This document also provides recommended quality assurance (QA) procedures and guidance to help monitoring agencies reliably achieve the data quality objectives (DQOs) established for PM2.5 monitoring. The goal for acceptable measurement uncertainty has been defined as 10 percent coefficient of variation (CV) for total precision and ±10 percent for total bias (Papp et al., 1998). The information pr...

To improve air quality, knowledge of the sources and locations of air pollutant emissions is critical. However, for many global cities, no previous estimates exist of how much exposure to fine particulate matter (PM2.5), the largest environmental cause of mortality, is caused by emissions within the city vs. outside its boundaries. We use the Intervention Model for Air Pollution (InMAP) global-thr...

This lecture describes indoor air quality modelling and its advantages. The lecture also includes the numerical modelling of indoor air flow and the programs for indoor air quality modelling....

This lecture illustrates the concepts and significance of receptor modelling and its application in source apportionment studies....

This lecture explains how to apportion the sources of emissions and methods of carrying out a source apportionment study....

This lecture illustrates the basic concepts of an airshed and the methods to estimate the assimilative capacity of an airshed....

This lecture presents the practice examples on the determination of concentration of pollutants from point, line, and area sources using the Gaussian dispersion model....

This lecture briefly describes the Gaussian dispersion model for line source and area source, their assumptions, derivation, and examples....

This lecture explains the Gaussian dispersion model for a point source, its derivation, and the estimation of parameters of the Gaussian plume equation....

This lecture focuses on the basics of air quality modelling, and its components. The lecture also includes the different types of air quality models....