adapt EmissionFators so that it reades splitted csv files incl. tests

co2calculator/constants.py

@@ -17,26 +17,20 @@
 class HeatingFuel(enum.Enum):
     """Enum for heating fuel types"""
 
-    HEAT_PUMP_AIR = "heat_pump_air"
-    HEAT_PUMP_GROUND = "heat_pump_ground"
-    HEAT_PUMP_WATER = "heat_pump_water"
-    LIQUID_GAS = "liquid_gas"
     OIL = "oil"
-    PELLETS = "pellets"
-    SOLAR = "solar"
-    WOODCHIPS = "woodchips"
-    ELECTRICITY = "electricity"
-    GAS = "gas"
     COAL = "coal"
-    DISTRICT_HEATING = "district_heating"
+    GAS = "gas"
+    WOOD_PELLETS = "wood pellets"
+    WOOD_CHIPS = "wood chips"
+    LPG = "liquid_gas"
 
 
 @enum.unique
 class ElectricityFuel(str, enum.Enum):
     """Enum for electricity fuel types"""
 
-    GERMAN_ENERGY_MIX = "german_energy_mix"
-    SOLAR = "solar"
+    PRODUCTION_FUEL_MIX = "production fuel mix"
+    RESIDUAL_FUEL_MIX = "residual fuel mix"
 
 
 @enum.unique

co2calculator/data/emission_factors_heating.csv

@@ -0,0 +1,7 @@
+,country_code,category,source,name,unit,fuel_type,co2e_unit,co2e
+0,global,heating,"UK, Department for Business, Energy & Industrial Strategy",coal (domestic),kWh,coal,kg/kWh,0.35
+1,global,heating,"UK, Department for Business, Energy & Industrial Strategy",natural gas,kWh,gas,kg/kWh,0.18
+2,global,heating,"UK, Department for Business, Energy & Industrial Strategy",LPG,kWh,liquid_gas,kg/kWh,0.21
+3,global,heating,"UK, Department for Business, Energy & Industrial Strategy",fuel oil,kWh,oil,kg/kWh,0.27
+4,global,heating,"UK, Department for Business, Energy & Industrial Strategy",wood pellets,kWh,wood pellets,kg/kWh,0.01074
+5,global,heating,"UK, Department for Business, Energy & Industrial Strategy",wood chips,kWh,wood chips,kg/kWh,0.01074

co2calculator/data/emission_factors_transport.csv

@@ -0,0 +1,61 @@
+,country_code,category,subcategory,source,name,unit,size_class,range,fuel_type,co2e_unit,co2e,seating
+1,global,transport,bus,mobitool,Stadtbus (9m),P.km,small,local,cng,kg/P.km,0.1464,
+2,global,transport,bus,mobitool,Stadtbus (13m),P.km,medium,local,cng,kg/P.km,0.1034,
+3,global,transport,bus,mobitool,Stadtbus (18m),P.km,large,local,cng,kg/P.km,0.0709,
+4,global,transport,bus,mobitool,Stadtbus (13m),P.km,average,local,cng,kg/P.km,0.1034,
+5,global,transport,bus,mobitool,Stadtbus (13m),P.km,average,local,diesel,kg/P.km,0.1338,
+6,global,transport,bus,mobitool,Stadtbus (13m),P.km,medium,local,diesel,kg/P.km,0.1338,
+7,global,transport,bus,mobitool,Stadtbus (18m),P.km,large,local,diesel,kg/P.km,0.0905,
+8,global,transport,bus,mobitool,Stadtbus (9m),P.km,small,local,diesel,kg/P.km,0.1716,
+9,global,transport,bus,mobitool,Reisebus,P.km,small,long-distance,diesel,kg/P.km,0.0465,
+10,global,transport,bus,mobitool,Trolleybus,P.km,average,local,electric,kg/P.km,0.0296,
+11,global,transport,car,mobitool,Personenkraftwagen,P.km,large,,cng,kg/P.km,0.1528,
+12,global,transport,car,mobitool,Personenkraftwagen,P.km,small,,cng,kg/P.km,0.1033,
+13,global,transport,car,mobitool,Personenkraftwagen,P.km,medium,,cng,kg/P.km,0.1233,
+14,global,transport,car,mobitool,Personenkraftwagen,P.km,average,,average,kg/P.km,0.1864,
+15,global,transport,car,mobitool,Personenkraftwagen,P.km,average,,gasoline,kg/P.km,0.186,
+16,global,transport,car,mobitool,Personenkraftwagen,P.km,small,,gasoline,kg/P.km,0.1297,
+17,global,transport,car,mobitool,Personenkraftwagen,P.km,medium,,gasoline,kg/P.km,0.1506,
+18,global,transport,car,mobitool,Personenkraftwagen,P.km,large,,gasoline,kg/P.km,0.2004,
+19,global,transport,car,mobitool,Personenkraftwagen,P.km,average,,diesel,kg/P.km,0.189,
+20,global,transport,car,mobitool,Personenkraftwagen,P.km,small,,diesel,kg/P.km,0.1109,
+21,global,transport,car,mobitool,Personenkraftwagen,P.km,medium,,diesel,kg/P.km,0.1322,
+22,global,transport,car,mobitool,Personenkraftwagen,P.km,large,,diesel,kg/P.km,0.1757,
+23,global,transport,train,mobitool,Eisenbahn,P.km,,long-distance,,kg/P.km,0.0068,
+24,global,transport,train,mobitool,Eisenbahn,P.km,,local,,kg/P.km,0.008,
+25,global,transport,train,mobitool,Eisenbahn,P.km,,average,,kg/P.km,0.007,
+26,global,transport,tram,mobitool,Strassenbahn,P.km,,local,electric,kg/P.km,0.0428,
+27,DE,transport,train,mobitool,Bahn Deutschland,P.km,,average,,kg/P.km,0.0408,
+28,FR,transport,train,mobitool,Bahn Frankreich,P.km,,average,,kg/P.km,0.0125,
+29,IT,transport,train,mobitool,Bahn Italien,P.km,,average,,kg/P.km,0.0747,
+30,AT,transport,train,mobitool,Bahn �sterreich,P.km,,average,,kg/P.km,0.0151,
+31,global,transport,car,mobitool,Personenkraftwagen,P.km,large,,hybrid,kg/P.km,0.1785,
+32,global,transport,car,mobitool,Personenkraftwagen,P.km,small,,hybrid,kg/P.km,0.1182,
+33,global,transport,car,mobitool,Personenkraftwagen,P.km,medium,,hybrid,kg/P.km,0.1397,
+34,global,transport,car,mobitool,Personenkraftwagen,P.km,average,,hybrid,kg/P.km,0.1397,
+35,global,transport,car,mobitool,Personenkraftwagen,P.km,average,,plug-in_hybrid,kg/P.km,0.1278,
+36,global,transport,car,mobitool,Personenkraftwagen,P.km,small,,plug-in_hybrid,kg/P.km,0.0799,
+37,global,transport,car,mobitool,Personenkraftwagen,P.km,medium,,plug-in_hybrid,kg/P.km,0.1278,
+38,global,transport,car,mobitool,Personenkraftwagen,P.km,large,,plug-in_hybrid,kg/P.km,0.1718,
+39,global,transport,car,mobitool,Personenkraftwagen,P.km,average,,electric,kg/P.km,0.0898,
+40,global,transport,car,mobitool,Personenkraftwagen,P.km,small,,electric,kg/P.km,0.0599,
+41,global,transport,car,mobitool,Personenkraftwagen,P.km,medium,,electric,kg/P.km,0.0697,
+42,global,transport,car,mobitool,Personenkraftwagen,P.km,large,,electric,kg/P.km,0.091,
+43,global,transport,plane,mobitool,Flugzeug,P.km,,average,kerosine,kg/P.km,0.263,average
+44,global,transport,plane,mobitool,Flugzeug,P.km,,short-haul,kerosine,kg/P.km,0.3192,average
+45,global,transport,plane,mobitool,Flugzeug,P.km,,short-haul,kerosine,kg/P.km,0.2918,economy_class
+46,global,transport,plane,mobitool,Flugzeug,P.km,,short-haul,kerosine,kg/P.km,0.4488,business_class
+47,global,transport,plane,mobitool,Flugzeug,P.km,,long-haul,kerosine,kg/P.km,0.2372,average
+48,global,transport,plane,mobitool,Flugzeug,P.km,,long-haul,kerosine,kg/P.km,0.1895,economy_class
+49,global,transport,plane,mobitool,Flugzeug,P.km,,long-haul,kerosine,kg/P.km,0.3914,business_class
+50,global,transport,plane,mobitool,Flugzeug,P.km,,long-haul,kerosine,kg/P.km,0.6031,first_class
+51,global,transport,ferry,"UK, Department for Business, Energy & Industrial Strategy","Ferry, Average",P.km,,,,kg/P.km,0.11286,average
+52,global,transport,motorbike,mobitool,Motorrad,P.km,small,,,kg/P.km,0.121,
+53,global,transport,motorbike,mobitool,Motorrad,P.km,medium,,,kg/P.km,0.1548,
+54,global,transport,motorbike,mobitool,Motorrad,P.km,large,,,kg/P.km,0.2036,
+55,global,transport,motorbike,mobitool,Motorrad,P.km,average,,,kg/P.km,0.1636,
+56,global,transport,bicycle,mobitool,Fahrrad,P.km,,,,kg/P.km,0.0056,
+57,global,transport,pedelec,mobitool,E-Bike,P.km,,,,kg/P.km,0.0113,
+58,global,transport,ferry,"UK, Department for Business, Energy & Industrial Strategy","Ferry, Foot passenger",P.km,,,,kg/P.km,0.01874,foot_passenger
+59,global,transport,ferry,"UK, Department for Business, Energy & Industrial Strategy","Ferry, Car passenger",P.km,,,,kg/P.km,0.12952,car_passenger
+60,global,transport,bus,mobitool,Reisebus,P.km,large,long-distance,diesel,kg/P.km,0.0474,

co2calculator/data_handlers.py

@@ -12,40 +12,74 @@
 class EmissionFactors:
     def __init__(self):
         """Init"""
-        self.emission_factors = pd.read_csv(f"{script_path}/data/emission_factors.csv")
-        self.column_names = self.emission_factors.columns
+        self.electricity = pd.read_csv(
+            f"{script_path}/data/emission_factors_electricity.csv"
+        )
+        self.heating = pd.read_csv(f"{script_path}/data/emission_factors_heating.csv")
+        self.transport = pd.read_csv(
+            f"{script_path}/data/emission_factors_transport.csv"
+        )
+
+        self.databases = {
+            "electricity": self.electricity,
+            "heating": self.heating,
+            "transport": self.transport,
+        }
 
     def get(self, parameters: dict):
         """
-        Returns factors from the database
+        Returns factor from the database
         :param parameters:
         :type parameters:
         :return:
         :rtype:
         """
-        selected_factors = self.emission_factors
+        assert (
+            "category" in parameters
+        ), "Please provide a category for the emission factor."
+        assert parameters["category"] in [
+            "electricity",
+            "heating",
+            "transport",
+        ], "Please provide a valid emission factor category."
 
-        for k, v in parameters.items():
-            # TODO: shortterm hack to make it work until occupancy is removed from emission factors
-            if not isinstance(v, int):
-                v = str(v.value)
-            if v is None or k not in self.column_names:
-                continue
+        # Search suitable emission factors
+        selected_factors = self._search_factors(parameters, parameters["category"])
 
-            selected_factors_new = selected_factors[selected_factors[k] == v]
-            selected_factors = selected_factors_new
-            if selected_factors_new.empty:
-                raise EmissionFactorNotFound(
-                    "No suitable emission factor found in database. Please adapt your query."
-                )
-
-        if len(selected_factors) > 1:
+        if len(selected_factors) == 0:
+            raise EmissionFactorNotFound(
+                "No suitable emission factor found in database. Please adapt your query."
+            )
+        elif len(selected_factors) > 1:
             raise EmissionFactorNotFound(
                 f"{len(selected_factors)} emission factors found. Please provide more specific selection criteria."
             )
         else:
             return selected_factors["co2e"].values[0]
 
+    def _search_factors(self, parameters, emission_category):
+        """
+        Searches for factors in the database
+        :param parameters: Search parameters
+        :type parameters: dict
+        :param emission_category: Category of emission factors
+        :type emission_category: str
+        """
+        # Select table for emission category
+        candidates = self.databases[emission_category]
+        for k, v in parameters.items():
+            # TODO: shortterm hack to make it work until occupancy is removed from emission factors
+            if not isinstance(v, int):
+                v = str(v.value)
+            if v is None or k not in candidates.columns:
+                continue
+            new_candidates = candidates[candidates[k] == v]
+            if new_candidates.empty:
+                return new_candidates
+            candidates = new_candidates
+
+        return candidates
+
 
 class Airports:
     def __init__(self):

co2calculator/parameters.py

@@ -16,12 +16,14 @@
     ElectricityFuel,
     HeatingFuel,
     Unit,
+    EmissionCategory,
 )
 from typing import Union
 
 
 class TrainEmissionParameters(BaseModel):
 
+    category: TransportationMode = EmissionCategory.TRANSPORT
     subcategory: TransportationMode = TransportationMode.TRAIN
     fuel_type: Union[TrainFuel, str] = TrainFuel.AVERAGE
     range: Union[BusTrainRange, str] = BusTrainRange.LONG_DISTANCE
@@ -51,6 +53,7 @@ def check_size(cls, v):
 
 class TramEmissionParameters(BaseModel):
 
+    category: TransportationMode = EmissionCategory.TRANSPORT
     subcategory: TransportationMode = TransportationMode.TRAM
     size: Union[Size, str] = Size.AVERAGE
 
@@ -64,6 +67,7 @@ def check_size(cls, v):
 
 class CarEmissionParameters(BaseModel):
 
+    category: TransportationMode = EmissionCategory.TRANSPORT
     subcategory: TransportationMode = TransportationMode.CAR
     fuel_type: Union[CarFuel, str] = CarFuel.AVERAGE
     size: Union[Size, str] = Size.AVERAGE
@@ -86,6 +90,7 @@ def check_size(cls, v, values):
 
 class PlaneEmissionParameters(BaseModel):
 
+    category: TransportationMode = EmissionCategory.TRANSPORT
     subcategory: TransportationMode = TransportationMode.PLANE
     seating: Union[FlightClass, str] = FlightClass.AVERAGE
     range: Union[FlightRange, str]
@@ -108,6 +113,7 @@ def check_seating(cls, v):
 
 class FerryEmissionParameters(BaseModel):
 
+    category: TransportationMode = EmissionCategory.TRANSPORT
     subcategory: TransportationMode = TransportationMode.FERRY
     seating: Union[FerryClass, str] = FerryClass.AVERAGE
 
@@ -121,6 +127,7 @@ def check_seating(cls, v):
 
 class BusEmissionParameters(BaseModel):
 
+    category: TransportationMode = EmissionCategory.TRANSPORT
     subcategory: TransportationMode = TransportationMode.BUS
     fuel_type: Union[BusFuel, str] = BusFuel.DIESEL
     size: Union[Size, str] = Size.AVERAGE
@@ -151,6 +158,7 @@ def check_range(cls, v):
 
 class MotorbikeEmissionParameters(BaseModel):
 
+    category: TransportationMode = EmissionCategory.TRANSPORT
     subcategory: TransportationMode = TransportationMode.MOTORBIKE
     size: Union[Size, str] = Size.AVERAGE
 
@@ -164,7 +172,8 @@ def check_size(cls, v):
 
 class ElectricityEmissionParameters(BaseModel):
 
-    fuel_type: Union[Size, str] = ElectricityFuel.GERMAN_ENERGY_MIX
+    category: TransportationMode = EmissionCategory.ELECTRICITY
+    fuel_type: Union[Size, str] = ElectricityFuel.PRODUCTION_FUEL_MIX
 
     @validator("fuel_type", allow_reuse=True)
     def check_fueltype(cls, v):
@@ -176,6 +185,7 @@ def check_fueltype(cls, v):
 
 class HeatingEmissionParameters(BaseModel):
 
+    category: TransportationMode = EmissionCategory.HEATING
     fuel_type: Union[Size, str] = HeatingFuel.GAS
 
     @validator("fuel_type", allow_reuse=True)

data/emission_factors.csv

@@ -1,4 +1,4 @@
-,country_code,category,subcategory,source,name,unit,size_class,range,fuel_type,co2e_unit,co2e,seating
+,country_code,category,subcategory,source,name,unit,size,range,fuel_type,co2e_unit,co2e,seating
 0,global,heating,,"UK, Department for Business, Energy & Industrial Strategy",coal (domestic),kWh,,,coal,kg/kWh,0.35,
 1,global,heating,,"UK, Department for Business, Energy & Industrial Strategy",natural gas,kWh,,,gas,kg/kWh,0.18,
 2,global,heating,,"UK, Department for Business, Energy & Industrial Strategy",LPG,kWh,,,liquid_gas,kg/kWh,0.21,

docs/businesstrips.rst

@@ -0,0 +1,30 @@
+==============
+Business trips
+==============
+
+.. toctree::
+   :maxdepth: 2
+   :caption: See also:
+   :titlesonly:
+   :includehidden:
+
+   calculate/distances
+   calculate/transport_modes
+
+The calculation of emissions from business trips is currently supported for the following modes of transport:
+
+* car
+* bus
+* train
+* plane
+* ferry
+
+The user must specify either the distance of a trip or the location of departure and destination.
+The distance (in km) may be used, when the user has the direct information of the distance travelled, e.g., from the speedometer of a car.
+In other cases, the distance can be calculated from the given locations, see :ref:`Distance calculations <Distance calculations>`.
+With the boolean paramter ``roundtrip``, users can indicate whether a trip was a roundtrip, in which case the distance wil be doubled.
+
+Aside of the mode of transport, the user should provide the specifica of the trip, depending on the mode of transport
+(see :doc'Transportation modes <calculate/transport_modes>' :doc:`Emission factors <calculate/emission_factors>`).
+
+.. autofunction:: co2calculator.calculate.calc_co2_businesstrip

tests/functional/test_data_code_compliance.py

@@ -0,0 +1,43 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""Check if values in the csv files are compliant with enums"""
+
+import pytest
+
+from co2calculator import HeatingFuel, emission_factors, ElectricityFuel
+
+
+@pytest.mark.parametrize(
+    "column_name,enum,emission_category",
+    [
+        pytest.param(
+            "fuel_type", HeatingFuel, "heating", id="fuel_type: 'HeatingFuel'"
+        ),
+        pytest.param(
+            "fuel_type",
+            ElectricityFuel,
+            "electricity",
+            id="fuel_type: 'ElectricityFuel'",
+        ),
+    ],
+)
+def test_enums_heating(column_name, enum, emission_category):
+    """Test whether all values in the csv files are present in the enums"""
+
+    # Get unique values of the size column
+    column_values = emission_factors.databases[emission_category][column_name].unique()
+
+    # Check if all column values are present in the enum
+    for v in column_values:
+        # skip is v is nan
+        if str(v) == "nan":
+            continue
+        assert v in (
+            item.value for item in enum
+        ), f"'{v}' in column '{column_name}' of csv file is not contained in enum '{enum}'."
+
+    # Check if all values in the enum are present in the emission factor csv file
+    for item in enum:
+        assert (
+            item.value in column_values
+        ), f"Column '{enum}' in emission_factors.csv does not contain value '{item.value}' of enum 'Size'"

tests/unit/test_data_handlers.py

@@ -0,0 +1,14 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""Test data handlers"""
+
+from co2calculator.data_handlers import EmissionFactors
+import pandas as pd
+
+
+def test_load_emission_factors():
+    """Test if the emission factors are loaded correctly"""
+    emission_factors = EmissionFactors()
+    assert isinstance(emission_factors.heating, pd.DataFrame)
+    assert isinstance(emission_factors.electricity, pd.DataFrame)
+    assert isinstance(emission_factors.transport, pd.DataFrame)