Data Mining a City: Where Does Data for Emissions Calculation Come From and How Are Gaps Managed?

City Emission Data: Sources and Gaps

Calculating a city's carbon footprint is like completing a giant jigsaw puzzle. The pieces of this puzzle are made up of thousands of different data points from each building, each bus, landfills and factories. the success of the "City Calculator" depends on the accuracy and diversity of this data.

But where are such complex and diverse data sets collected from, and how does the GPC Standard provide a roadmap in case of data gaps?

Multi-Source Data Streaming: Taking the Pulse of the City

A single source is never enough to calculate city emissions. Data is obtained by combining information flowing through different veins of the city. Here are the main data sources:

Municipal and Energy Statistics: Electricity and natural gas consumption data for residential, commercial and public buildings in the city, usually from distribution companies or national energy balance tables.
Transportation Data: Statistics on urban traffic density, fuel consumption of public transport, number of registered vehicles and fuel consumption per kilometer are critical.
Waste Records: Data on the amount of solid waste generated in the city, waste composition (organic, plastic, etc.) and wastewater treatment plants are vital sources, especially for calculating methane emissions.
International Databases (CIRIS etc.): Where local data is insufficient, databases from tools such as CIRIS (City Inventory Reporting and Information System) provide a reliable source for standard emission factors and global warming potentials (GWP).

Dealing with Lack of Data: Proxy and Scaling Methods

In the real world, not every city has perfect data sets. Some data may be missing, outdated or inaccessible. Instead of stopping the calculation in these cases, the GPC Standard recommends scientifically accepted compensation methods:

Scaling: If you do not have data for the whole city, you can generalize from a representative sample. For example, if waste data for 10% of the population is known, this data can be scaled according to the population to create an estimate for the whole city.
Using Proxy Data: When direct data is not available, another indicator that can represent that data is used. For example, if the exact fuel consumption of a building is unknown, a "proxy" value can be assigned using national averages based on the square meter of the building and its intended use (residential/commercial).

The Power of Technology: CimpactPro CITY and Integration

Managing this multi-source and complex data flow manually (e.g. with Excel) increases the risk of errors and wastes time. Advanced software like CimpactPro CITY solves this problem by centralizing data from hundreds of different sources (schools, public transport, public facilities, etc.) on a single platform.

Moreover, thanks to its AI-powered modules (EcoPilot City), it automatically classifies large and dispersed data sets, identifies missing data and recommends gap-filling methods that comply with GPC standards. In this way, cities not only collect data, but also turn it into a strategic climate action plan.