Quantification of urban atmospheric boundary layer greenhouse gas dry mole fraction enhancements in the dormant season: Results from the Indianapolis Flux Experiment (INFLUX)

Abstract

We assess the detectability of city emissions via a tower-based greenhouse gas (GHG) network, as part of the Indianapolis Flux (INFLUX) experiment. By examining afternoon-averaged results from a network of carbon dioxide (CO 2 ), methane (CH 4 ), and carbon monoxide (CO) mole fraction measurements in Indianapolis, Indiana for 2011-2013, we quantify spatial and temporal patterns in urban atmospheric GHG dry mole fractions. The platform for these measurements is twelve communications towers spread across the metropolitan region, ranging in height from 39 to 136 m above ground level, and instrumented with cavity ring-down spectrometers. Nine of the sites were deployed as of January 2013 and data from these sites are the focus of this paper. A background site, chosen such that it is on the predominantly upwind side of the city, is utilized to quantify enhancements caused by urban emissions. Afternoon averaged mole fractions are studied because this is the time of day during which the height of the boundary layer is most steady in time and the area that influences the tower measurements is likely to be largest. Additionally, atmospheric transport models have better performance in simulating the daytime convective boundary layer compared to the nighttime boundary layer. Averaged from January through April of 2013, the mean urban dormant-season enhancements range from 0.3 ppm CO 2 at the site 24 km typically downwind of the edge of the city (Site 09) to 1.4 ppm at the site at the downwind edge of the city (Site 02) to 2.9 ppm at the downtown site (Site 03). When the wind is aligned such that the sites are downwind of the urban area, the enhancements are increased, to 1.6 ppm at Site 09, and 3.3 ppm at Site 02. Differences in sampling height affect the reported urban enhancement by up to 50%, but the overall spatial pattern remains similar. The time interval over which the afternoon data are averaged alters the calculated urban enhancement by an average of 0.4 ppm. The CO 2 observations are compared to CO 2 mole fractions simulated using a mesoscale atmospheric model and an emissions inventory for Indianapolis. The observed and modeled CO 2 enhancements are highly correlated (r 2 = 0.94), but the modeled enhancements prior to inversion average 53% of those measured at the towers. Following the inversion, the enhancements follow the observations closely, as expected. The CH 4 urban enhancement ranges from 5 ppb at the site 10 km predominantly downwind of the city (Site 13) to 21 ppb at the site near the landfill (Site 10), and for CO ranges from 6 ppb at the site 24 km downwind of the edge of the city (Site 09) to 29 ppb at the downtown site (Site 03). Overall, these observations show that a dense network of urban GHG measurements yield a detectable urban signal, well-suited as input to an urban inversion system given appropriate attention to sampling time, sampling altitude and quantification of background conditions.

Source Sector Attribution of CO2 Emissions Using an Urban CO/CO2 Bayesian Inversion System

“…The CO 2 ‐only results, on the other hand, are probably the least reliable, despite the apparent trend agreement among both prior‐ratio cases (posteriors of 1.35 and 0.94 for the high‐ratio and low‐ratio priors, respectively). Further, we would expect additional error in the CO 2 ‐based inversions, because, despite having chosen the analysis period to minimize the biogenic influence (following Miles, Richardson, Lauvaux, et al, ), there will always be some biogenic CO 2 flux (Gurney et al, ; Turnbull et al, ). This biogenic flux, which may be between 5% and 20% of the fossil fuel flux in Indianapolis during this period (Turnbull et al, ), is not included in the CO 2 ff prior flux maps used in the pseudo‐data inversion described here, and should hamper the inversion's posterior improvement to some extent.…”

“…The INdianapolis FLUX (INFLUX) project focuses on monitoring greenhouse gas (GHG) emissions from the Indianapolis urban area (Davis et al, ; Miles, Richardson, Lauvaux, et al, ). Twelve Cavity Ring‐Down Spectrometers (Crosson, ; Rella et al, ) have been deployed to continuously record (1 Hz) GHG (i.e., CO 2 , CO, and CH 4 ) atmospheric mole fractions (Miles, Richardson, Lauvaux, et al, ) with calibration using NOAA tertiary standards (Richardson et al, ). Here hourly CO and CO 2 observations from 1 January to 30 April 2015 collected at towers 1, 2, 3, 6, and 9 of the INFLUX network (Miles, Richardson, Davis, et al, ) were assimilated in our inversion system.…”

The Hestia fossil fuel CO<sub>2</sub> emissions data product for the Los Angeles megacity (Hestia-LA)

“…Begun in the late 2000s, INFLUX has explored many aspects of the individual elements of a scientifically driven urban flux assessment (e.g., Wu et al, 2018), in addition to demonstrating potential reconciliation between Hestia and the atmospheric measurements (Gurney et al, 2017;Turnbull et al, 2015). Similar efforts are ongoing in the Salt Lake City (Mitchell et al, 2018;Lin et al, 2018) and Baltimore (Martin et al, 2018) domains with a different arrangement of atmospheric monitoring and modeling. As with INFLUX, a Hestia FFCO 2 emissions data product was produced in each domain (Patarasuk et al, 2016;Gurney et al, 2018).…”

“…Because urban areas differ in key attributes such as size, geography, and emission sector composition, multiple cities are now being used to test aspects of anthropogenic CO 2 monitoring and modeling. For example, ongoing efforts in integration of atmospheric measurements and bottom-up emissions information are taking place in Paris (Bréeon et al, 2015;Staufer et al, 2016), Boston (Sargent et al, 2018), Salt Lake City (Mitchell et al, 2018) and London (Font et al, 2015), to name a few. The Hestia approach has been used in a number of these urban domains.…”

Constraining Fossil Fuel CO2 Emissions From Urban Area Using OCO‐2 Observations of Total Column CO2

“…Some attempts have been made to derive local‐scale emissions for the urban areas by utilizing the inverse modeling method (Bousquet, 2000; Ciais et al, 2010) with ground‐based observations (Bréon et al, 2015; Lauvaux et al, 2016; McKain et al, 2012; Staufer et al, 2016; Wunch et al, 2009) or by the mass‐balance approach with aircraft measurements (Cambaliza et al, 2014). However, one of the key limitations of these approaches is the unavailability of direct, continuous, and high‐frequency atmospheric CO 2 measurements representing CO 2 enhancement in urban areas (Bréon et al, 2015), as only a handful of cities, mostly in Europe and North America, are instrumented with networks of CO 2 sensors (Bréon et al, 2015; Davis et al, 2017; McKain et al, 2012; Miles et al, 2017; Verhulst et al, 2017).…”