Particulate Emission Factors Research Articles

First Stage Lint Cleaning Systems Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Also, some commonly used cotton gin systems were not represented or were combined with another system under a single emission factor in AP-42. No EPA AP-42 emission factors were published for 1st stage lint cleaning systems. The objective of this study was to collect PM10 emission factor data for 1st stage lint cleaning systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems and 4) abatement technologies. Four of the seven gins were equipped with 1st stage lint cleaning systems where the exhaust airstreams were not combined with 2nd stage lint cleaning systems. In terms of capacity, the four gins were typical of the industry, averaging 28.1 bales/h during testing. Some test runs, included in the analyses, had cotton lint fibers that collected in the ≤ 10 µm samples. This larger lint material can affect the reported emissions data, but EPA Method 201A does not suggest methods to account for these anomalies. The 1st stage lint cleaning system average emission factors for PM10 and total particulate were 0.041 kg/227-kg bale (0.091 lb/500-lb bale) and 0.066 kg/bale (0.146 lb/bale), respectively. System average PM10 and total particulate emission factors were lower than those currently published in EPA AP-42 for 1st and 2nd stage lint cleaning systems combined. The 1st stage lint cleaning system PM10 emission rate test averages ranged from 0.26 to 2.92 kg/h (0.58-6.44 lb/h). The ratio of 1st stage lint cleaning system PM10 to total particulate was 62.3%.

Cyclone Robber System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect additional cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Cotton gin data received these low ratings because they were collected almost exclusively from a single geographical region. The objective of this study was to collect additional PM10 emission factor data for cyclone robber systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems, and 4) abatement technologies. Three of the seven gins were equipped with cyclone robber systems. In terms of capacity, the three gins were typical of the industry, averaging 26.6 bales/h during testing. Some test runs were excluded from the test averages because they failed to meet EPA Method 201A test criteria. Also, other test runs included in the analyses had cotton lint fibers that collected in the ≤ 10 µm samples. This larger lint material can affect the reported emissions data, but EPA Method 201A does not suggest methods to account for these anomalies. The cyclone robber system average emission factors for PM10 and total particulate were 0.010 kg/227-kg bale (0.022 lb/500-lb bale) and 0.018 kg/bale (0.040 lb/bale), respectively. System average PM10 and total particulate emission factors were lower than those currently published in EPA AP-42. The cyclone robber system PM10 emission rate test averages ranged from 0.16 to 0.44 kg/h (0.35-0.96 lb/h). The ratio of cyclone robber system PM10 to total particulate was 55.9%.

Combined Lint Cleaning System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect additional cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Cotton gin data received these low ratings because they were collected almost exclusively from a single geographical region. The objective of this study was to collect additional PM10 emission factor data for combined lint cleaning systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems and 4) abatement technologies. Three of the seven gins had 1st and 2nd stage lint cleaning systems where the exhaust airstreams were combined. In terms of capacity, the three gins were typical of the industry, averaging 28.0 bales/h during testing. Some test runs, included in the analyses, had cotton lint fibers that collected in the ≤ 10 µm samples. This larger lint material can affect the reported emissions data, but EPA Method 201A does not suggest methods to account for these anomalies. The combined lint cleaning system average emission factors for PM10 and total particulate were 0.150 kg/227-kg bale (0.332 lb/500-lb bale) and 0.293 kg/bale (0.647 lb/bale), respectively. System average PM10 and total particulate emission factors were higher than those currently published in EPA AP-42. The combined lint cleaning system PM10 emission rate test averages ranged from 1.62 to 5.19 kg/h (3.56-11.45 lb/h). The ratio of combined lint cleaning system PM10 to total particulate was 51.3%.

Mote Trash System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect additional cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Cotton gin data received these low ratings because they were collected almost exclusively from a single geographical region. The objective of this study was to collect additional PM10 emission factor data for mote trash systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems, and 4) abatement technologies. Two of the seven gins had mote trash systems where the exhaust airstreams were not combined with other major systems. In terms of capacity, the two gins were typical of the industry, averaging 32.4 bales/h during testing. The mote trash system average emission factors for PM10 and total particulate were 0.011 kg/227-kg bale (0.025 lb/500-lb bale) and 0.021 kg/bale (0.046 lb/bale), respectively. The system average PM10 emission factor was higher and the system average total particulate emission factor was lower than those currently published in EPA AP-42. Mote trash system PM10 emission rate test averages ranged from 0.32 to 0.37 kg/h (0.72-0.81 lb/h). The ratio of mote trash system PM10 to total particulate was 53.2%.

First Stage Seed-Cotton Cleaning System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect additional cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Cotton gin data received these low ratings because they were collected almost exclusively from a single geographical region. The objective of this study was to collect additional PM10 emission factor data for 1st stage seed-cotton cleaning systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems and 4) abatement technologies. In terms of capacity, the seven gins were typical of the industry, averaging 31.9 bales/h during testing. Some test runs were excluded from the test averages because they failed to meet EPA Method 201A test criteria. Also, other test runs, included in the analyses, had cotton lint fibers that collected in the ≤ 10 µm samples. This larger lint material can affect the reported emissions data, but EPA Method 201A does not suggest methods to account for these anomalies. The 1st stage seed-cotton cleaning system average emission factors for PM10 and total particulate were 0.097 kg/227-kg bale (0.215 lb/500-lb bale) and 0.144 kg/bale (0.317 lb/bale), respectively. The system average PM10 emission factor was higher, and the system average total particulate emission factor was lowerthan those currently published in EPA AP-42. First stage seed-cotton cleaning system PM10 emission rate test averages ranged from 1.61 to 4.72 kg/h (3.55 to 10.40 lb/h). The ratio of 1st stage seed-cotton cleaning system PM10 to total particulate was 67.7%.

Third Stage Seed-Cotton Cleaning System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect additional cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Cotton gin data received these low ratings because they were collected almost exclusively from a single geographical region. The objective of this study was to collect additional PM10 emission factor data for 3rd stage seed-cotton cleaning systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems and 4) abatement technologies. Two of the seven gins were equipped with 3rd stage seed-cotton cleaning systems. In terms of capacity, the two gins were typical of the industry, averaging 22.0 bales/h during testing. The 3rd stage seed-cotton cleaning system average emission factors for PM10 and total particulate were 0.019 kg/227-kg bale (0.042 lb/500-lb bale) and 0.024 kg/bale (0.054 lb/bale), respectively. The system average PM10 emission factor was higher and the system average total particulate emission factor was lower than those currently published in EPA AP-42. Third stage seed-cotton cleaning system PM10 emission rate test averages ranged from 0.28 to 0.56 kg/h (0.61-1.24 lb/h). The ratio of 3rd stage seed-cotton cleaning system PM10 to total particulate was 79.1%.

Mote Cleaner System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Also, some commonly used cotton gin systems were not represented or were combined with another system under a single emission factor in AP-42. There were no 1996 EPA AP-42 emission factors published for mote cleaner systems. The objective of this study was to collect PM10 emission factor data for mote cleaner systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems, and 4) abatement technologies. Two of the seven gins had mote cleaner systems. The exhaust from one of the mote cleaner systems was combined with the module feeder dust system. The ginning rate of the two gins averaged 36.0 and 46.2 bales/h during testing for the stand-alone mote cleaner system and mote cleaner and module feeder dust system, respectively. Some test runs were excluded from the test averages because they failed to meet EPA Method 201A test criteria. Also, other test runs, included in the analyses, had cotton lint fibers that collected in the ≤ 10 µm samples. This larger lint material can affect the reported emissions data, but EPA Method 201A does not suggest methods to account for these anomalies. The average measured PM10 and total particulate emission factors for the stand-alone mote cleaner system were 0.050 kg/227-kg bale (0.109 lb/500-lb bale) and 0.090 kg/bale (0.199 lb/bale), respectively. The ratio of mote cleaner system PM10 to total particulate was 54.9%. The PM10 emission rate averaged 1.79 kg/h (3.95 lb/h) for the stand-alone mote cleaner system. The average measured PM10 and total particulate emission factors for the mote cleaner system combined with the module feeder dust system were 0.071 kg/bale (0.157 lb/bale) and 0.109 kg/bale (0.241 lb/bale), respectively. The ratio of PM10 to total particulate for the mote cleaner system combined with the module feeder dust system was 65.1%. The PM10 emission rate averaged 3.27 kg/h (7.21 lb/h) for the combined mote cleaner and module feeder dust system.

Second Stage Mote System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins are extremely low. Also, some commonly used cotton gin systems were not represented or were combined with another system under a single emission factor in AP-42. There were no 1996 EPA AP-42 emission factors published for 2nd stage mote systems. The objective of this study was to collect PM10 emission factor data for 2nd stage mote systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems. and 4) abatement technologies. Five of the seven gins were equipped with 2nd stage mote systems that were not combined with 1st stage mote systems. In terms of capacity, the five gins were typical of the industry, averaging 29.4 bales/h during testing. The 2nd stage mote system average emission factors for PM10 and total particulate were 0.0081 kg/227-kg bale (0.018 lb/500-lb bale) and 0.011 kg/bale (0.025 lb/bale), respectively. System average PM10 and total particulate emission factors were lower than those currently published in EPA AP-42 for 1st and 2nd stage mote systems combined. The 2nd stage mote system PM10 emission rate test averages ranged from 0.072 to 0.59 kg/h (0.16-1.31 lb/h). The ratio of 2nd stage mote system PM10 to total particulate was 72.1%.

Master Trash System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect additional cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Cotton gin data received these low ratings because they were collected almost exclusively from a single geographical region. The objective of this study was to collect additional PM10 emission factor data for master trash systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems, and 4) abatement technologies. Five of the seven gins had master trash systems. In terms of capacity, the five gins were typical of the industry, averaging 36.2 bales/h during testing. Some test runs were excluded from the test averages because they failed to meet EPA Method 201A test criteria. Also, other test runs, included in the analyses, had cotton lint fibers that collected in the ≤ 10 µm samples. This larger lint material can affect the reported emissions data, but EPA Method 201A does not suggest methods to account for these anomalies. The master trash system average emission factors for PM10 and total particulate were 0.056 kg/227-kg bale (0.123 lb/500-lb bale) and 0.152 kg/bale (0.335 lb/bale), respectively. The system average PM10 emission factor was higher and the system average total particulate emission factor was lower than those currently published in EPA AP-42. Master trash system PM10 emission rate test averages ranged from 1.39 to 4.18 kg/h (3.06-9.21 lb/h). The ratio of master trash system PM10 to total particulate was 36.9%.

Unloading System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect additional cotton gin emissions data to address current regulatory issues. A key component of this study was focused on EPA emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Cotton gin data received these low ratings because they were collected almost exclusively from a single geographical region. The objective of this study was to collect additional PM10 emission factor data for unloading systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems and 4) abatement technologies. Three of the seven gins had unloading systems that used pneumatic conveyance and had exhaust airstreams that were not combined with another system. In terms of capacity, the three gins were typical of the industry, averaging 26.1 bales/h during testing. Some test runs were excluded from the test averages because they failed to meet EPA Method 201A test criteria. Also, other test runs, included in the analyses, had cotton lint fibers that collected in the ≤ 10 µm samples. This larger lint material can affect the reported emissions data, but EPA Method 201A does not suggest methods to account for these anomalies. The unloading system average emission factors for PM10 and total particulate were 0.107 kg/227-kg bale (0.237 lb/500-lb bale) and 0.131 kg/bale (0.289 lb/bale), respectively. The system average PM10 emission factor was higher and the system average total particulate emission factor was about the same as those currently published in EPA AP-42. Unloading system PM10 emission rate test averages ranged from 1.16 to 3.99 kg/h (2.57-8.79 lb/h). The ratio of unloading system PM10 to total particulate was 81.9%.

Second Stage Lint Cleaning System PM10 Emission Factors and Rates for Cotton Gins: Method 201A PM10 Sizing Cyclones

This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. The impetus behind this project was the urgent need to collect cotton gin emissions data to address current regulatory issues. A key component of this study was focused on Environmental Protection Agency (EPA) emission factors for particulate matter with a particle diameter nominally less than or equal to 10 µm (PM10). The 1996 EPA AP-42 emission factors were assigned quality ratings, from A (Excellent) to E (Poor), to assess the quality of the data being referenced. Emission factor quality ratings for cotton gins were extremely low. Also, some commonly used cotton gin systems were not represented or were combined with another system under a single emission factor in AP-42. There were no 1996 EPA AP-42 emission factors published for 2nd stage lint cleaning systems. The objective of this study was to collect PM10 emission factor data for 2nd stage lint cleaning systems at cotton gins located in regions across the cotton belt based on EPA-approved stack sampling methodology, Method 201A. The project plan included sampling seven cotton gins across the cotton belt. Key factors for selecting specific cotton gins included: 1) facility location, 2) production capacity, 3) processing systems and 4) abatement technologies. Four of the seven gins were equipped with 2nd stage lint cleaning systems where the exhaust airstreams were not combined with the 1st stage lint cleaning systems. In terms of capacity, the four gins were typical of the industry, averaging 29.4 bales/h during testing. Some test runs were excluded from the test averages because they failed to meet EPA Method 201A test criteria. Also, other test runs, included in the analyses, had cotton lint fibers that collected in the ≤ 10 µm samples. This larger lint material can affect the reported emissions data, but EPA Method 201A does not suggest methods to account for these anomalies. The 2nd stage lint cleaning system average emission factors for PM10 and total particulate were 0.018 kg/227-kg bale (0.039 lb/500-lb bale) and 0.035 kg/bale (0.078 lb/bale), respectively. System average PM10 and total particulate emission factors were lower than those currently published in EPA AP-42 for 1st and 2nd stage lint cleaning systems combined. The 2nd stage lint cleaning system PM10 emission rate test averages ranged from 0.15 to 0.98 kg/h (0.33-2.17 lb/h). The ratio of 2nd stage lint cleaning system PM10 to total particulate was 50.5%.

Characterization of operating conditions of two residential wood combustion appliances

This work presents the main physical characteristics and operating conditions of a fireplace and a stove commonly used in Portugal for domestic heating based on biomass combustion. The fuel used was wood from pine (softwood) and eucalyptus (hardwood). The general trend during the batch combustion of wood logs was characterized by three main periods: i) a first period of fuel heating followed by fuel drying and initial steps of devolatilization without the existence of a visible flame, ii) a second period characterized by devolatilization, ignition, combustion of volatiles and char, during which a vigorous flame is observed, and iii) a third period, mainly identified by the combustion of the char, during which there are only localized small visible flames over the char particles. Each of these periods is characterized by specific fuel consumption rate, flue gas temperature and flue gas composition. The main differences between the wood combustion conditions in the fireplace and in the stove include: i) a lower flue gas temperature in the fireplace, ii) a higher combustion flue gas flow rate in the fireplace, iii) a higher rate of fuel consumption in the stove, and iv) higher CO, total hydrocarbon and particle emission factors during the combustion of wood in the fireplace. Differences between hardwood and softwood combustion were also pointed out.

Effect of low-density polyethylene on smoke emissions from burning of simulated debris piles

Low-density polyethylene (LDPE) plastic is used to keep piled debris from silvicultural activities—activities associated with development and care of forests—dry to enable efficient disposal by burning. The effects of inclusion of LDPE in this manner on smoke emissions are not well known. In a combustion laboratory experiment, 2-kg mixtures of LDPE and manzanita (Arctostaphylos sp.) wood containing 0, 0.25, and 2.5% LDPE by mass were burned. Gaseous and particulate emissions were sampled in real time during the entire flaming, mixed combustion phase—when the flaming and smoldering phases are present at the same time—and during a portion of the smoldering phase. Analysis of variance was used to test significance of modified combustion efficiency (MCE)—the ratio of concentrations of fire-integrated excess CO2 to CO2 plus CO—and LDPE content on measured individual compounds. MCE ranged between 0.983 and 0.993, indicating that combustion was primarily flaming; MCE was seldom significant as a covariate. Of the 195 compounds identified in the smoke emissions, only the emission factor (EF) of 3M-octane showed an increase with increasing LDPE content. Inclusion of LDPE had an effect on EFs of pyrene and fluoranthene, but no statistical evidence of a linear trend was found. Particulate emission factors showed a marginally significant linear relationship with MCE (0.05 < P-value < 0.10). Based on the results of the current and previous studies and literature reviews, the inclusion of small mass proportions of LDPE in piled silvicultural debris does not appear to change the emissions produced when low-moisture-content wood is burned. In general, combustion of wet piles results in lower MCEs and consequently higher levels of emissions.Implications:Current air quality regulations permit the use of burning to dispose of silvicultural piles; however, inclusion of low-density polyethyelene (LDPE) plastic in silvicultural piles can result in a designation of the pile as waste. Waste burning is not permitted in many areas, and there is also concern that inclusion of LDPE leads to toxic air emissions.

Ultrafine particle emission of waste incinerators and comparison to the exposure of urban citizens

On the basis of the growing interest on the impact of airborne particles on human exposure as well as the strong debate in Western countries on the emissions of waste incinerators, this work reviewed existing literature to: (i) show the emission factors of ultrafine particles (particles with a diameter less than 100nm) of waste incinerators; and (ii) assess the contribution of waste incinerators in terms of ultrafine particles to exposure and dose of people living in the surrounding areas of the plants in order to estimate eventual risks. The review identified only a limited number of studies measuring ultrafine particle emissions, and in general they report low particle number concentrations at the stack (the median value was equal to 5.5×103partcm−3), in most cases higher than the outdoor background value. The lowest emissions were achieved by utilization of the bag-house filter which has an overall number-based filtration efficiency higher than 99%. Referring to reference case, the corresponding emission factor is equal to 9.1×1012partmin−1, that is lower than one single high-duty vehicle. Since the higher particle number concentrations found in the most contributing microenvironments to the exposure (indoor home, transportation, urban outdoor), the contribution of the waste incinerators to the daily dose can be considered as negligible.

Physical and chemical characterisation of PM emissions from two ships operating in European Emission Control Areas

Abstract. In this paper emission factors (EFs) for particulate matter (PM) and some sub-components as well as gaseous substances were investigated in two onboard measurement campaigns. Emissions from two 4-stroke main engines were measured under stable-load conditions. The impact of varying engine load on the emissions was investigated on one of the engines, and the impact of fuel quality on the other, where heavy fuel oil (HFO) with sulphur content 1% and 0.5% and marine gas oil (MGO) with sulphur content 0.1% were used. Furthermore, emissions from one auxiliary engine were studied. The measured EFs for PM mass were in the range of 0.3 to 2.7 g kg−1 fuel with the lowest values for emissions from the combustion of MGO, and the highest values for HFO with a sulphur content of 1%. The PM mass size distribution was dominated by particles in accumulation mode. Emission factors for particle numbers EF(PN) in the range of 5 × 1015–1 × 1017 # kg−1 fuel were found, the number concentration was dominated by particles in the ultrafine mode and ca. 2/3 of the particle number were non-volatile. The most abundant component of the PM mass was organic carbon, making up 25–60% of the PM. The measured EFs for organic carbon (OC) were 0.6 g kg−1 fuel for HFO and 0.2 g kg−1 fuel for MGO. Elemental carbon (EC) made up 10–38% of the PM mass, with no significant differences between HFO and MGO fuels. The concentrations of metals on sampled filters were investigated with energy dispersive X-ray fluorescence (EDXRF) and the detected metal elements in exhaust when using HFO was concluded to originate from both the fuel (V, Ni, Fe) and the lubricant (Ca, Zn), while for the case of MGO combustion, most of the metals were concluded to originate from the lubricants. The measured emission factors for sulphate particles, EF (SO2−4), were low, ca. 0.1–0.2 g kg−1 fuel for HFO with 1% sulphur, 0.07–0.09 g kg−1 fuel for HFO with 0.5% sulphur and 0.003–0.006 g kg−1 fuel for MGO. This corresponds to 0.1–0.8% and 0.1–0.6% of fuel S converted to PM sulphate for HFO and MGO, respectively. Scanning transmission electron microscopy (STEM) images of the collected PM showed three different types of particles: relatively pure soot; char and char-mineral particles; and amorphous, probably organic particles containing inorganic impurities. The maps of elements obtained from STEM showed a heterogeneous composition of primary soot particles with respect to the trace metals and sulphur. Temperature-programmed oxidation (TPO) of PM showed higher soot oxidation reactivity compared to automotive diesel soot, PM from the HFO exhaust being more reactive than PM from the MGO exhaust. Oxidative potential measured as the rate of consumption of Dithiothreitol (DTT) was for the first time measured on PM from ship exhaust. The obtained values were between 0.01 and 0.04 nmol DTT min−1 μg−1 PM, which is quite similar to oxidative potentials of PM collected at urban and traffic sites. The data obtained during the experiments add information about emission factors for both gaseous and PM-bound compounds from ship engines using different fuels and under different engine-load conditions. Observed variability of the EFs illustrates uncertainties of these emission factors as a result of influences from fuel and lubricant composition, from differences between individual engines and from the differences in sampling conditions.

Laboratory characterization of PM emissions from combustion of wildland biomass fuels

Particle emissions from open burning of southwestern (SW) and southeastern (SE) U.S. fuel types during 77 controlled laboratory burns are presented. The fuels include SW vegetation types: ceanothus, chamise/scrub oak, coastal sage scrub, California sagebrush, manzanita, maritime chaparral, masticated mesquite, oak savanna, and oak woodland, as well as SE vegetation types: 1 year, 2 year rough, pocosin, chipped understory, understory hardwood, and pine litter. The SW fuels burned at higher modified combustion efficiency (MCE) than the SE fuels resulting in lower particulate matter mass emission factor. Particle mass distributions for six fuels and particle number emission for all fuels are reported. Excellent mass closure (slope = 1.00,r2 = 0.94) between ions, metals, and carbon with total weight was obtained. Organic carbon emission factors inversely correlated (R2 = 0.72) with average MCE, while elemental carbon (EC) had little correlation with average MCE (R2 = 0.10). The EC/total carbon ratio sharply increased with MCE for MCEs exceeding 0.94. The average levoglucosan and total polycyclic aromatic hydrocarbon (PAH) emissions factors ranged from 25 to 1272 mg/kg fuel and 1.8 to 11.3 mg/kg fuel, respectively. No correlation between average MCE and emissions of PAHs/levoglucosan was found. Additionally, PAH diagnostic ratios were observed to be poor indicators of biomass burning. Large fuel type and regional dependency were observed in the emission rates of ammonium, nitrate, chloride, sodium, and potassium.

Redox activity and PAH content in size-classified nanoparticles emitted by a diesel engine fuelled with biodiesel and diesel blends

Diesel and biodiesel emissions are important sources of ambient air pollution. Therefore, the influence of using different blending percentages of biodiesel to diesel as fuel on redox activity, particulate matter (PM) and polycyclic aromatic hydrocarbons (PAH) emission profiles, and the corresponding carcinogenicity index (BaPE) size distributions are not well known. In this way, the present work aims to investigate the effect of diesel/biodiesel blends on the physical, chemical, and toxicological properties of diesel engine exhaust at low condition, through the study of the changes in size-distribution and emission factors of PAH associated to PM, corresponding carcinogenicity index (BaPE) size distributions and PM redox activity. For that, particle emissions from commercial petroleum-based diesel with 4% of soy biodiesel (B4), a biodiesel blend of 25% and 50% (B25 and B50) and also pure biodiesel (B100) were measured on a steady-state dynamometer in a test using a diesel engine at low load. Size-fractionated PM samples were collected by using the NanoMOUDI impactor and analyzed for the 16 priority PAH by HPLC–fluorescence detector. In addition, PM2.5 samples were collected and analyzed for redox activity by DTT assay. PM was distributed in all sizes, while PAH size distribution was found in higher levels in the accumulation mode (30nm<Dp<2.5μm). Total PAH emission factors (ng kgfuel-1) for B4, B25, B50 and B100 were: 237,111,182 and 319ng kgfuel-1, respectively. Individual PAH emission factors showed that PAH containing four or more rings (MW>202) such as BBF, BAA, PYR and BGP were the main PAH emitted by the four studied fuels. The percentage reductions of individual PAH emission factors for the blend fuels in comparison with B4 were 37% and 22% for B25 and B50, respectively, and an increase around 31% for B100. On the other hand it was observed increase in redox activity for B25, B50 and B100 when compared to B4. In general, the results from our study suggest that emissions from pure waste cooking biodiesel may not be the better fuel choice in terms of PM, PAH and BaPE particle size distribution and emission factors as well as redox activity. However, B25 and B50 blends presented some improvements in terms of PM, HPA, BaPE size distribution and redox activity of engine exhaust in comparison to B4. This suggests that addition of low percentages of biodiesel to diesel promotes benefices in both environmental and human health concerns.

Distribution, sources and potential risk of HCH and DDT in soils from a typical alluvial plain of the Yangtze River Delta region, China

Spatial distribution, sources and potential health risks of organochlorine pesticides (OCPs), including hexachlorocyclohexane (HCH) and dichlorodiphenyltrichloroethane (DDT), in surface soils (n = 544) collected from a typical alluvial plain of the Yangtze River Delta region, China, were elucidated. Concentrations of ΣHCH and ΣDDT in soils ranged from less than the limit of detection (<LOD) to 99.0 ng g(-1), dry weight (dw) (mean 3.23 ng g(-1) dw) and <LOD to 600 ng g(-1) dw (mean 88.8 ng g(-1) dw), respectively. Historical applications of HCH and DDT were the major sources of the residue in soils. HCH was mainly distributed in Anthrosols in the southern part of the watershed, while DDT was mainly distributed in Cambosols in the northern part. The 95 % cumulative probability incremental lifetime cancer risks (ILCRs) of different age groups such as children, youths, and adults all exceeded the acceptable risk level of 10(-6) recommended by USEPA for carcinogenic chemicals. The spatial distributions of ∑ILCRs were consistent with concentrations of OCPs in soils, while they were slight different for the different age groups. Adult females had the greatest risk of OCPs in soils, followed by children, while youths had the least risk. The ingestion of OCPs in soils was the more important route of exposure compared with dermal and inhalation exposures. The concentration of OCPs in soils, the particulate emission factor, the fraction of dermal exposure ratio, and the soil ingestion rate were the major contributing variables to total ILCRs according to sensitivity analyses.

Fugitive particulate emission factors for dry fly ash disposal

Dry fly ash disposal involves dropping ash from a truck and the movement of a heavy grader or similar vehicle across the ash surface. These operations are known to produce fugitive particulate emissions that are not readily quantifiable using standard emission measurement techniques. However, there are numerous situations--such as applying for a source air permit--that require these emissions be quantified. Engineers traditionally use emission factors (EFs) derived from measurements of related processes to estimate fly ash disposal emissions. This study near a dry fly ash disposal site using state-of-the-art particulate monitoring equipment examines for the first time fugitive emissions specific to fly ash handling at an active disposal site. The study measured hourly airborne mass concentrations for particles smaller than 2.5 μm (PM2.5) and 10 μm (PM10) along with meteorological conditions and atmospheric turbidity at high temporal resolution to characterize and quantify fugitive fly ash emissions. Fugitive fly ash transport and dispersion were computed using the on-site meteorological data and a regulatory air pollutant dispersion model (AERMOD). Model outputs coupled with ambient measurements yielded fugitive fly ash EFs that averaged 96 g Mg−1 (of ash processed) for the PMc fraction (=PM10 - PM2.5) and 18 g Mg−1 for PM2.5. Median EFs were much lower due to the strongly skewed shape of the derived EF distributions. Fugitive EFs from nearby unpaved roads were also characterized. Our primary finding is that EFs for dry fly ash disposal are considerably less than EFs derived using US Environmental Protection Agency AP-42 Emissions Handbook formulations for generic aggregate materials. This appears to be due to a large difference (a factor of 10+) between fugitive vehicular EFs estimated using the AP-42 formulation for vehicles driving on industrial roads (in this case, heavy slow-moving grading equipment) and EFs derived by the current study. Implications Fugitive fly ash emission factors (EFs) derived by this study contribute to the small existing knowledge base for a type of pollutant that will become increasingly important as ambient particulate standards become tighter. In areas that are not in attainment with standards, realistic EFs can be used for compliance modeling and can help identify which classes of sources are best targeted to achieve desired air quality levels. In addition, understanding the natural variability in fugitive fly ash emissions can suggest methods that are most likely to be successful in controlling fugitive emissions related to dry fly ash storage.

Heated submicron particle fluxes using an optical particle counter in urban environment

Abstract. From May 2008 to March 2009 aerosol emissions were measured using the eddy covariance method covering the size range 0.25 to 2.5 μm diameter (Dp) from a 105 m tower, in central Stockholm, Sweden. Supporting chemical aerosol data were collected at roof and street level. Results show that the inorganic fraction of sulfate, nitrate, ammonium and sea salt accounts for approximately 15% of the total aerosol mass &lt; 1 μm Dp (PM1) with water soluble soil contributing 11% and water insoluble soil 47%. Carbonaceous compounds were at the most 27% of PM1 mass. It was found that heating the air from the tower to 200 °C resulted in the loss of approximately 60% of the aerosol volume at 0.25 μm Dp whereas only 40% of the aerosol volume was removed at 0.6 μm Dp. Further heating to 300 °C caused very little additional losses &lt;0.6 μm Dp. The chemical analysis did not include carbonaceous compounds, but based on the difference between the total mass concentration and the sum of the analyzed non-carbonaceous materials, it can be assumed that the non-volatile particulate material (heated to 300 °C) consists mainly of carbonaceous compounds, including elemental carbon. Furthermore, it was found that the non-volatile particle fraction &lt;0.6 μm Dp correlated (r2 = 0.4) with the BC concentration at roof level in the city, supporting the assumption that the non-volatile material consists of carbonaceous compounds. The average diurnal cycles of the BC emissions from road traffic (as inferred from the ratio of the incremental concentrations of nitrogen oxides (NOx) and BC measured on a densely trafficked street) and the fluxes of non-volatile material at tower level are in close agreement, suggesting a traffic source of BC. We have estimated the emission factors (EFs) for non-volatile particles &lt;0.6 μm Dp to be 2.4 ± 1.4 mg veh−1 km−1 based on either CO2 fluxes or traffic activity data. Light (LDV) and heavy duty vehicle (HDV) EFs were estimated using multiple linear regression and reveal that for non-volatile particulate matter in the 0.25 to 0.6 μm Dp range, the EFHDV is approximately twice as high as the EFLDV, the difference not being statistically significant.