Global_CO2_from_cement_production

Global CO2 from Cement Production Dataset

This repository downloads the Andrew dataset on global CO2 emissions from cement production from Zenodo.

Description

This repository downloads datasets on global CO2 emissions from cement production from Zenodo. The downloaded dataset can then be converted into CSV (.csv file extension) or NetCDF (.nc file extension) format. The data management tool DataLad is used to version control the data sets. Commands to run the scripts are executed via the pydoit package.

Installation

• Install datalad according to the DataLad handbook. It is recommended to install globally.
• DataLad is based on Git. You need to install Git to run DataLad. If you are already a Git user you can skip this step.
• You need to have Python installed on your computer.

• pydoit can be installed with

  pip install doit
  

Getting Started

1. Clone the repository

Download the repository using the following command.

datalad clone

Do not use git clone to download the repository! This way DataLad will not have the necessary information to run the program.

2. Easy Access

Users who simply want to download the dataset have the option to access both the original and extracted files with the following command.

dataland get <filename>

For example, the extracted data set for the 2023/09/13 release can be downloaded with:

datalad get extracted_data/v230913/Robbie_Andrew_Cement_Production_CO2_230913.csv 

3. Executing the program

3.1 Set up the virtual environment with doit

doit setup_env

3.2 Download the version from the command line.

This will download all files from Zenodo as they are.

doit download_version --version <YYMMDD>

3.3 Convert the data sets into CSV and NetCDF files.

doit read_version --version <YYMMDD>

How to add a new version

To add a new version go to versions.py in the src directory and create a new entry in the dictionary. Fill all the required information similar to the previous entries. For example, the code added for the 13-Sep-2023 release looks like this:

versions = {
    "v230913": {
        'date': '13-Sep-2023',
        'ver_str_long': 'version 230913',
        'ver_str_short': '230913',
        "folder": "v230913",
        "transpose": False,
        "filename": "0. GCP-CEM.csv",
        'ref': '10.5281/zenodo.8339353',
        'ref2': '10.5194/essd-11-1675-2019',
        'title': 'Global CO2 emissions from cement production',
        'institution': "CICERO - Center for International Climate Research",
        'filter_keep': {},
        'filter_remove': {},
        'contact': "johannes.guetschow@climate-resource.com",
        'comment': ("Published by Robbie Andrew, converted to PRIMAP2 format by "
                    "Johannes Gütschow"),
        'unit': 'kt * CO2 / year',
        'country_code': True,
    },
}

Then run the two commands as described in [3.2]() and [3.3]().

Help

Show all doit commands

doit help

See a list with possible doit commands specific to this repository

doit list

Get help on a specific command

doit help <command>

For developers

Repository structure

• /.datalad contains config file for datalad
• /downloaded_data contains original data from Zenodo.
• /extracted_data contains data in .csv and .nc format
• /literature contains link to publication by Robbie M. Andrew. You need to get it with datalad get
• src/ adjust this for all
  • download_version.py downloads files from zenodo for a given version. The version to read will be taken from the command line using argparse.
  • download_version_datalad.py calls datalad API to run the data reading function.
  • helper_functions.py contains a function to map country codes.
  • read_version.py reads the data for a given version and saves to primap2 native and interchange format.
  • read_version_datalad.py calls datalad to run the data reading function.
  • version.py is a dictionary that contains metadata for each release. This file should be updated when adding a new version
• dodo.py defines pydoit commands.
• pyproject.toml
• requirements.txt dependencies for virtual environment
• requirements_dev.txt development requirements
• setup.cfg all the requirments are actually here
• setup.py to install python packages