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Differences in the carbon composition of source profiles for diesel- and gasoline-powered vehicles
Abstract
Filter samples of diesel-fueled heavy-duty and gasoline-fueled light-duty vehicle exhaust were acquired under controlled conditions associated with the State of Arizona's motor vehicle inspection and maintenance program. Samples of a mixture of emissions from these vehicles were also acquired at roadside sites. These samples were analysed for mass, elements, ions, and carbon. The carbon which evolved at temperatures of 120, 250, 450, and 550 C in a pure helium atmosphere, and at temperatures of 550, 700, and 800 C in a 2°0 oxygen 98°0 helium (by volume) atmosphere was measured with a flame ionization detector. The fraction of carbon which evolved at 700 C in the 2°0 oxygen atmosphere was found to be nearly 10-times as abundant (as a fraction of PM2.5 mass emissions) in the heavy-duty diesel-fueled vehicle emissions relative to the light-duty gasoline-fueled vehicle emissions. The organic carbon which evolved at 120 C was twice as abundant in diesel exhaust. The fraction of carbon which evolved at 550 C in an oxidizing atmosphere was twice as abundant in gasoline-fueled vehicle exhaust as it was in diesel exhaust. These differences in relative composition may be sufficient to allow diesel- and gasoline-fueled vehicle exhaust contributions to be distinguished from each other in ambient samples through the use of receptor models.
... According to the IMPROVE thermal/optical (TOR) protocol, OC was defined as OC1 + OC2 + OC3 + OC4 + OPC (OPC means pyrolized organic carbon), and EC was considered as EC1 + EC2 + EC3 − OPC [46]. Studies have shown that the different carbon components available through the IMPROVE protocol represent different emission sources [42,47,48]. In this study, we used eight carbon fractions to determine the source apportionment of carbonaceous aerosols in PM 1 , PM 2.5 , and PM 10 size fractions, OC1 representing a biomass combustion source, OC2, OC3, and OC4 representing coal combustion Atmosphere 2020, 11, 1368 9 of 16 emission sources, OPC and EC1 representing gasoline vehicle emissions, and EC2 and EC3 representing the emissions of diesel vehicles [20,46,48]. ...
... Studies have shown that the different carbon components available through the IMPROVE protocol represent different emission sources [42,47,48]. In this study, we used eight carbon fractions to determine the source apportionment of carbonaceous aerosols in PM 1 , PM 2.5 , and PM 10 size fractions, OC1 representing a biomass combustion source, OC2, OC3, and OC4 representing coal combustion Atmosphere 2020, 11, 1368 9 of 16 emission sources, OPC and EC1 representing gasoline vehicle emissions, and EC2 and EC3 representing the emissions of diesel vehicles [20,46,48]. ...
... Atmosphere 2020, 11, x FOR PEER REVIEW 9 of 16 emission sources, OPC and EC1 representing gasoline vehicle emissions, and EC2 and EC3 representing the emissions of diesel vehicles [20,46,48]. As shown in Figure 6, EC1, OC2, and OPC were the main components of carbon and represented pollution sources from coal, motor vehicle exhaust emissions, and biomass combustion. ...
Carbonaceous particles have been confirmed as major components of ambient aerosols in urban environments and are related to climate impacts and environmental and health effects. In this study, we collected different-size particulate matter (PM) samples (PM 1 , PM 2.5 , and PM 10) at an urban site in Lanzhou, northwest China, during three discontinuous one-month periods (January, April, and July) of 2019. We measured the concentrations and potential transport pathways of carbonaceous aerosols in PM 1 , PM 2.5 , and PM 10 size fractions. The average concentrations of OC (organic carbon) and EC (elemental carbon) in PM 1 , PM 2.5 , and PM 10 were 6.98 ± 3.71 and 2.11 ± 1.34 µg/m 3 , 8.6 ± 5.09 and 2.55 ± 1.44 µg/m 3 , and 11.6 ± 5.72 and 4.01 ± 1.72 µg/m 3. The OC and EC concentrations in PM 1 , PM 2.5 , and PM 10 had similar seasonal trends, with higher values in winter due to the favorable meteorology for accumulating pollutants and urban-increased emissions from heating. Precipitation played a key role in scavenge pollutants, resulting in lower OC and EC concentrations in summer. The OC/EC ratios and principal component analysis (PCA) showed that the dominant pollution sources of carbon components in the PMs in Lanzhou were biomass burning, coal combustion, and diesel and gasoline vehicle emissions; and the backward trajectory and concentration weight trajectory (CWT) analysis further suggested that the primary pollution source of EC in Lanzhou was local fossil fuel combustion.
... OC is primarily formed from the incomplete combustion of fuel and lubricant (Jiang et al. 2019), and EC is formed via fuel pyrolysis at a relatively low ambient temperature or from gas-to-particle conversion at high ambient temperature (Han et al. 2007;Watson et al. 1994). More large-size particles of OC and EC were observed to have been formed in 97# than those in 93# petrol exhausts. ...
... The EC composition is usually divided into two categories: EC1 is the char-EC and directly forms via the fuel pyrolysis at a relatively low ambient temperatures, while EC2 and EC3 are defined as soot-EC, and derived from gasto-particle conversion at high ambient temperatures (Han et al. 2007;Watson et al. 1994). Therefore, a higher combustion temperature of petrol can produce more EC2. ...
The most common commercial oils in the Chinese market are two petrol types with octane levels of 93 and 97. To determine the source spectrum of air pollutant emissions, we herein investigated the specific emission sizes of the total suspended particles (TSP), total carbon (TC), elemental carbon (EC), organic carbon (OC), and polycyclic aromatic hydrocarbons (PAHs) from a petrol engine fueled with 93# and 97# petrol in 2016 (based on Chinese national IV gasoline standard). We found that while 93# emitted a higher TSP content, 97# emitted greater TC, EC, OC, and PAHs. The highest carbon contents were found in the < 0.25 µm and 0.44-1.0 µm size fractions for the 93# and 97# petrol, respectively. OC content showed a significant positive correlation with EC, and EC2 (at 740 ℃) was the main carbon fragment in both petrol exhausts. The highest PAH content occurred in the 0.25-0.44 µm size-bin, differing from the results for TC, EC, and OC, and medium molecular weight (4 rings) PAHs were the primary component in the emissions. These results indicate that fuel composition and octane sensitivity have a prominent effect on the size distributions of TC (including EC, OC, and PAHs). Thus, more studies on the carbon content at specific emission sizes in petrol exhaust should be conducted to clarify the main factors impacting these variations.
... The increase in engine speed from 1000 to 2000 rpm causes formation of less H-VS (− 6.2%), and more L-VS (11.0%) and non-VS (20.4%) which are in line with the findings of , as they found less volatile substances and more non-volatile substances in the PM of diesel engines with the increase in engine speed. It is because the rise in combustion temperature as a consequence of the rise in the engine load or speed leads to more gas-to-particle conversion of elemental carbon (Watson et al., 1994;Han et al., 2007), hence formation of more non-VS and fewer H-VS . Also, the higher air/fuel ratio because of the rise in the engine load or speed leads to less availability of oxygen for oxidation of elemental carbon (Li et al., 2014), hence formation of more non-VS and fewer H-VS . ...
... The magnitudes of activation energy and frequency factor calculated in this study are located in the ranges of the studies available in the literature for diesel engines fueled with diesel, as approximately 100-200 kJ/mol for the activation energy and 6.3E+ 04-9.5E+ 08 s -1 for the frequency factor Tse, 2016;Watson et al., 1994;Man et al., 2015;Lu et al., 2012). ...
The lifetime and efficiency of diesel particulate filters (DPFs) strongly depend on the proper and periodic cleaning and servicing. Unfortunately, in some cases, inappropriate methods are applied to clean the DPFs, e.g., using air compressors without proper disposal procedures that can have negative impacts on human health, the environment, and DPF’s efficiency. However, there is no information available about the properties of this kind of PM. This research is therefore presented to explore the physicochemical and toxicity properties of aged PM trapped in a DPF (using compressed air for PM sampling) employing STEM, SEM, EDS, Organic Carbon Analyzer, TGA/DSC, and Raman Spectrometer for investigating the physicochemical properties, and assays of cell viability, cellular reactive oxygen species (ROS), interleukin-6, and tumor necrosis factor-alpha (TNF-α) for investigating the toxicity properties. Also, analyses from fresh PM samples from the diesel vehicle at two engine speeds are presented. It is found that at a certain/fixed PM number/mass for all three samples tested, the PM from DPF compared with the fresh PM can have both positive (particularly having the lowest water-soluble total carbon ratio) and negative impacts on human health (particularly having the highest cell death rate of 13.4%, ROS, and TNF-α) and the environment.
... Significant correlation coefficients (r) between OC2 and EC1 for sites OS2 (~0.9) and OS4 (~0.9) allow for diesel emission inference from vehicles in the area. Large amounts of OC4 in TC are associated with emissions from gasoline-fueled engines (Watson et al. 1994). A significant correlation of OC2 and OC3 indicates the presence of charcoal burning Watson et al. 2001). ...
... The different sources of air pollution can be analyzed by considering the collected data on the eight carbonaceous components. The content of the carbonaceous fractions has been mainly used in source profile studies to differentiate gasoline vehicles from diesel vehicles and to differentiate among different geological dusts (Watson et al. 1994;Kalaiarasan et al. 2018;Qi et al. 2018). However, analyzing the proportions of carbonaceous fractions in particulate matter indicates the sources that are contributing to pollutants in the atmosphere. ...
Variations in the carbonaceous aerosol contents, organic carbon (OC) and elemental carbon (EC), in particulate matter less than 10 μm in size (PM10), were analyzed at sites influenced by coal mining in an open-pit mine located in northern Colombia. Samples were collected during different seasonal periods throughout 2015. Meteorological variables for each site were examined during the different seasons. Aerosols were detected using a thermal-optical reflectance protocol method. The highest PM10 concentrations, between the ranges of 28.2 ± 8.2 μg m−3 and 75.0 ± 36.5 μg m−3, were recorded during the dry season. However, the highest concentrations of OC (4.8–14.2 μg m−3) and EC (2.9–13.9 μg m−3) in PM10 were observed during the transition period between the dry and wet seasons. The strong correlation between OC and EC in PM10 (r = 0.6–1.0) during the transition season indicates a common primary combustion source. High OC (> 8.3 μg m−3) and EC (> 6.9 μg m−3) concentrations were associated with low wind speeds (< 2.1 m s−1) moving in different directions. Analyses of the sources of atmospheric aerosol pollutants in the mining area in northern Colombia showed that the daily maximum total carbon concentrations were mainly associated with regional atmospheric transport of particulate matter from industrial areas and biomass burning sites located in the territory of Venezuela.
... 70−72 For example, EC2 is used as an indicator for diesel emissions, while gasoline vehicles and wood burning are not apt to emit abundant EC2, because of lower burning temperatures. 73,74 OC1 and OC2 are more abundant in gasoline and diesel exhaust. 73,75 Yan et al. suggested that OC1 and OC4 were the dominant carbon fractions for gasoline emissions, accounting for∼40% and 25% of TC. 63 OC3 and EC1-PyC are considered good markers of biomass burning sources, 76 but Kim and Hopke reported that gasoline vehicles can emit much higher concentrations of high-temperature OC3 and OC4 in comparison with other OC fractions. ...
... 73,74 OC1 and OC2 are more abundant in gasoline and diesel exhaust. 73,75 Yan et al. suggested that OC1 and OC4 were the dominant carbon fractions for gasoline emissions, accounting for∼40% and 25% of TC. 63 OC3 and EC1-PyC are considered good markers of biomass burning sources, 76 but Kim and Hopke reported that gasoline vehicles can emit much higher concentrations of high-temperature OC3 and OC4 in comparison with other OC fractions. The present field-based study revealed that the OC3 and EC1-PyC fractions from biomass burning (19% and 29%) were significantly (p < 0.05) higher than those from coal combustion (13% and 17%). ...
... However, EC1 and EC2 respectively were the dominant part of total EC to LDG and HDG, by 76.9% and 79.5%. EC1 was mainly formed from fuel by pyrolysis at relatively low combustion temperature, while EC2 and EC3 (soot-EC) were formed via gas-toparticle conversion at higher combustion temperature (Han et al., 2007;Watson et al., 1994). At the same engine load as LDG, HDG produced more EC2 because of its higher engine combustion temperature and pressure in the cylinder . ...
... Shorter air-fuel mixing time and lower air-fuel ratio are likely to generate more EC emission as a result of the low oxygen concentration in the cylinder (Karjalainen et al., 2014;Li et al., 2014). As to EC3, the combustion temperature for forming it was relatively high (Watson et al., 1994), and hence EC3 emitted from all vehicles was the smallest part in each size range, accounting for less than 5%. ...
Particles emitted from five typical types of vehicles (including light-duty gasoline vehicles, LDG; heavy-duty gasoline vehicles, HDG; diesel buses, BUS; light-duty diesel vehicles, LDD and heavy-duty diesel vehicles, HDD) were collected with a dilution sampling system and an electrical low-pressure impactor (ELPI+, with particle sizes covering fourteen stages from 6 nm to 10 μm) on dynamometer benches. The mass concentrations and emission factors (EF) for organic carbon (OC) and elemental carbon (EC) were obtained with a DRI Model 2001 thermal/optical carbon analyzer. A respiratory deposition model was used to calculate the deposition fluxes of size-segregated carbonaceous aerosols in human respiratory system. Results indicated that the OC produced from LDG mainly existed in the size range of 2.5–10 μm, while EC from HDG enriched in 0.94–2.5 μm. For diesel vehicles, both OC and EC concentrations peaked at 0.094–0.25 μm. The OC/EC ratios for PM2.5 varied from different types of vehicles, from 0.61 to 8.35. The primary emissions from LDD and HDD exhibited high OC/EC ratios (>3), suggesting that using OC/EC higher than 2 to indicate the formation of secondary organic aerosol (SOA) was not universal. The emission factors for OC and EC of LDG (HDG) in PM10 were 1.78 (3.14) mg km⁻¹ and 0.88 (4.32) mg km⁻¹, respectively. The OC2 and OC3 were the main section (over 60%) of OC emitted from all the five types of vehicles. EC1 was the most abundant EC fraction of LDG (76.9%), while EC2 dominated for other types of vehicles (more than 62%). About 60% of the OC in ultrafine particles could be deposited in the alveoli. Diesel EC mainly could be deposited in the alveolar region. It is necessary to control the emission of ultrafine particles and diesel EC.
... Carbon abundances in each of these fractions differed from carbon sources (8,9) . The abundance of eight carbon fractions in the source sample showed certain character of source composition. ...
... Carbon content in each of these fractions differs by carbon sources (8) . The reason for lower concentrations of OC1 could be associated with the highly volatile nature of this component. ...
... Moreover, the above studies also highlighted a seasonal variability in the OC and EC concentrations in PM 10 , with higher concentrations generally observed during the heating season (Bautista VII et al., 2014;Cao et al., 2004;Chow et al., 2004b;Gu et al., 2010;Watson et al., 1994). For example, both organic and elemental carbon showed elevated winter concentrations at an urbanized monitoring station in Belfast (UK), in agreement with the major local primary emission sources (Jones and Harrison, 2005). ...
... They can also indicate the influence of emissions from local primary sources in the study region (Hoffmann and Warnke, 2007;Klejnowski et al., 2017). Higher EC concentrations in PM 10 usually suggest a significant contribution from the combustion of liquid fossil fuels, particularly from road traffic (Bautista VII et al., 2014;Cao et al., 2004;Chow et al., 2004b;Gu et al., 2010;Watson et al., 1994). Discrepancy in the OC and EC concentrations in PM 10 aerosols may also be attributed to differences in meteorological conditions in the region of measurements. ...
PM10 samples were collected at eight monitoring (urban, industrial and regional background) stations during 2011 in SW Poland (Voivodeship of Lower Silesia) with the objectives of identifying their potential sources, as well as of quantitatively estimating the anthropogenic impact on their carbon content by coupling carbon stable isotope compositions of the total carbon (TC) with organic (OC) and elemental carbon (EC) concentrations. Results showed that (i) the highest OC and EC concentrations measured at the five urban background stations were 11.9 and 1.9 μg m⁻³, respectively, with an average δ¹³CTC of −26.5 ± 1.13‰. Annual average concentrations measured (ii) at the industrial and (iii) the two regional stations were similar for OC (6.9 and 6.4 μg m⁻³, respectively) and EC (0.9 and 0.8 μg m⁻³, respectively) with average δ¹³CTC of −27.4 ± 0.81 and −27.6 ± 0.99‰, respectively. This indicates that similar contamination sources explain the PM10 levels at stations (ii) and (iii), however significantly different from the source(s) influencing station (i). Moreover, using an isotope mass balance that incorporates δ¹³CTC and OC and EC concentrations, we show that while during the heating season coal is the dominant source of aerosol contamination (with contributions ranging from 5.1 to 73.8 μg m⁻³), during the vegetative season road traffic is the dominant one (with contributions ranging from 2.2 to 20.2 μg m⁻³). These large ranges confirm the spatiotemporal heterogeneity of air contamination, even within such a small monitoring area, and should be taken into consideration for future implementation of air quality management measures at larger, e.g. national and international, scales.
... Studies showed that OC1 originated mainly from biomass burning, OC2 from coal combustions and OC3 and OC4 from road dust or gasoline exhaust. Similarly, OPC is predominantly emitted from biomass burning or gasoline exhaust, EC1 from gasoline exhaust and EC2 and EC3 from diesel exhaust [20,49,50]. Table 3 shows the concentrations of eight carbonaceous components in the winters of 2016 and 2020. ...
The goals of the “dual carbon” program in China are to implement a series of air pollution policies to reduce the emission of carbon-bearing particulate matter (PM). Following improvements in the reduction in carbon emissions in Handan City, China, fine particulate matter (PM2.5) was collected in the winters from 2016 to 2020 to characterize the concentrations and sources of carbonaceous components in PM2.5. Trend analysis revealed that both organic carbon (OC) and elemental carbon (EC) concentrations significantly decreased. The proportion of total carbon aerosol (TCA) in PM2.5 decreased by 47.0%, highlighting the effective reduction in carbon emissions. Secondary organic carbon (SOC) concentrations increased from 2016 (12.86 ± 14.10 μg·m−3) to 2018 (36.76 ± 21.59 μg·m−3) and then declined gradually. SOC/OC was larger than 67.0% from 2018 to 2020, implying that more effective synergistic emission reduction measures for carbonaceous aerosol and volatile organic compounds (VOCs) were needed. In the winters from 2016 to 2020, primary organic carbon (POC) concentrations reduced by 76.1% and 87.6% under a light/moderate pollution period (LP) and heavy/severe pollution periods (HPs), respectively. The TCA/PM2.5 showed a decreasing trend under LP and HP conditions, decreasing by 42.1% and 54.7%, respectively. Source analysis revealed that carbonaceous components were mainly from biomass burning, coal combustion and automotive exhaust emissions in the winters of 2016 and 2020. OC/EC and K+/EC analysis pointed out that air pollutant reduction measurements should focus on rectification biomass fuels in the next stage. Compared with 2016, the contributions of automotive exhaust emissions decreased in 2020. OC and EC concentrations decreased due to control measures on automotive exhaust emissions.
... A high proportion of OC1 and OPC in PM 2.5 represent BB (Cao et al., 2005). OC1 and EC3 are mainly derived from motor vehicle emissions, and large abundances of EC2 and EC3 are associated with diesel vehicle emissions (Watson, 1994). OC2 has the highest abundance in coal combustion, followed by OC3, OC4, and EC1 (Cao et al., 2005). ...
... Previous studies have shown that OC1 mainly comes from biomass burning, OC2 mainly originates from coal combustion and atmospheric secondary processing, OC3 comes from gasoline vehicle exhaust, OC4 and EC1 come from coal combustion and gasoline vehicle exhaust, and EC2 and EC3 are derived from diesel vehicle exhaust (Chow et al. 2004;Turpin and Huntzicker 1991;Watson 1994;Zhang et al. 2018). Factors 1 and 2 were dominated by EC3 and EC1 respectively, thus were identified as diesel vehicle emission and gasoline vehicle emission respectively. ...
Domestic heating is an important source of carbonaceous aerosols in northern China in winter. The seasonal variations, sources, and regional transport of carbonaceous species in PM 2.5 in Yuncheng in the winter and summer of 2020–2021 were investigated in this study, with a particular focus on the role of domestic heating. Meanwhile, the pollution characteristics of carbonaceous aerosols in Beijing in winter were also investigated for comparison. The mass concentrations of organic carbon (OC) and elemental carbon (EC) and their contributions to PM 2.5 were significantly enhanced during the heating period compared to other sampling periods in Yuncheng, however, no obvious differences were observed before and during the heating periods in Beijing. Source apportionment results showed that the heating related emission (50.9%) was the dominant source of total carbon in Yuncheng in the heating period, while vehicular emission (49.6%) was dominant in summer. Combing the positive matrix factorization (PMF) and potential source contribution function (PSCF) analysis, it was concluded that both local and regional heating activities contributed highly to carbonaceous aerosols in Yuncheng. It would be therefore of great environmental benefits to promote the clean residential heating transition in Yuncheng and other similar cities.
Graphical Abstract
... OC1 is mainly derived from volatile organic compounds emitted by biomass combustion, motor MA ET AL. (Cao et al., 2005). EC1 is primarily from gasoline exhaust emissions, while EC2 and EC3 are emitted by diesel exhaustion (Duan et al., 2012;Waston et al., 1994). Therefore, it is feasible to use different carbonaceous components to determine the sources of carbonaceous aerosols in marine environment and facilitate the quantification of anthropogenic influences. ...
Based on a shipboard observation conducted in winter 2018, we reported the aerosol chemical properties and their differences in offshore and remote oceans over the Western Pacific Ocean (WPO). It's found that the chemical compositions over the WPO have significant spatial heterogeneity due to the influences of regional transport of anthropogenic aerosols and long‐path transport of dust aerosols. The average concentration of water soluble ions during the whole sampling period followed Cl⁻ > OC > Na⁺ > SO42− ${{\text{SO}}_{4}}^{2-}$ > NO3− ${{\text{NO}}_{3}}^{-}$ > Ca²⁺ > Mg²⁺ > EC > K⁺ > NH4+ ${{\text{NH}}_{4}}^{+}$. Crustal elements of Ca (980.41 ng/m³), Na (971.55 ng/m³), and Al (781.16 ng/m³) were uniformly distributed in offshore area, but high proportion of Na elements dominated in remote regions. The total concentration of heavy metals including Zn, Cu, Cr, Pb and others originating from anthropogenic sources were 208 ng/m³ along the coastal region, about 10 times higher than that of 20.2 ng/m³ in the offshore and remote seas. For the reconstructed components, we found an increase of sea‐salt aerosol ranged from 3% to 72%, and a decrease of black carbon, organic matter and secondary inorganic salts, indicating a transformation from anthropogenic influence to marine environment. The rapidly increased secondary organic matter during dust event revealed that the transport of dust serves as catalysts to promote multi‐phase reactions. Cl⁻ photochemical reaction rate in offshore area was mainly affected by sulfate from anthropogenic emissions, with an average chlorine loss rate of 18%, whereas it was inverse Cl⁻ excess in the remote oceans.
... As previously discussed, two coal-fired heating plants are located in the closest proximity of the study area. However, due to strict controlling regulations regarding their emissions, we hypothesize that their impact may be overprinted by more preponderant emissions such as residential heating or road traffic (Bautista VII et al., 2014;Buch et al., 2021;Cao et al., 2004;Chow et al., 2004;Gu et al., 2010;Watson et al., 1994). Additionnally, the FTIR analysis of the PM 2.5 samples collected in winter (Fig. 3A and B), supports the conclusion that incomplete combustion of fossil fuels is the most probable source of pollution during that season as it shows the presence of both polycyclic aromatic hydrocarbons (PAHs) and aliphatic hydrocarbons (n-alkanes) (Górka et al., 2014). ...
... Although the thermal fractions were originally intended to reduce the OP correction, early source characterization studies (e.g., Chow et al., 2003;Chow et al., 2004b;Watson et al., 1994) found that their abundances could be indicative of different source types, such as engine exhaust, vegetative burning, and fugitive dust. As a result, these fractions were added to the OC and EC reporting on ambient and source characterization studies and efforts were made to assure their comparability across changes in instruments and procedures over the past four decades. ...
... OC1 is the marker of biomass burning; OC3 and EC1 are the indicators of the exhaust gas of gasoline-powered vehicles (Cao et al., 2005). EC3 is a marker for diesel vehicle emission (Watson et al., 1994). Therefore, Factor 1 is characterized as vehicle and biomass burning emissions. ...
Samples of PM 2.5 are collected and analyzed in the urban areas of Lahore, Pakistan, during the sampling periods of the winter and summertime. The mass concentrations of PM 2.5 and its carbonaceous species (OC and EC) show a significant variation during both sampling periods. The mean OC concentration in winter and summertime are 50.7 ± 30.5 µg/m ³ , and 14.6 ± 5.6 µg/m ³ , whereas EC concentrations are 26.5 ± 18.0 µg/m ³ and 8.6 ± 3.4 µg/m ³ , respectively. In the winter and summertime, the OC/EC average ratios reported are 2.1 and 1.9, respectively. There is a strong OC-EC correlation in the wintertime, indicating that they have a common source. The weak OC-EC correlation in the summertime is attributed to increased biogenic emissions and secondary organic aerosol formation through photochemical processes. Secondary organic carbon (SOC) contributes 16.7% of organic carbon in the winter and 22.6% in the summertime sampling. The exposure risk of EC is estimated based on inhalation dose. The higher exposure risk of EC inhalation in winter can adversely affect human health. According to principal component analysis (PCA), the major sources of the carbonaceous species of PM 2.5 at Lahore included vehicle emission, secondary organic aerosol formation, emissions from combustion sources, and dust. The potential source contribution function (PSCF) and trajectory cluster analysis also demonstrated that the high concentrations of PM 2.5 and its carbonaceous species in Lahore resulted from regional and local pollution sources.
... The contents of eight carbonaceous components (OC1, OC2, OC3, OC4, EC1, EC2, EC3, and OP) in PM 2.5 samples were obtained using TOR method, and the abundances of these carbonaceous components can represent the source spectrum to a certain extent. Previous studies have shown that OC1 mainly comes from biomass combustion; abundant OC2 can be found in coal burning sources; OC3 and OC4 are rich in road dust; abundant EC1 and OP can be found in gasoline vehicle exhaust, and EC2 and EC3 represent the source of diesel exhaust Li and Bai 2009;Watson et al., 1994). ...
... Therefore, these EC fractions may have different formation pathways during combustion. Furthermore, the contents of these subfractions of EC from different sources can be very different; 17 these are significantly correlated with the fuel type and combustion condition. 18 Han et al. 19 found that biomass char contains more heat-labile EC fractions, which are oxidized first at relatively low temperatures, than that in vehicle-emitted soot. ...
... Speciated data are used from the PM 2.5 samples, with water-soluble ions (e.g., SO 4 2− , NO 3 − ) detected via ion chromatography, elements from sodium (Na) to manganese (Mn) measured with particle-induced X-ray emission (PIXE), and elements ranging from iron (Fe) to lead (Pb) detected with X-ray fluorescence (XRF). Organic carbon (OC) and elemental carbon (EC) were measured with a thermal optical reflectance method of carbon analysis [26,27]. We report IMPROVE concentrations for fine soil in the PM 2.5 fraction, which are calculated using this equation [25], supported by earlier analysis of local soils and ambient aerosol particles [28,29] ...
A significant concern for public health and visibility is airborne particulate matter, especially during extreme events. Of most relevance for health, air quality, and climate is the role of fine aerosol particles, specifically particulate matter with aerodynamic diameters less than or equal to 2.5 micrometers (PM2.5). The purpose of this study was to examine PM2.5 extreme events between 1989 and 2018 at Mesa Verde, Colorado using Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring data. Extreme events were identified as those with PM2.5 on a given day exceeding the 90th percentile value for that given month. We examine the weekly, monthly, and interannual trends in the number of extreme events at Mesa Verde, in addition to identifying the sources of the extreme events with the aid of the Navy Aerosol Analysis and Prediction (NAAPS) aerosol model. Four sources were used in the classification scheme: Asian dust, non-Asian dust, smoke, and “other”. Our results show that extreme PM2.5 events in the spring are driven mostly by the dust categories, whereas summertime events are influenced largely by smoke. The colder winter months have more influence from “other” sources that are thought to be largely anthropogenic in nature. No weekly cycle was observed for the number of events due to each source; however, interannual analysis shows that the relative amount of dust and smoke events compared to “other” events have increased in the last decade, especially smoke since 2008. The results of this work indicate that, to minimize and mitigate the effects of extreme PM2.5 events in the southwestern Colorado area, it is important to focus mainly on smoke and dust forecasting in the spring and summer months. Wintertime extreme events may be easier to regulate as they derive more from anthropogenic pollutants accumulating in shallow boundary layers in stagnant conditions.
... Different and significant correlations of OC and EC fractions with δ 13 C TC indicate different sources for individual fractions. In the case of fractions EC1 and EC2 (which also include most PC), probable sources are emissions from biomass burning (Chuang et al., 2013), while in the case of high-temperature EC3 and EC4, probable sources are high-temperature processes, e.g., diesel emissions (Watson et al., 1994). Jung and Kawamura (2011) successfully used a comparative analysis of δ 13 C TC with the proportion of OC fractions to distinguish aerosol episodes. ...
Isotope fractionation between the gas and aerosol phases is an important phenomenon for studying atmospheric processes. Here, for the first time, seasonally resolved stable carbon isotope ratio (δ¹³C) values are systematically used to study phase interactions in bulk aerosol and gaseous carbonaceous samples. Seasonal variations in the δ¹³C of total carbon (TC; δ¹³CTC) and water-soluble organic carbon (WSOC; δ¹³CWSOC) in fine aerosol particles (PM2.5) as well as in the total carbon of part of the gas phase (TCgas; δ¹³CTCgas) were studied at a suburban site in Prague, Czech Republic, Central Europe. Year-round samples were collected for the main and backup filters from 14 April 2016 to 1 May 2017 every 6 days with a 48 h sampling period (n = 66). During all seasons, the highest ¹³C enrichment was found in WSOC, followed by particulate TC, whereas the highest ¹³C depletion was found in gaseous TC. We observed a clear seasonal pattern for all δ¹³C, with the highest values in winter (avg. δ¹³CTC = -25.5 ± 0.8‰, δ¹³CWSOC = -25.0 ± 0.7‰, δ¹³CTCgas = -27.7 ± 0.5‰) and the lowest values in summer (avg. δ¹³CTC = -27.2 ± 0.5‰, δ¹³CWSOC = -26.4 ± 0.3‰, δ¹³CTCgas = -28.9 ± 0.3‰). This study supports the existence of different aerosol sources at the site during the year. Despite the different seasonal compositions of carbonaceous aerosols, the isotope difference (Δδ¹³C) between δ¹³CTC (aerosol) and δ¹³CTCgas (gas phase) was similar during the seasons (year avg. 1.97 ± 0.50‰). Moreover, Δδ¹³C between WSOC and TC in PM2.5 showed a difference between spring and winter, but in general, these values were also similar year-round (year avg. 0.71 ± 0.37‰). During the entire period, TCgas and WSOC were the most ¹³C-depleted and most ¹³C-enriched fractions, respectively, and although the resulting difference Δ(δ¹³CWSOC − δ¹³CTCgas) was significant, it was almost invariant throughout the year (2.67 ± 0.44‰). The present study suggests that the stable carbon isotopic fractionation between the bulk aerosol and gas phases is probably not entirely dependent on the chemical composition of individual carbonaceous compounds from different sources.
... They are also increasing in areas of heavy traffic. In general, both OC and EC are characterized by higher concentrations near traffic routes than in rural or industrial areas [42][43][44][45]. When the OC/EC value is between 2.6 and 6.0, the organic carbon comes from the combustion of fossil fuels [43]. ...
The aim of this study was to determine the influence of transport on the concentration of carbon species in aerosols collected in the coastal zone of the Gulf of Gdansk in the period outside the heating season. Elemental carbon (EC), organic carbon (OC), and the ΣPAHs5 concentrations were measured in aerosols of two size: <3 μm (respirable aerosols) and >3 μm in diameter (inhalable aerosols). Samples were collected between 13 July 2015 and 22 July 2015 (holiday period) and between 14 September 2015 and 30 September 2015 (school period). In both periods samples were taken only during the morning (7:00–9:00 a.m.) and afternoon (3:00–5:00 p.m.) road traffic hours. The highest mean values of the ΣPAHs5 and EC were recorded in small particles during the school period in the morning road traffic peak hours. The mean concentration of OC was the highest in small aerosols during the holiday period. However, there were no statistically significant differences between the concentrations of organic carbon in the morning and afternoon peak hours. Strict sampling and measurement procedures, together with the analysis of air mass backward trajectories and pollutant markers, indicated that the role of land transport was the greatest when local to regional winds prevailed, bringing pollution from nearby schools and the beltway.
... The high levels of OC2, OC3, OC4, OP, and EC1 were observed in the winter season, which suggests the emission from a combination of various sources such as automobiles, biomass burning, and coal combustion [73]. Further, a slight increase in the concentrations of EC2 and EC3 was observed during postmonsoon and winter seasons, which indicates the emission of these carbon subfractions from diesel vehicles [74]. ...
Seasonal variation in the concentration of Organic Carbon (OC) and Elemental Carbon (EC) was investigated in PM1 size fraction over a residential area in Delhi, India. The sampling was carried out using a cascade impactor from April 2018 to March 2019. The OC/EC content in the sample was measured by a carbon analyzer (Thermal/Optical, DRI 2001). The annual average concentration of OC and EC was found to be 28.01 ± 14.61 μg/m³ and 10.40 ± 7.41 μg/m³, respectively in PM1 (139.52 ± 49.20 μg/m³). The highest concentrations of OC and EC were observed in the post-monsoon and winter season, respectively. Average OC & EC concentrations in summer, monsoon, post-monsoon, and winter seasons were found to be 22.57 ± 3.72 & 5.51 ± 1.28, 11.70 ± 3.07 & 3.60 ± 0.39, 42.06 ± 7.10 & 11.72 ± 2.45 and 37.28 ± 14.45 & 18.52 ± 6.23 µg/m³, respectively. Total carbonaceous material (TCM) accounted for approximately 40% of PM1 concentration. The annual average OC/EC ratio was observed to be 2.69, which ranged between 1.77 to 5.39. Analysis of carbon subfractions reveals OC3 and EC1 as the dominant fraction suggesting fossil fuel combustion as dominant emission sources. The exposure risk estimated on the basis of inhalation dose was observed very high during the winter season which can adversely affect the health of people. This study also revealed that the emissions from the residential area are the key source of OC and EC, along with PM1.
... Cabada et al. (2002) indicated that EC from wood burning profiles presented in the literature varied in accordance with the nature of the wood consumed and the characteristics of combustion. Watson et al. (1994) also reported that species discharged from motor vehicles were highly variable and dependent on the vehicle, fuel used and operating mode. While caution is advised regarding the use of OC and EC ratios for source identification purposes, the breakdown of these compounds into additional temperature-dependent carbon fractions (such as those provided by the TOR method) has proved useful Lowenthal and Rahn, 1987). ...
... Cabada et al. (2002) indicated that EC from wood burning profiles presented in the literature varied in accordance with the nature of the wood consumed and the characteristics of combustion. Watson et al. (1994) also reported that species discharged from motor vehicles were highly variable and dependent on the vehicle, fuel used and operating mode. While caution is advised regarding the use of OC and EC ratios for source identification purposes, the breakdown of these compounds into additional temperature-dependent carbon fractions (such as those provided by the TOR method) has proved useful Lowenthal and Rahn, 1987). ...
... The comparison between multi-datasets revealed that the total concentration of OC via anthropogenic and biomass burning has a huge difference (Fig. 1). The anthropogenic emission of OC reaches 1.2 × 10 2 Tg/year (MACCity), 4.00 × 10 1 Tg/year (ACCMIP), and 1.20 × 10 2 Tg/year (RCP 8.5), suggesting the difference in the efficiency of multisatellite datasets (Ellis and Novakov 1982;Watson et al. 1994). Similar trends were also recorded for NO 2 through multisensory over Pakistan (Murtaza et al. 2018). ...
Organic carbon (OC) is the amount of carbon found in an organic compound. Once entered, the environment OC may cause climate change and effects on public health. The objective of the study was to assess the spatio-temporal trends of OC, climatology, and to develop inventories. The three satellite datasets (MACCity, ACCMIP, RCP 8.5) showed significant different trends in OC levels. Results indicated significantly higher trends in OC distribution during anthropogenic activities and the industrial era as compared with natural sources and the pre-industrial era. The residential and industrial sectors showed higher emission of OC 1.0 × 10−5to 2.5 × 102 Tg/year, respectively as compared with other sectors. Spatial distribution of OC revealed higher levels in bigger cities (Islamabad, Lahore, Karachi, Multan, Punch, and Mardan districts) of Pakistan. The temporal analysis shows irregular increasing trends in OC distribution with the passage of time. Principal component analysis (PCA) revealed that residential OC showed a positive correlation with surface temperature, wind and heat and OC transport, sum, residential, and energy sector with relative humidity in MACCity and RCP 8.5 datasets, respectively. The study indicated that savanna burning and residential sectors were a major contributor to the level of OC. The results will be helpful for the government to devise policies regarding OC management.
... For example, the clear dominance of the EC2 and EC3 fractions could indicate that the important pollution sources in analyzed areas were diesel vehicle exhaust, while gasoline exhaust emissions contributed less to carbonaceous aerosol in the air [18]. In other papers, it was pointed out that diesel emissions were identified based on the high contribution of high-temperature components of EC (EC3, EC4) [86,87]. In turn, in [32] it was also noted that gasoline emissions could also be responsible for high shares of the EC1-EC3 fractions. ...
The purpose of this study is to obtain a detailed picture of the spatial and seasonal variability of carbonaceous matter in southern Poland. Particulate matter (PM) samples from eight selected urban and rural background sites were analyzed for organic carbon (OC) and elemental carbon (EC) (thermal-optical method, “eusaar_2” protocol), and the content of secondary (SOC) and primary organic carbon (POC) was estimated. The OC and EC dynamics were further studied using each of the thermally-derived carbon fractions (OC1–4, PC, and EC1–4). Clear spatiotemporal variability of carbonaceous compounds concentrations was observed, with higher levels recorded during the heating season. The considered measurement sites differed particularly in the shares of SOC and POC, with higher values of POC contents especially in rural areas. In terms of the content of carbon fractions, the analyzed sites showed roughly the same characteristics, with PC, OC4, and OC2 as dominant fractions of OC and with clear dominance of EC3 and EC2 over other EC fractions. The results obtained as part of this work may be a valuable source of information about the actual status of the carbonaceous matter, which remains one of the least known components of atmospheric PM.
... Cette variabilité est présentée dans le tableau I.6. On note par exemple que les rapports OC/EC des émissions par la combustion de bois ou de fabrication de charbon de bois sont compris entre 9 et 17 alors que ceux liés aux émissions par les véhicules diesel sont de l'ordre de 2. Les véhicules légers à essence ont un rapport plus élevé compris entre 2,2 et 4,1 (Watson et al., 1994 ;Schauer et al., 2002a). Il est intéressant de mentionner que ce rapport est plus élevé pour des véhicules non catalysés. ...
Cette thèse s'inscrit dans les objectifs scientifiques du programme DACCIWA-WP2. Il s'agit d'établir un lien entre émissions, pollution atmosphérique et effets sur la santé humaine en termes d'inflammation du système respiratoire pour des sources de combustions urbaines, typiques d'Afrique de l'Ouest : trafic, feux domestiques et feux de décharge à Abidjan (Côte d'Ivoire) et à Cotonou (Bénin) pendant les saisons sèches et humides 2015-2017. Nos résultats montrent que les concentrations particulaires observées sur l'ensemble des sites dépassent largement les recommandations de l'OMS. Le site influencé par les feux domestiques est le site le plus pollué, dominé par une fraction importante de particules ultrafines (UF) et fines (F). La comparaison des sites trafic révèle que les concentrations moyennes pour chaque classe de taille sont plus élevées d'un facteur deux à Cotonou qu'à Abidjan. La caractérisation physicochimique de ces particules (carbone organique, carbone élémentaire, carbone organique soluble, ions, poussières, éléments traces) souligne que le carbone organique et les poussières sont les deux plus importants contributeurs pour les particules de taille fine et ultrafine avec plus de carbone organique à Abidjan et de poussières à Cotonou respectivement. Des études biologiques ont été menées en parallèle afin d'évaluer la réponse pro-inflammatoire induite par les particules prélevées sur chaque site, en quantifiant la libération de la cytokine IL-6 par des cellules épithéliales bronchiques humaines. Il en résulte que les particules provenant du site feu domestique sont les plus pro-inflammatoires toutes saisons confondues alors que les fractions fines et ultrafines des particules des deux sites trafic provoquent des effets comparables non négligeables à chaque saison, le site de Cotonou se démarquant par la réactivité de sa fraction grossière, liée à la présence de poussières. Les particules F et UF des sources de combustion semblent donc avoir un impact important. Ceci est confirmé par l'analyse croisée entre les données physicochimiques et toxicologiques qui montre que la composante carbonée de l'aérosol (EC, OC, WSOC) est la mieux corrélée au biomarqueur IL-6. Ce résultat nous permet de dresser des cartes régionales d'impact inflammatoire lié aux particules carbonées et à leurs sources d'émission. Ces études permettront à terme de mettre en place des solutions de réduction des émissions pour améliorer qualité de l'air et santé.
... This occurrence has been found in other areas, including during summer in southern California and seasonally in the southeastern U.S. (Novakov et al. 1972;Hidy et al. 2014). Other possible sources include SO 2 adsorbed onto, or non-extractable from, diesel exhaust particles (Watson et al. , 1994. Since wood burning produces traces of volatile or semivolatile species that can produce OC in air (e.g., McDonald et al. 2000), the non-sulfate component could be linked with VOC oxidation in the presence of water, and acidity to produce organosulfate esters (Hallquist et al. 2009;Surratt et al. 2007;Carlton et al. 2018). ...
Characterizing the origins and variability of urban haze involves integration of pollution source emissions, meteorological and atmospheric aerosol processes. Studies of these elements require spatial and temporal measurements relevant to appearance and disappearance of haze. One of the first of such studies was implemented in Denver, Colorado (USA), setting an example for follow-on efforts throughout the world. This winter 1978 campaign employed six ground stations and mid-day aircraft observations, supplemented with boundary layer meteorological observations and emissions data. Aerosol measurements employed 4-h sampling for mass concentration and composition. Results include a spatial and temporal interpretation of the observations, complementing results reported from a location NNE of the city. Fine, not coarse, particles were responsible for Denver’s “Brown Cloud”. Fine particles were composed of a mixture from local sources of carbon, dust, and atmospheric chemical reactions, especially SO2 and NOx oxidation, which is common knowledge today, but was unknown at the time. The distribution of particles varied with winds and inversion conditions. Receptor modeling found that light extinction depended on carbonaceous combustion byproducts from motor vehicles, power plants, industrial operations and residential activity. Subsequent studies of Denver’s winter haze showed similar source apportionment of extinction even with major reductions in emissions.
... The carbon components were mainly divided into OC (OC1, OC2, OC3, OC4) and EC (EC1, EC2, EC3), and different components also represent different sources of pollution. According to previous research, OC1 mainly comes from biomass combustion, OC2 mainly comes from coal combustion, OC3 and OC4 mainly comes from road dust, and EC1 mainly comes from automobile exhaust, EC2 and EC3 mainly comes from diesel emissions [41][42][43][44]. ...
A low-vol sampler was used to collect PM2.5 samples for half-year in three sampling sites, including industrial park (A1), school (A2), factory (A3) in Shihezi, China. The result showed that the high levels of Na+ and K+ were likely originate from burning Zhundong coal. In general, the atmospheric aerosol of A1, A2 and A3 was alkaline. Most of the OC (organic carbon)/EC (element carbon) values were greater than 2.2, which indicated that there was significant secondary pollution. In the carbon component analysis, the values of OC1, EC2 and EC3 were significantly lower than OC2, OC3, OC4 and EC1. In addition, OC2 accounts for the largest proportion of OC. Combined with the source analysis of water-soluble ions, carbon component and HYSPLIT Trajectory Model, the main sources of Shihezi were local coal-fired emissions, road dust and car exhaust, and pollutants transmitted from western cities. This study provides a basis for investigating the pollution sources of PM2.5 and the influence of Zhundong coal combustion in Shihezi in the future.
... Carbonaceous aerosols make up a substantial fraction of atmospheric particulate loading, ranging from averages of about 60% in parts of the western United States to 25-40% in the East (Hand et al., 2013;Malm et al., 2017). Typically, carbonaceous aerosols are categorized into operationally defined organic carbon (OC) and elemental carbon (EC) components and sometimes inorganic carbon in the form of calcium carbonate (Cao et al., 2003;Chow et al., 1993Chow et al., , 2005Chow et al., , 2006Watson et al., 1994Watson et al., , 2005Yu et al., 2002), all of which are of interest because of differing health, climate forcing, and visibility effects. In the literature, EC, black carbon (BC), soot, and light absorbing carbon (LAC) have often been used interchangeably (Bond & Bergstrom, 2006), although Petzold et al. (2013) have recommended terminology to clarify the terms used in atmospheric research. ...
The thermal evolution procedure used by most monitoring programs in the United States to determine carbonaceous aerosol concentrations is referred to as the thermal‐optical reflectance method, where an aerosol sample that has been collected on a quartz filter is heated and evolved carbon is characterized as either organic (OC) or light absorbing carbon (LAC). Evolved carbon assigned to OC is multiplied by a factor, Roc, to achieve an estimate of organic mass. Over the last 10–15 years, Roc, estimated through multiple linear regression analysis of data collected in the Interagency Monitoring of Protected Visual Environments (IMPROVE) program, has increased at about a rate of about 0.02 per year, reaching values above 2.0 in many regions of the United States. Analysis of evolved carbon concentration temporal trends suggests that thermal‐optical reflectance analysis, on the average, inaccurately bifurcates particulate carbon into the OC and LAC fractions with some LAC being inadvertently and wrongly assigned to the OC fraction. It is shown that misapportioned LAC assigned to OC is decreasing faster than true OC, resulting in a compensating increase in the Roc assigned to reported OC over time. A first‐order model is proposed to correct for the misapportioned carbon.
... Similar trends (reduction in H-VS and increase in non-VS due to increase in engine load) were also found in the literature using diesel, biodiesel and DBE Tse and Kyprianidis, 2016;Lu et al., 2012a;Mustafi et al., 2010). The rise in engine load (or speed) causes to increase in combustion temperature resulting in more gas-to-particle conversion of EC (Watson et al., 1994;Han et al., 2007) which leads to increase in non-VS and decrease in H-VS. In addition, less availability of oxygen at higher engine load (or speed) due to lower air-fuel ratio also causes suppress the oxidation of EC (Li et al., 2014), resulting in increase in non-VS and decrease in H-VS. ...
The present experimental study aims to examine the impacts of various fueling modes of operation on the particle-phase polycyclic aromatic hydrocarbons (PAHs) and n-alkanes (C16-C30), and volatility and oxidation reactivity of particulate matter (PM) emitted from a diesel engine fueled with a ternary fuel (80% diesel, 5% biodiesel and 15% ethanol (D80B5E15, volume %)) under four engine operating conditions. Four fueling modes, including diesel, blended, fumigation and combined fumigation + blended (F + B) modes were tested using pure diesel fuel for diesel mode and a constant fuel content of D80B5E15 for the blended, fumigation and F + B modes to create the same condition for comparing their impacts on the parameters investigated. The average results illustrate that both blended and fumigation modes can reduce the PAHs (-78.4% and -31.3%), benzo[a]pyrene equivalent (-81.7% and -38.9%), n-alkanes (-46.5% and -21.5%) and non-volatile substance fraction (-25.1% and -11.1%), but increase the high-volatile substance fraction (12.8% and 6.9%) and oxidation reactivity rate (34.0% and 4.9%), respectively compared to those of the diesel mode. While the effect of the blended mode on the parameters investigated is stronger than the fumigation mode. And the F + B mode has the effects in between the results of the blended and fumigation modes.
... EC1 is defined as char-EC and directly formed via the fuel pyrolysis at a relatively low ambient temperature, while EC2 + EC3 is defined as soot-EC and derived from gasto-particle conversion at high ambient temperature. 31,32 Therefore, the higher fuel injection mass and more local fuel-rich regions, as well as a higher ambient temperature at a high load could produce more EC. It can be found that the proportion of soot-EC increases faster. ...
Particulate matter (PM) emissions from ships are increasingly exposing the health risks for population living along coastal areas. However, studies on the characteristics of particulate emissions from ships fueled with heavy fuel oil (HFO) are quite rare yet. In this paper, the characteristics of PM sampled from the exhaust of a low-speed two-stroke common-rail marine diesel engine fueled with HFO are investigated at different loads. The thermal/optical carbon analyzer was employed to discriminate the elemental and organic carbons (EC and OC), the combustion-based elemental analysis was performed to obtain the C/H ratio, and the nuclear magnetic resonance spectrometer was used to analyze the molecular structure in the sample. Increasing loads, the EC/OC and C/H mass ratios, and the mole ratio of polycyclic aromatic hydrocarbons (PAHs) to aliphatic hydrocarbons increase. From transmission electron microscopy (TEM) images, noticeable changes of soot particles in nanostructure, size, morphology and nanostructural parameters were analyzed. Furthermore, the elemental spatial distribution in soot particles was observed by the energy dispersive X-ray spectroscopy (EDS) mapping. The main elements were detected by the point- analyzed spectra. These results are believed to be valuable references for hazard evaluation and building strategy of reducing particulate emissions from low-speed marine diesel engines.
Before and during the COVID-19 outbreak in the heated winter season of 2019, the carbonaceous fractions including organic carbon (OC), elemental carbon (EC), OC1-4, and EC1-5 were investigated between normal (November 1, 2019, to January 24, 2020) and lockdown (January 25, to February 29, 2020) periods in polluted regions of northern Henan Province. In comparison to urban site, four rural sites showed higher concentrations of carbonaceous components, especially secondary OC (SOC); the concentration of SOC in rural sites was 1.5-3.4 times that in the urban site. During the lockdown period, SOC in urban site decreased slightly, while it increased significantly in rural sites. NO2 has a significant effect on SOC generation, particularly in normal period when NO2 concentrations were high. Nevertheless, NO2 significantly decreased, and the elevated O3 (increased by 103-138%) contributed considerably to the generation of SOC during lockdown. Relative humidity (RH) promoted SOC production when RH was below 60%, but SOC was negatively correlated or uncorrelated with RH when RH exceeded 60%. Additionally, RH has a more pronounced effect on SOC during lockdown. The contribution of gasoline vehicle emissions decreases significantly in both urban and rural sites (3-12%) due to the significant reduction of anthropogenic activities during lockdown, although the urban site remained with the biggest contributions (37%). These results provide innovative insights into the variations in carbonaceous aerosols and SOC generation during the unique time when anthropogenic sources were significantly reduced and illustrate the differences in pollution characteristics and sources of carbonaceous fractions in different environments.
Fine particulate matter (PM2.5) significantly impacts global air quality and human health due to its smaller particle size and larger specific surface area. Nitrogen and carbon aerosols, as the main components of PM2.5, play key roles in air pollution. This study identified the sources and seasonal variation of nitrogen and carbon aerosols in PM2.5 in typical cities of Zhejiang. The annual average PM2.5 concentrations of Hangzhou (HZ), Ningbo (NB), and Huzhou (HUZ) were 39.8 ± 19.1 μg m−3, 40.0 ± 21.5 μg m⁻³, and 50.1 ± 22.6 μg m⁻³, respectively, which exceeded the Chinese air quality limit of 35.0 μg m⁻³. The results showed that the concentrations of nitrogen aerosols (NO3⁻ and NH4⁺) in water-soluble inorganic ions were higher at 9.6 ± 4.6 μg m⁻³, 9.0 ± 4.5 μg m⁻³ and 11.5 ± 5.4 μg m⁻³ in HZ, NB and HUZ, respectively, especially in winter, accounting for over 60% of the total. The annual average δ¹⁵N values of PM2.5 were 6.2 ± 1.9‰, 6.4 ± 2.2‰ and 6.7 ± 1.9‰ in HZ, NB and HZ, respectively; the δ¹⁵N values in winter were relatively low. A Bayesian isotopic mixing model was employed to analyse the sources of nitrogen aerosols in winter; the results showed that nitrogen concentration was mainly affected by NH3 and NOX emitted by motor vehicle exhaust, coal combustion, biomass combustion, biogenic soil emissions, animal wastes and ocean evaporation (NB). In addition, the carbon component analysis of PM2.5 showed that the annual average mass concentration of TC accounted for 18.7%, 16.4% and 20.1% of PM2.5 in HZ, HUZ and NB, respectively. The same isotope model was used to analyse the sources of carbon aerosols; the results showed that carbon aerosols were mainly affected by the sources of motor vehicle exhaust, coal combustion, biomass combustion and dust. In the PM2.5 in Zhejiang, the most contributory sources of nitrogenous aerosols and carbon aerosols were motor vehicle exhaust sources.
Solid fuel is the most widely used energy source for cooking and heating in the rural households in developing countries. In this study, emissions from 13 fuel–stove combinations were studied in two typical rural villages in the Fenhe Basin, Shanxi Province, China. This study gathered data on the emission characteristics of particles with an aerodynamic diameter of ≤2.5 μm (PM2.5), organic carbon (OC), elemental carbon (EC), and 21 parent and oxygenated polycyclic aromatic hydrocarbons (pPAHs and oPAHs, respectively); the mechanism of gas formation was also determined. The PM2.5 EFs of biomass burning ranged from 4.11 ± 2.12 to 138 ± 47.2 g/kg, which was higher than that of coal combustion (1.57 ± 0.89 to 4.11 ± 0.63 g/kg). Notably, the average PM2.5 EFs of biomass burning in a traditional stove and elevated kang were 50.9 ± 13.8 and 23.0 ± 3.99 g/kg, respectively, suggesting that the elevated kang had superior emission mitigation. Wood pellet burning in a biomass furnace yielded lower PM2.5 EFs than firewood burning in the biomass furnace, which demonstrated wood pellet combustion's superior emission reduction effect. The relative contribution of OC4 to OC subfractions may be useable as tools for identifying the sources of coal and biomass burning. Regarding PAHs, biomass with abundant lignin pyrolysis produced numerous hydroxyl radicals that were conducive to the release of greater proportions of oPAHs. By contrast, pPAHs had greater relative contributions in coal combustion. Regarding gaseous pollutants, its formation mechanism varied with combustion phase. Emission differences between the two phases were mainly determined by the relative contributions of volatile C/N and char. Clarifying the pollutant formation mechanism can better guide the implementation of emission control from household solid fuel combustion.
Alcohol fuels can effectively reduce particle emissions of diesel engines. However, the effects of lower and higher alcohols on the microscopic physicochemical properties of the particles, such as the graphitization degree, surface aliphatic C–H functional groups, O/C ratio, and the carbon atom hybridization is still unclear. Moreover, the relationship between microscopic physicochemical properties and particle oxidation activity has not been systematically studied. Therefore, the alcohol-diesel mixtures with different carbon chain lengths and the same oxygen content were used as the fuel for commercial diesel engines in this research, such as methanol/diesel mixture (M10), n-butanol/diesel mixture (NB25), and n-octanol/diesel mixture (NO45), and the pure diesel (D100) was used as a reference. The physicochemical properties of different fuel particles under two loads were analyzed using Raman spectroscopy, Fourier Transform Infrared, and X-ray photoelectron spectroscopy. The results showed that as the load increased, the AD1/AG of the particles decreased, which meant that the graphitization degree increased. Moreover, the addition of alcohol fuel will increase the graphitization degree of the particles. In addition, the addition of alcohol fuel will reduce the aliphatic C–H functional groups and the O/C ratio on the surface of the particles. However, with the use of M10 to NO45, the aliphatic C–H functional groups continued to increase, while the O/C ratio first decreased and then increased, and the NB25 particle had the smallest O/C ratio. Through the Partial Least Square analysis, it was found that the fringe length and fringe separation distance had the most significant impact on the activation energy of the particles. Interestingly, among the characteristic parameters of Raman spectroscopy, the D1-full width at half maximum had the largest contribution to the activation energy.
Seventy-seven PM2.5 samples were collected at an urban site (Chongqing University Campus A) in October 2015 (autumn), December 2015 (winter), March 2016 (spring), and August 2016 (summer). These samples were analysed for organic carbon (OC), elemental carbon (EC), and their associated char, soot, 16 PAHs, and 28 n-alkanes to trace sources, and atmospheric transport pathways. The annual average of OC, EC, char, soot, ΣPAHs, and Σn-alkanes were 20.75 μg/m³, 6.18 μg/m³, 5.43 μg/m³, 0.75 μg/m³, 38.29 ng/m³, and 328.69 ng/m³, respectively. OC, ΣPAHs, and Σn-alkane concentrations were highest in winter and lowest in summer. EC, char, and soot concentrations were highest in autumn and lowest in winter. Source apportionment via positive matrix factorization (PMF) indicated that coal/biomass combustion-natural gas emissions (23.8%) and motor vehicle exhaust (20.2%) were the two major sources, followed by diesel and petroleum residue (21.1%), natural biogenic sources (17.7%), and evaporative/petrogenic sources (17.2%). The highest source contributor in autumn and winter was evaporative/petrogenic sources (30.6%) and natural biogenic sources (34.5%), respectively, whereas diesel engine emission contributed the most in spring and summer (32.1% and 38.0%, respectively). Potential source contribution function (PSCF) analysis identified southeastern Sichuan and northwestern Chongqing as the major potential sources of these pollutants. These datasets provide critical information for policymakers to establish abatement strategies for the reduction of carbonaceous pollutant emissions and improve air quality in Chongqing and other similar urban centres across China.
Evaluation of applied emission control programs for ambient air quality improvement in the short term is important for timely policy adjustment and air quality protection. However, this is generally a non-trivial task because of the possible contribution of various factors, such as the regional background effect, meteorological impact, and other source impacts, which must be quantified and eliminated from the observed concentration changes. In this study, we developed an ensemble assessment approach employing multiple methods: spatiotemporal analysis, wind pollution decomposition (WPD) analysis, elemental carbon (EC)-WPD hybrid analysis, and air quality modelling. By combining these methods, we showed that the contributions of different factors could be resolved, and the combined results of all methods formed a consistent result clearly demonstrating that a significant reduction in NOx (112.4 ± 25.9 μg/m³ reduction), NO2 (31.5 ± 6.0 μg/m³ reduction), and PM10 and PM2.5 (reduced by 6.8 μg/m³ and 4.5 μg/m³, respectively) occurred due to the impact of the applied control programs. This study could serve as a springboard for future vehicular emission control strategies in Hong Kong in the near future. Moreover, this holistic analysis could also provide an independent method for estimating the emission control impact in other megacities.
Heavy fuel oil (HFO) accounts for approximately 80% of the fuel consumption of ocean-going ships in the world. Multiple toxic species are found in HFO exhaust, however, carbonaceous substances emitted from low-speed marine engine exhaust at different operating loads have not been thoroughly addressed. Therefore, a bench test for a low-speed marine engine with HFO fuel under different operating modes was carried out in this study. Emission factors and characteristics of CO2, CO, OC, EC, as well as OC and EC fragments, organic matters of n-alkanes and PAHs are given and discussed. Combined with the correlation analysis results among the measured species and engine technical parameters, the formation processes and influence factors of carbonaceous components are also inferred in this study. Besides, together with OC to EC ratio, n-alkanes to PAHs ratio, etc., char-EC to soot-EC ratio in PM can be considered as tracer characteristic of high-sulfur-content HFO ship distinguished from diesel fuel ships. Profiles of n-alkanes and PAHs in PM can be used to distinguish shipping emission source from other combustion sources. Moreover, characteristics of carbonaceous components in size-segregated particles are also discussed, including OC, EC, OC and EC fragments, as well as organic matters. Results show that most of the particle mass, OC, EC, and organic matters are concentrated in fine particles with size of less than 1.1 μm, indicating the significance of ultrafine particles. Formation processes of OC and EC fragments, char-EC and soot-EC are also deduced and proved combined with the characteristics of OC and EC fragments, organic matters, and especially PAHs. Besides, the large variations of OC to EC ratios and speciated profiles of n-alkanes and PAHs in different particle size bins indicate that particle size should be considered when they are used as characteristic tracer in source apportionment studies.
The present study was carried out to investigate the seasonal variation of organic carbon (OC) and elemental carbon (EC) in PM1 during 2018–2019 in the industrial area of Delhi, India. A cascade impactor was used to collect aerosol particles in four different size fractions (≥ PM10, PM2.5–10, PM2.5–1, ≤ PM1). The OC/EC analysis was performed by thermal/optical carbon analyzer (DRI 2001). The highest concentration of aerosol particles was observed in PM1 among four different size fractions (≥ PM10: 37.77 ± 16.07 µg/m3, PM2.5–10: 90.28 ± 41.84 µg/m3, PM2.5–1: 81.65 ± 43.85 µg/m3, and ≤ PM1: 151.75 ± 58.57 µg/m3). The annual average concentration of OC and EC in PM1 was found to be 34.12 ± 22.94 µg/m3 and 13.91 ± 11.45 µg/m3, respectively. Furthermore, a clear seasonal difference in the concentrations of OC and EC was observed. The highest OC and EC concentration were found during post-monsoon (OC: 59.58 ± 21.66 µg/m3) and winter season (EC: 23.90 ± 12.08 µg/m3), respectively. Although the lowest concentration of OC and EC was observed in the monsoon season (OC: 12.08 ± 6.98 µg/m3, EC: 3.88 ± 1.97 µg/m3). The annual average percentage contribution of OC and EC in PM1 was observed to be 22.48 and 9.16%, respectively. Total carbonaceous aerosol (TCA) accounted for 45.18% of PM1. The annual average OC/EC ratio was found to be 2.45, which indicates the secondary organic aerosol (SOA) formation. The OC/EC analysis reveals that OC2 and EC1 were dominant among eight carbon subfractions, which suggest a mixed source of emission. The higher value of inhalation dose of EC was observed during the winter season (309 µg), which can lead to a higher risk of cardiac and respiratory illness.
Various measures for reducing air pollution have been promulgated since 2013 in China. To investigate the synergistic results of emission control and meteorological environment, PM2.5 samples collected from October 2013 to July 2016 and November 2018 to October 2019 in Jiaozuo city were analyzed for their compositions, secondary species (Ss) variations, and factors changing for Ss formation. The results showed that the concentrations of sulfate, nitrate, ammonium, and secondary organic aerosols (SOAs) generally decreased over the same seasonal period during these years. In addition, the concentrations and proportions of each Ss increased with the increase in the PM2.5 level in these years, implying that although PM2.5 levels have been reduced by various control policies, Ss formation would remain the major contributor to PM elevations. The enhanced effects of gas-phase reactions on intensification of sulfate, SOA, and PM were observed in 2018-2019, which was consistent with the elevation of nitrate and SOA at PM levels of >150 μg/m3. Only sulfate in all PM levels sharply decreased after 2015, showing the fine effect of coal-related pollution control and the importance of collaborative control of NO
x
, volatile organic compounds, and organic aerosol emissions with SO2 emissions in the future.
Receptor models have been widely used for the source apportionment of airborne particulate matter. However, in the last 10 years, the use of factor analysis-based models, such as PMF and UNMIX, has increased significantly. The results yielded by these models must be interpreted by users who must know all variables influencing the modeling, and without this knowledge, the probability of incorrect interpretation of the source profiles may increase, especially when two or more sources have similar chemical profiles. Concerning the quality of data, this work shows that a broad characterization of PM composition, including inorganic, organic, and mineralogical species can improve this process, avoiding misinterpretation and the attribution of mixed or unidentified sources. This work aims to provide readers with some answers for a question often risen during source apportionment studies: Which source markers should be used for better separation and interpretation of source profiles? This review shows there is no right answer for this because different strategies can be used for this purpose. Therefore, this review aims to compile and highlight qualitatively the key strategies already used by several experienced receptor models users, combining the use of inorganic, organic, and mineralogical markers of PM for better separation and interpretation of the profiles yielded by receptor models. Also, this work presents a compilation in tables of the main chemical species reported in the literature as markers for interpreting the source profiles.
This study aims to critically evaluate the source apportionment of fine particles by multiple receptor modelling approaches, including carbon mass balance modelling of filter-based Radiocarbon (14C) data, Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) analysis on filter-based chemical speciation data, and PMF analysis on Aerosol Mass Spectrometer (AMS-PMF) or Aerosol Chemical Speciation Monitor (ACSM-PMF) data. These data were collected as part of the APHH-Beijing (Atmospheric Pollution and Human Health in a Chinese megacity) field observation campaigns from 9th November to 12th December in winter 2016 and 22nd May to 24th June in summer 2017. 14C analysis revealed the predominant contribution of fossil fuel combustion to carbonaceous aerosols over non-fossil fuel sources in winter, which is supported by the results from other methods. An extended Gelencser (EG) method incorporating 14C data, as well as CMB and AMS/ACSM-PMF methods all generated a consistent source apportionment of fossil and non-fossil fuel primary organic carbon (POC). The CMB and EG methods were also comparable when used to apportion secondary OC. Coal combustion, traffic and biomass burning POC was comparable for CMB and AMS/ACSM-PMF. There are uncertainties in the EG method to estimate biomass burning and cooking OC. POC from cooking estimated by different methods was poorly correlated between the different methods, suggesting a large uncertainty in differentiating this source type. PM2.5 source apportionment results varied between different methods. Through the comparison and correlation analysis of CMB, PMF and AMS/ACSM-PMF, the CMB method appears to give the most complete and representative source apportionment of Beijing aerosols. Based upon the CMB results, the fine aerosols in Beijing were mainly secondary inorganic ions, secondary organic aerosols, primary coal combustion and biomass burning emissions.
The MONterey Aerosol Research Campaign (MONARC) in May–June 2019 featured 14 repeated identical flights off the California coast over the open ocean at the same time each flight day. The objective of this study is to use MONARC data along with machine learning analysis to evaluate relationships between both supermicrometer sea salt aerosol number (N>1) and volume (V>1) concentrations and wind speed, wind direction, sea surface temperature (SST), ambient temperature (Tamb), turbulent kinetic energy (TKE), relative humidity (RH), marine boundary layer (MBL) depth, and drizzle rate. Selected findings from this study include the following: (i) Near surface (<60 m) N>1 and V>1 concentration ranges were 0.1–4.6 cm⁻³ and 0.3–28.2 μm³ cm⁻³, respectively; (ii) four meteorological regimes were identified during MONARC with each resulting in different N>1 and V>1 concentrations and also varying horizontal and vertical profiles; (iii) the relative predictive strength of the MBL properties varies depending on predicting N>1 or V>1, with MBL depth being more highly ranked for predicting N>1 and with TKE being higher for predicting V>1; (iv) MBL depths >400 m (<200 m) often correspond to lower (higher) N>1 and V>1 concentrations; (v) enhanced drizzle rates coincide with reduced N>1 and V>1 concentrations; (vi) N>1 and V>1 concentrations exhibit an overall negative relationship with SST and RH and an overall positive relationship with Tamb; and (vii) wind speed and direction were relatively weak predictors of N>1 and V>1.
Desulfurization kinetics and regeneration of silica gel-supported TiO2 extrudates were explored for reactive adsorptive desulfurization (RADS) process in this work. RADS using TiO2/SiO2 extrudates with varied particle sizes were evaluated. The textural and chemical properties of molded adsorbents were well maintained after extrusion, with a negligible decrease (<0.97%) in desulfurization capacity for 50 ppm low-sulfur diesel. The RADS of trilobed TiO2/SiO2 was well described with first-order adsorption kinetic model of ln(C) = –9.42×10-3 t + 3.84, and TiO2/SiO2 extrudates with smaller particle size may provide greater external surface area and shorter diffusion path. Impacts of packing density and weight hour space velocity (WHSV) on fixed-bed dynamic RADS were discussed. The desorption of adsorbed diesel can be well presented by a first-order model, where the total diesel yield of RADS process reached above 99.5% at nitrogen purging temperature≥150 °C. The effects of solvent structure, polarity and alkalinity on adsorbent regeneration were further illustrated. This work provides an insight into the aspects of kinetics and regeneration of molded adsorbents to pave the way for industrial fixed-bed desulfurization processes.
Residential coal combustion is a major source of carbonaceous aerosol globally. Clean coal briquettes can be used for pollution emission control. In this study, red mud (RM), a high alkalinity byproduct generated from the Bayer process, was employed as additive in coal briquettes. Combustion tests of briquettes and raw coal were conducted to evaluate the emission reduction effects on PM2.5 and carbonaceous aerosols. The highest emission reduction rates of PM2.5, organic carbon (OC), elemental carbon (EC) for bituminous were 37.5%, 13.2%, 82.6% and for anthracite were 31.2%, 11.1%, 30.0%. Total carbon (TC)/PM2.5 remained stable between raw coal and briquettes while EC/OC was altered significantly (from 0.32 to 0.08 and 0.08 to 0.03 for bituminous and anthracite). Subfractions (in both OC, EC) showed a similar decreasing trend with the increase of RM content, while OC3 and OC4 reduction was not significantly compared to raw coal emission. Regression model showed that volatile matter and RM content are the two most significant (p < 0.01) fuel properties affecting the emission of PM2.5 and OC. Moisture and RM content influenced EC emission most significantly (p < 0.01). This study demonstrated that RM-added coal briquettes can effectively improve regional air quality.
An aerosol sampling study was carried out at six monitoring sites in California's San Joaquin Valley from June 14, 1988 through June 9, 1989. Concentrations of PM[sub 10] (particles < 10[mu]m in aerodynamic diameter) and PM[sub 2.5] (particles < 2.5[mu]m in aerodynamic diameter) mass, elements, water-soluble nitrate, sulfate, ammonium, sodium, potassium, and organic and elemental carbon were determined in 24-h aerosol samples collected during this period. Federal and state standards for PM[sub 10] were exceeded at both urban and nonurban sites. PM[sub 10] concentrations were generally highest during winter and were dominated by PM[sub 2.5] during this time. The coarse (PM[sub 10] minus PM[sub 2.5]) aerosol fraction constituted more than half of PM[sub 10] mass during the summer and fall. PM[sub 10] concentrations of secondary ammonium nitrate were elevated during the winter at all sites. Conversely, concentrations of coarse particle iron, indicative of geologically related dust, were higher under less humid conditions during the summer and fall. Regionwide meteorological and chemical transformation processes influence the secondary (nitrate and sulfate) components of PM[sub 10]. Elevated concentrations of coarse-particle dust, however, appear to originate from local emissions, such as agricultural and transportation-related activities, as well as region-wide emissions. 74 refs., 4 figs., 4 tabs.
The predominant peak in the mass distribution emitted from each source measured in this study occurs at or below about 0.2 μm in particle diameter, whereas the Los Angeles atmospheric aerosol contains peaks at a variety of sizes in the range between 0.1 and 1.0 μm in particle diameter, including peaks at sizes larger than 0.2 μm. This suggests that considerable modification of the primary aerosol size distribution occurs because of subsequent processes in the atmosphere. The data presented here are intended for use in defining the size distribution of the primary combustion source effluent for use with mathematical models of the evolution of the atmospheric aerosol size distribution. Portions of this paper were presented at the 1988 AAAR Conference, Chapel Hill, NC.
An international specialty conference, jointly sponsored by the Air Waste Management Association (A WMA) and the US Environmental Protection Agency (EPA), entitled [open quotes]PM[sub 10] Standards and Nontraditional Particulate Source Controls,[close quotes] was held in Scottsdale, Arizona, January 12-15, 1992. The conference included 92 presentations in 17 technical sessions. Eight-one peer-reviewed technical papers, two keynote addresses and one panel session summary describing novel applications, measurement processes, modeling techniques and control measures for nontraditional pollution sources are assembled in the Transactions. The technical issues addressed during the conference included: (1) measurement methods and data bases; (2) emissions source characterization; (3) source apportionment of nontraditional sources; (4) fugitive dust characterization and control technologies; (5) vegetative burning characterization and control technologies; (6) sources and controls of secondary aerosol and motor vehicle precursors; and (7) regulatory policies and State Implementation Plan (SIP) development. This paper gives an overview of the technical program. 105 refs., 1 tab.
An APCA (now, the Air & Waste Management Associ- ation) International Specialty Conference was held in San Francisco, California in February 1988 to ex- change new information on novel applications, model theory, measurement processes, and software related to receptor models used in the management of air resources. Forty-six papers were presented in eight sessions which addressed: 1) PMio source apportion- ment for state implementation plan development; 2) measurements and source apportionment of pollut- ants other than PMio; 3) the requirements and avail- ability of receptor model data bases; 4) the implemen- tation of receptor models and their input data bases on microcomputers; 5) source characterization methods and results; and 6) model evaluation and develop- ment.
Experiments at the Allegheny and Tuscarora Mountain Tunnels of the Pennsylvania Turnpike in 1975–1979 have resulted in a comprehensive description of the airborne particulate matter associated with highway traffic. Because of strong variations of traffic composition with time, emission rates of most species were resolvable into emission rates for each of the two vehicle categories: gasoline-powered vehicles and heavy-duty diesels. Thirty-four elements were identified, accounting for all of the vehicle-derived airborne particulate mass. The principal component was carbon (elemental and organic) from exhausts of heavy-duty diesels, which comprised on the average 10%–15% of the traffic. Per vehicle-kilometer, diesels were the preponderant source of most of the other species as well. Other emissions resulted from oxidation of diesel-fuel sulfur to H2SO4 (5% of the particulate mass total for traffic overall), inorganic additives and adventitious components of fuels and motor oils (10% of the overall mass total, over half of it Pb), tire wear debris (1%), and soil dust (10%), leaving unidentified the origins of only ∼3.5% of the mass. Soil dust accounted fully for seven of the elements and a prominent share of at least nine more. Size distributions of the component species proved to be generally consistent with the putative origins. The gross mass median aerodynamic diameter was 0.15 μm, similar to diesel exhaust particles. Comparison of compositions reported here with compositions of urban and rural ambient-air particulate matter leads to estimates that the primary particulate matter from vehicles can account for most ambient airborne particulate Br and Pb; much of the C., H, Ba, and extractable organics; a measurable share of the Mn, Mg, Ca, Sr, CI, and P; and inconsequential amounts of the others. It appears to account for ∼ 11% of the airborne [pacute]articulate mass in cities and ∼2% in a remote rural area in the Northeast.
Air filter samples were collected at four sites in Washington, D.C. during the summer of 1974 and analyzed for 27 elements. The average concentrations were interpreted by a chemical-element-balance method. The observed concentration pattern was resolved into six components: coal, oil and refuse combustion, marine aerosols, soil and motor vehicle emissions. Eight elements were used in the least-squares fitting of components. Concentrations of the non-volatile elements among the remaining 19 elements were predicted, on the average, to within a factor of two, with most elements agreeing within a factor of three. The major exceptions are Cr and Sb, for which the observed/predicted ratios were approx 4. Major sources of the elements indicated by the resolution are: coal, I, As, Se; soil, K, Mg, Mn; coal and soil, Al, Ca, Sc, Ti, Cr, Fe, La, Ce, Th; refuse, Zn, Cd, Sb; marine aerosols, Na; oil, V, Ni; motor vehicles, Pb, Br; mixed sources, Cu, Co, Cl, Ba. Despite considerable improvement of this resolution over previous attempts, several limitations of the method are noted and further refinements suggested.
Source profiles representing diesel- and gasoline-powered vehicle emissions were tested for their ability to resolve source contributions in Chemical Mass Balance apportionments. For individual samples in simulated data sets, such contributions were estimated to within 25% for a simple source mixture and to within 50% for a mixture also containing wood smoke. Averaged over the entire data set, the estimated contributions were precise to within a few per cent. These uncertainties are related to random errors only. They do not account for additional bias error which in real-world applications may result from missing or inaccurately specified source profiles. Profiles for diesel- and gasoline-powered vehicle emissions were not seriously collinear. These profiles were also used to apportion sources of PM10 in Santa Barbara, CA. Contributions based on various composites were consistent with those based on the “pure” profiles.
A general methodology for performing simulations of the Chemical Mass Balance (CMB) model is developed and applied to simple and complex local scale scenarios. The simple scenario consists of crustal, coal-fired power plant, motor vehicle and vegetative burning sources; the complex scenario adds oil-fired power plant, ocean, steel mill, lead smelter, municipal incinerator and background aerosol sources. Daily receptor filter concentrations of the most commonly measured elements in the primary emissions are simulated. These simulations incorporate daily fluctuations in source strengths, daily fluctuations in source profiles (as parameterized by a coefficient of variation, or CV, of temporal source profiles) and measurement error at the receptor (as parameterized by a CV of measurement error). The CMB is applied to each daily measurement using a source library containing all sources and their long-term profiles (which, though correct on average, are incorrect on any particular day). The extent of agreement of the actual and CMBestimated primary emission source strengths is measured as an average absolute error (AAE, the absolute difference between the daily actual and estimated primary emission source strengths averaged over 100 simulated days). These moderately realistic simulations provide an encouraging picture of CMB accuracy and precision. The CMB yields acceptable accuracy and precision (an AAE of 50% or less) even when the CV of temporal source profiles is 25% and the CV of measurement error is 10%.
This report recommends procedures for source and ambient sampling and analysis in source apportionment studies. The recommendations are based on the results of receptor model studies of atmospheric particles in urban areas, especially a recent study of Houston, TX, undertaken as part of the Mathematical and Empirical Receptor Models Workshop (Quail Roost II). The recommendations are presented at three levels of increasing cost and detail of information obtained. Existing mass emissions inventories combined with chemically resolved test data from similar sources (not necessarily in the same locale) can be used to initially estimate the sources of elements present on ambient particles. To aid local users in construction of chemically resolved emission estimates, the U.S. Environmental Protection Agency (EPA) is compiling a library of compositions and size distributions of particulate emissions from major source types. More reliable source characterization can be achieved if the actual sources are tested directly. EPA should develop and publish detailed procedures for source sampling that would be more appropriate for receptor model use than are existing standard methods. Source and ambient sampling should be conducted by similar methods. If possible, particles from sources should be collected in a way that simulates changes that would normally occur before they reach distant receptors (e.g. by diluting and cooling the particles from hot sources). It is recommended that particulate samples be routinely collected in two size fractions by use of virtual impactors and that all samples be subjected, at a minimum, to mass and X-ray fluorescence analyses. Additional measurements are suggested for obtaining more detailed information: neutron activation analysis; X-ray diffraction; automated particle classification by electron microscopy; analyses for classes of organic species, 14C and thermally released carbonaceous species; and real-time observation of several gases during sample collection. Methods for collecting meteorological data in parallel with ambient samples are described, as are methods for incorporating such data into the source identification process.
A PM10 (particulate matter with aerodynamic diameter equal to or less than 10 μm) aerosol study was carried out at six sites in California's San Joaquin Valley (SJV) from 14 June 1988 to 9 June 1989, as part of the 1988–1989 Valley Air Quality Study (VAQS). Concentrations of PM10 and PM2.5 (particles with aerodynamic diameters equal to or less than 2.5 μm) mass, organic and elemental carbon, nitrate, sulfate, ammonium and elements were determined in 24-h aerosol samples collected at three urban (Stockton, Fresno, Bakersfield) and three non-urban (Crows Landing, Fellows, Kern Wildlife Refuge) locations during this period. The sources which contributed to ambient concentrations of PM10 were determined by applying the Chemical Mass Balance (CMB) receptor model using the source profiles determined specifically for that study area.The VAQS data indicates the federal 24-h PM10 standard of 150 μg m−3 was exceeded at four out of the six sites and for reasons which differ by season and by spatial region of influence. The annual average source contributions to the PM10 at Bakersfield, the site with the highest annual average, were 54% from primary geological material, 15% from secondary ammonium nitrate, 10% from primary motor vehicle exhaust, 8% from primary construction; the remaining 4% was unexplained. The results of the source apportionment at all sites show that geological contributions (fugitive dust from tilling, roadways and construction) are largest in summer and fall months, while secondary ammonium nitrate contributions (deriving from direct emissions of ammonia and oxides of nitrogen from agricultural activities and engine exhaust) are largest during winter months.
The effective variance weighted least squares solution to the mass balance receptor model is derived from the theory of maximum likelihood. The solution is one which contains the effects of random uncertainties in both the receptor concentrations and the source compositions. The solution involves trancendental equations of the unknown source contribution variables, and an iterative solution is required.This solution and the ordinary weighted least squares solution are applied to ten sets of simulated data generated from known source contributions and source compositions, perturbed by random experimental errors typical of those to be found in environmental sampling. The standard deviation of the source contributions calculated from each of these data sets is compared with the uncertainty obtained from the ordinary and effective variance least squares solutions; the effective variance solution provides the more accurate estimate. Extensions of this method to other least squares treatments of environmental data are proposed.
The thermal/optical reflectance method of carbon analysis developed by Huntzicker et al. (in Particulate Carbon, Atmospheric Life Cycle, edited by Wolff G. T. and Klimisch R. L., pp. 79–88, Plenum Press, New York, 1982) has been adapted by several laboratories for the quantification of organic and elemental carbon on quartz-fiber filter deposits. While the principle used by these laboratories is identical to that of Huntzicker et al., the details differ with respect to calibration standards, analysis time, temperature ramping and volatilization/combustion temperatures. This paper reports a variation on this method which has been applied to over 27,000 samples taken in more than a dozen urban and regional air quality studies in the U.S.A. In this variation, a 0.5 cm² punch from a dozen urban and regional air quality studies in 120, 250, 450 and 550°C in a pure helium atmosphere, then to combustion at temperatures of 550, 700 and 800°C in a 2% oxygen and 98% helium atmosphere. The carbon which evolves at each temperature is converted to methane and quantified with a flame ionization detector. The seven separate carbon fractions facilitate evaluation of the method and increase the information content concerning the samples.
This paper presents the U.S. Environmental Protection Agency's Chemical Mass Balance Model developed in cooperation with the Desert Research Institute, Reno, NV. CMB 7.0 apportions source contributions to pollutants measured at a receptor site, using measured profiles of the source chemical and elemental compositions. The model incorporates uncertainties in both the pollutant measurements and the source profile measurements in producing contribution estimates and their standard errors.
The chemical compositions of fine particles in motor vehicle exhaust were measured on dynamometer and exhaust samples during the winter in Denver, CO (elevation ∼ 1600 m above sea level). Forty-one inorganic and other species were quantified for tests involving different vehicle types, different fuels, and different operating cycles. It was found that addition of ethanol or MTBE (methyl tertiary butyl ether) to leaded and unleaded gasoline (in order to lower CO emissions) has no major effect on the chemical composition of particulate emissions from motor vehicles. On the Federal Test Procedure (FTP) driving schedule but at temperatures of 0 to 5 °C to simulate Denver winter conditions, compositions of emissions were similar among the cold-transient, cold-stabilized, and hot-transient cycles in the case of the leaded-fuel vehicles and also in the case of the diesel vehicles. Cold starts do cause a major change in the composition of emissions from unleaded catalyst-equipped vehicles by increasing the elemental carbon. Two-stroke diesel buses emit a much higher fraction of organic carbon and a much lower fraction of elemental carbon than do cars or four-stroke diesel trucks.