python cURL JavaScript (browser) JavaScript (NodeJS)
Overview

Overview

Welcome to the Hestia API documentation!

API

API

To access the API:

  1. Create an Account.
  2. Retrieve your access token:
curl -X POST "<APIUrl>/users/signin" \
  -H "Content-Type: application/json" \
  --data '{"email":"email@email.com","password":"pwd"}' | jq '.token'
import json
import requests

headers = {'Content-Type': 'application/json'}
body = json.dumps({"email":"email@email.com","password":"pwd"})
token = requests.post('<APIUrl>/users/signin', body, headers=headers).json().get('token')
print(token)
(async () => {
  const url = '<APIUrl>/users/signin';
  const headers = {
    'Content-Type': 'application/json'
  };
  const body = JSON.stringify({ email: 'email@email.com', password: 'pwd' });
  const response = await fetch(url, { method: 'POST', headers, body });
  const { token } = await response.json();
  console.log(token);
})();
const axios = require('axios');

(async () => {
  const url = '<APIUrl>/users/signin';
  const body = { email: 'email@email.com', password: 'pwd' };
  const { data: { token } } = await axios.post(url, body);
  console.log(token);
})();
Documentation

Documentation

You can view the API documentation and test it here.

Samples

Samples

Retrieving your profile

curl -H "X-ACCESS-TOKEN: <your-token>" \
  -H "Content-Type: application/json" \
  "<APIUrl>/users/me"
import requests

headers = {'Content-Type': 'application/json', 'X-ACCESS-TOKEN': '<your-token>'}
profile = requests.get('<APIUrl>/users/me', headers=headers).json()
print(profile)
(async () => {
  const url = '<APIUrl>/users/me';
  const headers = {
    'Content-Type': 'application/json',
    'X-ACCESS-TOKEN': '<your-token>'
  };
  const response = await fetch(url, { headers });
  const profile = await response.json();
  console.log(profile);
})();
const axios = require('axios');

(async () => {
  const url = '<APIUrl>/users/me';
  const headers = {
    'X-ACCESS-TOKEN': '<your-token>'
  };
  const { data } = await axios.get(url, { headers });
  console.log(data);
})();

Downloading a node (example for a Term)

curl "<APIUrl>/terms/sandContent"
import requests

headers = {'Content-Type': 'application/json'}
node = requests.get('<APIUrl>/terms/sandContent', headers=headers).json()
print(node)
# or use our utils library
from hestia_earth.schema import SchemaType
from hestia_earth.utils.api import download_hestia

node = download_hestia('sandContent', SchemaType.TERM)
(async () => {
  const url = '<APIUrl>/terms/sandContent';
  const headers = {
    'Content-Type': 'application/json'
  };
  const response = await fetch(url, { headers });
  const node = await response.json();
  console.log(node);
})();
const axios = require('axios');

(async () => {
  const url = '<APIUrl>/terms/sandContent';
  const { data } = await axios.get(url);
  console.log(data);
})();

Getting related nodes

curl "<APIUrl>/terms/sandContent/sites"
import requests

headers = {'Content-Type': 'application/json'}
node = requests.get('<APIUrl>/terms/sandContent/sites', headers=headers).json()
print(node)
# or use our utils library
from hestia_earth.schema import SchemaType
from hestia_earth.utils.api import find_related

cycles = find_related(SchemaType.TERM, 'sandContent', SchemaType.SITE)
(async () => {
  const url = '<APIUrl>/terms/sandContent/sites';
  const headers = {
    'Content-Type': 'application/json'
  };
  const response = await fetch(url, { headers });
  const node = await response.json();
  console.log(node);
})();
const axios = require('axios');

(async () => {
  const url = '<APIUrl>/terms/sandContent/sites';
  const { data } = await axios.get(url);
  console.log(data);
})();

All of our Nodes are linked together by a Graph Database, which means you can get a list of Site that are linked to a Term for example.

Full Examples

Full Examples

from hestia_earth.schema import SchemaType
from hestia_earth.utils.api import find_node, download_hestia

# this will give you partial information only
cycles = find_node(SchemaType.CYCLE, {
  'emissions.term.name': 'NO3, to groundwater, soil flux'
})

for cycle in cycles:
  # to retrieve the complete data of the cycle
  data = download_hestia(cycle['@id'], SchemaType.CYCLE, data_state='recaclulated')
  inputs = data.get('inputs', [])
  N_filter = [sum(input.get('value')) if input.get('term', {}).get('units') == 'kg N' else 0 for input in inputs]
  total = sum(N_filter)
  print(cycle, 'total nitrogen fertilizer', total)
from hestia_earth.schema import SchemaType
from hestia_earth.utils.api import find_node, download_hestia
from hestia_earth.utils.model import find_term_match

# searching for aggregated GWP100 emissions on "Maize, grain"
impacts = find_node(SchemaType.IMPACTASSESSMENT, {
  'aggregated': 'true',
  'product.name': 'Maize, grain'
})
# only download the first impact to test, but there would be many more
data = download_hestia(impacts[0]['@id'], SchemaType.IMPACTASSESSMENT, data_state='aggregated')
# 'gwp100' here refers to the @id and not the name
emission = find_term_match(data['impacts'], 'gwp100')
print(emission['value'])
(async () => {
  const apiUrl = '<APIUrl>';
  const searchUrl = '<APIUrl>/search';
  const headers = {
    'Content-Type': 'application/json'
  };
  const body = JSON.stringify({
    fields: ['@id'],
    limit: 10,
    query: {
      bool: {
        'must': [
          { match: { '@type': 'Cycle' } },
          { match: { 'emissions.term.name': 'NO3, to groundwater, soil flux' } }
        ]
      }
    }
  });
  const { results: cycles } = await (await fetch(searchUrl, { method: 'POST', headers, body })).json();
  cycles.map(async cycle => {
    const data = await (await fetch(`${apiUrl}/cycles/${cycle['@id']}`, { headers })).json();
    const values = (data.inputs || [])
      .filter(input => input.term.units === 'kg N')
      .flatMap(input => input.value);
    const total = values.reduce((a, b) => a + b, 0);
    console.log(cycle, 'total nitrogen fertilizer', total);
  });
})();
(async () => {
  const apiUrl = '<APIUrl>';
  const searchUrl = '<APIUrl>/search';
  const headers = {
    'Content-Type': 'application/json'
  };
  // searching for aggregated GWP100 emissions on "Maize, grain"
  const body = JSON.stringify({
    fields: ['@id'],
    limit: 10,
    query: {
      bool: {
        'must': [
          { match: { '@type': 'ImpactAssessment' } },
          { match: { 'aggregated': true } },
          { match: { 'product.term': 'Maize, grain' } }
        ]
      }
    }
  });
  const { results: impacts } = await (await fetch(searchUrl, { method: 'POST', headers, body })).json();
  impacts.map(async impact => {
    const url = `${apiUrl}/impactassessments/${impact['@id']}?dataState=aggregated`;
    const data = await (await fetch(url, { headers })).json();
    const value = (data.impacts || []).find(impact => impact.term.name === 'GWP100').value;
    console.log(value);
  });
})();
const axios = require('axios');

(async () => {
  const apiUrl = '<APIUrl>';
  const searchUrl = '<APIUrl>/search';
  const body = {
    fields: ['@id'],
    limit: 10,
    query: {
      bool: {
        'must': [
          { match: { '@type': 'Cycle' } },
          { match: { 'emissions.term.name': 'NO3, to groundwater, soil flux' } }
        ]
      }
    }
  };
  const { data: { results: cycles } } = await axios.post(searchUrl, body);
  cycles.map(async cycle => {
    const { data } = await axios.get(`${apiUrl}/cycles/${cycle['@id']}`);
    const values = (data.inputs || [])
      .filter(input => input.term.units === 'kg N')
      .flatMap(input => input.value);
    const total = values.reduce((a, b) => a + b, 0);
    console.log(cycle, 'total nitrogen fertilizer', total);
  });
})();
const axios = require('axios');

(async () => {
  const apiUrl = '<APIUrl>';
  const searchUrl = '<APIUrl>/search';
  // searching for aggregated GWP100 emissions on "Maize, grain"
  const body = {
    fields: ['@id'],
    limit: 10,
    query: {
      bool: {
        'must': [
          { match: { '@type': 'ImpactAssessment' } },
          { match: { 'aggregated': true } },
          { match: { 'product.term': 'Maize, grain' } }
        ]
      }
    }
  };
  const { data: { results: impacts } } = await axios.post(searchUrl, body);
  impacts.map(async impact => {
    const url = `${apiUrl}/impactassessments/${impact['@id']}?dataState=aggregated`;
    const { data } = await axios.get(url);
    const value = (data.impacts || []).find(impact => impact.term.name === 'GWP100').value;
    console.log(value);
  });
})();
Validate CSV/JSON files

Validate CSV/JSON files

Hestia provides some functions to validate a CSV / JSON / JSON-LD files formatted following the Hestia format.

Validating a CSV file

Validating a CSV file

To validate a CSV file, you will first need to convert it to JSON. This can be done using the Hestia's utils package:

  1. Install NodeJS version 12
  2. Install the utils library globally: npm install --global @hestia-earth/schema-convert
  3. Drop your CSV files into a specific folder then run:
hestia-convert-to-json folder

You will find in the folder the list of CSV files converted to JSON with the .json extension. These files can be then used for validation described below.

Validating the Terms

Validating the Terms

When uploading data on the Hestia platform, you will need to use our Glossary of Terms. You can follow these steps to install a package to validate the terms:

  1. Install NodeJS version 12
  2. Install the utils library globally: npm install --global @hestia-earth/utils
  3. Drop your JSON / JSON-LD files into a specific folder then run:
API_URL=<APIUrl> hestia-validate-terms folder

Errors will appear in the console if any have been found.

Validating the Schema

Validating the Schema

When uploading data on the Hestia platform, you will need to follow our Schema. You can follow these steps to install a package to validate the schema:

  1. Install NodeJS version 12
  2. Install the schema validation library globally: npm install --global @hestia-earth/schema-validation
  3. Drop your JSON / JSON-LD files into a specific folder then run:
hestia-validate-jsonld '' folder

Errors will appear in the console if any have been found.

Validating the Data

Validating the Data

One important step when uploading data on the Hestia platform is making sure the data is consistent using the Data Validation package. You can follow these steps to install a package to validate the data:

  1. Install Python version 3 minimum
  2. Install the data validation library: pip install hestia_earth.validation
  3. Drop your JSON / JSON-LD files into a specific folder then run:
API_URL=<APIUrl> GEE_API_ENABLED=false VALIDATE_EXISTING_NODES=true hestia-validate-data folder

Errors will appear in the console if any have been found.

Hestia Utils

Hestia Utils

The utils library contains useful functions to work with Hestia data.

Pivoting Headers by Terms

Pivoting Headers by Terms

After downloading data as CSV from the Hestia platform, the format will look like this:

site.@id site.measurements.0.term.@id site.measurements.0.value site.measurements.1.term.@id site.measurements.1.value site.measurements.2.term.@id site.measurements.2.value site.dataPrivate
xvflr sandContent 90 siltContent 6 clayContent 4 false
gght sandContent 90 siltContent 6 clayContent 4 false

It is possible to pivot some data based on the term.@id and move them as columns, such as:

site.@id site.measurements.sandContent.value site.measurements.siltContent.value site.measurements.clayContent.value site.dataPrivate
xvflr 90 6 4 false
gght 90 6 4 false
Usage

Usage

  1. Install Python version 3 minimum
  2. Install the data validation library: pip install hestia_earth.utils
  3. Run:
hestia-pivot-csv source.csv dest.csv

The dest.csv file will be pivoted.

Hestia Calculation Models

Hestia Calculation Models

The Calculation Models are a set of modules for creating structured data models from LCA observations and evaluating biogeochemical aspects of specific farming cycles.

Usage

Usage

  1. You will need to use python 3 (we recommend using python 3.6 minimum).
  2. Install the library:
pip install hestia_earth.models
  1. Set the following environment variables:
API_URL="<APIUrl>"
WEB_URL="<WEBUrl>"

Now you can scroll to the model you are interested in and follow the instructions to run them.

Logging

Logging

The models library is shipped with it's own logging which will be displayed in the console by default. If you want to save the logs into a file, please set the LOG_FILENAME environment variable to the path of the file when running the models.

Example with a my_file.py file like:

from hestia_earth.models.pooreNemecek2018 import run

run('no3ToGroundwaterSoilFlux', cycle_data)

You can save the output in the models.log file by running LOG_FILENAME=models.log python my_file.py.

Orchestrator

Orchestrator

Hestia has developed a library to run the models in a specific sequence defined in a configuration file called the Hestia Engine Orchestrator.

Whereas when running a single model you would do:

from hestia_earth.models.pooreNemecek2018 import run

run('no3ToGroundwaterInorganicFertilizer', cycle_data)

You can run a sequence of models by doing instead:

from hestia_earth.orchestrator import run

config = {
  "models": [
    {
      "key": "emissions",
      "model": "pooreNemecek2018",
      "value": "no3ToGroundwaterInorganicFertilizer",
      "runStrategy": "add_blank_node_if_missing"
    },
    {
      "key": "emissions",
      "model": "pooreNemecek2018",
      "value": "no3ToGroundwaterOrganicFertilizer",
      "runStrategy": "add_blank_node_if_missing"
    }
  ]
}

run(cycle_data, config)

More information and examples are available in the Hestia Engine Orchestrator repository.

Agribalyse (2016)

Agribalyse (2016)

These models use data from the Agribalyse (2016) dataset to gap fill average values.

Fuel and Electricity

Fuel and Electricity

This model calculates fuel and electricity data from the number of hours each machine is operated for using.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.agribalyse2016 import run

print(run('fuelElectricity', Cycle))

View source on Gitlab

Machinery infrastructure, depreciated amount per Cycle

Machinery infrastructure, depreciated amount per Cycle

The quantity of machinery infrastructure, depreciated over its lifetime, divided by the area it operates over, and expressed in kilograms per functional unit per Cycle.

Machinery gradually depreciates over multiple production Cycles until it reaches the end of its life. As a rough rule, the more the machinery is used, the faster it depreciates. Machinery use can be proxied for by the amount of fuel used. From 139 processes in AGRIBALYSE, the ratio of machinery depreciated per unit of fuel consumed (kg machinery kg diesel–1) was established. Recognizing that farms in less developed countries have poorer access to capital and maintain farm machinery for longer, the machinery-to-diesel ratio was doubled in countries with a Human Development Index of less than 0.8.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.agribalyse2016 import run

print(run('machineryInfrastructureDepreciatedAmountPerCycle', Cycle))

View source on Gitlab

Akagi et al (2011) and IPCC (2006)

Akagi et al (2011) and IPCC (2006)

These models calculate the emissions from crop residue burning, using the methodology detailed in the IPCC (2006, Volume 4, Chapter 2, Section 2.4) guidelines and the emissions factors detailed in Akagi et al (2011).

CH4, to air, crop residue burning

CH4, to air, crop residue burning

Methane emissions to air from crop residue burning.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.akagiEtAl2011AndIpcc2006 import run

print(run('ch4ToAirCropResidueBurning', Cycle))

View source on Gitlab

N2O, to air, crop residue burning, direct

N2O, to air, crop residue burning, direct

Nitrous oxide emissions to air from crop residue burning.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.akagiEtAl2011AndIpcc2006 import run

print(run('n2OToAirCropResidueBurningDirect', Cycle))

View source on Gitlab

NH3, to air, crop residue burning

NH3, to air, crop residue burning

Ammonia emissions to air, from crop residue burning.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.akagiEtAl2011AndIpcc2006 import run

print(run('nh3ToAirCropResidueBurning', Cycle))

View source on Gitlab

NOx, to air, crop residue burning

NOx, to air, crop residue burning

Nitrogen oxides emissions to air, from crop residue burning.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.akagiEtAl2011AndIpcc2006 import run

print(run('noxToAirCropResidueBurning', Cycle))

View source on Gitlab

AWARE

AWARE

These models are based on the geospatial AWARE model (see UNEP (2016); Boulay et al (2016); Boulay et al (2020); EC-JRC (2017)).

Scarcity weighted water use

Scarcity weighted water use

This model calculates the scarcity weighted water use based on the geospatial AWARE model (see UNEP (2016); Boulay et al (2016); Boulay et al (2020); EC-JRC (2017)).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Different lookup files are used depending on the situation: - awareWaterBasinId.csv -> using awareWaterBasinId and YR_IRRI (for cropland or permanent pasture) or YR_NONIRRI - region-aware-factors.csv -> using region and YR_IRRI (for cropland or permanent pasture) or YR_NONIRRI

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.aware import run

print(run('scarcityWeightedWaterUse', ImpactAssessment))

View source on Gitlab

Blonk Consultants (2016)

Blonk Consultants (2016)

These models calculate the land transformation and emissions related to land use change, using the Blonk Consultants (2016) direct land use change assessment model.

CH4, to air, natural vegetation burning

CH4, to air, natural vegetation burning

Methane emissions to air, from natural vegetation burning during deforestation or other land conversion.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.blonkConsultants2016 import run

print(run('ch4ToAirNaturalVegetationBurning', Cycle))

View source on Gitlab

CO2, to air, soil carbon stock change

CO2, to air, soil carbon stock change

Carbon dioxide emissions to air from soil carbon stock change.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.blonkConsultants2016 import run

print(run('co2ToAirSoilCarbonStockChange', Cycle))

View source on Gitlab

Land transformation, from forest, 20 year average, during Cycle

Land transformation, from forest, 20 year average, during Cycle

The amount of land used by this Cycle, that changed use from forest to the current use in the last 20 years, divided by 20.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.blonkConsultants2016 import run

print(run('landTransformationFromForest20YearAverage', ImpactAssessment))

View source on Gitlab

N2O, to air, natural vegetation burning, direct

N2O, to air, natural vegetation burning, direct

Direct nitrous oxide emissions to air, from natural vegetation burning during deforestation or other land conversion.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.blonkConsultants2016 import run

print(run('n2OToAirNaturalVegetationBurningDirect', Cycle))

View source on Gitlab

Chaudhary et al (2015)

Chaudhary et al (2015)

This model calculates the biodiversity impacts related to habitat loss as defined in Chaudhary et al (2015, Environ. Sci. Technol. 49, 16, 9987–9995).

Biodiversity loss, land occupation

Biodiversity loss, land occupation

The potential loss of global species due to land occupation.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Different lookup files are used depending on the situation: - ecoregion-factors.csv -> using ecoregion and TAXA_AGGREGATED_Median_occupation columns - region-ecoregion-factors.csv -> using region and TAXA_AGGREGATED_Median_occupation columns

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.chaudharyEtAl2015 import run

print(run('biodiversityLossLandOccupation', ImpactAssessment))

View source on Gitlab

Biodiversity loss, land transformation

Biodiversity loss, land transformation

The potential loss of global species due to land transformation.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Different lookup files are used depending on the situation: - ecoregion-factors.csv -> using ecoregion and TAXA_AGGREGATED_Median_transformation columns - region-ecoregion-factors.csv -> using region and TAXA_AGGREGATED_Median_transformation columns

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.chaudharyEtAl2015 import run

print(run('biodiversityLossLandTransformation', ImpactAssessment))

View source on Gitlab

Biodiversity loss, total land use effects

Biodiversity loss, total land use effects

The potential loss of global species due to land use (occupation, transformation, and permanent effects).

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.chaudharyEtAl2015 import run

print(run('biodiversityLossTotalLandUseEffects', ImpactAssessment))

View source on Gitlab

CML 2001 Baseline

CML 2001 Baseline

These models characterise emissions and resource use according to the CML2001 Baseline method (see Guinée et al. 2002; Jenkin & Hayman, 1999; Derwent et al. 1998, Huijbregts, 1999).

Eutrophication potential, excluding fate

Eutrophication potential, excluding fate

The potential of nutrient emissions to cause excessive growth of aquatic plants and algae in aquatic ecosystems.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cml2001Baseline import run

print(run('eutrophicationPotentialExcludingFate', ImpactAssessment))

View source on Gitlab

Terrestrial acidification potential, including fate, average Europe

Terrestrial acidification potential, including fate, average Europe

Changes in soil chemical properties following the deposition of nitrogen and sulfur in acidifying forms, including average fate of the emissions in Europe.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cml2001Baseline import run

print(run('terrestrialAcidificationPotentialIncludingFateAverageEurope', ImpactAssessment))

View source on Gitlab

CML 2001 Non-Baseline

CML 2001 Non-Baseline

These models characterise emissions and resource use according to the CML2001 Non-Baseline method.

Eutrophication potential, including fate, average Europe

Eutrophication potential, including fate, average Europe

The potential of nutrient emissions to cause excessive growth of aquatic plants and algae in aquatic ecosystems, including an estimated fate of these emissions in Europe.

Characterisation factors used

Characterisation factors used

Characterisation factors applied to every emission can be found in emission lookup, using column noxeqEutrophicationIncludingFateAverageEuropeCml2001Non-Baseline.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cml2001NonBaseline import run

print(run('eutrophicationPotentialIncludingFateAverageEurope', ImpactAssessment))

View source on Gitlab

Terrestrial acidification potential, excluding fate

Terrestrial acidification potential, excluding fate

Changes in soil chemical properties following the deposition of nitrogen and sulfur in acidifying forms, excluding average fate of the emissions in Europe.

Characterisation factors used

Characterisation factors used

Characterisation factors applied to every emission can be found in emission lookup, using column so2EqTerrestrialAcidificationExcludingFateCml2001Non-Baseline.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cml2001NonBaseline import run

print(run('terrestrialAcidificationPotentialExcludingFate', ImpactAssessment))

View source on Gitlab

Cycle

Cycle

These models are specific to Cycle.

Above ground crop residue, total

Above ground crop residue, total

The total amount of above ground crop residue as dry matter. This total is the value prior to crop residue management practices (for example, burning or removal). Properties can be added, such as the nitrogen composition.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('aboveGroundCropResidueTotal', Cycle))

View source on Gitlab

Cycle duration

Cycle duration

This model calculates the cycle duration using the cropping intensity for a single year.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('cycleDuration', Cycle))

View source on Gitlab

Animal feed

Animal feed

This model checks if the site is a cropland and updates the Data Completeness value.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('dataCompleteness', Cycle))

View source on Gitlab

Crop Residue

Crop Residue

This model checks if we have all the crop residue terms and updates the Data Completeness value.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('dataCompleteness', Cycle))

View source on Gitlab

Excreta management

Excreta management

This model checks if the site is a cropland and updates the Data Completeness value.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('dataCompleteness', Cycle))

View source on Gitlab

Material

Material

This model checks if the machinery Input has been added and updates the Data Completeness value.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('dataCompleteness', Cycle))

View source on Gitlab

Other

Other

This model checks if the seed or saplings Input has been added and updates the Data Completeness value.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('dataCompleteness', Cycle))

View source on Gitlab

Soil Amendments

Soil Amendments

This model checks if the soilPh from geospatial dataset is greater than 6.5 and updates the Data Completeness value.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('dataCompleteness', Cycle))

View source on Gitlab

Energy content (lower heating value)

Energy content (lower heating value)

The amount of heat released by combusting a specified quantity in a calorimiter. The combustion process generates water vapor, but the heat in the water vapour is not recovered and accounted for.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('energyContentLowerHeatingValue', Cycle))

View source on Gitlab

Feed conversion ratio (carbon)

Feed conversion ratio (carbon)

The feed conversion ratio (kg C of feed per kg of liveweight produced), based on the carbon content of the feed.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('feedConversionRatio', Cycle))

View source on Gitlab

Feed conversion ratio (dry matter)

Feed conversion ratio (dry matter)

The feed conversion ratio (kg of feed per kg of liveweight produced), based on the dry matter weight of the feed.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('feedConversionRatio', Cycle))

View source on Gitlab

Feed conversion ratio (energy)

Feed conversion ratio (energy)

The feed conversion ratio (MJ of feed per kg of liveweight produced), based on the energy content of the feed.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('feedConversionRatio', Cycle))

View source on Gitlab

Feed conversion ratio (fed weight)

Feed conversion ratio (fed weight)

The feed conversion ratio (kg of feed per kg of liveweight produced), based on the fed weight of the feed.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('feedConversionRatio', Cycle))

View source on Gitlab

Feed conversion ratio (nitrogen)

Feed conversion ratio (nitrogen)

The feed conversion ratio (kg N of feed per kg of liveweight produced), based on the nitrogen content of the feed.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('feedConversionRatio', Cycle))

View source on Gitlab

ecoinvent v3

ecoinvent v3

This model calculates background emissions related to the production of Inputs from the ecoinvent database, version 3.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('input.ecoinventV3', Cycle))

View source on Gitlab

Hestia Aggregated Data

Hestia Aggregated Data

This model adds impactAssessment to Input based on data which has been aggregated into country level averages. Note: to get more accurate impacts, we recommend setting the input.impactAssessment instead of using World or Country averages using this model.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('input.hestiaAggregatedData', Cycle))

View source on Gitlab

Input Value

Input Value

This model calculates the value of the Input by taking an average from the min and max values.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('input.value', Cycle))

View source on Gitlab

Irrigated

Irrigated

More than 25 mm of irrigation per year. The area irrigated can be specified as a percentage.

Irrigated

This model returns the Practice irrigated. Cycles are marked as irrigated if the sum of the irrigation Inputs is greater than 25mm per hectare (250m3 per hectare).

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('irrigated', Cycle))

View source on Gitlab

Live Animal

Live Animal

This model calculates the amount of live animal produced during a Cycle, based on the amount of animal product.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('liveAnimal', Cycle))

View source on Gitlab

Cycle Post Checks

Cycle Post Checks

List of models to run after any other model on an Cycle.

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import primary
from hestia_earth.models.cycle import post_checks

product = primary.run(cycle)
cycle = post_checks.run(cycle)
print(cycle)
Site

Site

This model is run only if the pre model has been run before. This model will restore the cycle.site as a "linked node" (i.e. it will be set with only @type, @id and name keys).

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run(Cycle))

View source on Gitlab

Cycle Pre Checks

Cycle Pre Checks

List of models to run before any other model on an Cycle.

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import primary
from hestia_earth.models.cycle import pre_checks

cycle = pre_checks.run(cycle)
product = primary.run(cycle)
print(product)
Site

Site

Some Cycle models need a full version of the linked Site to run. This model will fetch the complete version of the Site and include it.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run(Cycle))

View source on Gitlab

Start Date

Start Date

This model calculates the startDate from the endDate and cycleDuration.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run(Cycle))

View source on Gitlab

Product Currency

Product Currency

Converts all the currencies to USD using historical rates.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('product.currency', Cycle))

View source on Gitlab

Product Economic Value Share

Product Economic Value Share

This model quantifies the relative economic value share of each marketable Product in a Cycle. Marketable Products are all Products in the Glossary with the exception of crop residue not sold.

It works in the following order: 1. If revenue data are provided for all marketable products, the economicValueShare is directly calculated as the share of revenue of each Product; 2. If the primary product is a crop and it is the only crop Product, economicValueShare is assigned based on a lookup table containing typical global average economic value shares drawn from Poore & Nemecek (2018).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Depending on the primary product termType: - crop.csv -> global_economic_value_share - excreta.csv -> global_economic_value_share

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('product.economicValueShare', Cycle))

View source on Gitlab

Product Price

Product Price

Calculates the price of crop and animalProduct using FAO data.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Depending on the primary product termType: - crop.csv -> cropGroupingFaostatProduction - region-crop-cropGroupingFaostatProduction-price.csv -> use value from above - animalProduct.csv -> animalProductGroupingFAOEquivalent; animalProductGroupingFAO; liveAnimal - region-animalProduct-animalProductGroupingFAO-price.csv -> use value from above - region-animalProduct-animalProductGroupingFAO-averageCarcassWeight.csv -> use value from above

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('product.price', Cycle))

View source on Gitlab

Product Primary

Product Primary

Determines the primary product which is the product with the highest economicValueShare.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('product.primary', Cycle))

View source on Gitlab

Product Revenue

Product Revenue

This model calculates the revenue of each product by multiplying the yield with the revenue. - In the case the product value is 0, the revenue will be set to 0. - In the case the product price is 0, the revenue will be set to 0.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('product.revenue', Cycle))

View source on Gitlab

Product Value

Product Value

This model calculates the value of the Product by taking an average from the min and max values.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('product.value', Cycle))

View source on Gitlab

Residue removed

Residue removed

The amount of crop residue removed.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('residueRemoved', Cycle))

View source on Gitlab

Site duration

Site duration

This model calculates the siteDuration on the Cycle to the same value as cycleDuration when only a single Site is present.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('siteDuration', Cycle))

View source on Gitlab

Transformations

Transformations

This model will merge every Emission from the Transformation back in the Cycle.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.cycle import run

print(run('transformations', Cycle))

View source on Gitlab

Dämmgen (2009)

Dämmgen (2009)

These models calculate direct and indirect greenhouse gas emissions from the German GHG inventory guidelines, Dämmgen (2009).

NOx, to air, excreta

NOx, to air, excreta

Nitrogen oxides emissions to air, from animal excreta.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.dammgen2009 import run

print(run('noxToAirExcreta', Cycle))

View source on Gitlab

de Ruijter et al (2010)

de Ruijter et al (2010)

These models calculate the emissions due to crop residue decomposition using the regression model in de Ruijter et al (2010).

NH3, to air, crop residue decomposition

NH3, to air, crop residue decomposition

Ammonia emissions to air, from crop residue decomposition.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.deRuijterEtAl2010 import run

print(run('nh3ToAirCropResidueDecomposition', Cycle))

View source on Gitlab

EMEA-EEA (2019)

EMEA-EEA (2019)

These models implements the methods in the EMEP-EEA Handbook (2019) Part B, Chapter 1.A.4, page 22.

CO2, to air, fuel combustion

CO2, to air, fuel combustion

Carbon dioxide emissions to air from the combustion of fuel.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.emeaEea2019 import run

print(run('co2ToAirFuelCombustion', Cycle))

View source on Gitlab

N2O, to air, fuel combustion, direct

N2O, to air, fuel combustion, direct

Nitrous oxide emissions to air from the combustion of fuel.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.emeaEea2019 import run

print(run('n2OToAirFuelCombustionDirect', Cycle))

View source on Gitlab

NH3, to air, excreta

NH3, to air, excreta

Ammonia emissions to air, from animal excreta.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.emeaEea2019 import run

print(run('nh3ToAirExcreta', Cycle))

View source on Gitlab

NH3, to air, inorganic fertilizer

NH3, to air, inorganic fertilizer

Ammonia emissions to air, from inorganic fertilizer volatilization.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.emeaEea2019 import run

print(run('nh3ToAirInorganicFertilizer', Cycle))

View source on Gitlab

NOx, to air, fuel combustion

NOx, to air, fuel combustion

Nitrogen oxides emissions to air from the combustion of fuel.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.emeaEea2019 import run

print(run('noxToAirFuelCombustion', Cycle))

View source on Gitlab

SO2, to air, fuel combustion

SO2, to air, fuel combustion

Sulfur dioxide emissions to air from the combustion of fuel.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.emeaEea2019 import run

print(run('so2ToAirFuelCombustion', Cycle))

View source on Gitlab

EPA (2014)

EPA (2014)

These models calculate direct and indirect greenhouse gas emissions using the methodology detailed in the EPA (2014), Anexx 3 guidelines.

NO3, to groundwater, excreta

NO3, to groundwater, excreta

Nitrate leaching to groundwater, from animal excreta.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.epa2014 import run

print(run('no3ToGroundwaterExcreta', Cycle))

View source on Gitlab

FAOSTAT (2018)

FAOSTAT (2018)

These models uses data from the FAOSTAT database (accessed 2018) to calculate values like seed based on crop yield.

Carcass weight per head

Carcass weight per head

The carcass weight of the animals per head.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.faostat2018 import run

print(run('carcassWeightPerHead', Cycle))

View source on Gitlab

Dressed carcass weight per head

Dressed carcass weight per head

The dressed carcass weight (i.e., excluding offal and slaughter fats) of the animals per head.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.faostat2018 import run

print(run('dressedCarcassWeightPerHead', Cycle))

View source on Gitlab

Land transformation, from temporary cropland, 100 year average, during Cycle

Land transformation, from temporary cropland, 100 year average, during Cycle

The amount of land used by this Cycle, that changed use from temporary cropland to the current use in the last 100 years, divided by 100.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.faostat2018 import run

print(run('landTransformationFromCropland100YearAverage', ImpactAssessment))

View source on Gitlab

Land transformation, from temporary cropland, 20 year average, during Cycle

Land transformation, from temporary cropland, 20 year average, during Cycle

The amount of land used by this Cycle, that changed use from temporary cropland to the current use in the last 20 years, divided by 20.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.faostat2018 import run

print(run('landTransformationFromCropland20YearAverage', ImpactAssessment))

View source on Gitlab

Liveweight per head

Liveweight per head

The liveweight of the animals per head.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.faostat2018 import run

print(run('liveweightPerHead', Cycle))

View source on Gitlab

Ready-to-cook weight per head

Ready-to-cook weight per head

The ready-to-cook weight of the animals per head.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.faostat2018 import run

print(run('readyToCookWeightPerHead', Cycle))

View source on Gitlab

Seed

Seed

The seed of a crop.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.faostat2018 import run

print(run('seed', Cycle))

View source on Gitlab

Global Crop Water Model (2008)

Global Crop Water Model (2008)

This model adds rooting depths based on the Global Crop Water Model (Siebert and Doll, 2008).

Rooting depth

Rooting depth

The rooting depth of the crop.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.globalCropWaterModel2008 import run

print(run('rootingDepth', Cycle))

View source on Gitlab

HYDE 3.2

HYDE 3.2

This model uses the HYDE database v3.2 to calculate land use and land use change.

Land transformation, from cropland, 100 year average, during Cycle

Land transformation, from cropland, 100 year average, during Cycle

The amount of land used by this Cycle, that changed use from cropland (temporary and permanent) to the current use in the last 100 years, divided by 100.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

One of (depending on site.siteType): - region-forest-landTransformation100years.csv.csv -> cropland - region-permanent_pasture-landTransformation100years.csv.csv -> cropland - region-other_natural_vegetation-landTransformation100years.csv.csv -> cropland

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.hyde32 import run

print(run('landTransformationFromCropland100YearAverage', ImpactAssessment))

View source on Gitlab

Land transformation, from cropland, 20 year average, during Cycle

Land transformation, from cropland, 20 year average, during Cycle

The amount of land used by this Cycle, that changed use from cropland (temporary and permanent) to the current use in the last 20 years, divided by 20.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

One of (depending on site.siteType): - region-forest-landTransformation20years.csv.csv -> cropland - region-permanent_pasture-landTransformation20years.csv.csv -> cropland - region-other_natural_vegetation-landTransformation20years.csv.csv -> cropland

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.hyde32 import run

print(run('landTransformationFromCropland20YearAverage', ImpactAssessment))

View source on Gitlab

Land transformation, from forest, 100 year average, during Cycle

Land transformation, from forest, 100 year average, during Cycle

The amount of land used by this Cycle, that changed use from forest to the current use in the last 100 years, divided by 100.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

One of (depending on site.siteType): - region-cropland-landTransformation100years.csv.csv -> forest - region-permanent_pasture-landTransformation100years.csv.csv -> forest - region-other_natural_vegetation-landTransformation100years.csv.csv -> forest

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.hyde32 import run

print(run('landTransformationFromForest100YearAverage', ImpactAssessment))

View source on Gitlab

Land transformation, from forest, 20 year average, during Cycle

Land transformation, from forest, 20 year average, during Cycle

The amount of land used by this Cycle, that changed use from forest to the current use in the last 20 years, divided by 20.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

One of (depending on site.siteType): - region-cropland-landTransformation20years.csv.csv -> forest - region-permanent_pasture-landTransformation20years.csv.csv -> forest - region-other_natural_vegetation-landTransformation20years.csv.csv -> forest

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.hyde32 import run

print(run('landTransformationFromForest20YearAverage', ImpactAssessment))

View source on Gitlab

Land transformation, from other natural vegetation, 100 year average, during Cycle

Land transformation, from other natural vegetation, 100 year average, during Cycle

The amount of land used by this Cycle, that changed use from other natural vegetation to the current use in the last 100 years, divided by 100.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

One of (depending on site.siteType): - region-cropland-landTransformation100years.csv.csv -> other natural vegetation - region-forest-landTransformation100years.csv.csv -> other natural vegetation - region-permanent_pasture-landTransformation100years.csv.csv -> other natural vegetation

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.hyde32 import run

print(run('landTransformationFromOtherNaturalVegetation100YearAverage', ImpactAssessment))

View source on Gitlab

Land transformation, from other natural vegetation, 20 year average, during Cycle

Land transformation, from other natural vegetation, 20 year average, during Cycle

The amount of land used by this Cycle, that changed use from other natural vegetation to the current use in the last 20 years, divided by 20.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

One of (depending on site.siteType): - region-cropland-landTransformation20years.csv.csv -> other natural vegetation - region-forest-landTransformation20years.csv.csv -> other natural vegetation - region-permanent_pasture-landTransformation20years.csv.csv -> other natural vegetation

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.hyde32 import run

print(run('landTransformationFromOtherNaturalVegetation20YearAverage', ImpactAssessment))

View source on Gitlab

Land transformation, from permanent pasture, 100 year average, during Cycle

Land transformation, from permanent pasture, 100 year average, during Cycle

The amount of land used by this Cycle, that changed use from permanent pasture to the current use in the last 100 years, divided by 100.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

One of (depending on site.siteType): - region-cropland-landTransformation100years.csv.csv -> permanent pasture - region-forest-landTransformation100years.csv.csv -> permanent pasture - region-other_natural_vegetation-landTransformation100years.csv.csv -> permanent pasture

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.hyde32 import run

print(run('landTransformationFromPermanentPasture100YearAverage', ImpactAssessment))

View source on Gitlab

Land transformation, from permanent pasture, 20 year average, during Cycle

Land transformation, from permanent pasture, 20 year average, during Cycle

The amount of land used by this Cycle, that changed use from permanent pasture to the current use in the last 20 years, divided by 20.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

One of (depending on site.siteType): - region-cropland-landTransformation20years.csv.csv -> permanent pasture - region-forest-landTransformation20years.csv.csv -> permanent pasture - region-other_natural_vegetation-landTransformation20years.csv.csv -> permanent pasture

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.hyde32 import run

print(run('landTransformationFromPermanentPasture20YearAverage', ImpactAssessment))

View source on Gitlab

Impact Assessment

Impact Assessment

These models are specific to Impact Assessment.

Emissions

Emissions

Creates an Indicator for every Emission contained within the ImpactAssesment.cycle. It does this by dividing the Emission amount by the Product amount, and applying an allocation between co-products.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import run

print(run('emissions', ImpactAssessment))

View source on Gitlab

Freshwater withdrawals, during Cycle

Freshwater withdrawals, during Cycle

Withdrawals of water from freshwater lakes, rivers, and aquifers that occur during the Cycle.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import run

print(run('freshwaterWithdrawals', ImpactAssessment))

View source on Gitlab

Organic

Organic

Detects if the Cycle was irrigated.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import run

print(run('irrigated', ImpactAssessment))

View source on Gitlab

Organic

Organic

Detects if the Cycle has an organic label.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import run

print(run('organic', ImpactAssessment))

View source on Gitlab

Impact Assessment Post Checks

Impact Assessment Post Checks

List of models to run after any other model on an ImpactAssessment.

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import irrigated
from hestia_earth.models.impact_assessment import post_checks

impact['irrigated'] = irrigated.run(impact)
impact = post_checks.run(impact)
print(impact)
Cycle

Cycle

This model is run only if the pre model has been run before. This model will restore the impactAssessment.cycle as a "linked node" (i.e. it will be set with only @type, @id and name keys).

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import run

print(run(ImpactAssessment))

View source on Gitlab

Site

Site

This model is run only if the pre model has been run before. This model will restore the impactAssessment.site as a "linked node" (i.e. it will be set with only @type, @id and name keys).

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import run

print(run(ImpactAssessment))

View source on Gitlab

Impact Assessment Pre Checks

Impact Assessment Pre Checks

List of models to run before any other model on an ImpactAssessment.

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import irrigated
from hestia_earth.models.impact_assessment import pre_checks

impact = pre_checks.run(impact)
impact['irrigated'] = irrigated.run(impact)
print(impact)
Cycle

Cycle

Some ImpactAssessment models need a full version of the linked Cycle to run. This model will fetch the complete version of the Cycle and include it.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import run

print(run(ImpactAssessment))

View source on Gitlab

Site

Site

Some ImpactAssessment models need a full version of the linked Site to run. This model will fetch the complete version of the Site and include it.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import run

print(run(ImpactAssessment))

View source on Gitlab

Primary Product

Primary Product

The product of an ImpactAssessment is the primary product of the Cycle.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.impact_assessment import run

print(run('product', ImpactAssessment))

View source on Gitlab

IPCC (2006)

IPCC (2006)

These models calculates direct and indirect greenhouse gas emissions, or uses lookup tables, based on the methodology detailed in the IPCC (2006) guidelines, primarily found in Volume 4, Chapters 10 and 11.

Above ground crop residue, removed

Above ground crop residue, removed

The amount of above ground crop residue dry matter that was removed as part of the crop residue management practice.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('aboveGroundCropResidueRemoved', Cycle))

View source on Gitlab

Above ground crop residue, total

Above ground crop residue, total

The total amount of above ground crop residue as dry matter. This total is the value prior to crop residue management practices (for example, burning or removal). Properties can be added, such as the nitrogen composition.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('aboveGroundCropResidueTotal', Cycle))

View source on Gitlab

Below ground crop residue

Below ground crop residue

The total amount of below ground crop residue as dry matter. Properties can be added, such as the nitrogen composition.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('belowGroundCropResidue', Cycle))

View source on Gitlab

CO2, to air, organic soil cultivation

CO2, to air, organic soil cultivation

Carbon dioxide emissions to air, from organic soil (histosol) cultivation.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('co2ToAirOrganicSoilCultivation', Cycle))

View source on Gitlab

N2O, to air, crop residue decomposition, indirect

N2O, to air, crop residue decomposition, indirect

Nitrous oxide emissions to air, related to leaching, runoff, or redeposition of nitrogen off-site, from crop residue decomposition.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('n2OToAirCropResidueDecompositionIndirect', Cycle))

View source on Gitlab

N2O, to air, excreta, direct

N2O, to air, excreta, direct

Nitrous oxide emissions to air from animal excreta.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('n2OToAirExcretaDirect', Cycle))

View source on Gitlab

N2O, to air, excreta, indirect

N2O, to air, excreta, indirect

Nitrous oxide emissions to air, indirectly created from NOx and NH3 emissions from animal excreta.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('n2OToAirExcretaIndirect', Cycle))

View source on Gitlab

N2O, to air, inorganic fertilizer, direct

N2O, to air, inorganic fertilizer, direct

Nitrous oxide emissions to air from nitrification and denitrification of inorganic fertilizer.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('n2OToAirInorganicFertilizerDirect', Cycle))

View source on Gitlab

N2O, to air, inorganic fertilizer, indirect

N2O, to air, inorganic fertilizer, indirect

Nitrous oxide emissions to air, related to leaching, runoff, or redeposition of nitrogen off-site, from inorganic fertilizer.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('n2OToAirInorganicFertilizerIndirect', Cycle))

View source on Gitlab

N2O, to air, organic fertilizer, direct

N2O, to air, organic fertilizer, direct

Nitrous oxide emissions to air from nitrification and denitrification of organic fertilizer.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('n2OToAirOrganicFertilizerDirect', Cycle))

View source on Gitlab

N2O, to air, organic fertilizer, indirect

N2O, to air, organic fertilizer, indirect

Nitrous oxide emissions to air, related to leaching, runoff, or redeposition of nitrogen off-site, from organic fertilizer.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('n2OToAirOrganicFertilizerIndirect', Cycle))

View source on Gitlab

N2O, to air, organic soil cultivation, direct

N2O, to air, organic soil cultivation, direct

Direct nitrous oxide emissions to air, from organic soil (histosol) cultivation.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2006 import run

print(run('n2OToAirOrganicSoilCultivationDirect', Cycle))

View source on Gitlab

IPCC (2013) excluding feedbacks

IPCC (2013) excluding feedbacks

These models characterise different greenhouse gases into a global warming or global temperature potential, following the IPCC (2013) guidelines. Conversions from each gas to CO2 equivalents exclude climate carbon feedbacks. Climate carbon feedbacks were not included in the IPCC (2007) or earlier guidelines, and were first provided in the IPCC (2013) Table 8.7.

GWP100

GWP100

The global warming potential of mixed greenhouse gases on the mid-term climate (100 years), expressed as CO2 equivalents.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2013ExcludingFeedbacks import run

print(run('gwp100', ImpactAssessment))

View source on Gitlab

IPCC (2013) including feedbacks

IPCC (2013) including feedbacks

These models characterise different greenhouse gases into a global warming or global temperature potential, following the IPCC (2013) guidelines. Conversions from each gas to CO2 equivalents include climate carbon feedbacks. Climate carbon feedbacks were not included in the IPCC (2007) or earlier guidelines, and were first provided in the IPCC (2013) Table 8.7.

GWP100

GWP100

The global warming potential of mixed greenhouse gases on the mid-term climate (100 years), expressed as CO2 equivalents.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2013IncludingFeedbacks import run

print(run('gwp100', ImpactAssessment))

View source on Gitlab

IPCC (2019)

IPCC (2019)

These models calculates direct and indirect greenhouse gas emissions using the methodology detailed in the IPCC 2019 Volume 4 Chapter 10 and 11

Above ground crop residue, total

Above ground crop residue, total

The total amount of above ground crop residue as dry matter. This total is the value prior to crop residue management practices (for example, burning or removal). Properties can be added, such as the nitrogen composition.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('aboveGroundCropResidueTotal', Cycle))

View source on Gitlab

Below ground crop residue

Below ground crop residue

The total amount of below ground crop residue as dry matter. Properties can be added, such as the nitrogen composition.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('belowGroundCropResidue', Cycle))

View source on Gitlab

CH4, to air, enteric fermentation

CH4, to air, enteric fermentation

Methane emissions to air from enteric fermentation by ruminants.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('ch4ToAirEntericFermentation', Cycle))

View source on Gitlab

CH4, to air, excreta

CH4, to air, excreta

Methane emissions to air from animal excreta.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('ch4ToAirExcreta', Cycle))

View source on Gitlab

CH4, to air, flooded rice

CH4, to air, flooded rice

Methane emissions to air from flooded paddy rice fields.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('ch4ToAirFloodedRice', Cycle))

View source on Gitlab

CO2, to air, lime hydrolysis

CO2, to air, lime hydrolysis

Carbon dioxide emissions to air from lime hydrolysis (including dolomitic lime).

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('co2ToAirLimeHydrolysis', Cycle))

View source on Gitlab

CO2, to air, urea hydrolysis

CO2, to air, urea hydrolysis

Carbon dioxide emissions to air from urea hydrolysis (a corresponding negative emission occurs during fertilizer production).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('co2ToAirUreaHydrolysis', Cycle))

View source on Gitlab

Cropping Duration

Cropping Duration

For temporary crops, the period from planting to harvest in days. For perennial crops such as asparagus, the period from planting to removal in days. For transplant rice and other crops with a nursery stage, cropping duration excludes the nursery stage.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('croppingDuration', Cycle))

View source on Gitlab

N2O, to air, excreta, direct

N2O, to air, excreta, direct

Nitrous oxide emissions to air from animal excreta.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('n2OToAirExcretaDirect', Cycle))

View source on Gitlab

Nitrogen content

Nitrogen content

The total nitrogen content of something, as N, expressed as a percentage.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.ipcc2019 import run

print(run('nitrogenContent', Cycle))

View source on Gitlab

Köble (2014)

Köble (2014)

These models estimate the amount of crop residue burnt and removed using country average factors for different crop groupings based on Köble (2014).

Above Ground Crop Residue

Above Ground Crop Residue

This model returns the amounts and destinations of above ground crop residue, working in the following order: 1. Above ground crop residue, removed; 2. Above ground crop residue, incorporated; 3. Above ground crop residue, burnt; 4. Above ground crop residue, left on field.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.koble2014 import run

print(run('aboveGroundCropResidue', Cycle))

View source on Gitlab

Residue burnt

Residue burnt

The amount of crop residue burnt, after multiplication by the combustion factor (which allows for residue burnt but not combusted).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.koble2014 import run

print(run('residue', Cycle))

View source on Gitlab

Residue incorporated

Residue incorporated

The amount of crop residue incorporated.

Returns

Returns

Not implemented

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.koble2014 import run

print(run('residue', Cycle))

View source on Gitlab

Residue left on field

Residue left on field

The amount of crop residue left on field.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.koble2014 import run

print(run('residue', Cycle))

View source on Gitlab

Residue removed

Residue removed

The amount of crop residue removed.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.koble2014 import run

print(run('residue', Cycle))

View source on Gitlab

Hestia Engine Models Mocking

Hestia Engine Models Mocking

When deploying the calculations models on your own server, you might want to bypass any calls to the Hestia API. You can use this mocking functionality in that purpose.

from hestia_earth.models.pooreNemecek2018.aboveGroundCropResidueTotal import run
from hestia_earth.models.mocking import enable_mock

enable_mock()
run(cycle)

View source on Gitlab

Other background database

Other background database

These models calculate background emissions related to the production of Inputs from a background database not included in the Hestia glossary.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.otherBackgroundDatabase import run

emissions = run('all', cycle)
print(emissions)
Poore Nemecek (2018)

Poore Nemecek (2018)

These models implements the models described in the supporting material of Poore & Nemecek (2018).

Above ground crop residue, total

Above ground crop residue, total

The total amount of above ground crop residue as dry matter. This total is the value prior to crop residue management practices (for example, burning or removal). Properties can be added, such as the nitrogen composition.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('aboveGroundCropResidueTotal', Cycle))

View source on Gitlab

Below ground crop residue

Below ground crop residue

The total amount of below ground crop residue as dry matter. Properties can be added, such as the nitrogen composition.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('belowGroundCropResidue', Cycle))

View source on Gitlab

CH4, to air, aquaculture systems

CH4, to air, aquaculture systems

Methane emissions to air from the methanogenesis of organic carbon in excreta, unconsumed feed, fertilizer, and net primary production. Reaches the air through diffusion and ebullition.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('ch4ToAirAquacultureSystems', Cycle))

View source on Gitlab

Excreta (kg N)

Excreta (kg N)

This model uses a mass balance to calculate the total amount of excreta (as N) created by animals. The inputs into the mass balance are the total amount of feed and the total amount of net primary production in the water body. The outputs of the mass balance are the weight of the animal and the excreta. The formula is excreta = feed + NPP - animal. If the mass balance fails (i.e. animal feed is not complete, see requirements below) for live aquatic species, the fomula is = total nitrogen content of the fish * 3.31. It is described in Poore & Nemecek (2018).

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('excretaKgN', Cycle))

View source on Gitlab

Excreta (kg VS)

Excreta (kg VS)

This model calculates the Excreta (kg VS) from the products as described in Poore & Nemecek (2018). The model computes it as the balance between the carbon in the inputs plus the carbon produced in the pond minus the carbon contained in the primary product. If the mass balance fails (i.e. animal feed is not complete, see requirements below), the fomula is = total excreta as N / Volatile solids content.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('excretaKgVs', Cycle))

View source on Gitlab

Flowing Water

Flowing Water

This model returns a measurement of fast flowing water or slow flowing water depending on the type of the site.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('flowingWater', Site))

View source on Gitlab

Land occupation, during Cycle

Land occupation, during Cycle

The amount of land required to produce the Product during the Cycle, multiplied by the time (in years) that the land was occupied including fallow periods.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('landOccupation', ImpactAssessment))

View source on Gitlab

Long Fallow Period

Long Fallow Period

In a cropping rotation, the period which lasts more than one year, but less than five years. Expressed in days.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('longFallowPeriod', Cycle))

View source on Gitlab

N2O, to air, aquaculture systems, direct

N2O, to air, aquaculture systems, direct

Nitrous oxide emissions to air, directly created from the breakdown of excreta and unconsumed feed in aquaculture systems.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('n2OToAirAquacultureSystemsDirect', Cycle))

View source on Gitlab

N2, to air, aquaculture systems

N2, to air, aquaculture systems

Nitrogen emissions to air, created from the breakdown of excreta and unconsumed feed in aquaculture systems.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('n2ToAirAquacultureSystems', Cycle))

View source on Gitlab

Net Primary Production

Net Primary Production

The quantity of organic compounds produced from atmospheric or aqueous carbon dioxide.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('netPrimaryProduction', Site))

View source on Gitlab

NH3, to air, aquaculture systems

NH3, to air, aquaculture systems

Ammonia emissions to air, created from the breakdown of excreta and unconsumed feed in aquaculture systems.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('nh3ToAirAquacultureSystems', Cycle))

View source on Gitlab

NO3, to groundwater, crop residue decomposition

NO3, to groundwater, crop residue decomposition

Nitrate leaching to groundwater, from crop residue decomposition.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('no3ToGroundwaterCropResidueDecomposition', Cycle))

View source on Gitlab

NO3, to groundwater, excreta

NO3, to groundwater, excreta

Nitrate leaching to groundwater, from animal excreta.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('no3ToGroundwaterExcreta', Cycle))

View source on Gitlab

NO3, to groundwater, inorganic fertilizer

NO3, to groundwater, inorganic fertilizer

Nitrate leaching to groundwater, from inorganic fertilizer.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('no3ToGroundwaterInorganicFertilizer', Cycle))

View source on Gitlab

NO3, to groundwater, organic fertilizer

NO3, to groundwater, organic fertilizer

Nitrate leaching to groundwater, from organic fertilizer.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('no3ToGroundwaterOrganicFertilizer', Cycle))

View source on Gitlab

NO3, to groundwater, soil flux

NO3, to groundwater, soil flux

The total amount of nitrate leaching into groundwater from the soil, including from nitrogen added in fertilizer, excreta, and residue, and from natural background processes.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('no3ToGroundwaterSoilFlux', Cycle))

View source on Gitlab

NOx, to air, aquaculture systems

NOx, to air, aquaculture systems

Nitrogen oxides emissions to air, created from the breakdown of excreta and unconsumed feed in aquaculture systems.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('noxToAirAquacultureSystems', Cycle))

View source on Gitlab

Nursery duration

Nursery duration

The time from planting seedlings to the sale of marketable trees

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('nurseryDuration', Cycle))

View source on Gitlab

Orchard Bearing Duration

Orchard Bearing Duration

The length, in days, of the period when an orchard is bearing marketed fruit, as defined in FAOSTAT (2011).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('orchardBearingDuration', Cycle))

View source on Gitlab

Orchard density

Orchard density

The number of trees required for 1 ha of mature orchard

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('orchardDensity', Cycle))

View source on Gitlab

Orchard Duration

Orchard Duration

The length, in days, from the establishment of an orchard to its removal.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('orchardDuration', Cycle))

View source on Gitlab

Rotation Duration

Rotation Duration

The length, in days, of the entire crop rotation, including the long fallow period.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('rotationDuration', Site))

View source on Gitlab

Saplings

Saplings

The number of saplings (young trees) produced or used per hectare per year.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('saplings', Cycle))

View source on Gitlab

Total nitrogen (per kg soil)

Total nitrogen (per kg soil)

The sum of organic and mineral nitrogen in the soil.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('totalNitrogenPerKgSoil', Site))

View source on Gitlab

Water depth

Water depth

The depth of a water body.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pooreNemecek2018 import run

print(run('waterDepth', Site))

View source on Gitlab

Pribyl (2010)

Pribyl (2010)

This model calculates soil organic carbon from soil organic matter and vice versa based on data that soil organic matter is 50% carbon (instead of the conventional factor of 58%).

Organic carbon (per kg soil)

Organic carbon (per kg soil)

The concentration of organic carbon in the soil.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pribyl2010 import run

print(run('organicCarbonPerKgSoil', Site))

View source on Gitlab

Organic carbon (per m3 soil)

Organic carbon (per m3 soil)

The concentration of organic carbon in the soil.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pribyl2010 import run

print(run('organicCarbonPerM3Soil', Site))

View source on Gitlab

Organic matter (per kg soil)

Organic matter (per kg soil)

The concentration of organic matter in the soil. The term refers to any material produced originally by living organisms (plant or animal) that is returned to the soil and goes through the decomposition process.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pribyl2010 import run

print(run('organicMatterPerKgSoil', Site))

View source on Gitlab

Organic matter (per m3 soil)

Organic matter (per m3 soil)

The concentration of organic matter in the soil. The term refers to any material produced originally by living organisms (plant or animal) that is returned to the soil and goes through the decomposition process.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.pribyl2010 import run

print(run('organicMatterPerM3Soil', Site))

View source on Gitlab

ReCiPe 2016 Egalitarian

ReCiPe 2016 Egalitarian

These models characterise emissions and resource use according to the ReCiPe 2016 method, using an egalitarian perspective (see Huijbregts et al (2016), WMO (2011); Hayashi et al. (2006); De Schryver et al. (2011)).

Ecosystem damage ozone formation

Ecosystem damage ozone formation

The potential of emissions to contribute to low level smog (summer smog).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('ecosystemDamageOzoneFormation', ImpactAssessment))

View source on Gitlab

Fossil resource scarcity

Fossil resource scarcity

This model calculates the fossil resource scarcity.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('fossilResourceScarcity', ImpactAssessment))

View source on Gitlab

Freshwater aquatic ecotoxicity potential (1,4-DCBeq)

Freshwater aquatic ecotoxicity potential (1,4-DCBeq)

This model calculates the freshwater aquatic ecotoxicity potential (1,4-dcbeq).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('freshwaterAquaticEcotoxicityPotential14Dcbeq', ImpactAssessment))

View source on Gitlab

Freshwater eutrophication potential

Freshwater eutrophication potential

The potential of nutrient emissions to cause excessive growth of aquatic plants and algae in freshwater ecosystems (e.g. lakes, rivers, streams). Freshwater eutrophication is primarily linked to phosphorus as this tends to be the limiting nutrient in these ecosystems.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('freshwaterEutrophicationPotential', ImpactAssessment))

View source on Gitlab

Human carcinogenic toxicity

Human carcinogenic toxicity

The potential of emissions to contribute to the risk of increased incidence of cancer diseases.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('humanCarcinogenicToxicity', ImpactAssessment))

View source on Gitlab

Human damage ozone formation

Human damage ozone formation

The potential of emissions to contribute to the increase in tropospheric ozone population intake.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('humanDamageOzoneFormation', ImpactAssessment))

View source on Gitlab

Human non-carcinogenic toxicity

Human non-carcinogenic toxicity

The potential of emissions to contribute to the risk of increased incidence of non-cancer diseases.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('humanNonCarcinogenicToxicity', ImpactAssessment))

View source on Gitlab

Marine aquatic ecotoxicity potential (1,4-DCBeq)

Marine aquatic ecotoxicity potential (1,4-DCBeq)

This model calculates the marine aquatic ecotoxicity potential (1,4-dcbeq).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('marineAquaticEcotoxicityPotential14Dcbeq', ImpactAssessment))

View source on Gitlab

Marine eutrophication potential

Marine eutrophication potential

The potential of nutrient emissions to cause excessive growth of aquatic plants and algae in marine ecosystems (e.g. seas, oceans, estuaries). Marine eutrophication is primarily linked to nitrogen as this tends to be the limiting nutrient in these ecosystems.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('marineEutrophicationPotential', ImpactAssessment))

View source on Gitlab

Ozone depletion potential

Ozone depletion potential

The potential of emissions to cause thinning of the stratospheric ozone layer.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('ozoneDepletionPotential', ImpactAssessment))

View source on Gitlab

Terrestrial acidification potential

Terrestrial acidification potential

Changes in soil chemical properties following the deposition of nitrogen and sulfur in acidifying forms.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('terrestrialAcidificationPotential', ImpactAssessment))

View source on Gitlab

Terrestrial ecotoxicity potential (1,4-DCBeq)

Terrestrial ecotoxicity potential (1,4-DCBeq)

This model calculates the terrestrial ecotoxicity potential (1,4-dcbeq).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Egalitarian import run

print(run('terrestrialEcotoxicityPotential14Dcbeq', ImpactAssessment))

View source on Gitlab

ReCiPe 2016 Hierarchist

ReCiPe 2016 Hierarchist

These models characterise emissions and resource use according to the ReCiPe 2016 method, using a hierarchist perspective (see Huijbregts et al (2016), WMO (2011); Hayashi et al. (2006); De Schryver et al. (2011)).

Ecosystem damage ozone formation

Ecosystem damage ozone formation

The potential of emissions to contribute to low level smog (summer smog).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('ecosystemDamageOzoneFormation', ImpactAssessment))

View source on Gitlab

Fossil resource scarcity

Fossil resource scarcity

This model calculates the fossil resource scarcity.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('fossilResourceScarcity', ImpactAssessment))

View source on Gitlab

Freshwater aquatic ecotoxicity potential (1,4-DCBeq)

Freshwater aquatic ecotoxicity potential (1,4-DCBeq)

This model calculates the freshwater aquatic ecotoxicity potential (1,4-dcbeq).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('freshwaterAquaticEcotoxicityPotential14Dcbeq', ImpactAssessment))

View source on Gitlab

Freshwater eutrophication potential

Freshwater eutrophication potential

The potential of nutrient emissions to cause excessive growth of aquatic plants and algae in freshwater ecosystems (e.g. lakes, rivers, streams). Freshwater eutrophication is primarily linked to phosphorus as this tends to be the limiting nutrient in these ecosystems.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('freshwaterEutrophicationPotential', ImpactAssessment))

View source on Gitlab

Human carcinogenic toxicity

Human carcinogenic toxicity

The potential of emissions to contribute to the risk of increased incidence of cancer diseases.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('humanCarcinogenicToxicity', ImpactAssessment))

View source on Gitlab

Human damage ozone formation

Human damage ozone formation

The potential of emissions to contribute to the increase in tropospheric ozone population intake.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('humanDamageOzoneFormation', ImpactAssessment))

View source on Gitlab

Human non-carcinogenic toxicity

Human non-carcinogenic toxicity

The potential of emissions to contribute to the risk of increased incidence of non-cancer diseases.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('humanNonCarcinogenicToxicity', ImpactAssessment))

View source on Gitlab

Marine aquatic ecotoxicity potential (1,4-DCBeq)

Marine aquatic ecotoxicity potential (1,4-DCBeq)

This model calculates the marine aquatic ecotoxicity potential (1,4-dcbeq).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('marineAquaticEcotoxicityPotential14Dcbeq', ImpactAssessment))

View source on Gitlab

Marine eutrophication potential

Marine eutrophication potential

The potential of nutrient emissions to cause excessive growth of aquatic plants and algae in marine ecosystems (e.g. seas, oceans, estuaries). Marine eutrophication is primarily linked to nitrogen as this tends to be the limiting nutrient in these ecosystems.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('marineEutrophicationPotential', ImpactAssessment))

View source on Gitlab

Ozone depletion potential

Ozone depletion potential

The potential of emissions to cause thinning of the stratospheric ozone layer.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('ozoneDepletionPotential', ImpactAssessment))

View source on Gitlab

Terrestrial acidification potential

Terrestrial acidification potential

Changes in soil chemical properties following the deposition of nitrogen and sulfur in acidifying forms.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('terrestrialAcidificationPotential', ImpactAssessment))

View source on Gitlab

Terrestrial ecotoxicity potential (1,4-DCBeq)

Terrestrial ecotoxicity potential (1,4-DCBeq)

This model calculates the terrestrial ecotoxicity potential (1,4-dcbeq).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Hierarchist import run

print(run('terrestrialEcotoxicityPotential14Dcbeq', ImpactAssessment))

View source on Gitlab

ReCiPe 2016 Individualist

ReCiPe 2016 Individualist

These models characterise emissions and resource use according to the ReCiPe 2016 method, using an individualist perspective (see Huijbregts et al (2016), WMO (2011); Hayashi et al. (2006); De Schryver et al. (2011)).

Ecosystem damage ozone formation

Ecosystem damage ozone formation

The potential of emissions to contribute to low level smog (summer smog).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('ecosystemDamageOzoneFormation', ImpactAssessment))

View source on Gitlab

Fossil resource scarcity

Fossil resource scarcity

This model calculates the fossil resource scarcity.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('fossilResourceScarcity', ImpactAssessment))

View source on Gitlab

Freshwater aquatic ecotoxicity potential (1,4-DCBeq)

Freshwater aquatic ecotoxicity potential (1,4-DCBeq)

This model calculates the freshwater aquatic ecotoxicity potential (1,4-dcbeq).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('freshwaterAquaticEcotoxicityPotential14Dcbeq', ImpactAssessment))

View source on Gitlab

Freshwater eutrophication potential

Freshwater eutrophication potential

The potential of nutrient emissions to cause excessive growth of aquatic plants and algae in freshwater ecosystems (e.g. lakes, rivers, streams). Freshwater eutrophication is primarily linked to phosphorus as this tends to be the limiting nutrient in these ecosystems.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('freshwaterEutrophicationPotential', ImpactAssessment))

View source on Gitlab

Human carcinogenic toxicity

Human carcinogenic toxicity

The potential of emissions to contribute to the risk of increased incidence of cancer diseases.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('humanCarcinogenicToxicity', ImpactAssessment))

View source on Gitlab

Human damage ozone formation

Human damage ozone formation

The potential of emissions to contribute to the increase in tropospheric ozone population intake.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('humanDamageOzoneFormation', ImpactAssessment))

View source on Gitlab

Human non-carcinogenic toxicity

Human non-carcinogenic toxicity

The potential of emissions to contribute to the risk of increased incidence of non-cancer diseases.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('humanNonCarcinogenicToxicity', ImpactAssessment))

View source on Gitlab

Marine aquatic ecotoxicity potential (1,4-DCBeq)

Marine aquatic ecotoxicity potential (1,4-DCBeq)

This model calculates the marine aquatic ecotoxicity potential (1,4-dcbeq).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('marineAquaticEcotoxicityPotential14Dcbeq', ImpactAssessment))

View source on Gitlab

Marine eutrophication potential

Marine eutrophication potential

The potential of nutrient emissions to cause excessive growth of aquatic plants and algae in marine ecosystems (e.g. seas, oceans, estuaries). Marine eutrophication is primarily linked to nitrogen as this tends to be the limiting nutrient in these ecosystems.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('marineEutrophicationPotential', ImpactAssessment))

View source on Gitlab

Ozone depletion potential

Ozone depletion potential

The potential of emissions to cause thinning of the stratospheric ozone layer.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('ozoneDepletionPotential', ImpactAssessment))

View source on Gitlab

Terrestrial acidification potential

Terrestrial acidification potential

Changes in soil chemical properties following the deposition of nitrogen and sulfur in acidifying forms.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('terrestrialAcidificationPotential', ImpactAssessment))

View source on Gitlab

Terrestrial ecotoxicity potential (1,4-DCBeq)

Terrestrial ecotoxicity potential (1,4-DCBeq)

This model calculates the terrestrial ecotoxicity potential (1,4-dcbeq).

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.recipe2016Individualist import run

print(run('terrestrialEcotoxicityPotential14Dcbeq', ImpactAssessment))

View source on Gitlab

Scherer Pfister (2015)

Scherer Pfister (2015)

These models implement the phosphorus emissions models detailed in Scherer & Pfister (2015), many of which were originally developed in the SALCA guidelines.

N, erosion, soil flux

N, erosion, soil flux

Nitrogen losses from soil erosion.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.schererPfister2015 import run

print(run('nErosionSoilFlux', Cycle))

View source on Gitlab

P, erosion, soil flux

P, erosion, soil flux

Phosphorus losses from soil erosion.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.schererPfister2015 import run

print(run('pErosionSoilFlux', Cycle))

View source on Gitlab

P, to drainage water, soil flux

P, to drainage water, soil flux

The total amount of phosphorus which enters drainage water, including from phosphorus added in fertilizer, excreta, and residue, and from natural processes.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.schererPfister2015 import run

print(run('pToDrainageWaterSoilFlux', Cycle))

View source on Gitlab

P, to groundwater, soil flux

P, to groundwater, soil flux

The total amount of phosphorus which leaches from the soil into the groundwater, including from phosphorus added in fertilizer, excreta, and residue, and from background leaching due to natural processes.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.schererPfister2015 import run

print(run('pToGroundwaterSoilFlux', Cycle))

View source on Gitlab

P, to surface water, soil flux

P, to surface water, soil flux

The total amount of phosphorus runoff from the soil, including from phosphate added in fertilizer, excreta, and residue, and from background runoff due to natural processes.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.schererPfister2015 import run

print(run('pToSurfaceWaterSoilFlux', Cycle))

View source on Gitlab

Site

Site

These models are specific to Site.

Measurement Value

Measurement Value

This model calculates the value of the Measurement by taking an average from the min and max values.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.site import run

print(run('measurement.value', Site))

View source on Gitlab

Spatial

Spatial

Data are imputed from satellite or other geospatial datasets. Point data are point sampled. Polygon data are mean or mode sampled depending on the dataset. The dataset source is defined in the source field.

Aware Water Basin ID

Aware Water Basin ID

This model calculates the the AWARE water basin identifier.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('aware', Site))

View source on Gitlab

Clay content

Clay content

The clay content of the topsoil. Clay is defined as particles of less than 0.002mm in size.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('clayContent', Site))

View source on Gitlab

Cropping intensity

Cropping intensity

A metric of multi-cropping. If calculated from area, it is the maximum monthly growing area divided by the total cropland area.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('croppingIntensity', Site))

View source on Gitlab

Drainage Class

Drainage Class

A six level factor describing drainage class based on soil type, texture, soil phase, and terrain slope. Defined in the Harmonized World Soil Database.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('drainageClass', Site))

View source on Gitlab

Eco-Climate Zone

Eco-Climate Zone

A grouping areas based on their ecology and climate, defined by the JRC.

They approximataely map to the IPCC (2019) Climate Zones. Data are derived from Hiederer et al. (2010) Biofuels: A new methodology to estimate GHG emissions from global land use change, European Commission Joint Research Centre.

Value Climate Zone
1 Warm Temperate Moist
2 Warm Temperate Dry
3 Cool Temperate Moist
4 Cool Temperate Dry
5 Polar Moist
6 Polar Dry
7 Boreal Moist
8 Boreal Dry
9 Tropical Montane
10 Tropical Wet
11 Tropical Moist
12 Tropical Dry
Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('ecoClimateZone', Site))

View source on Gitlab

Ecoregion

Ecoregion

Ecoregions represent the original distribution of distinct assemblages of species and communities. There are 867 terrestrial ecoregions as defined by WWF.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('ecoregion', Site))

View source on Gitlab

Erodibility

Erodibility

The erodibility is a quantitative estimate of the vulnerability of the soil to erosion.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('erodibility', Site))

View source on Gitlab

Fallow correction

Fallow correction

The time/area under fallow relative to the time/area under both cultivation and fallow per year. If calculated from time based terms, it is "rotationDuration / (rotationDuration - longFallowPeriod)". If calculated from area, it is the total cropland area divided by the area harvested in a year (where total cropland area included areas under fallow. Fallow is defined as areas left fallow for more than a year but less than five years.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('fallowCorrection', Site))

View source on Gitlab

Heavy winter precipitation

Heavy winter precipitation

At least one winter month where precipitation exceeds 15 % of the annual average.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('heavyWinterPrecipitation', Site))

View source on Gitlab

Histosol

Histosol

Soils having organic material: 1. starting at the soil surface and having a thickness of ≥ 10 cm and directly overlying: a. ice, or b. continuous rock or technic hard material, or c. coarse fragments, the interstices of which are filled with organic material; or 2. starting ≤ 40 cm from the soil surface and having within ≤ 100 cm of the soil surface a combined thickness of either: a. ≥ 60 cm, if ≥ 75% (by volume) of the material consists of moss fibres; or b. ≥ 40 cm in other materials. The area of the Site occupied by histosols can be specified as a percentage.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('histosol', Site))

View source on Gitlab

Nutrient loss to aquatic environment

Nutrient loss to aquatic environment

The percentage of nutrients reaching the aquatic environment. Defined in Scherer & Pfister (2015).

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('nutrientLossToAquaticEnvironment', Site))

View source on Gitlab

Organic carbon (per kg soil)

Organic carbon (per kg soil)

The concentration of organic carbon in the soil.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('organicCarbonPerKgSoil', Site))

View source on Gitlab

Phosphorus (per kg soil)

Phosphorus (per kg soil)

The concentration of phosphorous in the soil.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('phosphorusPerKgSoil', Site))

View source on Gitlab

Potential evapotranspiration (annual)

Potential evapotranspiration (annual)

The total annual potential evapotranspiration, expressed in mm / year.

Must be associated with at least 1 Cycle that has an endDate after 1958 and before 2021.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('potentialEvapotranspirationAnnual', Site))

View source on Gitlab

Potential evapotranspiration (long-term annual mean)

Potential evapotranspiration (long-term annual mean)

The long-term average annual potential evapotranspiration, averaged over all years in the recent climate record.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('potentialEvapotranspirationLongTermAnnualMean', Site))

View source on Gitlab

Rainfall (annual)

Rainfall (annual)

The total annual rainfall, expressed in mm / year.

Must be associated with at least 1 Cycle that has an endDate after 1979 and before 2020.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('rainfallAnnual', Site))

View source on Gitlab

Rainfall (long-term annual mean)

Rainfall (long-term annual mean)

The long-term average annual rainfall on the Site. A mean of all available years in the recent climate record.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('rainfallLongTermAnnualMean', Site))

View source on Gitlab

Region

Region

The model calculates the finest scale GADM region possible, moving from gadm level 5 (for example, a village) to GADM level 0 (Country).

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('region', Site))

View source on Gitlab

Sand content

Sand content

The sand content of the topsoil. Sand is defined as particles of 2.0-0.05mm in size.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('sandContent', Site))

View source on Gitlab

Silt content

Silt content

The silt content of the topsoil. Silt is defined as particles of 0.05mm to 0.002mm in size.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('siltContent', Site))

View source on Gitlab

Slope

Slope

This model calculates the slope.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('slope', Site))

View source on Gitlab

Slope length

Slope length

This model calculates the slope length.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('slopeLength', Site))

View source on Gitlab

Soil pH

Soil pH

The pH of the topsoil (the negative log of the hydrogen ion concentration in moles per litre). Add the depth interval and further information about the measurement using the appropriate schema fields.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('soilPh', Site))

View source on Gitlab

Temperature (annual)

Temperature (annual)

The annual air temperature, averaged over each day in a year.

Must be associated with at least 1 Cycle that has an endDate after 1979 and before 2020.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('temperatureAnnual', Site))

View source on Gitlab

Temperature (long-term annual mean)

Temperature (long-term annual mean)

The long-term average annual air temperature, averaged over each day in the year, averaged over all years in the recent climate record.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('temperatureLongTermAnnualMean', Site))

View source on Gitlab

Total nitrogen (per kg soil)

Total nitrogen (per kg soil)

The sum of organic and mineral nitrogen in the soil.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('totalNitrogenPerKgSoil', Site))

View source on Gitlab

Water depth

Water depth

The depth of a water body.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.spatial import run

print(run('waterDepth', Site))

View source on Gitlab

Stehfest Bouwman (2006)

Stehfest Bouwman (2006)

These models calculate the emissions due to the use of fertilizer using the regression model detailed in Stehfest & Bouwman (2006).

N2O, to air, crop residue decomposition, direct

N2O, to air, crop residue decomposition, direct

Nitrous oxide emissions to air from crop residue decomposition.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('n2OToAirCropResidueDecompositionDirect', Cycle))

View source on Gitlab

N2O, to air, excreta, direct

N2O, to air, excreta, direct

Nitrous oxide emissions to air from animal excreta.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('n2OToAirExcretaDirect', Cycle))

View source on Gitlab

N2O, to air, inorganic fertilizer, direct

N2O, to air, inorganic fertilizer, direct

Nitrous oxide emissions to air from nitrification and denitrification of inorganic fertilizer.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('n2OToAirInorganicFertilizerDirect', Cycle))

View source on Gitlab

N2O, to air, organic fertilizer, direct

N2O, to air, organic fertilizer, direct

Nitrous oxide emissions to air from nitrification and denitrification of organic fertilizer.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('n2OToAirOrganicFertilizerDirect', Cycle))

View source on Gitlab

N2O, to air, soil flux

N2O, to air, soil flux

The total amount of nitrous oxide emissions to air from the soil, including from nitrogen added in fertilizer, excreta, and residue, and from natural background processes.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('n2OToAirSoilFlux', Cycle))

View source on Gitlab

NOx, to air, crop residue decomposition

NOx, to air, crop residue decomposition

Nitrogen oxides emissions to air, from crop residue decomposition.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('noxToAirCropResidueDecomposition', Cycle))

View source on Gitlab

NOx, to air, excreta

NOx, to air, excreta

Nitrogen oxides emissions to air, from animal excreta.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('noxToAirExcreta', Cycle))

View source on Gitlab

NOx, to air, inorganic fertilizer

NOx, to air, inorganic fertilizer

Nitrogen oxides emissions to air, from inorganic fertilizer nitrification and denitrification.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('noxToAirInorganicFertilizer', Cycle))

View source on Gitlab

NOx, to air, organic fertilizer

NOx, to air, organic fertilizer

Nitrogen oxides emissions to air, from organic fertilizer nitrification and denitrification.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('noxToAirOrganicFertilizer', Cycle))

View source on Gitlab

NOx, to air, soil flux

NOx, to air, soil flux

The total amount of nitrous oxide emissions to air from the soil, including from nitrogen added in fertilizer, excreta, and residue, and from natural background processes.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006 import run

print(run('noxToAirSoilFlux', Cycle))

View source on Gitlab

Stehfest Bouwman (2006) GIS Implementation

Stehfest Bouwman (2006) GIS Implementation

These models calculate the direct emissions due to the use of fertilizer, by creating a country-average version of the Stehfest & Bouwman (2006) model using GIS software.

NOx, to air, crop residue decomposition

NOx, to air, crop residue decomposition

Nitrogen oxides emissions to air, from crop residue decomposition.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006GisImplementation import run

print(run('noxToAirCropResidueDecomposition', Cycle))

View source on Gitlab

NOx, to air, excreta

NOx, to air, excreta

Nitrogen oxides emissions to air, from animal excreta.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006GisImplementation import run

print(run('noxToAirExcreta', Cycle))

View source on Gitlab

NOx, to air, inorganic fertilizer

NOx, to air, inorganic fertilizer

Nitrogen oxides emissions to air, from inorganic fertilizer nitrification and denitrification.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006GisImplementation import run

print(run('noxToAirInorganicFertilizer', Cycle))

View source on Gitlab

NOx, to air, organic fertilizer

NOx, to air, organic fertilizer

Nitrogen oxides emissions to air, from organic fertilizer nitrification and denitrification.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006GisImplementation import run

print(run('noxToAirOrganicFertilizer', Cycle))

View source on Gitlab

NOx, to air, soil flux

NOx, to air, soil flux

The total amount of nitrous oxide emissions to air from the soil, including from nitrogen added in fertilizer, excreta, and residue, and from natural background processes.

Returns

Returns

Requirements

Requirements

Lookup used

Lookup used

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.stehfestBouwman2006GisImplementation import run

print(run('noxToAirSoilFlux', Cycle))

View source on Gitlab

Transformation

Transformation

These models are specific to Transformation.

Transformation Post Checks

Transformation Post Checks

List of models to run after any other model on a Transformation.

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.transformation import post_checks

transformation = post_checks.run(transformation)
print(transformation)

View source on Gitlab

Product value

Product value

This model calculates the value of every Product by taking the value of the Input with the same term. Note: this model also substract Emissions for Input with units = kg N.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.transformation import run

print(run(Transformation))

View source on Gitlab

Webb et al (2012) and Sintermann et al (2012)

Webb et al (2012) and Sintermann et al (2012)

These models calculate the emissions due to the addition of organic fertilizer based on a compilation of emissions factors from Webb et al (2012) and Sintermann et al (2012). The methodology for compiling these emissions is detailed in Poore & Nemecek (2018).

NH3, to air, organic fertilizer

NH3, to air, organic fertilizer

Ammonia emissions to air, from organic fertilizer volatilization.

Returns

Returns

Requirements

Requirements

Usage

Usage

  1. Install the library: pip install hestia_earth.models
  2. Import the library and run the model:
from hestia_earth.models.webbEtAl2012AndSintermannEtAl2012 import run

print(run('nh3ToAirOrganicFertilizer', Cycle))

View source on Gitlab