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.

Keywords

• greenhouse gas
• emission rates
• precision
• urban
• quantification