Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
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Assessment of Atmospheric Greenhouse Gas Concentration Equipment Performance

대기 중 온실가스 농도 관측 장비 성능 비교 검증

  • Chaerin Park (Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University) ;
  • Sujong Jeong (Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University) ;
  • Seung-Hyun Jeong (Korea Testing & Research Institute) ;
  • Jeong-il Lee (Department of Environmental and Chemical Engineering, SeoKyeong University) ;
  • Insun Kim (National Institute of Environmental Research) ;
  • Cheol-Soo Lim (National Institute of Environmental Research)
  • Received : 2023.11.04
  • Accepted : 2023.11.21
  • Published : 2023.11.30
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Abstract

This study evaluates three distinct observation methods, CRDS, OA-ICOS, and OF-CEAS, in greenhouse gas monitoring equipment for atmospheric CO2 and CH4 concentrations. The assessment encompasses fundamental performance, high-concentration measurement accuracy, calibration methods, and the impact of atmospheric humidity on measurement accuracy. Results indicate that within a range of approximately 500 ppm, all three devices demonstrate high accuracy and linearity. However, beyond 1000 ppm, CO2 accuracy sharply declines (84%), emphasizing the need for caution when interpreting high-concentration CO2 data. An analysis of calibration methods reveals that both CO2 and CH4 measurements achieve high accuracy and linearity through 1-point calibration, suggesting that multi-point calibration is not imperative for precision. In dynamic atmospheric conditions with significant CO2 and CH4 concentration variations, a 1-point calibration suffices for reliable data (99% accuracy). The evaluation of humidity impact demonstrates that humidity removal devices significantly reduce air moisture levels, yet this has a negligible effect on dry CO2 concentrations (less than 0.5% relative error). All three observation method instruments, which have integrated humidity correction to calculate dry CO2 concentrations, exhibit minor sensitivity to humidity removal devices, implying that additional removal devices may not be essential. Consequently, this study offers valuable insights for comparing data from different measurement devices and provides crucial information to consider in the operation of monitoring sites.

Keywords

Acknowledgement

본 논문은 환경부의 재원으로 국립환경과학원의 지원을 받아 수행하였습니다(NIER-2022-04-02-046).

References

  1. Chen, L., G. Msigwa, M. Yang, A. I. Osman, S. Fawzy, D. W. Rooney, and P.-S. Yap, 2022: Strategies to achieve a carbon neutral society: a review. Environ. Chem. Lett., 20, 2277-2310, doi:10.1007/s10311-022-01435-8.
  2. Coumou, D., and S. Rahmstorf, 2012: A decade of weather extremes. Nature Climate Change, 2, 491-496, doi:10.1038/nclimate1452.
  3. Friedlingstein, P., and Coauthors, 2019: Global carbon budget 2019. Earth Syst. Sci. Data, 11, 1783-1838, doi:10.5194/essd-11-1783-2019.
  4. G2301: Picarro Inc., Santa Clara, CA, USA [Available online at https://www.picarro.com/g2301_gas_concentration_analyzer].
  5. Gao, Y., X. Lee, S. Liu, N. Hu, X. Wei, C. Hu, C. Liu, Z. Zhang, and Y. Yang, 2018: Spatiotemporal variability of the Near-Surface CO2 concentration across an industrial-urban-rural transect, nanjing, China. Sci. Total Environ., 631, 1192-1200, doi:10.1016/j.scitotenv.2018.03.126.
  6. GLA331-GGA: ABB-LGR Inc., Zurich, Switzerland [Available online at https://new.abb.com/products/measurement-products/analytical/laser-gas-analyzers/laseranalyzers/lgr-icos-enhanced-performance-rackmount-analyzers/lgr-icos-enhanced-performance-rackmount-analyzers-gla331-series].
  7. Hutyra, L. R., S. Raciti, N. G. Phillips, and J. William Munger, 2011: Exploring Space-Time Variation in Urban Carbon Metabolism. Addressing Grand Challenges for Global Sustainability, 11-14 [Available online at https://static.sustainability.asu.edu/docs/ugec/viewpoints/ugec-view-points-6.pdf#page=11].
  8. LI-7810: Licor Inc., Lincoln, NE, USA [Available online at https://www.licor.com/env/products/trace_gas/LI-7810].
  9. LI-7815: Licor Inc., Lincoln, NE, USA [Available online at https://www.licor.com/env/products/trace_gas/LI-7815].
  10. McKain, K., S. C. Wofsy, T. Nehrkorn, J. Eluszkiewicz, J. R. Ehleringer, and B. B. Stephens, 2012: Assessment of Ground-Based atmospheric observations for verification of greenhouse gas emissions from an urban region. Proc. Natl. Acad. Sci., 109, 8423-8428, doi:10.1073/pnas.1116645109.
  11. Miyaoka, Y., H. Y. Inoue, Y. Sawa, H. Matsueda, and S. Taguchi, 2007: Diurnal and seasonal variations in Atmospheric CO2 in Sapporo, Japan: anthropogenic sources and biogenic sinks. Geochem. J., 41, 429-436, doi:10.2343/GEOCHEMJ.41.429.
  12. Moore, J., and A. D. Jacobson, 2015: Seasonally varying contributions to urban CO2 in the Chicago, illinois, USA region: insights from a High-Resolution CO2 concentration and δ13C record. Elementa: Sci. Anthropocene, 3, 000052, doi:10.12952/journal.elementa.000052.
  13. Nangini, C., and Coauthors, 2019: A global dataset of CO2 emissions and ancillary eata related to emissions for 343 cities. Sci. Data, 6, 1-29, doi:10.1038/sdata.2018.280.
  14. Pan, C., X. Zhu, N. Wei, X. Zhu, Q. She, W. Jia, M. Liu, and W. Xiang, 2016: Spatial variability of daytime CO2 concentration with landscape structure across urbanization gradients, Shanghai, China. Climate Res., 69, 107-116, doi:10.3354/cr01394.
  15. Park, C., and Coauthors, 2020: Challenges in monitoring atmospheric CO2 concentrations in Seoul using Low-Cost sensors. Asia-Pac. J. Atmos. Sci., 57, 547-553, doi:10.1007/s13143-020-00213-2.
  16. Park, C., S. Jeong, Y.-S. Shin, Y.-S. Cha, and H.-C. Lee, 2021: Reduction in urban atmospheric CO2 enhancement in Seoul, South Korea, resulting from social distancing policies during the COVID-19 Pandemic. Atmos. Pollut. Res., 12, 101176, doi:10.1016/j.apr.2021.101176.
  17. Park, C., S. Jeong, H. Park, S. Sim, J. Hong, and E. Oh, 2022a: Comprehensive assessment of vertical variations in urban atmospheric CO2 concentrations by using tall tower measurement and an atmospheric transport model. Urban Climate, 45, 101283, doi:10.1016/j.uclim.2022.101283.
  18. Park, C., S. Jeong, M.-S. Park, H. Park, J. Yun, S.-S. Lee, and S.-H. Park, 2022b: Spatiotemporal variations in urban CO2 flux with Land-Use types in Seoul. Carbon Balance and Manag., 17, 1-14, doi:10.1186/s13021-022-00206-w.
  19. Park, C., S. Jeong, C. Kim, J. Shin, and J. Joo, 2023: Machine learning based estimation of urban on-road CO2 concentration in Seoul. Environ. Res., 231, 116256, doi:10.1016/j.envres.2023.116256.
  20. Shusterman, A. A., V. E. Teige, A. J. Turner, C. Newman, J. Kim, and R. C. Cohen, 2016: The BErkeley atmospheric CO2 observation network: initial evaluation. Atmos. Chem. Phys., 16, 13449-13463, doi:10.5194/acp-16-13449-2016.
  21. Sim, S., and Coauthors, 2020: Co-Benefit potential of urban CO2 and air quality monitoring: a study on the first mobile campaign and building monitoring experiments in Seoul during the winter. Atmos. Pollut. Res., 11, 1963-1970, doi:10.1016/j.apr.2020.08.009.
  22. Stocker, T., 2014: Climate Change 2013: The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge university press, 1535 pp [Available online at https://www.ipcc.ch/report/ar5/wg1/].
  23. Sugawara, H., S. Ishidoya, Y. Terao, Y. Takane, Y. Kikegawa, and K. Nakajima, 2021: Anthropogenic CO2 emissions changes in an urban area of Tokyo, Japan, due to the COVID-19 pandemic: a case study during the state of emergency in April-May 2020. Geophys. Res. Lett., 48, e2021GL092600, doi:10.1029/2021GL092600.
  24. Takano, T., and M. Ueyama, 2021: Spatial variations in daytime methane and carbon dioxide emissions in two urban landscapes, Sakai, Japan. Urban Climate, 36, 100798, doi:10.1016/j.uclim.2021.100798.
  25. Verhulst, K. R., and Coauthors, 2017: Carbon dioxide and methane measurements from the Los Angeles megacity carbon Project-Part 1: calibration, urban enhancements, and uncertainty estimates. Atmos. Chem. Phys., 17, 8313-8341, doi:10.5194/acp-17-8313-2017.
  26. Xueref-Remy, I., and Coauthors, 2018: Diurnal, synoptic and seasonal variability of atmospheric CO2 in the Paris megacity area. Atmos. Chem. Phys., 18, 3335-3362, doi:10.5194/acp-18-3335-2018.