Intra-urban spatial variability and uncertainty assessment of PM2.5 sources based on carbonaceous species

Abstract

To identify the sources of PM2.5 – bound carbonaceous species and examine the spatial variability of source contributions in the Denver metropolitan area, positive matrix factorization (PMF) was applied to one year of every sixth day ambient PM2.5 compositional data, including elemental carbon (EC), organic carbon (OC), and 32 organic molecular markers, from four sites (two residential and two near-traffic). Statistics (median, inner quantiles and 5th – 95th percentiles range) of factor contributions, expressed as reconstructed carbonaceous mass (EC + OC), were estimated from PMF solutions of replicate datasets generated by using a stationary block bootstrap technique. A seven-factor solution was resolved for a set of data pooled across the four sites, as it gave the most interpretable results and had the highest rate of neural network factor matching (76.9%). Identified factors were primarily associated with high plant wax, summertime emission, diesel vehicle emission, fossil fuel combustion, motor vehicle emission, lubricating oil combustion and wood burning. Pearson correlation coefficients (r) and coefficients of divergence (COD) were used to assess spatial variability of factor contributions. The summertime emission factor exhibited the highest spatial correlation (r = 0.74 – 0.88) and lowest CODs (0.32 – 0.38) among all resolved factors; while the three traffic dominated factors (diesel vehicle emission, motor vehicle emission and lubricating oil combustion) showed lower correlations (r = 0.47 – 0.55) and higher CODs (0.41 – 0.53) on average. Average total EC and OC mass were apportioned to each factor and showed a similar distribution across the four sites. Modeling uncertainties were defined as the 5th – 95th percentile range of the factor contributions derived from valid bootstrap PMF solutions, and were highly correlated with the median factor contribution in each factor (r = 0.77 – 0.98). Source apportionment was also performed on site specific datasets; the results exhibited similar factor profiles and temporal variation in factor contribution as those obtained for the pooled dataset, indicating that the four sites are primarily influenced by similar types of sources. On the other hand, differences were observed in absolute factor contributions between PMF solutions for the pooled versus site-specific datasets, likely due to the large uncertainties in EC and OC factor profiles derived from the site specific datasets with limited numbers of observations.

Sources and composition of PM2.5 in the Colorado Front Range during the DISCOVER‐AQ study

“…Both components showed relatively modest concentration enhancements during the day, with peak concentrations around 12:00–14:00 local time. Past studies suggest that OM and sulfate are predominantly regional during summer in the Colorado Front Range [ Hand et al ., ; Xie et al ., ]. Wind rose analyses showed no enhancements in either the OM or the sulfate concentration as a function of wind direction (not shown), consistent with a regional source for both components.…”

“…Rapid expansion of oil and gas operations over the past decade has contributed to changing air quality in the region [ Pétron et al ., ; Thompson et al ., ]. On the regional scale, sulfate and secondary organic aerosols (SOA) from biogenic VOC emissions make important contributions to aerosol levels [ Hand et al ., ; Xie et al ., ]. Finally, aerosol concentrations in the region are subject to intermittent influences from the long‐range transport of fire, dust, and marine air [ Hallar et al ., ; Young et al ., ].…”

Water soluble organic aerosols in the Colorado Rocky Mountains, USA: composition, sources and optical properties

“…For our study, the Denver metropolitan area is about 80 km to the southeast of the sampling site, and the air masses more frequently originate from the south and southwest in summer periods, as shown in the backward trajectory analysis results (Supplementary Figs S2 and S3). In addition, summer upslope wind conditions are known to prevail in the summer, and these conditions may transport Front Range-derived EC, shown to have increased source strength in the summer43, to higher elevations. As such, emissions from the urban area in and around Denver may contribute to the multiple peaks of EC concentrations observed at our site in the summer and may, therefore, also play a role in summertime WSOC and OC inputs.…”

“…This method has been introduced and applied in previous work4376. Briefly, PMF uses an uncertainty-weighted least-squares fitting approach to resolve factor profiles and contributions from a series of compositional data of ambient particles.…”

The short-term association of selected components of fine particulate matter and mortality in the Denver Aerosol Sources and Health (DASH) study

“…Measurement error might be expected to be greater for those PM 2.5 components such as EC and OC that are more affected by local sources than are total PM 2.5 mass or secondary sulfate and nitrate components. However, in a supplemental study in which sampling was carried out in 2009 at three additional sites in the Denver area in addition to the site described in this study, we found little spatial heterogeneity of the PM 2.5 components time series or for pollution sources estimated by positive matrix factorization (PMF) across the four sites [ 34 , 35 ]. We were also reassured by preliminary analyses of the DASH site showing that our PM 2.5 component concentrations were highly correlated (0.70-0.86) over time with those at an EPA Chemical Speciation Network site located 13 kilometers away (Fig.…”