The washout effects of rainfall on atmospheric particulate pollution in two Chinese cities

Highlights

• Relative effect is an approach that links washout effect to precipitation amount.

• Particle size plays an important role in washout effect of rainfall.

• The threshold is helpful in discriminating whether rainfall can improve air quality.

• The lag period lengths determine the improvement of air quality following rain.

• Restricted by relative effect, the washout effect to particles is limited.

Abstract

Though rainfall is recognized as one of the main mechanisms to reduce atmospheric particulate pollution, few studies have quantified this effect, particularly the corresponding lag effect and threshold. This study aimed to investigate the association between rainfall and air quality using a distributed lag non-linear model. Daily data on ambient PM_2.5 and PM_2.5–10 (particulate matter with an aerodynamic diameter less than 2.5 μm and from 2.5 to 10 μm) and meteorological factors were collected in Guangzhou and Xi'an from 2013 to 2014. A better washout effect was found for PM_2.5–10 than for PM_2.5, and the rainfall thresholds for both particle fractions were 7 mm in Guangzhou and 1 mm in Xi'an. The decrease in PM_2.5 levels following rain lasted for 3 and 6 days in Guangzhou and Xi'an, respectively. Rainfall had a better washout effect in Xi'an compared with that in Guangzhou. Findings from this study contribute to a better understanding of the washout effects of rainfall on particulate pollution, which may help to understand the category and sustainability of dust-haze and enforce anthropogenic control measures in time.

Introduction

With increasing attention to dust-haze and related harmful health effects in China, air pollution has become a significant environmental concern for the public and policy makers (WHO, 2011, Rauhala, 2013, Xu et al., 2013). One of the major factors that causes dust-haze is atmospheric particles, especially PM_2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm), which originates mainly from fuel combustion, construction dust and vehicle exhaust (Vingarzan and Li, 2006). The natural and anthropogenic processes for reducing atmospheric particle levels are important to improve air quality.

Rainfall is recognized as one of the main natural processes to improve air quality (Duhanyan and Roustan, 2011, Elperin et al., 2011), and it can greatly enhance the positive reductions achieved by anthropogenic control measures (Leung and Gustafson, 2005). Our previous study assessed the rainfall removal efficiency for total suspended particles (TSP) and found that artificial rain interventions may worsen air quality due to the lower removal of TSP without rainfall (Guo et al., 2014). However, there is limited information about the washout of particles and improvement in air quality following a single rain event and corresponding lag effects, as previous studies usually combined several rain events in one sample or focused on insufficient daily samples (Mattiot and Scafe, 1999, Encinas et al., 2004, He and Balasubramanian, 2009, Huang et al., 2009, Guo et al., 2014). Moreover, the results for analyzing washout of TSP are not applicable to a more narrowly defined specific size range of particle (e.g., PM_2.5), as the washout effects are variable among different sizes of particles (Baklanov and Sørensen, 2001, Wang et al., 2010).

Numerous studies have conducted experimental and theoretical assessments on scavenging coefficients; a microphysical approximation of the particle washout effect by raindrops (Slinn, 1984, Flossmann et al., 1985, Volken and Schumann, 1993, Mircea et al., 2000, Andronache, 2003, Laakso et al., 2003, Loosmore and Cederwall, 2004, Bae et al., 2006, Feng, 2007, Wang et al., 2010, Quérel et al., 2014a, Quérel et al., 2014b, Wang et al., 2014). However, due to the complex collection of microphysical parameters (e.g., raindrop diameter, particle diameter, collision efficiency between raindrop and atmospheric particles, etc.) and huge computing resources required (Mircea et al., 2000, Bae et al., 2006, Wang et al., 2010), the scavenging coefficient is not easy to calculate, and therefore not suitable to evaluate air quality directly. Instead of linking air quality to scavenging coefficient, an approach is needed that links it to observable meteorological parameters such as rainfall conditions (Quérel et al., 2014b). Also, focusing on observable parameters may allow a more direct evaluation of the change in air quality following rain. For example, rainfall may worsen air quality following low amounts of precipitation (Levin and Cotton, 2008, Feng and Wang, 2012, Yuan, 2014) and identifying the critical threshold which corresponds to precipitation amount may help to discriminate and forecast changes in air quality.

In view of this knowledge gap, we assessed the removal effects of rainfall by collecting daily PM_2.5 and PM_2.5–10 (particulate matter with an aerodynamic diameter between 2.5 and 10 μm) concentrations and meteorological factors (wind speed and precipitation) in Guangzhou and Xi'an during 2013 and 2014. This study aims to provide a quantitative description of the rainfall washout effect using a new approach, which can enhance the knowledge for evaluating particulate pollution, and hence assist in implementing efficient control measures to cope with worsening air quality.