Optimization of air quality monitoring network based on a spatiotemporal-spectrum manifold analysis

Abstract

An effective air quality monitoring network (AQMN) is able to promptly reflect the characteristics of ambient air pollutants for air pollution control and management nearby potential hazardous emissions. This research proposed an innovative spatiotemporal-spectrum manifold analysis to investigate the multi-pollutant emission variation and sampling. The analysis established a coordinate system with spatial relation, temporal correlation, and the frequency spectrum of the multi-pollutant emission data. The pairwise manifold distances were estimated accordingly. We formulated a manifold-based multi-objective optimization model, which optimizes the population coverage and monitoring efficiency of the AQMN nearby the emission. We applied the manifold analysis and the optimization model to a petrochemical complex in Taiwan. The spatial and temporal variation of the complex’s multi-pollutant emission was analyzed. Then, the optimization model solved for the best configuration of AQMN that satisfied the design objectives. We examined the tradeoff between the multiple objectives. Improvement of the existing monitoring stations was suggested based on the optimization results. Adding one or two monitoring stations at the densely populated area was recommended to provide better coverage for residents. Our results also settled for an optimal addition location to increase monitoring efficiency.