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Release Date: Apr 24, 2024
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License

MIT

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Last Release: 7 months ago
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Package

Python Versions Compatibility: <4.0,>=3.9

Age: 7 months
Latest Release: 7 months ago
Dependencies: 0 Direct
Versions: 1
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Readme

🐮 Cattle_lca, a lifecycle assessment tool for livestock systems

Based on the GOBLIN (General Overview for a Backcasting approach of Livestock INtensification) LifeCycle Analysis tool, the Cattle_lca module decouples this module making it an independent distribution package.

The package is shipped with key data for emissions factors, concentrate feed inputs, animal features, grassland parameters and upstream emissions.

Currently parameterised for Ireland, but the database can be updated with additional emissions factor contexts, which are selected able with an emissions factor key.

Final results are output as a dictionary object capturing emissions for:

-   enteric_ch4
-   manure_management_N2O
-   manure_management_CH4
-   manure_applied_N
-   N_direct_PRP
-   N_direct_PRP
-   N_indirect_PRP
-   N_direct_fertiliser
-   N_indirect_fertiliser
-   soils_CO2
-   soil_organic_N_direct
-   soil_organic_N_indirect
-   soil_inorganic_N_direct
-   soil_inorganic_N_indirect
-   soil_histosol_N_direct
-   crop_residues_N_direct
-   soil_N_direct
-   soil_N_indirect
-   soils_N2O

Note, that the soil_histosol_N_direct and crop_residues_N_direct category will be 0. Estimation of the soils N2O direct emissions from histosols uses requires the land use data. Emissions can be included using the landcover_lca module and the crop_lca module.

Installation

Install from git hub.

pip install "cattle_lca@git+https://github.com/GOBLIN-Proj/cattle_lca.git@main"

Install from PyPI.

pip install cattle_lca

Usage

import pandas as pd
from cattle_lca.resource_manager.models import load_livestock_data, load_farm_data
from cattle_lca.lca import ClimateChangeTotals


def main():


    #Create some data to generate results 

    livestock_data = [
        ['ireland', 2018, 2018, 'dairy_cows', 175298, 538, 14.953, 'irish_grass', 'pasture', 'concentrate', 2.992828296, 13.5890411, 10.4109589, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'suckler_cows', 30587, 600, 1.410958904, 'irish_grass', 'pasture', 'concentrate', 0.842751605, 12.2739726, 11.7260274, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxD_heifers_more_2_yr', 384.1446311, 122.125, 0, 'irish_grass', 'pasture', 'concentrate', 0, 12.98630137, 11.01369863, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxB_heifers_more_2_yr', 0, 94.75, 0, 'irish_grass', 'pasture', 'concentrate', 0, 12.98630137, 11.01369863, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'BxB_heifers_more_2_yr', 0, 103.875, 0, 'irish_grass', 'pasture', 'concentrate', 0, 12.38356164, 11.61643836, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxD_heifers_less_2_yr', 49298.56099, 395.875, 0, 'irish_grass', 'pasture', 'concentrate', 0, 11.56164384, 12.43835616, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxB_heifers_less_2_yr', 30347.42586, 346.6, 0, 'irish_grass', 'pasture', 'concentrate', 0, 11.56164384, 12.43835616, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'BxB_heifers_less_2_yr', 14763.98982, 412.3, 0, 'irish_grass', 'pasture', 'concentrate', 0, 11.56164384, 12.43835616, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxD_steers_less_2_yr', 37646.17385, 463.475, 0, 'irish_grass', 'pasture', 'concentrate', 0, 11.56164384, 12.43835616, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxB_steers_less_2_yr', 29323.04018, 474.425, 0, 'irish_grass', 'pasture', 'concentrate', 0, 11.56164384, 12.43835616, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'BxB_steers_less_2_yr', 14327.92261, 479.9, 0, 'irish_grass', 'pasture', 'concentrate', 0, 11.56164384, 12.43835616, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxD_steers_more_2_yr', 5506.073046, 140.45, 0, 'irish_grass', 'pasture', 'concentrate', 0, 18.73972603, 5.260273973, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxB_steers_more_2_yr', 4225.590942, 129.5, 0, 'irish_grass', 'pasture', 'concentrate', 0, 18.73972603, 5.260273973, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'BxB_steers_more_2_yr', 2273.779022, 162.35, 0, 'irish_grass', 'pasture', 'concentrate', 0, 18.73972603, 5.260273973, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxD_calves_f', 46993.69321, 149.575, 0, 'irish_grass', 'pasture', 'concentrate', 1, 7.945205479, 16.05479452, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxB_calves_f', 33164.48649, 116.725, 0, 'irish_grass', 'pasture', 'concentrate', 1, 7.945205479, 16.05479452, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'BxB_calves_f', 13985.29837, 175.125, 0, 'irish_grass', 'pasture', 'concentrate', 1, 7.945205479, 16.05479452, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxD_calves_m', 32140.1008, 122.2, 0, 'irish_grass', 'pasture', 'concentrate', 1, 7.945205479, 16.05479452, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'DxB_calves_m', 31755.95617, 118.55, 0, 'irish_grass', 'pasture', 'concentrate', 1, 7.945205479, 16.05479452, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'BxB_calves_m', 13424.64053, 178.775, 0, 'irish_grass', 'pasture', 'concentrate', 1, 7.945205479, 16.05479452, 0, 0, 'tank liquid', 'broadcast', 0, 0],
        ['ireland', 2018, 2018, 'bulls', 4641.388771, 773, 0, 'irish_grass', 'pasture', 'concentrate', 0.654140961, 11.56164384, 12.43835616, 0, 0, 'tank liquid', 'broadcast', 0, 0]
        ]


    columns = ['ef_country', 'farm_id', 'year', 'cohort', 'pop', 'weight', 'daily_milk', 'forage', 'grazing',
                'con_type', 'con_amount', 't_outdoors', 't_indoors', 'wool', 't_stabled', 'mm_storage',
                'daily_spreading', 'n_sold', 'n_bought']

    livestock_data_frame = pd.DataFrame(livestock_data, columns=columns)

    farm_data = {
        'ef_country': ['ireland'],
        'farm_id': [2018],
        'year': [2018],
        'total_urea_kg': [2072487.127],
        'total_lime_kg': [2072487.127],
        'an_n_fert': [2072487.127],
        'urea_n_fert': [2072487],
        'total_urea_abated': [17310655.18],
        'total_p_fert': [1615261.859],
        'total_k_fert': [3922778.8],
        'diesel_kg': [0],
        'elec_kwh': [0]
    }

    farm_dataframe = pd.DataFrame(farm_data)

    # Instantiate ClimateChange Totals Class, passing Ireland as the emissions factor country
    climatechange = ClimateChangeTotals("ireland")

    #Create a dictionary to store results 
    index = -1
    emissions_dict = climatechange.create_emissions_dictionary([index])
    
    #load the dataframes 
    animals = load_livestock_data(livestock_data_frame)
    farms = load_farm_data(farm_dataframe)


    animals_loc = list(animals.keys())[0]
    farm_loc = list(farms.keys())[0]

    #generate results and store them in the dictionary

    emissions_dict["enteric_ch4"][index] += (
        climatechange.CH4_enteric_ch4(
            animals[animals_loc]["animals"]
        )
    )
    emissions_dict["manure_management_N2O"][index] += (
        climatechange.Total_storage_N2O(
            animals[animals_loc]["animals"]
        )
    )
    emissions_dict["manure_management_CH4"][index] += (
        climatechange.CH4_manure_management(
            animals[animals_loc]["animals"]
        )
        
    )
    emissions_dict["manure_applied_N"][index] += (
        climatechange.Total_N2O_Spreading(
            animals[animals_loc]["animals"]
        )
        
    )
    emissions_dict["N_direct_PRP"][index] += (
        climatechange.N2O_total_PRP_N2O_direct(
            animals[animals_loc]["animals"]
        )
        
    )

    emissions_dict["N_indirect_PRP"][index] += (
        climatechange.N2O_total_PRP_N2O_indirect(
            animals[animals_loc]["animals"]
        )
        
    )
    emissions_dict["N_direct_fertiliser"][index] = (
        climatechange.N2O_direct_fertiliser(
            farms[farm_loc].urea_n_fert,
            farms[farm_loc].total_urea_abated,
            farms[farm_loc].an_n_fert
        )
        
    )

    emissions_dict["N_indirect_fertiliser"][index] += (
        climatechange.N2O_fertiliser_indirect(
            farms[farm_loc].urea_n_fert,
            farms[farm_loc].total_urea_abated,
            farms[farm_loc].an_n_fert,
        )
        
    )
    emissions_dict["soils_CO2"][index] += (
        climatechange.CO2_soils_GWP(
            farms[farm_loc].total_urea_kg,
            farms[farm_loc].total_lime_kg,
        )
        
    )


    # Add the totals 
    emissions_dict["soil_organic_N_direct"][index] = (
        emissions_dict["manure_applied_N"][index]
        + emissions_dict["N_direct_PRP"][index]
    )
    emissions_dict["soil_organic_N_indirect"][index] = emissions_dict[
        "N_indirect_PRP"
    ][index]

    emissions_dict["soil_inorganic_N_direct"][index] = emissions_dict[
        "N_direct_fertiliser"
    ][index]
    emissions_dict["soil_inorganic_N_indirect"][
        index
    ] = emissions_dict["N_indirect_fertiliser"][index]

    emissions_dict["soil_N_direct"][index] = (
        emissions_dict["soil_organic_N_direct"][index]
        + emissions_dict["soil_inorganic_N_direct"][index]
    )

    emissions_dict["soil_N_indirect"][index] = (
        emissions_dict["soil_inorganic_N_indirect"][index]
        + emissions_dict["soil_organic_N_indirect"][index]
    )

    emissions_dict["soils_N2O"][index] = (
        emissions_dict["soil_N_direct"][index]
        + emissions_dict["soil_N_indirect"][index]
    )

    #Print the emission results dictionary
    print(emissions_dict)


if __name__ == "__main__":
    main()

License

This project is licensed under the terms of the MIT license.

FAQs

What is cattle_lca?

Tier 2 Environmental Impact Assessment tool for dairy and beef cattle. Visit Snyk Advisor to see a full health score report for cattle_lca, including popularity, security, maintenance & community analysis.

Is cattle_lca popular?

We’re still processing downloads data for the python package cattle_lca. Visit the popularity section on Snyk Advisor to see the full popularity analysis.

Is cattle_lca well maintained?

We found indications that cattle_lca is an Inactive project. See the full package health analysis to learn more about the package maintenance status.

Is cattle_lca safe to use?

The python package cattle_lca was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 28 November-2024, at 20:36 (UTC).

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cattle_lca

Tier 2 Environmental Impact Assessment tool for dairy and beef cattle. For more information about how to use this package see README

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🐮 Cattle_lca, a lifecycle assessment tool for livestock systems

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🐮 Cattle_lca, a lifecycle assessment tool for livestock systems

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