------------------------------------------------------------------------------------------------------------------------
This dataset contains the 10 Hz observations and the python codes that were used to calculate methane emissions from
natural gas vehicles in China in the article "Methane Emissions from Natural Gas Vehicles in China" by Da Pan, Lei Tao,
Kang Sun, Levi M. Golston, David J. Miller, Tong Zhu, Yue Qin, Yan Zhang, Denise L. Mauzerall, Mark, A. Zondlo.

The dataset contains:
1. Calculate_ER.py
2. 0610_10Hz_with_ratios_1s_final.csv
3. 0611_10Hz_with_ratios_1s_final.csv
4. 0612_10Hz_with_ratios_1s_final.csv
5. 0610_NGV_encounter.csv
6. 0611_NGV_encounter.csv
7. 0612_NGV_encounter.csv
8. Gaussian_puff.py
9. README.txt

All the files should be placed together in order for the codes to work.
------------------------------------------------------File 1------------------------------------------------------------
"Calculate_ER.py" is the source code for calculation of enhancement ratios.

The code was made to run with Python 2.7. Three packages are needed:
1. Numpy
2. Scipy
3. Pandas

These packages are included in Anaconda Python distribution which can be downloaded freely from
(https://www.anaconda.com/). The typical install time is 30 min.

The code has been tested on Windows 10, with an Anaconda2-2019.10-Windows-x86_64 distribution and on MacOS High Sierra
with an Anaconda2-2019.10-MacOSX-x86-64 distribution.

The code loads file 2-4, which contain raw CH4, CO2, NH3 observations, and pre-calculated enhancement ratios and
determination coefficients (R^2), and file 5-7, which contain start times and durations of NGV encounters during our
field campaign. There are three major sections in the code. The first one calculates enhancement ratios, and the typical
run time is one day. The second and the third sections can run without executing the first section. The second section
identifies plumes related to NGVs. The typical runtime for section 2 is 30 - 60 s. The third section calculates mean
ERs and their uncertainty. The typical runtime is <10 s.
------------------------------------------------------File 2-4----------------------------------------------------------
For each of the file, there are 11 columns corresponding to:

TS: Time stamps of data collection time (local time, format: mm/dd/yyyy HH:MM:SS)
TSCO2: 10 Hz carbon dioxide (CO2) observations in ppmv
TSCH4: 10 Hz methane (CH4) observations in ppmv
TSNH3: 10 Hz ammonia (NH3) observations in ppbv
CO2peak: 10 Hz local CO2 enhancement peaks in ppmv
CH4peak: 10 Hz local CH4 enhancement peaks in ppmv
NH3peak: 10 Hz local NH3 enhancement peaks in ppbv
ratio: CH4:CO2 enhancement ratios calculated as orthogonal regression slope between CH4 and CO2 in ppmv/ppmv
ratio_nh3: NH3:CO2 enhancement ratios calculated as orthogonal regression slope between NH3 and CO2 in ppmv/ppmv
coeff: determination coefficients (R^2) of CH4 and CO2 regression
coeff_nh3: determination coefficients (R^2) of NH3 and CO2 regression
------------------------------------------------------File 5-7----------------------------------------------------------
For each of the file, there are 5 columns corresponding to:

Hour of the encounter
Minute of the encounter
Second of the encounter
Duration of the encounter in second
Type of the NGV (0=bus, 1=taxi)
------------------------------------------------------File 8------------------------------------------------------------
File 8 contains the code for the Random Walk Gaussian Puff Model, which does not require additional package to run.