Eika CAN technical description

Background

Facing climate change and nature loss, reflecting on the interlinked climate-nature crisis, calls actions in different economic sectors. To enhance corporate transparency, investor confidence and finally more sustainable practices across different sectors, the European Sustainability Reporting Standards (ESRS) under the Corporate Sustainability Reporting Directive (CSRD) have been established. The standard requires estimation and reporting regarding the companies effect on environment and society.

The following application (CAN tool), at the proof of concept (POC) stage, facilitates reporting and tracking impacts of building activities on climate and nature. Thus, climate effects (E1) and natue effects (E4) of the ESRS are partially covered with the tool.

Novelty

The tool uses spatial explicit data of the area of building activity (plot or region of impact) and locally valid climate and nature data. Consequently, the reporting of climate and nature impact summarizes project-based impact estimates.

Goals

• Screen projects for potential high risk exposure/vulnerabilities regarding climate change
• Screen projects for potential negative impacts on valuable nature
• Facilitate reporting of a whole project portfolio

Data

To calculate potential risk exposure of climate change and impacts on valuable nature of specific projects, local valid and high resolution data layers are used:

Calculations

The calculations of climate and nature risk follows a three step approach:

1. Selection of a municipality Load the local data and visualize the data through WMS layers

2. Select a plot from the “teig” data using brusknummer, gårdsnummer and teignummer

• Load the plot geometry
• Calculate min distance of the plot to each data layer (climate & nature)

distance <- st_distance(plot_geom, layers[[i]]) %>% min()  # Closest distance

• if min dist == 0 calculate intersection polygon and intersection polygon area

 if(as.numeric(distance) == 0){
        # Compute intersection AREA
        intersection <- TRUE
        intersect_poly<-st_intersection(geom, layers[[i]])%>%select()%>%mutate(layer_id = names(layers[i])) #geometry
        intersection_area <- st_area(intersect_poly) #area

      }else{
        intersection <- FALSE
        intersect_poly<- NULL
        intersection_area <- NA

      }

• Calculate area per land-use/land-cover (raster) class within the plot

overlap_stats <- exactextractr::exact_extract(raster, plot_geom)

3. Visualize results of project screening and update portfolio.

Outputs

The outputs show red and green “flags” according to intersection and non-intersection of the project area with one or several climate or nature layers. For each layer the intersection, intersection area and areas per land-cover/land-use class can be saved as CSV. In addition the results for each plot are saved on a DUCK data base (duckdb)

Covered ESRS data points

The tools covers the following data points from the ESRS reporting standard on numerical, spatially explicit basis.