Data and Methodology#

 

The project uses primarily input–output (IO) data and theory to calculate life cycle module results, complying with consequential life cycle assessment (LCA) concepts. Here we describe the methodology underlying BONSAI-IO and detailed information on the data included.

1. The Make-use Framework#

The following picture shows the structure of BONSAI IO following the the make-use framework (see the terminology in Glossary section):

 

 

An alternative illustration:

Core Concepts#

Here we define some concepts that are essential in the BONSAI IO framework

The Markets#

A market is an intermediate activity between producers and users. Producers from several countries (exporting activities) feed products to a national market (importing country). Other inputs to the markets are:

  • the transport services to move the products from the origin country to the destination one;

  • trade services which includes all the other margins of the trade intermediaries;

  • net taxes on products.

The market is the entity where basic prices are converted into purchaser prices.

 

The National Mix (in future export market)#

A national mix is inserted anytime a traded product is more disaggregated than its producing activities. One of the example is the fish. Fish can be provided by wild caputure or by aquaculture. However, trade statistics do not distinguish between sources.

A national mix collects homogeneous products from several sources and produces one unique (mixed) product. The output of the national mix is always associated to the lowest product resolution which can be obtained combining trade accounts and use tables.

 

 

If homogenous products from different producers are not exported from one region to another, there is no need of creating a national mix. Those products will feed to the national markets.

Notice that a national mix differs from conventional market because it does not include trade and sale margins, plus net taxes on products.

Principal Production#

From an economic perspective, the principal production of an activity is the output from which the highest revenues are gained. The princinpal production is strictly linked to the sector classification of the activity.

However, in BONSAI IO the choice of the principal production is mostly driven by the function of the activty rather than the generated economic values. However, for the majority of cases, both createrias converge to the same principal production. In other cases, as for some waste treatment services, they could differ. An example is the incineration of waste. Revenues from the sale of electricity might exceeds those from the management of waste. In BONSAI, an incineration plant is always associated to the waste treatement sector. Contrarily, following the economic definition, an incineration plant might be associated to the electricity sector. We use in BONSAI IO also the term determing production.

Combined and Joint By-production#

Parameterized Production Function (PPF)#

Parameterized production functions are the least elements to build make-use tables. It defines the relationship between input factors and output factors for a production process. PPFs are embedded into the general make-use framework following the procedures described here

More about PPFs can be found here and here.

Sectoral Modelling#

Agriculture#

Land Use#

  • Grass land

  • Arable land

  • Forest land
    The currently using data source for land use (FAOSTAT) includes the following types of forestry land: primary forest, secondary forest, planted forest, and naturally regenerated forest. In the land use module, we re-classify those forest lands into three categories:

    • Unmanaged forest

    • Extensively managed forest

    • Intensively managed forest

    First, the theoretical maximum area of managed forest is calculated as:

    \[ Area_{\text{manage, max}}=\frac{WR}{Y_{\text{min}}} \]

    where:

    • \(WR\): is the annual wood removal (\(m^3\)) in a country.

    • \(Y_{\text{min}}\): is the minimum yield of managed forests in a country (\(m^3/ha*year\)). This is defined as 1 \(m^3/ha*year\) weighted with potential productivity (based on \(NPP0\)).

    1. If \(Area_{\text{manage, max}}\le(Area_{\text{plant}})\)

      • the area of intensively managed forest \(Area_{\text{int}}=0\),

      • the area of extensively managed forest \(Area_{\text{ext}}=Area_{\text{manage, max}}\), and

      • the area of unmanaged forest \(Area_{\text{unmanaged}}=Area_{\text{prim}}+Area_{\text{sec}}+Area_{\text{nat}}\)

    2. If \(Area_{\text{plant}}<Area_{\text{manage, max}}\le(Area_{\text{plant}}+Area_{\text{nat}})\)

      • the area of intensively managed forest \(Area_{\text{int}}=0\),

      • the area of extensively managed forest \(Area_{\text{ext}}=Area_{\text{manage, max}}\), and

      • the area of unmanaged forest \(Area_{\text{unmanaged}}=Area_{\text{prim}}+Area_{\text{sec}}+(Area_{\text{plant}}+Area_{\text{nat}}-Area_{\text{manage,max}})\)

    3. If \(Area_{\text{manage, max}}>(Area_{\text{plant}}+Area_{\text{nat}})\)

      • Then, the area of intensively managed forest \(Area_{\text{int}}\) is calculated as follows:

        \[ Area_{\text{int, max}} = \frac{WR - (Area_{\text{nat}} + Area_{\text{plant}}) \cdot Y_{\text{min}}}{Y_{\text{int}}} \]

        where:

        • \(Area_{\text{int,max}}\): is the theoretical max area intensive managed forest (ha*year) in a country.

        • \(Y_{\text{int}}\): estimated standard yield of intensive managed forests in a country (\(m^3/ha*year\)). This is defined as 4 \(m^3/ha*year\) weighted with potential productivity (based on NPP0).

        \(Area_{\text{int}}=min[Area_{\text{int,max}}, (Area_{\text{nat}} + Area_{\text{plant}})]\)

      • The area of extensively managed forest \(Area_{\text{ext}}=(Area_{\text{nat}} + Area_{\text{plant}})-Area_{\text{int}}\)

      • The area of unmanaged forest \(Area_{\text{unmanaged}}=Area_{\text{prim}}+Area_{\text{sec}}\)

Energy#

Packaging#

Packaging “means all products made of any materials of any nature to be used for the containment, protection, handling, delivery and presentation of goods, from raw materials to processed goods, from the producer to the user or the consumer” [EEA].

In BONSAI we assume that each packaging has its own capacity, which can be considered as a service. For example a 50cl bottle provides the service of protecting 50cl of a liquid material.

Activities determine the required packaging based on their capacity needs. The volume of packaging is then converted into mass units. Consequently, activities receive a mass flow from packaging producers that equals the mass of the packaging required. In return, activities pay a corresponding monetary flow to the producers.

 

In BONSAI IO packaging supplied by activities to contain their output is reported in the extensions under specific packaging accounts. These packaging accounts describe the use and supply of packaging between suppliers and users. When packaging no longer provides its service, it becomes waste and is subsequently reported in the waste accounts as a regular waste flow.

Trade#

Average Market#

Related tasks:

create_stone_market

The average market account is calculated using production volume and trade data to estimate domestic market supply for each product. The formula is:

\[ V_{ij, \space \text{market supply}} = V_{ij, \space \text{domestic production}} + V_{ij, \space \text{import}} - V_{ij, \space \text{export}} \quad \text{for location } i \text{ and product } j \]

where,

  • \(V_{\text{market supply}}\): is the total volume of domestic market supply.

  • \(V_{\text{domestic production}}\): is the total domestic production.

  • \(V_{\text{import}}\): is the total import.

  • \(V_{\text{export}}\): is the total export.

It indicates that each product has its own domestic market, where domestic production and import are not differentiated. Additionally, re-exports needs to be identified and adjusted as those goods do not contribute to the domestic market. Re-exports are identified using the following logic:

\[\begin{split} \text{HasReexport} = \begin{cases} 1, \quad \text{if} \quad V_{ij,\space \text{domestic}}+V_{ij, \space \text{import}} <= V_{ij,\space \text{export}} \\ 0, \quad \text{if} \quad V_{ij,\space \text{domestic}}+V_{ij, \space\text{import}} > V_{ij, \space\text{export}} \\ \end{cases} \end{split}\]

For locations that import a product from a re-exporting location, its import will be sourcing from the market supply of the re-exporting location instead of the industrial supply.

Special treatment is given to the delineation of electricity markets. Electricity market is composed of two market: domestic production (i.e. the national mix) and import markets. The domestic production mix is composed of different domestic electricity generation technologies, e.g., solar PV, wind, and nuclear power. No individual markets are defined for each technology; all are grouped under the domestic production mix. The import market consists of electricity imported from foreign sources.

 

Transport#

The Transportation module is subdivided into two kinds of transport services: freight transport and passenger transport.

More about the methodology on the construction of the transport account here

Material for Treatment#

A material for treatment is a by-product of activities that needs a further treatment before being able to replace other matherials.

Materials for treatment include waste flows but also scraps that are sold by activities who gain some revenues. Often the terms waste is used in BONSAI to indicate material for treatment.

  • Waste supply

  • Waste use

Emissions#

Related tasks

merge_emission_account

The emission account compiles data on the direct emissions produced by various activities. This account is constructed by combining information from the product supply account and the emission coefficient account. Specifically, it quantifies emissions based on the total supply of principal products and the corresponding emission coefficients for each activity.

The emissions are calculated using the following formula:

\[ B = E \cdot \text(V_{d}) \]

  • \(B\): is the emission matrix that represents direct emissions of activities.

  • \(E\): is the emission coefficient matrix that represent direct emission coeffient of activities.

  • \(V_{d}\): is the diagonal entries of the supply matrix.

The emission coefficient account is compiled based on different data sources including bonsai-ipcc,

Properties#

Related tasks

merge_property_of_products

The property account includes the conversion factors to convert a product flow across different property layers. It includes the following conversion factors:

  • Price

  • Heat value

  • Weight

  • Dry matter content

Balance#

A graph-based multi-layer SUT balance framework is developed to balance the hybrid supply and use tables, as shown in the figure below:

 

Graph-based multi-layer SUT balance framework

 

The balance problem is formulated as follows:

\[\begin{equation*} \begin{aligned} \min_{\alpha} \quad & \sum_{i} \sum_{j} \sum_{k} |v_{ijk}| (\alpha_{ijk} - 1)^2 + \sum_{i} \sum_{j} \sum_{k} |u_{ijk}| (\beta_{ijk} - 1)^2 \\ \text{subject to:} \\ & \sum_{j} v_{ijk} \alpha_{ijk} = \sum_{j} u_{ijk} \beta_{ijk}, && \forall i \in \{1,2,3,\dots,I\}, \quad k \in \{1,2,3,\dots, K\} \\ & \sum_{i} v_{ijk} \alpha_{ijk} \leq \sum_{i} u_{ijk} \beta_{ijk}, && \forall j \in \{1,2,3, \dots, J\}, \quad k \in \{1,2,3,\dots, K\} \\ & v_{pjk} \alpha_{pjk} = r_{p, j} v_{bjk} \alpha_{bjk}, && \forall j \in \{1,2,3, \dots, J\}, \quad k \in \{1,2,3,\dots, K\}, \quad p,b \in P_j, \quad p \neq b \end{aligned} \end{equation*}\]

where:

  • \(\alpha_{ijk}\): Adjustment factor for supply of product \(i\), activity \(j\), and unit \(k\).

  • \(\beta_{ijk}\): Adjustment factor for use of product \(i\), activity \(j\), and unit \(k\).

  • \(v_{ijk}\): Initial supply volume of product \(i\) by activity \(j\) in unit \(k\).

  • \(v_{ibk}\): Initial supply volume of the base/determining product \(b\) by activity \(j\) in unit \(k\).

  • \(u_{ijk}\): Initial use volume of product \(i\) by activity \(j\) in unit \(k\).

  • \(P_j\): Set of products co-produced by activity \(j\).

  • \(r_{p, j}\): The initial ratio between products \(p\) and \(b\) by activity \(j\) (\(v_{pjk}/v_{bjk}\)).

Constraints

  • Product Balance ensures total supply of a product equals its total use.

  • Activity Balance ensures total input to an activity does not exceed its total output.

  • Output Ratio Constraint ensures the ratio of co-produced products for an activity remains constant.

Flow balance

To be added

Activity balance

It is imposed that for each inputs to an activity the following condition holds:

 

Disaggregation#

Household

The household production and consumption are disaggregated via distribution keys generated by household expenditure and time-use survey following the formula below.

For the use matrix:

\[ U_{f} = D_{use}^{T}f \]

where:

  • \(U_{f}\): is disaggregated use matrix by household, with dimensions \(p \times a\).

  • \(D_{use}\): is the market use distribution key matrix of size \(p \times a\), containing non-negative elements no greater than 1. A market use distribution key \(d_{p,a}\) shows the percentage of each product used per household group-activity with each summing to 1

\[ \sum_{a}(D_{use})_{p,a}=1,\quad \forall p \]

  • \(f\): is the household final demand vector of dimensions \(p \times 1\).

For the supply matrix:

\[ V_{w} = D_{supply}w \]

where:

  • \(V_{w}\): is disaggregated household supply matrix, with dimensions \(a \times p\).

  • \(D_{supply}\): is the product supply distribution key matrix of size \(p \times a\), containing non-negative elements no greater than 1. A market use distribution key \(d_{p,a}\) shows the percentage of each product used per household group-activity with each summing to 1

\[ \sum_{a}(D_{use})_{p,a}=1,\quad \forall p \]

  • \(f\): is the labor supply vector of dimensions \(p \times 1\).

The full workflow to disaggregate the houshold production and consumption is as follows: