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11:19
Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
Published on: October 21, 2016
Assessment of global carbon dioxide concentration using MODIS and GOSAT data.
Meng Guo1, Xiufeng Wang, Jing Li
1Graduate School of Agriculture, Hokkaido University, Sapporo 060-8589, Japan. guomeng@env.agr.hokudai.ac.jp
Sensors (Basel, Switzerland)
|February 28, 2013
Summary
This study introduces the TVP model, utilizing MODIS remote sensing data to estimate global carbon dioxide (CO2) concentrations. The model shows varying accuracy across continents, offering a new method for long-term CO2 monitoring.
Area of Science:
- Earth and Environmental Sciences
- Atmospheric Science
- Remote Sensing
Background:
- Carbon dioxide (CO2) is a primary greenhouse gas driving global warming.
- Current CO2 monitoring relies on limited ground stations and short satellite data series, hindering long-term regional/global analysis.
- Remote sensing data offers a solution, especially for areas with sparse ground observations.
Purpose of the Study:
- To develop and validate a novel model (TVP) for assessing global CO2 concentrations.
- To leverage MODIS remote sensing data for improved CO2 monitoring capabilities.
- To evaluate the TVP model's accuracy against satellite-derived CO2 measurements.
Main Methods:
- Developed the TVP model integrating MODIS data: temperature (MOD11C3), vegetation cover (MOD13C2, MOD15A2), and productivity (MOD17A2).
- Utilized CO2 concentration data from the Thermal And Near infrared Sensor for carbon Observation (TANSO) aboard the Greenhouse gases Observing SATellite (GOSAT) as ground truth.
- Assessed TVP model accuracy using Pearson's correlation coefficient (R2) and Root Mean Square Error (RMSE) across different continents.
Main Results:
- The TVP model demonstrated varying accuracy globally, with the highest R2 of 0.75 in Eurasia and South America (RMSE = 1.16-1.17).
- The lowest accuracy was observed in Australia, with an R2 of 0.57 (RMSE = 0.73).
- Overall global accuracy against TANSO-observed CO2 (XCO2) ranged from -2.56 to 3.14 ppm.
Conclusions:
- The TVP model provides a viable method for global CO2 concentration assessment using MODIS data.
- Continental variations in model accuracy were identified, necessitating further analysis of uncertainty sources.
- The study highlights the potential of remote sensing for enhancing long-term greenhouse gas monitoring.
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