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eflookup

This package supports the look-up of emissions factors used to compute emissions from wildland fires. Multiple sets of EF are supported, including:

  • FCCS specific EFs, based on Prichard, S.J. and O'Neill, S. In prep. Wildland fire EFs in North America: summary of existing data, measurement needs and management applications. International Journal of Wildland Fire.
  • FEPS style EFs
  • Crop-specific EFs from Pouliot 2017 and McCarty 2011

This software is provided for research purposes only. It's output may not accurately reflect observed data due to numerous reasons. Data are provisional; use at own risk.

Python 2 and 3 Support

This package was originally developed to support python 2.7, but has since been refactored to support 3.5. Attempts to support both 2.7 and 3.5 have been made but are not guaranteed.

Development

Clone Repo

Via ssh:

git clone git@github.com:pnwairfire/eflookup.git

or http:

git clone https://github.com/pnwairfire/eflookup.git

Install Dependencies

Run the following to install dependencies:

pip install -r requirements.txt

Run the following to install packages required for development and testing:

pip install -r requirements-test.txt
pip install -r requirements-dev.txt

Notes

pip issues

If you get an error like AttributeError: 'NoneType' object has no attribute 'skip_requirements_regex, it means you need in upgrade pip. One way to do so is with the following:

pip install --upgrade pip

Setup Environment

To import eflookup in development, you'll have to add the repo root directory to the search path.

Running tests

Use pytest:

py.test
py.test test/unit/eflookup/fccs2ef/test_lookup.py

You can also use the --collect-only option to see a list of all tests.

py.test --collect-only

See pytest for more information about

Installing

Installing With pip

First, install pip (with sudo if necessary):

apt-get install python-pip

Then, to install, for example, v4.0.11, use the following (with sudo if necessary):

pip install --extra-index https://pypi.airfire.org/simple eflookup==4.0.11

See the Development > Install Dependencies > Notes section, above, for notes on resolving pip and gdal issues.

Usage:

Using the Python Package

eflookup.lookup.BasicEFLookup

BasicEFLookup is look-up object for arbitrary, phase specific emission factors. Instantiated with a nested dict of phase-specific EFS:

>>> EFS = {
    'flaming': {
        'CH4': 0.003819999999999997,
        'CO': 0.07179999999999997,
        'VOC': 0.017341999999999996
    },
    'residual': {
        'NOx': 0.000908,
        'PM10': 0.01962576,
    },
    'smoldering': {
        'NH3': 0.00341056,
    }
}
>>> from eflookup.lookup import BasicEFLookup
>>> lu = BasicEFLookup(EFS)

And then access the EFs with get:

>>> lu.get()
{
    'flaming': {
        'CH4': 0.003819999999999997,
        'CO': 0.07179999999999997,
        'VOC': 0.017341999999999996
    },
    'residual': {
        'NOx': 0.000908,
        'PM10': 0.01962576
    },
    'smoldering': {
        'NH3': 0.00341056
    }
}
>>> lu.get(phase='flaming')
{
    'CH4': 0.003819999999999997,
    'CO': 0.07179999999999997,
    'VOC': 0.017341999999999996
}
>>> lu.get(phase='flaming', species='CO')
0.07179999999999997

or []:

>>> lu
{
    'flaming': {
        'CH4': 0.003819999999999997,
        'CO': 0.07179999999999997,
        'VOC': 0.017341999999999996
    },
    'residual': {
        'NOx': 0.000908,
        'PM10': 0.01962576
    },
    'smoldering': {
        'NH3': 0.00341056
    }
}
>>> lu['flaming']
{
    'CH4': 0.003819999999999997,
    'CO': 0.07179999999999997,
    'VOC': 0.017341999999999996
}
>>> lu['flaming']['CO']
0.07179999999999997

The one difference is that using brackets will result in KeyErrors for invalid keys, whereas 'get' returns None if any of the arguments are invalid. For example:

>>> lu.get(phase='flaminsdfg')
>>> lu['flaminsdfg']
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
KeyError: 'flaminsdfg'

eflookup.fepsef.FepsEFLookup

There's only one look-up class for FEPS style EFs. It has one option: to include or exclude HAPS (hazardous air pollutants) chemical species; the default is to exclude them. The following example includes them, but the usage is identical if they are excluded.

First, import and instantiate:

>>> from eflookup.fepsef import FepsEFLookup
>>> lu = FepsEFLookup(include_haps=True)

Then, get all EFs

>>> lu.get()
{
    'flaming': {
        'CH4': 0.003819999999999997,
        'CO': 0.07179999999999997,
        ...
        'hap_85018': 2.5e-06
    },
    'residual': {
        'CH4': 0.009868000000000002,
        'CO': 0.21011999999999997,
        ...
        'hap_85018': 2.5e-06
    },
    'smoldering': {
        'CH4': 0.009868000000000002,
        'CO': 0.21011999999999997,
        ...
        'hap_85018': 2.5e-06
    }
}

Or, get specifically the flaming EFs

>>> lu.get(phase='flaming')
{
    'CH4': 0.003819999999999997,
    'CO': 0.07179999999999997,
    ...
    'hap_85018': 2.5e-06
}

Or, get an EF for a specific species

>>> lu.get(phase='flaming', species='CO')
0.07179999999999997

As with BasicEFLookup, you can use []

>>> lu['flaming']
{
    'CH4': 0.003819999999999997,
    'CO': 0.07179999999999997,
    ...
    'hap_85018': 2.5e-06
}

>>> lu['flaming']['CO']
0.07179999999999997

eflookup.fccs2ef

There are four look-up classes to choose from, depending on whether you're keying off of FCCS id or cover type: Fccs2Ef, Fccs2SeraEf, CoverType2Ef, CoverType2SeraEf. Also, each class can be instantiated either for wild fires or Rx burns. The following example illustrates use of Fccs2Ef for an Rx burn, but the usage of CoverType2Ef is identical other than passing in a cover type id instead of an FCCS id, and the usage for wild fires is identical other than setting is_rx to False when instantiating the look-up object.

Fccs2SeraEf (and CoverType2SeraEf) try to lookup the species (pollutant) in the SERA data. If the pollutant is not found, then the original Fccs2Ef (or CoverType2Ef) class is used.
Optionally, the "stat" can be specified:
EF = emissions factor (this is the default if not specified)
SD = standard deviation
n = count
all: returns EF, SD, and n
Example usage:

>>> from eflookup.fccs2ef import Fccs2SeraEf
>>> lu = Fccs2SeraEf(52)
>>> lu.get(phase="flaming",fuel_category="woody fuels",fuel_sub_category="1-hr fuels",species="PM2.5")
13.5
>>> lu.get(phase="flaming",fuel_category="woody fuels",fuel_sub_category="1-hr fuels",species="PM2.5", stat="all")
{'SD': 5.18, 'n': 21, 'EF': 13.5}
>>> lu.get(phase="flaming",fuel_category="woody fuels",fuel_sub_category="1-hr fuels",species="PM2.5", stat="SD")
5.18
>>>
>>>
>>> from eflookup.fccs2ef import CoverType2SeraEf
>>> lu = CoverType2SeraEf(118)
>>> lu.get(phase="flaming",fuel_category="woody fuels",fuel_sub_category="1-hr fuels",species="PM2.5", stat="SD")
5.18
>>> lu.get(phase="flaming",fuel_category="woody fuels",fuel_sub_category="1-hr fuels",species="PM2.5")
13.5
>>> lu.get(phase="flaming",fuel_category="woody fuels",fuel_sub_category="1-hr fuels",species="PM2.5", stat="all")
{'SD': 5.18, 'n': 21, 'EF': 13.5}

This next case shows a species that is not in the SERA data. When looking up values in Fccs2SeraEf, the is_rx setting comes into play. It can be set using set_is_rx(). The default for Fccs2SeraEf is prescribed fire. To obtain wildfire emission factors, set rx to False. Note: the default for Fccs2Ef is wildfire.

>>>
>>> lu.get(phase="flaming",fuel_category="woody fuels",fuel_sub_category="1-hr fuels",species="C2H2")
0.312
>>> lu.set_is_rx(False)
>>> lu.get(phase="flaming",fuel_category="woody fuels",fuel_sub_category="1-hr fuels",species="C2H2")
0.24

First import and instantiate

>>> from eflookup.fccs2ef import Fccs2Ef
>>> lu = Fccs2Ef(4, is_rx=True)

then get the EF for a given fuel category, fuel sub-category, phase, and species.

>>> lu.get(phase="flaming", fuel_category="nonwoody",
        fuel_sub_category="primary live", species="PM2.5")
17.57

If no corresponding EF, None is returned

>>> lu.get(phase="residual", fuel_category="nonwoody",
        fuel_sub_category="primary live", species="PM2.5")

Note that fccs2ef does not support using __getitem__ brackets instead of get.

eflookup.Crops2Ef

Crop emission factors are determined based on the underlying crop type. A modified crop ID is derived from the sum of 9000 and the CDL ID.

First, import and instantiate:

>>> from eflookup.crops2ef import Crops2Ef
>>> lu = Crops2Ef(9001)

Now get the EF for the specified pollutant:

>>> lu.get('CO')
0.05305007535

Using the Executables

fepsef

To get all EFs:

$ fepsef
{"smoldering": {"CO2": 1.39308, "CO": 0.21011999999999997, "PM10": 0.01962576, "VOC": 0.04902680000000001, "SO2": 0.00098, "CH4": 0.009868000000000002, "NH3": 0.00341056, "NOx": 0.000908, "PM2.5": 0.016632}, "flaming": {"CO2": 1.6497, "CO": 0.07179999999999997, "PM10": 0.008590399999999998, "VOC": 0.017341999999999996, "SO2": 0.00098, "CH4": 0.003819999999999997, "NH3": 0.0012063999999999998, "NOx": 0.002420000000000001, "PM2.5": 0.007280000000000002}, "residual": {"CO2": 1.39308, "CO": 0.21011999999999997, "PM10": 0.01962576, "VOC": 0.04902680000000001, "SO2": 0.00098, "CH4": 0.009868000000000002, "NH3": 0.00341056, "NOx": 0.000908, "PM2.5": 0.016632}}

To get all EFs for a particular phase:

$ fepsef -p flaming
{"flaming": {"CO2": 1.6497, "CO": 0.07179999999999997, "PM10": 0.008590399999999998, "VOC": 0.017341999999999996, "SO2": 0.00098, "CH4": 0.003819999999999997, "NH3": 0.0012063999999999998, "NOx": 0.002420000000000001, "PM2.5": 0.007280000000000002}}

To get the EF for a particular chemical species

$ fepsef -p flaming -s CO
{"flaming": {"CO": 0.07179999999999997}}

Any call to fepsef can be made with '-i'/'--include-haps-polutants' option, which as the name implies, will include the HAPS (hazardous air pollutants) chemical species. For example:

$ fepsef --include-haps-polutants -p flaming
{"flaming": {"hap_75070": 0.000204125, "hap_120127": 2.5e-06, "hap_203338": 1.2999999999999998e-06, "hap_108883": 0.00028412500000000004, "hap_74873": 6.41625e-05, "hap_50328": 7.4e-07, "hap_192972": 1.33e-06, "hap_85018": 2.5e-06, "hap_206440": 3.365e-06, "hap_1330207": 0.000121, "hap_195197": 1.95e-06, "hap_56832736": 2.57e-06, "CH4": 0.003819999999999997, "hap_26714181": 4.1149999999999996e-06, "PM2.5": 0.007280000000000002, "hap_2381217": 4.525000000000001e-06, "hap_463581": 2.67e-07, "CO": 0.07179999999999997, "hap_129000": 4.6449999999999996e-06, "SO2": 0.00098, "NOx": 0.002420000000000001, "NH3": 0.0012063999999999998, "hap_247": 1.48e-06, "hap_106990": 0.00020250000000000002, "hap_56553": 3.1e-06, "CO2": 1.6497, "hap_198550": 4.28e-07, "PM10": 0.008590399999999998, "hap_50000": 0.0012875, "VOC": 0.017341999999999996, "hap_110543": 8.20125e-06, "hap_248": 3.95e-06, "hap_218019": 3.1e-06, "hap_207089": 1.2999999999999998e-06, "hap_193395": 1.705e-06, "hap_191242": 2.5400000000000002e-06, "hap_71432": 0.0005625, "hap_107028": 0.000212}}

The -i option will have no effect if you're specifying a non-HAP species:

$ fepsef -p flaming -s CO
{"flaming": {"CO": 0.07179999999999997}}
$ fepsef -i -p flaming -s CO
{"flaming": {"CO": 0.07179999999999997}}

But the -i option must be used if you specify a HAP species:

$ fepsef -p flaming -s hap_191242
{"flaming": {"hap_191242": null}}
$ fepsef -p flaming -s hap_191242 -i
{"flaming": {"hap_191242": 2.5400000000000002e-06}}

Note that, when using the script, the resulting JSON data's nested depth is the same regardless of the input specificity. The format is always like the following:

{
    <PHASE>: {
        <SPECIES>: ...
    }
}

fccs2seraef & fccs2ef & ct2ef

Use FCCS id with '''fccs2seraef''' and '''fccs2ef'''. Use Cover Type with '''ct2ef'''. The following example illustrates use of '''fccs2ef''' for a wild fire (the default fire type). Usage of '''fccs2seraef''' is identical to '''fccs2ef'''. As with the classes described above, the usage of '''ct2ef''' is identical other than passing in a cover type id instead of an FCCS id. Using the scripts for Rx burns is also idential other than having to add the option '--rx'

To see the script's usage, you can use the '-h' options:

fccs2ef -h

The script takes an FCCS id, phase, fuel_category, fuel_sub_category, and species the associated EF value. For example:

$ ./bin/fccs2ef 52 flaming 'woody fuels' '1-hr fuels' PM2.5
26.0

These examples show the difference between fccs2ef and fccs2seraef. Note: the default for fccs2ef is wildfire, the default for fccs2seraef is prescribed. So, now there is no option for setting fccs2seraef to wildfire when using the executable. To get wildfire emissions factors using Fccs2SeraEf, use the python module directly and set set_is_rx(False) as described above.

$ fccs2ef 52 flaming 'woody fuels' '1-hr fuels' C2H2
0.24
(wildfire)
$ fccs2ef 52 flaming 'woody fuels' '1-hr fuels' C2H2 --rx
0.312
(prescribed)
$ fccs2seraef 52 flaming 'woody fuels' '1-hr fuels' C2H2
0.312
(prescribed)
$ fccs2seraef 52 flaming 'woody fuels' '1-hr fuels' C2H2 --rx
0.312
(prescribed, --rx option is redundant in this case)

Invoking the Executables In Perl

The following example illustrates using fccs2ef, but could be easily modified to work for the other executables.

Setup

To use the code below, you'll need JSON, which you can install with cpanm

sudo cpanm --install JSON::Parse

To try it in a perl console, you can either use:

perl -d -e 1

or you can use Devel::Repl, which you can install with

sudo cpanm --install TAP::Harness::Env
sudo cpanm --install MooseX::Object::Pluggable
sudo cpanm --install Devel::REPL
sudo cpanm --install Devel::REPL::Script

and invoked with

re.pl

The Code

Once you're in the console (or in your perl script), you can do something like the following:

use JSON;
use Data::Dumper;
my $j = `fccs2ef 13`;
my $p = decode_json($j);

At this point $p should be a perl hash object, and you should be able to do something like:

print Dumper($p{"flaming"}{"CH4"})
...

(Note: I [Joel], couldn't get decode_json to work on my Mac, so take the above code with a grain of salt.)

About

This package supports the look-up of emissions factors used to compute emissions from wildland fires.

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