a threshold level for ambient hydrogen sulfide levels.     

Open-path tunable diode laser absorption spectroscopy for acquisition of fugitive emission flux data

Air pollutant emission from unconfined sources is an increasingly important environmental issue. The U.S. Environmental Protection Agency (EPA) has developed a ground-based optical remote-sensing method that enables direct measurement of fugitive emission flux from large area sources. Open-path Fourier transform infrared spectroscopy (OP-FTIR) has been the primary technique for acquisition of pollutant concentration data used in this emission measurement method. For a number of environmentally important compounds, such as ammonia and methane, open-path tunable diode laser absorption spectroscopy (OP-TDLAS) is shown to be a viable alternative to Fourier transform spectroscopy for pollutant concentration measurements. Near-IR diode laser spectroscopy systems offer significant operational and cost advantages over Fourier transform instruments enabling more efficient implementation of the measurement strategy. This article reviews the EPA's fugitive emission measurement method and describes its multipath tunable diode laser instrument. Validation testing of the system is discussed. OP-TDLAS versus OP-FTIR correlation testing results for ammonia (R2 = 0.980) and methane (R2 = 0.991) are reported. Two example applications of tunable diode laser-based fugitive emission measurements are presented.     

Emissions from Burning Grass Stubble and Straw

The emissions from burning the residue following grass-seed harvest were determined by means of a combined laboratory-field study. Samples of the straw and stubble residue were burned in the laboratory burning tower at the University of California at Riverside. Complete analyses were determined for gaseous and particulate emissions for the important grass species from the Willamette Valley of Oregon. Particulate emissions averaged 15.6 lb/ton of fuel burned. Carbon monoxide averaged 101 lb/ton of fuel burned. Hydrocarbon emission averages, in pounds per ton of fuel burned, were 1.74 for saturates plus acetylene, 2.80 for defines, and 1.68 for ethylene. The NO_x emission, at the temperature peak during the burn, averaged 29.3 ppm. Field studies, conducted by personnel from Oregon State University, measured only particulate emissions, carbon dioxide, and temperature over the burn. The carbon dioxide values were found to be similar to those obtained on the burning table at UCR and it was therefore concluded that the other gaseous emissions were similar and could be used as reasonably accurate for emission inventories. The temperature values obtained in the laboratory and field were also similar and further justifies extrapolating the burning table data to field situations. The particulate matter collected in the field studies averaged 15.55 lb of particulate per ton of fuel burned. This is the same average obtained for the burning table data which again serves to validate the emissions reported from Riverside. Much more variability was found in the particulate emissions obtained in the field which reflects the wider range of environmental conditions encountered in the field.     

Emissions of persistent organic pollutants and eight candidate POPs from UNECE–Europe in 2000, 2010 and 2020 and the emission reduction resulting from the implementation of the UNECE POP protocol

An emission inventory for persistent organic pollutants (POP) is made for the year 2000 based on submissions of emission data from the Parties to the Convention on LRTAP. The inventory covers the UNECE territory except Canada and the United States. For the countries, sources or compounds lacking in official submissions, default emission estimates have been prepared and applied to complete the inventory. An indicative comparison of the year 2000 emissions with the 1990 emission levels from a previous study is presented as well as emission projections for 2010, 2015, 2020 based on activity scenarios developed in the framework of the EU CAFE programme. The key source analysis of the projected emissions assuming full implementation of the UNECE protocols allows identification of remaining source strengths which subsequently are briefly discussed in terms of their potential for (further) reduction. A number of chemicals are currently being investigated for inclusion on the UN/ECE POPs protocol list of priority compounds but for these substances emission estimation methodologies are scarce or non-existent. For eight of these substances (dicofol, edosulfan, hexachlorobutadiene (HBU), pentabromodiphenyl ether (PBDE), pentachlorobenzene (PCBe), pentachlorophenol (PCP), polychloronated naftalenes (PCN) and short chained chlorinated paraffins (SCCPs)) an emission estimation methodology is proposed and a preliminary emission inventory for the year 2000 is presented.     

A fuel-based approach for emission factor development for highway paving construction equipment in China

The objective of this paper is to develop and demonstrate a fuel-based approach for emissions factor estimation for highway paving construction equipment in China for better accuracy. A highway construction site in Chengdu was selected for this study with NO emissions being characterized and demonstrated. Four commonly used paving equipment, i.e., three rollers and one paver were selected in this study. A portable emission measurement system (PEMS) was developed and used for emission measurements of selected equipment during real–world highway construction duties. Three duty modes were defined to characterize the NO emissions, i.e., idling, moving, and working. In order to develop a representative emission factor for these highway construction equipment, composite emission factors were estimated using modal emission rates and the corresponding modal durations in the process of typical construction duties. Depending on duty mode and equipment type, NO emission rate ranged from 2.6–63.7mg/s and 6.0–55.6g/kg–fuel with the fuel consumption ranging from 0.31–4.52 g/s correspondingly. The NO composite emission factor was estimated to be 9–41mg/s with the single-drum roller being the highest and double-drum roller being the lowest and 6–30g/kg-fuel with the pneumatic tire roller being the highest while the double-drum roller being the lowest. For the paver, both time-based and fuel consumption-based NO composite emission rates are higher than all of the rollers with 56mg/s and 30g/kg-fuel, respectively. In terms of time–based quantity, the working mode contributes more than the other modes with idling being the least for both emissions and fuel consumption. In contrast, the fuel-based emission rate appears to have less variability in emissions. Thus, in order to estimate emission factors for emission inventory development, the fuel-based emission factor may be selected for better accuracy.

Implications: The fuel-based composite emissions factors will be less variable and more accurate than time-based emission factors. As a consequence, emissions inventory developed using this approach will be more accurate and practical.     

Estimating Emissions from Air Concentration Measurements

A one-year-long experiment in which two different tracers were simultaneously released from two different locations was used to test various hybrid receptor modeling techniques to estimate the tracer emissions using the measured air concentrations and a meteorological model. Air concentrations were measured over an 8-hour averaging time at three sites 14 to 40 km downwind. When the model was used to estimate emissions at only one tracer source, 6 percent of the short-term (8-h) emission estimates were within a factor of 2 of the actual emissions. Temporal averaging of the 8-h data enhanced the precision of the estimate such that after 10 days 42 percent of the estimates were within a factor of 2 and after six months all of them (each source-receptor pair) were within a factor of 2. To test the ability of the model to separate two sources, both tracer sources were combined, and a multiple linear regression technique was used to determine the emissions from each source from a time series of air concentration measurements representing the sum of both tracers. In general, 50 percent of the short-term estimates were within a factor of 10, 25 percent were biased low, and in another 25 percent the regression technique failed. The bias and failures are attributed to low or no correlation between measured air concentrations and model calculated dispersion factors. In the regression method increased temporal averaging did not consistently improve the emission estimate since the ability of the model to distinguish emissions between sources was diminished with increased averaging time. However, including progressively longer time periods (more data) into the regression or spatially averaging the data over all the receptors was found to be the most effective method to improve the estimated emissions. At best about 75 percent of the estimated monthly emission data were within a factor of 10 of the measured values. This suggests that the usefulness of meteorological models and statistical methods to address questions of source attribution requires many data points to reduce the uncertainty in the emission estimates.     

Development of a microscale emission factor model for particulate matter for predicting real-time motor vehicle emissions

The U.S. Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant exposure microenvironments. Current particulate matter (PM) emission models, particle emission factor model (used in the United States, except California) and motor vehicle emission factor model (used in California only), are suitable only for county-scale modeling and emission inventories. There is a need to develop a site-specific real-time emission factor model for PM emissions to support human exposure studies near roadways. A microscale emission factor model for predicting site-specific real-time motor vehicle PM (MicroFacPM) emissions for total suspended PM, PM less than 10 microm aerodynamic diameter, and PM less than 2.5 microm aerodynamic diameter has been developed. The algorithm used to calculate emission factors in MicroFacPM is disaggregated, and emission factors are calculated from a real-time fleet, rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacPM requires input information necessary to characterize the site-specific real-time fleet being modeled. Other variables required include average vehicle speed, time and day of the year, ambient temperature, and relative humidity.     

Chlorination reactions of 1,2,3,4-tetrachlorodibenzo-p-dioxin on fly ash with HC1 in air

Chlorine substitution reactions of 1,2,3,4-TCDD to higher chlorinated PCDD occurred on fly ash between 50°C to 250°C with an HC1 in air atmosphere in a laboratory reaction apparatus used to simulate emission conditions in municipal incinerators. Percent conversion of 1,2,3,4-TCDD through such reactions was as high as 66% by mass corrected for losses to irreversable absorption. Production of penta-, hexa-, hepta- and octa-CDD was evident and a maximum in production of P₅CDD and H₆CDD was reached in 10 to 30 min. Results showed that these reactions may involve complex mechanisms which include several states of adsorption with different reactivities of 1,2,3,4-TCDD on fly ash.     

Quantification of emission factor uncertainty

Emissions factors are important for estimating and characterizing emissions from sources of air pollution. There is no quantitative indication of uncertainty for these emission factors, most factors do not have an adequate data set to compute uncertainty, and it is very difficult to locate the data for those that do. The objectives are to compare the current emission factors of Electric Generating Unit NOx sources with currently available continuous emission monitoring data, develop quantitative uncertainty indicators for the Environmental Protection Agency (EPA) data quality rated emission factors, and determine the possible ranges of uncertainty associated with EPA's data quality rating of emission factors. EPA's data letter rating represents a general indication of the robustness of the emission factor and is assigned based on the estimated reliability of the tests used to develop the factor and on the quantity and representativeness of the data. Different sources and pollutants that have the same robustness in the measured emission factor and in the representativeness of the measured values are assumed to have a similar quantifiable uncertainty. For the purposes of comparison, we assume that the emission factor estimates from source categories with the same letter rating have enough robustness and consistency that we can quantify the uncertainty of these common emission factors based on the qualitative indication of data quality which is known for almost all factors. The results showed that EPA's current emission factor values for NOx emissions from combustion sources were found to be reasonably representative for some sources; however AP-42 values should be updated for over half of the sources to reflect current data. The quantified uncertainty ranges were found to be 25-62% for A rated emission factors, 45-75% for B rated emission factors, 60-82% for C rated emission factors, and 69-86% for D rated emission factors, and 82-92% for E rated emission factors.     

加油站气液比检测方法及其影响

气液比(A/L)是加油站油气回收系统的一项重要控制指标,利用A/L测试仪、光离子化VOCs检测仪和油气排放因子测试装置,研究了不同A/L检测连接方式对A/L检测结果、检测人员暴露浓度、油气排放和油气回收效率等的影响。结果表明,不同连接方式和是否预先向检测油桶注油会导致A/L检测结果不一致,如果油桶与流量计不连接,A/L检测值将是实际A/L的1.04倍,当按照A/L=1.00~1.20调整加油枪A/L时,实际A/L将在0.96~1.15之间;按照国标GB20952-2007连接方式检测A/L可以减少检测过程中约80%的加油油气排放,夏季检测人员暴露油气浓度将由451×10-6(体积浓度)下降至91×10-6(体积浓度),油气排放因子将由1 056 mg/L下降至242 mg/L,更可减少因油罐吸入空气造成额外的汽油挥发排放,但不能减少倒油油气排放。     

Measurement of Hydrocarbon Emissions Fluxes from Refinery Wastewater Impoundments Using Atmospheric Tracer Techniques

Sulfur hexafluoride (SF6) tracer was used in a series of the experiments to simulate emissions of benzene, toluene, ethyl-benzene, and xylenes (BTEX) from a refinery wastewater basin. The ratio of the measured tracer release to the ambient tracer concentration established a dilution factor which was then used to calculate the mass flux of BTEX from the wastewater basin using the ambient BTEX concentration data. Measured fluxes of BTEX varied from 7 g/min to 70 g/min.

The CHEMDAT7 air emissions model was then used to predict emissions for comparison with the emissions measured using the tracer flux simulation. CHEMDAT7 typically overpredicted total measured BTEX emissions by factors of twelve to seventeen. The degree of overprediction varied both by the individual compound and the module of CHEMDAT7 used to predict emission fluxes.     

A composite receptor and dispersion model approach for estimation of effective emission factors for vehicles

It is difficult to estimate vehicular emission factors at traffic junctions for use in dispersion modelling studies. Firstly, because the vehicles are in various modes of operation and secondly, it is difficult to delineate the effects of other contributing sources, mainly the effects of road dust and deposited constituents, which are very prominent at traffic junctions in India. Factor analysis-multiple regression (FA-MR), a receptor modelling technique has been used in this study for apportioning the contributing sources. The measurement data consist of one year's temporal variation of suspended particulate matter (SPM), analysed for its trace metal constituents, and two gaseous components NO₂ and SO₂ at two traffic junctions in Mumbai (India). FA-MR apportioned 40% of the observed SPM to road dust and 15% to vehicular sources. Of the total Pb observed in the SPM, FA-MR apportioned 60% to vehicular sources and 20% to road dust. The field-observed vehicular counts, meteorological parameters and road geometry were used in California line source dispersion model to estimate the effective vehicular emission factor for Pb at one traffic junction. This derived emission factor was used to predict the Pb concentration at second (independent observation) traffic junction. The result was found to be more satisfactory than using default emission factors obtained from literature. Similarly, effective vehicular emission factor for NO₂ was also evaluated for one site and tested for predicting concentrations at the other site.     

Development and preliminary evaluation of a particulate matter emission factor model for European motor vehicles

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 microns, either from published data or from user-defined size distributions. A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM10, PM5, PM2.5, and PM1] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway). A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM10 was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Black carbon particulate matter emission factors for buoyancy-driven associated gas flares

Flaring is a technique used extensively in the oil and gas industry to burn unwanted flammable gases. Oxidation of the gas can preclude emissions of methane (a potent greenhouse gas); however, flaring creates other pollutant emissions such as particulate matter (PM) in the form of soot or black carbon (BC). Currently available PM emissionfactors for flares were reviewed and found to be questionably accurate, or based on measurements not directly relevant to open-atmosphere flares. In addition, most previous studies of soot emissions from turbulent diffusion flames considered alkene or alkyne based gaseous fuels, and few considered mixed fuels in detail and/or lower sooting propensity fuels such as methane, which is the predominant constituent of gas flared in the upstream oil and gas industry. Quantitative emission measurements were performed on laboratory-scale flares for a range of burner diameters, exit velocities, and fuel compositions. Drawing from established standards, a sampling protocol was developed that employed both gravimetric analysis of filter samples and real-time measurements of soot volume fraction using a laser-induced incandescence (LII) system. For the full range of conditions tested (burner inner diameter [ID] of 12.7-76.2 mm, exit velocity 0.1-2.2 m/sec, 4- and 6-component methane-based fuel mixtures representative of associated gas in the upstream oil industry), measured soot emission factors were less than 0.84 kg soot/10(3) m3 fuel. A simple empirical relationship is presented to estimate the PM emission factor as a function of the fuel heating value for a range of conditions, which, although still limited, is an improvement over currently available emission factors.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.