Using the U.S. EPA’s latest positive matrix factorization model, STI scientists developed a real-time source apportionment tool for the Shanghai Environmental Monitoring Center (SEMC) that identifies real-time sources of PM2.5 in Shanghai, China. Using SEMC’s hourly speciated PM2.5 data, the tool shows how specific emissions sources are impacting the previous hour’s air pollution, enabling SEMC to alert the public when pollutant emissions are high. In the long term, this tool can also be used to track the amount of PM2.5 emitted by certain sources and to evaluate the effectiveness of emissions reduction activities.
As air quality agencies acquire and communicate real-time air quality data to the public, the need to evaluate sources of air pollution in real time becomes more pressing. With additional, more advanced air quality monitors and sensors being deployed, the wealth of data can deliver current, actionable information on sources of air pollution and future trends.