Update eodashMarkdown_EXTREME_POLLUTION_2.md

app/public/data/storytelling-md/eodashMarkdown_EXTREME_POLLUTION_2.md

@@ -11,11 +11,11 @@ The region along the Himalayas in Northern India and Pakistan, also know as the
 
 The following map shows the population density for 2020, provided by the Center for International Earth Science Information Network - CIESIN - Columbia University. Darker shades indicate higher density, with values ranging from 1-10.000 persons/km<sup>2</sup>.
 
-##  <!--{as="eox-map" style="width: 100%; height: 500px;" layers='[{"type":"Tile","properties":{"id":"Overlay labels"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/overlay_base_bright_3857/default/g/{z}/{y}/{x}.jpg"]}},{"type":"Tile","properties":{"id":"population_density"},"source":{"type":"TileWMS","urls":["https://services.sentinel-hub.com/ogc/wms/0635c213-17a1-48ee-aef7-9d1731695a54"],"params":{"layers":"AWS_POPULATION_DENSITY","styles":"","format":"image/png","time":"2020-05-01"}}},{"type":"Tile","properties":{"id":"Terrain light"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/terrain-light_3857/default/g/{z}/{y}/{x}.jpg"]}}]' zoom="5.199752548020474" center=[79.94493602969328,24.295288218801616] }-->
-##  <!--{as="eox-stacinfo" for="https://eurodatacube.github.io/eodash-catalog/trilateral/population_density/collection.json" featured='["description","providers","assets","links"]'  properties='["satellite","sensor","agency","extent"]' header='["title"]' tags='["tags"]' footer='["sci:citation"]' }-->
+## <!--{as="eox-map" style="width: 100%; height: 500px;" layers='[{"type":"Tile","properties":{"id":"Overlay labels"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/overlay_base_bright_3857/default/g/{z}/{y}/{x}.jpg"]}},{"type":"Tile","properties":{"id":"population_density"},"source":{"type":"TileWMS","urls":["https://services.sentinel-hub.com/ogc/wms/0635c213-17a1-48ee-aef7-9d1731695a54"],"params":{"layers":"AWS_POPULATION_DENSITY","styles":"","format":"image/png","time":"2020-05-01"}}},{"type":"Tile","properties":{"id":"Terrain light"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/terrain-light_3857/default/g/{z}/{y}/{x}.jpg"]}}]' zoom="5.199752548020474" center=[79.94493602969328,24.295288218801616] }-->
+## <!--{as="eox-stacinfo" for="https://eurodatacube.github.io/eodash-catalog/trilateral/population_density/collection.json" featured='["description","providers","assets","links"]'  properties='["satellite","sensor","agency","extent"]' header='["title"]' tags='["tags"]' footer='["sci:citation"]' }-->
 
 
-## Air Pollution from Space
+## Earth Observations
 Agencies such as ESA, NASA and JAXA have Earth-observing satellites whose instruments observe air pollutants around the world. Missions such as NASA's Aura Satellite carrying the [Ozone Monitoring Instrument (OMI)](https://www.earthdata.nasa.gov/learn/find-data/near-real-time/omi) or ESA's Sentinel-5p carrying the [TROPOspheric Monitoring Instrument (TROPOMI)](https://www.tropomi.eu/) provide essential data that is used to study the impact of air pollution on human health and agriculture.
 
 Measurable air pollutants include: 
@@ -60,8 +60,8 @@ Explore [MODIS active fire data on EO Dashboard over the IGP]( https://www.eodas
 
 The following map shows the horizontal wind from ERA5 hourly data provided by the Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Hersbach 2023). Values range from [-4, 4] m/s. Blue shades indicate lower values. 
 
-## New Delhi U Wind <!--{as="eox-map" style="width: 100%; height: 500px;" layers='[{"type":"Tile","properties":{"id":"Overlay labels"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/overlay_base_bright_3857/default/g/{z}/{y}/{x}.jpg"]}},{"type":"Tile","properties":{"id":"wind_100m_u_newDeli-2023-11-10"},"opacity":0.77,"source":{"type":"TileWMS","urls":["https://services.sentinel-hub.com/ogc/wms/0635c213-17a1-48ee-aef7-9d1731695a54"],"params":{"layers":"VIS_ERA5_SINGLELEVEL_WIND_U_100M","styles":"","format":"image/png","time":"2023-11-10"}}},{"type":"Tile","properties":{"id":"OSM Background"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/osm_3857/default/g/{z}/{y}/{x}.jpg"]}}]' zoom="6.509882184402946" center=[76.9845663060298,28.234047216613092] }-->
-## StacInfo example <!--{as="eox-stacinfo" for="https://eurodatacube.github.io/eodash-catalog/trilateral/wind_100m_u_newDeli/collection.json" featured='["description","providers","assets","links"]'  properties='["satellite","sensor","agency","extent"]' header='["title"]' tags='["tags"]' footer='["sci:citation"]' }-->
+## <!--{as="eox-map" style="width: 100%; height: 500px;" layers='[{"type":"Tile","properties":{"id":"Overlay labels"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/overlay_base_bright_3857/default/g/{z}/{y}/{x}.jpg"]}},{"type":"Tile","properties":{"id":"wind_100m_u_newDeli-2023-11-10"},"opacity":0.77,"source":{"type":"TileWMS","urls":["https://services.sentinel-hub.com/ogc/wms/0635c213-17a1-48ee-aef7-9d1731695a54"],"params":{"layers":"VIS_ERA5_SINGLELEVEL_WIND_U_100M","styles":"","format":"image/png","time":"2023-11-10"}}},{"type":"Tile","properties":{"id":"OSM Background"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/osm_3857/default/g/{z}/{y}/{x}.jpg"]}}]' zoom="6.509882184402946" center=[76.9845663060298,28.234047216613092] }-->
+## <!--{as="eox-stacinfo" for="https://eurodatacube.github.io/eodash-catalog/trilateral/wind_100m_u_newDeli/collection.json" featured='["description","providers","assets","links"]'  properties='["satellite","sensor","agency","extent"]' header='["title"]' tags='["tags"]' footer='["sci:citation"]' }-->
 
 ##
 For each city a rectangle of -0.4 to 0.4° of longitude and -0.4 to 0.4° latitude was generated (from the given coordinates of the chosen city in latitude and longitude) which corresponds to -39.8 to 39.8km in longitude and to -44.5 to 44.5km in latitude. Then the computed time series of each day is the average value of all CO concentration values measured by TROPOMI within that rectangle (with a resolution of 0.025°). The percentile method is a strategy utilized to recognize outliers or extreme values based upon a defined percent limit. It involves calculating the threshold values based on percentiles and the steps are to first determine the percentage threshold (in this case 90%, 95%, and 99%), then calculate the threshold values, and then identify outliers and extreme values above this threshold.
@@ -81,7 +81,7 @@ Furthermore, when these extreme episodes were quantified, the number of days whi
 <span style="font-size:15px;">The table indicates the number of days which can be considered as extremes (for 90%, 95%, and 99%). We notice that these number of days are almost the same for the 3 cities, indicating a potential correlation between the extreme pollution events in the 3 cities. Note that the total number of days in 2023 is not 365 since for some days we do not have measurements because of clouds or other factors.</span>
 
 
-## CO Map Tour <!--{ as="eox-map" mode="tour" }-->
+## <!--{ as="eox-map" mode="tour" }-->
 
 ### <!--{ layers='[{"type":"Tile","properties":{"id":"Overlay labels"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/overlay_base_bright_3857/default/g/{z}/{y}/{x}.jpg"]}},{"type":"Tile","properties":{"id":"CO_3_daily-2023-11-08"},"source":{"type":"TileWMS","urls":["https://services.sentinel-hub.com/ogc/wms/0635c213-17a1-48ee-aef7-9d1731695a54"],"params":{"layers":"AWS_VIS_CO_3DAILY_DATA","styles":"","format":"image/png","time":"2023-11-08"}}},{"type":"Tile","properties":{"id":"OSM Background"},"source":{"type":"XYZ","urls":["//s2maps-tiles.eu/wmts/1.0.0/osm_3857/default/g/{z}/{y}/{x}.jpg"]}}]' zoom="9.879889469918195" center=[74.28590944565705,31.547289411942756] animationOptions={duration:500}}-->
 #### Lahore 
@@ -149,7 +149,7 @@ In general, wind speed was low during this period. However, it was also noticed
 	* The IGP is a highly polluted region characterized by mixtures of gaseous pollutants and aerosols (such as fine particles, known as PM2.5). CO is one among many pollutants emitted during vegetation fires. In the case of the November 2023 air pollution episode, it was interesting to study this molecule, as the cause of the November 2023 smog was agricultural waste burning. However, for other pollution episodes (such as those occurring in summer), it might be more interesting to study tropospheric ozone, as it is predominantly produced under strong sunlight conditions. Additionally, studying ammonia, a precursor of fine particles, is also important because hot weather leads to high ammonia emissions, thereby promoting smog formation. Furthermore, TROPOMI also measures NO2 and SO2, two other precursor gases of PM2.5, offering the opportunity to track their evolution throughout the year to determine days with smog events.
 
 
-### Open Science 
+## Open Science 
 
 The analysis was carried out on the [ESA DeepESDL (Deep Earth System Data Lab)](https://earthsystemdatalab.net ). For research purposes, ESA is offering this resources under a sponsorship scheme through the Network of Resources.
 * [DeepESDL website](https://earthsystemdatalab.net)