barronh

__doc__ = """
INTEGRATE CMAQ Columns
======================

---
    author: Barron H. Henderson
    last-updated: 2026-07-17
---

Integrate columns from CMAQ using GRIDCRO2D, METCRO3D, and CONC files.

barronh

__doc__ = """
Requires pycno, pandas, matplotlib, xarray and the airnowcompare.py gist.

pip install pycno pyproj pandas matplotlib xarray
wget -N https://gist.githubusercontent.com/barronh/945df1b465905b0f5454258b317cee1b/raw/airnowcompare.py
"""
import airnowcompare
import pycno
import pandas as pd
import matplotlib.animation as ani

barronh

#!/usr/bin/python
__doc__ = """
Relies on NASA credentials in .netrc and tested with
harmony-py==1.3.4
pandas==2.3.1
"""
import logging
from harmony import BBox, Client, Collection, Request, Environment
import os
import pandas as pd

barronh

def xmlcmap2cmap(xmlcmap):
    import numpy as np
    import matplotlib.colors as mc
    inf = np.inf
    nan = np.nan
    for elem in xmlcmap:
        if elem.tag == 'Entries':
            los = []
            his = []
            rgbs = []

barronh

#!/usr/bin/env bash
INPATH=${1?Required input CMAQ File}
if [[ ${INPATH} == "-h" || ${INPATH} == "--help" ]]; then
   echo $0 [-h] INPATH INVAR [OUTPATH]
   echo "Convert CMAQ IOAPI meta data to SRS and create raster using gdal_translate"
   echo "  -h --help: print this help menu"
   echo "  INPATH   : path to CMAQ input/output file"
   echo "  INVAR    : name of variable in INPATH"
   echo "  OUTPATH  : Path for output raster (default: INPATH_INVAR.tif)"
   exit

barronh

barronh

def get_epacmapnorm(spc, freq):
    """
    Arguments
    ---------
    spc : str
        choices 'pm25' or 'o3'
    freq : str
        choices '1h', '24h' (pm-only), '8h' (o3-only), 'mda8' (o3-only)

    Returns

barronh

Overview

---

title: CMAQ Dust Emulator
author: Barron H. Henderson
organization: US EPA
last updated: 2025-11-03

---

github.com/USEPA/CMAQ/emis/emis/DUST_EMIS.F routines and functions converted

barronh

County and Population Coverage of Monitors

The incomplete spatial coverage of monitors is a good motivation for data fusion. Monitors cover less than 30% of US counties, but more like 70% of the population. This is because dense populations often coincide with sources of polution and, therefore, are better monitored. The precise coverage of monitoring data depends on the period of interest. For example, ozone monitors are often not depolyed during winter.

barronh

"""
# Convert a CMAQ IOAPI File to a GeoTiff

---
    author: Barron H. Henderson
    last updated: 2025-09-05
---

Demonstrates converting a CMAQ file to a GeoTiff. GeoTiff is useful for ArcGIS or QGIS.