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BEGIN:VEVENT
UID:a01d239d07d2aa4e3dfe4671dbd411c2
CATEGORIES:Polar Online Events
CREATED:20210712T072915
SUMMARY:ACCAP Webinar: Using a random forest model to predict historical PM2.5 in Alaska
LOCATION:Online
DESCRIPTION:Tuesday, July 13 (10am AKDT)Using a random forest model to predict historic
 al PM2.5 in Alaska (https://uaf-accap.org/event/pm2-point-5-alaska/)Allison
  Baer | PhD Candidate\nUniversity of Maryland, Department of Geographical S
 ciences The spatiotemporal coverage of regulatory-grade, ground-based air q
 uality monitoring stations measuring PM2.5 concentrations is low across Ala
 ska. Recently, there has been an increase in the number of low-cost air qua
 lity monitoring stations for PM2.5 that expand the spatiotemporal coverage 
 of PM2.5 monitoring in Alaska and globally. This study uses a random forest
  model to predict PM2.5 concentrations from regulatory-grade data and corre
 cted low-cost air quality monitoring data from the 2019 wildfire season (Ma
 y through September) in Alaska. Results show that the model predicts a high
  amount of the variance at over 0.75. These results will inform mapping of 
 PM2.5 continuous concentrations across Alaska. ACCAP is partnering with NAS
 A’s Arctic-Boreal Vulnerability Experiment (ABoVE) (https://above.nasa.gov/
 ) to highlight Alaska research results from this ongoing field campaign. AB
 oVE is a large-scale study of environmental change and its implications for
  social-ecological systems. ABoVE links field-based, process-level studies 
 with geospatial data products derived from airborne and satellite sensors, 
 providing a foundation for improving the analysis, and modeling capabilitie
 s needed to understand and predict ecosystem responses and societal implica
 tions. ABoVE also has occasional webinar series focused on research in Yuko
 n Territory and Northwest Territories. More information and registration: h
 ttps://uaf-accap.org/event/pm2-point-5-alaska/ (https://uaf-accap.org/event
 /pm2-point-5-alaska/)
X-ALT-DESC;FMTTYPE=text/html:<div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr">
 <div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr">
 <div dir="ltr"><div><div><div dir="ltr"><div dir="ltr"><div style="text-ali
 gn: justify;"><strong>Tuesday, July 13 (10am AKDT)</strong></div><div style
 ="text-align: justify;"><a href="https://uaf-accap.org/event/pm2-point-5-al
 aska/" target="_blank" rel="noopener">Using a random forest model to predic
 t historical PM2.5 in Alaska</a></div><div style="text-align: justify;"><em
 >Allison Baer | PhD Candidate<br />University of Maryland, Department of Ge
 ographical Sciences</em></div><div style="text-align: justify;">&nbsp;</div
 ><div style="text-align: justify;">The spatiotemporal coverage of regulator
 y-grade, ground-based air quality monitoring stations measuring PM2.5 conce
 ntrations is low across Alaska. Recently, there has been an increase in the
  number of low-cost air quality monitoring stations for PM2.5 that expand t
 he spatiotemporal coverage of PM2.5 monitoring in Alaska and globally. This
  study uses a random forest model to predict PM2.5 concentrations from regu
 latory-grade data and corrected low-cost air quality monitoring data from t
 he 2019 wildfire season (May through September) in Alaska. Results show tha
 t the model predicts a high amount of the variance at over 0.75. These resu
 lts will inform mapping of PM2.5 continuous concentrations across Alaska.</
 div></div></div></div></div></div></div></div></div></div></div></div></div
 ></div></div></div><div style="text-align: justify;"><div><div>&nbsp;</div>
 <div>ACCAP is partnering with <a href="https://above.nasa.gov/" target="_bl
 ank" rel="noopener">NASA’s Arctic-Boreal Vulnerability Experiment (ABoVE)</
 a> to highlight Alaska research results from this ongoing field campaign. A
 BoVE is a large-scale study of environmental change and its implications fo
 r social-ecological systems. ABoVE links field-based, process-level studies
  with geospatial data products derived from airborne and satellite sensors,
  providing a foundation for improving the analysis, and modeling capabiliti
 es needed to understand and predict ecosystem responses and societal implic
 ations. ABoVE also has occasional webinar series focused on research in Yuk
 on Territory and Northwest Territories.&nbsp;</div></div></div><div style="
 text-align: justify;">More information and registration: <a href="https://u
 af-accap.org/event/pm2-point-5-alaska/" target="_blank" rel="noopener">http
 s://uaf-accap.org/event/pm2-point-5-alaska/</a></div>
DTSTAMP:20260805T005158
DTSTART;TZID=UTC;VALUE=DATE:20210713
DTEND;TZID=UTC;VALUE=DATE:20210714
SEQUENCE:0
TRANSP:OPAQUE
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