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Health Risk Assessment of China's Main Air Pollutants

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Health Risk Assessment of China's Main Air Pollutants Sun and Zhou BMC Public Health (2017) 17:212 DOI 10.1186/s12889-017-4130-1 RESEARCHARTICLE Open Access Health risk assessment of China’s main air pollutants Jian Sun1* and Tiancai Zhou1,2 Abstract Background: With the rapid development of China’s economy, air pollution has attracted public concern because of its harmful effects on health. Methods: The source apportioning of air pollution, the spatial distribution characteristics, and the relationship between atmospheric contamination, and the risk of exposure were explored. The in situ daily concentrations of the principal air pollutants (PM2.5,PM10,SO2,NO2, CO and O3) were obtained from 188 main cities with many continuous air-monitoring stations across China (2014 and 2015). 2 Results: The results indicate positive correlations between PM2.5 and SO2 (R = 0.395/0.404, P < 0.0001), 2 2 CO (R = 0.187/0.365, P < 0.0001), and NO2 (R = 0.447/0.533, P < 0.0001), but weak correlations with O3 (P > 0.05) for both 2014 and 2015. Additionally, a significant relationship between SO2,NO2, and CO was discovered using regression analysis (P < 0.0001), indicating that the origin of air pollutants is likely to be vehicle exhaust, coal consumption, and biomass open-burning. For the spatial pattern of air pollutants, we found that the highest concentration of SO2,NO2, and CO were mainly distributed in north China (Beijing-Tianjin-Hebei regions), Shandong, Shanxi and Henan provinces, part of Xinjiang and central Inner Mongolia (2014 and 2015). Conclusions: The highest concentration and risk of PM2.5 was observed in the Beijing–Tianjin–Hebei economic belts, and Shandong, Henan, Shanxi, Hubei and Anhui provinces. Nevertheless, the highest concentration of O3 was irregularly distributed in most areas of China. A high-risk distribution of PM10,SO2 and NO2 was also observed in these regions, with the high risk of PM10 and NO2 observed in the Hebei and Shandong province, and high-risk of PM10 in Urumchi. The high-risk of NO2 distributed in Beijing-Yangtze River Delta region-Pearl River Delta region-central. Although atmospheric contamination slightly improved in 2015 compared to 2014, humanity faces the challenge of reducing the environmental and public health effects of air pollution by altering the present mode of growth to achieve sustainable social and economic development. Keywords: Air pollutants, Haze, Spatial patterns, Health risk, China Background (the incomplete combustion of carbonaceous combusti- Haze is principally formed by an increase in particle size bles) [1], dust, sea salt [2], heavy metals, and polycyclic in the atmospheric medium, which affects atmospheric aromatic hydrocarbon [3]. Haze incidents are a relatively absorption, emission, and scattering of light. PM2.5:fine new threat to human health [4], air quality [5], global inhalable particles, with diameters that are generally 2.5 climate change [6], ecological suitability for human settle- micrometers and smaller, and originates from construc- ment, and regional sustainable development. tion sites, unpaved roads, fields, smokestacks or fires, Recently, haze has become a principal environmental including congregated aerosols (e.g. sulfur dioxide, nitro- issue in China. Consequently, the causes of particulate gen dioxide, carbon monoxide, and so on), black carbon pollution have been discussed widely: e.g., secondary aerosol [5], aerosol optical properties [7], and aerosol * Correspondence: [email protected] chemical components [8]. And the formation and evolu- 1 Institute of Geographic Sciences and Natural Resources Research, Chinese tion mechanism of haze has been similarly explored [9]: Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China e.g., long-lasting haze occurrences in Nanjing [10], a Full list of author information is available at the end of the article © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Sun and Zhou BMC Public Health (2017) 17:212 Page 2 of 14 winter regional haze in the North China Plain [11], and temporal distribution of atmospheric contamination over the heavy haze pollution episode over central and eastern China, and monthly in every city to analyze the relation- China [12]. In addition, we know that understanding the ships among air pollutions for 2014 and 2015. origin of fine particulate matter is essential to finding ap- propriate strategies to combat haze and the harm it Method of health risk assessment causes. Thus, the source apportioning of fine particulate This study used the risk assessment method of the U.S. during the haze events in Shanghai [13], Harbin [14], and Environmental Protection Agency (EPA) [21], which Fuzhou [15] was implemented, and the characteristics of focused on the health risk assessment through inhalation atmospheric carbonyls were documented [16] in Beijing. pathway for three kinds of people (adult males, adult We have known for some time that haze boosts air females, and children), thus, avoided the effects of popu- pollution, causing significant harm to human health lation density. The assessment study focuses on the risk [17]. Previous studies have reported extensively on of exposure to air pollutants (PM10,SO2, and NO2)in cardiovascular disease, lung disease, exposure time, China; Ri was the individual health risk for exposure pol- mortality, and the mechanisms of biochemistry for haze. lution, calculated as Eq. 1 [22]: Short-term exposure was investigated in metropolitan ÀÁ ¼ Â −6= Â ð Þ areas [18], and the effects of dust-haze on mortality were Ri ADDopt 10 Rf dij 70 1 explored [19]. In fact, the relationship between haze and ADD was the average daily dose, calculated as respiratory diseases in Brunei Darussalam were analyzed, opt Eq. 2 [23]: and it was found that PM10 and CO levels have a signifi- cant bearing on the incidence of respiratory diseases ADDopt ¼ ðÞCA Â IR Â ED = ðÞðBW Â AT 2Þ [20]. In China, Sun et al. [4] explored the relationship − between economic development and air pollution, and where CA was the concentration (mg m 3) of air they found that the variation explained by both total pollutants, the average values of inhalation rate (IR), ED SO2 emissions and total smoke and dust emissions were (exposure duration in days) and AT (averaging exposure 33 and 24% of pertussis (whooping cough), respectively. time in days) were showed in Table 1 [22], and the aver- However, source apportioning of fine particulate re- age weight (BW) was obtained from national physical quires considerable investment in time and money. fitness test communiqués (http://www.gov.cn/test). The Thus, in this study, we attempt to analyze source appor- Rfdij (reference dose) values for PM10,SO2, and NO2 tioning using data mining. Because the risk of exposure referred to the U.S EPA (https://www3.epa.gov/). to haze across China has been insufficiently discussed, Based on the IDW (inverse distance weighted) the object of the present study is to address the relation- interpolation method to model the spatial distribution of ship between atmospheric contamination and human health risk in China, then, calculated the Rfdij values and health in China. Specifically, we seek to accomplish the reclassified by the national air quality standard to get the following: (1) to analyze the spatial-temporal distribution expose risk level of air pollutants. of atmospheric contamination over China; (2) to explore the source apportioning of fine particulate in China; and Tools of analysis (3) to analyze the relationship between atmospheric con- In the present study, the ArcGIS 10.2 (ESRI, Inc., Red- tamination and the risk of human exposure in China. lands, CA, USA) was used to draw spatial graphs, and SigmaPlot for Windows 10.0 (Systat Software, Inc., Methods Chicago, IL, USA) was used to conduct correlation and Data collection regression analysis. Correlations between different vari- All air measurements (SO2,NO2, CO, O3,PM10, and ables were determined using two-tailed Pearson’s Correl- PM2.5) were obtained from 188 main cities with continu- ation at 0.05 levels. ous air-monitoring stations (Fig. 1), the stations were set up accord with the standard “Technical regulation for Results selection of ambient air quality monitoring stations (HJ The size of main air pollutants 664–2013)”, and were obtained from the Ministry of As shown in Fig. 2, the frequency distribution of air pol- Environmental Protection of the People’s Republic of lutant (PM2.5,SO2, CO, NO2, and O3) concentrations in China (http://datacenter.mep.gov.cn/). The disease data of 2014 and 2015 was observed. The values of the PM2.5, −3 pertussis was collected from China Statistical Yearbook SO2, CO, NO2 and O3 range from 18.58 μgm to − − − (www.stats.gov.cn, 2004–2015) and China Statistical 130.46 μgm 3, from 2.17 μgm 3 to 117.82 μgm 3, from − − − Yearbook of Health and Family Planning (www.moh. 0.47 μgm3 to 2.42 mg m 3,from12.56μgm3 to − − − gov.cn, 2004–2015). In addition, the atmospheric contam- 66.09 μgm3,from48.78μgm3 to 198.61 μgm3,with − − − ination was compiled annual means to analyze the spatial- median values of 61.44 μgm 3,30.11μgm 3,1.12μgm 3, Sun and Zhou BMC Public Health (2017) 17:212 Page 3 of 14 Fig. 1 Study areas and the continuous air monitoring stations (CAMS) in China − − − 36.05 μgm3,103.97μgm3, respectively.
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