A multi-city urban atmospheric greenhouse gas measurement data synthesis.

Urban regions emit a large fraction of anthropogenic emissions of greenhouse gases (GHG) such as carbon dioxide (CO2) and methane (CH4) that contribute to modern-day climate change. As such, a growing number of urban policymakers and stakeholders are adopting emission reduction targets and implementing policies to reach those targets. Over the past two decades research teams have established urban GHG monitoring networks to determine how much, where, and why a particular city emits GHGs, and to track changes in emissions over time. Coordination among these efforts has been limited, restricting the scope of analyses and insights. Here we present a harmonized data set synthesizing urban GHG observations from cities with monitoring networks across North America that will facilitate cross-city analyses and address scientific questions that are difficult to address in isolation.

Constraining Urban CO2 Emissions Using Mobile Observations from a Light Rail Public Transit Platform.

Urban environments are characterized by pronounced spatiotemporal heterogeneity, which can present sampling challenges when utilizing conventional greenhouse gas (GHG) measurement systems. In Salt Lake City, Utah, a GHG instrument was deployed on a light rail train car that continuously traverses the Salt Lake Valley (SLV) through a range of urban typologies. CO2 measurements from a light rail train car were used within a Bayesian inverse modeling framework to constrain urban emissions across the SLV during the fall of 2015. The primary objectives of this study were to (1) evaluate whether ground-based mobile measurements could be used to constrain urban emissions using an inverse modeling framework and (2) quantify the information that mobile observations provided relative to conventional GHG monitoring networks. Preliminary results suggest that ingesting mobile measurements into an inverse modeling framework generated a posterior emission estimate that more closely aligned with observations, reduced posterior emission uncertainties, and extends the geographical extent of emission adjustments.

Long-term urban carbon dioxide observations reveal spatial and temporal dynamics related to urban characteristics and growth.

Cities are concentrated areas of CO2 emissions and have become the foci of policies for mitigation actions. However, atmospheric measurement networks suitable for evaluating urban emissions over time are scarce. Here we present a unique long-term (decadal) record of CO2 mole fractions from five sites across Utah's metropolitan Salt Lake Valley. We examine "excess" CO2 above background conditions resulting from local emissions and meteorological conditions. We ascribe CO2 trends to changes in emissions, since we did not find long-term trends in atmospheric mixing proxies. Three contrasting CO2 trends emerged across urban types: negative trends at a residential-industrial site, positive trends at a site surrounded by rapid suburban growth, and relatively constant CO2 over time at multiple sites in the established, residential, and commercial urban core. Analysis of population within the atmospheric footprints of the different sites reveals approximately equal increases in population influencing the observed CO2, implying a nonlinear relationship with CO2 emissions: Population growth in rural areas that experienced suburban development was associated with increasing emissions while population growth in the developed urban core was associated with stable emissions. Four state-of-the-art global-scale emission inventories also have a nonlinear relationship with population density across the city; however, in contrast to our observations, they all have nearly constant emissions over time. Our results indicate that decadal scale changes in urban CO2 emissions are detectable through monitoring networks and constitute a valuable approach to evaluate emission inventories and studies of urban carbon cycles.