Metadata-Version: 2.1
Name: transport-co2
Version: 0.2.0
Summary: Library to calculate CO2 (equivalent) emissions for a given transport trip.
Home-page: https://github.com/maasglobal/sustainable-mobility-api
Author: Brylie Christopher Oxley, Markus Schepke
Author-email: brylie.oxley@maas.global, markus.schepke@maas.global
License: MIT
Project-URL: Documentation, https://github.com/maasglobal/sustainable-mobility-api/tree/master/estimator/README.md
Project-URL: Source, https://github.com/maasglobal/sustainable-mobility-api/tree/master/estimator
Project-URL: Tracker, https://github.com/maasglobal/sustainable-mobility-api/issues
Keywords: transport,co2,carbon,sustainability
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown


# Transport CO2

Calculate CO2 (equivalent) emissions for a given transport trip and provide a simple interpretation of the result.

Install from [PyPI](https://pypi.org/project/transport-co2/) via
```bash
pip install transport-co2
```

## Usage examples

You can list the currently supported modes like so:
```python
from transport_co2 import Mode
list(Mode)
```
Each `Mode` allows you to estimate the CO2 emission per passenger for a journey given its distance (in km):
```python
Mode.SMALL_CAR.estimate_co2(distance_in_km=100)
# 11200.0
```
This estimate is based on an average occupancy (in this example `1.5`). You can also specify the occupancy:
```python
Mode.SMALL_CAR.estimate_co2(distance_in_km=100, occupancy=3)
# 5600.0
```
If you don't want to work with the `Mode` enum, you can instead work with the `estimate_co2` function:
```python
from transport_co2 import estimate_co2
estimate_co2(mode="light_rail", distance_in_km=100)
# 1400.0
```
You can also specify the occupancy like above:
```python
estimate_co2(mode="light_rail", distance_in_km=100, occupancy=250)
# 873.6
```

## Running unit tests
In order to run the unit tests for this project:

1. activate the virtual environment with `pipenv shell`
2. run `pytest`

## Goals

This project is intended to be used to help raise awareness about the cost of transportation choices, so people can make informed decisions.

## Initial focus

We are initially focused on ground (road and rail) transport, as it is the most significant source on transport greenhouse gas emissions.

## API Design

This library intends to provide:

- a statistical estimate of greenhouse gase emissions given information about a trip (origin/destination, mode, and/or distance)
- a simple interpretation of the statistical emissions estimate, in terms such as "high" or "low"

## Research

The carbon estimates produced by this model may be based on the following resources. A full description of the model, including data sources, will be provided as the library takes shape.

- European Environment Agency [CO2 emissions from passenger transport](https://www.eea.europa.eu/media/infographics/co2-emissions-from-passenger-transport/view)

Further improvements to the model may come from other sources, such as the following.

- IPCC AR5 [Chapter 8 - Transport](https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_chapter8.pdf)
- Wikipedia: [Environmental impact of transport](https://en.wikipedia.org/wiki/Environmental_impact_of_transport)

## Attribution

Initial package structure forked from [navdeep-G/setup.py](https://github.com/navdeep-G/setup.py).

Friendly nod to [jamiebull1/transport-carbon](https://github.com/jamiebull1/transport-carbon).


