Ambient PM2.5 in the residential area near industrial complexes: Spatiotemporal variation, source apportionment, and health impact
Graphical abstract
Introduction
Fine particles (PM2.5, particulate matter (PM) ≦ 2.5 μm in aerodynamic diameter) are a complex mixture with various shapes, sizes, and chemical components (such as sulfate, nitrate, ammonium, inorganic and organic carbons, and trace elements). PM2.5 can affect the atmospheric visibility, play key roles in the formation of acid rain and climate change, and deteriorate the local and regional air quality. Exposure to ambient PM2.5 has been recognized as one of the leading causes of adverse health outcomes in relation to cardiopulmonary morbidity and mortality (Cascio et al., 2009, Dockery et al., 1993, Dominici et al., 2006, Pope et al., 2002). In addition, outdoor PM has been classified by the International Agency for Research on Cancer (IARC) as carcinogenic to humans (Group 1). Given these reasons, the governments in various countries have enforced strict air quality standards for PM2.5.
Although Taiwan has a regulatory history in terms of its ongoing efforts to protect public health from ambient particle pollutants, overall the PM2.5 level (annual mean = ~ 25 μg m− 3 in 2014) still exceeds the guideline limit set by the Taiwan EPA (15 μg m− 3). In particular, the residential regions (such as Changhua and Yunlin Counties) near energy-consuming and high-polluting industries in central Taiwan, have a poor air quality of PM2.5 (annual mean = 30 μg m− 3) that is usually attributed to their emissions but rarely to be clarified. Within the region, frequently occurring episodes of elevated PMs during the winter period caused by both local emissions with a poor dispersion conditions and regional contributions from seasonal monsoons have been reported (Chen et al., 2015, Kuo et al., 2010, Kuo et al., 2013, Lin et al., 2004). As a result, a number of protests against the poor air quality of PM2.5 have been launched by residents and environmentalists who claim that their inhaled PM2.5 is predominantly from surrounding industrial emissions which is likely to induce adverse health effects. In response to public concerns about environmental health, numerous investigations on particulate air pollutants and associated metals/PAHs have been conducted in this disputed area (Chen et al., 2015, Chen et al., 2016; Hsu et al., 2016, Kuo et al., 2013, Liao et al., 2015). However, significant gaps to be filled still exit, such as the lack of systematically comprehensive investigations on employing PM2.5 chemical profiles with spatiotemporal variations and the relevant source apportionment.
The receptor-based source apportionment of PM, which can identify source categories and quantify source contributions, has been widely performed worldwide (Belis et al., 2013, Viana et al., 2008). One technique, positive matrix factorization (PMF) based on the contents of ionic components, carbons and trace metals in particles has been increasingly applied in many studies (Contini et al., 2014, Stortini et al., 2009, Tao et al., 2014) due to its advantages over other receptor models (Liang et al., 2016). It is recommended that the conditional probability function (CPF) and potential source contribution function (PSCF) can be incorporated with PMF results to qualify the contribution of each identified local and long-range transport source in a more accurate way (Heo et al., 2009, Kang et al., 2006, Kim et al., 2003, Lee and Hopke, 2006).
In addition, the associated outcomes/diseases (such as cardiopulmonary effects) on residents attributed to ambient PM2.5 and the resultant sources are not clear within this area, which is important for the development of control measures directly based on the health burden. Beyond the particle mass metric, many studies have also indicated that the toxicity responses or adverse health outcomes are related to the chemical constituents of PM2.5, which can be referred to specific emission sources (Bell et al., 2010, Chen and Lippmann, 2009, Franklin et al., 2008, Gehring et al., 2015). For instance, Bell et al. (2014) indicated that the risk of cardiovascular hospitalization is associated with PM2.5 calcium, black carbon, vanadium, and zinc, which could be further referred to the contribution of PM2.5 road dust. Thus, to develop more effective control strategies, the investigation of the PM2.5 source apportionment linking to the health effects is crucial. Given the described research gaps, a mission-oriented project of PM2.5 measurements and health impact analyses in Changhua and Yunlin Counties was conducted by the National Health Research Institutes in Taiwan. This study aimed to investigate the ambient PM2.5 with comprehensive analyses of its chemical composition, identify its potential contributors, and evaluate resultant respiratory physician visits. The assessment of the health impacts enables the estimations of both the burden of disease attributable to air pollution and the potential benefit from policies driven to improve the air quality (Boldo et al., 2006, Kunzli et al., 2000). This study also sought to propose a PM2.5 control measure from sources in accordance with the abatement of the health burden.
Section snippets
Sampling sites and PM2.5 collection
The sampling was conducted in residential areas of Changhua (23° 53′ N, 120° 23′ E, 16 m above sea level) and Yunlin Counties (23° 42′ N, 120° 22′ E, 8 m above sea level) in central Taiwan. The selected sampling sites are within approximately 20 km radius of the Mailiao petrochemical complex (which is the largest oil refinery in Taiwan and the largest naphtha cracking plant in the world) containing a coal-fired power plant (ranked No. 8 worldwide in terms of carbon dioxide emissions). The sites
PM2.5 mass concentrations and chemical compositions
Table 1 shows a statistical description of the annual and seasonal concentrations for PM2.5 mass, and associated OC, EC, water-soluble ions and metals obtained from the selected sampling sites. Based on the coefficient of divergence (CD) results (ranging from 0.13 to 0.26; see Fig. S2 in the Supplementary material and the methods), the low spatial heterogeneity among sampling sites (A–F) for the concentrations of PM2.5 mass and chemical compositions allows us to integrate those data for further
Conclusion
Our study provided comprehensive results on the chemical constituents of PM2.5 with spatial and seasonal variations. While a low spatial contract in PM2.5 and associated chemical concentrations was observed in a residential area near industrial complexes in central Taiwan, the seasonal variation showed that those were higher in the winter than in the spring or summer. Our result also clarified the contributions of potential PM2.5 sources in this area. In addition to nearby oil refinery plants
Acknowledgements
The authors acknowledge the funding support from the National Environmental Health Research Center, National Health Research Institutes (NHRI) in Taiwan (grant number: EH-PP07-104). The authors also acknowledge the NOAA Air Resources Laboratory (ARL) for its HYSPLIT transport and dispersion model and READY website (http://www.ready.noaa.gov) available to the public.
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