Data collection guidelines for GBS assessments – v1.2

Data collection

guidelines for GBS assessments – v1.2

July 2020

1. Introduction

a. Perimeters definition

b. Data & impact factor quality

c. Uncertainty: Central, optimistic, conservative values d. Two options for data collection

2. Data for the framework of the assessment

a. Hierarchy: group dimensioning b. Hierarchy: group attribution

3. Data for the screening phase

a. Ecological integrity screening b. Risk of extinction screening

4. Data for the refined data collection phase

a. Ecological data b. Pressures data

c. Physical inventory flow data d. Monetary inventory flow data

5. References

PAGE 2

Content

1. Introduction

PAGE 4

Steps of a GBS-based Biodiversity Footprint Assessment

Assessme nt framework

(1.1)

• Perimeters Definition: geographical, organisational, temporal

• Scopes: 1, 2 and 3

• Hierarchy structure: “Site level” definition, hierarchy design

Screening (1.2)

• “Ecological integrity” screening: default assessment of the value chain of the company

• “Risk of extinction” screening: protected areas, endangered species, etc.

Refined data collection

• Ecological survey data

• Pressures data: terrestrial and aquatic pressures data

• Physical inventory data: physical and/or monetary flow

• Qualitative data: interviews and literature

Assessme nt of impacts

• Quantitative analysis

Results

• Interpretation & qualitative analysis – environmental safeguards

• Comparison to references

• Recommendations for a biodiversity action plan

Step 1 Framing

Steps 4,5,6 Results

Step 2 Pressures

Step 3 Analysis

STEPS REQUIRING DATA

COLLECTION

◼Data is needed to draw a link between the company’s activities and the pressures they exert to calculate the impacts of these pressures on biodiversity

◼The approach and the level of detail of the analysis will depend on the accessibility and quality of data collected

1. Introduction

PAGE 5

◼A perimeter must be chosen for the biodiversity footprint assessment.

◼This perimeter is:

❑Organisational: which business unit, subsidiary, etc. (either financial, operational or share of the assets owned approach)

❑Geographical: which countries, sites, etc.

❑Temporal: the period to be assessed (the financial year (FY), several years, etc.) & the baseline year (if any)

1.a. Introduction – Perimeters definition

PAGE 6

1.b. Introduction – Quality of data & impact factors

PAGE 7

Accurate and precise impact factors, and by extension data, have to be used to limit uncertainties in results. Accuracy refers to how close an

assessed value is to the actual (true) value. Precision refers to how close

the assessed values are to each other.

PAGE 8

1.b. Introduction – Quality of data & impact factors

◼ In order to quickly estimate impact factor, and associated data, accuracy, we use a tier system similar to the IPCC’s tier system, tier 1 being generally the least accurate:

❑ Data quality tier 1: Simple, impact factor-based approach (e.g. average agricultural yield of wheat across the world). Tier 1 impact factors are international defaults;

❑ Data quality tier 2: More region (country)-specific impact factors or more refined empirical estimation methodologies (e.g. average agriculture yield of wheat in France);

❑ Data quality tier 3: Dynamic bio-geophysical simulation models using multi-year time series and context-specific parameterization, with coarse data. For instance, direct use of GLOBIO

pressure/impact links with secondary data approximated from coarse datasets;

❑ Data quality tier 4: Dynamic bio-geophysical simulation models using multi-year time series and context-specific parameterization, with precise data. For instance, direct use of GLOBIO

pressure/impact links with primary data (e.g. on habitats broken down into the 13 habitat types used in GLOBIO);

❑ Data quality tier 5: Direct measurements

PAGE 9

1.c. Introduction – Uncertainty

◼In order to deal with the uncertainty of the data, for each of the input except for the financial data, a range can be provided:

▪ Central value: “best estimate” of the actual value

▪ Optimistic value: value which leads to the lower impacts on biodiversity

▪ Conservative value: value which leads to the higher impacts on biodiversity

◼The uncertainty associated can be reflected in the

results.

PAGE 10

1.c. Introduction – Two options for data collection

◼For each data need, the guidelines distinguish between:

❑ “Idealistic” option: the data format the GBS really needs

❑“Realistic” option: data we believe should be more readily

accessible to the company, but require additional work and

hypotheses to be used in the GBS

PAGE 11

1.d. Introduction – Localised data

◼Data can be associated to the GPS coordinates of the location of the activities

◼What do GPS coordinates stand for and how are they determined?

- For us, geo-referenced data are data associated to a GPS (latitude, longitude) location

- GIS polygons are not necessary (nor useful); instead, latitude and longitude should be

provided. Any point of the geographical entity considered can be used, the best being to

use the centroid of the entity

PAGE 12

1.d. Introduction – Localised data

◼Data can be associated to the GPS coordinates of the location of the activities

◼What do GPS coordinates stand for and how are they determined?

- For us, geo-referenced data are data associated to a GPS (latitude, longitude) location

- GIS polygons are not necessary (nor useful); instead, latitude and longitude should be

provided. Any point of the geographical entity considered can be used, the best being to

use the centroid of the entity

PAGE 13

1.d. Introduction – Scopes

◼ Scope 1: impacts generated on the area controlled by the entity and other impacts directly caused by the entity during the period assessed.

◼ Scope 2: impacts resulting from non-fuel energy (electricity,

steam, heat and cold) generation, including impacts resulting from land use changes, fragmentation, etc.

◼ Scope 3: impacts which are a consequence of the activities of the company but occur from sources not owned or controlled by the company, both upstream and downstream of its activities

2. Data for the framework of the

assessment

PAGE 15

2. Framework of the assessment

◼For the whole assessment, data must be entered within a precise hierarchy, starting from the site level to the company boundaries, or to the equity owners of the company.

◼The hierarchy is the company’s entire choice: ideally, it should match the granularity of available data.

◼It must be described in the following excel file:

GBS_organizational_information_data-collection.xlsx

◼ Dimensioning groups: hierarchy within the boundaries of the

company, from group_1_dimension to group_n_dimension (as many as you need, group_1_dimension being the first level (similar to “site-level”)

◼ Attribution groups: structure of investment responsibility GBS_organizational_information_

data-collection.xlsx

2. Framework of the assessment

Company 1 Business

unit 1 Site 1

Site 2 Site 3

Business unit 2 Site 4

Site 5 Site 6

Company 2 Business

unit 1 Site 1b

Business unit 2

Group Attribution Group Dimensioning

Group Attribution: % of the entity controlled by its "parent"

Group Dimensioning: organizational link GBS_organizational_information_

data-collection.xlsx

16%

2%

10% Company

1 Portfolio 1

Fund 1

Portfolio 2 Fond 2

Portfolio 3

Company

2 20%

Site 1 Site 2 Site 3 Site 4 Site 5 Site 6 Site 1b

2.a. Framework of the assessment – Hierarchy:

group dimensioning

PAGE 17

◼Group 1:

◼ Must correspond to the smallest level of hierarchy

◼ Ideally, all data needed are provided in this level

Then hierarchy is built up (group 2) per region, country or continent ; per sector ; per type of site (production, support offices, …).

Name

Business Group 1 Group 2 Group 3 … Group N Company 1 Site 1 Business

unit 1 Company 1 Site 2 Business

unit 1

…

GBS_organizational_information_

data-collection.xlsx

Group_

dimensioning

2.b. Framework of the assessment – Hierarchy:

group attribution

PAGE 18

◼ Group attribution:

◼ Describes the links between parent and child entities in terms of equity control to determine which share of the child's impact should be attributed to the parent

◼ The share to input is the proportion of the child’s owned by the parent (the rest being owned by other capital owners). Caution: this is different from the share the child represents in a given portfolio.

◼ All parent-child pairs that should be distinguished in the assessment have to be reported here. Without information, default attribution is 100%

Date of Input Name Child Name Parent Equity Control (Parent' share of child total)

02/08/2018 Site 1b Company 1 80%

02/08/2018 Company 1 Portfolio 1 1%

02/08/2018 Company 1 Portfolio 2 2%

GBS_organizational_information_

data-collection.xlsx

Group_

attribution

3. Data for the screening phase

PAGE 20

3.a. Screening – “Ecological integrity” – Idealistic option

◼ The attribution data needs to be informed. It describes the content of the portfolios and funds of the financial institution assessed (financial company data and share owned by the financial institution)

◼ In the case of a single company assessment, fill in a single line with the company's financial data and indicate that the share owned is 100%

Name Business

Local currency

Exchange rate (EUR/local

currency)

Total market capitalisation

(local currency)

Total debt (local currency)

Total cash (local currency)

Total enterprise

value (local currency)

Total turnover

(local currency)

Enterprise value owned

by your FI (local currency)

Share of enterprise value owned by

your FI (%)

Company 1 EUR 1 50 000 504 000 000 0.28%

Company 2 USD 0.91 100 000 50 000 10 000 1 000 000 1 600

GBS_Financial_Information_data-

collection.xlsx Attribution

PAGE 21

3.a. Screening – “Ecological integrity” – Idealistic option

◼ The “Ecological Integrity” screening phase corresponds to a first GBS-based financial default assessment

◼ Data needed is in the following format and has to be filled in the dimensioning tab:

Name

Business Group n Scope Region

name Industry name

Turnover in this region and industry (local

currency)

Turnover in this region and industry (% of total turnover) Company 1 Business unit 1 Scope 1 Belgium Animal

products nec 20%

Company 1 Business unit 2 Scope 1 Brazil Cattle farming 500000

• Region: corresponding to EXIOBASE regions (listed in CDC Biodiversité (2019))

• Industry: corresponding to 163 EXIOBASE sectors (listed in CDC Biodiversité (2019))

GBS_Financial_Information_data-

collection.xlsx Dimensioning

Data quality tier 2 or Data quality tier 1

3.a. Screening – “Ecological integrity” – Realistic options

PAGE 22

◼Turnover per group_x_dimension may not be available, proxies can be used (number of employees per site for example) to approximate

turnover.

◼Region and sector may not correspond directly to EXIOBASE options

◼In this case, the company indicates manually industry group or region group (or macro-region).

• Region: region or country

• Sector: NACE code, or business unit description

GBS_Financial_Information_data-

collection.xlsx Dimensioning

Data quality tier 2 or Data quality tier 1

3.a. Screening – “Ecological integrity” – Realistic options

PAGE 23

◼ When the turnover split by region is not known, i.e. when you enter region groups or industry groups, you can still constrain the regions and industries in which the company operates for each line of the sheet Dimensioning by listing them in the regions constraint and industry constraint tabs, as follow:

GBS_Financial_Information_data- collection.xlsx

Regional/Industry constraint

Index Name Business Industry Region

3 Company 2 Crop and animal production, hunting and related service activities RoW America 3 Company 2 Crop and animal production, hunting and related service activities RoW Africa

Index Name Business Region name Industry

2 Company 1 Brazil Cultivation of crops nec

2 Company 1 Brazil Cultivation of plant-based fibers

RegionalconstraintIndustryconstraint

PAGE 24

3.b. Screening – “Risk of extinction” – Idealistic option

◼ If no proxy of turnover per group_x_dimensionis available, then no “ecological integrity” screening is possible, and the screening only focuses on the “risk of extinction” dimension. The “Risk of extinction”

screening phase corresponds to a screening per site to assess what is not taken into account by the MSA metric.

This screening is coherent with the Stage 1 detailed by UNEP-WCMC in their report

“Biodiversity Indicators for Extractives, How-To Guide for Phase 3 Piloting”

◼ This is a company-level assessment of biodiversity sensitivity of sites plus a 50 km area of influence around each site.

◼ Idealistic option: the company has access to IBAT for its Scope 1 but also its entire supply chain

◼ Data quality tier 5

Source: Biodiversity Indicators for

Extractives, How-To Guide for Phase 3 Piloting, UNEP- WCMC

3.b. Screening – “Risk of extinction” – Realistic option

PAGE 25

◼ Realistic option: the company is able to partially fill in the following table per group_x_dimension and / or only for its Scope 1 sites

◼ Data must be of a similar quality to what is obtained through IBAT

Company name

Group_n Number of endangered species in a 50 km buffer

Area

overlapping with protected areas (ha)

Area

overlapping with critical habitat (ha)

CR E V NT

4. Data for the refined data collection

phase

4.1. Refined data - Introduction

PAGE 27

◼ The goal of the refined approach is to use the most accurate data available at each step of calculation, in order to best assess the biodiversity footprint of the company

◼ This document presents the different types of data to collect, from the most valuable (comprehensive ecological surveys) to the least valuable (monetary flows)

◼ For each category of data, data should be provided with the most detailed hierarchy possible: from group_1_dimension to group_n_dimension,

according to the hierarchy decided in section 1.

4.1. Ecological data

PAGE 28

PAGE 29

4.1. Refined data – Ecological Data

◼In theory, if comprehensive site-level ecological surveys are available, MSA per site could be directly calculated

• Da ta required per taxon:

- Number of observed individuals

- Density of individuals in an undisturbed ecosystems

• For each taxon, representing the 6 taxa needed for MSA: mammals, birds, reptiles, amphibians, invertebrates, vascular plants.

Data quality tier 5

◼Yet this kind of information is rarely available

4.2. Pressures data

PAGE 30

PAGE 31

4.2. Refined data – Pressures – Introduction

◼If comprehensive ecological data are not available, then pressure- impact relationships are used to assess biodiversity footprint

◼Pressures data are divided into 2 types (terrestrial pressures and

aquatic pressures), used resp. in GLOBIO and GLOBIO Aquatic within the GBS.

◼Some data on pressures are relatively easily available, others are not.

We present all data type below.

4.2.1. Refined data – Terrestrial

pressures

PAGE 33

4.2.1.1. Refined data – Terrestrial pressures – Land- use

◼

Unit: area (hectares)

◼

Format: Excel sheet with the area of land-use categories per site-level, as follow

GBS_Pressure_Land-Use_data- collection.xlsx

Most-recent data available at the

beginning of assessment (or before) - stage 1

Most-recent data available at the end of the assessment (or

after) - stage 2 Name

business Group 1 Scope Geographical data

Land use nomenclat

ure

Land use Data date

(year) Area (ha) Data date

(year) Area (ha) Company 1 Site 1 Scope 1 Catchment

Basin

YUKON

RIVER GLOBIO Forest -

Natural 2016 30 2017 20

Company 1 Site 1 Scope 1 Country Argentina GLOBIO Extensive

cropland 2016 20 2017 30

Company 1 Site 1 Scope 1 GPS

Location 46.159415 5.563461 GLOBIO Intensive

cropland 2016 20 2017 40

If data is not available regarding beginning of the assessment (or end), then indicate the

most recent land-use data that you have (even if it is before assessment).

PAGE 34

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Idealistic Option

❑

Land-use areas are directly provided using the 16 land-use categories of GLOBIO (see the two slides below for land-use categories and description)

❑

Bear in mind that land-use areas should be referenced for both

and n to allow for an assessment of the land-use evolution within a year (and thus the dynamic impacts)

❑ Data quality tier 4

GBS_Pressure_Land-Use_data-

collection.xlsx

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Idealistic Option

PAGE 35

Land-use Description (Alkemade et al. 2009) Examples MSA

Natural Forest

Also called Primary vegetation (forest). Minimal disturbance,

where flora and fauna species abundance are near pristine 100 % Forest -

Plantation Planted forest often with exotic species

Very degraded semi-

natural forest 30 %

Forest - Clear-cut harvesting

Also called Secondary forests. Areas originally covered with forest or woodlands, where vegetation has been removed, forest is re-growing or has a different cover and is no longer in use

Degraded semi-

natural forest 50 %

Forest - Selective logging

Also called Lightly used natural forest. Forests with

extractive use and associated disturbance like hunting and selective logging, where timber extraction is followed by a

long period of re-growth with naturally occurring tree species 70 % Forest -

Reduced impact logging

Light used forest (limited selective logging of semi-natural forest with Reduced Impact Logging management)

Undisturbed forest in Europe

Restored forests 85 %

Agroforestry

Agricultural production intercropped with (native) trees. Trees are kept for shade or as wind shelter

Planted forest often

with exotic species 50 %

Source: GLOBIO (The Netherlands Environmental Assessment Agency - PBL)

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Idealistic Option

PAGE 36

Source: GLOBIO (The Netherlands Environmental Assesment Agency - PBL)

Land-use Description (Alkemade et al. 2009) Examples MSA

Natural grassland

Also called Primary vegetation (grass- or scrublands). Grassland or scrubland-

dominated vegetation (for example, steppe,

tundra, or savannah) 100 %

Pasture -

moderately to intensively used

Also called Livestock grazing. Grasslands where wildlife is replaced by grazing

livestock

Grassland managed with a late-mowing

practice 60 %

Pasture - man-made

Also called Man-made pastures. Forests and woodlands that have been converted to

grasslands for livestock grazing. 30 %

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Idealistic Option

PAGE 37

Land-use Description (Alkemade et al. 2009) Examples MSA

Extensive cropland

Also called Low input agriculture.

Subsistence and traditional farming, extensive farming, and low external input

agriculture 30 %

Intensive cropland

Also called Intensive agriculture. High external input agriculture, conventional agriculture, mostly with a degree of regional specialization, irrigation-based agriculture,

drainage-based agriculture. 10 %

Irrigated cropland

High external input irrigation-based

agriculture, conventional agriculture, mostly with a degree of regional specialization, ,

drainage-based agriculture 5 %

Woody

biofuels Perennial crops & woody biofuels 30 %

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Idealistic Option

PAGE 38

Land-use Description (Alkemade et al. 2009) Example MSA

Bare area

Areas permanently without vegetation (for

example, deserts, high alpine areas) 100 %

Snow and ice

Areas permanently covered with snow or

ice considered as undisturbed areas 100 %

Urban area

Also called Built-up areas. Areas more than

80% built up 5 %

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Idealistic Option – Additional information on agricultural lands

PAGE 39

The following criteria can be used to determine the GLOBIO land use category of grasslands, by summing up the “note” indicated in column.

Criteria / note 0 1 2 3

Reported intensity Un-grazed or abandoned

Natural grazing Moderate

grazing intensity

High grazing intensity Visual alteration of

the vegetation structure

Not or slightly altered

Significantly altered in height or species composition , including exotics

/ /

Rangeland management

No management Presence of management such as soil disturbance, clearance of vegetation and application of fertilizers, planting or sowing grass or forage crops

/ /

Seasonal variation Only seasonal grazing

corresponding to natural grazing pattern

Continuous grazing regardless of the season

/ /

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Idealistic Option – Additional information on agricultural lands

PAGE 40 Name (grazing intensity)

Description Rule of assignment MSA Threshold stocking rate in the studies of the meta-analysis Un-grazed,

abandoned range-land (0)

“Original grasslands no longer in use, lacking wildlife grazing and no forests developed”

“If the reported intensity of rangeland management equals 0, and the description is clear on the absence of wildlife grazing then grazing is assigned as un-grazed, abandoned rangeland”

70% “removing 20% of herbage annually”

(Hart 2001)

Natural (1) “Rangeland ecosystems determined by climatic and geographical circumstances and grazed by

wildlife or domestic animals at rates similar to those of free- roaming wildlife”

“If the sum of reported intensity, visual alteration of the vegetation structure and seasonal variation equals 1 than grazing is ‘natural’”

100% “0.07 animal units per ha (Unit = a 455 kg steer)” (O’Connor 2005)

Moderately used grazing lands (2)

“Rangelands with higher stocking rates: grazing has different

seasonal patterns or vegetation structure is different compared with natural rangelands”

“If this sum is 2 or 3 then it moderately used grazing lands”

60% “by 1 cow on 12-17 ha” (Bock),

“0.4 AU. Mown 2-4 times a year”

(O’Connor 2005)

Depending on the “note” obtained in the previous slide, one of the following 5 categories of

land use can be deduced. The ones associated to 100%, 60% and 30% MSA broadly match

GLOBIO land use categories.

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Idealistic Option – Additional information on agricultural lands

PAGE 41 Name (grazing intensity)

Description Description / rule of

assignment

MSA Threshold stocking rate in the studies of the meta- analysis

Intensively used range- land (3)

“Rangelands with very high stocking rates: grazing has different seasonal patterns and vegetation structure is different compared with natural rangelands”

“and if the sum is 4 or 5 then the intensity class is intensively used rangeland”

50% “stocking rate of 0.25-0.5 cows / ha” (Cagnolo 2012),

"> 0.8 AU” (O'Connor 2005),

"0.88 livestock units per ha"

(Smart 2005),

"0.1 adult equivalent per ha"

(Woinarski) Man-made

grasslands (4)

“Rangeland with high degree of human management, including converted forests”

“if the rangeland management equals 1, then the intensity class is man made grasslands”

30% NA

PAGE 42

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Realistic Option 1

❑ Realistic Option 1: Land-use areas are reported with non-GLOBIO categories, but with a similar or better level of detail

❑ For example, the company is able to provide data extracted from a (Geographic) Information System, however it is under a terminology different from the 16 listed categories

❑ A correspondance table should adapt it to the GLOBIO categories

❑ As for other options, such land-use data is to be provided for year n-1 and year n

❑ Data quality tier 3

GBS_Pressure_Land-Use_data-

collection.xlsx

PAGE 43

4.2.1.1. Refined data – Terrestrial pressures – Land- use – Realistic Option 2

❑ Realistic Option 2: Land-use areas are reported using broad categories, requiring significant approximations to link them to the GLOBIO terminology

▪ This should be done for year n-1 and year n

❑ Data quality tier 3

❑ In the example below, only 3 land-use types are distinguished, conservation areas can be approximated to be natural forests inside an agricultural

plantation for instance GBS_Pressure_Land-Use_data-

collection.xlsx

Land-use information Year n

Site 1 (country A)

Site 2 (country A)

Crop 1 (ha) 12 664 1 418

Crop 2 (ha) NA 672

Conservation area (ha) 2214 265

PAGE 44

4.2.1.2. Refined data – Terrestrial pressures – Climate change – Idealistic option

◼

Unit: tonnes

◼

Amount of GHG Emissions per GHG (CO

, CH

, N

O, SF

, HFCs, PFCs) in accordance with the Kyoto Protocol, per Scope and per Group 1

◼

Emissions must be provided for the period considered

Data quality tier 4

Name

Business Group 1 Scope GHG type Used GWP Used GWP time horizon (years)

Emission date (year)

Annual emissions (tons)

Company 1 Site 1 Scope 1 CO2-eq IPCC 2014 (AR5) 100 2018 1000

Company 1 Site 1 Scope 1 CH4 Not concerned Not concerned 2018 20

Company 1 Site 1 Scope 1 N2O Not concerned Not concerned 2018 10

GBS_Pressure_Climate-

change_data-collection.xlsx

PAGE 45

4.2.1.2. Refined data – Terrestrial pressures – Climate change – Realistic option

◼Realistic option:

◼Global

(not detailed by group 1) amount of yearly GHG Emissions (no distinction between gases) in kg CO2-eq

◼

For Scopes 1,2 and partially for upstream Scope 3

❑ Data quality tier 3

GBS_Pressure_Climate-

change_data-collection.xlsx

4.2.1.3. Refined data – Terrestrial pressures – Terrestrial – Others

PAGE 46

◼The data on the remaining terrestrial pressures (Atmospheric Nitrogen Deposition, Encroachment, Fragmentation) are quite complex to collect.

◼Due to the complexity of this pressure, the realistic option is to use the "financial default" approach

Data quality tier 2 or Data quality tier 1

Yet below are presented the entry data needed if these pressures had to be

assessed directly

PAGE 47

4.2.1.3. Refined data – Pressures – Terrestrial – Nitrogen emissions – Idealistic option

◼Unit: exceedance of nitrogen (g/m²)

◼Format: Excel sheet

◼Data must be provided for the period considered, and the discharge environment must be precised (air, water, soil)

Data quality tier 4

Company name

Group_x _dimensi on

… Group_1_

dimension

Exceedanc e of

nitrogen (g/m²)

Exceedance of nitrogen in air

Exceedance of nitrogen in the soil

Very idealistic

option

PAGE 49

4.2.1.4. Refined data – Terrestrial pressures – Others

◼The fourth pressure on terrestrial biodiversity is Encroachment.

◼Unit: ha or km²

◼Land-use type on a 10km radius around the site (with the GLOBIO land-use categories quoted slides 30 to 33)

Data quality tier 4

Very idealistic

option

Company name

Group_x_

dimension

… Group_1_

dimension

Encroachement_

Forest-natural (ha)

Encroachement_

Forest-Plantation (ha)

…

PAGE 50

4.2.1.4. Refined data – Terrestrial pressures – Others

◼The fifth pressure on terrestrial biodiversity is Fragmentation.

◼Unit: ha or km²

◼Surface of natural areas (with 100% MSA) by patch size categories in km² or ha

Data quality tier 4

Company name

Group_x_

dimension …

Group_1_

dimension

Surface of

Natural areas by patchs of less than 1 km²

Surface of

Natural areas by patchs of 1 to 10 km²

…

Surface of

Natural areas by patchs of more than 10 000 km²

Very idealistic

option

4.2.2. Refined data – Aquatic pressures

PAGE 51

4.2.2. Refined data – Aquatic pressures –

Hydrological Disturbances – Idealistic option (1/2)

PAGE 53

◼ The Hydrological Disturbances pressure is assessed through water withdrawal or water consumption.

◼ Unit of the pressure: m

◼ Reported per group n at the catchment basin level Data quality tier 2

Name

Business Group 1 Scope Geographical data

type Geographical data Date (year)

Annual water consumption (m³)

Annual water withdrawal (m³)

Company 1 Site 1 Scope 1 Catchment Basin ALSEK RIVER 2018 1000 1000 Company 1 Site 2 Scope 1 GPS Location 49,02953 3,3821 2018 1000 1000

GBS_Pressure_Hydrological-

Disturbance_data-collection.xlsx

4.2.2. Refined data – Aquatic pressures –

Hydrological Disturbances – Idealistic option (2/2)

PAGE 54

◼Water withdrawal:

Definition: “[water pumped out] of e.g. a groundwater body or diverted from a river.” Also called “water abstraction” or “water use”.” (Source:

CREEA_D8.1_Water Case Study Report, p. 10)

◼Water consumption:

Definition: “share of the water originally abstracted [incorporated] into the product or lost to the ecosystem it was taken from (e.g. water evapotranspirated throughout a production process)”. In other words, the “water consumption” is the abstraction minus the return flows. It is also called “consumptive use”.

(Source: CREEA_D8.1_Water Case Study Report, p. 10) GBS_Pressure_Hydrological-

Disturbance_data-collection.xlsx

❑ The realistic option is to report the water consumed and withdrawn at the country level, EXIOBASE region or

region group

❑ In the GBS 1.0, the catchment-level impact factors are actually not more accurate than country-level impact factors and the Realistic option is thus similar to the

Idealistic option. It is however useful to collect data at a more granular spatial level, to use them in future

versions of the GBS.

4.2.2. Refined data – Aquatic pressures – Hydrological Disturbances – Realistic option

PAGE 55

GBS_Pressure_Hydrological-

Disturbance_data-collection.xlsx

PAGE 56

4.2.2. Refined data – Aquatic pressures – Nutrient concentration – Idealistic option

◼Ideally, if an aquatic ecosystem can be identified (e.g. polygon

corresponding to a body of water) and the N and P concentrations in this body of water can be assessed, they can be used directly

Data quality tier 4

GBS_Pressure_Nutrient_concentration_Freshwater _eutrophication_data-collection.xlsx

Name

business Group Scope Geographical data

Discharge comparment

Discharge compartment

area (km²)

Data date (year)

Total nitrogen concentration

(g N/m3)

Total phosphorous concentration

(g P/m3)

Data date (year)

Total nitrogen concentration

(g N/m3)

Total phosphorous concentration

(g P/m3)

PAGE 57

4.2.2. Refined data – Aquatic pressures – Nutrient emissions – Realistic option

◼Realistic option: nutrient emission is assessed through total Nitrogen and Phosphorous emissions.

◼Unit of the pressure: kg N-content or kg P-content

Data quality tier 4

GBS_Pressure_Nutrient_Emission_Freshwater _eutrophication_data-collection.xlsx

Name

Business Group Scope Geographical data

Discharge comparment

Date (year)

Total Nitrogen Emission (kg N-

content)

Total Phosphorous Emission (kg P-

content)

4.3.1. Refined – Physical Inventory Flow

PAGE 59

4.3.1. Refined – Physical Inventory Flow – Foreword

◼Collecting data on activity and in particular intermediary consumptions follows a similar process to the one presented for pressures

◼The level of detail of the analysis will depend on the depth of

knowledge you have on the upstream raw materials your activities require and/or upstream purchases you make, or your ability to track data from your suppliers

◼The following slides also apply to raw material production (and not just

to intermediary consumptions)

PAGE 60

4.3.1. Refined – Physical Inventory Flow – Idealistic option 1

◼In a very idealistic world, the land-use and climate change pressures caused by suppliers are known and directly reported, following the guidelines of section 4.2. Data on pressures

◼Data quality tier 3 or Data quality tier 4

PAGE 61

4.3.1. Refined – Physical Inventory Flow – Idealistic option 2

◼ In a slightly less idealistic world, the volumes or quantity of (unprocessed) raw materials or services (purchased or produced) are reported with the associated "Commodity Tool" or "Service Tool"

nomenclature in an appropriate unit (t, m³, etc.)

◼ Please refer to the input files for a full list of nomenclatures from the Commodity Tools and Service Tools – for now:

◼ Crop: indicate the amount of all the crops consumed & the associated yield, per crop and per geographical location. The use of certifications (e.g. organic, RSPO …) can be documented as it might be used in future versions of the GBS (but has no quantitative effect in the GBS 1.0).

◼ Extractive: indicate the amount and ore grade of each of the 15 metals products, 5 coal types and 4 mineral types, per item and geographical location

◼ Livestock husbandry: indicate the amount of each of the 12 livestock items consumed per geographical location

◼ Grass: indicate the amount of grass consumed per geographical location

◼ Oil & Gas: indicate the amount of oil or gas consumed per geographical location

◼ Woodlogs: indicate the amount of hardwood or softwood consumed per geographical location, reported with a 50% water content (and with a wet density of respectively 1025 kg/m³ and 850 kg/m³)

◼ The provision of refinement variable (e.g.agricultural yields) can help significantly refine the analysis Data quality tier 2 or Data quality tier 1

PAGE 62

4.3.1. Refined – Physical Inventory Flow – Realistic option 1 & 2

◼Option 1:

◼Option 2:

Data quality tier 2 or Data quality tier 1

• The volumes or quantity of (unprocessed) raw materials or services (purchased or produced) are reported with a custom nomenclature in an appropriate unit (t, m

, etc. )

• The volumes or quantity of processed materials (purchased or produced) are reported with a custom nomenclature in an

appropriate unit (t, m

, barrels of crude oil, etc. )

• It is then necessary to use tables linking processed materials to raw

material involved (including through product life cycle inventories)

PAGE 63

❑

If no physical flow data is available, input-output models will be used to assess emissions and raw material consumptions. This is the "financial default"

approach.

❑ Sales

or purchases by country and by industry (EUR) need to be provided

❑

Purchases must be flagged as Tier 1 of upstream Scope 3 in the input file

❑

The industry can be classified according to one of the following nomenclatures, from the most to the least preferred:

▪ Exiobase v.3 (163 sectors)

▪ NACE rev2

▪ Custom nomenclature

Data quality tier 2 or Data quality tier 1

4.3.2. Refined – Monetary Inventory Flow – Idealistic option 1

GBS_Financial_Information_data-

collection.xlsx

◼CDC Biodiversité. 2019. ‘Global Biodiversity Score: A Tool to

Establish and Measure Corporate and Financial Commitments for Biodiversity’. 14. Biodiv’2050 Outlook. CDC Biodiversité.

http://www.mission-economie-biodiversite.com/wp-

content/uploads/2019/05/N14-TRAVAUX-DU-CLUB-B4B-GBS- UK-WEB.pdf.

◼Alkemade, Rob, Mark van Oorschot, Lera Miles, Christian Nellemann, Michel Bakkenes, and Ben ten Brink. 2009.

‘GLOBIO3: A Framework to Investigate Options for Reducing

Global Terrestrial Biodiversity Loss’. Ecosystems 12 (3): 374–90.

https://doi.org/10.1007/s10021-009-9229-5.

5. References

PAGE 64

Antoine Cadi

Directeur Recherche et Innovation Mail:

antoine.cadi@cdc-biodiversite.fr Tél. : +33 (0)1 80 40 15 16 Mobile : +33 (0) 6 21 63 18 00

Joshua Berger

Chef de projet B4B+

Mail:

joshua.berger@cdc-biodiversite.fr Tél. : +33 (0)1 80 40 15 41 Mobile : +33 (0) 6 21 86 16 81