Strategies for the control of particulate air quality: least-cost solutions based on receptor-oriented models

When combined with emission inventory data, receptor modeling methods can be used to identify the least costly array of emission controls needed to solve regional particulate air quality problems. This approach to the identification of minimum cost solutions to regional particulate pollution is potentially more accurate and less resource-intensive than prior methods based on atmospheric diffusion models. A receptor-oriented modeling scheme is used to determine the source contributions to ambient air quality at each monitoring site in an air basin. The air quality model is attached to a linear programming algorithm to compute the least costly combination of emission controls. The method is illustrated by application to particulate pollution problems using historically available data for the Los Angeles, CA, basin.