RUFAS.routines.EEE.emissions module

RUFAS.routines.EEE.emissions.FINAL_DAY_SLICE_START = -1

These are constants for calculating the embedded emissions of synthetic nitrogen and phosphorus fertilizer. Their units are in kg CO2e / kg N and kg CO2e / kg P, respectively. The nitrogen and phosphorus constants reference IPCC 2021, GWP 100, the potassium constant references BASF’s Eco-efficiency analysis tool.

class RUFAS.routines.EEE.emissions.EmissionsEstimator

Bases: object

Estimates emissions associated with purchased feeds used for animals.

Attributes

imInputManager

An instance of the InputManager class.

omOutputManager

An instance of the OutputManager class.

crop_species_to_purchased_feed_iddict[str, list[str]]

A dictionary mapping crop species to their corresponding RuFaS feed IDs.

__init__() → None

estimate_emissions() → None

_calculate_purchased_feed_emissions(homegrown_feeds: list[dict[str, Any]]) → None

_gather_homegrown_feeds_and_fertilizer_apps() → dict[str, list[dict[str, Any]]]

Gathers the yields that were harvested and fertilizer applications that were applied in the last 365 days of the simulation.

_gather_ration_feed_totals() → dict[str, float]

Collects totals of feeds from rations given to animals in the last 365 days of the simulation and collapses them into single set of numbers.

_transform_outputs_to_list_of_dicts(data: dict[str, Any]) → list[dict[str, Any]]

Transforms dictionary of lists collected from the Output Manager into list of dictionaries.

Examples

>>> a = {'one': {'values': [1, 2, 3]}, 'two': {'values': [4, 5, 6]}}
>>> _transform_outputs_to_list_of_dicts(a)
[{'one': 1, 'two': 4}, {'one': 2, 'two': 5}, {'one': 3, 'two': 6}]

_calculate_actual_purchased_feeds(homegrown_feeds: list[dict[str, Any]], purchased_feeds: dict[str, float]) → dict[str, float]

Calculates the difference between the purchased feeds and feeds grown on the farm.

_calculate_total_homegrown_feed_amounts_by_crop_type(homegrown_feeds: list[dict[str, Any]]) → dict[str, float]

Calculates the total amount of each crop species grown on the farm.

_calculate_actual_purchased_feed_emissions(actual_purchased_feeds: dict[str, float]) → tuple[dict[str, float], dict[str, float]]

Calculates the emissions from feeds that were actually purchased during the simulation.

_get_feed_emissions_data(county_code: int, feed_emissions_data: dict[str, list[float]]) → dict[str, float]

Grabs the appropriate list of emissions for purchased feeds for the location of the simulation.

_calculate_homegrown_feed_emissions(homegrown_feeds: list[dict[str, Any]], fertilizer_applications: list[dict[str, Any]], manure_applications: list[dict[str, Any]], manure_requests: list[dict[str, Any]]) → None

Calculates the emissions associated with feeds grown on the farm.

_collect_target_soil_characteristics(field_names: list[str]) → dict[str, dict[str, Any]]

Collects the emissions and soil carbon characteristics used to calculate farm-grown feed emissions.

_calculate_emissions_by_field(field_name: str, feeds_grown: list[dict[str, Any]], field_emissions: dict[str, float], manure_applications: dict[str, float], manure_requests: dict[str, float], fertilizer_applications_data: list[dict[str, Any]]) → list[dict[str, Any]]

Partitions emissions from the field where crops/feeds were grown to those crops.

_partition_applied_crop_fertilizer_emissions(fertilizer_application: dict[str, float], applied_crops: list[dict[str, Any]]) → None

Partitions synthetic emissions from fertilizer applications to crop(s) whose planting and harvesting dates encompass the fertilizer application date.

_filter_results(filters: dict[str, Any], date_cutoff: date, year_key: str, day_key: str) → list[dict[str, Any]]

This method help with filtering data based on the timeframe provided.

Parameters

filters: dict[str, Any]

A filter to collect the desired data from OutputManager.

date_cutoff: datetime

Date before which all data collected from the Output Manager is filtered out.

year_key: str

How the key is named for the year data retrieved from OM.

day_key: str

How the key is named for the day data retrieved from OM.

Returns

list[dict[str, Any]]

Filtered result of the retrieved data.

_aggregate_data(operations: list[dict[str, Any]], all_fields: list[str], nutrients: list[str]) → dict[str, dict[str, float]]

Aggregate nutrient data for different types of applications (fertilizer, manure, etc.).

Parameters

operationslist[dict[str, Any]]

A list of application dictionaries. Each dictionary contains the field name and nutrient amounts. Example: {“field_name”: “Field1”, “nitrogen”: 50.0, “phosphorus”: 20.0}

all_fieldslist[str]

A list of field names to aggregate data for, usually combining fields with crops and fields with applications.

nutrientslist[str]

A list of nutrient keys to aggregate (e.g., [“nitrogen”, “phosphorus”, “potassium”]).

Returns

dict

A dictionary where keys are field names and values are dictionaries of aggregated nutrient values.

_apply_fertilizer_to_next_crop(fertilizer_application: dict[str, Any], sorted_crops: list[dict[str, Any]], fertilizer_application_date: date) → bool

Applies fertilizer to the next available crop after harvest and before the next planting. Returns True if fertilizer was applied, False otherwise.

_extract_applied_crops(sorted_crops: list[dict[str, Any]], fertilizer_application_date: date) → list[dict[str, Any]]

Extracts a list of crops that had fertilizer applied to them between their planting and harvesting dates.

Parameters

sorted_cropslist[dict[str, Any]]

The list of crops in the field sorted by planting date.

fertilizer_application_datedate

The date of the fertilizer applciation.

Returns

list[dict[str, Any]]

A list of the crops whose planting and harvesting dates encompass the fertilizer application date.

_soil_data_update(filters: dict[str, dict[str, Any]]) → dict[str, int | Literal[0]]

This method will update the soil data update according to data extracted using the filters.

Parameters

filters: dict[str, dict[str, Any]]

A dictionary of filters to retrieve data from the OM.

Return

dict[str, int | Literal[0]]

The updated soil data.