Molecular Marker-based Chemical Mass Balance Research Articles

Chemical Characteristics and Source Apportionment of Organic Aerosols in Atmospheric PM2.5 in Winter in Beijing

To explore the concentrations, characteristics, and sources of organic aerosols in winter in Beijing, atmospheric fine particulate matter (PM2.5) samples were collected from November 10, 2016 to December 10, 2016. One hundred and twenty-nine particulate organic matters (POM) were quantified by gas chromatography-mass spectrometry, accounting for approximately 9.3%±1.2% of the total concentration of organic matter. The most abundant class was sugar, among which levoglucosan alone accounted for 18% of the quantified organic matter mass. The next most abundant classes were alkanoic acids, normal alkanes, dicarboxylic acids, and polycyclic aromatic hydrocarbons. The influence of winter heating and biomass burning emissions on organic aerosols in winter in Beijing was analyzed by the characteristics of the molecular markers in the POM. Compared with those during the non-heating period, the concentrations and proportions of hopane species, which are tracers for fossil fuels, increased in the organic matters during the heating period. Moreover, the influence of coal burning emissions on the distribution of hopane species was enhanced. The species with the maximum concentration and carbon predominance index in n-alkanes also reflected the influence of enhanced fossil fuel emissions. The results of the concentration-weighted trajectory model for levoglucosan, a tracer for biomass combustion, suggested that straw burning pollution in the surrounding areas of Beijing would affect the composition of organic aerosols in Beijing via airmass transport. A molecular marker-based chemical mass balance model was used to apportion the sources of organic carbon in the winter of 2016 in Beijing, and the results were compared with those of research in 2006 to quantify the changes in the source contributions over 10 years. The contribution of motor vehicles increased significantly in 2016 compared with that in 2006, whereas the contribution of coal burning and wood burning decreased to a large extent. The contribution of cooking emissions could not be ignored. Therefore, the control of motor vehicle and cooking emissions is of great importance to reduce the problem of PM2.5 pollution in winter in Beijing.

A hybrid source apportionment strategy using positive matrix factorization (PMF) and molecular marker chemical mass balance (MM-CMB) models

The molecular marker-based chemical mass balance (MM-CMB) method performs well in the source apportionment of organic carbon (OC) but has some difficulty with contributions from primary sources to inorganic secondary ions when apportioning PM2.5 (particles with aerodynamic diameter of 2.5 μm or less) sources. Positive matrix factorization (PMF) with the input of inorganic and organic tracers can properly estimate the contributions of primary and secondary sources to inorganic secondary ions; however, PMF is unable to apportion several PM2.5 sources with large fractions of organic carbon and few elemental compositions. In this study regarding data collected in 2011 and 2012 at three sites in Wuhan, China, the MM-CMB model was used to apportion OC in the PM2.5, and the PMF model was used to apportion the inorganic ions (sulfate, nitrate, and ammonia), dust, and EC. The source contributions of PM2.5 were estimated by reconstructing masses of bulk chemical components that had been apportioned to real-world sources using suitable source apportionment methods. Good performance of this hybrid source apportionment strategy was observed with ten resolved factors, explaining 70–80% of measured PM2.5 mass on average. The hybrid strategy takes the advantages of both models in PM2.5 source apportionment and yields unique source apportionment results for PM2.5 bulk chemical components, which could provide new information for optimizing air quality regulations for the emission abatement of target PM mass and compositions for countries around the world.

Chemical composition and redox activity of PM0.25 near Los Angeles International Airport and comparisons to an urban traffic site

To investigate the relative impacts of emissions from Los Angeles International Airport (LAX), as well as the impacts of traffic emissions from freeways, on the oxidative potential of particulate matter (PM), PM0.25 were collected at two urban background locations in Los Angeles. Redox activity of the PM samples was measured by means of an in vitro alveolar macrophage assay that quantifies the formation of reactive oxygen species (ROS) in cells, and detailed chemical analyses were performed to determine the speciated chemical composition of collected PM. A molecular marker-based chemical mass balance (MM-CMB) model was applied to estimate the relative contributions from the following primary sources to the organic carbon (OC) component of PM: mobile sources (combined gasoline and diesel vehicles), wood smoke, vegetative detritus, road dust and ship emissions. A source profile of aircraft emissions was not included in the model; however its contribution was estimated from un-apportioned primary OC in the MM-CMB model (“other OC”) after accounting for the contribution of secondary organic carbon (SOC) to OC. The contribution of mobile sources to OC was 82% and 28% at the central Los Angeles site (freeway emissions) and the LAX site, respectively. The estimated contribution of aircraft emissions to PM0.25 OC was 36% at the LAX site. ROS activity levels showed little spatial variability, with no statistically significant difference between the averages observed at LAX (24.75±4.01μgZymosan/m3) and central Los Angeles (27.77±2 0.32μgZymosan/m3), suggesting similar levels of inhalation exposure to redox active species of PM0.25. A multiple linear regression analysis indicated that the variability in ROS activity is best explained by the chemical markers of major identified sources: EC emitted by traffic, and sulfur, considered in our study as a potential tracer of aircraft emissions, with statistically significantly higher concentrations of sulfur at the LAX site (p<0.001).

Fine and ultrafine particulate organic carbon in the Los Angeles basin: Trends in sources and composition

In this study, PM2.5 and PM0.18 (particles with dp<2.5μm and dp<0.18μm, respectively) were collected during 2012–2013 in Central Los Angeles (LA) and 2013–2014 in Anaheim. Samples were chemically analyzed for carbonaceous species (elemental and organic carbons) and individual organic compounds. Concentrations of organic compounds were reported and compared with many previous studies in Central LA to quantify the impact of emissions control measurements that have been implemented for vehicular emissions over the past decades in this area. Moreover, a novel hybrid approach of molecular marker-based chemical mass balance (MM-CMB) analysis was conducted, in which a combination of source profiles that were previously obtained from a Positive Matrix Factorization (PMF) model in Central LA, were combined with some traditional source profiles. The model estimated the relative contributions from mobile sources (including gasoline, diesel, and smoking vehicles), wood smoke, primary biogenic sources (including emissions from vegetative detritus, food cooking, and re-suspended soil dust), and anthropogenic secondary organic carbon (SOC). Mobile sources contributed to 0.65±0.25μg/m3 and 0.32±0.25μg/m3 of PM2.5 OC in Central LA and Anaheim, respectively. Primary biogenic and anthropogenic SOC sources were major contributors to OC concentrations in both size fractions and sites. Un-apportioned OC (“other OC”) accounted for an average 8.0 and 26% of PM2.5 OC concentration in Central LA and Anaheim, respectively. A comparison with previous studies in Central LA revealed considerable reduction of EC and OC, along with tracers of mobile sources (e.g. PAHs, hopanes and steranes) as a result of implemented regulations on vehicular emissions. Given the significant reduction of the impacts of mobile sources in the past decade in the LA Basin, the impact of SOC and primary biogenic emissions have a larger relative impact and the new hybrid model allows the impact of these sources to be better quantified.

Impact of primary and secondary organic sources on the oxidative potential of quasi-ultrafine particles (PM0.25) at three contrasting locations in the Los Angeles Basin

To investigate the changing contribution of primary and secondary sources on the oxidative potential of particulate matter (PM) in a real-world urban atmosphere, 7 sets of quasi-ultrafine particles (PM0.25) were collected at three contrasting locations in the Los Angeles Basin, California, USA. Samples were collected in the coastal area of Long Beach during the morning rush hour period, representing fresh primary emissions from nearby freeways and the LA port; in central Los Angeles during midday, representing a mixture of fresh primary emissions and early products of photochemical secondary organic aerosol (SOA) formation; and at a downwind site (Upland) during afternoon, when the impacts of photochemically aged secondary PM are significant. Chemical composition showed distinctive trends, with the lowest fraction of water soluble organic carbon (WSOC) and other organic tracers of SOA formation (e.g. organic acids) at Long Beach, and the lowest abundance of organic tracers of primary vehicular emissions (such as polycyclic aromatic hydrocarbons and hopanes) at Upland. A molecular marker-based chemical mass balance (MM-CMB) model indicated that 72% of the total organic carbon at Long Beach was comprised of primary vehicular sources (combined heavy duty and light duty vehicles), while the vehicular fraction was found to be 50% and 39% at Los Angeles and Upland, respectively. Regression analysis suggested that at Long Beach, the variation in oxidative potential of PM0.25 (quantified using a macrophage-based reactive oxygen species (ROS) assay) was mainly driven by mobile vehicular emissions and the water-insoluble fraction of the organic carbon. In contrast, at Upland, where photochemical processing and secondary aerosol formation was the highest, WSOC and secondary organics were the major drivers of the oxidative potential variation. The multivariate regression analysis also indicated that as much as 58% of the overall spatial and temporal variation in the oxidative potential of PM0.25 at these three locations can be explained by mobile emissions and SOA.

Chemical characterization and source apportionment of indoor and outdoor fine particulate matter (PM2.5) in retirement communities of the Los Angeles Basin

Concurrent indoor and outdoor measurements of fine particulate matter (PM2.5) were conducted at three retirement homes in the Los Angeles Basin during two separate phases (cold and warm) between 2005 and 2006. Indoor-to-outdoor relationships of PM2.5 chemical constituents were determined and sources of indoor and outdoor PM2.5 were evaluated using a molecular marker-based chemical mass balance (MM-CMB) model. Indoor levels of elemental carbon (EC) along with metals and trace elements were found to be significantly affected by outdoor sources. EC, in particular, displayed very high indoor-to-outdoor (I/O) mass ratios accompanied by strong I/O correlations, illustrating the significant impact of outdoor sources on indoor levels of EC. Similarly, indoor levels of polycyclic aromatic hydrocarbons (PAHs), hopanes, and steranes were strongly correlated with their outdoor components and displayed I/O ratios close to unity. On the other hand, concentrations of n-alkanes and organic acids inside the retirement communities were dominated by indoor sources (e.g. food cooking and consumer products), as indicated by their I/O ratios, which exceeded unity. Source apportionment results revealed that vehicular emissions were the major contributor to both indoor and outdoor PM2.5, accounting for 39 and 46% of total mass, respectively. Moreover, the contribution of vehicular sources to indoor levels was generally comparable to its corresponding outdoor estimate. Other water-insoluble organic matter (other WIOM), which accounts for emissions from uncharacterized primary biogenic sources, displayed a wider range of contributions, varying from 2 to 73% of PM2.5, across all sites and phases of the study. Lastly, higher indoor than outdoor contribution of other water-soluble organic matter (other WSOM) was evident at some of the sites, suggesting the production of secondary aerosols as well as direct emissions from primary sources (including cleaning or other consumer products) at the indoor environments.

Source apportionment and organic compound characterization of ambient ultrafine particulate matter (PM) in the Los Angeles Basin

In this study, quasi-UFP (PM0.25, dp < 0.25 μm) were collected for 24 h once per week from April 2008 to March 2009 at 10 different locations in the Los Angeles Basin. Samples were chemically analyzed and organic constituents of PM0.25 were grouped into polycyclic aromatic hydrocarbon (PAHs), hopanes and steranes, n-alkanes, and levoglucosan, with concentration levels ranging from 0.16 to 5.5, 0.09 to 2.2, 9.3 to 48, and 2.2 to 106.2 ng m−3 over all sites and seasons, respectively. A molecular marker-based chemical mass balance (MM-CMB) model was applied to estimate the relative contributions from the following primary sources: mobile sources (combined gasoline and diesel vehicles), wood smoke, natural gas combustion, vegetative detritus, and ship emissions. Secondary organic aerosol (SOA) tracers were not included in the model; however their contributions were estimated from non-biomass burning water soluble organic carbon (WSOCnb) and un-apportioned OC from MM-CMB model (“other OC”). High correlation (R2 = 0.8) between “other OC” and WSOCnb in summer suggests that “other OC” is highly impacted by SOA, however un-apportioned primary sources may contribute to “other OC” as well. Mobile sources were expectedly the major primary contributor to PM0.25, with seasonal average contributions of 31 ± 12% in summer and 57 ± 17% in winter. “Other organic matter” was the second largest contributor to PM0.25 in all seasons, across the basin, with substantially higher contribution during warmer spring and summer seasons (27%), while lowest during cold seasons (13%). Wood smoke was the third major contributor to PM0.25 in winter, whereas its contribution was lowest in summer. As expected, ship emissions displayed the highest contribution at the near-harbor HUD site, and their levels continually decreased as a function of distance from coast. Two other primary sources, vegetative detritus and natural gas combustion, collectively contributed to 1.3 ± 0.8% of PM0.25 on an annual average basis over all sites. Comparison of our results to PM2.5 OC apportionment, conducted at central LA, shows that contribution of mobile sources to PM0.25 OC is more than two times higher than PM2.5 (75% and 30%, respectively), while “other OC” contributed significantly higher to PM2.5 OC compared to PM0.25 (56% and 21%, respectively).

Contemporary or Fossil Origin: Split of Estimated Secondary Organic Carbon in the Southeastern United States

One year of high-volume PM2.5 filter samples were collected from 2004 to 2005 at one rural site and three urban sites in the Southeastern Aerosol Research and Characterization (SEARCH) network. These filters were analyzed for both organic tracers and carbon isotopes. Sources for primary carbon were previously apportioned based on molecular marker-based chemical mass balance modeling (CMB-MM). In this study, these primary sources were further classified into two categories as having fossil and contemporary origins. 14C data were used to estimate the relative contributions of fossil and contemporary contents in total carbon (TC). Combined these two sets of independent results, fossil and contemporary contributions to secondary carbon source, which was estimated by the unexplained OC in CMB-MM, were calculated. The fossil secondary organic carbon (SOCF) and the contemporary secondary organic carbon (SOCC) ranged from 0.56 to 3.20 microgC/m3 and 0.82 to 4.09 microgC/m3, respectively. SOCF was higher at urban sites and exhibited small seasonal variation at all sites, probably resulting from higher fossil precursor emissions in urban areas. In contrast, SOCC was higher at the rural site and exhibited obvious seasonal variation at all sites. During the whole year SOCF was the major secondary organic carbon (SOC) contributor at the urban sites, while SOCC dominated SOC at the rural site. In summer isoprene-derived SOC showed a large contribution to SOCC and exhibited significant positive correlation with SOCC, indicating the importance of isoprene-derived secondary organic aerosol (SOA) formation during summer. It is interesting to note that the secondary items, including SOCF, SOCC, secondary sulfate, and secondary ammonium, exhibited significant correlations between the monitoring sites, suggesting the regional impact of secondary aerosol in the southeastern United States.

Comparison of PM2.5 source apportionment using positive matrix factorization and molecular marker-based chemical mass balance

A comprehensive comparison of positive matrix factorization (PMF) and molecular marker-based chemical mass balance (CMB-MM) modeling on PM2.5 source contributions was conducted for particulate matter measurements taken at Jefferson Street, Atlanta, Georgia (JST). The datasets used in each type of receptor modeling were different: CMB-MM used data of primarily organic tracers plus a couple elements measured from 51 24-h PM2.5 samples collected in July 2001 and January 2002. While for PMF, with elements, ions, five gaseous components, and eight temperature-resolved carbon fractions as the input data, both source profiles and contributions were resolved from a total of 932 daily PM2.5 samples covering a 3-year period between January 2000 and December 2002. The model results for the overlapping periods (July 2001 and January 2002) were extracted for comparison. Seven primary sources and three secondary sources were resolved by CMB-MM, while a total of nine primary and secondary factors were resolved by PMF. On average, 107% and 85% of PM2.5 mass were explained by CMB-MM and PMF, respectively, with secondary aerosols handled differently in the above two methods. Four similar sources were resolved by both methods, with good correlation for road dust, but fair for gasoline exhaust and wood combustion. The CMB-MM diesel exhaust has very poor correlation with the PMF resolved diesel exhaust. However, the CMB-MM combined mobile source has improved correlation with the PMF result as compared with the diesel exhaust source. If only the winter data were included, the CMB-MM combined mobile source shows enhanced correlation with the PMF combined source, as compared with the single source of diesel exhaust or gasoline exhaust.

Source apportionment of PM2.5 in Beijing by positive matrix factorization

Air pollution associated with atmospheric fine particulate matter (PM2.5, i.e., particles with an aerodynamic diameter of 2.5 μm or less) is a serious problem in Beijing, China. To provide a better understanding of the sources contributing to PM2.5, 24-h samples were collected at 6-day intervals in January, April, July, and October in 2000 at five locations in the Beijing metropolitan area. Both backward trajectory and elemental analyses identified two dust storm events; the distinctly low value of Ca:Si (<0.2) and high Al:Ca (>1.7) in Beijing PM2.5 appear indicative of contributions from dust storms. Positive matrix factorization (PMF) was used to apportion sources of PM2.5, and eight sources were identified: biomass burning (11%), secondary sulfates (17%), secondary nitrates (14%), coal combustion (19%), industry (6%), motor vehicles (6%), road dust (9%), and yellow dust. The lower organic carbon (OC), elemental carbon (EC), SO 4 2−, and Ca values of yellow dust enable it to be distinguished from road dust. The PMF method resolved 82% of PM2.5 mass concentrations and showed excellent agreement with a previous calculation using organic tracers in a chemical mass balance (CMB) model. The present study is the first reported comparison between a PMF source apportionment model and a molecular marker-based CMB in Beijing.