Hourly, Daily, and Seasonal Patterns of Atmospheric CO2 Along an Urbanization Gradient
A. Dunn1, B. Briber2, L. Hutyra2 and J.W. Munger3
1Worcester State University, 486 Chandler St, Worcester, MA 01602; 508-929-8641, E-mail: firstname.lastname@example.org
2Boston University, Department of Geography/Environment, Center for Energy/Environmental Studies, Boston, MA 02215
3Department of Earth and Planetary Sciences and the Division of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
Cities occupy less than 3% of global land area, but are estimated to produce nearly three-quarters of anthropogenic CO2 emissions (IEA 2008). Therefore, these small geographic features exert a disproportionate influence on atmospheric CO2 concentrations on multiple spatial scales. However, the patterns of CO2 in urban areas are controlled not only by anthropogenic emissions, but also by biogenic and micrometeorological processes. The aggregate behavior of these diverse processes on atmospheric CO2 concentrations represents a critical gap in our understanding of the terrestrial carbon cycle, complicating efforts to develop a framework for regulation and verification of carbon emissions.
In order to better understand these drivers of atmospheric CO2 in an urbanized area, we analyzed measurements of atmospheric CO2 made from towers in Boston, Worcester, and Harvard Forest (Petersham), Massachusetts. These locations span the urban-rural gradient of central and eastern Massachusetts, allowing detection of the factors contributing the atmospheric CO2 signal in this region. Our results show significant differences between the sites on hourly, seasonal, and annual timesteps. The annual mean CO2 mixing ratios were 408.2 ± 0.2, 401.5 ± 0.4, and 393.0 ± 0.3ppm at Boston, Worcester, and Harvard Forest, respectively. Across the gradient, peak CO2 concentrations were observed in winter, corresponding with the timing of maximum anthropogenic emissions (Gurney et al. 2009) and minimum biogenic uptake. Midday CO2 concentrations in the summer demonstrate significant drawdown (≥ 10 ppm) from the 24-hour median value across all three sites, highlighting the importance of biogenic fluxes, even at the highly urbanized Boston site.
These data represent a critical component of a model-data framework designed to make high-resolution inferences about sources and sinks of atmospheric CO2. We will use the Stochastic Time Inverted Lagrangian Transport model to estimate surface fluxes on the basis of the time series data at our three locations. The results from this work will allow us to directly connect the influence of anthropogenic processes to observed atmospheric CO2 for verification of future greenhouse gas agreements and treaties.