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 (CO 2 ), carbon monoxide (CO) and methane (CH 4 ) 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 CO 2 , CH 4 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 CO 2 , 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 CO 2 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 CH 4 , 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 CO 2 and CO for the same flight data, we conclude that this much larger scatter in the observed CH 4 emission rate is most likely due to variability of CH 4 emissions, suggesting that the assumption of constant daily emissions is not correct for CH 4 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.

We present a high-resolution atmospheric inversion system combining a Lagrangian Particle Dispersion Model (LPDM) and the Weather Research and Forecasting model (WRF), and test the impact of assimilating meteorological observation on transport accuracy. A Four Dimensional Data Assimilation (FDDA) technique continuously assimilates meteorological observations from various observing systems into the transport modeling system, and is coupled to the high resolution CO 2 emission product Hestia to simulate the atmospheric mole fractions of CO 2 . For the Indianapolis Flux Experiment (INFLUX) project, we evaluated the impact of assimilating different meteorological observation systems on the linearized adjoint solutions and the CO 2 inverse fluxes estimated using observed CO 2 mole fractions from 11 out of 12 communications towers over Indianapolis for the Sep.-Nov. 2013 period. While assimilating WMO surface measurements improved the simulated wind speed and direction, their impact on the planetary boundary layer (PBL) was limited. Simulated PBL wind statistics improved significantly when assimilating upper-air observations from the commercial airline program Aircraft Communications Addressing and Reporting System (ACARS) and continuous ground-based Doppler lidar wind observations. Wind direction mean absolute error (MAE) decreased from 26 to 14 degrees and the wind speed MAE decreased from 2.0 to 1.2 m s –1 , while the bias remains small in all configurations (< 6 degrees and 0.2 m s –1 ). Wind speed MAE and ME are larger in daytime than in nighttime. PBL depth MAE is reduced by ~10%, with little bias reduction. The inverse results indicate that the spatial distribution of CO 2 inverse fluxes were affected by the model performance while the overall flux estimates changed little across WRF simulations when aggregated over the entire domain. Our results show that PBL wind observations are a potent tool for increasing the precision of urban meteorological reanalyses, but that the impact on inverse flux estimates is dependent on the specific urban environment.

The objective of the Indianapolis Flux Experiment (INFLUX) is to develop, evaluate and improve methods for measuring greenhouse gas (GHG) emissions from cities. INFLUX’s scientific objectives are to quantify CO 2 and CH 4 emission rates at 1 km 2 resolution with a 10% or better accuracy and precision, to determine whole-city emissions with similar skill, and to achieve high (weekly or finer) temporal resolution at both spatial resolutions. The experiment employs atmospheric GHG measurements from both towers and aircraft, atmospheric transport observations and models, and activity-based inventory products to quantify urban GHG emissions. Multiple, independent methods for estimating urban emissions are a central facet of our experimental design. INFLUX was initiated in 2010 and measurements and analyses are ongoing. To date we have quantified urban atmospheric GHG enhancements using aircraft and towers with measurements collected over multiple years, and have estimated whole-city CO 2 and CH 4 emissions using aircraft and tower GHG measurements, and inventory methods. Significant differences exist across methods; these differences have not yet been resolved; research to reduce uncertainties and reconcile these differences is underway. Sectorally- and spatially-resolved flux estimates, and detection of changes of fluxes over time, are also active research topics. Major challenges include developing methods for distinguishing anthropogenic from biogenic CO 2 fluxes, improving our ability to interpret atmospheric GHG measurements close to urban GHG sources and across a broader range of atmospheric stability conditions, and quantifying uncertainties in inventory data products. INFLUX data and tools are intended to serve as an open resource and test bed for future investigations. Well-documented, public archival of data and methods is under development in support of this objective.