March 15, 2017 - March 29, 2017

Air pollution caused by particles with a diameter of 2.5 microns or less (PM2.5) can reduce visibility and adversely affect human health. As a result, the United Nations has addressed this type of pollution in the 2030 Agenda for Sustainable Development.

Recently, annual mean PM2.5 maps have been developed using MODIS, MISR, and SeaWiFS observations from 1998-2015 and have been used by organizations, such as the World Health Organization (WHO) and Greenpeace, to assess global air quality and health impacts. In this webinar, participants learn how to use this database to analyze PM2.5 over cities using satellite observations. This training covers data access, analyzing long-term trends, and combining PM2.5 and population datasets to understand long-term exposure.

Agenda Cite This Training

(2017). ARSET - Satellite Derived Annual PM2.5 Datasets in Support of United Nations Sustainable Development Goals. NASA Applied Remote Sensing Training Program (ARSET).

Attendees will: 

  • Become familiar with the UN Sustainable Development Goals, as well as the satellite observations of air quality that are used to calculate indicators 3.9.1 and 11.6.2
  • Learn about PM2.5 estimates made using satellite, surface, and model datasets
  • Understand how to use the 2014 WHO data set and access the indicator data for a city or country

Agencies involved in addressing and reporting on United Nations Sustainable Development Goals (SDGs), as well as, local, regional, state, federal, and international organizations interested in assessing PM2.5 air quality.

Course Format
  • Three 1-hour sessions
Part 1: Sustainable Development Goals (SDGs) and Relevant Air Quality Observations

The goals, targets, and indicators of the UN sustainable development goals; the satellite observations of air quality that are used to calculate indicators 3.9.1 and 11.6.2; how satellite observations can fill in the gaps; and methodology and applications.



Part 2: World Health Organization (WHO) PM2.5 Data Set

PM2.5 estimates using satellite, surface, and model data sets for 2014, released by the WHO; how the data applies to indicators 3.9.1 and 11.6.2; and methodology, limitations, and data access.



Part 3: Case Study Analysis

Using the 2014 WHO data set, read and convert the data for a region of interest, complete a mapping exercise, perform a case study analysis on spatial pattern comparisons for different cities, and learn to apply all the skills learned to create a time series once more data becomes available.





Contact Us