Characterizing CO and NO_y Sources and Relative Ambient Ratios in the Baltimore Area Using Ambient Measurements and Source Attribution Modeling

Abstract

Modeled source attribution information from the Community Multiscale Air Quality model was coupled with ambient data from the 2011 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality Baltimore field study. We assess source contributions and evaluate the utility of using aircraft measured CO and NOy relationships to constrain emission inventories. We derive ambient and modeled ΔCO:ΔNOy ratios that have previously been interpreted to represent CO:NOy ratios in emissions from local sources. Modeled and measured ΔCO:ΔNOy are similar; however, measured ΔCO:ΔNOy has much more daily variability than modeled values. Sector‐based tagging shows that regional transport, on‐road gasoline vehicles, and nonroad equipment are the major contributors to modeled CO mixing ratios in the Baltimore area. In addition to those sources, on‐road diesel vehicles, soil emissions, and power plants also contribute substantially to modeled NOy in the area. The sector mix is important because emitted CO:NOx ratios vary by several orders of magnitude among the emission sources. The model‐predicted gasoline/diesel split remains constant across all measurement locations in this study. Comparison of ΔCO:ΔNOy to emitted CO:NOy is challenged by ambient and modeled evidence that free tropospheric entrainment, and atmospheric processing elevates ambient ΔCO:ΔNOy above emitted ratios. Specifically, modeled ΔCO:ΔNOy from tagged mobile source emissions is enhanced 5–50% above the emitted ratios at times and locations of aircraft measurements. We also find a correlation between ambient formaldehyde concentrations and measured ΔCO:ΔNOy suggesting that secondary CO formation plays a role in these elevated ratios. This analysis suggests that ambient urban daytime ΔCO:ΔNOy values are not reflective of emitted ratios from individual sources.

Top‐Down Estimates of NOx and CO Emissions From Washington, D.C.‐Baltimore During the WINTER Campaign

“…The C-130 CO/NO x enhancement ratios range from 2.8 to 6.4 ppbv ppbv À1 and were determined from measurements conducted on 3 February 2015 (D.C.-Balt and Philadelphia, PA) and 6 February 2015 (Cincinnati, OH). Similar to the large range in day-to-day CO/NO x enhancement ratios observed during the WINTER campaign, Simon et al (2018) also report large daily variability in CO/NO y enhancement ratios (4.9-13.6) in D.C.-Balt from airborne observations conducted in July 2011 (DISCOVER-AQ). Emitted ratios of CO/NO x from different combustion sources can be highly variable; for example, CO/NO x emission ratios from gasoline on-road vehicles are 3 orders of magnitude greater than power plant emission ratios (Simon et al, 2018).…”

“…Similar to the large range in day-to-day CO/NO x enhancement ratios observed during the WINTER campaign, Simon et al (2018) also report large daily variability in CO/NO y enhancement ratios (4.9-13.6) in D.C.-Balt from airborne observations conducted in July 2011 (DISCOVER-AQ). Emitted ratios of CO/NO x from different combustion sources can be highly variable; for example, CO/NO x emission ratios from gasoline on-road vehicles are 3 orders of magnitude greater than power plant emission ratios (Simon et al, 2018). With the exception of fires (agricultural, wood), the NEI predicts gasoline vehicles and nonroad mobile equipment (construction, lawn, and recreation equipment/vehicles) emit the highest CO/NO x ratios relative to other combustion sources (Simon et al, 2018;Wallace et al, 2012).…”

“…Emitted ratios of CO/NO x from different combustion sources can be highly variable; for example, CO/NO x emission ratios from gasoline on‐road vehicles are 3 orders of magnitude greater than power plant emission ratios (Simon et al, ). With the exception of fires (agricultural, wood), the NEI predicts gasoline vehicles and nonroad mobile equipment (construction, lawn, and recreation equipment/vehicles) emit the highest CO/NO x ratios relative to other combustion sources (Simon et al, ; Wallace et al, ). These relatively high NEI‐predicted CO/NO x ratios are supported by in‐use vehicle fleet CO/NO x ratio measurements in Chicago (9.8; Fall 2014; Bishop et al, ), Tulsa (11.5; Fall 2015; Bishop & Stedman, ), and Los Angeles (7.7–10.7; Summer 2010; Bishop et al, ; Fujita et al, ).…”

Reflecting on progress since the 2005 NARSTO emissions inventory report

“…Several challenges make it difficult to compare field observations with concentrations from models that combine recent inventory inputs with state-of-the art treatments of atmospheric chemistry and transport. These include spatial and temporal measurement scale incommensurability between instantaneous point measurements and grid-scale hourly model outputs (Swall and Foley 2009) and uncertainties in model chemistry and meteorological treatment (Simon et al 2018). Some measurement-model hybrid studies have attempted to address these issues either by using near-source measurements or by looking at pollutant ratios (e.g.…”

“…In doing such comparisons to emissions ratios, however, it is important for researchers to carefully consider aging timescales and related uncertainties in relation to measurement scales for any pollutants that are not inert, or which have secondary sources. Lack of appropriate accounting for these factors has the potential to bias conclusions about inventory errors (Simon et al 2018).…”