compute-indicator-GRE-2-2-exceedance-days-air-pollution.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3478617d-5758-4d08-8e2a-3cd77b92ecc9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import io, sys, os, datetime, requests\n",
    "from collections import defaultdict\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import netCDF4\n",
    "import shapely\n",
    "import boto3\n",
    "import geopandas as gpd\n",
    "import io"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a312e99e-7585-4d7e-8801-6c492fbaa1dd",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "Requirement already satisfied: notebook-shim>=0.1.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from nbclassic~=0.2->jupyterlab>=3->geemap) (0.1.0)\n",
      "Requirement already satisfied: notebook<7 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from nbclassic~=0.2->jupyterlab>=3->geemap) (6.4.11)\n",
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      "Requirement already satisfied: bleach in /srv/conda/envs/notebook/lib/python3.8/site-packages (from nbconvert>=6.4.4->jupyter-server~=1.4->jupyterlab>=3->geemap) (5.0.0)\n",
      "Requirement already satisfied: nbclient>=0.5.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from nbconvert>=6.4.4->jupyter-server~=1.4->jupyterlab>=3->geemap) (0.5.13)\n",
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      "Requirement already satisfied: jupyterlab-pygments in /srv/conda/envs/notebook/lib/python3.8/site-packages (from nbconvert>=6.4.4->jupyter-server~=1.4->jupyterlab>=3->geemap) (0.2.2)\n",
      "Requirement already satisfied: fastjsonschema in /srv/conda/envs/notebook/lib/python3.8/site-packages (from nbformat>=4.2.0->ipywidgets->ipyfilechooser>=0.6.0->geemap) (2.15.3)\n",
      "Requirement already satisfied: ptyprocess>=0.5 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from pexpect>4.3->ipython>=4.0.0->ipywidgets->ipyfilechooser>=0.6.0->geemap) (0.7.0)\n",
      "Requirement already satisfied: wcwidth in /srv/conda/envs/notebook/lib/python3.8/site-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=4.0.0->ipywidgets->ipyfilechooser>=0.6.0->geemap) (0.2.5)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from pyasn1-modules>=0.2.1->google-auth>=1.4.1->earthengine-api>=0.1.304->geemap) (0.4.8)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from requests->folium>=0.11.0->geemap) (2021.10.8)\n",
      "Requirement already satisfied: charset-normalizer~=2.0.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from requests->folium>=0.11.0->geemap) (2.0.12)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from requests->folium>=0.11.0->geemap) (1.26.9)\n",
      "Collecting plotly>=5.2.2\n",
      "  Using cached plotly-5.10.0-py2.py3-none-any.whl (15.2 MB)\n",
      "Requirement already satisfied: tenacity>=6.2.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from plotly>=5.2.2->sankee>=0.1.0->geemap) (8.0.1)\n",
      "Requirement already satisfied: whitebox in /srv/conda/envs/notebook/lib/python3.8/site-packages (from whiteboxgui>=0.6.0->geemap) (2.1.2)\n",
      "Requirement already satisfied: argon2-cffi-bindings in /srv/conda/envs/notebook/lib/python3.8/site-packages (from argon2-cffi->jupyter-server~=1.4->jupyterlab>=3->geemap) (21.2.0)\n",
      "Requirement already satisfied: cffi>=1.0.1 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from argon2-cffi-bindings->argon2-cffi->jupyter-server~=1.4->jupyterlab>=3->geemap) (1.15.0)\n",
      "Requirement already satisfied: pycparser in /srv/conda/envs/notebook/lib/python3.8/site-packages (from cffi>=1.0.1->argon2-cffi-bindings->argon2-cffi->jupyter-server~=1.4->jupyterlab>=3->geemap) (2.21)\n",
      "Requirement already satisfied: pytz>=2015.7 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from babel->jupyterlab-server~=2.10->jupyterlab>=3->geemap) (2022.1)\n",
      "Requirement already satisfied: webencodings in /srv/conda/envs/notebook/lib/python3.8/site-packages (from bleach->nbconvert>=6.4.4->jupyter-server~=1.4->jupyterlab>=3->geemap) (0.5.1)\n",
      "Requirement already satisfied: filelock in /srv/conda/envs/notebook/lib/python3.8/site-packages (from gdown->geemap) (3.6.0)\n",
      "Requirement already satisfied: tqdm in /srv/conda/envs/notebook/lib/python3.8/site-packages (from gdown->geemap) (4.64.0)\n",
      "Requirement already satisfied: click in /srv/conda/envs/notebook/lib/python3.8/site-packages (from geocoder->geemap) (8.0.4)\n",
      "Collecting ratelim\n",
      "  Using cached ratelim-0.1.6-py2.py3-none-any.whl (4.0 kB)\n",
      "Requirement already satisfied: google-cloud-core<3.0dev,>=1.6.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from google-cloud-storage->earthengine-api>=0.1.304->geemap) (2.2.2)\n",
      "Requirement already satisfied: google-resumable-media>=1.3.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from google-cloud-storage->earthengine-api>=0.1.304->geemap) (2.1.0)\n",
      "Requirement already satisfied: google-crc32c<2.0dev,>=1.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from google-resumable-media>=1.3.0->google-cloud-storage->earthengine-api>=0.1.304->geemap) (1.1.2)\n",
      "Requirement already satisfied: cycler>=0.10 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from matplotlib->geemap) (0.11.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from matplotlib->geemap) (4.33.3)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from matplotlib->geemap) (1.4.2)\n",
      "Requirement already satisfied: PySocks!=1.5.7,>=1.5.6 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from requests->folium>=0.11.0->geemap) (1.7.1)\n",
      "Requirement already satisfied: executing in /srv/conda/envs/notebook/lib/python3.8/site-packages (from stack-data->ipython>=4.0.0->ipywidgets->ipyfilechooser>=0.6.0->geemap) (0.8.3)\n",
      "Requirement already satisfied: asttokens in /srv/conda/envs/notebook/lib/python3.8/site-packages (from stack-data->ipython>=4.0.0->ipywidgets->ipyfilechooser>=0.6.0->geemap) (2.0.5)\n",
      "Requirement already satisfied: pure-eval in /srv/conda/envs/notebook/lib/python3.8/site-packages (from stack-data->ipython>=4.0.0->ipywidgets->ipyfilechooser>=0.6.0->geemap) (0.2.2)\n",
      "Installing collected packages: ratelim, plotly, logzero, branca, scooby, sankee, ipyleaflet, geocoder, geeadd, ffmpeg-python, ee-extra, geemap\n",
      "  Attempting uninstall: branca\n",
      "    Found existing installation: branca 0.4.2\n",
      "    Uninstalling branca-0.4.2:\n",
      "      Successfully uninstalled branca-0.4.2\n",
      "  Attempting uninstall: ipyleaflet\n",
      "    Found existing installation: ipyleaflet 0.16.0\n",
      "    Uninstalling ipyleaflet-0.16.0:\n",
      "      Successfully uninstalled ipyleaflet-0.16.0\n",
      "Successfully installed branca-0.5.0 ee-extra-0.0.14 ffmpeg-python-0.2.0 geeadd-0.5.6 geemap-0.16.7 geocoder-1.38.1 ipyleaflet-0.17.1 logzero-1.7.0 plotly-5.10.0 ratelim-0.1.6 sankee-0.2.0 scooby-0.6.0\n"
     ]
    }
   ],
   "source": [
    "#!{sys.executable} -m pip install pip earthengine-api\n",
    "#!{sys.executable} -m pip install pip geemap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5901237b-55df-454c-a304-332c3cefdb34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p>To authorize access needed by Earth Engine, open the following\n",
       "        URL in a web browser and follow the instructions:</p>\n",
       "        <p><a href=https://code.earthengine.google.com/client-auth?scopes=https%3A//www.googleapis.com/auth/earthengine%20https%3A//www.googleapis.com/auth/devstorage.full_control&request_id=fn0KxhgvClSZm8s_8dZUvqhGeVIIpTDS-kXmrPp7UTs&tc=M6YLDhw2O-Nxf2UTpgcQPlkGoLWJ-5X5AZW1267Dzo4&cc=0RzbrYq8tUTDOST_qz7Y8-e4PKbztU8f-U-QSio0jPQ>https://code.earthengine.google.com/client-auth?scopes=https%3A//www.googleapis.com/auth/earthengine%20https%3A//www.googleapis.com/auth/devstorage.full_control&request_id=fn0KxhgvClSZm8s_8dZUvqhGeVIIpTDS-kXmrPp7UTs&tc=M6YLDhw2O-Nxf2UTpgcQPlkGoLWJ-5X5AZW1267Dzo4&cc=0RzbrYq8tUTDOST_qz7Y8-e4PKbztU8f-U-QSio0jPQ</a></p>\n",
       "        <p>The authorization workflow will generate a code, which you should paste in the box below.</p>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter verification code:  4/1AdQt8qjVXI1_LE69C1deNGNPWm3kkKLUOoTp5mljRYMmVGwUeVh-WTgptm8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Successfully saved authorization token.\n"
     ]
    }
   ],
   "source": [
    "import geemap\n",
    "import ee\n",
    "#ee.Authenticate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0728d5e4-6883-44f9-b4b0-0b7ec5fb2e94",
   "metadata": {},
   "outputs": [],
   "source": [
    "ee.Initialize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a8aec839-08f7-40f9-aba2-1274cf652046",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "SPECIES_INFO = {\n",
    "    'no2': {\n",
    "        'name': 'nitrogen dioxide',\n",
    "        'molar_mass': 46.0055,\n",
    "        'cams_unit': 'kg/kg',\n",
    "        'who_threshold': 25.0,\n",
    "    },\n",
    "    'so2': {\n",
    "        'name': 'sulfur dioxide',\n",
    "        'molar_mass': 64.066,\n",
    "        'cams_unit': 'kg/kg',\n",
    "        'who_threshold': 40.0\n",
    "    },\n",
    "    'o3': {    # Ozone thresholds are based on 8-hour average, not 24-hour.\n",
    "               # We use averages at 9am, noon, 3pm to get a 9-hour average at peak O3 production.\n",
    "        'name': 'ozone',\n",
    "        'molar_mass': 48.0,\n",
    "        'cams_unit': 'kg/kg',\n",
    "        'who_threshold': 100.0\n",
    "    },\n",
    "    'pm25': {\n",
    "        'name': 'fine particulate matter',\n",
    "        'cams_unit': 'kg/m^3',\n",
    "        'who_threshold': 15.0\n",
    "    },\n",
    "    'pm10': {\n",
    "        'name': 'coarse particulate matter',\n",
    "        'cams_unit': 'kg/m^3',\n",
    "        'who_threshold': 45.0\n",
    "    },\n",
    "    'co': {\n",
    "        'name': 'carbon monoxide',\n",
    "        'molar_mass': 28.01,\n",
    "        'cams_unit': 'kg/kg',\n",
    "        'who_threshold': 4000.0\n",
    "    }\n",
    "}\n",
    "\n",
    "datasets = defaultdict(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a1f274a5-2ac6-4ce4-a837-d553bb3d1fe4",
   "metadata": {},
   "outputs": [],
   "source": [
    "ACCESS_KEY = \"AKIA4GK7IHHC5RCMFKEG\"\n",
    "SECRET_KEY = \"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\"\n",
    "s3client = boto3.client(\n",
    "    service_name='s3',\n",
    "    aws_access_key_id=ACCESS_KEY,\n",
    "    aws_secret_access_key=SECRET_KEY\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5a200364-f586-4ea7-aa36-4e3574b33d4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "bucket = 'cities-cities4forests'\n",
    "for species in SPECIES_INFO:\n",
    "    local_filename = 'cams-eac4_{}_sfc_2020.nc'.format(species)\n",
    "    f = s3client.download_file(bucket, 'data/air_pollution/cams/cams-eac4_{}_sfc_2020.nc'.format(species), local_filename)\n",
    "    datasets[species] = xr.open_dataset(local_filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "580deb58-0a63-4319-8a4e-d6949aefa74e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define directory\n",
    "out_dir = os.getcwd()\n",
    "aws_s3_dir = \"https://cities-cities4forests.s3.eu-west-3.amazonaws.com/data\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "14b55112-91dc-4237-ab25-3674c73b0b04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city_name</th>\n",
       "      <th>geo_name</th>\n",
       "      <th>aoi_boundary_name</th>\n",
       "      <th>units_boundary_name</th>\n",
       "      <th>city_boundary_name</th>\n",
       "      <th>country_code</th>\n",
       "      <th>geo_level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Salvador</td>\n",
       "      <td>BRA-Salvador</td>\n",
       "      <td>ADM4union</td>\n",
       "      <td>ADM4</td>\n",
       "      <td>BRA-Salvador-ADM4</td>\n",
       "      <td>BRA</td>\n",
       "      <td>ADM4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bukavu</td>\n",
       "      <td>COD-Bukavu</td>\n",
       "      <td>ADM3union</td>\n",
       "      <td>ADM3</td>\n",
       "      <td>COD-Bukavu-ADM2</td>\n",
       "      <td>COD</td>\n",
       "      <td>ADM2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Uvira</td>\n",
       "      <td>COD-Uvira</td>\n",
       "      <td>ADM3union</td>\n",
       "      <td>ADM3</td>\n",
       "      <td>COD-Uvira-ADM3</td>\n",
       "      <td>COD</td>\n",
       "      <td>ADM3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Brazzaville</td>\n",
       "      <td>COG-Brazzaville</td>\n",
       "      <td>ADM4union</td>\n",
       "      <td>ADM4</td>\n",
       "      <td>COG-Brazzaville-ADM4</td>\n",
       "      <td>COG</td>\n",
       "      <td>ADM4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Barranquilla</td>\n",
       "      <td>COL-Barranquilla</td>\n",
       "      <td>ADM4union</td>\n",
       "      <td>ADM4</td>\n",
       "      <td>COL-Barranquilla-ADM4</td>\n",
       "      <td>COL</td>\n",
       "      <td>ADM4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Addis_Ababa</td>\n",
       "      <td>ETH-Addis_Ababa</td>\n",
       "      <td>ADM4union</td>\n",
       "      <td>ADM4</td>\n",
       "      <td>ETH-Addis_Ababa-ADM4</td>\n",
       "      <td>ETH</td>\n",
       "      <td>ADM4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Dire_Dawa</td>\n",
       "      <td>ETH-Dire_Dawa</td>\n",
       "      <td>ADM3union</td>\n",
       "      <td>ADM3</td>\n",
       "      <td>ETH-Dire_Dawa-ADM3</td>\n",
       "      <td>ETH</td>\n",
       "      <td>ADM3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nairobi</td>\n",
       "      <td>KEN-Nairobi</td>\n",
       "      <td>ADM3union</td>\n",
       "      <td>ADM3</td>\n",
       "      <td>KEN-Nairobi-ADM3</td>\n",
       "      <td>KEN</td>\n",
       "      <td>ADM3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Antananarivo</td>\n",
       "      <td>MDG-Antananarivo</td>\n",
       "      <td>ADM4union</td>\n",
       "      <td>ADM4</td>\n",
       "      <td>MDG-Antananarivo-ADM4</td>\n",
       "      <td>MDG</td>\n",
       "      <td>ADM4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Mexico_City</td>\n",
       "      <td>MEX-Mexico_City</td>\n",
       "      <td>ADM2union</td>\n",
       "      <td>ADM2</td>\n",
       "      <td>MEX-Mexico_City-ADM2</td>\n",
       "      <td>MEX</td>\n",
       "      <td>ADM2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Monterrey</td>\n",
       "      <td>MEX-Monterrey</td>\n",
       "      <td>ADM2union</td>\n",
       "      <td>ADM2</td>\n",
       "      <td>MEX-Monterrey-ADM2</td>\n",
       "      <td>MEX</td>\n",
       "      <td>ADM2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       city_name          geo_name aoi_boundary_name units_boundary_name  \\\n",
       "0       Salvador      BRA-Salvador         ADM4union                ADM4   \n",
       "1         Bukavu        COD-Bukavu         ADM3union                ADM3   \n",
       "2          Uvira         COD-Uvira         ADM3union                ADM3   \n",
       "3    Brazzaville   COG-Brazzaville         ADM4union                ADM4   \n",
       "4   Barranquilla  COL-Barranquilla         ADM4union                ADM4   \n",
       "5    Addis_Ababa   ETH-Addis_Ababa         ADM4union                ADM4   \n",
       "6      Dire_Dawa     ETH-Dire_Dawa         ADM3union                ADM3   \n",
       "7        Nairobi       KEN-Nairobi         ADM3union                ADM3   \n",
       "8   Antananarivo  MDG-Antananarivo         ADM4union                ADM4   \n",
       "9    Mexico_City   MEX-Mexico_City         ADM2union                ADM2   \n",
       "10     Monterrey     MEX-Monterrey         ADM2union                ADM2   \n",
       "\n",
       "       city_boundary_name country_code geo_level  \n",
       "0       BRA-Salvador-ADM4          BRA      ADM4  \n",
       "1         COD-Bukavu-ADM2          COD      ADM2  \n",
       "2          COD-Uvira-ADM3          COD      ADM3  \n",
       "3    COG-Brazzaville-ADM4          COG      ADM4  \n",
       "4   COL-Barranquilla-ADM4          COL      ADM4  \n",
       "5    ETH-Addis_Ababa-ADM4          ETH      ADM4  \n",
       "6      ETH-Dire_Dawa-ADM3          ETH      ADM3  \n",
       "7        KEN-Nairobi-ADM3          KEN      ADM3  \n",
       "8   MDG-Antananarivo-ADM4          MDG      ADM4  \n",
       "9    MEX-Mexico_City-ADM2          MEX      ADM2  \n",
       "10     MEX-Monterrey-ADM2          MEX      ADM2  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get list of c4f cities\n",
    "boundary_georef = pd.read_csv('https://cities-cities4forests.s3.eu-west-3.amazonaws.com/data/boundaries/v_0/geo_ref.csv')\n",
    "\n",
    "# remove cities without tree cover data availability\n",
    "#tml_not_available_cities = ['BRA-Salvador','MEX-Monterrey']\n",
    "tml_not_available_cities = []\n",
    "boundary_georef = boundary_georef[~boundary_georef['geo_name'].isin(tml_not_available_cities)].reset_index(drop=True)\n",
    "boundary_georef"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "efe8118f-af0e-47a2-a2ff-da275e7e751d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def massfraction_to_concentration(massfraction):\n",
    "    # input masses in kg, volumes in m^3\n",
    "    # returns ug/m^3\n",
    "    # 10^9 ug/kg\n",
    "    # air density 1.223803 kg/m3 from https://confluence.ecmwf.int/display/UDOC/L60+model+level+definitions\n",
    "    return massfraction * 1.223803 * 10**9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e94cc144-64cc-4984-a6d7-df4b6259d421",
   "metadata": {},
   "outputs": [],
   "source": [
    "def kilogrampersquaremeter_to_microgrampersquaremeter(conc):\n",
    "    return conc * 10**9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cb02e4c3-c822-45b6-aebc-62388c51c053",
   "metadata": {},
   "outputs": [],
   "source": [
    "def exceedancedays(species, lon, lat):\n",
    "    speciesdata = datasets[species]\n",
    "    threshold = SPECIES_INFO[species]['who_threshold']\n",
    "    localdata = speciesdata.sel(latitude=lat, longitude=lon, method='nearest')\n",
    "    if SPECIES_INFO[species]['cams_unit'] == 'kg/kg':\n",
    "        conc = massfraction_to_concentration(localdata)\n",
    "    elif SPECIES_INFO[species]['cams_unit'] == 'kg/m^3':\n",
    "        conc = kilogrampersquaremeter_to_microgrampersquaremeter(localdata)\n",
    "    else:\n",
    "        raise Exception('Unknown CAMS unit')\n",
    "    dailymax = pd.DataFrame()\n",
    "    dailymax['thedata'] = conc.to_array()[0]\n",
    "    dailymax = dailymax.set_index(conc.time.to_index())\n",
    "    dailymax = dailymax.resample('D').mean()\n",
    "    return np.sum(dailymax.thedata >= threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0c92c7f2-6f68-467b-aa21-811e70091047",
   "metadata": {},
   "outputs": [],
   "source": [
    "cams_multispecies_aq_indicator = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "450db1c5-ff0c-4854-9098-ecd3ebe691bc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "\n",
      " geo_name: BRA-Salvador-ADM4union\n",
      "\n",
      " boundary_id_aoi: BRA-Salvador-ADM4union\n"
     ]
    }
   ],
   "source": [
    "for i in range(0, len(boundary_georef)):\n",
    "    print(i)\n",
    "    geo_name = boundary_georef.loc[i, 'geo_name']\n",
    "    \n",
    "    \n",
    "    boundary_id_aoi = boundary_georef.loc[i, 'geo_name']+'-'+boundary_georef.loc[i, 'aoi_boundary_name']\n",
    "    boundary_id_unit = boundary_georef.loc[i, 'geo_name']+'-'+boundary_georef.loc[i, 'units_boundary_name']\n",
    "    \n",
    "    print(\"\\n geo_name: \"+boundary_id_aoi)\n",
    "    \n",
    "    # AOI\n",
    "    boundary_id = boundary_id_aoi\n",
    "    print(\"\\n boundary_id_aoi: \"+boundary_id_aoi)\n",
    "    # read boundaries\n",
    "    boundary_path = aws_s3_dir +'/boundaries/v_0/boundary-'+boundary_id_aoi+'.geojson'\n",
    "    boundary_geo = requests.get(boundary_path).json()\n",
    "    boundary_geo_ee = geemap.geojson_to_ee(boundary_geo)\n",
    "    shape = shapely.geometry.shape(boundary_geo['features'][0]['geometry'])\n",
    "    centroid = shape.centroid\n",
    "    clon, clat = centroid.coords[0]  # Breaks if multipolygon\n",
    "    df = geemap.ee_to_pandas(boundary_geo_ee)\n",
    "\n",
    "    for species in SPECIES_INFO:\n",
    "        print(SPECIES_INFO[species]['name'])\n",
    "        df['exceedancedays {}'.format(SPECIES_INFO[species]['name'])] = exceedancedays(species, clon, clat)\n",
    "    cams_multispecies_aq_indicator = pd.concat([cams_multispecies_aq_indicator, df])\n",
    "       \n",
    "    # UNITS\n",
    "#    boundary_id = boundary_id_unit\n",
    "#    if boundary_id[-3:] != 'nan':\n",
    "#        print(\"\\n boundary_id_unit: \"+boundary_id_unit)\n",
    "#        boundary_path = aws_s3_dir +'/boundaries/v_0/boundary-'+ boundary_id +'.geojson'\n",
    "#        boundary_geo = requests.get(boundary_path).json()\n",
    "#        boundary_geo_ee = geemap.geojson_to_ee(boundary_geo)\n",
    "#        df = geemap.ee_to_pandas(boundary_geo_ee)\n",
    "#        results = {}\n",
    "#        for species in SPECIES_INFO:\n",
    "#            results[species] = {}\n",
    "#        for feature in boundary_geo['features']:\n",
    "#            print(\"\\n     geo_id: \" + feature['properties']['geo_id'])\n",
    "#            shape = shapely.geometry.shape(feature['geometry'])\n",
    "#            centroid = shape.centroid\n",
    "#            clon, clat = centroid.coords[0]\n",
    "#            for species in SPECIES_INFO:\n",
    "#                print(SPECIES_INFO[species]['name'])\n",
    "#                results[species][feature['properties']['geo_id']] = exceedancedays(species, clon, clat)\n",
    "#        for species in results:\n",
    "#            df['exceedancedays {}'.format(SPECIES_INFO[species]['name'])]= df['geo_id'].map(results[species])\n",
    "#        cams_multispecies_aq_indicator = pd.concat([cams_multispecies_aq_indicator, df])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f3ae6889-b188-40c1-8ae6-3d2f63aa7e0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geo_parent_name</th>\n",
       "      <th>geo_level</th>\n",
       "      <th>creation_date</th>\n",
       "      <th>geo_id</th>\n",
       "      <th>geo_name</th>\n",
       "      <th>exceedancedays nitrogen dioxide</th>\n",
       "      <th>exceedancedays sulfur dioxide</th>\n",
       "      <th>exceedancedays ozone</th>\n",
       "      <th>exceedancedays fine particulate matter</th>\n",
       "      <th>exceedancedays coarse particulate matter</th>\n",
       "      <th>exceedancedays carbon monoxide</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BRA-Salvador</td>\n",
       "      <td>ADM4-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>BRA-Salvador_ADM4-union_1</td>\n",
       "      <td>BRA-Salvador</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>266</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COD-Bukavu</td>\n",
       "      <td>ADM3-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>COD-Bukavu_ADM3-union_1</td>\n",
       "      <td>COD-Bukavu</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>2</td>\n",
       "      <td>366</td>\n",
       "      <td>335</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COD-Uvira</td>\n",
       "      <td>ADM3-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>COD-Uvira_ADM3-union_1</td>\n",
       "      <td>COD-Uvira</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>366</td>\n",
       "      <td>143</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COG-Brazzaville</td>\n",
       "      <td>ADM4-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>COG-Brazzaville_ADM4-union_1</td>\n",
       "      <td>COG-Brazzaville</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>366</td>\n",
       "      <td>281</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COL-Barranquilla</td>\n",
       "      <td>ADM4-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>COL-Barranquilla_ADM4-union_1</td>\n",
       "      <td>COL-Barranquilla</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>365</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ETH-Addis_Ababa</td>\n",
       "      <td>ADM4-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>ETH-Addis_Ababa_ADM4-union_1</td>\n",
       "      <td>ETH-Addis_Ababa</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>366</td>\n",
       "      <td>196</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ETH-Dire_Dawa</td>\n",
       "      <td>ADM3-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>ETH-Dire_Dawa_ADM3-union_1</td>\n",
       "      <td>ETH-Dire_Dawa</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>366</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KEN-Nairobi</td>\n",
       "      <td>ADM3-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>KEN-Nairobi_ADM3-union_1</td>\n",
       "      <td>KEN-Nairobi</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>366</td>\n",
       "      <td>342</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MDG-Antananarivo</td>\n",
       "      <td>ADM4-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>MDG-Antananarivo_ADM4-union_1</td>\n",
       "      <td>MDG-Antananarivo</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>293</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MEX-Mexico_City</td>\n",
       "      <td>ADM2-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>MEX-Mexico_City_ADM2-union_1</td>\n",
       "      <td>MEX-Mexico_City</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>366</td>\n",
       "      <td>306</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MEX-Monterrey</td>\n",
       "      <td>ADM2-union</td>\n",
       "      <td>2022-08-03</td>\n",
       "      <td>MEX-Monterrey_ADM2-union_1</td>\n",
       "      <td>MEX-Monterrey</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>366</td>\n",
       "      <td>295</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    geo_parent_name   geo_level creation_date                         geo_id  \\\n",
       "0      BRA-Salvador  ADM4-union    2022-08-03      BRA-Salvador_ADM4-union_1   \n",
       "0        COD-Bukavu  ADM3-union    2022-08-03        COD-Bukavu_ADM3-union_1   \n",
       "0         COD-Uvira  ADM3-union    2022-08-03         COD-Uvira_ADM3-union_1   \n",
       "0   COG-Brazzaville  ADM4-union    2022-08-03   COG-Brazzaville_ADM4-union_1   \n",
       "0  COL-Barranquilla  ADM4-union    2022-08-03  COL-Barranquilla_ADM4-union_1   \n",
       "0   ETH-Addis_Ababa  ADM4-union    2022-08-03   ETH-Addis_Ababa_ADM4-union_1   \n",
       "0     ETH-Dire_Dawa  ADM3-union    2022-08-03     ETH-Dire_Dawa_ADM3-union_1   \n",
       "0       KEN-Nairobi  ADM3-union    2022-08-03       KEN-Nairobi_ADM3-union_1   \n",
       "0  MDG-Antananarivo  ADM4-union    2022-08-03  MDG-Antananarivo_ADM4-union_1   \n",
       "0   MEX-Mexico_City  ADM2-union    2022-08-03   MEX-Mexico_City_ADM2-union_1   \n",
       "0     MEX-Monterrey  ADM2-union    2022-08-03     MEX-Monterrey_ADM2-union_1   \n",
       "\n",
       "           geo_name  exceedancedays nitrogen dioxide  \\\n",
       "0      BRA-Salvador                                0   \n",
       "0        COD-Bukavu                                0   \n",
       "0         COD-Uvira                                0   \n",
       "0   COG-Brazzaville                                2   \n",
       "0  COL-Barranquilla                                0   \n",
       "0   ETH-Addis_Ababa                                0   \n",
       "0     ETH-Dire_Dawa                                0   \n",
       "0       KEN-Nairobi                                0   \n",
       "0  MDG-Antananarivo                                0   \n",
       "0   MEX-Mexico_City                                0   \n",
       "0     MEX-Monterrey                                0   \n",
       "\n",
       "   exceedancedays sulfur dioxide  exceedancedays ozone  \\\n",
       "0                              0                     0   \n",
       "0                             39                     2   \n",
       "0                              0                    14   \n",
       "0                              0                    60   \n",
       "0                              0                    17   \n",
       "0                              0                     8   \n",
       "0                              0                    21   \n",
       "0                              0                     1   \n",
       "0                              0                    11   \n",
       "0                              0                     4   \n",
       "0                              0                    16   \n",
       "\n",
       "   exceedancedays fine particulate matter  \\\n",
       "0                                     266   \n",
       "0                                     366   \n",
       "0                                     366   \n",
       "0                                     366   \n",
       "0                                     365   \n",
       "0                                     366   \n",
       "0                                     366   \n",
       "0                                     366   \n",
       "0                                     293   \n",
       "0                                     366   \n",
       "0                                     366   \n",
       "\n",
       "   exceedancedays coarse particulate matter  exceedancedays carbon monoxide  \n",
       "0                                         3                               0  \n",
       "0                                       335                               0  \n",
       "0                                       143                               0  \n",
       "0                                       281                               0  \n",
       "0                                       151                               0  \n",
       "0                                       196                               0  \n",
       "0                                        56                               0  \n",
       "0                                       342                               0  \n",
       "0                                        19                               0  \n",
       "0                                       306                               0  \n",
       "0                                       295                               0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cams_multispecies_aq_indicator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a78612c5-70c5-49bc-8f77-6e605af93b7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "cams_multispecies_aq_indicator.to_csv('multispecies_aq.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0007ef0a-6148-43ed-95d3-9822d83ae1d5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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