Assessing the optimized precision of the aircraft mass balance method for measurement of urban greenhouse gas emission rates through averaging

Abstract

To effectively address climate change, aggressive mitigation policies need to be implemented to reduce greenhouse gas emissions. Anthropogenic carbon emissions are mostly generated from urban environments, where human activities are spatially concentrated. Improvements in uncertainty determinations and precision of measurement techniques are critical to permit accurate and precise tracking of emissions changes relative to the reduction targets. As part of the INFLUX project, we quantified carbon dioxide (CO2), carbon monoxide (CO) and methane (CH4) emission rates for the city of Indianapolis by averaging results from nine aircraft-based mass balance experiments performed in November-December 2014. Our goal was to assess the achievable precision of the aircraft-based mass balance method through averaging, assuming constant CO2, CH4 and CO emissions during a three-week field campaign in late fall. The averaging method leads to an emission rate of 14,600 mol/s for CO2, assumed to be largely fossil-derived for this period of the year, and 108 mol/s for CO. The relative standard error of the mean is 17% and 16%, for CO2 and CO, respectively, at the 95% confidence level (CL), i.e. a more than 2-fold improvement from the previous estimate of ~40% for single-flight measurements for Indianapolis. For CH4, the averaged emission rate is 67 mol/s, while the standard error of the mean at 95% CL is large, i.e. ±60%. Given the results for CO2 and CO for the same flight data, we conclude that this much larger scatter in the observed CH4 emission rate is most likely due to variability of CH4 emissions, suggesting that the assumption of constant daily emissions is not correct for CH4 sources. This work shows that repeated measurements using aircraft-based mass balance methods can yield sufficient precision of the mean to inform emissions reduction efforts by detecting changes over time in urban emissions.

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

“…We show that NO x and CO emission rates from X/CO 2 × Vulcan CO 2 are consistent with the D.C.‐Balt NO x and CO emission rates calculated using the mass balance approach (section 2.7). We conduct a similar exercise with the Indianapolis Winter 2014 CO/CO 2 enhancement ratio reported in this study and the Hestia Indianapolis CO 2 emission rate and see agreement with the mass balance CO emission rate reported from the area by Heimburger et al (). The results of the exercise are provided in Table .…”

“…Figure also shows CO/CO 2 enhancement ratios observed by the UMD aircraft in D.C.‐Balt for the year after WINTER (February 2016), as well as CO/CO 2 enhancement ratios observed by the Purdue aircraft during a 3‐week observations period in Indianapolis in November–December 2014 (Heimburger et al, ). This is a useful comparison, since mobile sources (on‐road + nonroad) account for 77% (Table ) and 93% of D.C.‐Balt and Indianapolis CO emissions during the measurement months (EPA, ), respectively, and we expect the D.C.‐Balt and Indianapolis mobile fleets to be comparable.…”

“…The Purdue aircraft was used to conduct measurements in Indianapolis in November to December 2014. Methods for the Indianapolis measurements are discussed by Heimburger et al ().…”

“…The flux values calculated at each downwind sampling point, F C , i , are interpolated/extrapolated to create a two‐dimensional x ‐ z plane, or matrix ( M C ) of downwind CO or NO y * fluxes (Heimburger et al, ). The matrix extends from the surface to the top of the boundary layer and only extends horizontally to include urban‐influenced air (section 2.5).…”

The NASA Carbon Airborne Flux Experiment (CARAFE): instrumentation and methodology

“…Uncertainties, dominated by the stochastic nature of turbulence, typically range from 20 to 80 % for horizontal averaging scales of 1-30 km but can exceed 100 % when fluxes are small. Similar error ranges are reported for other surface exchange quantification methods (Cambaliza et al, 2014;Chang et al, 2014;Heimburger et al, 2017).…”