Lung-deposited dose of particulate matter from residential exposure to smoke from wood burning

Environmental Science and Pollution Research - Residential settings are of utmost importance for human exposure, as it is where people spend most of their time. Residential wood combustion is a...     

Evaluation of total particulate matter emission factors for copper slag in dry abrasive blasting

Abrasive blasting was performed in enclosed conditions to evaluate the effect of blast pressure, feed rate and surface contamination on Total Particulate Matter (TPM) emission factors for copper slag. Stack sampling methods were used to collect uncontrolled TPM. Emission factors were calculated as grams of TPM emitted per pound of copper slag used (g/lb) and grams of TPM emitted per square foot of area cleaned (g/sq.ft). Emission factor models were developed to study variation of TPM emission factors with pressure, feed rate and surface contamination. These models can be used to reduce emissions by selecting optimum operating condition as well as to determine emission factors at any operating conditions, within the tested range, for copper slag.     

The fractionation of extracts of ambient particulate matter for mutagenicity testing

Extracts of air paniculate matter were fractionated by column chromatography over three different adsorbentia. It is shown that chromatography over alumina and over silicagel should be avoided, because of the low recovery of mutagenicity involved. On the other hand, fractionation over XAD-2 is strongly recommended, because of its ease of use and the superior recoveries of both mass and mutagenicity. HPLC subfractionation of the most mutagenic XAD-2 fraction showed that the mutagenicity cannot be attributed to a limited number of compounds.     

Evaluation of particulate matter abatement strategies for almond harvest

Almond harvest accounts for substantial PM10 (particulate matter [PM] < or =10 microm in nominal aerodynamic diameter) emissions in California each harvest season. This paper evaluates the effects of using reduced-pass sweepers and lower harvester separation fan speeds (930 rpm) on lowering PM emissions from almond harvesting operations. In-canopy measurements of PM concentrations were collected along with PM concentration measurements at the orchard boundary; these were used in conjunction with on-site meteorological data and inverse dispersion modeling to back-calculate emission rates from the measured concentrations. The harvester discharge plume was measured as a function of visible plume opacity during conditioning operations. Reduced-pass sweeping showed the potential for reducing PM emissions, but results were confounded because of differences in orchard maturity and irrigation methods. Fuel consumption and sweeping time per unit area were reduced when comparing a reduced-pass sweeper to a conventional sweeper. Reducing the separation fan speed from 1080 to 930 rpm led to reductions in PM emissions. In general, foreign matter levels within harvested product were nominally affected by separation fan speed in the south (less mature) orchard; however, in samples conditioned using the lower fan speed from the north (more mature) orchard, these levels were unacceptable.     

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.     

Application of a microscale emission factor model for particulate matter to calculate vehicle-generated contributions to fine particulate emissions

This paper discusses the evaluation and application of a new generation of particulate matter (PM) emission factor model (MicroFacPM). MicroFacPM that was evaluated in Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA shows good agreement between measured and modeled emissions. MicroFacPM application is presented to the vehicle traffic on the main approach road to the Ambassador Bridge, which is one of the most important international border entry points in North America, connecting Detroit, MI, with Windsor, Ontario, Canada. An increase in border security has forced heavy-duty diesel vehicles to line up for several kilometers through the city of Windsor causing concern about elevated concentrations of ambient PM. MicroFacPM has been developed to model vehicle-generated PM (fine [PM2.5] and coarse < or = 10 microm [PM10]) from the on-road vehicle fleet, which in this case includes traffic at very low speeds (10 km/h). The Windsor case study gives vehicle generated PM2.5 sources and their breakdown by vehicle age and class. It shows that the primary sources of vehicle-generated PM2.5 emissions are the late-model heavy-duty diesel vehicles. We also applied CALINE4 and AERMOD in conjunction with MicroFacPM, using Canadian traffic and climate conditions, to describe the vehicle-generated PM2.5 dispersion near this roadway during the month of May in 2003.     

An alternative way to determine the size distribution of airborne particulate matter

We developed and tested a methodology to extract both the size-segregated source apportionment of atmospheric aerosol and the size distribution of each detected element. The experiment is based on the parallel use of a standard low-volume sampler to collect Particulate Matter (PM) and an Optical Particle Counter (OPC). The approach is complementary to size-segregated PM sampling, and it was tested versus a 12-stage cascade impactor. Samples were collected inside the urban area of Genoa (Italy) and their elemental composition was measured by Energy Dispersive-X Ray Fluorescence (ED-XRF). Positive Matrix Factorization (PMF) was applied to time series of elemental concentrations to identify major PM sources, and both PM mass concentration and size-segregated particle number concentration were apportioned. Source profiles and temporal trends extracted by PMF were analyzed together with the OPC data to obtain the size distribution for several elements. The new methodology proved to be reliable for the PM apportionment as well as in providing the elemental concentrations in PM10, PM2.5, and PM1 (PM with aerodynamic diameter, D_ae < 10, 2.5, and 1 μm, respectively). The elemental size distributions are in good agreement with those obtained by the cascade impactor for several elements but some discrepancies, in particular for traffic emissions, are stressed and discussed in the text. The new methodology has two main advantages: it only requires standard semi-automatic sampling equipment and compositional analysis and it provides size-segregated information averaged over quite long periods (typically several months). This is particularly important since campaigns with cascade impactors are generally laborious and thus limited to short periods.     

燃油催化微粒捕集器在柴油机排气后处理中的应用研究

分析探讨了柴油机排气颗粒物的组成及危害,介绍了一种燃油催化微粒捕集器的结构及原理,结合发动机台架试验数据分析了该微粒捕集器对柴油机排气颗粒物的改善效果,同时研究了该微粒捕集器的强制再生过程以及对柴油机动力性和燃油经济性的影响.试验结果表明,该微粒捕集器具有较大的应用前景.     

关中地区机动车颗粒物排放清单

利用本地化修正的MOVES模型模拟确定了关中地区不同类型车辆的颗粒物排放因子,结合实地调研的保有量和行驶里程数据测算了该地区的机动车颗粒物年排放总量,并从季节、城市、车型和燃油等多个角度详细分析了颗粒物的排放分担率。结果表明：关中地区2012年的机动车颗粒物排放总量分别为PM2.5 4.06×103 t,PM10 5.52×103 t;关中五市一区中西安市的颗粒物排放量最高,PM2.5和PM10排放分别占到该地区的46.53%和48.39%;不同类型车辆中,重型货车的排放分担率最高,其次为中型货车,二者之和占到颗粒物总排放的50%以上;不同燃油车辆中,柴油车的排放分担率远远高于汽油车,是颗粒物的主要贡献者;因此中型和重型柴油货车是关中地区控制颗粒物排放污染的重点车型。     

Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur

Long-term measurements (2004–2011) of PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) and trace gases (carbon monoxide [CO], ozone [O₃], nitrogen oxide [NO], oxides of nitrogen [NO_x], nitrogen dioxide [NO₂], sulfur dioxide [SO₂], methane [CH₄], nonmethane hydrocarbon [NMHC]) have been conducted to study the effect of physicochemical factors on the PM₁₀ concentration. In addition, this study includes source apportionment of PM₁₀ in Kuala Lumpur urban environment. An advanced principal component analysis (PCA) technique coupled with absolute principal component scores (APCS) and multiple linear regression (MLR) has been applied. The average annual concentration of PM₁₀ for 8 yr is 51.3 ± 25.8 μg m^?3, which exceeds the Recommended Malaysian Air Quality Guideline (RMAQG) and international guideline values. Detail analysis shows the dependency of PM₁₀ on the linear changes of the motor vehicles in use and the amount of biomass burning, particularly from Sumatra, Indonesia, during southwesterly monsoon. The main sources of PM₁₀ identified by PCA-APCS-MLR are traffic combustion (28%), ozone coupled with meteorological factors (20%), and windblown particles (1%). However, the apportionment procedure left 28.0 μg m^?3, that is, 51% of PM₁₀ undetermined.

Implications: Air quality is always a top concern around the globe. Especially in the South Asian regions, measures are not yet sufficient; as revealed in our studies, the concentrations of particulate matters exceed the tolerable limits. Long-term data analysis and characterization of particular matters and their sources will aid the policy makers and the concerned authority to adapt measures and policies according to the circumstances. Additionally, similar intensive studies will give insight about future implications of air quality management.     

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.     

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.     

Investigation and modeling of the residential infiltration of fine particulate matter in Beijing,China

The objective of this study was to estimate the residential infiltration factor (Finf) of fine particulate matter (PM_2.5) and to develop models to predict PM_2.5 Finf in Beijing. Eighty-eight paired indoor–outdoor PM_2.5 samples were collected by Teflon filters for seven consecutive days during both non-heating and heating seasons (from a total of 55 families between August, 2013 and February, 2014). The mass concentrations of PM_2.5 were measured by gravimetric method, and elemental concentrations of sulfur in filter deposits were determined by energy-dispersive x-ray fluorescence (ED-XRF) spectrometry. PM_2.5 Finf was estimated as the indoor/outdoor sulfur ratio. Multiple linear regression was used to construct Finf predicting models. The residential PM_2.5 Finf in non-heating season (0.70 ± 0.21, median = 0.78, n = 43) was significantly greater than in heating season (0.54 ± 0.18, median = 0.52, n = 45, p < 0.001). Outdoor temperature, window width, frequency of window opening, and air conditioner use were the most important predictors during non-heating season, which could explain 57% variations across residences, while the outdoor temperature was the only predictor identified in heating season, which could explain 18% variations across residences. The substantial variations of PM_2.5 Finf between seasons and among residences found in this study highlight the importance of incorporating Finf into exposure assessment in epidemiological studies of air pollution and human health in Beijing. The Finf predicting models developed in this study hold promise for incorporating PM_2.5 Finf into large epidemiology studies, thereby reducing exposure misclassification.

Implications: Failure to consider the differences between indoor and outdoor PM_2.5 may contribute to exposure misclassification in epidemiological studies estimating exposure from a central site measurement. This study was conducted in Beijing to investigate residential PM_2.5 infiltration factor and to develop a localized predictive model in both nonheating and heating seasons. High variations of PM_2.5 infiltration factor between the two seasons and across homes within each season were found, highlighting the importance of including infiltration factor in the assessment of exposure to PM_2.5 of outdoor origin in epidemiological studies. Localized predictive models for PM_2.5 infiltration factor were also developed.     

桂林地区大气细颗粒物(PM2.5)工业排放源清单

通过现场勘测以及走访调研的形式,获得桂林地区2011至2013年工业生产情况统计,参照国内外相关文献资料确定排放因子,并通过数据处理得到桂林地区工业排放源清单。结果表明,近三年桂林地区工业污染源年均向大气排放细颗粒物(PM2.5)10 751.01 t,其中以兴安县贡献量最大,达到5 024.92 t;永福县次之,为2 924.31 t。在企业类型中,以火力发电企业、水泥及砖瓦厂对桂林地区大气排放细颗粒物的贡献量较大,分别为2 540.81、6 544.51和555.13 t。同时,桂林地区以煤炭作为主要燃料,其对大气排放细颗粒物的年均贡献量达到2 672.17 t。     

Comparison of real-time instruments and gravimetric method when measuring particulate matter in a residential building

This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the Northeastern US and compared performance of those instruments. PM_2.5 24-hr average concentrations were determined using a Personal Modular Impactor (PMI) with 2.5 µm cut (SKC Inc., Eighty Four, PA) and a direct reading pDR-1500 (Thermo Scientific, Franklin, MA) as well as its filter. 1-hr average PM_2.5 concentrations were measured in the same apartments with an Aerotrak Optical Particle Counter (OPC) (model 8220, TSI, Inc., Shoreview, MN) and a DustTrak DRX mass monitor (model 8534, TSI, Inc., Shoreview, MN). OPC and DRX measurements were compared with concurrent 1-hr mass concentration from the pDR-1500. The pDR-1500 direct reading showed approximately 40% higher particle mass concentration compared to its own filter (n = 41), and 25% higher PM_2.5 mass concentration compared to the PMI_2.5 filter. The pDR-1500 direct reading and PMI_2.5 in non-smoking homes (self-reported) were not significantly different (n = 10, R² = 0.937), while the difference between measurements for smoking homes was 44% (n = 31, R² = 0.773). Both OPC and DRX data had substantial and significant systematic and proportional biases compared with pDR-1500 readings. However, these methods were highly correlated: R² = 0.936 for OPC versus pDR-1500 reading and R² = 0.863 for DRX versus pDR-1500 reading. The data suggest that accuracy of aerosol mass concentrations from direct-reading instruments in indoor environments depends on the instrument, and that correction factors can be used to reduce biases of these real-time monitors in residential green buildings with similar aerosol properties.

Implications: This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the northeastern United States and compared performance of those instruments. The data show that while the use of real-time monitors is convenient for measurement of airborne PM at short time scales, the accuracy of those monitors depends on a particular instrument. Bias correction factors identified in this paper could provide guidance for other studies using direct-reading instruments to measure PM concentrations.     

Removal of ultrafine and fine particulate matter from air by a granular bed filter

The removal efficiency of granular filters packed with lava rock and sand was studied for collection of airborne particles 0.05-2.5 microm in diameter. The effects of filter depth, packing wetness, grain size, and flow rate on collection efficiency were investigated. Two packing grain sizes (0.3 and 0.15 cm) were tested for flow rates of 1.2, 2.4, and 3.6 L/min, corresponding to empty bed residence times (equal to the bulk volume of the packing divided by the airflow rate) in the granular media of 60, 30, and 20 sec, respectively. The results showed that at 1.2 L/min, dry packing with grains 0.15 cm in diameter removed more than 80% (by number) of the particles. Particle collection efficiency decreased with increasing flow rate. Diffusion was identified as the predominant collection mechanism for ultrafine particles, while the larger particles in the accumulation mode of 0.7-2.5 microm were removed primarily by gravitational settling. For all packing depths and airflow rates, particle removal efficiency was generally higher on dry packing than on wet packing for particles smaller than 0.25 microm. The results suggest that development of biological filters for fine particles is possible.     

A new alternative fuel for reduction of polycyclic aromatic hydrocarbon and particulate matter emissions from diesel engines

This study investigated the emissions of polycyclic aromatic hydrocarbons (PAHs), carcinogenic potential of PAH and particulate matter (PM), brake-specific fuel consumption (BSFC), and power from diesel engines under transient cycle testing of six test fuels: premium diesel fuel (PDF), B100 (100% palm biodiesel), B20 (20% palm biodiesel + 80% PDF), BP9505 (95% paraffinic fuel + 5% palm biodiesel), BP8020 (80% paraffinic fuel + 20% palm biodiesel), and BP100 (100% paraffinic fuel; Table 1). Experimental results indicated that B100, BP9505, BP8020, and BP100 were much safer when stored than PDF. However, we must use additives so that B100 and BP100 will not gel as quickly in a cold zone. Using B100, BP9505, and BP8020 instead of PDF reduced PM, THC, and CO emissions dramatically but increased CO2 slightly because of more complete combustion. The CO2-increased fraction of BP9505 was the lowest among test blends. Furthermore, using B100, B20, BP9505, and BP8020 as alternative fuels reduced total PAHs and total benzo[a]pyrene equivalent concentration (total BaPeq) emissions significantly. BP9505 had the lowest decreased fractions of power and torque and increased fraction of BSFC. These experimental results implied that BP9505 is feasible for traveling diesel vehicles. Moreover, paraffinic fuel will likely be a new alternative fuel in the future. Using BP9505 instead of PDF decreased PM (22.8%), THC (13.4%), CO (25.3%), total PAHs (88.9%), and total BaPeq (88.1%) emissions significantly.     

Evaluation and comparison of continuous fine particulate matter monitors for measurement of ambient aerosols

To provide a scientific basis for the selection and use of continuous monitors for exposure and/or health effects studies, and for compliance and episode measurements at strategic locations in the State of New Jersey, we evaluated the performance of seven continuous fine particulate matter (PM2.5) monitors in the present study. Gravimetric samplers, as reference methods, were collocated with realtime instruments in both laboratory and field tests. The results of intercomparison of real-time monitors showed that the two nephelometers used in this study correlated extremely well (r2 approximately 0.97), and two tapered element oscillating monitors (TEOM 1400 and TEOM filter dynamics measurement system [FDMS]) correlated well (r2 > 0.85), whereas two beta gauges displayed a weaker correlation (r2 < 0.6). During a summertime controlled (laboratory) evaluation, the measurements made with the gravimetric method correlated well with the 24-hr integrated measurements made with the real-time monitors. The SidePak nephelometer overestimated the particle concentration by a factor of approximately 3.4 compared with the gravimetric method. During a summertime field evaluation, the TEOM FDMS monitor reported approximately 30% higher mass concentration than the Federal Reference Method (FRM); and the difference could be explained by the loss of semi-volatile materials from the FRM sampler. Results also demonstrated that 24-hr average PM2.5 mass concentrations measured by beta gauges and TEOM (50 degrees C) in winter correlated well with the integrated gravimetric method. Seasonal differences were observed in the performance of the TEOM (50 degrees C) monitor in measuring the particle mass attributed to the higher semi-volatile material loss in the winter weather. In applying the realtime particulate matter monitoring data into Air Quality Index (AQI) reporting, the Conroy method and the 8-hr end-hour average method were both found to be suitable.     

Evaluation of particulate matter emissions from non-passenger diesel vehicles in Qatar

ABSTRACT

Road traffic is one of the main sources of particulate matter (PM) in the atmosphere. Despite its importance, there are significant challenges in the quantitative evaluation of its contribution to airborne concentrations. In order to propose effective mitigation scenarios, the proportions of PM traffic emissions, whether they are exhaust or non-exhaust emissions, should be evaluated for any given geographical location. In this work, we report on the first study to evaluate particulate matter emissions from all registered heavy duty diesel vehicles in Qatar. The study was applied to an active traffic zone in urban Doha. Dust samples were collected and characterized for their shape and size distribution. It was found that the particle size ranged from few to 600 μm with the dominance of small size fraction (less than 100 μm). In-situ elemental composition analysis was conducted for side and main roads traffic dust, and compared with non-traffic PM. The results were used for the evaluation of the enrichment factor and preliminary source apportionment. The enrichment factor of anthropogenic elements amounted to 350. The traffic source based on sulfur elemental fingerprint was almost 5 times higher in main roads compared with the samples from non-traffic locations. Moreover, PM exhaust and non-exhaust emissions (tyre wear, brake wear and road dust resuspension) were evaluated. It was found that the majority of the dust was generated from tyre wear with 33% followed by road dust resuspension (31%), brake wear (19%) and then exhaust emissions with 17%. The low contribution of exhaust PM₁₀ emissions was due to the fact that the majority of the registered vehicle models were recently made and equipped with efficient exhaust PM reduction technologies.

Implication: This study reports on the first results related to the evaluation of PM emission from all registered diesel heavy duty vehicles in Qatar. In-situ XRF elemental analysis from main, side roads as well as non-traffic dust samples was conducted. Several characterization techniques were implemented and the results show that the majority of the dust was generated from tyre wear, followed by road dust resuspension and then brake wear; whereas exhaust emissions were tremendously reduced since the majority of the registered vehicle models were recently made and equipped with efficient exhaust PM reduction technologies. This implies that policy makers should place stringent measures on old vehicle license renewals and encourage the use of metro and public transportation.     

Hot filter/impinger and dilution sampling for fine particulate matter characterization from ferrous metal casting processes

A study using two stack-sampling methodologies for collecting particulate matter (PM) emissions was conducted using a hot filter followed by a cold impinger sampling train and a dilution sampler. Samples were collected from ferrous iron metal casting processes that included pouring molten iron into a sand mold containing an organic binder, metal cooling, removal of the sand from the cooled casting (shakeout), and postshakeout cooling. The shakeout process contributed more to PM emissions than the metal pouring and cooling processes. Particulate matter less than 2.5 microm in aerodynamic diameter (PM2.5) mass emissions for the entire casting cycle ranged from 3.4 to 4.7 lb/t of metal for the hot filter/impinger method and from 0.8 to 1.8 lb/t of metal for the dilution method. Most of the difference was due to PM captured by the impingers, much of which was probably dissolved gases rather than condensable vapors. Of the PM fraction captured by the impingers, 96-98% was organic in nature. The impinger PM fraction contributed 32-38% to the total suspended particle mass and caused a factor of 2-4 positive bias for PM2.5 emissions. For the pouring and cooling processes only, the factor increased to over seven times.