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SwolfPy is a free, multi-platform, Python-based, open-source, SWM LCA optimization framework with built-in parametric and Monte Carlo sensitivity and uncertainty analysis capabilities.

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Solid Waste Optimization Life-cycle Framework in Python(SwolfPy)

Supported Python Versions License Downloads Format Documentation Status Test DOi

Features

  • Life-cycle assessment of Municipal Solid Waste (MSW) systems
    • Comparative LCA
    • Contribution analysis
    • LCI report
  • Monte Carlo simulation
    • Uncertainty analysis
    • Data visualization (distributions & correlations)
  • Optimization
    • Minimize environmental burdens or cost subject to a number of technical or policy-related constraints
Life-cycle process models
  Process model Description
1 Landfill (LF) Calculates emissions, material use, and energy use associated with construction, operations, closure and post-closure activities, landfill gas and leachate management, and carbon storage.
2 Waste-to-Energy (WTE) Calculates emissions, mass flows, and resource use and recovery for the mass burn WTE process.
3 Gasification & Syngas Combustion (GC) Calculates emissions, mass flows, and resource use and recovery for the GC process (Produced syngas from gasification is combusted to produce electricity by steam turbine).
4 Composting (Comp) Calculates emissions, mass flows, and resource use and recovery for aerobic composting process and final use of compost.
5 Home Composting (HC) Calculates emissions, mass flows, and resource use and recovery for home composting process and final use of compost.
6 Anaerobic Digestion (AD) Calculates emissions, mass flows, and resource use and recovery for anaerobic digestion process and final use of compost.
7 Single-Stream Material Recovery facility (SS_MRF) Calculates cost, emissions, and energy use associated with material recovery facilities.
8 Refuse-Derived Fuel (RDF) Calculates cost, emissions, and energy use associated with RDF prodcution facilities.
9 Reprocessing (Reproc) Calculates emissions, mass flows, and resource use and recovery associated with recycling materials.
10 Transfer Station (TS) Calculates cost, emissions, and energy use associated with Transfer Stations.
11 Single Family Collection (SF_Col) Calculates cost, emissions, and fossil fuel use associated with MSW collection.

Installation

1- Download and install miniconda from: https://docs.conda.io/en/latest/miniconda.html

2- Update conda in a terminal window or anaconda prompt:

conda update conda

3- Add conda channels:

conda config --append channels conda-forge
conda config --append channels cmutel
conda config --append channels haasad

4- Create a new environment for swolfpy:

conda create --name swolfpy python=3.7

5- Activate the environment:

conda activate swolfpy

6- Install swolfpy in the environment:

pip install swolfpy

7- Open python to run swolfpy:

python

8- Run swolfpy in python:

import swolfpy as sp
sp.swolfpy()

About

SwolfPy is a free, multi-platform, Python-based, open-source, SWM LCA optimization framework with built-in parametric and Monte Carlo sensitivity and uncertainty analysis capabilities.

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