This repository estimates the global emissions impacts of different universal mobile broadband strategies (focusing on terrestrial 4G and 5G options).
Sustainable Development Goal (SDG) 9 aims to build resilient infrastructure and promote inclusive and sustainable industrialization. For example, via universal mobile broadband.
However, there is a trade-off in attempting to deliver this aspirational objective. Expanding existing broadband infrastructure will incur new emissions, potentially contrevening SDG13, which aims to take urgent steps to combat climate change and its impacts via decarbonization.
This analysis quantifies this trade-off by first estimating (i) the existing energy and emissions produced globally by mobile broadband networks and (ii) the additional energy and emissions impacts from providing universal mobile broadband via terrestrial 4G or 5G.
Oughton, E.J., Oh, J., Ballan, S., Kusuma, J., 2023. Sustainability assessment of 4G and 5G universal mobile broadband strategies. https://doi.org/10.48550/arXiv.2311.05480
You can install the existing conda environment using:
conda env create -f environment.yml
Otherwise, you can create one from scratch:
conda create --name cucumber python=3.7 gdal
Once you've completed either optionm you can activate your environment (and run this each time you switch projects):
conda activate cucumber
Some packages will be required if you didn't use the pre-existing conda environment:
conda install geopandas rasterio rasterstats
To begin running the code, we first need to collect the data:
python scripts/collect_data.py
And then process the demand inputs:
python scripts/demand.py
Next, we can preprocess other required data:
python scripts/preprocess.py
Before identifying local sites:
python scripts/supply.py
The energy layers also need processing:
python scripts/energy.py
- Ed Oughton (George Mason University)