📦 DEALA --- Differentiated Economic Assessment in a Life cycle-oriented Analysis

DEALA is a Python package developed to perform comprehensive and differentiated economic assessments within Life Cycle (Sustainability) Assessment (LC(S)A) or Life Cycle Costing (LCC).
It integrates economic data, provides three predefined economic life cycle impact assessment methods, and extends existing LCA frameworks such as Brightway2 with economic databases and characterization models.

📚 Further Information

Detailed information about the DEALA method can be found in the following scientific publication:

👉 https://doi.org/10.1111/jiec.13584

Popien, J.-L., Barke, A., Ginster, R., Striecks, T., Thies, C., & Spengler, T. S. (2024).
DEALA --- A novel economic life cycle impact assessment method for differentiated economic assessments in the context of life cycle sustainability assessments.
Journal of Industrial Ecology. https://doi.org/10.1111/jiec.13584

📘 Doctoral Thesis (German only)

Additional background, theoretical derivations, and detailed data structures can be found in the dissertation:

👉 https://link.springer.com/book/9783658500016\ (German language)

🚀 Key Features

1. Three economic LCIA methods
   DEALA-Cost, DEALA-Profit, and DEALA-Invest.

2. Integrated marketsphere database
   Contains economic flows enabling economic impact calculations directly.

3. Support for Life Cycle Sustainability Assessments (LCSA)
   Unified environmental, social, and economic assessment.

4. Case studies & example notebooks

   • pan_production.ipynb -- main worked example\
   • regioinvent.ipynb -- regionalized modeling with Regiopremise + efficient database generation\
   • calculation_results.ipynb -- computing results & verifying correct setup

5. Example data and templates
   Useful datasets to support typical DEALA workflows.

6. Regionalized and time-dependent assessments
   Including scenario-specific and temporally resolved economic parameters.

🏁 Getting Started

🔧 Installation Options

DEALA can be installed using pip or the recommended uv-based setup.

✔ Option A --- Install via pip

pip install deala

✔ Option B --- Recommended installation using uv (Astral)

1️⃣ Install uv

👉 https://docs.astral.sh/uv/getting-started/installation/

2️⃣ Additional steps for macOS

1. Install Homebrew
   👉 https://brew.sh/

2. Install required packages:

brew install swig suite-sparse pkg-config

3. Set compiler flag:

export CFLAGS="$CFLAGS -Wno-int-conversion"

3️⃣ Create an empty project directory

mkdir deala_env
cd deala_env
code .

4️⃣ Initialize the project using uv

uv init --python 3.11.8

5️⃣ Add DEALA to the environment

uv add deala

6️⃣ (Optional) Add Regiopremise for regionalized inventories

uv add "regioinvent @ git+https://github.com/matthieu-str/Regiopremise"

🧪 Example: Loading DEALA & Importing Databases

import deala as de
from deala import deala_io

deala_io_instance = deala_io()

1. Setup DEALA

Loads the marketsphere database and the DEALA LCIA methods.

deala_io_instance.deala_setup(overwrite=True)

2. Import DEALA activities

Uses predefined datasets (labor, construction, materials, etc.) and generates scenario-dependent databases.

deala_io_instance.import_DEALA_activities_fast(
    base_year,
    dict_scenarios,
    directory_deala,
    price_calculation=price_calculation_method,
    method_calc_r=method_calculation_real_prices,
    modus=None
)

Import PPP-based regionalized material prices:

deala_io_instance.import_PPP_DEALA_activities(FP_material_regionalized)

3. Create default DEALA activities

Creates activities with unknown ex-ante prices (investment-dependent, cost-based, etc.).

deala_io_instance.create_default_DEALA_activities_fast(
    "DEALA_activities_",
    dict_scenarios,
    overwrite=False
)

📄 License

BSD 3-Clause License

🙋 Support

For questions, suggestions, or contributions, please open an issue on GitHub or contact the development team.