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Human health risk characterization of petroleum coke calcining facility emissions
Regulatory Toxicology and Pharmacology 73 (2015) 706e711
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Human health risk characterization of petroleum coke calcining facility emissions Davinderjit Singh, Giffe T. Johnson*, Raymond D. Harbison Center for Environmental and Occupational Risk Analysis and Management, University of South Florida, Tampa, FL, 33612, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 10 February 2015 Received in revised form 6 October 2015 Accepted 25 October 2015 Available online xxx
Calcining processes including handling and storage of raw petroleum coke may result in Particulate Matter (PM) and gaseous emissions. Concerns have been raised over the potential association between particulate and aerosol pollution and adverse respiratory health effects including decrements in lung function. This risk characterization evaluated the exposure concentrations of ambient air pollutants including PM10 and gaseous pollutants from a petroleum coke calciner facility. The ambient air pollutant levels were collected through monitors installed at multiple locations in the vicinity of the facility. The measured and modeled particulate levels in ambient air from the calciner facility were compared to standards protective of public health. The results indicated that exposure levels were, on occasions at sites farther from the facility, higher than the public health limit of 150 mg/m3 24-h average for PM10. However, the carbon fraction demonstrated that the contribution from the calciner facility was de minimis. Exposure levels of the modeled SO2, CO, NOx and PM10 concentrations were also below public health air quality standards. These results demonstrate that emissions from calcining processes involving petroleum coke, at facilities that are well controlled, are below regulatory standards and are not expected to produce a public health risk. © 2015 Elsevier Inc. All rights reserved.
Keywords: Calciner facility Petrochemical industry Calcined coke Particulate matter Black carbon
1. Introduction Calcined coke is a high quality carbon material produced by calcining green petroleum coke. Calcining is the process of heating green petroleum coke in a kiln to remove excess moisture, extract all remaining hydrocarbons and modify the crystalline structure of the coke, resulting in a denser more electrically conductive product. The temperatures in the kiln during the calcining process can range from 1200 C to 1450 C. The final product, calcined coke, is primarily used to make carbon anodes for the aluminum industry and recarburizing agent for other industries such as the steel industry. Green coke is basically an inert substance and the health hazards assigned to green coke are mostly associated with Particulate Matter (PM) exposures, which can be produced in the occupational setting during the process of calcination (McKee et al., 2014). If not appropriately controlled, this process could lead to the excess production of particulate emissions from either handling or storing
* Corresponding author. Center for Environmental/Occupational Risk Analysis and Management, College of Public Health, University of South Florida, 13201 Bruce B Downs Blvd., MDC 56, Tampa, FL, 33612, USA. E-mail address: [email protected] (G.T. Johnson). http://dx.doi.org/10.1016/j.yrtph.2015.10.025 0273-2300/© 2015 Elsevier Inc. All rights reserved.
of raw coke, or from the stack emissions during the production of calcined coke. Though industries that store, transfer or process petroleum products are broadly described as “petroleum industries”, the coke calcining industry is unique in that it can and is a standalone process distinct from other petroleum industries in producing a different profile of air emissions compared to what could be termed “petrochemical” industries, such as oil refineries. Unlike calcined coke production, petroleum oil refineries produce a variety of products and each product has a varied level of hazard potential (Clark et al., 2013). Calcining facilities process green coke to produce the final product, calcined coke, which substantially limits the constituents and quantity of emissions. The high temperatures required for the process of calcination and the further processing of the emissions gases in a combustion chamber, sometimes referred to as a pyro scrubber, provides sufficient heat and retention that destroys most of the emissions from this process for volatile organic compounds and combustible particles (CONCAWE, 1993). Though calcined coke has shown low hazard potential in human populations due to low volatile content, there remains some public health concern regarding the emissions from these facilities. The purpose of this research is to evaluate the emissions of a calcining
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facility engaged in the handling and storage of green coke, as well as in the calcining process itself, and characterize the presence of any public health risks associated with these emissions. Particular emphasis is placed on the particulate matter generated, the resultant ambient air quality, and the risks associated with these levels of particulate matter. 2. Methods and materials The calcining facility evaluated in this study has the potential to produce approximately 444,000 short tons of calcined coke product per year. The calcining facility is located on the west side of a shipping canal within a port in eastern Argentina. The long and narrow property containing the facility abuts the west side of the shipping canal and has a south-southwest to north-northeast orientation. From a turning basin at its south-southwestern terminus, the shipping canal extends north-northeast to the city of Rio de la Plata. Meteorological data were taken into account in evaluating emissions. The general direction of the air flowing over the weather station located in calcining facility is towards urban areas, and previously passes over the River Plate (influenced by its interaction with the water) and then, over a narrow surface on the shore, between the river and the weather station. The air towards the monitors flows previously over urban areas. Proximate to the area in which the calciner resides is an oil refinery that supplies the green coke feed, industrial ports, and a large, populated community. There are multiple sources of pollution in the area including the refinery, sand and gravel storage and transport, and other industrial activity. Substantial sources of non-industrial pollution exists in the local area including unpaved roads, non-municipal garbage burning, fuel combustion from automobiles and heating, as well as a large number of wood burning stoves in homes for cooking. The emissions constituents evaluated included PM10 and the gaseous emissions of CO, SO2, and NOx. Volatile Organic Compounds (VOC's) are a major byproduct of the petroleum refinery industry and concentrations of approximately 15% VOC's are found in green coke as a result of the coking process. However, these VOC's and other volatiles present in the green coke are efficiently combusted and destroyed because of the high temperatures during the calcining process and their presence is not detectable in calcining emissions; as a result, VOC's were not included in this analysis (Cetin et al., 2003; Lin et al., 2004; Hassan, 2005). Both measured and modeled emissions from the kiln stacks, as well as actual ambient air monitoring were conducted for various pollutants. Ambient air quality PM10 monitoring data was collected continuously by three tapered element oscillating microbalance (TEOM 1400) monitors, and one multi-angle absorption photometer (MAAP) monitor at various locations surrounding the facility. Air data collection for year 2009 was conducted by the Center for Environmental Investigations (CIMA by its Spanish acronym). For the period of 2010 through the second quarter 2013, air data was collected by the facility under the direct supervision of The Provincial Agency for Sustainable Development (which acts as the regulatory agency and is known as OPDS by its Spanish acronym). For the third quarter 2013 through second quarter 2014, air data was collected by the Geochronology and Isotopic Institute (INGEIS by its Spanish acronym). Both CIMA and INGEIS are scientific research centers and are considered independent third party experts in this activity. As part of the data collection activities, CIMA utilized three TEOM 1400 monitors, two HI-Vol PM10 monitors, and a MAAP monitor to measure the ambient air quality at various locations surrounding the calcining facility. The TEOM 1400s and MAAP monitors continued to be used for PM10 monitoring by the calcining facility at various locations from 2010 through the first half of 2013.
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INGEIS continued to use the same monitors at various locations around the facility for the second half of 2013 to the present. The locations and distance of these monitors have varied over time with the nearest location just at the entrance of the facility and the furthest at 1190 m from the calcining facility. TEOM monitors measure continuous ambient air quality values, while Hi-Vol samplers are based on 24-h samples that are typically taken on 3 or 6 day intervals. The estimated contribution from other sources of particulate emissions in the area was determined by wind trajectory analysis to estimate the emissions that contributed to PM10 concentrations. A wind trajectory analysis was performed using 5min meteorological data and coincident TEOM data to estimate the potential for the calcining plant to contribute to the reported Hi-Vol concentration. This analysis was performed using wind direction data from the facility meteorological tower that were coincident in time with the 24-h measured data collected at the monitors. The comparison was performed for 5-min average data since the TEOM PM10 data are available over 5-min intervals. If the wind was blowing in a direction such that a parcel of air would traverse the facility site and be transported to the specific monitor site, then the potential for percent contribution of particulate from the facility was identified. The MAAP monitor measures the black carbon concentration of the PM10 size particles. The entirety of particulate emissions from the calciner facility is black carbon since green petroleum coke and calcined coke are black carbon. Black carbon is an indicator of the amount of carbon related material such as calcined coke and raw petcoke that is present in the particulate (PM10) sample collected at the TEOM and can distinguish between emissions potentially from the calcining facility and non-calcining emissions. However, some black carbon measured at monitoring sites could also be attributed to diesel combustion or debris burning. The black carbon concentrations being measured by the MAAP monitor would, for the most part, represent emissions from the calciner facility since it is the largest source of black carbon in the area. The facility also conducted periodic stack testing to determine PM, NOx, CO and SO2 emission rates from the two kilns from 2011 through the third quarter of 2014. Particle size distribution was conducted on the measured total particulate matter to define the portion of PM10 in the stack gases. The kiln stack samples were collected using the EPA Conditional Test Method (CTM) 022/030. Per the CTM, a continuous stream of stack gas is pulled into the analyzer for a set period of time to determine the concentrations. The rates of emissions were calculated from the resulting concentrations and the volumetric flow. The rates of emissions of the various pollutants were then input into an air dispersion model along with 5 years of meteorological data. The USEPA AERMOD model was used for these assessments. AERMOD is a steady state Gaussian dispersion model developed by the USEPA and American Meteorological Society (AMS) and represents the current state of the art modeling (EPA, 2004). The modeling was performed in general accordance of the Argentinean modeling requirements of Stage III of Resolution Nr. 242/97 and using techniques that would be acceptable to EPA for the air quality assessment of a project located within the United States. The EPA's AERMOD model (Version 07026) was used with hourly meteorological data to predict PM emission impacts at ground-level receptor locations for 24-h averaging periods. AERMOD is a Gaussian plume model that calculates impacts at each receptor for each hour in the meteorological data set (typically a full year of data) and it provides maximum ground-level concentrations for point sources such as the two Kiln stacks. It also predicts concentrations in the cavity zone and uses Building Profile Input Program (BPIP) data to simulate the influence of proximate structures to estimate the
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downwash effects. The results of the modeling were compared to the ambient air quality sampling efforts discussed above as well as local and USEPA ambient air quality standards. The gaseous pollutants were modeled using AERMOD model to calculate 3-h and 1h concentrations. 1-h concentrations were compared with the USEPA and Argentina standards. The standard concentration for PM10 for 24-h averaging period is 150 mg/m3 not to be exceeded once per year averaged over 3 years (also the Argentina standard), and an annual average of 50 mg/m3. This annual standard was revoked by EPA effective December 17, 2006 due to lack of evidence linking health problems to long-term PM10 exposure. This standard is still used in the Argentina regulations. 3. Results Table 1 shows the measured 24-h ambient air quality concentrations for PM10 of Hi-Vol and TEOM samplers for the year 2009. As indicated before, the TEOM monitors and Hi-Vol monitors were both installed and operated by CIMA. TEOM monitors heat up the filter so that the semi-volatile organic mass is driven off. Hi-Vol samplers capture both semi-volatile mass (aerosol) as well as the particulate mass. As a result, the concentrations recorded by a HiVol monitor can sometimes be higher than the concentration obtained by the TEOM monitors. Table 2 analyzes the concentrations of PM10 from Hi-Vol and TEOM samplers as measured in Table 1. Typically, the semi-volatiles that are driven off from the TEOM are ammonia nitrates (Charron and Harrison, 2004). In a populated area the source of ammonia nitrates would most likely be associated with traffic. There are no ammonia nitrates present in petroleum coke so it could not be attributed to the calcining facility. Therefore, the higher concentrations associated with the Hi-Vol monitors in this study are most likely associated with traffic rather than the calcining facility. In most cases, the observed TEOM measured concentrations were substantially lower than the Hi-Vol measured concentrations indicating that traffic is a large contributor of particulate matter in the area. Based on an evaluation of the wind direction data and measured concentrations, it was concluded that when the wind direction is mainly blowing from the facility to the monitor, the TEOM concentrations are well below the 24-h standard of 150 mg per cubic meter of air (mg/m3). Table 3 shows the PM10 concentrations as measured around the calcining facility at various locations from the year 2009 through the 3rd quarter of 2014. The measurements were taken with three TEOM 1400 monitors at distances ranging from the entrance of the facility out to 1190 m from the calcining facility. Table 4 shows the number of measured PM10 values that were over the 24-h standard of 150 mg/m3. The vast majority of 24-h concentrations are well below the
country standard and the United States Environmental Protection Agency (USEPA) 24-h concentration of 150 mg/m3 not to be exceeded more than once per year, on average, over 3 years. The quarters showing average 24-h concentrations in excess of the standard were mainly associated with the monitor located over 850 m away from the facility. Given the distances of the monitors from the facility and as supported by the modeled results, the higher concentrations are most likely the result of local influences such as burning of garbage, stove cooking or fugitives from more closely located industrial facilities. The 24-h annual averages for TEOMs 3, 4, and 5, were 34.61 mg/ m3, 41.66 mg/m3, and 38.02 mg/m3, respectively. All of the annual averages are below the local annual PM10 standard of 50 mg/m3. The reported maximum annual averages for TEOM 3 and TEOM 4 are in years which fall below traditionally accepted data collection rates (80%). The maximum annual average for TEOM 3 and TEOM 4 for years that exceeded the data collection rate of 80% was 32.31 and 32.52 mg/m3, respectively. Given that the monitors reported concentrations were below the annual average standard, which have been developed to protect public health, the contribution of the calciner facility to the long term concentrations of PM10 in the area are de minimis. Fig. 1 shows the average concentrations of the ambient black carbon, which are associated with the calcining facility fugitive and stack emissions. The carbon concentrations are a small fraction of the overall concentrations seen in Table 3 for the ambient PM10 concentrations for TEOM 3, 4 and 5 for the same time period. It can be concluded that the carbon concentration represents the PM10 contribution from the calciner facility. Given the overall low measured concentrations, and the small fraction that represents contributions from the calcining facility, the overall contribution of PM10 from the calcining facility is de minimis. It should be noted that the average monthly black carbon concentrations presented in Fig. 1 correspond well with the modeled concentration for PM10. The maximum black carbon concentrations in Fig. 1 are higher than the modeled PM10 concentration but the concentrations from the monitors also include black carbon from other sources such as diesel fuel combustion (i.e. diesel fired trucks on the streets). The local community had no measured exceedance of 150 mg/m3 PM10 for years 2008 and 2014, all other exceedances are reported in Table 4. During the periods of 2008e2010 and 2012e2014, TEOM 3, TEOM 4, and TEOM 5 did not exceed the standard of 1 measure over 150 mg/m3 PM10 per year averaged over 3 years. During the periods 2009e2011, 2010e2012, and 2011e2013 only TEOM 4 exceeded the standard with 6 exceedances during each of these 3 year periods. However, for each of these exceedances, the carbon fraction (which represents the maximal potential contribution of the calcining facility) was less than 10 mg/m3 or less than 7% of the total PM10 measurement. While the community may not have met their PM10
Table 1 24-h PM10 concentrations measured by Hi-Vol and TEOM monitors in year 2009 Hi-Vol
mg/m3 mg/m3 %
%
mg/m3 mg/m3 %
%
Monitor 164 m from facility (Site A)
6/1/2009 12/1/2009 18/01/2009 24/01/2009 30/01/2009 5/2/2009 11/2/2009 18/02/2009 24/02/2009
219 124 115 145 19 50 55 48 65
62 25 2 52 36 96 30 43 57
167 122 71 94 24 46 56 24 42
51 67 6 77 54 97 30 87 71
TEOM
92 79 56 88 30 39 62 53 51
Calcining facility contribution
38 75 98 48 64 4 70 57 43
Monitor 485 m from facility (Site B)
6/1/2009 12/1/2009 18/01/2009 24/01/2009 30/01/2009 5/2/2009 11/2/2009 18/02/2009 24/02/2009
TEOM
75 49 38 46 25 30 42 24 34
Calcining facility contribution
Non-calcining facility contribution
Non-calcining facility contribution
Hi-Vol
49 33 94 23 46 3 70 13 29
D. Singh et al. / Regulatory Toxicology and Pharmacology 73 (2015) 706e711
709
Table 2 Analyses of 24-h PM10 concentrations measured by Hi-Vol and TEOM in year 2009. Site A
Hi-Vol mg/m3
TEOM mg/m3
Site B
Hi-Vol mg/m3
TEOM mg/m3
Min Max Median Half of Max Sqrt
19 219 65 109.5 14.8
30 92 56 46 9.5
Min Max Median Half of Max Sqrt
24 167 56 83.5 12.9
24 75 38 37.5 8.7
Table 3 Monthly 24-h average of PM10 for TEOM 3, 4, and 5 for time period 1st quarter 2009 through 3rd quarter 2014.
10
TEOM 5
2013
2014
Concentration in mg/m.3.
goals consistently over these periods at the TEOM 4 monitor, the source of these exceedances were not calcining operations as demonstrated by the black carbon PM10 measurements. The maximum potential emissions for all constituents from the facility were modeled using onsite meteorological data. The emission rates from stack test data for CO, NOx, SO2 and PM10 were scaled up to reflect the maximum production of the facility. The AERMOD dispersion model was used to determine offsite ambient concentrations. As presented in Table 5, all ambient concentrations are well below local standards and EPA NAAQS levels. The modeling demonstrates that any potential contribution from the stack gases to the overall ambient concentrations in the area would be small and with respect to CO, NOx and PM10 would contribute less than
2
Jun-14
0 Oct-14
2012
4
Feb-14
2011
6
Jun-13
2010
8
Oct-13
81.7 173.8 74.6 78.5 75.4 53.3 60.9 95.7 83.9 111.6 118.2 147.7 67.5 107.5 140 88.3 131.4 125.4 172 60.6 36.2 54.6 45.5
Feb-13
Max
5.8 5.7 3.5 9.1 7.1 6.7 2.2 8.7 9.1 7.3 7.1 6.9 11 5.9 6.8 5.8 10.7 3.9 6.7 6.5 9.4 4 1.4
Jun-12
Min
26.2 24.4 22 24.3 22.8 19.2 20.8 26.6 21.7 26.1 39.3 39.2 30.1 37 31.2 33.3 36.3 45.3 34.5 24.7 18.9 21.3 20.7
Oct-12
Avg
88.4 168.2 101.4 63.5 115.1 139.9 158.1 85 102.8 195.1 156.5 155.1 70 81 164.5 122.2 61.2 81.7 90 182.9 75.3 44.4 44.5
Feb-12
Max
12.2 6.5 5 12.8 12.7 8.2 5.3 16.4 6.1 11.6 10.5 6.7 10 5.2 6.9 5.5 8.1 6.7 3.9 5.5 6.2 2.2 7.1
Jun-11
Min
37.5 36.3 36.2 34.2 41.5 54 40.1 40.3 39.4 56.5 46.7 28.3 24.9 22.5 33 33.2 30.8 24.9 27.8 28.2 20 15.5 15.8
Oct-11
Avg
103.6 177.2 124.3 68.3 57.4 80 92.7 86.9 53.2 210.3 133.6 53.4 65.8 70.6 61.1 88.8 50.8 65.8 79 58.1 48.3 71.9 105.4
Feb-11
Max
2.4 6.3 7.8 7.6 7.6 6.1 3.5 11.7 11.4 9.2 9.4 12.1 10.1 6.8 5.4 6.8 5 7.3 8.6 8.2 6.5 10.5 13.2
Jun-10
Min
28.9 37.6 26.3 23.8 23 26.1 28.5 27.7 23.9 39.9 38.9 28.2 26.6 30.7 25.5 25 21.5 28.3 26.2 25.5 20.2 29.1 29.9
Oct-10
Avg
1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd
Feb-10
Quarter
2009
Jun-09
Year
Oct-09
TEOM 4
Feb-09
TEOM 3
Concentra on μg/m3
Period
12
X = Average concentraƟon Fig. 1. Black carbon monthly average concentrations measured by multi-angle absorption photometer.
20% of the standard. Stack emissions concentrations of NOx, CO and SO2 were measured from the two kilns at the calcining facility on a monthly basis. The measured stack gas emissions were below the emissions values used in the AERMOD modeling presented in Table 5. 4. Discussion The results of monitored and modeled emissions concentrations from the coke calcining facility evaluated in this study demonstrate that normal and maximum facility operation emissions produce ambient concentrations that are below regulatory standards designed to protect public health. This includes emissions from the actual calcining process of green coke as well as the actual fugitive emissions from the handling and storage of green coke at the facility. Due to the temperatures achieved during calcining, the emissions of VOCs from calcining facilities are almost non-existent
Table 4 PM10 values exceeding the level of 150 mg/m3. TEOM
Year
Month
Day
24-HR Ave (mg/m3)
Carbon fraction
Percent of total
3 3 4 4 4 4 4 4 4 4 5 5
2009 2011 2009 2010 2011 2011 2011 2011 2012 2013 2009 2013
4 6 4 8 4 5 7 11 7 12 4 9
24 13 24 10 15 31 12 22 7 30 24 19
177.24 210.33 168.20 158.15 195.05 160.94 156.53 155.07 164.47 182.90 173.80 171.95
3.620 3.145 3.620 9.512 3.068 2.843 3.746 2.091 5.882 3.611 3.620 3.621
2.04 1.50 2.15 6.01 1.57 1.77 2.39 1.35 3.58 1.97 2.08 2.11
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D. Singh et al. / Regulatory Toxicology and Pharmacology 73 (2015) 706e711 Table 5 Modeled ambient air concentrations. Pollutant
Averaging period
Modeled concentration (mg/m3)
Standard (mg/m3)
NOx
1h Annual 1h 8h 3h 24 h Annual 24 h Annual
72.2 2.15 106.1 79.2 365.4 215.5 11.8 2.8 0.04
400 100 40,000 10,000 1300 365 80 150 50
CO
SOx PM10
when compared to the nearby petrochemical facilities. The consistency in the overall Hi-Vol/TEOM data set among sites A and B suggests that the difference between Hi-Vol and TEOM measurements is attributable to prevailing pollution conditions in the area. Hi-Vol data almost always has a higher concentration than the TEOM concentrations. This discrepancy results from the design of the TEOMs that includes heating the TEOM samples to drive off moisture such that the mass is only particulate matter, with no volatiles or semi-volatiles. The difference between Hi-Vol and TEOM measurements appears to be linked to the presence of semivolatile compounds and nitrate compounds in the atmosphere that are collected by the Hi-Vol but are not collected by the TEOM. Calcined coke does not contain any volatile compounds since they are destroyed in the production process. This indicates that all samples exceeding the standard contained large amounts of particulates from sources other than the calcining facility. For the calcining facility, the highest measured PM10 annual average concentrations for 2009 through 2013 at TEOM 3, 4 and 5 locations were 34.61, 41.66, and 38.02 mg/m3, respectively, which are below the local Argentina standard of 50 mg/m3 annual average. During the periods 2009e2011, 2010e2012, and 2011e2013 only TEOM 4 exceeded the 24 h standard of 150 mg/m3 not to be exceeded more than once per year, on average, over 3 years with 6 exceedances during each of these 3 year periods. However, for each of these exceedances, the carbon fraction (which represents the maximal potential contribution of the calcining facility) was less than 10 mg/ m3 or less than 7% of the total PM10 measurement, demonstrating that calcining operations were not the cause of those exceedances. Though the monitored 24-h concentration does exceed the local and USEPA NAAQS concentration level of 150 mg/m3 for one monitor, it occurs at a location that is over 850 m away from the site, proximate to other sources of particulate emissions. It can be concluded that the fugitive emissions contribution from the calciner facility would be de minimis to the overall concentration levels as compared to nearby facilities and activities. The black carbon concentrations measured by the MAAP further validate that the overall PM10 contribution from the calciner facility during these events would most likely be small. The modeled results for maximum production at the facility shows the concentrations would be well below 20% of any of the regulatory standards except for the SO2 24-h standard where it would be slightly less than the 60% of the standard. An evaluation of the epidemiological literature regarding potential associations between exposures similar to those found at calcining facilities and respiratory illnesses demonstrates that contemporary epidemiological evidence does not support an association between emissions from the calcining facility and adverse health effects. Various studies have examined the effect of the PM on human health. These studies have included both acute as well as chronic effects on respiratory and cardiovascular health of the exposed populations (Samet et al., 2000; Katsouyanni et al., 1996; Dominici et al., 2006). Both PM and gaseous pollutants from combustion and
mobile sources have been evaluated for their potential to produce adverse cardiovascular and respiratory health effects. Mortality studies have assessed the number of deaths occurring during various time periods and have attempted to draw inferences on the exposure-associated mortality. Morbidity studies have attempted to correlate hospital admission rates, symptoms, disease diagnoses, and specific measurements of pulmonary function. However, none of these observational studies have identified an exposure response characterization that demonstrates increased disease rates at levels below current regulatory limits or an exposure response that can be used to inform risk assessment. These studies typically classify subjects as ‘exposed’ or ‘unexposed’ or broadly assign subjects an exposure value based on monitoring values that are not specific to their location. Without knowing specific exposure ranges for subjects and the associated rates of disease that occur within those ranges, it is not possible to use this type of data to characterize risk for other populations with similar exposure. As well, none of these studies have produced data that would inform a risk assessor that any increased risk occurs at or below regulatory limits designed to be protective of public health. Compared to the emissions values reported in this study, observational studies have not produced data that suggest the emissions from this calcining facility produces any public health risk. Other studies have attempted to examine the impact of industrial complexes that include petrochemical refineries and calcining facilities on the respiratory status of populations residing in surrounding areas, primarily that of children (Rusconi et al., 2011; White et al., 2009; Smargiassi et al., 2009; Wichmann et al., 2009). Although the calcining process is not the same as petroleum refinery operations and produces fewer emissions in both quantity and in composition than refining, coke calcining facilities have often been included as a potential contributor to area emissions. Of these studies, some authors suggested a potential association between particulate exposures and altered respiratory function, despite the fact that none of these studies were able to identify specific emissions from calcining as the cause of the abnormal pulmonary function changes. Exposure claims are misleading when one monitoring location is used as a source for ambient air measurements that have multiple sources. As well, a study conducted by Goldstein and Landovitz (1977) warned that using one air monitoring location is unreliable in determining the air quality of a large metropolitan area. Smargiassi et al. (2009) attempted to study the effect of point source SO2 emissions on asthma hospitalizations near petroleum refineries in Montreal, Canada. Though the study concluded that short term exposure to SO2 led to higher rates of asthma hospitalization, the exposures assigned to subjects (children aged 2e4) were poorly characterized. It was noted that the majority of exposures in these children were indoor air contaminants, and these were the likely cause of increased hospitalizations. The study failed to characterize a threshold of SO2, above which, these acute episodes were demonstrated to occur, and as well, the authors failed to demonstrate that the exposures were specific to the industrial
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sources cited in the study. As the authors of this study did not know individual subjects exposure levels at the time of acute asthmatic episodes, it is not possible to draw conclusions regarding the potential impact of these suspected exposures. White et al. (2009) studied the effect of proximity to a petroleum refinery and the development of asthma symptoms. The study reported that prevalence of asthma symptoms was higher in children due to presence of the petroleum refinery in the area. However, case classification in this study was determined by survey and no actual diagnosis of asthma or asthma symptoms were recorded in this study. Further, it is unknown if any of the subjects reporting more symptoms in this study actually experienced any exposure from local refinery emissions. Similarly, Rusconi et al. (2011) attempted to evaluate the effect of oil refinery emissions on asthma symptoms and pulmonary function in children and adults residing in the proximate areas. The study reported that the population residing in the areas proximate to refinery facilities had decreased lung function with higher rates of bronchial inflammation as compared to the control population. As in White et al. (2009) however, case classification was based solely on selfreporting of symptoms and the individual exposure levels of subjects were unknown, making it impossible to determine if ‘cases’ actually experienced higher exposures than ‘controls’. There is bias inherent to using questionnaires in studies evaluating health status, especially in areas widely assumed by the general public to have higher pollution levels, which obscures the reliability of the outcome. Wichmann et al. (2009) attempted to characterize the role of the petrochemical industry as a contributing factor in exacerbations of asthma and other respiratory symptoms in children. The authors reported that subjects in closer proximity to the local industrial complexes had ‘higher’ rates of respiratory symptoms and decreased pulmonary function. However, the authors were not able to identify specific sources of the exposures reported in this study or provide individual exposure estimates that would allow for an exposure response characterization to be made. In the region described in this study, various non-industrial sources of pollutants are likely to produce the same type of PM and gaseous pollutants reported including motor vehicles, unpaved roads, and fuel combustion at homes such as wood burning stoves and cooking. The pollutants emitted from these non-industrial sources may differ in amount and composition and thus may contribute differently to potential adverse health effects. When compared to the results of the current study, it is clear that the emissions contribution from a calcining facility would be de minimis compared to other emission sources indicated to be present in Wichmann et al., 2009. As well, in their discussion of health outcomes, the authors in this study classified subjects within the normal range of FVC and FEV1 as having pulmonary impairment, when in fact, no cases of pulmonary impairment were identified among any of the exposure groups using the American Thoracic Society criteria. Using this criterion, FVC and FEV1 values less than 80 percent predicted are classified as abnormal lung function (American Thoracic Society, 1991). No cases with abnormal lung function were reported in the Wichmann et al., 2009 study. Their conclusions are misleading and based on an irresponsible analysis of pulmonary function data. 5. Conclusions The results from the current study demonstrate that the emissions from a calcining facility as described are well below regulatory levels that are protective of public health and do not make a substantial contribution to related emissions in the local community. Therefore it would be appropriate to assign coke calcining facilities, such as the facility in our study when operated and
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maintained with similar control measures, as a de minimis contributor when evaluating the effects of community air emissions on community health. In addition, contemporary epidemiological evidence does not demonstrate an association between calciner facility emissions and adverse respiratory effects. It is likely that ambient air monitoring conducted in many of the studies examining these emissions sources are detecting a mixture of emissions from various sources including domestic exposure sources, mobile exposure sources, and other industrial sources with both greater quantity and greater composition diversity as compared to calcining facilities. The operation of a calcining facility using appropriate emission mitigation practices does not produce emissions for which there is evidence of a public health concern. COI: DS has no CI disclosures. GTJ received partial support for this research from Oxbow Carbon LLC; Oxbow Carbon LLC provided stack emissions data for this research but did not determine the content of this article. RDH has previously consulted with Oxbow Carbon LLC concerning this calcining facility. Transparency document Transparency document related to this article can be found online at http://dx.doi.org/10.1016/j.yrtph.2015.07.028. References American Thoracic Society, 1991. Lung function testing: selection of reference values and interpretative strategies. Am. Rev. Respir. Dis. 144, 1202e1218. Cetin, E., et al., 2003. Ambient volatile organic compound (VOC) concentrations around a petrochemical complex and a petroleum refinery. Sci. Total Environ. 312 (1e3), 103e112. http://dx.doi.org/10.1016/S0048-9697(03)00197-9. Charron, A., Harrison, R.M., 2004. Quantitative interpretation of divergence between PM 10 and PM 2.5 mass measurement by TEOM and gravimetric (partisol) instruments. Atmos. Environ. 38 (3), 415e423. http://dx.doi.org/10.1016/ j.atmosenv.2003.09.072. Clark, C.R., et al., 2013. A GHS-consistent approach to health hazard classification of petroleum substances, a class of UVCB substances. Regul. Toxicol. Pharmacol. 67, 409e420. CONCAWE, 1993. Petroleum Coke. Product Dossier No. 93/105. CONCAWE, Brussels, p. 16. Dominici, F., et al., 2006. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. JAMA 295 (10), 1127e1134. http:// dx.doi.org/10.1001/jama.295.10.1127. EPA, 2004. AERMOD: Description of Model Formulation. EPA-454/R-03e004 September 2004. Goldstein, I.F., Landovitz, L., 1977. Analysis of air pollution patterns in New York CitydI. Can one station represent the large metropolitan area? Atmos. Environ. (1967) 11 (1), 47e52. http://dx.doi.org/10.1016/0004-6981(77)90205-0. Hassan Al, H.I., 2005. Effect of the removal of sulphur and volatile matter on the true density of petroleum coke. Period. Polytech. Chem. Eng. 49, 19e24. Katsouyanni, K., et al., 1996. Short term effects of air pollution on health: a European approach using epidemiologic time series data: the APHEA protocol. J. Epidemiol. Community Health 50 (Suppl. 1), S12eS18. Lin, T.Y., et al., 2004. Volatile organic compound concentrations in ambient air of Kaohsiung petroleum refinery in Taiwan. Atmos. Environ. 38 (25), 4111e4122. http://dx.doi.org/10.1016/j.atmosenv.2004.04.025. McKee, et al., 2014. Toxicological assessment of green petroleum coke. Int. J. Toxicol. 33 (Suppl. 1), 156Se167S. Rusconi, F., et al., 2011. Asthma symptoms, lung function, and markers of oxidative stress and inflammation in children exposed to oil refinery pollution. J. Asthma Off. J. Assoc. Care Asthma 48 (1), 84e90. http://dx.doi.org/10.3109/ 02770903.2010.538106. Samet, J.M., et al., 2000. The national morbidity, mortality, and air pollution study. Part II: morbidity and mortality from air pollution in the United States. Res. Rep. Health Eff. Inst. 94 (Pt 2), 5e70 discussion 71e9. Smargiassi, A., et al., 2009. Risk of asthmatic episodes in children exposed to sulfur dioxide stack emissions from a refinery point source in Montreal, Canada. Environ. Health Perspect. 117 (4), 653e659. http://dx.doi.org/10.1289/ ehp.0800010. White, N., et al., 2009. Meteorologically estimated exposure but not distance predicts asthma symptoms in schoolchildren in the environs of a petrochemical refinery: a cross-sectional study. Environ. Health A Glob. Access Sci. Source 8 (1), 45. http://dx.doi.org/10.1186/1476-069X-8e45. Wichmann, F.A., et al., 2009. Increased asthma and respiratory symptoms in children exposed to petrochemical pollution. J. Allergy Clin. Immunol. 123 (3), 632e638. http://dx.doi.org/10.1016/j.jaci.2008.09.052.
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Human health risk characterization of petroleum coke calcining facility emissions Davinderjit Singh, Giffe T. Johnson*, Raymond D. Harbison Center for Environmental and Occupational Risk Analysis and Management, University of South Florida, Tampa, FL, 33612, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 10 February 2015 Received in revised form 6 October 2015 Accepted 25 October 2015 Available online xxx
Calcining processes including handling and storage of raw petroleum coke may result in Particulate Matter (PM) and gaseous emissions. Concerns have been raised over the potential association between particulate and aerosol pollution and adverse respiratory health effects including decrements in lung function. This risk characterization evaluated the exposure concentrations of ambient air pollutants including PM10 and gaseous pollutants from a petroleum coke calciner facility. The ambient air pollutant levels were collected through monitors installed at multiple locations in the vicinity of the facility. The measured and modeled particulate levels in ambient air from the calciner facility were compared to standards protective of public health. The results indicated that exposure levels were, on occasions at sites farther from the facility, higher than the public health limit of 150 mg/m3 24-h average for PM10. However, the carbon fraction demonstrated that the contribution from the calciner facility was de minimis. Exposure levels of the modeled SO2, CO, NOx and PM10 concentrations were also below public health air quality standards. These results demonstrate that emissions from calcining processes involving petroleum coke, at facilities that are well controlled, are below regulatory standards and are not expected to produce a public health risk. © 2015 Elsevier Inc. All rights reserved.
Keywords: Calciner facility Petrochemical industry Calcined coke Particulate matter Black carbon
1. Introduction Calcined coke is a high quality carbon material produced by calcining green petroleum coke. Calcining is the process of heating green petroleum coke in a kiln to remove excess moisture, extract all remaining hydrocarbons and modify the crystalline structure of the coke, resulting in a denser more electrically conductive product. The temperatures in the kiln during the calcining process can range from 1200 C to 1450 C. The final product, calcined coke, is primarily used to make carbon anodes for the aluminum industry and recarburizing agent for other industries such as the steel industry. Green coke is basically an inert substance and the health hazards assigned to green coke are mostly associated with Particulate Matter (PM) exposures, which can be produced in the occupational setting during the process of calcination (McKee et al., 2014). If not appropriately controlled, this process could lead to the excess production of particulate emissions from either handling or storing
* Corresponding author. Center for Environmental/Occupational Risk Analysis and Management, College of Public Health, University of South Florida, 13201 Bruce B Downs Blvd., MDC 56, Tampa, FL, 33612, USA. E-mail address: [email protected] (G.T. Johnson). http://dx.doi.org/10.1016/j.yrtph.2015.10.025 0273-2300/© 2015 Elsevier Inc. All rights reserved.
of raw coke, or from the stack emissions during the production of calcined coke. Though industries that store, transfer or process petroleum products are broadly described as “petroleum industries”, the coke calcining industry is unique in that it can and is a standalone process distinct from other petroleum industries in producing a different profile of air emissions compared to what could be termed “petrochemical” industries, such as oil refineries. Unlike calcined coke production, petroleum oil refineries produce a variety of products and each product has a varied level of hazard potential (Clark et al., 2013). Calcining facilities process green coke to produce the final product, calcined coke, which substantially limits the constituents and quantity of emissions. The high temperatures required for the process of calcination and the further processing of the emissions gases in a combustion chamber, sometimes referred to as a pyro scrubber, provides sufficient heat and retention that destroys most of the emissions from this process for volatile organic compounds and combustible particles (CONCAWE, 1993). Though calcined coke has shown low hazard potential in human populations due to low volatile content, there remains some public health concern regarding the emissions from these facilities. The purpose of this research is to evaluate the emissions of a calcining
D. Singh et al. / Regulatory Toxicology and Pharmacology 73 (2015) 706e711
facility engaged in the handling and storage of green coke, as well as in the calcining process itself, and characterize the presence of any public health risks associated with these emissions. Particular emphasis is placed on the particulate matter generated, the resultant ambient air quality, and the risks associated with these levels of particulate matter. 2. Methods and materials The calcining facility evaluated in this study has the potential to produce approximately 444,000 short tons of calcined coke product per year. The calcining facility is located on the west side of a shipping canal within a port in eastern Argentina. The long and narrow property containing the facility abuts the west side of the shipping canal and has a south-southwest to north-northeast orientation. From a turning basin at its south-southwestern terminus, the shipping canal extends north-northeast to the city of Rio de la Plata. Meteorological data were taken into account in evaluating emissions. The general direction of the air flowing over the weather station located in calcining facility is towards urban areas, and previously passes over the River Plate (influenced by its interaction with the water) and then, over a narrow surface on the shore, between the river and the weather station. The air towards the monitors flows previously over urban areas. Proximate to the area in which the calciner resides is an oil refinery that supplies the green coke feed, industrial ports, and a large, populated community. There are multiple sources of pollution in the area including the refinery, sand and gravel storage and transport, and other industrial activity. Substantial sources of non-industrial pollution exists in the local area including unpaved roads, non-municipal garbage burning, fuel combustion from automobiles and heating, as well as a large number of wood burning stoves in homes for cooking. The emissions constituents evaluated included PM10 and the gaseous emissions of CO, SO2, and NOx. Volatile Organic Compounds (VOC's) are a major byproduct of the petroleum refinery industry and concentrations of approximately 15% VOC's are found in green coke as a result of the coking process. However, these VOC's and other volatiles present in the green coke are efficiently combusted and destroyed because of the high temperatures during the calcining process and their presence is not detectable in calcining emissions; as a result, VOC's were not included in this analysis (Cetin et al., 2003; Lin et al., 2004; Hassan, 2005). Both measured and modeled emissions from the kiln stacks, as well as actual ambient air monitoring were conducted for various pollutants. Ambient air quality PM10 monitoring data was collected continuously by three tapered element oscillating microbalance (TEOM 1400) monitors, and one multi-angle absorption photometer (MAAP) monitor at various locations surrounding the facility. Air data collection for year 2009 was conducted by the Center for Environmental Investigations (CIMA by its Spanish acronym). For the period of 2010 through the second quarter 2013, air data was collected by the facility under the direct supervision of The Provincial Agency for Sustainable Development (which acts as the regulatory agency and is known as OPDS by its Spanish acronym). For the third quarter 2013 through second quarter 2014, air data was collected by the Geochronology and Isotopic Institute (INGEIS by its Spanish acronym). Both CIMA and INGEIS are scientific research centers and are considered independent third party experts in this activity. As part of the data collection activities, CIMA utilized three TEOM 1400 monitors, two HI-Vol PM10 monitors, and a MAAP monitor to measure the ambient air quality at various locations surrounding the calcining facility. The TEOM 1400s and MAAP monitors continued to be used for PM10 monitoring by the calcining facility at various locations from 2010 through the first half of 2013.
707
INGEIS continued to use the same monitors at various locations around the facility for the second half of 2013 to the present. The locations and distance of these monitors have varied over time with the nearest location just at the entrance of the facility and the furthest at 1190 m from the calcining facility. TEOM monitors measure continuous ambient air quality values, while Hi-Vol samplers are based on 24-h samples that are typically taken on 3 or 6 day intervals. The estimated contribution from other sources of particulate emissions in the area was determined by wind trajectory analysis to estimate the emissions that contributed to PM10 concentrations. A wind trajectory analysis was performed using 5min meteorological data and coincident TEOM data to estimate the potential for the calcining plant to contribute to the reported Hi-Vol concentration. This analysis was performed using wind direction data from the facility meteorological tower that were coincident in time with the 24-h measured data collected at the monitors. The comparison was performed for 5-min average data since the TEOM PM10 data are available over 5-min intervals. If the wind was blowing in a direction such that a parcel of air would traverse the facility site and be transported to the specific monitor site, then the potential for percent contribution of particulate from the facility was identified. The MAAP monitor measures the black carbon concentration of the PM10 size particles. The entirety of particulate emissions from the calciner facility is black carbon since green petroleum coke and calcined coke are black carbon. Black carbon is an indicator of the amount of carbon related material such as calcined coke and raw petcoke that is present in the particulate (PM10) sample collected at the TEOM and can distinguish between emissions potentially from the calcining facility and non-calcining emissions. However, some black carbon measured at monitoring sites could also be attributed to diesel combustion or debris burning. The black carbon concentrations being measured by the MAAP monitor would, for the most part, represent emissions from the calciner facility since it is the largest source of black carbon in the area. The facility also conducted periodic stack testing to determine PM, NOx, CO and SO2 emission rates from the two kilns from 2011 through the third quarter of 2014. Particle size distribution was conducted on the measured total particulate matter to define the portion of PM10 in the stack gases. The kiln stack samples were collected using the EPA Conditional Test Method (CTM) 022/030. Per the CTM, a continuous stream of stack gas is pulled into the analyzer for a set period of time to determine the concentrations. The rates of emissions were calculated from the resulting concentrations and the volumetric flow. The rates of emissions of the various pollutants were then input into an air dispersion model along with 5 years of meteorological data. The USEPA AERMOD model was used for these assessments. AERMOD is a steady state Gaussian dispersion model developed by the USEPA and American Meteorological Society (AMS) and represents the current state of the art modeling (EPA, 2004). The modeling was performed in general accordance of the Argentinean modeling requirements of Stage III of Resolution Nr. 242/97 and using techniques that would be acceptable to EPA for the air quality assessment of a project located within the United States. The EPA's AERMOD model (Version 07026) was used with hourly meteorological data to predict PM emission impacts at ground-level receptor locations for 24-h averaging periods. AERMOD is a Gaussian plume model that calculates impacts at each receptor for each hour in the meteorological data set (typically a full year of data) and it provides maximum ground-level concentrations for point sources such as the two Kiln stacks. It also predicts concentrations in the cavity zone and uses Building Profile Input Program (BPIP) data to simulate the influence of proximate structures to estimate the
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downwash effects. The results of the modeling were compared to the ambient air quality sampling efforts discussed above as well as local and USEPA ambient air quality standards. The gaseous pollutants were modeled using AERMOD model to calculate 3-h and 1h concentrations. 1-h concentrations were compared with the USEPA and Argentina standards. The standard concentration for PM10 for 24-h averaging period is 150 mg/m3 not to be exceeded once per year averaged over 3 years (also the Argentina standard), and an annual average of 50 mg/m3. This annual standard was revoked by EPA effective December 17, 2006 due to lack of evidence linking health problems to long-term PM10 exposure. This standard is still used in the Argentina regulations. 3. Results Table 1 shows the measured 24-h ambient air quality concentrations for PM10 of Hi-Vol and TEOM samplers for the year 2009. As indicated before, the TEOM monitors and Hi-Vol monitors were both installed and operated by CIMA. TEOM monitors heat up the filter so that the semi-volatile organic mass is driven off. Hi-Vol samplers capture both semi-volatile mass (aerosol) as well as the particulate mass. As a result, the concentrations recorded by a HiVol monitor can sometimes be higher than the concentration obtained by the TEOM monitors. Table 2 analyzes the concentrations of PM10 from Hi-Vol and TEOM samplers as measured in Table 1. Typically, the semi-volatiles that are driven off from the TEOM are ammonia nitrates (Charron and Harrison, 2004). In a populated area the source of ammonia nitrates would most likely be associated with traffic. There are no ammonia nitrates present in petroleum coke so it could not be attributed to the calcining facility. Therefore, the higher concentrations associated with the Hi-Vol monitors in this study are most likely associated with traffic rather than the calcining facility. In most cases, the observed TEOM measured concentrations were substantially lower than the Hi-Vol measured concentrations indicating that traffic is a large contributor of particulate matter in the area. Based on an evaluation of the wind direction data and measured concentrations, it was concluded that when the wind direction is mainly blowing from the facility to the monitor, the TEOM concentrations are well below the 24-h standard of 150 mg per cubic meter of air (mg/m3). Table 3 shows the PM10 concentrations as measured around the calcining facility at various locations from the year 2009 through the 3rd quarter of 2014. The measurements were taken with three TEOM 1400 monitors at distances ranging from the entrance of the facility out to 1190 m from the calcining facility. Table 4 shows the number of measured PM10 values that were over the 24-h standard of 150 mg/m3. The vast majority of 24-h concentrations are well below the
country standard and the United States Environmental Protection Agency (USEPA) 24-h concentration of 150 mg/m3 not to be exceeded more than once per year, on average, over 3 years. The quarters showing average 24-h concentrations in excess of the standard were mainly associated with the monitor located over 850 m away from the facility. Given the distances of the monitors from the facility and as supported by the modeled results, the higher concentrations are most likely the result of local influences such as burning of garbage, stove cooking or fugitives from more closely located industrial facilities. The 24-h annual averages for TEOMs 3, 4, and 5, were 34.61 mg/ m3, 41.66 mg/m3, and 38.02 mg/m3, respectively. All of the annual averages are below the local annual PM10 standard of 50 mg/m3. The reported maximum annual averages for TEOM 3 and TEOM 4 are in years which fall below traditionally accepted data collection rates (80%). The maximum annual average for TEOM 3 and TEOM 4 for years that exceeded the data collection rate of 80% was 32.31 and 32.52 mg/m3, respectively. Given that the monitors reported concentrations were below the annual average standard, which have been developed to protect public health, the contribution of the calciner facility to the long term concentrations of PM10 in the area are de minimis. Fig. 1 shows the average concentrations of the ambient black carbon, which are associated with the calcining facility fugitive and stack emissions. The carbon concentrations are a small fraction of the overall concentrations seen in Table 3 for the ambient PM10 concentrations for TEOM 3, 4 and 5 for the same time period. It can be concluded that the carbon concentration represents the PM10 contribution from the calciner facility. Given the overall low measured concentrations, and the small fraction that represents contributions from the calcining facility, the overall contribution of PM10 from the calcining facility is de minimis. It should be noted that the average monthly black carbon concentrations presented in Fig. 1 correspond well with the modeled concentration for PM10. The maximum black carbon concentrations in Fig. 1 are higher than the modeled PM10 concentration but the concentrations from the monitors also include black carbon from other sources such as diesel fuel combustion (i.e. diesel fired trucks on the streets). The local community had no measured exceedance of 150 mg/m3 PM10 for years 2008 and 2014, all other exceedances are reported in Table 4. During the periods of 2008e2010 and 2012e2014, TEOM 3, TEOM 4, and TEOM 5 did not exceed the standard of 1 measure over 150 mg/m3 PM10 per year averaged over 3 years. During the periods 2009e2011, 2010e2012, and 2011e2013 only TEOM 4 exceeded the standard with 6 exceedances during each of these 3 year periods. However, for each of these exceedances, the carbon fraction (which represents the maximal potential contribution of the calcining facility) was less than 10 mg/m3 or less than 7% of the total PM10 measurement. While the community may not have met their PM10
Table 1 24-h PM10 concentrations measured by Hi-Vol and TEOM monitors in year 2009 Hi-Vol
mg/m3 mg/m3 %
%
mg/m3 mg/m3 %
%
Monitor 164 m from facility (Site A)
6/1/2009 12/1/2009 18/01/2009 24/01/2009 30/01/2009 5/2/2009 11/2/2009 18/02/2009 24/02/2009
219 124 115 145 19 50 55 48 65
62 25 2 52 36 96 30 43 57
167 122 71 94 24 46 56 24 42
51 67 6 77 54 97 30 87 71
TEOM
92 79 56 88 30 39 62 53 51
Calcining facility contribution
38 75 98 48 64 4 70 57 43
Monitor 485 m from facility (Site B)
6/1/2009 12/1/2009 18/01/2009 24/01/2009 30/01/2009 5/2/2009 11/2/2009 18/02/2009 24/02/2009
TEOM
75 49 38 46 25 30 42 24 34
Calcining facility contribution
Non-calcining facility contribution
Non-calcining facility contribution
Hi-Vol
49 33 94 23 46 3 70 13 29
D. Singh et al. / Regulatory Toxicology and Pharmacology 73 (2015) 706e711
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Table 2 Analyses of 24-h PM10 concentrations measured by Hi-Vol and TEOM in year 2009. Site A
Hi-Vol mg/m3
TEOM mg/m3
Site B
Hi-Vol mg/m3
TEOM mg/m3
Min Max Median Half of Max Sqrt
19 219 65 109.5 14.8
30 92 56 46 9.5
Min Max Median Half of Max Sqrt
24 167 56 83.5 12.9
24 75 38 37.5 8.7
Table 3 Monthly 24-h average of PM10 for TEOM 3, 4, and 5 for time period 1st quarter 2009 through 3rd quarter 2014.
10
TEOM 5
2013
2014
Concentration in mg/m.3.
goals consistently over these periods at the TEOM 4 monitor, the source of these exceedances were not calcining operations as demonstrated by the black carbon PM10 measurements. The maximum potential emissions for all constituents from the facility were modeled using onsite meteorological data. The emission rates from stack test data for CO, NOx, SO2 and PM10 were scaled up to reflect the maximum production of the facility. The AERMOD dispersion model was used to determine offsite ambient concentrations. As presented in Table 5, all ambient concentrations are well below local standards and EPA NAAQS levels. The modeling demonstrates that any potential contribution from the stack gases to the overall ambient concentrations in the area would be small and with respect to CO, NOx and PM10 would contribute less than
2
Jun-14
0 Oct-14
2012
4
Feb-14
2011
6
Jun-13
2010
8
Oct-13
81.7 173.8 74.6 78.5 75.4 53.3 60.9 95.7 83.9 111.6 118.2 147.7 67.5 107.5 140 88.3 131.4 125.4 172 60.6 36.2 54.6 45.5
Feb-13
Max
5.8 5.7 3.5 9.1 7.1 6.7 2.2 8.7 9.1 7.3 7.1 6.9 11 5.9 6.8 5.8 10.7 3.9 6.7 6.5 9.4 4 1.4
Jun-12
Min
26.2 24.4 22 24.3 22.8 19.2 20.8 26.6 21.7 26.1 39.3 39.2 30.1 37 31.2 33.3 36.3 45.3 34.5 24.7 18.9 21.3 20.7
Oct-12
Avg
88.4 168.2 101.4 63.5 115.1 139.9 158.1 85 102.8 195.1 156.5 155.1 70 81 164.5 122.2 61.2 81.7 90 182.9 75.3 44.4 44.5
Feb-12
Max
12.2 6.5 5 12.8 12.7 8.2 5.3 16.4 6.1 11.6 10.5 6.7 10 5.2 6.9 5.5 8.1 6.7 3.9 5.5 6.2 2.2 7.1
Jun-11
Min
37.5 36.3 36.2 34.2 41.5 54 40.1 40.3 39.4 56.5 46.7 28.3 24.9 22.5 33 33.2 30.8 24.9 27.8 28.2 20 15.5 15.8
Oct-11
Avg
103.6 177.2 124.3 68.3 57.4 80 92.7 86.9 53.2 210.3 133.6 53.4 65.8 70.6 61.1 88.8 50.8 65.8 79 58.1 48.3 71.9 105.4
Feb-11
Max
2.4 6.3 7.8 7.6 7.6 6.1 3.5 11.7 11.4 9.2 9.4 12.1 10.1 6.8 5.4 6.8 5 7.3 8.6 8.2 6.5 10.5 13.2
Jun-10
Min
28.9 37.6 26.3 23.8 23 26.1 28.5 27.7 23.9 39.9 38.9 28.2 26.6 30.7 25.5 25 21.5 28.3 26.2 25.5 20.2 29.1 29.9
Oct-10
Avg
1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd
Feb-10
Quarter
2009
Jun-09
Year
Oct-09
TEOM 4
Feb-09
TEOM 3
Concentra on μg/m3
Period
12
X = Average concentraƟon Fig. 1. Black carbon monthly average concentrations measured by multi-angle absorption photometer.
20% of the standard. Stack emissions concentrations of NOx, CO and SO2 were measured from the two kilns at the calcining facility on a monthly basis. The measured stack gas emissions were below the emissions values used in the AERMOD modeling presented in Table 5. 4. Discussion The results of monitored and modeled emissions concentrations from the coke calcining facility evaluated in this study demonstrate that normal and maximum facility operation emissions produce ambient concentrations that are below regulatory standards designed to protect public health. This includes emissions from the actual calcining process of green coke as well as the actual fugitive emissions from the handling and storage of green coke at the facility. Due to the temperatures achieved during calcining, the emissions of VOCs from calcining facilities are almost non-existent
Table 4 PM10 values exceeding the level of 150 mg/m3. TEOM
Year
Month
Day
24-HR Ave (mg/m3)
Carbon fraction
Percent of total
3 3 4 4 4 4 4 4 4 4 5 5
2009 2011 2009 2010 2011 2011 2011 2011 2012 2013 2009 2013
4 6 4 8 4 5 7 11 7 12 4 9
24 13 24 10 15 31 12 22 7 30 24 19
177.24 210.33 168.20 158.15 195.05 160.94 156.53 155.07 164.47 182.90 173.80 171.95
3.620 3.145 3.620 9.512 3.068 2.843 3.746 2.091 5.882 3.611 3.620 3.621
2.04 1.50 2.15 6.01 1.57 1.77 2.39 1.35 3.58 1.97 2.08 2.11
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D. Singh et al. / Regulatory Toxicology and Pharmacology 73 (2015) 706e711 Table 5 Modeled ambient air concentrations. Pollutant
Averaging period
Modeled concentration (mg/m3)
Standard (mg/m3)
NOx
1h Annual 1h 8h 3h 24 h Annual 24 h Annual
72.2 2.15 106.1 79.2 365.4 215.5 11.8 2.8 0.04
400 100 40,000 10,000 1300 365 80 150 50
CO
SOx PM10
when compared to the nearby petrochemical facilities. The consistency in the overall Hi-Vol/TEOM data set among sites A and B suggests that the difference between Hi-Vol and TEOM measurements is attributable to prevailing pollution conditions in the area. Hi-Vol data almost always has a higher concentration than the TEOM concentrations. This discrepancy results from the design of the TEOMs that includes heating the TEOM samples to drive off moisture such that the mass is only particulate matter, with no volatiles or semi-volatiles. The difference between Hi-Vol and TEOM measurements appears to be linked to the presence of semivolatile compounds and nitrate compounds in the atmosphere that are collected by the Hi-Vol but are not collected by the TEOM. Calcined coke does not contain any volatile compounds since they are destroyed in the production process. This indicates that all samples exceeding the standard contained large amounts of particulates from sources other than the calcining facility. For the calcining facility, the highest measured PM10 annual average concentrations for 2009 through 2013 at TEOM 3, 4 and 5 locations were 34.61, 41.66, and 38.02 mg/m3, respectively, which are below the local Argentina standard of 50 mg/m3 annual average. During the periods 2009e2011, 2010e2012, and 2011e2013 only TEOM 4 exceeded the 24 h standard of 150 mg/m3 not to be exceeded more than once per year, on average, over 3 years with 6 exceedances during each of these 3 year periods. However, for each of these exceedances, the carbon fraction (which represents the maximal potential contribution of the calcining facility) was less than 10 mg/ m3 or less than 7% of the total PM10 measurement, demonstrating that calcining operations were not the cause of those exceedances. Though the monitored 24-h concentration does exceed the local and USEPA NAAQS concentration level of 150 mg/m3 for one monitor, it occurs at a location that is over 850 m away from the site, proximate to other sources of particulate emissions. It can be concluded that the fugitive emissions contribution from the calciner facility would be de minimis to the overall concentration levels as compared to nearby facilities and activities. The black carbon concentrations measured by the MAAP further validate that the overall PM10 contribution from the calciner facility during these events would most likely be small. The modeled results for maximum production at the facility shows the concentrations would be well below 20% of any of the regulatory standards except for the SO2 24-h standard where it would be slightly less than the 60% of the standard. An evaluation of the epidemiological literature regarding potential associations between exposures similar to those found at calcining facilities and respiratory illnesses demonstrates that contemporary epidemiological evidence does not support an association between emissions from the calcining facility and adverse health effects. Various studies have examined the effect of the PM on human health. These studies have included both acute as well as chronic effects on respiratory and cardiovascular health of the exposed populations (Samet et al., 2000; Katsouyanni et al., 1996; Dominici et al., 2006). Both PM and gaseous pollutants from combustion and
mobile sources have been evaluated for their potential to produce adverse cardiovascular and respiratory health effects. Mortality studies have assessed the number of deaths occurring during various time periods and have attempted to draw inferences on the exposure-associated mortality. Morbidity studies have attempted to correlate hospital admission rates, symptoms, disease diagnoses, and specific measurements of pulmonary function. However, none of these observational studies have identified an exposure response characterization that demonstrates increased disease rates at levels below current regulatory limits or an exposure response that can be used to inform risk assessment. These studies typically classify subjects as ‘exposed’ or ‘unexposed’ or broadly assign subjects an exposure value based on monitoring values that are not specific to their location. Without knowing specific exposure ranges for subjects and the associated rates of disease that occur within those ranges, it is not possible to use this type of data to characterize risk for other populations with similar exposure. As well, none of these studies have produced data that would inform a risk assessor that any increased risk occurs at or below regulatory limits designed to be protective of public health. Compared to the emissions values reported in this study, observational studies have not produced data that suggest the emissions from this calcining facility produces any public health risk. Other studies have attempted to examine the impact of industrial complexes that include petrochemical refineries and calcining facilities on the respiratory status of populations residing in surrounding areas, primarily that of children (Rusconi et al., 2011; White et al., 2009; Smargiassi et al., 2009; Wichmann et al., 2009). Although the calcining process is not the same as petroleum refinery operations and produces fewer emissions in both quantity and in composition than refining, coke calcining facilities have often been included as a potential contributor to area emissions. Of these studies, some authors suggested a potential association between particulate exposures and altered respiratory function, despite the fact that none of these studies were able to identify specific emissions from calcining as the cause of the abnormal pulmonary function changes. Exposure claims are misleading when one monitoring location is used as a source for ambient air measurements that have multiple sources. As well, a study conducted by Goldstein and Landovitz (1977) warned that using one air monitoring location is unreliable in determining the air quality of a large metropolitan area. Smargiassi et al. (2009) attempted to study the effect of point source SO2 emissions on asthma hospitalizations near petroleum refineries in Montreal, Canada. Though the study concluded that short term exposure to SO2 led to higher rates of asthma hospitalization, the exposures assigned to subjects (children aged 2e4) were poorly characterized. It was noted that the majority of exposures in these children were indoor air contaminants, and these were the likely cause of increased hospitalizations. The study failed to characterize a threshold of SO2, above which, these acute episodes were demonstrated to occur, and as well, the authors failed to demonstrate that the exposures were specific to the industrial
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sources cited in the study. As the authors of this study did not know individual subjects exposure levels at the time of acute asthmatic episodes, it is not possible to draw conclusions regarding the potential impact of these suspected exposures. White et al. (2009) studied the effect of proximity to a petroleum refinery and the development of asthma symptoms. The study reported that prevalence of asthma symptoms was higher in children due to presence of the petroleum refinery in the area. However, case classification in this study was determined by survey and no actual diagnosis of asthma or asthma symptoms were recorded in this study. Further, it is unknown if any of the subjects reporting more symptoms in this study actually experienced any exposure from local refinery emissions. Similarly, Rusconi et al. (2011) attempted to evaluate the effect of oil refinery emissions on asthma symptoms and pulmonary function in children and adults residing in the proximate areas. The study reported that the population residing in the areas proximate to refinery facilities had decreased lung function with higher rates of bronchial inflammation as compared to the control population. As in White et al. (2009) however, case classification was based solely on selfreporting of symptoms and the individual exposure levels of subjects were unknown, making it impossible to determine if ‘cases’ actually experienced higher exposures than ‘controls’. There is bias inherent to using questionnaires in studies evaluating health status, especially in areas widely assumed by the general public to have higher pollution levels, which obscures the reliability of the outcome. Wichmann et al. (2009) attempted to characterize the role of the petrochemical industry as a contributing factor in exacerbations of asthma and other respiratory symptoms in children. The authors reported that subjects in closer proximity to the local industrial complexes had ‘higher’ rates of respiratory symptoms and decreased pulmonary function. However, the authors were not able to identify specific sources of the exposures reported in this study or provide individual exposure estimates that would allow for an exposure response characterization to be made. In the region described in this study, various non-industrial sources of pollutants are likely to produce the same type of PM and gaseous pollutants reported including motor vehicles, unpaved roads, and fuel combustion at homes such as wood burning stoves and cooking. The pollutants emitted from these non-industrial sources may differ in amount and composition and thus may contribute differently to potential adverse health effects. When compared to the results of the current study, it is clear that the emissions contribution from a calcining facility would be de minimis compared to other emission sources indicated to be present in Wichmann et al., 2009. As well, in their discussion of health outcomes, the authors in this study classified subjects within the normal range of FVC and FEV1 as having pulmonary impairment, when in fact, no cases of pulmonary impairment were identified among any of the exposure groups using the American Thoracic Society criteria. Using this criterion, FVC and FEV1 values less than 80 percent predicted are classified as abnormal lung function (American Thoracic Society, 1991). No cases with abnormal lung function were reported in the Wichmann et al., 2009 study. Their conclusions are misleading and based on an irresponsible analysis of pulmonary function data. 5. Conclusions The results from the current study demonstrate that the emissions from a calcining facility as described are well below regulatory levels that are protective of public health and do not make a substantial contribution to related emissions in the local community. Therefore it would be appropriate to assign coke calcining facilities, such as the facility in our study when operated and
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maintained with similar control measures, as a de minimis contributor when evaluating the effects of community air emissions on community health. In addition, contemporary epidemiological evidence does not demonstrate an association between calciner facility emissions and adverse respiratory effects. It is likely that ambient air monitoring conducted in many of the studies examining these emissions sources are detecting a mixture of emissions from various sources including domestic exposure sources, mobile exposure sources, and other industrial sources with both greater quantity and greater composition diversity as compared to calcining facilities. The operation of a calcining facility using appropriate emission mitigation practices does not produce emissions for which there is evidence of a public health concern. COI: DS has no CI disclosures. GTJ received partial support for this research from Oxbow Carbon LLC; Oxbow Carbon LLC provided stack emissions data for this research but did not determine the content of this article. RDH has previously consulted with Oxbow Carbon LLC concerning this calcining facility. Transparency document Transparency document related to this article can be found online at http://dx.doi.org/10.1016/j.yrtph.2015.07.028. References American Thoracic Society, 1991. Lung function testing: selection of reference values and interpretative strategies. Am. Rev. Respir. Dis. 144, 1202e1218. Cetin, E., et al., 2003. Ambient volatile organic compound (VOC) concentrations around a petrochemical complex and a petroleum refinery. Sci. Total Environ. 312 (1e3), 103e112. http://dx.doi.org/10.1016/S0048-9697(03)00197-9. Charron, A., Harrison, R.M., 2004. Quantitative interpretation of divergence between PM 10 and PM 2.5 mass measurement by TEOM and gravimetric (partisol) instruments. Atmos. Environ. 38 (3), 415e423. http://dx.doi.org/10.1016/ j.atmosenv.2003.09.072. Clark, C.R., et al., 2013. A GHS-consistent approach to health hazard classification of petroleum substances, a class of UVCB substances. Regul. Toxicol. Pharmacol. 67, 409e420. CONCAWE, 1993. Petroleum Coke. Product Dossier No. 93/105. CONCAWE, Brussels, p. 16. Dominici, F., et al., 2006. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. JAMA 295 (10), 1127e1134. http:// dx.doi.org/10.1001/jama.295.10.1127. EPA, 2004. AERMOD: Description of Model Formulation. EPA-454/R-03e004 September 2004. Goldstein, I.F., Landovitz, L., 1977. Analysis of air pollution patterns in New York CitydI. Can one station represent the large metropolitan area? Atmos. Environ. (1967) 11 (1), 47e52. http://dx.doi.org/10.1016/0004-6981(77)90205-0. Hassan Al, H.I., 2005. Effect of the removal of sulphur and volatile matter on the true density of petroleum coke. Period. Polytech. Chem. Eng. 49, 19e24. Katsouyanni, K., et al., 1996. Short term effects of air pollution on health: a European approach using epidemiologic time series data: the APHEA protocol. J. Epidemiol. Community Health 50 (Suppl. 1), S12eS18. Lin, T.Y., et al., 2004. Volatile organic compound concentrations in ambient air of Kaohsiung petroleum refinery in Taiwan. Atmos. Environ. 38 (25), 4111e4122. http://dx.doi.org/10.1016/j.atmosenv.2004.04.025. McKee, et al., 2014. Toxicological assessment of green petroleum coke. Int. J. Toxicol. 33 (Suppl. 1), 156Se167S. Rusconi, F., et al., 2011. Asthma symptoms, lung function, and markers of oxidative stress and inflammation in children exposed to oil refinery pollution. J. Asthma Off. J. Assoc. Care Asthma 48 (1), 84e90. http://dx.doi.org/10.3109/ 02770903.2010.538106. Samet, J.M., et al., 2000. The national morbidity, mortality, and air pollution study. Part II: morbidity and mortality from air pollution in the United States. Res. Rep. Health Eff. Inst. 94 (Pt 2), 5e70 discussion 71e9. Smargiassi, A., et al., 2009. Risk of asthmatic episodes in children exposed to sulfur dioxide stack emissions from a refinery point source in Montreal, Canada. Environ. Health Perspect. 117 (4), 653e659. http://dx.doi.org/10.1289/ ehp.0800010. White, N., et al., 2009. Meteorologically estimated exposure but not distance predicts asthma symptoms in schoolchildren in the environs of a petrochemical refinery: a cross-sectional study. Environ. Health A Glob. Access Sci. Source 8 (1), 45. http://dx.doi.org/10.1186/1476-069X-8e45. Wichmann, F.A., et al., 2009. Increased asthma and respiratory symptoms in children exposed to petrochemical pollution. J. Allergy Clin. Immunol. 123 (3), 632e638. http://dx.doi.org/10.1016/j.jaci.2008.09.052.