Articles | Volume 16, issue 21
https://doi.org/10.5194/acp-16-13449-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-13449-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| Highlight paper
| 
31 Oct 2016
Research article | Highlight paper |
| 31 Oct 2016
The BErkeley Atmospheric CO2 Observation Network: initial evaluation
Alexis A. Shusterman
CORRESPONDING AUTHOR
Department of Chemistry, University of California Berkeley, Berkeley,
CA 94720, USA
Virginia E. Teige
Department of Chemistry, University of California Berkeley, Berkeley,
CA 94720, USA
Alexander J. Turner
School of Engineering and Applied Sciences, Harvard University,
Cambridge, MA 02138, USA
Catherine Newman
Department of Chemistry, University of California Berkeley, Berkeley,
CA 94720, USA
Jinsol Kim
Department of Earth and Planetary Science, University of California
Berkeley, Berkeley, CA 94720, USA
Department of Chemistry, University of California Berkeley, Berkeley,
CA 94720, USA
Department of Earth and Planetary Science, University of California
Berkeley, Berkeley, CA 94720, USA
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- Drone-based analysis of CO2 and noise emissions using traffic data and low-cost sensors O. Pascual-Anglès et al. https://doi.org/10.1038/s44333-026-00120-5
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- Monitoring of greenhouse gases and pollutants across an urban area using a light-rail public transit platform L. Mitchell et al. https://doi.org/10.1016/j.atmosenv.2018.05.044
- A city-level comparison of fossil-fuel and industry processes-induced CO2 emissions over the Beijing-Tianjin-Hebei region from eight emission inventories P. Han et al. https://doi.org/10.1186/s13021-020-00163-2
- Expected Performance of a Mobile e-nose platform for Real Time Victim Localization S. Blionas https://doi.org/10.1088/1742-6596/1730/1/012120
- Sustained Performance of Low-Cost Air Quality Sensors in Long-Term Deployments A. Winter et al. https://doi.org/10.1021/acssensors.5c00566
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- Simulating atmospheric tracer concentrations for spatially distributed receptors: updates to the Stochastic Time-Inverted Lagrangian Transport model's R interface (STILT-R version 2) B. Fasoli et al. https://doi.org/10.5194/gmd-11-2813-2018
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- A portable sensor for the determination of tree canopy air quality W. Berelson et al. https://doi.org/10.1039/D3EA00057E
- Monitoring Urban Greenhouse Gases Using Open-Path Fourier Transform Spectroscopy B. Byrne et al. https://doi.org/10.1080/07055900.2019.1698407
- Mapping trends and analyzing key themes in low-cost sensors for air quality monitoring K. Alhasa et al. https://doi.org/10.1007/s12145-025-01927-5
- MUCCnet: Munich Urban Carbon Column network F. Dietrich et al. https://doi.org/10.5194/amt-14-1111-2021
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- Carbon dioxide and methane measurements from the Los Angeles Megacity Carbon Project – Part 1: calibration, urban enhancements, and uncertainty estimates K. Verhulst et al. https://doi.org/10.5194/acp-17-8313-2017
- Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary) A. Clements et al. https://doi.org/10.3390/s17112478
- Toward Establishing a Low-cost UAV Coordinated Carbon Observation Network (LUCCN): First Integrated Campaign in China D. Yang et al. https://doi.org/10.1007/s00376-023-3107-5
- Statistical data pre-processing and time series incorporation for high-efficacy calibration of low-cost NO2 sensor using machine learning S. Koziel et al. https://doi.org/10.1038/s41598-024-59993-6
- Plume Detection and Emissions Quantification Potential Using a Dense Sensor Network M. Patel et al. https://doi.org/10.1021/acsestair.5c00069
- Towards a hygroscopic growth calibration for low-cost PM2.5 sensors M. Patel et al. https://doi.org/10.5194/amt-17-1051-2024
- Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties K. Wu et al. https://doi.org/10.1525/elementa.138
- COCAP: a carbon dioxide analyser for small unmanned aircraft systems M. Kunz et al. https://doi.org/10.5194/amt-11-1833-2018
- Modeling the Atmospheric CO2 Concentration in the Beijing Region and Assessing the Impacts of Fossil Fuel Emissions Z. Liang et al. https://doi.org/10.3390/environments12050156
- Wireless Sensor Node Self-Powered by a Hybrid-Supercapacitor and a Multi-Junction Solar Module M. Bruzzi et al. https://doi.org/10.3390/s26051475
- ACROPOLIS: Munich urban CO2 sensor network P. Aigner et al. https://doi.org/10.5194/amt-19-745-2026
- Using a gradient boosting model to improve the performance of low-cost aerosol monitors in a dense, heterogeneous urban environment N. Johnson et al. https://doi.org/10.1016/j.atmosenv.2018.04.019
- Optimising Citizen-Driven Air Quality Monitoring Networks for Cities S. Gupta et al. https://doi.org/10.3390/ijgi7120468
- An Analysis on the Performance of a Mobile Platform with Gas Sensors for Real Time Victim Localization A. Anyfantis & S. Blionas https://doi.org/10.3390/s21062018
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Short summary
We describe the design of and first results from the BErkeley Atmospheric CO2 Observation Network, a distributed instrument of 28 CO2 sensors stationed across and around the city of Oakland, California at ~ 2 km intervals. We evaluate the network via 4 performance parameters (cost, reliability, precision, systematic uncertainty) and find this high density technique to be sufficiently cost-effective and rigorous to inform understanding of small-scale urban emissions relevant to climate regulation.
We describe the design of and first results from the BErkeley Atmospheric CO2 Observation...
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