Spatiotemporally resolved urban fossil fuel CO2 (FFCO2) emissions are critical to urban carbon cycle research and urban climate policy. Two general scientific approaches have been taken to estimate spatiotemporally explicit urban FFCO2 fluxes, referred to here as “downscaling” and “bottom‐up.” Bottom‐up approaches can specifically characterize the CO2‐emitting infrastructure in cities but are labor‐intensive to build and currently available in few U.S. cities. Downscaling approaches, often available globally, require proxy information to allocate or distribute emissions resulting in additional uncertainty. We present a comparison of a downscaled FFCO2 emission data product (Open‐source Data Inventory for Anthropogenic CO2 (ODIAC)) to a bottom‐up estimate (Hestia) in four U.S. urban areas in an effort to better isolate and understand differences between the approaches. We find whole‐city differences ranging from −1.5% (Los Angeles Basin) to +20.8% (Salt Lake City). At the 1 km × 1 km spatial scale, comparisons reveal a low‐emission limit in ODIAC driven by saturation of the nighttime light spatial proxy. At this resolution, the median difference between the two approaches ranged from 47 to 84% depending upon city with correlations ranging from 0.34 to 0.68. The largest discrepancies were found for large point sources and the on‐road sector, suggesting that downscaled FFCO2 data products could be improved by incorporating independent large point‐source estimates and estimating on‐road sources with a relevant spatial surrogate. Progressively coarsening the spatial resolution improves agreement but greater than approximately 25 km2, there were diminishing returns to agreement suggesting a practical resolution when using downscaled approaches.

The total precipitation of previous August to current July was reconstructed on the basis of the Pinus tabulaeformis ring widths from three sites in Chifeng and Weichang regions, China, for the past 236 years. The explained variance of reconstruction is 47.4%. The intervals with below‐average precipitation (1768–2003) comprise 1779–1806, 1853–1883, 1926–1972, and 1980–1989. The intervals with above average precipitation consist of 1807–1852, 1884–1925, 1973–1979, and 1990–1999. Precipitation in the study area is dependent on the East Asian summer monsoon strength. The reconstructed series is significantly correlated with the average dryness/wetness index series of Datong and Beijing, as well as with previous results from Baiyinaobao, Helan Mountains, and even the state of Mongolia. A significant negative correlation (r = −0.63, p < 0.0001) is also found between the reconstruction and our previously reconstructed temperatures of Weichang for the period 1884–2002. Our result suggests that the variations of the East Asian summer monsoon on a decadal scale are coincident with the other regions within the environmentally sensitive zone of northern China as well as Mongolia for the past 236 years, and our reconstruction is representative of regional climate patterns.

Urban areas contribute approximately threequarters of fossil fuel derived CO 2 emissions, and many cities have enacted emissions mitigation plans. Evaluation of the effectiveness of mitigation efforts will require measurement of both the emission rate and its change over space and time. The relative performance of different emission estimation methods is a critical requirement to support mitigation efforts.Here we compare results of CO 2 emissions estimation methods including an inventory-based method and two different top-down atmospheric measurement approaches implemented for the Indianapolis, Indiana, U.S.A. urban area in winter. By accounting for differences in spatial and temporal coverage, as well as trace gas species measured, we find agreement among the wintertime whole-city fossil fuel CO 2 emission rate estimates to within 7%. This finding represents a major improvement over previous comparisons of urban-scale emissions, making urban CO 2 flux estimates from this study consistent with local and global emission mitigation strategy needs. The complementary application of multiple scientifically driven emissions quantification methods enables and establishes this high level of confidence and demonstrates the strength of the joint implementation of rigorous inventory and atmospheric emissions monitoring approaches.

The INFLUX experiment has taken multiple approaches to estimate the carbon dioxide (CO 2 ) 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 CO 2 measurements and the Hestia emissions estimate as a prior CO 2 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 CO 2 sources. Though there is some evidence for small biases in the Hestia fossil fuel carbon dioxide (FFCO 2 ) flux estimate as an explanation for the calculated difference, we find more support for missing CO 2 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 14 CO 2 . We conclude that comparison of bottomup 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 CO 2 fluxes reconciles the bottom-up and inverse-based approach in the INFLUX domain.

Abstract. We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the SoCAB to be 104 ± 26 Tg CO2 yr−1 for the study period of July 2013–August 2016. We obtain a slightly higher estimate of 120 ± 30 Tg CO2 yr−1 using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360 ± 90 Gg CH4 yr−1) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342–440 Gg CH4 yr−1). CO emissions are estimated at 487 ± 122 Gg CO yr−1, much lower than previous top-down estimates (1440 Gg CO yr−1). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25 %, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.