JpGU-AGU Joint Meeting 2020

Presentation information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS07] Atmospheric Chemistry

convener:Naoko Saitoh(Center for Environmental Remote Sensing), Tomoki Nakayama(Graduate School of Fisheries and Environmental Sciences, Nagasaki University), Sakae Toyoda(Department of Chemical Science and Engineering, Tokyo Institute of Technology), Risa Uchida(Japan Automobile Research Institute)

[AAS07-14] Quantifying thermal power plant CO2 emissions from CO2 total column measurements with portable FTIR spectrometers

*Hirofumi Ohyama1, Kei Shiomi2, Nobuhiro Kikuchi2, Isamu Morino1, Akihiro Hori1, Tsuneo Matsunaga1 (1.National Institute for Environmental Studies, 2.Japan Aerospace Exploration Agency)

Keywords:carbon dioxide, thermal power plant, emission amount, remote sensing

Emissions of carbon dioxide (CO2) from large point sources such as thermal power plants and steel plants account for approximately 40% of the world’s energy-related CO2 emissions. Nowadays, the CO2 emissions from thermal power plants have been quantified based on CO2 column abundances obtained by airborne and satellite-borne remote sensing. In the present study, we evaluated precisions in CO2 emission estimates from simpler and more inexpensive ground-based CO2 column measurements. To this end, we conducted two measurement campaigns for one month each during October 2018 and October−November 2019 to measure CO2 column abundances using two portable Fourier transform infrared (FTIR) spectrometers (EM27/SUN) around a thermal power plant in Japan. In addition, wind profiles in the planetary boundary layer and meteorological parameters at the ground were observed by a Doppler lidar and a meteorological observation system, respectively. We assumed that the CO2 plume rises by a certain height depending on heat emission rate and wind speed at the stack top, and that the horizontal distribution of CO2 column enhancement relative to the background can be represented by a Gaussian plume model. Because the shape of the plume is disturbed by turbulence, the observed CO2 column and meteorological data were averaged into 10 min bins to mitigate that effect. The wind speeds at an effective plume height and the plume widths necessary for CO2 emission estimates were obtained or estimated from the observed values, and highly variable wind directions were retrieved simultaneously with the CO2 emission. We compared the CO2 emissions estimated from the observed data with those converted from hourly fuel consumptions, and it was found that the standard deviation (1σ) of the differences was ~20%.