Evaluation of particulate matter deposition in the human respiratorytract during winter in Nanjing using size and chemically resolvedambient measurements

Xiaoyuan Liu1& Dongyang Nie1

& Kai Zhang1& Ziyao Wang1

& Xiaoqian Li1 & Zhihao Shi1 & Yiyi Wang1& Lin Huang1

&

Mindong Chen1& Xinlei Ge1 & Qi Ying2

& Xingna Yu3,4& Xingang Liu5

& Jianlin Hu1

Received: 22 October 2018 /Accepted: 2 January 2019# Springer Media B.V., onderdeel van Springer Nature 2019

AbstractSize-segregated ambient aerosols were collected by a five-stage impactor at a suburban Nanjing site during the winter of 2016–2017 to estimate the chemical composition and size distribution of particles deposited in different parts of the human respiratorytract. Chemical compositions of carbonaceous aerosols, water-soluble ions, and trace heavy metals were measured. Particulatematter (PM) mass deposited in nasopharyngeal (NOPL), tracheobronchial (TB), and pulmonary (P) was obtained by integratingthe size-dependent deposition fractions. During the sampling period, the average PM10 and PM2.5 concentrations were 108.8 ±30.8 and 77.2 ± 24.2 μg/m3, respectively. Organic matter and water-soluble ions were major components in fine particles. Thefine particles had a significant contribution to the particulate pollution in winter Nanjing. The mass concentration of particlesincreases significantly from the clean days to the pollution days, especially for particles in 1–2.5 μm. The proportion of NO3

− andundetected components in particulate matter increases on pollution days, while the proportion of elemental carbon (EC), SO4

2−,and NH4

+ decreases. During the study period, the total particulate matter deposit per minute in the NOPL, TB, and P was1.06 ± 0.35, 0.10 ± 0.03, and 0.42 ± 0.14 μg, respectively, assuming normal respiration of tidal volumes of 1450 cm3 per breathand 15 breaths per minute. Particles in 2.5–10 μm had the highest deposition mass in NOPL of 0.57 ± 0.16 μg, while particles in< 0.5 μm had the highest deposition mass in TB (0.03 ± 0.01 μg), and particles in 1–2.5 μm had the highest deposition mass in P(0.14 ± 0.06μg). The total particulate matter deposited in the NOPL, TB, and P increased from 0.79 ± 0.25, 0.08 ± 0.02, and 0.30± 0.09 μg on the clean days to 1.23 ± 0.29 μg, 0.12 ± 0.03 μg, and 0.49 ± 0.11 μg on the pollution days. More secondaryinorganic aerosol (SNA) and metals (especially Zn, Cr, and Cu) were in the PM deposited in TB and P than in the ambientPM, while more undetected components in the PM deposited in NOPL. The chemical composition fractions deposited in aspecific region were different from those measured in the ambient atmosphere, indicating that health effect studies of PM shouldconsider the deposition rates of PM in the human respiratory tract, in addition to the ambient size and chemical characteristics ofambient PM.

Keywords Size distribution . Chemical components . Inhalable particles . Deposition . Respiratory tract

Electronic supplementary material The online version of this article(https://doi.org/10.1007/s11869-019-00663-2) contains supplementarymaterial, which is available to authorized users.

* Jianlin Hujianlinhu@nuist.edu.cn

1 Collaborative Innovation Center of Atmospheric Environment andEquipment Technology, Jiangsu Key Laboratory of AtmosphericEnvironment Monitoring and Pollution Control, Nanjing Universityof Information Science & Technology, Nanjing 210044, China

2 Zachry Department of Civil Engineering, Texas A&M University,College Station, TX 77843, USA

3 Key Laboratory of Meteorological Disaster-Ministry of Education,Joint International Research Laboratory of Climate and EnvironmentChange, Collaborative Innovation Center on Forecast and Evaluationof Meteorological Disasters, Nanjing 210044, China

4 Key Laboratory for Aerosol-Cloud-Precipitation of ChinaMeteorological Administration, Nanjing University of InformationScience & Technology, Nanjing 210044, China

5 State Key Laboratory of Water Environment Simulation, School ofEnvironment, Beijing Normal University, Beijing 100875, China

Air Quality, Atmosphere & Healthhttps://doi.org/10.1007/s11869-019-00663-2

Introduction

Atmospheric particulate matter (PM) poses a great threat tohuman health. Epidemiological studies have shown that whenthe human body is exposed to high PM concentrations, thedeposition of particulate matter in the human body is one ofthe causes of the occurrence or aggravation of various diseases(Brook et al. 2002; Delfino et al. 2005; Simkhovich et al.2008; Vu et al. 2015). Long-term exposure to high concentra-tions of PM is associated with increases in morbidity andmortality (Zwozdziak et al. 2017; Nirmalkar and Deb 2016).PM has become one of the major air pollutants in China inrecent years (Chan and Yao 2008; Chen and Xie 2013). Due tothe severe PM pollution, it is estimated that fine PM (i.e.,PM2.5) can cause over 1.3 million premature deaths per yearin China (Hu et al. 2017; Lelieveld et al. 2015; Liu et al. 2016).

Atmospheric PM contains various chemical compositions,such as SO4

2−, NO3−, and NH4

+, heavy metals, mineral dust,elemental carbon (EC), and organic carbon (OC), etc. It hasbeen demonstrated that the health impacts of PM vary greatlywith its chemical composition (Ding et al. 2017; Zhao et al.2011). For examples, OC is rich in carcinogens and genotoxicmutagens, sulfuric acid damages human lung function, andtrace metals (such as Pb, Mn, Cd, Ni, Cr) are harmful to thehuman nervous system and can even lead to cancer and heartdisease (Li et al. 2014; Wu et al. 2012; Yang et al. 2012). Inaddition, ambient PM has a wide size distribution, rangingfrom a few nanometers to over 10 μm. The particle size isan important factor that determines the extent to which parti-cles enter and eventually deposit in the body through respira-tion (Li et al. 2016; Tian et al. 2016). The dominant particleremoval mechanism in the respiratory tract varies as a functionof particle size and depends on the geometry of different partsof the respiratory system (Ruzer and Harley 2004). The nasalcavity and oral cavity do not block PM2.5 and PM10 very well,about 50% of PM2.5 and PM10 particles penetrate through thenasal cavity and oral cavity respectively, and a small numberof particles with smaller particle size can penetrate deeper intothe human trachea and the lower respiratory tract (Chow et al.2012; Guo et al. 2016).

The Yangtze River Delta region is one of the regions inChina with the most severe PM pollution (Guo et al. 2016;Jiang et al. 2015). Nanjing is located at the west Yangtze RiverDelta. Previous studies have investigated the concentrationlevels, chemical compositions, and particle size distributionsof PM in Nanjing’s ambient atmosphere (Dan et al. 2016; Liet al. 2015; Wang et al. 2015; Wu et al. 2014). The resultsrevealed that Nanjing is also suffering from the severe hazepollution (visibility generally less than 2 km when relativehumidity below 80%), mainly due to high PM2.5 concentra-tions. The pollution is the most severe during winter (Hu et al.2014; Wang et al. 2014). Water-soluble ions are the maincomponents of PM2.5; components of OC, EC, SO4

2−, and

NH4+ and the elements Zn, Pb, Bi, Hg, Cd, Mn, and Cu are

more distributed in the fine particles, while components of F−,Cl−, Na, Mg, Al, Ca, Ti, Fe, As, and Ba are more concentratedin the coarse particles (Li et al. 2015; Qian et al. 2008; Wuet al. 2014; Xue et al. 2014).

Although size-resolved chemical measurements of parti-cles have been conducted in Nanjing and provided insightsabout the pollution characteristics, sources, and formationmechanisms, it has rarely been discussed how the PM chem-ical compositions change from ambient particles to depositionin the human body in this region. The objective of this study isto assess the PM compositions and size distributions retainedin the different parts of the human respiratory. To do that,concentrations and compositions of four PM fractions(PM2.5–10, PM1–2.5, PM0.5–1, and PM0.5) in ambient air weremeasured at a site in Nanjing. Then, the results were used asinputs to calculate the compositions of particles deposited inthe human respiratory tract. The study will help understandthe difference of the chemical characteristics between ambientparticles and particles deposited in the human respiratory tract.

Materials and methods

Experimental site

The sampling site was located on the campus of NanjingUniversity of Information Science and Technology (NUIST,32.2 N,118.7 E) in the northwest of Nanjing city, shown inFig. S1a in the Supplementary Materials. The site issurrounded by industrial and residential zone on the east andfarmland on the west. Two highways, Ningliu ExpresswayG205 on the east and Hushan Highway G40 on the west, areabout 1–2 km away from the site. Forty-eight-hour size-segregated PM samples were collected from 22 December2016 to 1 March 2017. A total of 52 samples were collectedduring the sampling period for data analysis, and the sampleschedules are listed in Table S1 in the SupplementaryMaterials. Figure S1b and S1c shows the meteorological con-ditions during the monitoring period. The mean temperaturewas 7 ± 4 °C, the relative humidity was 64% ± 13%, and thewind speed was 1.9 ± 0.7 m/s (Fig. S1b). The west and eastwind was the main wind directions (Fig. S1c).

Instrumentation and sample collection

The Nano Sampler, a five-stage particle impactor built byKanazawa University in Japan, was used to collect size-segregated PM samples. The cutoff aerodynamic diametersare 10, 2.5, 1.0, 0.5, and 0.1 μm, respectively. The filters onthe last stage with PM size < 0.1 μmwere not analyzed in thisstudy due to large uncertainties, and therefore, the particleswere collected for four size fractions, i.e., PM < 0.5, 0.5–1,

Air Qual Atmos Health

1–2.5, and 2.5–10 μm. The sampler was operated at40 L min−1, and particles were collected on 55-mm quartzfiber filters for 48 h (Sun et al. 2014). Before sampling, thequartz fiber filters were heated at 450 °C in a muffle furnacefor 4 h and dried for 48 h at 30–40% relative humidity indesiccators before and after sampling, and then weighed witha microbalance (Million, BSA124S, Sartorius). After sam-pling, the filters were immediately weighed in the laboratoryafter they were retrieved from the impactor and then stored ina refrigerator at − 18 °C before chemical analysis. It should benoted that sampling artifacts of quartz filters due to sorption oforganic and water vapors could likely lead to slightly moreOM and nitrate concentrations (Chow 1995).

Chemical analysis

EC and OC were analyzed by an OC/EC analyzer (SunsetLaboratory Inc., USA) with the thermal-optical transmit-tance method (Kondo et al. 2006). Water-soluble ions(K+, Na+, Ca2+, Mg2+, NH4

+, F−, Cl−, NO3−, NO2

− andSO4

2−) in aerosol samples were analyzed using ion chro-matography. The one-eighth cut of quartz filters wereextracted with 40 mL deionized water in an ultrasonicbath and then the filtered solutions were stored in arefrigerator at 4 °C for water-soluble ions. Another oneeighth of the filters were extracted with 5 mL 65% nitricacid to digest in a microwave digestion instrument, thensuction filtration, and make up to 40 mL with deionizedwater, diluted 1200 times with 2% nitric acid and storedin a refrigerator at 4 °C for analysis.

The cation analysis instrument model is ICS3000equipped with Ion PacCS16 (5 × 250 mm) separation col-umn, Ion PacCG16 (5 × 50 mm) protection column, andCSRS 4-mm suppressor, and eluent is 33 mmol L−1 methanesulfonic acid; the anion analysis instrument model isICS2000, equipped with Ion Pac (4 × 250 mm) separationcolumn, Ion Pac AG11-HC (4 × 50 mm) protection column,and ASRS 4-mm suppressor, eluent is 10 mmol L−1 KOHsolution, and flow rate is 1 mL min−1. The minimum detec-tion limits (MDLs) were 0.01, 0.04, 0.07, 0.01, 0.05, 0.02,0.01, 0.12, 0.12, and 0.15 mg L−1 for K+, Na+, Ca2+, Mg2+,NH4

+, F−, Cl−, NO3−, NO2

−, and SO42− respectively. Heavy

metal species (V, Cr, Mn, Co, Cu, As, Sr, Cd, Ba, Pb, Al, Zn)were analyzed by inductively coupled plasma-mass spec-trometry (ICP-MS, X Series II, USA). The MDLs were0.002, 0.622, 0.065, 0.002, 0.183, 0.004, 0.050, 0.002,0.132, 0.028, 0.146, and 0.440 μg L−1 for V, Cr, Mn, Co,Cu, As, Sr, Cd, Ba, Pb, Al, and Zn, respectively. Allmeasured concentrations in the samples were significantlyhigher than the corresponding MDLs. The chemicalanalysis followed the procedures described in Sun et al.(2015) and Ge et al. (2017).

Calculation of deposition of inhalable particlesin the human respiratory tract

Deposition characteristics of inhaled particles are usually esti-mated using the human respiratory tract model (Gurman et al.1984; Francisco et al. 2015; Zhou and Cheng 2005) and com-putational fluid dynamics (CFD) simulations (Rostami 2009).Inhalation and deposition curves of particles in human bodyused in this study were obtained from Phalen et al. (1991),assuming normal respiration (tidal volumes of 1450 cm3 and15 breaths per minute) (Phalen et al. 1991). The curves areshown in Fig. S2 in the Supplementary Materials. To calculatethe deposition of different size particles in nasopharyngeal(NOPL), tracheobronchial (TB), and pulmonary (P) in the hu-man respiratory tract, the deposition fraction was estimated foreach particle size range measured in the present study by inte-grating the curves, assuming the particle mass is uniformlydistributed in each of the measured size range. The fractionsof particles of different sizes deposited in the different regionsare shown in Table 1. The deposition fractions in the same sizerange were assumed to be the same for all chemical composi-tions in each region (NOPL, TB, and P).

Results and discussion

PM concentrations

The concentrations of PM2.5 and PM10 measured by the NanoSampler were firstly checked by comparison to the concentra-tions measured by the National Air Quality MonitoringNetwork (NAQMN) at the sites in Nanjing. The results areshown in Fig. S3 in the Supplementary Materials. TheNAQMN-monitored PM2.5 and PM10 data were collected bya continuous monitoring system using the micro-oscillatingbalance method for PM2.5 and the β absorption method forPM10 (Wang et al. 2014). During the monitoring period, thetwo data sets were in good correlation, with correlation coef-ficients of 0.85 and 0.90 and the slopes of 0.82 and 0.78 forPM2.5 and PM10, respectively. The difference between the twodata sets was mainly due to the difference in the site locationsand the measurement technology. Sun et al. (2014) have dem-onstrated the validity of the Nano Sampler through compara-tive experiments.

Table 1 Deposition proportion of each particle size range in each region(NOPL, TB, and P)

< 0.5 μm 0.5–1 μm 1–2.5 μm 2.5–10 μm

NOPL 0.05267 0.22008 0.46881 0.82796

TB 0.10043 0.01762 0.03263 0.04949

P 0.36338 0.13236 0.18927 0.11660

Air Qual Atmos Health

Figure 1 displays the time series of size-resolved aerosolmass concentrations in the sampling period. PM10 mass con-centration ranged from 57.1 to 170.3 μg/m3 with an averageand standard deviation of 108.8 ± 30.8 μg/m3. PM2.5 mass con-centration ranged from 29.8 to 123.9 μg/m3 with an averageand standard deviation of 77.2 ± 24.2 μg/m3. During the sam-pling period, five Bclean^ periods and eight Bpollution^ periodswere separated based on the level-two standards of the NationalAmbient Air Quality Standard of China (PM10 < 150 μg/m3,PM2.5 < 75 μg/m3, GB3095–2012). The mass concentrationincreased significantly from clean days to pollution days.Figure 2 shows the PM mass proportion of different size frac-tions average over the entire sampling period, and under cleanand pollution conditions. During the sampling period, massconcentration in the size range of 0.5–1, 1–2.5, and 2.5–10 μm in Nanjing was 28.8 ± 8.7 (uncertainty is one standard

deviation, same below), 32.7 ± 14.5, and 31.6 ± 8.6 μg/m3, re-spectively (Table S2), accounting for 26.5%, 30.1%, and 29%of the PM10 concentrations. The proportion of each size rangewas different under clean and pollution conditions. In general,the proportion of fine particles increased from 67.8% ± 21.9%on clean days to 72.2% ± 17.5% on pollution days, and theproportion of coarse particles decreased. On clean days, themass percentage in size range of 0.5–1, 1–2.5, and 2.5–10 μm was 27.6% ± 5.9%, 25.4% ± 12.5%, and 32.2% ±8.8%, respectively. The percentage changed to 26.1% ± 6.1%,32.0% ± 8.7%, and 27.8% ± 5.8% on pollution days. Fromclean days to pollution days, the increase in the proportion ofparticles in 1–2.5 μm was most obvious. The mass concentra-tion of 0.5–1 μm increased significantly from the cleaning dayto the pollution day; however, its mass percentage was relative-ly similar (difference of 1.5%).

Fig. 2 PM mass proportion of different size bins in different pollution levels. TMC, total mass concentration

Fig. 1 Time series of size-resolved aerosol massconcentration during the samplingperiods

Air Qual Atmos Health

PM chemical components

Figure 3 shows the average distribution of chemical compo-nents in different sizes during the sampling period and detailedinformation is listed in Table S2. An OM/OC ratio of 1.6 wasused to estimate the organic matter (OM) concentrations(Xing et al. 2013). SOC = OC – EC × (OC/EC)min, where(OC/EC)min is the minimum ratio observed. Similar to organicmatter (OM), the mass concentration of secondary organicaerosol (SOA) is calculated by multiplying by 1.6 (Sun et al.2015). SO4

2−, NO3−, and NH4

+ (SNA) were the major com-ponents in each size. SNA in total account for 14.2% of thetotal mass of coarse particles (2.5–10 μm) and were also themost abundant chemical components in particles of < 0.5,0.5–1, and 1–2.5 μm, accounting for 41.2%, 49%, and38.9% of the particle mass, respectively. SNA were mainlydistributed in fine particles, and the distribution trends ofSO4

2−, NO3−, and NH4

+ (SNA) in different sizes were similar,indicating SNAwere in the presence of ammonium sulfate andammonium nitrate. OM was the largest single resolved com-ponent in particles of all size range; its fraction in < 0.5, 0.5–1,1–2.5, and 2.5–10 μmwas 31.1%, 27.3%, 19.2%, and 13.0%,respectively. The fraction of OM decreased with particle size,and the concentration was mainly in fine particles. The dom-inance of SOA in OM, its fraction in < 0.5, 0.5–1, 1–2.5, and2.5–10μmwas 43.2%, 83.9%, 78.0%, and 73.0%, respective-ly. EC was mainly distributed in particles < 0.5 μm. The frac-tion of heavy metal ions in coarse particles was approximately7.1%, while their proportion in fine particles was 8.3%. Thehighest mass concentration fraction of heavy metal ions was11% in < 0.5-μm particles. Ca2+ was clearly distributed incoarse particles, due to it mainly came from soil dust. Theunresolved components in 2.5–10 μm accounted for 51.3%of mass, and the fractions significantly reduced in the small

size ranges (2.8%, 8.7%, and 25.9% in < 0.5, 0.5–1, and 1–2.5μm size ranges, respectively). The unresolved componentsare expected to be mainly some crustal elements and traceelements that were not analyzed (Sun et al. 2015).

Tables S3 and S4 show the average mass concentrations ofchemical components in different sizes under the clean and thepollution conditions. SNA concentrations increased from27.2 ± 11.2 μg/m3 (34.3% ± 14.1%) on the clean days to44.4 ± 13.8 μg/m3 (34.9% ± 10.8%) on the pollution days.The mass fraction of NO3

− on pollution days increased, whilethe mass fraction of SO4

2− and NH4+ both declined, indicating

that NO3− contributed largely to the high PM pollution growth

during winter in Nanjing. OM+EC mass concentrations alsoincreased, but the proportion of EC was decreased slightly(1.8% ± 0.4% to 1.5% ± 0.5%). In coarse particles (2.5–10 μm), OM and EC fraction increased from 14.6% ± 4.2%on the clean days to 15.8% ± 6.5% on the pollution days.Except for Al, the mass concentration of other heavy metalions increased from clean to pollution conditions, especially in1–2.5 μm. Themass concentration of Al in particles decreasedfrom 2.20 ± 2.09μg/m3 on clean days to 1.36 ± 0.64μg/m3 onpollution days.

Particle depositions in the human respiratory tract

Deposition of different size particles

Figure4 shows the average deposition mass of size-resolvedaerosol in the human respiratory tract (NOPL, TB, P) perminute during the sampling periods. The PM10 deposited inthe NOPL, TB, and P was 1.06 ± 0.35 μg, 0.10 ± 0.03 μg, and0.42 ± 0.14 μg, respectively. The total mass of PM depositedin the NOPL is higher than that deposited in the TB and P. Themass of the particulate matter of the four size ranges (i.e., <

Fig. 3 Average apportionment ofchemical components in 4 sizebins during the sampling period

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0.5, 0.5–1, 1–2.5, and 2.5–10 μm) deposited in NOPL was0.018 ± 0.005, 0.138 ± 0.042, 0.334 ± 0.148, and 0.569 ±0.155 μg, respectively. The coarse particles were mainly de-posited in the NOPL. The total mass of PM deposited in theTB was the lowest, and the mass in the TB in the size range of< 0.5 μm was the highest (0.034 ± 0.010 μg) and that in thesize range of 0.5–1 μm (0.011 ± 0.003 μg) was the lowest.The mass of particles deposited in the P was the highest forthe size range of 1–2.5 μm (0.135 ± 0.060 μg) and the lowestfor the size of 2.5–10 μm (0.080 ± 0.022 μg).

Figure 5 shows significant differences in the PMmass frac-tion of different sizes to total mass in the ambient particles andin the particles deposited in human respiratory tracts during

the sampling periods. In ambient PM, the mass fraction was29%, 30.1%, 26.5%, and 14.4% for the size of 2.5–10, 1–2.5,0.5–1, and < 0.5 μm, respectively. In the NOPL, the fractionwas 53.7%, 31.5%, 13.0%, and 1.7% for the four sizes, re-spectively. The particles deposited in the TB were mainly ofparticles in the sizes of < 0.5 and 2.5–10 μm, accounting for33.3% and 33.2% of the mass of total deposited particles,respectively. Particles in 0.5–1 μm size range had the smallestcontribution of 10.8% in the TB. The main contributions ofparticles deposited in the P were mainly for particles of < 0.5and 1–2.5 μm, which accounted for 29.3% and 32% of themass of total deposited particles, respectively. The fraction ofparticulate mass in the 2.5–10 μm size range was the lowest

Fig. 4 The deposition mass ofsize-resolved aerosol in humanrespiratory tract per minute duringthe sampling periods

Fig. 5 Comparing the proportionof PM mass and particledepositions in human respiratorytracts in different particle sizesduring the sampling periods

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Fig. 7 Comparing the proportion of chemical components of particles and particulates deposited in human respiratory tracts in clean days during thesampling periods

Fig. 6 The deposition mass ofsize-resolved aerosol in humanrespiratory tract per minute inclean and pollution days duringthe sampling period

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(19%) in the P. The difference was caused by the depositionfractions of different size particles in different respiratorytracts, as shown in Fig. S2. The results indicate that the sizedistribution of ambient PM is very different from that depos-ited in human respiratory tracts.

The PM chemical compositions also changed in the respi-ratory tracts. Figure S4 shows the proportion of chemical com-ponents of ambient inhalable particles (< 10 μm) and particlesdeposited in human respiratory tracts during the sampling pe-riods. The deposition proportion of undetected components inNOPL, TB, and P was 36.9%, 24.6%, and 20.6%, respective-ly, while the undetected components accounted for 25.5% ofPM10 in the ambient air. The proportion of undetected com-ponents deposited in the NOPL was relatively large.Compared with the mass fraction of SNA in ambient particles(34.4%), the fraction of SNA in deposited PM changed to26.7% inNOPL, 32.5% in TB, and 36.5% in P. The depositionproportion in P was the largest, while the deposition in theNOPL was the smallest, because SNA mass fraction in thefine particles was much larger than that in the coarse particles(Fig. 3), and the deposition fraction of fine particles was muchlarger than that of coarse particles in the NOPL (Table 1). Theproportion of heavy metal ions in NOPL, TB, and P deposi-tions was 8.0%, 9.0%, and 9.1%, which was within 10% dif-ference from the fraction in ambient particles (8.5%).

Although the total fractions were similar, more fractions ofZn, Cr, and Cu appeared in the PM deposited in TB and P,while opposite trends were found in NOPL (Fig. S5).

Deposition on clean and pollution days

Figure 6 shows the deposition mass of size-resolved aerosol inthe human respiratory tract on clean and pollution days duringthe sampling periods. The average mass of PM deposited inhuman respiratory tracts was significantly higher on pollutiondays than on clean days. The largest increase of the depositionmass in NOPL, TB, and P was mainly for particles in the sizerange of 1–2.5 μm due to the mass concentration increase forthis size range from the clean to the pollution days. From cleandays to pollution days, the deposition proportion of particulatemass in 1–2.5μm increased in the NOPL, TB, and P, while theproportion of deposited particles of other sizes decreased.

Figures 7 and 8 show the proportion of chemical compo-nents of particles and particulates deposited in human respira-tory tracts on clean and pollution days, respectively. The massconcentration of each component in the particle increasedfrom the clean days to the pollution days. However, the pro-portion of each component had different changes, and theproportion of the mass concentration of each component de-posited in different regions also slightly changed. On the

Fig. 8 Comparing the proportion of chemical components of particles and particulates deposited in human respiratory tracts in pollution days during thesampling periods

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pollution day, the mass fraction of OM, Al, and Zn depositedin NOPL was smaller than that in the atmosphere, and themass fraction of deposition in TB and P was greater than thatin the atmosphere; the mass fraction of SNA deposited inNOPL and TB was smaller than that in the atmosphere, andthe mass fraction of deposition in P was greater than that in theatmosphere. The mass fraction of undetected components de-posited in NOPL was greater than that in the atmosphere, andthe mass fraction of deposition in P was less than that in theatmosphere. On the clean days, the mass fraction of undetect-ed components deposited in TB was greater than its propor-tion in the atmosphere, but the trend was the opposite onpollution day.

Conclusions

Size-segregated aerosols were collected using a Nano Samplerduring the winter of 2016–2017 in Nanjing, and chemicalcompositions of PM samples were analyzed. Deposition ofparticles in the NOPL, TB, and P regions of the respiratorytract was estimated. By comparing the size and chemical com-positions in NOPL, TB, and P to those in the ambient PM, afew conclusions can be drawn:

1. The average concentration of PM10 and PM2.5 was 108.8± 30.8 μg/m3 and 77.2 ± 24.2 μg/m3, respectively. PMmass was mainly distributed in size ranges of 0.5–1, 1–2.5, and 2.5–10 μm, with concentrations of 28.8 ± 8.7,32.7 ± 14.5, and 31.6 ± 8.6 μg/m3, respectively.

2. OM and SNAwere the major PM components. The dom-inance of SOA in OM. The mass concentration of parti-cles increased significantly from the clean days to thepollution days, especially for particles in 1–2.5 μm. Butthe proportion of each component had different changes.The proportion of NO3

− and undetected components inparticulate matter increased on pollution days, while theproportion of EC, SO4

2−, and NH4+ decreased. The mass

concentration fraction of unresolved component changedthe most significantly in the size of 1–2.5 μm, increasingfrom 13.0 to 30.0%. The mass concentration of heavymetals increased on pollution conditions, especially in1–2.5 μm, except that the mass concentration of Al parti-cles decreased from 2.20 ± 2.09 μg/m3 on the clean daysto 1.36 ± 0.64 μg/m3 on the pollution days.

3. The total particulate matter deposited per minute in theNOPL, TB, and P was 1.06 ± 0.35, 0.10 ± 0.03, and0.42 ± 0.14 μg, respectively. Particles in 2.5–10 μm hadthe highest deposition mass in NOPL of 0.57 ± 0.16 μg,particles in < 0.5 μm had the highest deposition mass inTB of 0.03 ± 0.01 μg, and particles in 1–2.5 μm had thehighest deposition mass in P of 0.14 ± 0.06 μg. The totalparticulate matter deposited in the NOPL, TB, and P

increased from 0.79 ± 0.25, 0.08 ± 0.02, and 0.30 ±0.09 μg on the clean days to 1.23 ± 0.29, 0.12 ± 0.03,and 0.49 ± 0.11 μg on the pollution days.

4. The chemical composition fractions deposited in a specif-ic region were different from those measured in the am-bient atmosphere. In general, more SNA and metals (es-pecially Zn, Cr, and Cu) were in the PM deposited in TBand P than in ambient PM, while more unresolved com-ponents in the PM deposited in NOPL.

This study helps understand how different of the chemicalcharacteristics between ambient particles and particles depos-ited in the human respiratory tract. The results suggest thathealth effect studies of PM should consider the depositionrates of PM in the human respiratory tract, in addition to theambient size and chemical characteristics of ambient PM.

Funding information This work was supported by the National KeyR&D Program of China (2016YFC0203500, Task No. 2); the NationalNatural Science Foundation of China (41675125, 91544221, and41775154); Public Welfare Projects for Environmental Protection(201509001) ; J i angsu Dis t i ngu i shed Pro fe s so r Pro j ec t(2191071503201); Jiangsu Six Major Talent Peak Project (2015-JNHB-010 and 2018-JNHB-057); and the Priority Academic ProgramDevelopment of Jiangsu Higher Education Institutions (PAPD).

Publisher’s note Springer Nature remains neutral with regard to jurisdic-tional claims in published maps and institutional affiliations.

References

Brook RD, Brook JR, Urch BU, Vincent R, Rajagopalan S, Silverman F(2002) Inhalation of fine particulate air pollution and ozone causesacute arterial vasoconstriction in health adults. ACC Curr J Rev11:32

Chan CK, Yao X (2008) Air pollution in mega cities in China. AtmosEnviron 42:1–42

Chen Y, Xie SD (2013) Long-term trends and characteristics of visibilityin two megacities in southwest China: Chengdu and Chongqing. JAir Waste Manage Assoc 63:1058–1069

Chow JC (1995) Measurement methods to determine compliance withambient air quality standards for suspended particles. Air Repair 45:320–382

Chow JC, Cao JJ, Shun-Cheng LI, Wang XL, Watson JG (2012) A briefhistory of PM_(2.5), its measurement and adverse effects. J EarthEnviron 5:1019–1029

Dan WU et al (2016) Characteristics of organic and elemental carbon inatmospheric aerosol in China: a review. Environ Sci Technol 39:23–32

Delfino RJ, Sioutas C, Malik S (2005) Potential role of ultrafine particlesin associations between airborne particle mass and cardiovascularhealth. Environ Health Perspect 113:934–946

Ding XX, Kong LD, du CT, Zhanzakova A, Fu HB, Tang XF, Wang L,Yang X, Chen JM, Cheng TT (2017) Characteristics of size-resolvedatmospheric inorganic and carbonaceous aerosols in urbanShanghai. Atmos Environ 167:625–641. https://doi.org/10.1016/j.atmosenv.2017.08.043

Francisco SS, Montse M, Vikas K, Joaquim R, Martí N, Marta S (2015)An approach to assess the particulate matter exposure for the

Air Qual Atmos Health

population living around a cement plant: modelling indoor air andparticle deposition in the respiratory tract. Environ Res 143:10–18

Ge X, Li L, Chen Y, Chen H, Wu D, Wang J, Xie X, Ge S, Ye Z, Xu J,Chen M (2017) Aerosol characteristics and sources in Yangzhou,China resolved by offline aerosol mass spectrometry and other tech-niques. Environ Pollut 225:74–85. https://doi.org/10.1016/j.envpol.2017.03.044

Guo Z, Shi L, Chen S, Jiang W, Wei Y, Rui M, Zeng G (2016) Sulfurisotopic fractionation and source appointment of PM 2.5 in Nanjingregion around the second session of the Youth Olympic Games.Atmos Res 174-175:9–17

Gurman J, Lioy PJ, Lippmann M, Schlesinger R (1984) Particle deposi-tion in replicate casts of the human upper tracheobronchial treeunder constant and cyclic inspiratory flow. II Experimental model.Aerosol Sci Technol 3:253–257

Hu J, Wang Y, Ying Q, Zhang H (2014) Spatial and temporal variabilityof fine and coarse particulate matter in the North China Plain and theYangtze River Delta. China Atmos Environ 95:598–609

Hu J, Huang L, Chen M, Liao H, Zhang H, Wang S, Zhang Q, Ying Q(2017) Premature mortality attributable to particulate matter inChina: source contributions and responses to reductions. EnvironSci Technol 51:9950–9959

Jiang WJ, Guo ZB, Liu FL, Rui ML, Shi L, Zeng G, Guo ZY (2015)Characteristics and sources apportionment of OC and EC in PM1.1from Nanjing. Environ Sci 36:774

Kondo Yet al (2006) Temporal variations of elemental carbon in Tokyo. JGeophys 111:2193–2214

Lelieveld J, Evans JS, Fnais M, Giannadaki D, Pozzer A (2015) Thecontribution of outdoor air pollution sources to premature mortalityon a global scale. Nature 525:367–371

Li Z, Ma Z, Kuijp TJVD, Yuan Z, Huang L (2014) A review of soil heavymetal pollution from mines in China: pollution and health risk as-sessment. Sci Total Environ 468-469:843–853

Li H, Wang J, Wang Q, Qian X, Qian Y, Yang M, Li F, Lu H, Wang C(2015) Chemical fractionation of arsenic and heavy metals in fineparticle matter and its implications for risk assessment: a case studyin Nanjing, China. Atmos Environ 103:339–346

Li X, Yan C, Patterson RF, Zhu Y, Yao X, Zhu Y, Ma S, Qiu X, Zhu T,Zheng M (2016) Modeled deposition of fine particles in humanairway in Beijing, China. Atmos Environ 124:387–395. https://doi.org/10.1016/j.atmosenv.2015.06.045.

Liu J, Han Y, Tang X, Zhu J, Zhu T (2016) Estimate adult mortalityattributable to PM2.5 exposure in China with assimilated PM2.5concentrations based on ground monitoring network. Sci TotalEnviron 568:1253–1262

Nirmalkar J, Deb MK (2016) Impact of intense field burning episode onaerosol mass loading and its possible health implications in ruralarea of eastern central India. Air Qual Atmos Health 9:1–9

Phalen RF, Cuddihy RG, Fisher GL, Moss OR, Schlesinger RB, SwiftDL, Yeh HC (1991) Main features of the proposed NCRP respira-tory tract model. Radiat Prot Dosim 38:179–184

Qian L, Yin Y, Tong YQ, Wang WW, Wei YX (2008) Characteristics ofsize distributions of atmospheric fine particles in the north suburbanarea of Nanjing. China Environ Sci 28:18–22

Rostami AA (2009) Computational modeling of aerosol deposition inrespiratory tract: a review. Inhal Toxicol 21:262–290

Ruzer LS, Harley NH (2004) Aerosols handbook : measurement, dosim-etry, and health effects. Scitech Book News 2:205–214

Simkhovich BZ, Kleinman MT, Kloner RA (2008) Air pollution andcardiovascular injury: epidemiology, toxicology and Mechanisms.J Am Coll Cardiol 52:719–726

Sun K, Qu Y, Wu Q, Han T, Gu J, Zhao J, Sun Y, Jiang Q, Gao Z, Hu M,Zhang Y, Lu K, Nordmann S, Cheng Y, Hou L, Ge H, Furuuchi M,Hata M, Liu X (2014) Chemical characteristics of size-resolvedaerosols in winter in Beijing. J Environ Sci 26:1641–1650

Sun K, Liu X, Gu J, Li Y, Qu Y, An J, Wang J, Zhang Y, Hu M, Zhang F(2015) Chemical characterization of size-resolved aerosols in fourseasons and hazy days in the megacity Beijing of China. J EnvironSci 32:155–167. https://doi.org/10.1016/j.jes.2014.12.020

Tian X, Zhu Y, Mu L, Zhang ZF, Liu S (2016) Pulmonary diseasesinduced by ambient ultrafine and engineered nanoparticles intwenty-first century. Nat Sci Rev 3:416–429

Vu TV, Delgado-Saborit JM, Harrison RM (2015) A review of hygro-scopic growth factors of submicron aerosols from different sourcesand its implication for calculation of lung deposition efficiency ofambient aerosols. Air Qual Atmos Health 8:1–12

Wang YG, Ying Q, Hu JL, Zhang HL (2014) Spatial and temporal vari-ations of six criteria air pollutants in 31 provincial capital cities inChina during 2013-2014. Environ Int 73:413–422

Wang H, Zhu B, Zhang Z, An J, Shen L (2015)Mixing state of individualcarbonaceous particles during a severe haze episode in January2013, Nanjing, China. Particuology 20:16–23

Wu S, Deng F, Wei H, Huang J, Wang H, Shima M, Wang X, Qin Y,Zheng C, Hao Y, Guo X (2012) Chemical constituents of ambientparticulate air pollution and biomarkers of inflammation, coagula-tion and homocysteine in healthy adults: a prospective panel study.Part Fibre Toxicol 9:49

WuML, Guo ZB, Liu FL, Liu J, Lu X, Jiang LX (2014) Size distributionsof organic carbon and elemental carbon in Nanjing aerosol particles.Environ Sci 35:451

Xing L, Fu TM, Cao JJ, Lee SC (2013) Seasonal and spatial variability ofthe organic matter-to-organic carbon mass ratios in Chinese urbanorganic aerosols and a first report of high correlations between aero-sol oxalic acid and zinc. Atmos Chem Phys, 13,8(2013-04-25) 13:4307–4318

Xue GQ, Zhu B, Wang HL (2014) Size distributions and source appor-tionment of soluble ions in aerosol in Nanjing. Huan jing ke xue=Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xuewei yuan hui BHuan jing ke xue^ bian ji wei yuan hui] 35:1633

YangC, PengX,HuangW, Chen R,XuZ, ChenB,KanH (2012) A time-stratified case-crossover study of fine particulate matter air pollutionand mortality in Guangzhou, China. Int Arch Occup Environ Health85:579–585

Zhao J, Zhang F, Xu Y, Chen J, Yin L, Shang X, Xu L (2011) Chemicalcharacteristics of particulate matter during a heavy dust episode in acoastal city, Xiamen, 2010. Aerosol Air Qual Res 11:299–308.https://doi.org/10.4209/aaqr.2010.09.0073

Zhou Y, Cheng Y (2005) Particle deposition in a cast of human tracheo-bronchial airways. Aerosol Sci Technol 39:492–500

Zwozdziak A, Gini MI, Samek L, Rogula-Kozlowska W, Sowka I,Eleftheriadis K (2017) Implications of the aerosol size distributionmodal structure of trace and major elements on human exposure,inhaled dose and relevance to the PM2.5 and PM10 metrics in aEuropean pollution hotspot urban area. J Aerosol Sci 103:38–52.https://doi.org/10.1016/j.jaerosci.2016.10.004

Air Qual Atmos Health