Hybrid LCA database generated using ecoinvent and EXIOBASE

Hybrid LCA database generated using ecoinvent and EXIOBASE, i.e., each process of the original ecoinvent database is added new direct inputs (coming from EXIOBASE) deemed missing (e.g., services). Each process of the resulting hybrid database is thus not (or at least less) truncated and the calculated lifecycle emissions/impacts should therefore be closer to reality.

For license reasons, only the added inputs for each process of ecoinvent are provided (and not all the inputs).

Why are there two versions for hybrid-ecoinvent3.5?

One of the version corresponds to ecoinvent hybridized with the normal version of EXIOBASE and the other is hybridized with a capital-endogenized version of EXIOBASE.

What does capital endogenization do?

It matches capital goods formation to the value chains of products where they are required. In a more LCA way of speaking, EXIOBASE in its normal version does not allocate capital use to value chains. It's like if ecoinvent processes had no inputs of buildings, etc. in their unit process inventory. For more detail on this, refer to (Södersten et al., 2019) or (Miller et al., 2019).

So which version do I use?

Using the version "with capitals" gives a more comprehensive coverage. Using the "without capitals" version means that if a process of ecoinvent misses inputs of capital goods (e.g., a process does not include the company laptops of the employees), it won't be added. It comes with its fair share of assumptions and uncertainties however.

Why is it only available for hybrid-ecoinvent3.5?

The work used for capital endogenization is not available for exiobase3.8.1.

How do I use the dataset?

First, to use it, you will need both the corresponding ecoinvent [cut-off] and EXIOBASE [product x product] versions. For the reference year of EXIOBASE to-be-used, take 2011 if using the hybrid-ecoinvent3.5 and 2019 for hybrid-ecoinvent3.6 and 3.7.1.

In the four datasets of this package, only added inputs are given (i.e. inputs from EXIOBASE added to ecoinvent processes). Ecoinvent and EXIOBASE processes/sectors are not included, for copyright issues. You thus need both ecoinvent and EXIOBASE to calculate life cycle emissions/impacts.

Module to get ecoinvent in a Python format: https://github.com/majeau-bettez/ecospold2matrix (make sure to take the most up-to-date branch)

Module to get EXIOBASE in a Python format: https://github.com/konstantinstadler/pymrio (can also be installed with pip)

If you want to use the "with capitals" version of the hybrid database, you also need to use the capital endogenized version of EXIOBASE, available here: https://zenodo.org/record/3874309. Choose the pxp version of the year you plan to study (which should match with the year of the EXIOBASE version). You then need to normalize the capital matrix (i.e., divide by the total output x of EXIOBASE). Then, you simply add the normalized capital matrix (K) to the technology matrix (A) of EXIOBASE (see equation below).

Once you have all the data needed, you just need to apply a slightly modified version of the Leontief equation:

\(\begin{equation} \textbf{q}^{hyb} = \begin{bmatrix} \textbf{C}^{lca}\cdot\textbf{S}^{lca} & \textbf{C}^{io}\cdot\textbf{S}^{io} \end{bmatrix} \cdot \left( \textbf{I} - \begin{bmatrix} \textbf{A}^{lca} & \textbf{C}^{d} \\ \textbf{C}^{u} & \textbf{A}^{io}+\textbf{K}^{io} \end{bmatrix} \right) ^{-1} \cdot \left( \begin{bmatrix} \textbf{y}^{lca} \\ 0 \end{bmatrix} \right) \end{equation}\)

qhyb gives the hybridized impact, i.e., the impacts of each process including the impacts generated by their new inputs.

Clca and Cio are the respective characterization matrices for ecoinvent and EXIOBASE.

Slca and Sio are the respective environmental extension matrices (or elementary flows in LCA terms) for ecoinvent and EXIOBASE.

I is the identity matrix.

Alca and Aio are the respective technology matrices for ecoinvent and EXIOBASE (the ones loaded with ecospold2matrix and pymrio).

Kio is the capital matrix. If you do not use the endogenized version, do not include this matrix in the calculation.

Cu (or upstream cut-offs) is the matrix that you get in this dataset.

Cd (or downstream cut-offs) is simply a matrix of zeros in the case of this application.

Finally you define your final demand (or functional unit/set of functional units for LCA) as ylca.

Can I use it with different versions/reference years of EXIOBASE?

Technically speaking, yes it will work, because the temporal aspect does not intervene in the determination of the hybrid database presented here. However, keep in mind that there might be some inconsistencies. For example, you would need to multiply each of the inputs of the datasets by a factor to account for inflation. Prices of ecoinvent (which were used to compile the hybrid databases, for all versions presented here) are defined in €2005.

What are the weird suite of numbers in the columns?

Ecoinvent processes are identified through unique identifiers (uuids) to which metadata (i.e., name, location, price, etc.) can be retraced with the appropriate metadata files in each dataset package.

Why is the equation (I-A)-1 and not A-1 like in LCA?

IO and LCA have the same computational background. In LCA however, the convention is to represents outputs and inputs in the technology matrix. That's why there is a diagonal of 1s (the outputs, i.e. functional units) and negative values elsewhere (inputs). In IO, the technology matrix does not include outputs and only registers inputs as positive values. In the end, it is just a convention difference. If we call T the technology matrix of LCA and A the technology matrix of IO we have T = I-A. When you load ecoinvent using ecospold2matrix, the resulting version of ecoinvent will already be in IO convention and you won't have to bother with it.

Pymrio does not provide a characterization matrix for EXIOBASE, what do I do?

You can find an up-to-date characterization matrix (with Impact World+) for environmental extensions of EXIOBASE here: https://zenodo.org/record/3890339

If you want to match characterization across both EXIOBASE and ecoinvent (which you should do), here you can find a characterization matrix with Impact World+ for ecoinvent: https://zenodo.org/record/3890367

It's too complicated...

The custom software that was used to develop these datasets already deals with some of the steps described. Go check it out: https://github.com/MaximeAgez/pylcaio. You can also generate your own hybrid version of ecoinvent using this software (you can play with some parameters like correction for double counting, inflation rate, change price data to be used, etc.). As of pylcaio v2.1, the resulting hybrid database (generated directly by pylcaio) can be exported to and manipulated in brightway2.

Where can I get more information?

The whole methodology is detailed in (Agez et al., 2021).

本混合生命周期评估（Life Cycle Assessment, LCA）数据库基于ecoinvent与EXIOBASE构建，即针对原始ecoinvent数据库中的每个单元过程，补充了被判定为缺失的（如服务类）直接投入（数据来源于EXIOBASE）。经此处理后，生成的混合数据库中的各过程不再（或至少更少）出现截断情况，计算得到的生命周期排放与影响结果也因此更贴近真实场景。

出于许可协议限制，本数据集仅提供针对ecoinvent各单元过程补充的投入项（而非全部原始投入）。

为何hybrid-ecoinvent3.5存在两个版本？
其中一个版本是采用常规版EXIOBASE与ecoinvent混合得到的产物，另一个则采用了资本内生化（capital endogenization）版本的EXIOBASE。

资本内生化（capital endogenization）有何作用？
其将资本品形成与所需产品的价值链相匹配。用更贴合LCA的表述来说，常规版EXIOBASE并未将资本使用分配至价值链中，这就好比ecoinvent的单元过程清单中未包含厂房等资本品投入。如需了解更多细节，可参考(Södersten et al., 2019)或(Miller et al., 2019)。

该如何选择合适的版本？
使用“含资本”版本可获得更全面的覆盖范围；使用“不含资本”版本时，若ecoinvent的某一过程缺失资本品投入（例如某过程未涵盖员工所用的公司笔记本电脑），则不会补充此类投入。不过两种版本均带有相应的假设与不确定性。

为何仅针对hybrid-ecoinvent3.5提供该双版本？
资本内生化所用到的研究成果并不适用于exiobase3.8.1版本。

该如何使用本数据集？
首先，使用本数据集需同时获取对应版本的ecoinvent[截断版（cut-off）]与EXIOBASE[产品×产品（product x product）]版本。对于所用EXIOBASE的基准年：若使用hybrid-ecoinvent3.5，则取2011年；若使用hybrid-ecoinvent3.6及3.7.1，则取2019年。

本数据包包含的四个数据集中，仅提供补充投入项（即从EXIOBASE添加至ecoinvent过程的投入）。由于版权问题，未包含ecoinvent与EXIOBASE的原始过程/行业数据，因此需同时获取ecoinvent与EXIOBASE数据才能计算生命周期排放与影响。

用于将ecoinvent转换为Python格式的模块：https://github.com/majeau-bettez/ecospold2matrix（请确保使用最新分支）
用于将EXIOBASE转换为Python格式的模块：https://github.com/konstantinstadler/pymrio（也可通过pip安装）

若需使用混合数据库的“含资本”版本，还需获取资本内生化版本的EXIOBASE，其下载地址为：https://zenodo.org/record/3874309。请选择与你研究年份匹配的产品×产品版本（需与所用EXIOBASE版本的年份一致），随后需对资本矩阵进行归一化处理（即除以EXIOBASE的总产出x）。最后，将归一化后的资本矩阵（K）添加至EXIOBASE的技术矩阵（A）中（详见下述公式）。

获取所有所需数据后，仅需应用经小幅修改的列昂惕夫方程（Leontief equation）：
egin{equation} extbf{q}^{hyb} = egin{bmatrix} extbf{C}^{lca}cdot extbf{S}^{lca} & extbf{C}^{io}cdot extbf{S}^{io} end{bmatrix} cdot left( extbf{I} - egin{bmatrix} extbf{A}^{lca} & extbf{C}^{d} \ extbf{C}^{u} & extbf{A}^{io}+ extbf{K}^{io} end{bmatrix}
ight) ^{-1} cdot left( egin{bmatrix} extbf{y}^{lca} \ 0 end{bmatrix}
ight) end{equation}
其中$ extbf{q}^{hyb}$为混合后的影响结果，即各过程的影响及其新增投入所产生的影响之和。

$ extbf{C}^{lca}$与$ extbf{C}^{io}$分别为ecoinvent与EXIOBASE的特征化矩阵（characterization matrix）。
$ extbf{S}^{lca}$与$ extbf{S}^{io}$分别为ecoinvent与EXIOBASE的环境扩展矩阵（environmental extension matrices）（或LCA术语中的基本流矩阵）。
$ extbf{I}$为单位矩阵（identity matrix）。
$ extbf{A}^{lca}$与$ extbf{A}^{io}$分别为ecoinvent与EXIOBASE的技术矩阵（technology matrix）（即通过ecospold2matrix与pymrio加载得到的矩阵）。
$ extbf{K}^{io}$为资本矩阵。若不使用内生化版本，则无需在计算中加入该矩阵。
$ extbf{C}^{u}$（或上游截断项（upstream cut-offs））为本数据集所提供的矩阵。
$ extbf{C}^{d}$（或下游截断项（downstream cut-offs））在本应用场景下仅为全零矩阵。
最后，将你的最终需求（或LCA中的功能单元（functional unit）/功能单元集）定义为$ extbf{y}^{lca}$。

能否将本数据集与其他版本/基准年的EXIOBASE搭配使用？
从技术层面而言，可行，因为本混合数据库的构建并未涉及时间维度。但需注意，此举可能会产生不一致性。例如，你需要通过乘以相应系数来调整各投入以适配通货膨胀。本数据集所有版本所用的ecoinvent价格均以2005年欧元为计价基准。

列中的一系列奇怪数字是什么？
ecoinvent过程通过唯一标识符（UUID）进行标识，可通过每个数据集包中的对应元数据文件追溯其元数据（如名称、地理位置、价格等）。

为何采用$(I-A)^{-1}$而非LCA中常用的$A^{-1}$？
投入产出分析（Input-Output, IO）与LCA具有相同的计算背景。但在LCA中，通常会在技术矩阵中表示产出与投入：矩阵主对角线为1（代表产出，即功能单元），其余位置为负值（代表投入）。而在IO分析中，技术矩阵仅记录正的投入值，不包含产出项。归根结底，这只是一种约定俗成的差异。若将LCA的技术矩阵记为$ extbf{T}$，IO的技术矩阵记为$ extbf{A}$，则有$ extbf{T} = extbf{I} - extbf{A}$。当通过ecospold2matrix加载ecoinvent数据时，所得版本已采用IO约定，无需额外处理。

pymrio未提供EXIOBASE的特征化矩阵，该如何处理？
你可在此处获取适配EXIOBASE环境扩展的最新特征化矩阵（采用Impact World+方法）：https://zenodo.org/record/3890339
若需实现EXIOBASE与ecoinvent的特征化方法匹配（建议完成此操作），可在此处获取适配ecoinvent的Impact World+特征化矩阵：https://zenodo.org/record/3890367

这过于复杂了……
用于开发本数据集的定制软件已处理了上述部分步骤。可前往https://github.com/MaximeAgez/pylcaio查看。你也可通过该软件自行生成ecoinvent的混合版本（可调整多项参数，如重复计算（double counting）修正、通货膨胀率、所用价格数据等）。截至pylcaio v2.1版本，该软件直接生成的混合数据库可导出至Brightway2中并进行后续操作。

如何获取更多相关信息？
完整的方法论细节可参考(Agez et al., 2021)。