Next Article in Journal
The Baja California Peninsula, a Significant Source of Dust in Northwest Mexico
Previous Article in Journal
Investigating the Behaviour of Human Thermal Indices under Divergent Atmospheric Conditions: A Sensitivity Analysis Approach
Previous Article in Special Issue
Evaluation of Different WRF Parametrizations over the Region of Iași with Remote Sensing Techniques
Open AccessArticle

Estimation of CO2 Emissions from Wildfires Using OCO-2 Data

Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Science, Changchun 130102, China
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(10), 581;
Received: 15 August 2019 / Revised: 14 September 2019 / Accepted: 24 September 2019 / Published: 25 September 2019
(This article belongs to the Special Issue Atmospheric Composition and Cloud Cover Observations)
The biomass burning model (BBM) has been the most widely used method for estimation of trace gas emissions. Due to the difficulty and variability in obtaining various necessary parameters of BBM, a new method is needed to quickly and accurately calculate the trace gas emissions from wildfires. Here, we used satellite data from the Orbiting Carbon Observatory-2 (OCO-2) to calculate CO2 emissions from wildfires (the OCO-2 model). Four active wildfires in Siberia were selected in which OCO-2 points intersecting with smoke plumes identified by Aqua MODIS (MODerate-resolution Imaging Spectroradiometer) images. MODIS band 8, band 21 and MISR (Multi-angle Imaging SpectroRadiometer) data were used to identify the smoke plume area, burned area and smoke plume height, respectively. By contrast with BBM, which calculates CO2 emissions based on the bottom–top mode, the OCO-2 model estimates CO2 emissions based on the top–bottom mode. We used a linear regression model to compute CO2 concentration (XCO2) for each smoke plume pixel and then calculated CO2 emissions for each wildfire point. The CO2 mass of each smoke plume pixel was added to obtain the CO2 emissions from wildfires. After verifying our results with the BBM, we found that the biases were between 25.76% and 157.11% for the four active fires. The OCO-2 model displays the advantages of remote-sensing technology and is a useful tool for fire-emission monitoring, although we note some of its disadvantages. This study proposed a new perspective to estimate CO2 emissions from wildfire and effectively expands the applied range of OCO-2 satellite data. View Full-Text
Keywords: wildfire; CO2 emission; OCO-2; MISR; MINX wildfire; CO2 emission; OCO-2; MISR; MINX
Show Figures

Figure 1

MDPI and ACS Style

Guo, M.; Li, J.; Wen, L.; Huang, S. Estimation of CO2 Emissions from Wildfires Using OCO-2 Data. Atmosphere 2019, 10, 581.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop