Could satellite measurement of CO help us to better understand sources of atmospheric CO2?
Regions of interest
Due to limited satellite observations and effective data retrievals of CO and CO2 measurements, we focus on three regions with relatively rich data information based on the visualization of global data distribution. The regions are North Africa, Central US and Central China, whose geolocation scopes are listed in the left table.
The time we focus on is 2005.
The time we focus on is 2005.
MOPITT
The CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) instrument, provide global information of CO mixing ratio in different altitude layers in troposphere.
Level 3M dataset provides column measurement, surface mixing ratio, mixing ratio profiles of CO within troposphere, with spatial resolution of 1 degree latitude by 1 degree longitude, temporal resolution of one month. Some ancillary variables are provided as well, like surface emission, surface temperature etc.
The data we use in this project is surface mixing ratio of CO with unit ppbv (Part Per Billion by Volume).
All the items in the data contains two independent data files, describing measurement average for daytime and nighttime. The data is in the form of HDF. Figure in the left shows the variable name list as well as some sample values in the data file.
Level 3M dataset provides column measurement, surface mixing ratio, mixing ratio profiles of CO within troposphere, with spatial resolution of 1 degree latitude by 1 degree longitude, temporal resolution of one month. Some ancillary variables are provided as well, like surface emission, surface temperature etc.
The data we use in this project is surface mixing ratio of CO with unit ppbv (Part Per Billion by Volume).
All the items in the data contains two independent data files, describing measurement average for daytime and nighttime. The data is in the form of HDF. Figure in the left shows the variable name list as well as some sample values in the data file.
SCIAMACHY
Global Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) dataset provides total column retrievals both for CO and CO2. The data is in ASCII format.
In this project, we use CO (version0.6) and CO2 (version 1.0) column data for analysis. The spatial resolution is 0.5 degree latitude by 0.5 degree longitude. And the temporal resolution is 1 month. The figure on the left side shows the CO2 column data in March in North Africa, where white grid means missing data.
In this project, we use CO (version0.6) and CO2 (version 1.0) column data for analysis. The spatial resolution is 0.5 degree latitude by 0.5 degree longitude. And the temporal resolution is 1 month. The figure on the left side shows the CO2 column data in March in North Africa, where white grid means missing data.
GFED
Global fire emission database (GFED) version 2 (Randerson, J. T., 2007) is a product which provides information about fire emission based on satellite data (fire areas detected) as well as biogeochemical models (amount of gas emission calculated). Here we use CO and CO2 emission datasets. The temporal resolution is one month while the spatial resolution is 1 degree latitude by 1 degree longitude.
EDGAR
Emission Database for Global Anthropogenic Research (EDGAR) provide the information of gas emission by human activity based on report from different countries. Categories involved are shown in the left table. For the year 2005, emission report of CO is not available. The data we use in this project is CO2 emission from EDGAR version 4.0 product.
Presented above are the constitutions of CO2 emissions in three regions. It is clear that in North Africa, emission from fires are much more than anthropogenic emission, while in other two regions, which are more industrialized than North Africa, anthropogenic emission overweights the fires emission.
From the figure above, it is evident that among the three regions, North Africa has the most fires emission of CO2 while central China has the most anthropogenic CO2 emission.
Simple summary of datasets used
Some characteristics of the datasets used in the project are listed here. For CO, we have satellite measurements from two sources: MOPITT and SCIAMACHY. EDGAR has the coarsest temporal resolution.
