Observing Anthropogenic and Biogenic CO₂ Emissions in Los Angeles Using a Dense Sensor Network.

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Urban Ecology

Background:

• Urban areas significantly contribute to greenhouse gas emissions, requiring robust monitoring for effective climate change mitigation.
• Dense sensor networks provide high-resolution data for tracking urban emissions.
• The Berkeley Environmental Air-quality & CO2 Observation Network (BEACO2N) offers a valuable tool for this purpose.

Purpose of the Study:

• To develop and validate a simple, precise method for quantifying urban greenhouse gas emissions.
• To differentiate between fossil fuel and biogenic CO2 emissions in urban environments.
• To establish a framework for constraining seasonal and annual emission trends using sensor network data.

Main Methods:

• Analysis of CO2 and CO measurements from 12 BEACO2N sites in Los Angeles (USC Carbon Census) within a box model.
• Partitioning of total CO2 emissions into fossil fuel and biogenic components.
• Correlation of inferred biogenic emissions with the MODIS enhanced vegetation index (EVI).

Main Results:

• A precise method for quantifying urban emissions was successfully demonstrated.
• Biogenic emissions were inferred to consume up to 60% of fossil fuel emissions during the growing season (daytime).
• Temporal changes in biogenic emissions corresponded with vegetation index variations.

Conclusions:

• The described approach enables precise quantification of urban emissions, aiding in the evaluation of mitigation strategies.
• The study highlights the significant role of biogenic processes in urban carbon cycling.
• The method is feasible for constraining annual and long-term emission trends.