Reductions in greenhouse gases are urgently needed to mitigate climate change.
The Intergovernmental Panel on Climate Change (IPCC) has highlighted the urgency of steep emissions reductions to keep global warming below 1.5° C. Cumulative emissions of 2,390 Gt CO2 since 1850 have been associated with global warming of about 1.07° C. To stay within the 1.5° ceiling with high probability, future emissions will need to be limited to 300 Gt CO2. The discussions at COP26 last year also highlighted the critical need for countries to accelerate carbon reductions in the near term and move towards net zero emissions in the longer term.
In their Nationally Determined Contributions (NDCs), more than 150 nations have outlined their ambition to reduce carbon emissions and adapt to the impacts of climate change. The Paris Agreement requires nations to measure and report progress toward their pledged reductions in emissions.
Limited information has impeded progress.
These pledges and action plans face a striking measurement challenge at the outset – many nations do not have the infrastructure to directly measure carbon emissions. They often rely on emissions parameters from engineering studies, which are applied to survey-based activity measures for transport, energy production and manufacturing. Standard engineering estimates are particularly suspect for developing countries because many of the parameters have been calibrated using databases and models developed for high-income economies.
The measurement challenge is particularly important for mitigation measures such as carbon credit and offset markets, as well as green bonds that rely on robust monitoring, reporting, and verification (MRV) systems.
Using the power of satellites to track carbon pledges
The database uses satellite data from NASA’s OCO (Orbiting Carbon Observatory)-2 satellite, which provides reliable information about global CO2 emissions at high levels of spatial resolution. OCO-2 follows a sun-synchronous near-polar orbit, crosses the equator in ascending mode around 1330 hours local time and has an observation repeat time of 16 days.
The satellite measures CO2 in the column of air between its position and the Earth’s surface, and can detect additional or reduced levels of the gas before it becomes uniformly mixed in the atmosphere. Extensive research has demonstrated that satellite data can provide direct, independent, low-cost and consistent measures for CO2 emissions monitoring (e.g., Pan et al. 2021).
While data from OCO-2 can be downloaded free of cost, significant processing is needed to make the data ready for emissions tracking. This includes filtering local emissions effects (termed “concentration anomalies”) from the trend in atmospheric CO2 that has accumulated since the industrial revolution, as well as seasonal changes reflecting differential absorption and release of CO2 by vegetation cover.
Constructing and processing the data
The World Bank’s Development Economics Vice Presidency’s Development Data Hub is establishing an open web facility that pre-filters the OCO-2 data and publishes spatially-referenced monthly mean CO2 concentration anomalies for the entire terrestrial world.
The database downloads monthly updates of the georeferenced measures of XCO2—the column-averaged, dry-air mole fraction of the gas—which it filters for the effects of concentration anomalies (i.e., local emissions). The filtering process follows the methodology of Hakkarainen et al. (2019). It incorporates both temporal and geographic elements, and uses the median as the representative daily XCO2 value since it is not skewed by extreme observations. Because the available data are not sufficient for estimating daily medians at resolutions higher than 10 degrees of latitude, the system computes the daily median XCO2 for each 10-degree latitude band and linearly interpolates the result to each OCO-2 observation at 1-degree resolution. It computes the concentration anomaly for each observation by subtracting the median value from observed XCO2, and computes and reports the monthly mean values in a terrestrial grid at 25 km resolution.
The gridded data can be aggregated to provide new data-driven insights into CO2 emissions for areas of interest (urban areas, other administrative areas such as districts/provinces/countries, landscapes/basins/watersheds or coastal zones) This can help promote a new generation of free/low-cost Monitoring, Reporting & Verification (MRV) systems that can facilitate mitigation investment instruments (e.g., performance-based payments in targeted areas of interest).
Accessing CO2 data at your fingertips
The database is accessible at this link and there are several dashboards that illustrate the visualization of the data (along with other development data), including the World Bank’s Development Data Hub, Geospatial Platform and Spatial Agent App. Since context matters, the CO2 data can be integrated with other climate and development data using a wide range of analytical/visualization tools to support diverse applications. In the future, these platforms will incorporate other greenhouse gasses such as methane.
The database responds to the SDG Decade of Action, which calls for broadening global access to policy-critical data and demonstrating their use. It meets the urgent need to track carbon pledges by providing objective, spatially-referenced, frequently-updated information for tracking CO2 trends in local areas and regions. With gridded information at 25 km resolution, the system can support analyses for states, provinces, urban areas and project areas. It can incorporate user-defined area boundaries, as well as standard boundaries for administrative areas. The system can be useful for World Bank studies such as CCDRs, as well as research by global stakeholders on CO2 emissions sources and changes over time.
We gratefully acknowledge financial support from the Knowledge for Change Program.