Futureproofed helps you to organise all climate-related data in one place. We acknowledge that "data" is a broad term. We classify data into three main categories:
Diagnosis. 🩺 Data needed to calculate an emissions inventory.
Impact. ⚡ Data needed to calculate the impact of climate measures.
Monitoring. 🖥️ Data needed to update the progress of the climate measures and actions.
In the next lines, you will find a list of must-have and good-to-have data for each category, as well as examples and tips. 🚀
Diagnosis data 🩺 Data needed to calculate an emissions inventory
Getting an emissions inventory is the first step to know what are the big challenges for your city and take action accordingly.
The must-have data needed in this step is:
Energy consumption (MWh) per type of energy (e.g. gasoline, heating oil) and per sector (e.g. households, tertiary, private transport).
Emission factors of electricity and warmth/cold per year (kg CO2/kWh).
The good-to-have data for this step include:
General city statistics (e.g. population in the number of inhabitants, the surface area of your city in km2).
Other emission factors (kg CO2/kWh).
Tips:
You can import in bulk the energy consumption data. This article explains how.
Futureproofed has developed a free portal with emissions data. If your territory is already covered with Launchpad, you can get started right away and have periodic updates.
Impact data ⚡ Data needed to calculate the impact of climate measures
Climate measures are the building blocks of your climate plan. Futureproofed enables you to assess the positive impact of measures in three returns: emissions reduced, financial savings and co-benefits.
Attention: ⚠️ This list might seem long, but the data needed in your plan will depend on the climate measures that your city chooses to take.
The must-have data needed in this step is:
For energy-efficiency measures such as building renovations:
General households data (e.g. average roof area in m2)
Energy efficiency (e.g. thermal transmittance through walls after the insulation in W/m²K)
For renewable energy measures:
Energy potential (e.g. yield of solar panels in kWh/kWp)
Investment costs (e.g. solar panel investment in €/kWp)
For adaptation measures:
Risk addressed (e.g. floods, heatwaves, ...)
Average additional investment costs (€/year)
For transportation measures
Statistics about the traffic (e.g. or number of vehicle kilometres driven by gasoline, diesel, electric, etc vehicles)
Specific economic figures for the transport sector (e.g. Additional investment cost EV in €)
Data useful for all measures
Fuel prices (e.g. electricity cost in €/kWh)
The lifespan of the measure (in years)
City-wide financial parameters (e.g. discount rate in %)
The good-to-have data for this step include:
General city statistics (e.g. number of company cars)
Specific data on nature (e.g. cost of planting a tree) and heating technologies (e.g. heat pump efficiency, biomass boiler running hours, ...)
Co-benefits
Ranking of co-benefits (3-star system)
Local examples
Tips:
When adding a new measure from the standardised list, we will suggest measure parameters based on known values for other cities so you don't start from zero.
This article explains more in detail the information needed to create your own measure from scratch.
Monitoring data 🖥️ Data needed to update the progress of the climate measures and actions
Once your city has chosen measures, you need data to follow up on the progress of implementation. This is done by updating the key performance indicators (KPIs) for each measure.
The must-have data needed in this step is:
The chosen unit for monitoring each measure that was added to your plan. The most common KPIs for measures are:
The number of households where a measure has been applied (e.g. households with new wall insulation, solar panels, ...)
The number of car kilometres reduced due to modal shift measures (e.g. car kilometres avoided thanks to an increase in walking/cycling).
Number of tertiary buildings where a measure has been applied (e.g. buildings with new lighting)
MWh of renewable energy produced (e.g. renewable energy produced via solar panels)
The good-to-have data for this step:
In case you don't have figures on specific KPIs, you can use derived units instead. For example, you can monitor the progress of an insulation measure in the household sector if you know the number of m2 renovated in a year, translating that into a number of households with the help of a conversion factor provided by us.
Tips:
For some territories, we help you find public sources of data for monitoring the progress of your measures. For example, this article (in French) showcases public data available in Wallonia for monitoring climate plans.
Good to know:
All of the data covered in this article is organised in your account via the Data input page.