Retrieving historical ambient PM2.5 concentrations using existing visibility measurements in Xi'an, Northwest China

Abstract Long term fine particulate matter (PM2.5) data are needed to assess air quality and climate issues, but PM2.5 data have only been monitored in the recent decade in Chinese cities. Considering strong correlations between PM2.5 and visibility, regression models can be useful tools for retrieving historical PM2.5 data from available visibility data. In this study, PM2.5 and visibility data are both available during 2004–2011 in Xi'an, a megacity in northwest China. Data from 2004 to 2007 were used to develop a regression model and those from 2008 to 2011 were used to evaluate the model. An exponential regression model was then chosen to retrieve the historical PM2.5 data from 1979 to 2003, which were then analyzed together with the measured data from 2004 to 2011 for long term trends. Seasonal PM2.5 increased from 1979 to 2011 with the fastest increase in winter and the slowest in summer. Annual average PM2.5 followed into three distinct periods with a slow decreasing trend from 1979 to 1996, a sharp increasing trend from 1997 to 2006, and a slow decreasing trend from 2007 to 2011. These increasing and decreasing trends are in agreement with the evolution of industrial development in Xi'an.