Abstract
Zhengzhou is one of the most heavily polluted cities in China. This study collected samples of PM2.5 (atmospheric fine particulate matter with aerodynamic diameter ≤ 2.5 μm) at five sites in different functional areas of Zhengzhou in 2016 to investigate the chemical properties and sources of PM2.5 at three pollution levels, i.e., PM2.5 ≤ 75 μg/m3 (non-pollution, NP), 75 μg/m3 < PM2.5 ≤ 150 μg/m3 (moderate pollution, MP), and PM2.5 > 150 μg/m3 (heavy pollution, HP). Chemical analysis was conducted, and source categories and potential source region were identified for PM2.5 at different pollution levels. The health risks of toxic elements were evaluated. Results showed that the average PM2.5 concentration in Zhengzhou was 119 μg/m3, and the sum of the concentrations of SO42−, NO3−, and NH4+ increased with the aggravation of pollution level (23, 42, and 114 μg/m3 at NP, MP, and HP days, respectively). Positive Matrix Factorization analysis indicated that secondary aerosols, coal combustion, vehicle traffic, industrial processes, biomass burning, and dust were the main sources of PM2.5 at three pollution levels, and accounted for 38.4%, 21.6%, 16.7%, 7.4%, 7.7%, and 8.1% on HP days, respectively. Trajectory clustering analysis showed that close-range transport was one of the dominant factors on HP days in Zhengzhou. The potential source areas were mainly located in Xinxiang, Kaifeng, Xuchang, and Pingdingshan. Significant risks existed in the non-carcinogenic risk of As (1.4–2.3) for children at three pollution levels and the non-carcinogenic risk of Pb (1.0–1.4) for children with NP and MP days.
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Data availability
The datasets used during the current study are available from the corresponding author on reasonable request (jiangn@zzu.edu.cn).
References
AEA (2011) UK emissions of air pollutants 1970 to 2009. UK Emissions Inventory Team, Department for Environment, Food and Rural Affairs. http://ukair.defra.gov.uk/reports/cat07/1401131501_NAEI_Annual_Report_2009.pdf. Accessed 22 December 2019
Almeida SM, Freitas MC, Pio CA (2008) Neutron activation analysis for identification of African mineral dust transport. Radioanal Nucl Chem 276:161–165. https://doi.org/10.1007/s10967-007-0426-4
Almeida SM, Lage J, Fernandez B, Garcia S, Reis MA, Chaves PC (2015) Chemical characterization of atmospheric particles and source apportionment in the vicinity of a steelmaking industry. Sci Total Environ 521-522:411–420. https://doi.org/10.1016/j.scitotenv.2015.03.112
Andreae MO, Rosenfeld D (2008) Aerosol–cloud–precipitation interactions. part 1. The nature and sources of cloud-active aerosols. Earth Sci Rev 89:13–41. https://doi.org/10.1016/j.earscirev.2008.03.001
Bhangare RC, Ajmal PY, Sahu SK, Pandit GG, Puranik VD (2011) Distribution of trace elements in coal and combustion residues from five thermal power plants in India. Int J Coal Geol 86:349–356. https://doi.org/10.1016/j.coal.2011.03.008
Bureau of Statistics of Henan Province (2017) Henan Statistical Yearbook 2017. China Statistics Press, Beijing (in Chinese). http://www.ha.stats.gov.cn/hntj/lib/tjnj/2017/indexch.htm. Accessed 20 December 2019
Bureau of Statistics of Zhengzhou (2017) Statistical Bulletins on National Economic and Social Development of Zhengzhou in 2016 (in Chinese). http://tjj.zhengzhou.gov.cn/tjgb/418270.jhtml. Accessed 25 December 2019
Cakmak S, Dales R, Kauri LM, Mahmud M, Van Ryswyk K, Vanos J, Liu L, Kumarathasan P, Thomson E, Vincent R, Weichenthal S (2014) Metal composition of fine particulate air pollution and acute changes in cardiorespiratory physiology. Environ Pollut 189:208–214. https://doi.org/10.1016/j.envpol.2014.03.004
Canha N, Freitas MC, Almeida-Silva M, Almeida SM, Dung HM, Dionísio I, Cardoso J, Pio CA, Caseiro A, Verburg TG, Wolterbeek HT (2012) Burn wood influence on outdoor air quality in a small village: foros de Arrao, Portugal. Radioanal Nucl Chem 291:83–88. https://doi.org/10.1007/s10967-011-1261-1
Cao JJ, Wu F, Chow JC, Lee SC (2005) Characterization and source apportionment of atmospheric organic and elemental carbon during fall and winter of 2003 in Xi’an, China. Atmos Chem Phys 5(11):3127–3137. https://doi.org/10.5194/acp-5-3127-2005
Chen J, Wei F, Zheng C, Wu Y, Adriano DC (1991) Background concentrations of elements in soils of China. Water Air Soil Pollut 57-58:699–712. https://doi.org/10.1007/BF00282934
Chen Y, Zhi G, Feng Y, Fu J, Feng J, Sheng G, Simoneit BRT (2006) Measurements of emission factors for primary carbonaceous particles from residential raw-coal combustion in China. Geophys Res Lett 33:L20815. https://doi.org/10.1029/2006gl026966
Chen ZY, Cai J, Gao BB, Xu B, Dai S, He B, Xie XM (2017) Detecting the causality influence of individual meteorological factors on local PM2.5 concentration in the Jing-Jin-Ji region. Sci Rep 7:40735. https://doi.org/10.1038/srep40735
Chow JC, Watson JG, Lu Z, Lowenthal DH, Frazier CA, Solomon PA, Thuillier RH, Magliano K (1996) Descriptive analysis of PM2.5 and PM10 at regionally representative locations during SJVAQS/ AUSPEX. Atmos Environ 30:2079–2112. https://doi.org/10.1016/1352-2310(95)00402-5
Chow JC, Bachmann JD, Wierman SSG, Mathai CV, Malm WC, White WH, Mueller PK, Kumar N, Watson JG (2002) Visibility: science and regulation. J Air Waste Manage Assoc 52:973–999. https://doi.org/10.1080/10473289.2002.10470844
Coyle YM, Minahjuddin AT, Hynan LS, Minna JD (2006) An ecological study of the association of metal air pollutants with lung cancer incidence in Texas. J Thorac Oncol 1:654–661. https://doi.org/10.1016/s1556-0864(15)30377-4
Dai QL, Bi XH, Liu BS, Li LW, Ding J, Song WB, Bi SY, Schulze BC, Song CB, Wu JH, Zhang YF, Feng YC, Hopke PK (2018) Chemical nature of PM2.5 and PM10 in Xi’an, China: Insights into primary emissions and secondary particle formation. Environ Pollut 240:155–166. https://doi.org/10.1016/j.envpol.2018.04.111
Feng JL, Yu H, Mi K, Su XF, Li Y, Li QL, Sun JH (2018) One year study of PM2.5 in Xinxiang city, North China: seasonal characteristics, climate impact and source. Ecotoxicol Environ Saf 154:75–83. https://doi.org/10.1016/j.ecoenv.2018.01.048
Fu QY, Zhuang GS, Wang J, Xu C, Huang K, Li J, Hou B, Lu T, Streets DG (2008) Mechanism of formation of the heaviest pollution episode ever recorded in the Yangtze River Delta, China. Atmos Environ 42:2023–2036. https://doi.org/10.1016/j.atmosenv.2007.12.002
Gildemeister AE, Hopke PK, Kim EG (2007) Sources of fine urban particulate matter in Detroit, MI. Chemosphere 69:1064–1074. https://doi.org/10.1016/j.chemosphere.2007.04.027
Han Y, Kim H, Cho S, Kim P, Kim W (2015) Metallic elements in PM2.5 in different functional areas of Korea: concentrations and source identification. Atmos Res 153:416–428. https://doi.org/10.1016/j.atmosres.2014.10.002
Heo JB, Hopke P, Yi SM (2009) Source apportionment of PM2.5 in Seoul, Korea. Atmos Chem Phys 9:4957–4971. https://doi.org/10.5194/acpd-8-20427-2008
Hleis D, Fernandez-Olmo I, Ledoux F, Kfoury A, Courcot L, Desmonts T, Courcot D (2013) Chemical profile identification of fugitive and confined particle emissions from an integrated iron and steel making plant. J Hazard Mater 250-251:246–255. https://doi.org/10.1016/j.jhazmat.2013.01.080
Hsu CY, Chiang HC, Lin SL, Chen MJ, Lin TY, Chen YC (2016) Elemental characterization and source apportionment of PM10 and PM2.5 in the western coastal area of central Taiwan. Sci Total Environ 541:1139–1150. https://doi.org/10.1016/j.scitotenv.2015.09.122
Huang XJ, Liu ZR, Zhang JK, Wen TX, Ji DS, Wang YS (2016) Seasonal variation and secondary formation of size-segregated aerosol water-soluble inorganic ions during pollution episodes in Beijing. Atmos Res 168:70–79. https://doi.org/10.1016/j.atmosres.2015.08.021
Huang XJ, Liu ZR, Liu JY, Hu B, Wen TX, Tang GQ, Zhang JK, Wu FK, Ji DS, Wang LL, Wang YS (2017) Chemical characterization and synergetic source apportionment of PM2.5 at multiple sites in the Beijing-Tianjin-Hebei region, China. Atmos Chem Phys 17(21):1–34. https://doi.org/10.5194/acp-2017-446
Jiang N, Guo Y, Wang Q, Kang PR, Zhang RQ, Tang XY (2017) Chemical composition characteristics of PM2.5 in three cities in Henan, central China. Aerosol Air Qual Res 17:2367–2380. https://doi.org/10.4209/aaqr.2016.10.0463
Jiang N, Li Q, Su FC, Wang Q, Yu X, Kang PR, Zhang RQ, Tang XY (2018a) Chemical characteristics and source apportionment of PM2.5, between heavily polluted days and other days in Zhengzhou, China. Environ Sci 66:188–198. https://doi.org/10.1016/j.jes.2017.05.006
Jiang N, Yin SS, Guo Y, Li JY, Kang PR, Zhang RQ, Tang XY (2018b) Characteristics of mass concentration, chemical composition, source apportionment of PM2.5 and PM10 and health risk assessment in the emerging megacity in China. Atmos Pollut Res 9:309–321. https://doi.org/10.1016/j.apr.2017.07.005
Jiang N, Dong Z, Xu YQ, Yu F, Yin SS, Zhang RQ, Tang XY (2018c) Characterization of PM10 and PM2.5 source profiles for fugitive dust in Zhengzhou, China. Aerosol Air Qual Res 18:314–329. https://doi.org/10.1016/S1352-2310(02)01028-2
Jiang N, Duan SG, Yu X, Zhang RQ, Wang K (2018d) Comparative major components and health risks of toxic elements and polycyclic aromatic hydrocarbons of PM2.5 in winter and summer in Zhengzhou: Based on three-year data. Atmos Res 213:173–184. https://doi.org/10.1016/j.atmosres.2018.06.008
Jiang N, Liu XH, Wang SS, Yu X, Yin SS, Duan SG, Wang SB, Zhang RQ, Li SL (2019) Pollution characterization, source identification, and health risks of atmospheric-particle-bound heavy metals in PM10 and PM2.5 at multiple sites in an emerging megacity in the central region of China. Aerosol Air Qual Res 19:247–271. https://doi.org/10.4209/aaqr.2018.07.0275
Khan MF, Latif MT, Saw WH, Amil N, Nadzir MSM, Sahani M, Tahir NM, Chung JX (2016) Fine particulate matter in the tropical environment: monsoonal effects, source apportionment, and health risk assessment. Atmos Chem Phys 16:597–617. https://doi.org/10.5194/acp-16-597-2016
Kim EG, Hopke PK (2008) Source characterization of ambient fine particles at multiple sites in the Seattle area. Atmos Environ 42:6047–6056. https://doi.org/10.1016/j.atmosenv.2008.03.032
Li Q, Jiang N, Yu X, Dong Z, Duan SG, Zhang RQ (2019) Sources and spatial distribution of PM2.5-bound polycyclic aromatic hydrocarbons in Zhengzhou in 2016. Atmos Res 216:65–75. https://doi.org/10.1016/j.atmosres.2018.09.011
Liang CS, Duan FK, He KB, Ma YL (2016) Review on recent progress in observations, source identifications and countermeasures of PM2.5. Environ Int 86:150–170. https://doi.org/10.1016/j.envint.2015.10.016
Lin YC, Tsai CJ, Wu YC, Zhang R, Chi KH, Huang YT, Lin SH, Hsu SC (2015) Characteristics of trace metals in traffic-derived particles in Hsuehshan Tunnel, Taiwan: size distribution, potential source, and finger printing metal ratio. Atmos Chem Phys 15:4117–4130. https://doi.org/10.5194/acp-15-4117-2015
Liu JW, Li J, Zhang YL, Liu D, Ding P, Shen CD, Shen KJ, He QF, Ding X, Wang XM, Chen DH, Szidat S, Zhang G (2014) Source apportionment using radiocarbon and organic tracers for PM2.5 carbonaceous aerosols in Guangzhou, South China: contrasting local- and regional-scale haze events. Environ Sci Technol 48:12002–12011. https://doi.org/10.1021/es503102w
Liu G, Li JH, Wu D, Xu H (2015) Chemical composition and source apportionment of the ambient PM2.5 in Hangzhou, China. Particuology 18:135–143. https://doi.org/10.1016/j.partic.2014.03.011
Liu BS, Song N, Dai QL, Mei RB, Sui BH, Bi XH, Feng YC (2016) Chemical composition and source apportionment of ambient PM2.5 during the nonheating period in Taian, China. Atmos Res 170:23–33. https://doi.org/10.1016/j.atmosres.2015.11.002
Liu BS, Wu JH, Zhang JY, Wang L, Yang JM, Liang DN, Dai QL, Bi XH, Feng YC, Zhang YF, Zhang QX (2017) Characterization and source apportionment of PM2.5 based on error estimation from EPA PMF 5.0 model at a medium city in China. Environ Pollut 222:10–22. https://doi.org/10.1016/j.envpol.2017.01.005
Liu B, Cheng Y, Zhou M, Liang D, Dai Q, Wang L, Jin W, Zhang L, Ren Y, Zhou J, Dai C, Xu J, Wang J, Feng Y, Zhang Y (2018) Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China. Atmos Chem Phys 18:7019–7039. https://doi.org/10.5194/acp-2017-1001
Liu XH, Jiang N, Yu X, Zhang RQ, Li SL, Li Q, Kang PR (2019) Chemical characteristics, sources apportionment, and risk assessment of PM2.5 in different functional areas of an emerging megacity in China. Aerosol Air Qual Res 19:2222–2238. https://doi.org/10.4209/aaqr.2019.02.0076
López ML, Ceppi S, Palancar GG, Olcese LE, Tirao G, Toselli BM (2011) Elemental concentration and source identification of PM10 and PM2.5 by SR-XRF in Córdoba City, Argentina. Atmos Environ 45:5450–5457. https://doi.org/10.1016/j.atmosenv.2011.07.003
Lough GC, Schauer JJ, Park JS, Shafer MM, DeMinter JT, Weinstein JP (2004) Emissions of metals associated with motor vehicle roadways. Environ Sci Technol 39:826–836. https://doi.org/10.1021/es048715f
Ma ZZ, Li Z, Jiang JK, Ye ZX, Deng JG, Duan L (2015) Characteristics of water-soluble inorganic ions in PM2.5 emitted from coal-fired power plants. Environ Sci. (in Chinese) 36:2361–2366. https://doi.org/10.13227/j.hjkx.2015.03.047
Manousakas M, Papaefthymiou H, Diapouli E, Migliori A, Karydas AG, Bogdanovic-Radovic I, Bogdanovic-Radovic K (2017) Assessment of PM2.5 sources and their corresponding level of uncertainty in a coastal urban area using EPA PMF 5.0 enhanced diagnostics. Sci Total Environ 574:155–164. https://doi.org/10.1016/j.scitotenv.2016.09.047
Ministry of Environmental Protection of the People’s Republic of China (2012) Technical Regulation on Ambient Air Quality Index (on trial) http://bz.mee.gov.cn/bzwb/jcffbz/201203/t20120302_224166.shtml Accessed 20 December 2019
Morishita M, Gerald J, Keeler GJ, Kamal AS, Wagner JG, Harkem JR, Rohr AC (2011) Source identification of ambient PM2.5 for inhalation exposure studies in Steubenville, Ohio using highly time-resolved measurements. Atmos Environ 45:7688–7697. https://doi.org/10.1016/j.atmosenv.2010.12.032
Nolting RF, Ramkema A, Everaarts JM (1999) The geochemistry of Cu, Cd, Zn, Ni and Pb in sediment cores from the continental slope of the Bancd’ Arguin (Mauritania). Cont Shelf Res 19:665–691. https://doi.org/10.1016/s0278-4343(98)00109-5
Ogulei D, Hopke PK, Zhou JL, Paatero P, Park SS, John M (2005) Receptor modeling for multiple time resolved species: the Baltimore supersite. Atmos Environ 39:3751–3762. https://doi.org/10.1016/j.atmosenv.2005.03.012
Ogulei D, Hopke PK, Zhou JL, Pancras P, Nair N, Ondov JM (2006) Source apportionment of Baltimore aerosol from combined size distribution and chemical composition data. Atmos Environ 40:396–410. https://doi.org/10.1016/j.atmosenv.2005.11.075
Paatero P, Tapper U (1994) Positive matrix factorization: a non-negative factor model with optimal utilization of error estimates of data values. Environ Metrics 5:111–126. https://doi.org/10.1002/env.3170050203
Paatero P, Eberly S, Brown SG, Norris GA (2014) Methods for estimating uncertainty in factor analytic solutions. Atmos Meas Tech 7:781–797. https://doi.org/10.5194/amt-7-781-2014
Reff A, Eberly SI, Bhave PV (2007) Receptor modeling of ambient particulate matter data using positive matrix factorization: review of existing methods. J Air Waste Manage Assoc 57:146–154. https://doi.org/10.1080/10473289.2007.10465319
Rogula-Kozłowska W, Błaszczak B, Szopa S, Klejnowski K, Sowka I, Zwozdziak A, Jabłonska M, Mathews B (2013) PM2.5 in the central part of Upper Silesia, Poland: concentrations, elemental composition, and mobility of components. Environ Monit Assess 185:581–601. https://doi.org/10.1007/s10661-012-2577-1
Schauer JJ, Kleeman MJ, Cass GR, Simoneit BR (2002) Measurement of emissions from air pollution sources. 5. C1-C32 organic compounds from gasoline-powered motor vehicles. Environ Sci Technol 35:1716–1728. https://doi.org/10.1021/es0108077
Schleicher NJ, Norra S, Chai F, Chen Y, Wang S, Cen K, Yu Y, Stueben D (2011) Temporal variability of trace metal mobility of urban particulate matter from Beijing-a contribution to health impact assessments of aerosols. Atmos Environ 45:7248–7265. https://doi.org/10.1016/j.atmosenv.2011.08.067
Shafer MM, Toner BM, Overdier JT, Schauer JJ, Fakra SC, Hu S, Herner JD, Ayala A (2012) Chemical speciation of vanadium in particulate matter emitted from diesel vehicles and urban atmospheric aerosols. Environ Sci Technol 46:189–195. https://doi.org/10.1021/es200463c
Simon H, Bhave PV, Swall JL, Frank NH, Malm WC (2011) Determining the spatial and seasonal variability in OM/OC ratios across the US using multiple regression. Atmos Chem Phys 11:2933–2949. https://doi.org/10.5194/acp-11-2933-2011
Srimuruganandam B, Nagendra SMS (2012) Application of positive matrix factorization in characterization of PM10 and PM2.5 emission sources at urban roadside. Chemosphere 88:120–130. https://doi.org/10.1016/j.chemosphere.2012.02.083
Subramanian R, Donahue NM, Bricker AB, Rogge WF, Robinson AL (2007) Insights into the primary–secondary and regional-local contribution to organic aerosol and PM2.5 mass in Pittsburgh, Pennsylvania. Atmos Environ 41:7414–7433. https://doi.org/10.1016/j.atmosenv.2007.05.058
Tan J, Duan J, He K, Ma Y, Duan F, Chen Y, Fu J (2009) Chemical characteristics of PM2.5 during a typical haze episode in Guangzhou. Environ Sci 21:774–781. https://doi.org/10.1016/s1001-0742(08)62340-2
Tang GQ, Zhang JQ, Zhu XW, Song T, Münkel C, Hu B, Schäfer K, Liu Z, Zhang JK, Wang LL, Xin JY, Suppan P, Wang YS (2016) Mixing layer height and its implications for air pollution over Beijing, China. Atmos Chem Phys 16:2459–2475. https://doi.org/10.5194/acp-16-2459-2016
Tao J, Cheng TT, Zhang RJ, Cao JJ, Zhu LH, Wang QY, Luo L, Zhang LM (2013) Chemical composition of PM2.5 at an urban site of Chengdu in southwestern China. Adv Atmos Sci 30:1070–1084. https://doi.org/10.1007/s00376-012-2168-7
Tao J, Zhang LM, Ho KF, Zhang RJ, Lin ZJ, Zhang ZS, Lin M, Cao JJ, Liu SX, Wang GH (2014) Impact of PM2.5 chemical compositions on aerosol light scattering in Guangzhou-the largest megacity in South China. Atmos Res 135-136:48–58. https://doi.org/10.1016/j.atmosres.2013.08.015
Tian YZ, Chen G, Wang HT, Huang-Fu YQ, Shi GL, Han B, Feng YC (2016) Source regional contributions to PM2.5 in a megacity in China using an advanced source regional apportionment method. Chemosphere 147:256–263. https://doi.org/10.1016/j.chemosphere.2015.12.132
Tullio AD, Reale S, Ciammola M, Arrizza L, Picozzi P, De Angelis F (2008) Characterization of atmospheric particulate: relationship between chemical composition, size and emission source. ChemSusChem. 1:110–117. https://doi.org/10.1002/cssc.200700056
Turpin BJ, Huntzicker JJ (1995) Identification of secondary organic aerosol episodes and quantitation of primary and secondary organic aerosol concentrations during SCAQS. Atmos Environ 29:3527–3544. https://doi.org/10.1016/1352-2310(94)00276-q
U.S. EPA (1989) Risk assessment guidance for superfund. In: Part A: Human Health Evaluation Manual. https://www.epa.gov/risk/risk-assessment-guidance-superfund-rags-part. Accessed 22 December 2019
U.S. EPA (2004) Risk assessment guidance for superfund. In: Part E, Supplemental guidance for dermal risk assessment. https://www.epa.gov/risk/risk-assessment-guidance-superfund-rags-part-e. Accessed 22 December 2019
U.S. EPA (2009) Risk assessment guidance for superfund. In: Part F, Supplemental Guidance for Inhalation Risk Assessment. https://www.epa.gov/risk/risk-assessment-guidance-superfund-rags-part-f. Accessed 22 December 2019
U.S. EPA (2011a) The screening level (RSL) Tables (last updated June 2011). Available on-line at: http://www.epa.gov/region9/superfund/prg/index.html Accessed 15 February 2020
U.S. EPA (2011b) User’s guide and background technical document for US EPA region 9's Preliminary remediation goals (PRG) table. http://www.epa.gov/reg3hwmd/risk/human/rb-concentrationtable/usersguide.htm Accessed 15 February 2020
U.S. EPA (2014) Positive Matrix Factorization (PMF) 5.0 Fundamentals and User Guide. Office of Research and Development, Washington, DC. https://www.epa.gov/sites/production/files/2015-02/documents/pmf_5.0_user_guide.pdf Accessed 15 February 2020
Wang AQ (2016) Pollution characteristics of air fine particulate matter (PM2.5) in Xuchang. Environ Sci Manag (in Chinese) 41:139–141. https://doi.org/10.3969/j.issn.1673-1212.2016.01.039
Wang Y, Zhuang GS, Sun YL, An ZS (2006) The variation of characteristics and formation mechanisms of aerosols in dust, haze, and clear days in Beijing. Atmos Environ 40:6579–6591. https://doi.org/10.1016/j.atmosenv.2006.05.066
Wang LT, Wei Z, Yang J, Zhang Y, Zhang FF, Su J, Meng CC, Zhang Q (2014) The 2013 severe haze over southern Hebei, China: model evaluation, source apportionment, and policy implications. Atmos Chem Phys 14:3151–3173. https://doi.org/10.5194/acp-14-3151-2014
Wang J, Li X, Jiang N, Zhang W, Zhang R, Tang X (2015) Long term observations of PM2.5-associated PAHs: comparisons between normal and episode days. Atmos Environ 104:228–236. https://doi.org/10.1016/j.atmosenv.2015.01.026
Wang F, Guo Z, Lin T, Rose NL (2016) Seasonal variation of carbonaceous pollutants in PM2.5 at an urban ‘supersite’ in Shanghai, China. Chemosphere 146:238–244. https://doi.org/10.1016/j.chemosphere.2015.12.036
Wang LM, Wang XY, Wang MS, Yu GQ, Liu XY, Wang ZF, Pan XL (2020a) Spatial and temporal distribution and potential source of atmospheric pollution in Jiaozuo City. Res Environ Sci (in Chinese) 33(4):820–830. https://doi.org/10.13198/j.issn.1001-6929.2019.04.22
Wang Q, Dong Z, Guo Y, Yu F, Zhan ZY, Zhang RQ (2020b) Characterization of PM2.5-bound polycyclic aromatic hydrocarbons at two central China cities: seasonal variation, sources, and health risk assessment. Arch Environ Contam Toxicol 78(1):20–33. https://doi.org/10.1007/s00244-019-00671-4
Widory D (2006) Lead isotopes decipher multiple origins within single PM10 samples in the atmosphere of Paris. Isot Environ Health Stud 42:97–105. https://doi.org/10.1080/10256010500502736
Yang Y, Wang Y, Huang W, Hu B, Wen T, Zhao Y (2010) Size distributions and elemental compositions of particulate matter on clear, hazy and foggy days in Beijing, China. Adv Atmos Sci 27:663–675. https://doi.org/10.1007/s00376-009-8197-1
Yang YR, Liu XG, Qu Y, An JL, Jiang R, Zhang YH, Sun YL, Wu ZJ, Zhang F, Xu WQ, Ma QX (2015) Characteristics and formation mechanism of continuous hazes in China: a case study during the autumn of 2014 in the North China Plain. Atmos Chem Phys 15:8165–8178. https://doi.org/10.5194/acp-15-8165-2015
Yao L, Yang LX, Yuan Q, Yan C, Dong C, Meng CP, Sui X, Yang F, Lu YL, Wang WX (2016) Sources apportionment of PM2.5 in a background site in the North China Plain. Sci Total Environ 541:590–598. https://doi.org/10.1016/j.scitotenv.2015.09.123
Zhang YX, Shao M, Zhang YH, Zeng LM, He LY, Zhu B, Wei YJ, Zhu XL (2007) Source profiles of particulate organic matters emitted from cereal straw burnings. J Environ Sci 19:167–175. https://doi.org/10.1016/S1001-0742(07)60027-8
Zhang R, Jing J, Tao J, Hsu SC, Wang G, Cao J, Lee CSL, Zhu L, Chen Z, Zhao Y, Shen Z (2013) Chemical characterization and source apportionment of PM2.5 in Beijing: seasonal perspective. Atmos Chem Phys 13:7053–7074. https://doi.org/10.5194/acp-13-7053-2013
Zhang RY, Wang GH, Guo S, Zamora ML, Ying Q, Lin Y, Wang WG, Hu M, Wang Y (2015a) Formation of urban fine particulate matter. Chem Rev 115:3803–3855. https://doi.org/10.1021/acs.chemrev.5b00067
Zhang F, Wang ZW, Cheng HR, Lv XP, Gong W, Wang XM, Zhang G (2015b) Seasonal variations and chemical characteristics of PM2.5 in Wuhan, central China. Sci Total Environ 518-519:97–105. https://doi.org/10.1016/j.scitotenv.2015.02.054
Zhao XJ, Zhang XL, Xu XF, Xu J, Meng W, Pu WW (2009) Seasonal and diurnal variations of ambient PM2.5 concentration in urban and rural environments in Beijing. Atmos Environ 43:2893–2900. https://doi.org/10.1016/j.atmosenv.2009.03.009
Zhao XJ, Zhao PS, Xu J, Meng W, Pu WW, Dong F, He D, Shi QF (2013) Analysis of a winter regional haze event and its formation mechanism in the North China Plain. Atmos Chem Phys 13:5685–5696. https://doi.org/10.5194/acp-13-5685-2013
Zheng M, Zhang Y, Yan C, Zhu X, Schauer JJ, Zhang Y (2014) Review of PM2.5 source apportionment methods in China (in Chinese). Acta Sci Nat Univ Pekin 50:1141–1154. https://doi.org/10.13209/j.0479-8023.2014.068
Funding
The study was supported by the financial support from the National Natural Science Foundation of China (51808510, 51778587), National Key Research and Development Program of China (2017YFC0212400), and Natural Science Foundation of Henan Province of China (162300410255).
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NJ, RZ, and SL conceived and designed the study; XL analyzed the date and wrote the paper; XY and QM performed aerosol sampling and date analyses.
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Highlights
• The mean levels of PM2.5 on NP, MP, and HP days were 52, 107, and 253 μg/m3.
• OC/EC ratios of 8.2, 7.6, and 9.8 were recorded on NP, MP, and HP days.
• The SAs had the highest contributions during every pollution levels.
• Significant non-carcinogenic risk of As and Pb exists for children.
• Risks of toxic elements on HP days were greater than those on the other days.
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Liu, X., Jiang, N., Zhang, R. et al. Composition analysis of PM2.5 at multiple sites in Zhengzhou, China: implications for characterization and source apportionment at different pollution levels. Environ Sci Pollut Res 28, 59329–59344 (2021). https://doi.org/10.1007/s11356-020-10943-5
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DOI: https://doi.org/10.1007/s11356-020-10943-5