Correlation networks of air particulate matter ($$\hbox {PM}_{2.5}$$): a comparative study

Abstract

Over the last decades, severe haze pollution constitutes a major source of far-reaching environmental and human health problems. The formation, accumulation and diffusion of pollution particles occurs under complex temporal scales and expands throughout a wide spatial coverage. Seeking to understand the transport patterns of haze pollutants in China, we review a proposed framework of time-evolving directed and weighted air quality correlation networks. In this work, we evaluate monitoring stations’ time-series data from China and California, to test the sensitivity of the framework to region size, climate and pollution magnitude across multiple years (2014–2020). We learn that the use of hourly $$\hbox {PM}_{2.5}$$ PM 2.5 concentration data is needed to detect periodicities in the positive and negative correlations of the concentrations. In addition, we show that the standardization of the correlation function method is required to obtain networks with more meaningful links when evaluating the dispersion of a severe haze event at the North China Plain or a wildfire event in California during December 2017. Post COVID-19 outbreak in China, we observe a significant drop in the magnitude of the assigned weights, indicating the improved air quality and the slowed transport of $$\hbox {PM}_{2.5}$$ PM 2.5 due to the lockdown. To identify regions where pollution transport is persistent, we extend the framework, partitioning the dynamic networks and reducing the networks’ complexity through node subsampling. The end result separates the temporal series of $$\hbox {PM}_{2.5}$$ PM 2.5 in set of regions that are similarly affected through the year.

A Framework for Characterizing the Multilateral and Directional Interaction Relationships Between PM Pollution at City Scale: A Case Study of 29 Cities in East China, South Korea and Japan

“…The strength of a potential interaction relationship between PM pollution in two adjacent cities is measured using a statistical measure called time lag-adjusted Pearson correlation coefficient. The time lag-adjusted Pearson correlation coefficient is calculated using cross correlation method ( 25 – 27 ).…”

Spatiotemporal cluster analysis of COVID-19 and its relationship with environmental factors at the city level in mainland China

“…Emerging evidence suggests potential links between exposure to polluted air and the epidemic of COVID-19(Chen et al 2021 ; Chen et al 2020 ; Konstantinoudis et al 2021 ). Research has shown that the airborne transmission is highly virulent (Srivastava 2021 ), particulate matter can be used as a carrier to carry viruses to spread it everywhere (Vlachogiannis et al 2021 ; Yao et al 2020 ), and respiratory infectious disease viruses that are efficiently transmitted through particulate matter can remain stable for a longer period of time.…”