Abstract
Abstract. Urban carbon dioxide comprises the largest fraction of anthropogenic greenhouse gas emissions, but quantifying urban emissions at subnational scales is highly challenging, as numerous emission sources reside in close proximity within each topographically intricate urban dome. In attempting to better understand each individual source's contribution to the overall emission budget, there exists a large gap between activity-based emission inventories and observational constraints on integrated, regional emission estimates. Here we leverage urban CO2 observations from the BErkeley Atmospheric CO2 Observation Network (BEACO2N) to enhance, rather than average across or cancel out, our sensitivity to these hyperlocal emission sources. We utilize a method for isolating the local component of a CO2 signal that accentuates the observed intra-urban heterogeneity and thereby increases sensitivity to mobile emissions from specific highway segments. We demonstrate a multiple-linear-regression analysis technique that accounts for boundary layer and wind effects and allows for the detection of changes in traffic emissions on scale with anticipated changes in vehicle fuel economy – an unprecedented level of sensitivity for low-cost sensor technologies. The ability to represent trends of policy-relevant magnitudes with a low-cost sensor network has important implications for future applications of this approach, whether as a supplement to existing, sparse reference networks or as a substitute in areas where fewer resources are available.
Highlights
Initiatives to curb greenhouse gas emissions and thereby reduce the extent of climate-change-related damages are gaining momentum from city to global scales (United Nations, 2015)
The characteristic length scale of this correlation is 2.9 km, which we interpret as an indicator of the distance at which various emission sources exert influence over a site’s measurements
This is an interesting result, given that the traffic flow measured on a single highway likely provides only a first-order approximation of the total traffic emissions influencing a single CO2 monitor, especially those situated at greater distances from said highway, which may be sensitive to additional highways, as well as local roads
Summary
Initiatives to curb greenhouse gas emissions and thereby reduce the extent of climate-change-related damages are gaining momentum from city to global scales (United Nations, 2015). In order to document baseline conditions in and upcoming changes to urban greenhouse gas emissions, surfacelevel monitoring campaigns in cities using varied approaches are being pursued (e.g., Bréon et al, 2015; Chen et al, 2016; McKain et al, 2012, 2015; Shusterman et al, 2016; Turnbull et al, 2015; and Verhulst et al, 2017) These networks, typically consisting of 2–15 instruments, attempt to constrain and supplement activity-based emission inventories with observation-based estimates. We provide an initial approach to quantifying changes in the mobile sector and separating the influence of that sector from other emissions
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
