DOI: 10.5061/dryad.wstqjq2vd
title: Data from: Plant radiocarbon across an urban-rural CO2 gradient matches surface and column CO2 observations

description: Atmospheric measurements are needed to verify progress in reducing fossil
 fuel carbon dioxide (ffCO2) emissions, especially in cities where most
 ffCO2 is emitted. However, because of complexities in atmospheric dynamics
 and large natural CO2 fluxes, ambient CO2 measurements alone cannot
 distinguish ffCO2 signals. Analysis of the radiocarbon (14C) content of
 urban plants can reveal ffCO2 patterns and is more cost-effective than air
 14CO2 sampling, but its use has been limited because of uncertainty in the
 temporal integration period and because it has not been quantitatively
 evaluated against other atmospheric monitoring approaches. We analyzed the
 14C content of turfgrasses collected along an urban to rural gradient in
 Southern California. The primary study sites are Downtown Los Angeles,
 Pasadena, Irvine, Riverside, and Beaumont, CA. We compare these plant 14C
 to multiscale, atmospheric CO2 measurements including surface CO2 and
 total column CO2 (XCO2). Surface CO2 was measured using cavity ringdown
 spectrometers, and XCO2 was measured using a portable Fourier Transform
 solar spectrometer. Our data shows that plant 14C is highly
 sensitive to local ffCO2 emissions at the intra-city scale and captures
 pronounced differences between urban to rural sites. We observe
 significant correlations between fossil fuel enhancements (Cff) derived
 from plant 14C and from atmospheric CO2. Our findings indicate that plant
 14C analysis can be a very useful tool for quantifying ffCO2 trends in
 cities that lack surface CO2 and XCO2 measurement infrastructure.
description: Measurements of plant <sup>14</sup>C,
 XCO<sub>2</sub>, and surface CO~2 ~were collected
 approximately every three months between May 2022 to March 2023. The study
 focused on five sites along an urban to rural gradient in the Greater Los
 Angeles area: Downtown Los Angeles, Pasadena, Irvine, Riverside, and
 Beaumont, CA. At each site, a series of turfgrass samples were collected
 on irrigated lawns, mostly on university campuses or public parks. A total
 of 147 plant samples were analyzed for <sup>14</sup>C content
 at the University of California's Keck Carbon Cycle AMS
 facility. We also collected ground-based
 XCO<sub>2</sub> measurements using a portable Fourier
 Transform Spectrometer ("EM27/SUN", Bruker).
 XCO<sub>2</sub> was measured at each site for two days per
 seasonal campaign during sunny conditions. The XCO<sub>2</sub>
 data was calibrated based on side-by-side measurements with the Total
 Carbon Column Observing Network (TCCON) site at Caltech, Pasadena. TCCON
 data is publicly available at https://tccondata.org/. Surface CO<sub>2</sub> data for Downtown Los Angeles, Pasadena, and Irvine was provided by the Los Angeles Megacities (LAM) Carbon Project, which is a network of rooftop or tower sites managed by the National Institute of Standards and Technology (NIST). The surface CO<sub>2</sub> data from the LAM network is publicly available at https://data.nist.gov/od/id/mds2-2388 (Verhulst et al., 2017; Kim et al., 2024). Surface CO<sub>2</sub> data collected in Riverside and Beaumont is not managed by NIST and is publicated here. At Beaumont, we measured surface CO<sub>2</sub> at a public park using a Picarro G2401 cavity ringdown spectrometer. Riverside surface CO<sub>2</sub> measurements were collected on a rooftop at the University of California, Riverside.  In addition to the five study sites along the urban-rural gradient, our analysis also relied on measurements at "background" sites. To estimate contributions from fossil fuel-derived CO<sub>2</sub> emissions, we used <sup>14</sup>C, surface CO<sub>2</sub>, and XCO<sub>2</sub> data at several sites to quantify the atmospheric background. For <sup>14</sup>C, the background estimates were based on monthly-integrated air samples collected at Utqiagvik, AK, a remote location far from fossil fuel emission sources (Xu, pers. comm 2023). For surface CO<sub>2</sub>, measurements at San Clemente Island and Victorville, CA were used to characterize the background (Verhulst et al., 2017; Kim et al., 2024). For XCO<sub>2</sub>, measurements at the NASA Armstrong Flight Research Center, a remote desert site near Edwards, CA, were used to estimate background. This site is part of the TCCON network and the data is available at https://tccondata.org/. 
description: # Data from: Plant radiocarbon across an urban-rural CO2 gradient matches
 surface and column CO2 observations
 [https://doi.org/10.5061/dryad.wstqjq2vd](https://doi.org/10.5061/dryad.wstqjq2vd) This dataset includes measurements of plant 14C, surface CO2, and total column CO2 (XCO2), which were collected approximately every three months between May 2022 to March 2023 along an urban to rural gradient in Southern California. The study sites are listed below in order from highest to lowest population density (urban to rural). Unless otherwise stated on the table below, all plant samples were turf grasses. | Site ID | City | Location | Plant 14C data included | XCO2 data included | Surface CO2 data included | | :------ | :----------- | :---------------------------------- | :--------------------------- | :--------------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------- | | **DLA** | Los Angeles | University of Southern California | Yes | Yes | No. Publicly available from NIST at [https://data.nist.gov/od/id/mds2-2388](https://data.nist.gov/od/id/mds2-2388) | | **PAS** | Pasadena | California Institute of Technology | Yes | Yes | No. Publicly available from NIST at [https://data.nist.gov/od/id/mds2-2388](https://data.nist.gov/od/id/mds2-2388) | | **IRV** | Irvine | University of California, Irvine | Yes | Yes | no. Publicly available from NIST at [https://data.nist.gov/od/id/mds2-2388](https://data.nist.gov/od/id/mds2-2388) | | **RIV** | Riverside | University of California, Riverside | Yes | Yes | Yes | | **BEA** | Beaumont | Noble Creek Regional Park | Yes | Yes | Yes | | **SMM** | Calabasas | Stunt Ranch, Santa Monica Mountains | One annual grass in Aug 2022 | Yes, but only visited on two days (Aug 8, 2022 and Nov 14, 2022) | yes | | **MWO** | Mount Wilson | Mount Wilson Observatory | One annual grass in Aug 2022 | Yes, only visited on one day (Aug 8, 2022) | n/a | We aimed to visit DLA, PAS, IRV, RIV, and BEA twice per seasonal measurement campaign if the weather permitted XCO2 measurements (little to no cloud cover). MWO and SMM are secondary sites and were only visited occasionally to evaluate local background conditions.   To calculate fossil fuel CO2 enhancements, our study also relied on measurements collected in "background" sites to represent clean, ambient conditions prior to the enhancement caused by fossil fuel CO2 emissions. The background sites are either upwind of the urban area or in remote locations assumed to have minimal influence from fossil sources. The background data were provided by other publicly accessible datasets and so are not in this repository.  * Background for surface CO2 provided by the Los Angeles Megacity Carbon Project ([https://data.nist.gov/od/id/mds2-2388) ](https://data.nist.gov/od/id/mds2-2388)(Kim et al., 2024; Verhulst et al., 2017) * San Clemente Island (SCI) * Victorville (VIC) * Background XCO2 provided by the TCCON ([https://tccondata.org/) (Wunch et al., 2009)](https://tccondata.org/) * Edwards (AFRC) * Background Air 14C (Xu, pers. comm. 2023) * Utqiagvik, AK (PTB) ## Description of the data and file structure This dataset includes three sets of measurements, each in their own .csv file: 1. plant_14C.csv - Plant radiocarbon data 2. surface_CO2_1hour_BEA_SMM_RIV.csv - 1 hour averages of surface CO2 measured at BEA, SMM, and RIV sites 3. em27_xco2_fivemin.csv - five-minute averages of XCO2 at DLA, PAS, IRV, RIV, BEA, SMM, and MWO Further details about each file are described below. ### Plant 14C (plant\_14C.csv) This file includes radiocarbon data from 147 plant samples collected at the sites listed above. The columns included are:  * UCIT: lab sample identification number * site: three letter site ID defined in the table above * collection_date: the date the sample was collected * year: year of collection * month: month of collection * description: describes location of plant sample relative to where the EM27 was stationed in the format "campus_season_distance-from-EM27-in-meters_direction-from-EM27" * latitude: coordinates in degrees north * longitude: coordinates in degrees east * season: seasonal campaign when sample was collected (Spring 2022, Summer 2022, Fall 2022, Winter 2023) * D14C_obs: measured 14C content of the sample, in the ∆14C notation. The units are in per mil (‰). The ∆14C notation represents the absolute amount of radiocarbon at the time it was measured, including a correction for the radioactive decay of the standard. This notation was used for all analyses in the manuscript. 14C notations are described in detail in Trumbore et al. (2016) * D14C_obs_err: AMS measurement uncertainty of the 14C result in per mil units (‰) * D14C_bg_ptb: the estimated ∆14C (‰) background based on air 14CO2 measurements collected in Utqiagvik, AK (Xu, pers. comm., 2023). These air samples are collected in flasks over approximately one month. The values reported here are the average of the air samples collected in the month the plant samples were collected. ### Surface CO2 (surface\_CO2\_1hour\_BEA\_SMM\_RIV.csv) This file includes the surface CO2 measurements collected at BEA, SMM, and RIV. The data has been aggregated to 1-hour resolution. BEA and SMM measurements were only collected during the site visit while RIV measurements were collected continuously on the roof of Winston Chung Hall at UC Riverside. All values have been calibrated against standard tanks with known CO2 moixing ratios. The columns included are:  * timestamp_PTZ: time in Pacific time zone * site: three letter side ID defined in the table above * CO2: 1-hour averaged CO2 in ppm * CO2_sd: standard deviation of the 1-hour CO2 average in ppm ### XCO2 (em27\_xco2\_fivemin.csv) This file includes XCO2 measurements collected with the EM27/SUN. Column description:  * timestamp_PTZ: time in Pacific time zone * lat(deg): latitude coordinates in degrees north * long(deg): longitude coordinates in degrees east * year * month * day * dayID: date identifier in format YYYYMMDD * season: measurement campaign code. (1 = Spring 2022; 2 = Summer 2022; 3 = Fall 2022; 4 = Winter 2023) * site: three letter side ID defined in the table above * xco2(ppm): total column CO2 in units of ppm, averaged into 5-minute bins * xco2(ppm)_error: measurement uncertainty in total column CO2 Further details about our methodology can be found in our manuscript titled "Plant radiocarbon across an urban-rural CO2 gradient matches surface and column CO2 observations," currently in review. ## References Kim, J., Verhulst, K., Lueker, T., Salameh, P., Cox, A., Walker, S., Paplawsky, W., Prinzivalli, S., Fain, C., Stock, M., DiGangi, E., Biggs, B., Angel, B., Karion, A., Pongetti, T., Callahan, W., Weiss, R., Keeling, R., & Miller, C. (2022). *In Situ Carbon Dioxide, Methane, and Carbon Monoxide Mole Fractions from the Los Angeles Megacity Carbon Project, National Institute of Standards and Technology* [dataset]. https://doi.org/10.18434/mds2-2388 Trumbore, S. E., Sierra, C. A., & Hicks Pries, C. E. (2016). Radiocarbon Nomenclature, Theory, Models, and Interpretation: Measuring Age, Determining Cycling Rates, and Tracing Source Pools. In E. A. G. Schuur, E. Druffel, & S. E. Trumbore (Eds.), *Radiocarbon and Climate Change: Mechanisms, Applications and Laboratory Techniques* (pp. 45–82). Springer International Publishing. [https://doi.org/10.1007/978-3-319-25643-6_3](https://doi.org/10.1007/978-3-319-25643-6_3) Verhulst, K. R., Karion, A., Kim, J., Salameh, P. K., Keeling, R. F., Newman, S., Miller, J., Sloop, C., Pongetti, T., Rao, P., Wong, C., Hopkins, F. M., Yadav, V., Weiss, R. F., Duren, R. M., & Miller, C. E. (2017). Carbon dioxide and methane measurements from the Los Angeles Megacity Carbon Project–Part 1: calibration, urban enhancements, and uncertainty estimates. *Atmospheric and Climate Sciences*. [https://doi.org/10.5194/acp-17-8313-2017](https://doi.org/10.5194/acp-17-8313-2017) Wunch, D., Wennberg, P. O., Toon, G. C., Keppel-Aleks, G., & Yavin, Y. G. (2009). Emissions of greenhouse gases from a North American megacity. *Geophysical Research Letters*, *36*(15). [https://doi.org/10.1029/2009gl039825](https://doi.org/10.1029/2009gl039825)