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GID – Global Infrastructure Emission Database GHGs

Global economic development is highly dependent on fossil fuels currently. The infrastructure worldwide emits a large amount of greenhouse gases (GHGs) and air pollutants when generating and consuming fossil fuels, which has detrimental impact on climate change, air quality and human health. Considering their several-decade lifetime, the newly built highly

Global economic development is highly dependent on fossil fuels currently. The infrastructure worldwide emits a large amount of greenhouse gases (GHGs) and air pollutants when generating and consuming fossil fuels, which has detrimental impact on climate change, air quality and human health. Considering their several-decade lifetime, the newly built highly CO2-emitting infrastructure in the developing countries with rapid economic growth will continuously produce a great quantity of carbon emissions (i.e. committed carbon emissions), seriously threating the transformation towards low-carbon energy structure and the realization of carbon neutral. Energy infrastructure is the basic unit of GHGs and air pollutant emissions, and is also the foothold to formulate the strategies targeting climate change and air pollution control. However, for a long time, the basic infrastructure data of many countries and regions is opaque and unpublished, and unified data basis and technical methods are also lacking. Thus, currently most research targeting global emissions of key sectors and their climate and environmental impact can only be conducted at a relatively macroscopic scale, and struggle to provide enough support for scientific research and policy making.

The Global Energy Infrastructure Emissions Database (GID) was developed to establish a global energy infrastructure database including unit-/facility-level basic information and emissions in order to provide solid data support for scientific research and policy making. The GID team conducts data mining on multiple global and regional energy infrastructure databases, sorts out basic information of more than 100,000 energy-generating and consuming facilities in service worldwide, and uses big data methods to develop a unified emission quantification model, successfully obtaining unit-/facility-level CO2 and air pollutant emissions on the basis of efforts above.

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