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 CO₂ and CH₄ emission rates at 1 km₂ 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 CO₂ and CH₄ 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 CO₂ 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.

Quantifying greenhouse gas (GHG) emissions from cities is a key challenge towards effective emissions management. An inversion analysis from the INdianapolis FLUX experiment (INFLUX) project, as the first of its kind, has achieved a top-down emission estimate for a single city using CO₂ data collected by the dense tower network deployed across the city. However, city-level emission data, used as a priori emissions, are also a key component in the atmospheric inversion framework. Currently, fine-grained emission inventories (EIs) able to resolve GHG city emissions at high spatial resolution, are only available for few major cities across the globe. Following the INFLUX inversion case with a global 1.1 km ODIAC fossil fuel CO₂ emission dataset, we further improved the ODIAC emission field and examined its utility as a prior for the city scale inversion. We disaggregated the 1.1 km ODIAC non-point source emissions using geospatial datasets such as the global road network data and satellite-data driven surface imperviousness data to a 30 . 30 m resolution. We assessed the impact of the improved emission field on the inversion result, relative to priors in previous studies (Hestia and ODIAC). The posterior total emission estimate (5.1 MtC/yr) remains statistically similar to the previous estimate with ODIAC (5.3 MtC/yr). However, the distribution of the flux corrections was very close to those of Hestia inversion and the model-observation mismatches were significantly reduced both in forward and inverse runs, even without hourly temporal changes in emissions. EIs reported by cities often do not have estimates of spatial extents. Thus, emission disaggregation is a required step when verifying those reported emissions using atmospheric models. Our approach offers gridded emission estimates for global cities that could serves as a prior for inversion, even without locally reported EIs in a systematic way to support city-level Measuring, Reporting and Verification (MRV) practice implementation.

Atmospheric radiocarbon (¹⁴C) represents an important observational constraint on emissions of fossil-fuel derived carbon into the atmosphere due to the absence of ¹⁴C in fossil fuel reservoirs. The high sensitivity and precision that accelerator mass spectrometry (AMS) affords in atmospheric ¹⁴C analysis has greatly increased the potential for using such measurements to evaluate bottom-up emissions inventories of fossil fuel CO₂(CO₂ff), as well as those for other co-emitted species. Here we use observations of ¹⁴CO₂ and a series of primary hydrocarbons and combustion tracers from discrete air samples collected between June 2009 and September 2010 at the National Oceanic and Atmospheric Administration Boulder Atmospheric Observatory (BAO; Lat: 40.050° N, Lon: 105.004° W) to derive emission ratios of each species with respect to CO₂ff. The BAO tower is situated at the boundary of the Denver metropolitan area to the south and a large industrial and agricultural region to the north and east, making it an ideal location to study the contrasting mix of emissions from the activities in each region. The species considered in this analysis are carbon monoxide (CO), methane (CH₄), acetylene (C₂H₂), benzene (C₆H₆), and C₃–C₅ alkanes. We estimate emissions for a subset of these species by using the Vulcan high resolution CO2ff emission data product as a reference. We find that CO is overestimated in the 2008 National Emissions Inventory (NEI08) by a factor of ~2. A close evaluation of the inventory suggests that the ratio of CO emitted per unit fuel burned from on-road gasoline vehicles is likely over-estimated by a factor of 2.5. Using a wind-directional analysis of the data, we find enhanced concentrations of CH₄, relative to CO₂ff, in air influenced by emissions to the north and east of the BAO tower when compared to air influenced by emissions in the Denver metro region to the south. Along with enhanced CH₄, the strongest enhancements of the C₃–C₅ alkanes are also found in the north and east wind sector, suggesting that both the alkane and CH₄ enhancements are sourced from oil and gas fields located to the northeast, though it was not possible to rule out the contribution of non oil and gas CH₄ sources.

Urban environments are the primary contributors to global anthropogenic carbon emissions. Because much of the growth in CO₂ emissions will originate from cities, there is a need to develop, assess, and improve measurement and modeling strategies for quantifying and monitoring greenhouse gas emissions from large urban centers. In this study the uncertainties in an aircraft-based mass balance approach for quantifying carbon dioxide and methane emissions from an urban environment, focusing on Indianapolis, IN, USA, are described. The relatively level terrain of Indianapolis facilitated the application of mean wind fields in the mass balance approach. We investigate the uncertainties in our aircraft-based mass balance approach by (1) assessing the sensitivity of the measured flux to important measurement and analysis parameters including wind speed, background CO₂ and CH₄, boundary layer depth, and interpolation technique, and (2) determining the flux at two or more downwind distances from a point or area source (with relatively large source strengths such as solid waste facilities and a power generating station) in rapid succession, assuming that the emission flux is constant. When we quantify the precision in the approach by comparing the estimated emissions derived from measurements at two or more downwind distances from an area or point source, we find that the minimum and maximum repeatability were 12 and 52%, with an average of 31%. We suggest that improvements in the experimental design can be achieved by careful determination of the background concentration, monitoring the evolution of the boundary layer through the measurement period, and increasing the number of downwind horizontal transect measurements at multiple altitudes within the boundary layer.

The ‘Hestia Project’ uses a bottom-up approach to quantify fossil fuel CO₂(FFCO₂) emissions spatially at the building/street level and temporally at the hourly level. Hestia FFCO₂ emissions are provided in the form of a group of sector-specific vector layers with point, line, and polygon sources to support carbon cycle science and climate policy. Application to carbon cycle science, in particular, requires regular gridded data in order to link surface carbon fluxes to atmospheric transport models. However, the heterogeneity and complexity of FFCO₂ sources within regular grids is sensitive to spatial resolution. From the perspective of a data provider, we need to find a balance between resolution and data volume so that the gridded data product retains the maximum amount of information content while maintaining an efficient data volume.

The Shannon entropy determines the minimum bits that are needed to encode an information source and can serve as a metric for the effective information content. In this paper, we present an analysis of the Shannon entropy of gridded FFCO₂ emissions with varying resolutions in four Hestia study areas, and find: (1) the Shannon entropy increases with smaller grid resolution until it reaches a maximum value (the max-entropy resolution); (2) total emissions (the sum of several sector-specific emission fields) show a finer max-entropy resolution than each of the sector-specific fields; (3) the residential emissions show a finer max-entropy resolution than the commercial emissions; (4) the max-entropy resolution of the onroad emissions grid is closely correlated to the density of the road network. These findings suggest that the Shannon entropy can detect the information effectiveness of the spatial resolution of gridded FFCO₂ emissions. Hence, the resolution-entropy relationship can be used to assist in determining an appropriate spatial resolution for urban CO₂ flux studies. We conclude that the optimal spatial resolution for providing Hestia total FFCO₂ emissions products is centered around 100 m, at which the FFCO₂ emissions data can not only fully meet the requirement of urban flux integration, but also be effectively used in understanding the relationships between FFCO₂ emissions and various social-economic variables at the U.S. census block group level.

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 (CO₂), methane (CH₄), 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 CO₂ 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 CO₂ observations are compared to CO₂ mole fractions simulated using a mesoscale atmospheric model and an emissions inventory for Indianapolis. The observed and modeled CO₂ enhancements are highly correlated (r² = 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 CH₄ 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.

The INFLUX experiment has taken multiple approaches to estimate the carbon dioxide (CO₂) flux in a domain centered on the city of Indianapolis, Indiana. One approach, Hestia, uses a bottom-up technique relying on a mixture of activity data, fuel statistics, direct flux measurement and modeling algorithms. A second uses a Bayesian atmospheric inverse approach constrained by atmospheric CO₂ measurements and the Hestia emissions estimate as a prior CO₂ flux. The difference in the central estimate of the two approaches comes to 0.94 MtC (an 18.7% difference) over the eight-month period between September 1, 2012 and April 30, 2013, a statistically significant difference at the 2-sigma level. Here we explore possible explanations for this apparent discrepancy in an attempt to reconcile the flux estimates. We focus on two broad categories: 1) biases in the largest of bottom-up flux contributions and 2) missing CO₂ sources. Though there is some evidence for small biases in the Hestia fossil fuel carbon dioxide (FFCO2) flux estimate as an explanation for the calculated difference, we find more support for missing CO₂ fluxes, with biological respiration the largest of these. Incorporation of these differences bring the Hestia bottom-up and the INFLUX inversion flux estimates into statistical agreement and are additionally consistent with wintertime measurements of atmospheric ¹⁴CO₂. We conclude that comparison of bottom-up and top-down approaches must consider all flux contributions and highlight the important contribution to urban carbon budgets of animal and biotic respiration. Incorporation of missing CO₂ fluxes reconciles the bottom-up and inverse-based approach in the INFLUX domain.

Megacities are major sources of anthropogenic fossil fuel CO₂(FFCO₂) emissions. The spatial extents of these large urban systems cover areas of 10 000 km² or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO₂ emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO₂ emission product, Hestia-LA, to simulate atmospheric CO₂ concentrations across the LA megacity at spatial resolutions as fine as  ∼  1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO₂ emission products to evaluate the impact of the spatial resolution of the CO₂ emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO₂ concentrations. We find that high spatial resolution in the fossil fuel CO₂ emissions is more important than in the atmospheric model to capture CO₂ concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO₂ fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO₂ fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO₂ concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO₂ emissions monitoring in the LA megacity requires FFCO₂ emissions modelling with  ∼1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.

Recent advances in fossil fuel CO₂ (FFCO₂) emission inventories enable sensitivity tests of simulated atmospheric CO₂ concentrations to sub-annual variations in FFCO₂ emissions and what this implies for the interpretation of observed CO₂. Six experiments are conducted to investigate the potential impact of three cycles of FFCO₂ emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO₂ rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO₂ rectification due to the covariation of diurnal FFCO₂ emissions and diurnal vertical mixing, as well as a smaller positive seasonal FFCO₂ rectification driven by the covariation of monthly FFCO₂ emissions and monthly atmospheric transport. The diurnal FFCO₂ emissions are responsible for a diurnal FFCO₂ concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO₂ emissions are responsible for a simulated seasonal CO₂ amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO₂ emissions, when only sampled in the local afternoon, is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO₂ concentration impacts from the diurnally and seasonally varying FFCO₂ emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO₂ emissions on simulated CO₂ concentration and suggests that inversion studies must take account of these variations in the affected regions.