Distribution characteristics and noncarcinogenic risk assessment of culturable airborne bacteria and fungi during winter in Xinxiang, China

Abstract

Bioaerosols are an important component of particulate matter in the atmosphere and are harmful to human health. In this study, the concentration, size distribution, and factors influencing culturable airborne bacteria and fungi in the atmosphere were investigated using a six-stage impactor device in the city of Xinxiang, China, during the winter season. The results revealed that the concentration of culturable airborne bacteria and fungi varied significantly during the sampling period: 4595 ± 3410 and 6358 ± 5032 CFU/m3, respectively. The particle sizes of the bioaerosols were mainly within stage V (1.1–2.1 μm), and fine particulate matter accounted for 45.9% ± 18.9% of airborne bacteria and 52.0% ± 18.5% of airborne fungi, respectively. With the deterioration of air quality, the concentration of airborne fungi gradually increased, and that of airborne bacteria increased when the air quality index was lower than 200 and decreased when it was higher than 200. With respect to the diurnal variation pattern of bioaerosol concentration, the highest and lowest concentrations were registered at night and noon, respectively, probably because of changes in ultraviolet radiation intensity. Bioaerosol concentration positively correlated with humidity, concentration of PM2.5, PM10, SO2, and NO2 and negatively correlated with O3 concentration. The risk of exposure of humans to the airborne bacteria was primarily associated with the respiratory inhalation pathway, and the risk of skin exposure was negligible. These results should improve our understanding of the threat of bioaerosols to public health.

Full text

RESEARCH ARTICLE
Distribution characteristics and noncarcinogenic risk assessment
of culturable airborne bacteria and fungi during winter
in Xinxiang, China
Xu Yan
1
&Dezhi Qiu
1
&Shikan Zheng
1
&Jie Yang
1
&Hongyan Sun
1
&Yue Wei
1
&Jingru Han
1
&Jianhui Sun
1
&
Xianfa Su
1
Received: 28 March 2019 /Accepted: 7 October 2019 /Published online: 18 November 2019
#Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract
Bioaerosols are an important component of particulate matter in the atmosphere and are harmful to human health. In this study,
the concentration, size distribution, and factors influencing culturable airborne bacteria and fungi in the atmosphere were
investigated using a six-stage impactor device in the city of Xinxiang, China, during the winter season. The results revealed that
the concentration of culturable airborne bacteria and fungi varied significantly during the sampling period: 4595 ± 3410 and 6358
±5032CFU/m
3
, respectively. The particle sizes of the bioaerosols were mainly within stage V (1.1–2.1 μm), and fine particulate
matter accounted for 45.9% ± 18.9% of airborne bacteria and 52.0% ± 18.5% of airborne fungi, respectively. With the deteri-
oration of air quality, the concentration of airborne fungi gradually increased, and that of airborne bacteria increased when the air
quality index was lower than 200 and decreased when it was higher than 200. With respect to the diurnal variation pattern of
bioaerosol concentration, the highest and lowest concentrations were registered at night and noon, respectively, probably because
of changes in ultraviolet radiation intensity. Bioaerosol concentration positively correlated with humidity, concentration of PM
2.5
,
PM
10
,SO
2
,andNO
2
and negatively correlated with O
3
concentration. The risk of exposure of humans to the airborne bacteria
was primarily associated with the respiratory inhalation pathway, and the risk of skin exposure was negligible. These results
should improve our understanding of the threat of bioaerosols to public health.
Keywords Culturable bioaerosols .Concentration distribution .Size distribution .Influencing factors .Noncarcinogenic risk
assessment .Central China
Environmental Science and Pollution Research (2019) 26:36698–36709
https://doi.org/10.1007/s11356-019-06720-8
Introduction
In the past decades, due to rapid urbanization and industrial and
economic development, massive consumption of energy and a
rapid increase in traffic have caused a significant increase in the
emission of air pollutants as well as deterioration of air quality.
An increase in suspended particulate matter (PM) and haze
pollution in the atmosphere has been reported worldwide, in-
cluding in China, and can significantly adversely affect
ecosystems and human health (Tao et al. 2014;Zhuangetal.
2014; Latif et al. 2018).
Bioaerosols are a group of organic aerosols with a particle
size in the range of nm10–100 mm. Specifically, they include
airborne particles and large molecules that either carry living
organisms or are released from living organisms (Ariyap and
Amyot 2004). The biological organisms or dispersal units (dead
or alive, isolated or aggregated), including bacteria, fungi, pro-
tozoa, algae, spores, pollen, lichen, archaea, viruses, and their
solid fragments or excretions, including detritus, microbial frag-
ments, plant debris/leaf litter, animal tissue and excrements,
brochosomes, all comprise the bioaerosol (Després et al.,
2012). They are often dispersed attached to other biological or
non-biological particles, such as soil, dust, skin flakes, saliva, or
water droplets (Zhai et al. 2018). Bioaerosols are an important
component of PM and are harmful to human health. They can
cause or aggravate skin allergies, respiratory tract infections,
asthma, cardiovascular diseases, and chronic lung diseases
Responsible Editor: Diane Purchase
*Xu Yan
yanxu@htu.cn
1
School of Environment, Key Laboratory for Yellow River and Huai
River Water Environment and Pollution Control, Ministry of
Education, Henan Key Laboratory for Environmental Pollution
Control, Henan Normal University, Xinxiang 453007, Henan, China

Environ Sci Pollut Res (2019) 26:36698–36709 36699
through damaged skin, the mucosa, digestive tract, and respira-
tory tract (Douwes et al. 2003;Yamamotoetal.2012;Walser
et al. 2015; Frohlich-Nowoisky et al. 2016). Via microbiological
and chemical processes, bioaerosols affect atmospheric chemis-
try and vice versa. This adverse impact may be harmful and
deteriorative (Burrows et al. 2009). Additionally, bioaerosols
are closely related to ecological processes and play an important
role in the natural cycling of matter (Fang et al. 2016). Research
on bioaerosols in an ambient atmosphere has gradually become a
hot spot in the field of environmental studies.
Most of China has frequently been affected by severe haze or
smog days in recent years. Especially in winter, an anomalous
steady atmosphere caused by sudden stratospheric warming has
often occurred and is conducive to PM formation and cumulation
and to haze pollution (Zhang et al. 2016;Shietal.2018). At a
high concentration of atmospheric chemicals on haze days, po-
tential synergistic effects between biological and chemical pol-
lutants may further intensify the hazards to human health (WHO
2005). Therefore, it is essential to investigate the bioaerosol char-
acteristics, influencing factors, and risks of resulting exposure for
public health in a period of frequent haze days.
Some researchers have focused on studying bioaerosols
from the atmospheric environment in recent years (Xu et al.
2011; Xie et al. 2018b; Bragoszewska and Pastuszka 2018).
Nonetheless, bioaerosols have significant regional character-
istics owing to the broad diversity and tremendous variability
of microbial composition. Bioaerosols have different sources
of origin and are influenced by seasonal factors, local climatic
differences, local human activities, and local wind currents
(Shaffer and Lighthart 1997). The concentrations and distri-
bution characteristics of bioaerosols in central China have
seldom been investigated. A typical medium-sized city,
Xinxiang, was chosen as a model for sampling of culturable
bioaerosols in this study. Xinxiang is located in central China
and is a Beijing-Tianjin-Hebei Air Pollution Transmission
Channel City (2 + 26 City) (Ministry of Ecology and
Environment of the People’s Republic of China 2017), which
has been affected by haze frequently in recent years. During
the winters of 2016–2018, PM
2.5
was considered the chief
pollutant in the atmosphere of Xinxiang (XEPB 2016–2018).
The objective of this study was to provide a basis for study-
ing the environmental and health effects of bioaerosols on haze
days of winter on public health. It is also expected to serve as a
reference for studies on the atmospheric environment of the
Beijing-Tianjin-Hebei region and the surrounding area.
Materials and methods
Sampling sites
Xinxiang (35.3 °N, 113.9 °E, 72 m above sea level) is located
in the northern Henan Province, has a population of over 6.10
million, and occupies an area of 8249 km
2
(http://www.
xinxiang.gov.cn/sitesources/xxsrmzf/page_pc/index.html).
This city is between the Yellow River in the south and Tai-
hang Mountain in the north. It has a temperate continental
monsoon climate. In winter, the predominant wind direction
was northeast (HMS 2018). The topography of Xinxiang is
mainly plain; this characteristic applies to 76.6% of the total
area (Zhou 1988).
The field sampling of ambient bioaerosols was carried out
on the top roof of the School of Environment Building located
at Henan Normal University. The distance of the site from the
ground was about 30 m. The site is surrounded by trees and
residential and school buildings. There are no large industrial
pollution sources near the site.
Measurement of culturable bioaerosols
Sampling time and frequency
The distribution characteristics of the bioaerosols at different
air quantities and diurnal periods were investigated. A six-
stage impactor (Tisch Environmental, Inc., USA) was
installed at a height of about 1.5 m above the building roof
surface, and bioaerosols of different particle size ranges were
collected. The size ranges of the particles captured are present-
ed in Table 1. Bioaerosol with size smaller than 2.1 μmwas
defined as fine particles and that with size larger than 2.1 μm
was defined as coarse particles because this impactor does not
have a 2.5-μm cutoff point (Wu et al. 2017).
Samples were collected from the period of November 2017
to March 2018, and the main pollutants during this period was
PM
2.5
(78 days), PM
10
(43 days), NO
2
(22 days), and O
3
(5
days) (Ministry of Ecology and Environment of the People’s
Republic of China 2018). To detect diurnal variation, samples
were collected at 9:00, 14:00, and 19:00 on each sampling
day. Three consecutive replicates were collected for each sam-
pling time point. The sampling flow rate was 28.3 L/min, and
sampling time was 4 min. Each sampling device was sterilized
by 75% ethanol before every sampling.
Table 1 Range of particles captured
Stage Aerodynamic diameter Aperture
I > 7.0 μm1.18mm
II 4.7–7.0 μm0.91mm
III 3.3–4.7 μm0.71mm
IV 2.1–3.3 μm0.53mm
V1.1–2.1 μm0.34mm
VI 0.65–1.1 μm0.25mm

36700 Environ Sci Pollut Res (2019) 26:36698–36709
Culture method for bacterial and fungal samples
Bacterial samples were cultured on Beef-Peptone mediums
(3 g beef extract, 10 g peptone, 5 g NaCl, 16 g agar, 1 L
distilled H
2
O, pH 7.2–7.6) at 37 °C and incubated for 48 h.
Fungal samples were cultured on Rose Bengal mediums (10 g
glucose, 5 g peptone, 1 g KDP (potassium dihydrogen phos-
phate), 0.5 g MgSO
4
·7H
2
O, 15 g agar, 0.03 g rose bengal, 1 L
distilled H
2
O) at 25°C and incubated for 72 h (Li et al. 2011).
Counting method
Colony-forming units (CFUs) were counted using positive-
hole correction (Andersen, 1958). The concentration of
bioaerosol was calculated via the following formula:
C¼Pr1000
tQð1Þ
where cis the concentration of the bioaerosol (CFU/m
3
), P
r
is the revised colony number at each stage, tis the sampling
time (min), and Qis the sampling flow rate (L/min).
Noncarcinogenic risk assessment
A noncarcinogenic risk assessment model was used to evalu-
ate the risk of exposure to airborne bacteria for public health.
According to a study by Li et al. (2013), the exposure and
health risk assessment can be evaluated based on the models
developed by US EPA (US Environmental Protection
Agency), which included two main exposure pathways: inha-
lation and dermal contact.
Dose contacted through inhalation of bioaerosols (ADD
inh
)
canbecalculatedas
ADDinh CFU=kg dðÞ½¼
cIR EF ET
BW AT ð2Þ
Dose absorbed through dermal contact with bioaerosols
(ADD
dermal
) can be expressed as
ADDdermal CFU=kg d½Þ
i¼cSA SL ABS EF ET
BW AT ð3Þ
where IR is the inhalation rate, EF is the exposure frequen-
cy, ET is the exposure time, SA denotes the exposure of skin
surface area, SL is the skin adherence factor, ABS represents
the dermal absorption factor, BW is the average body weight,
and AT denotes the averaging time to define noncarcinogenic
exposure.
The risk for noncarcinogenic pollutants was expressed
as the hazard quotient (HQ) and is given by the follow-
ing equation:
HQ ¼ADD
RfD ð4Þ
HI ¼∑HQið5Þ
where hazard index (HI) represents the sum of the hazard
quotients for each pathway and for each target pollutant, and
RfD is the daily dose compared with the reference dose for
chronic exposure. When HQ ≤1orHI≤1, noncarcinogenic
effects are not of concern, whereas when HQ > 1 or HI > 1,
noncarcinogenic effects are cause for concern.
Because of the differences among geographic conditions,
the parameter values of this calculation are different for each
country. The parameter values that are suitable for Chinese
people are presented in Table 2.
Data analysis
The concentration of particulates such as PM
2.5
and PM
10
and
meteorological parameters including temperature, relative hu-
midity, and SO
2
,NO
2
,andO
3
concentrations were retrieved
from the Air Quality Forecast and Release System in Henan
(http://1.192.88.18:8088/TodayMonitor). The basic
information during the period of sampling days is listed in
Tab le 3. SPSS 24.0 software was used to calculate descriptive
statistical parameters and perform such tests as one-way anal-
ysis of variance (ANOVA), the group ttest, and nonparametric
Spearman’s correlation analysis. A Pvalue of less than 0.05
indicated a statistically significant difference at a confidence
level of 95%. The correlations between culturable bioaerosols
and the influencing factors were then analyzed.
Results and discussion
Concentration distribution of bioaerosols
during the sampling period
The concentration distribution of culturable bioaerosols is pre-
sented in Fig. 1, as determined during the sampling period
from November 2017 to March 2018. The concentrations of
culturable airborne bacteria and fungi varied significantly dur-
ing the sampling period with the mean value of 4595 ± 3410
CFU/m
3
and6358±5032CFU/m
3
, respectively. The
culturable airborne bacteria and fungi reached the highest con-
centrations on January 14, 2018 (12853 ± 4520 CFU/m
3
)and
December 27, 2017 (16534 ± 4622 CFU/m
3
), respectively.
The highest concentrations of fine particles of airborne bacte-
ria (7836 ± 3530 CFU/m
3
) and fungi (10433 ± 2476 CFU/m
3
)
were also detected during the same sampling period at rela-
tively high PM
2.5
concentrations of 131 ± 13 and 138 ± 21 μg/
m
3
,respectively.
Because particles in the atmosphere act as the vector for
microorganisms, an increase in the PM concentration

Environ Sci Pollut Res (2019) 26:36698–36709 36701
generally leads to an increase in the concentration of
bioaerosols. PM at high concentrations may contain some
harmful substances such as crustal elements, pollution ele-
ments, and inorganic ions that have a negative impact on mi-
croorganisms (Sun et al. 2006; Sun et al. 2013; Gao et al.
2015b). This phenomenon probably resulted in a low concen-
tration of airborne bacteria (2563 ± 268 CFU/m
3
)on
December 3, 2017, at the highest PM
2.5
concentration of
209 ± 16 g/m
3
. Rain and snow have a scouring effect on the
particles in the air (Almaguer et al. 2014; Lee et al. 2016;Li
et al. 2017; Xie et al. 2018b). Thus, the lowest concentrations
of airborne bacteria and fungi were detected on December 17,
2017, and January 8, 2018, respectively, with snowfall before
the sampling day.
Concentration and size distribution of bioaerosols
at different air quality levels
The air quality index (AQI) is usually used to describe the air
quality situation. According to Technical Regulation on
Ambient Air Quality Index (on trial), the status of air quality
was categorized into six classes: excellent (0–50), good (51–
100), slight pollution (101–150), moderate pollution (151–
200), heavy pollution (201–300), and serious pollution (>
300) (HJ 633- 2012 2012). Figures 2,3,and4present the
concentration and size distributions for culturable airborne
bacteria and fungi at different AQIs. Because there was no
sampling date during serious-pollution weather in the sam-
pling period, the AQI higher than 200 was interpreted as
heavy pollution.
The average culturable airborne bacteria concentrations in
different AQI classes were in the range of 1237 ± 928 to
10097 ± 6380 CFU/m
3
. An increase in airborne bacteria con-
centrations with the increasing AQI was observed when AQI
was lower than 200. At AQI higher than 200, the concentra-
tion of airborne bacteria decreased to 4875 ± 2745 CFU/m
3
.
Fig. 1 Concentration distribution of culturable airborne bacteria and
fungi and PM
2.5
concentrations during sampling days (a, culturable
airborne bacteria; b, culturable airborne fungi)
Table 2 The appropriate
exposure parameters of Chinese
people
Parameter Values
Inhalation rate (IR) (m
3
/day) 7.60 (children), 19.02 (adult male), 14.17 (adult female)
Exposure time (ET) (years) 6 (children), 24 (adult)
Exposure frequency (EF) (day/year) 180
Average body weight (BW) (kg) 15.0 (children), 62.7 (adult male), 54.4 (adult female)
Ave ra gi ng t im e (AT) (days) 69.6 × 365 (male), 73.3 × 365 (female)
Exposure skin area (SA)(m
2
) 0.115 (children), 0.215 (adult)
Skin adherence factor (SL)(kg/(m
3
·day)) 0.20 (children), 0.07 (adult)
Dermal absorption factor (ABS)0.001
RfD (CFU/m
3
)5000
Table 3 Information of air quality during sampling days
Number Minimum Maximum Mean
Temperature (°C) 34 −8.1 23.9 5.6
Relative humidity (%) 34 12.0 89.0 43.6
PM
2.5
(μg/m
3
)341123090
PM
10
(μg/m
3
) 34 29 315 144
SO
2
(μg/m
3
) 34 6 56 30
NO
2
(μg/m
3
)341714264
O
3
(μg/m
3
) 34 5 160 46
AQI 36 29 280 119

36702 Environ Sci Pollut Res (2019) 26:36698–36709
The concentration of airborne bacteria under excellent weath-
er conditions was significantly lower than that under other
weather conditions (AQI > 50; P< 0.05). Generally, the con-
centration of airborne fungi increased with the increasing
AQI, and the highest concentration of 12729 ± 6765 CFU/
m
3
was observed in heavy-pollution weather. The concentra-
tion of airborne fungi in slight-pollution weather was signifi-
cantly higher than that in good weather (P<0.05).
Bioaerosols were influenced by many factors in the
atmosphere (physical, chemical, and biological factors)
(Zhong et al. 2016). The bioaerosol characteristics often
varied significantly among regions because the atmo-
spheric conditions differed greatly among different time
points and locations (Timo 1997; Wei et al. 2015;Dong
et al., 2016;Xieetal.2018a). In Xi’an of China, the total
airborne microbial concentration was found to increase
initially and then to slightly decrease with the increasing
AQI. The peak appeared at the moderate pollution level
(Xie et al. 2018b). Wei et al. (2016) found bioaerosol
concentration to be significantly higher during haze
weather than during sunny weather from December 2013
to March 2014 in Beijing. Nonetheless, the community
structures of airborne bacteria and fungi in PM
2.5
samples
did not show significant differences at different AQI
levels during the 2014 APEC Summit Periods in Beijing
(from October 15, 2014, to November 12, 2014) (Du et al.
2018b).
The size distribution of culturable bioaerosols is presented
in Figs. 3and 4. For airborne bacteria, the concentration dis-
tributions of particle sizes at different stages were close within
the excellent-weather class. During sampling days with AQI
greater than 50, the culturable airborne bacteria were found to
be mainly within Stage V (1.1–2.1 μm) (34.9% ± 16.2%,
49.4% ± 8.7%, 40.8% ± 15.7%, and 34.6% ± 16.2% for good
weather, slight pollution, moderate pollution, and heavy-
pollution weather, respectively). With the increase in size
range, the concentration distribution gradually decreased. A
similar distribution trend was observed for culturable airborne
fungi. On the sampling days with AQI greater than 50, the
highest concentrations were seen at Stage V (1.1–2.1 μm)
(49.4% ± 20.3%, 50.0% ± 13.2%, 45.0% ± 7.1%, and
52.7% ± 6.4% for good weather, slight pollution, moderate
pollution, and heavy-pollution weather, respectively). In the
class of excellent weather, the highest concentration, 402 ±
355 CFU/m
3
, was noted at stage III (25.4% ± 13.0%).
Generally, our results indicate that 45.9% ± 18.9% of
culturable airborne bacteria and 52.0% ± 18.5% of culturable
airborne fungi that were detected during the sampling period
had a particle size less than 2.1 μm. This result was probably
due to PM
2.5
, which was identified as the chief pollutant dur-
ing 52% of the sampling period from November 2017 to
March 2018 (PM
10
accounted for 29%), as described in
2.2.1. the “Sampling time and frequency”subsection. The
particles served as existence vectors for the microorganisms
in the atmosphere. A similar phenomenon was observed in a
study by Wei et al. (2015), which revealed that the biological
fraction of PM
2.5
in 11 major cities of China ranged from 55 to
91% in 2013. Different size distribution characteristics of
culturable bioaerosols have also been observed in other re-
gions. From January 14, 2013, to January 22, 2014, detected
culturable airborne bacteria were mainly coarse particles,
which accounted for approximately 55–80% of the total
bioaerosol concentration on both haze days and nonhaze days
in Beijing (Gao et al. 2015a). From October 8 to 22, 2014, in
Xi’an, the culturable airborne bacteria and fungi were mainly
within particle size ranges of 1.1–2.1 μm (25.0% ± 6.8%) and
3.3–4.7 μm (29.4% ± 4.1%), respectively (Li et al. 2015). In
Qingdao, the bacterial particles were mainly coarse particles
(except in the fall season), whereas the fungal particles follow-
ed a log-normal distribution (Qi et al. 2014). Therefore, char-
acteristics of the distribution of bioaerosol particle sizes varied
among regions and depended on geographical and climatic
factors and atmospheric and environmental characteristics.
The pollutant characteristics in different regions caused differ-
ences in the spatial distribution of bioaerosols (Li et al. 2011;
Weietal.2015; Zhong et al. 2016;Luetal.2018).
Fig. 2 Concentration distribution of culturable airborne bacteria and
fungi at different AQIs (a, culturable airborne bacteria; b, culturable
airborne fungi). **Correlation is significant at the 0.01 level (two-
tailed). *Correlation is significant at the 0.05 level (two-tailed)

Environ Sci Pollut Res (2019) 26:36698–36709 36703
Diurnal variation of the concentration and size
distribution of bioaerosols
Thediurnalvariationintheconcentrationofculturable
airborne bacteria and fungi during the study period is
presented in Fig. 5. The lowest concentrations of airborne
bacteria and fungi were observed at noon: 3624 ± 2887
and4412±3946CFU/m
3
, respectively. The highest con-
centrations of airborne bacteria and fungi were registered
at night: 5773 ± 4987 and 9780 ± 7233 CFU/m
3
, respec-
tively. Moreover, the temporal variations in the culturable
bioaerosols during the sampling day were not obvious (P
> 0.05). This finding is probably due to the relative sta-
bility of the atmospheric environment throughout the sam-
pling day.
The sun radiation was one of the important factors
influencing the bioaerosol concentration (Dong et al. 2015).
Ultraviolet radiation from the sun probably inhibited the
growth of bacteria by damaging their DNA (Pakulski et al.
2007). Given that the surface solar irradiance at noon was
often higher than that in the morning and evening (Tong
et al. 1997;Xuetal.2013), the reduction in solar radiation
at night reduced the proportion of microbial death, resulting in
accumulation of microorganisms (Hwang et al. 2010). The
temporal distribution characteristics of bioaerosols during
the study period were attributed to UV radiation. A similar
phenomenon was observed in Beijing in a 1-year data analysis
by Gao et al. (2016), which revealed the highest concentration
of airborne bacteria and fungi were present at 21: 00. The
lowest concentration was detected at 12:00 and 15:00,
Fig. 3 Size distribution of
culturable airborne bacteria at
different AQIs (a, excellent
weather; b, good weather; c,
slight-pollution weather; d,
moderate-pollution weather; e,
heavy-pollution weather; f, total)

36704 Environ Sci Pollut Res (2019) 26:36698–36709
respectively. The airborne bacteria concentrations at 9:00 and
17:00 were also found to be significantly higher than that at
13:00 in Hangzhou (Fang et al. 2016).
The diurnal variations in the particle size distribution for
culturable airborne bacteria and fungi were similar (Fig. 6),
and no statistically significant differences were found during
the three sampling diurnal periods (P> 0.05), which are
depicted in Fig. 5. The particle size of culturable airborne
bacteria and fungi was found to mainly be distributed within
stage V, within the particle size range of 1.1–2.1 μm and with
proportions of 36.2% ± 16.7% and 46.3% ± 17.4%, respec-
tively. The diurnal fine particle concentrations of airborne
bacteria and fungi were 47.2% ± 19.4% and 46.6% ± 16.5%
in the morning, 40.7% ± 20.8% and 51.1% ± 22.5% at noon,
and 50.0% ± 14.8% and 58.2% ± 13.6% at night, respectively.
The particle size is an important parameter for evaluation of
the harmfulness of PM for human health (Du et al. 2018a).
The deposition efficiency in the human respiratory tract varies
among different sizes of particles (coarse particles are mainly
deposited in the extrathoracic region, and fine particles can
penetrate and deposit deeper in the tracheal, bronchial, and
alveolar regions) (Gao et al. 2015a;Lietal.2017).
Moreover, ultrafine particles (< 0.1 μm) are deposited at a
much higher efficiency rate and act as efficient carriers of
toxic compounds into the pulmonary alveoli (Kawanaka
et al. 2009).
Analysis of factors affecting the concentration
of bioaerosols
To explore the effects of meteorological factors and particles
on bioaerosols, the relations between the concentration of air-
borne bacterial or fungal aerosols and different particle sizes
and temperatures, relative humidity levels, and PM
2.5
,PM
10
,
SO
2
,NO
2
,andO
3
concentrations were analyzed by
Spearman’s correlation method (Fig. 7). Airborne bacteria
and fungi from stage I to stage VI and total bacteria and fungi
were labeled as BI-VI, FI-VI, TB, and TF, respectively.
Fig. 4 Size distribution of
culturable airborne fungi at
different AQIs (a, excellent
weather; b, good weather; c,
slight-pollution weather; d,
moderate-pollution weather; e,
heavy-pollution weather; f, total)

Environ Sci Pollut Res (2019) 26:36698–36709 36705
According to Fig. 7,NO
2
was an important factor influenc-
ing the culturable bioaerosol concentration and had a statisti-
cally significant association with BIII-VI (P<0.05),TB(P<
0.01), FII-VI (P< 0.01), and TF (P< 0.01; Fig. 7). Being
considered an acid gas, SO
2
also showed a positive correlation
with the culturable bioaerosol concentration (except at stages
BI and FI). This positive correlation is probably due to the fact
that SO
2
and NO
2
can combine with moisture in the air to
form SO
4
2-
and NO
3
-
, which are beneficial for the growth of
microorganisms (Chen et al. 2008;Dongetal.2016). A pos-
itive correlation between bioaerosols and acid gases has been
observed in several other studies too (Grinn-Gofron et al.
2011; Xie et al. 2018b).
O
3
showed a statistically significant association with BIII-
V(P<0.05),TB(P< 0.01), FIII-VI (P<0.05),andTF(P<
0.01). The negative correlation between O
3
and airborne bac-
terial and fungal concentrations in other stages was also ob-
served (Fig. 7). A high concentration of O
3
was toxic to the
bioaerosol, especially after reacting with atmospheric olefins
and forming so-called open air factors (Cox et al. 1973;Cox
1995).
Both PM
2.5
and PM
10
manifested a positive correlation
with culturable bioaerosols of different particle sizes, and
there were significant correlations with BIV, TB, FIII-V, and
TF (P< 0.05). Because this study was conducted in winter
under relatively stable atmospheric conditions, the microor-
ganisms adhered to the particles and were difficult to disperse.
Therefore, the high concentrations of culturable bioaerosols
were investigated at high PM
2.5
and PM
10
concentrations.
The significant positive correlation between culturable
airborne-bacteria aerosols or culturable airborne-fungi aero-
sols (including coarse, fine, and total aerosols) with AQI
(PM
2.5
) was also found in Xi’an during the autumn haze days
(Li et al. 2015). On the other hand, we uncovered a significant
negative correlation of the culturable airborne-bacteria con-
centration and culturable airborne-fungal concentration with
Fig. 6 Size distribution of
culturable airborne bacteria and
fungi at different time points (a
and c, culturable airborne
bacteria; b and d, culturable
airborne fungi)
Fig. 5 Diurnal variation of concentrations of culturable airborne bacteria
and fungi (a, culturable airborne bacteria; b, culturable airborne fungi)

36706 Environ Sci Pollut Res (2019) 26:36698–36709
PM
2.5
and PM
10
in Beijing (Gao et al. 2015a; Gao et al. 2016).
As carriers of air pollutants, particles adsorb greater amounts
of chemical components, which may shorten the survival pe-
riod of a microorganism (Eeftens et al. 2012;Luetal.2018).
Most particle size stages showed a positive correlation with
relative humidity, and significant correlations between BIV-V
and TB and relative humidity were observed (P<0.05).
Because moisture in the air may alter the integrity of the cell
wall or viral capsid (Jones et al. 2004), relative humidity was
found to be the main factor affecting the culturablebioaerosols
(Jo and Kang 2006;Lietal.2011). It had different effects on
different kinds of microorganisms (Macher et al. 1991;
Pasanen et al. 1991; Theunissen et al. 1993). Li et al. (2017)
reported high relative humidity can favor microbial growth,
resulting in elevated bioaerosol concentrations. The high hu-
midity values (about 70–80%) particularly assisted the release
of basidiospores and ascospores. High relative humidity could
also trigger spore release, thereby increasing the abundance of
spores and improving archaeal diversity (Gabey et al. 2010;
Fröhlichnowoisky et al. 2014; Zhai et al. 2018). This was
probably the cause of the positive correlation between
bioaerosol concentration and relative humidity in this work.
Moreover, negative correlations were noted between
culturable bioaerosol concentrations and temperature (Fig.
7). This finding is consistent with the results reported by Li
et al. (2017) and Lu et al. (2018), who also found a negative
and positive correlation between bioaerosols (bacteria and
fungi) and temperature and relative humidity, respectively.
High temperature was disadvantageous for the microorgan-
isms because it enhanced the release of toxic compounds
and promoted their chemical reactions to occur on particulate
surfaces (Gao et al. 2016). The increased temperature could
also speed up convective air movements, which might en-
hance bacterial dispersal and dilution effect, leading to a de-
crease of bioaerosol concentrations in the atmosphere (Smets
et al. 2016; Zhong et al. 2016). Nonetheless, some investiga-
tors have reached the opposite conclusions. Bioaerosol con-
centration increases with increasing relative humidity at suffi-
ciently high temperatures and can hardly be influenced at low
temperatures (Kethley et al. 1957). Webb and Dumasia (1968)
reported that the decline rate of bioaerosols is dependent on
both temperature and relative humidity.
The formation and size distribution of the bioaerosols were
complicated, and many factors were involved in this process
(Chen et al. 2012). The PM concentration was considered the
most significant factor on the bioaerosol size distribution, as
the airborne bacteria and fungi can attach to the surfaces of
PM suspended in the atmosphere (Gao et al. 2015b; Dong
et al. 2016). In this work, most of the particle size stages
showed a positive correlation with PM
2.5
and PM
10
.
However, exceptions were found in the measurements of BI
and FI, which was likely due to the aggregation of fine partic-
ulates that frequently occurred on hazy days (Kulmala et al.
2004). Sources of bioaerosols played a leading role in shaping
the characteristic of bioaerosol particle size and had a larger
impact than that caused by meteorological conditions (Zhai
et al., 2018). The bioaerosol generated from the respiratory
tract was found to be smaller than that generated from dust
sources (Hoeksma et al., 2015). At a subway station, Dybwad
et al. (2014) found a significantly larger fraction of bioaerosol
(particles between 1.1 and 3.3 μm) during the daytime than at
nighttime. Anthropogenic activities (mainly passengers) were
demonstrated to be major sources of airborne bacteria and
predominantly contributed to the bioaerosol particles of this
range. Relative humidity is an important meteorological pa-
rameter influencing the size distribution of bioaerosol. High
relative humidity will augment the probability of deposition
due to the presence of suspended particles that absorb ambient
moisture, leading to an increase in particle weight and size
(Zhen et al., 2017). The bigger and heavier particles will have
Fig. 7 Spearman’s analysis of
correlation between bioaerosols
and influencing factors.
**Correlation is significant at the
0.01 level (two-tailed).
*Correlation is significant at the
0.05 level (two-tailed)

Environ Sci Pollut Res (2019) 26:36698–36709 36707
a higher settling velocity in the air. Temperature could indi-
rectly influence the size distribution of bioaerosols by chang-
ing the parameter of cross-ventilation that decides the suspen-
sion and diffusion of microbes (Zhai et al., 2018). Moreover,
factors such as organic carbon, elementary carbon, NH
4
+
,
SO
4
2–
,NO
3
–
, metals, and polycyclic aromatic hydrocarbons
have been shown to affect the size distributions of the bacterial
aerosol (Lai et al. 2010;Chenetal.2012). The size distribu-
tions of airborne fungi were influenced by various factors such
as microorganism species, spore age, sample culture medium,
and differences in aggregation rates of spores (Nasir et al.
2012).
Noncarcinogenic exposure risk assessment
Assessment of culturable bioaerosols during the sampling pe-
riod was conducted in this study, and it is important for people
to understand the risk of air quality for the living environment
and take preventive measures. Table 4summarizes the hazard
quotients for inhalation (HQ
inh
) and dermal (HQ
dermal
)routes
and the HI of bioaerosols at different time points and air qual-
ity classes during the sampling period.
In this study, the highest diurnal risk of exposure to
bioaerosols was noted at night, and with the rise in AQI, the
risk increased too. The ranges of HQ
inh
for adult males, adult
females, and children were 1.28 × 10
-2
to 1.04 × 10
-1
,1.04×
10
-2
to 8.49 × 10
-2
, and 5.19 × 10
-3
to 4.24 × 10
-2
,respectively,
which were several orders of magnitude higher than those of
HQ
dermal
. Therefore, the risk of exposure to bioaerosols in the
atmosphere was primarily associated with the respiratory in-
halation pathway. The risk of exposure of skin was negligible.
For different populations, the order of HQ
inh
values was as
follows: adult males > adult females > children, whereas that
of HQ
dermal
values was children > adult females > adult males.
Nevertheless, the risk of exposure to bioaerosols analyzed
in this study was relatively low when compared with those
analyzed in other studies (Li et al. 2013). We recommended
that outdoor activities be avoided when AQI is higher than
150, especially at night. Some necessary protective measures
are still essential for people living in high-AQI atmospheric
conditions. The noncarcinogenic risk assessment model used
in this work was based on the concentration of airborne bac-
teria. The community structure of opportunistic pathogenic
airborne bacteria is closely related to human health (Fan
et al. 2019), but is not considered in this evaluation process.
In addition, the bioaerosols investigated in this study
contained only culturable airborne bacteria, which represent
only a small part of the airborne microorganisms. In further
studies, other analytical methods, such as molecular tools,
should be considered to comprehensively reveal the species
and quantities of bioaerosols and their effects on public health.
Conclusion
In this study, we monitored the concentration of culturable
airborne bacteria and fungi at different air quality levels and
during different diurnal periods in winter in Xinxiang, China.
The concentrations of culturable airborne bacteria and fungi
were strongly linked to air quality (AQI). The particle sizes of
bioaerosols were mainly within stage V (1.1–2.1 μm), and
fine PM accounted for 45.9% ± 18.9% of airborne bacteria
and 52.0% ± 18.5% of airborne fungi, respectively. Analysis
of diurnal variation of bioaerosols showed that the concentra-
tion was obviously higher at night than in the morning or at
noon. Bioaerosol concentration positively correlated with hu-
midity and concentrations of PM
2.5
,PM
10
,SO
2
,andNO
2
and
negatively correlated with the concentration of O
3
. The risk of
exposure to bioaerosols among humans was primarily associ-
ated with the respiratory inhalation pathway, and the risk of
skin exposure was negligible.
Funding information This research was financially supported by the
National Natural Science Foundation of China (No. 51408199) and the
Natural Science Foundation of Henan Province of China (No.
182300410157).
Table 4 Individual non-carcinogenic risks corresponding to different exposure pathways
Expose HQ
inh
HQ
dermal
HI
Types Adult male Adult female Children Adult male Adult female Children Adult male Adult female Children
B-morning 4.53E−02 3.69E−02 1.84E−02 3.58E−08 3.92E−08 5.57E−08 4.53E−02 3.69E−02 1.84E−02
B-noon 3.74E−02 3.05E−02 1.52E−02 2.96E−08 3.24E−08 4.60E−08 3.74E−02 3.05E−02 1.52E−02
B-night 5.96E−02 4.86E−02 2.42E−02 4.71E−08 5.16E−08 7.33E−08 5.96E−02 4.86E−02 2.42E−02
B-excellent 1.28E−02 1.04E−02 5.19E−03 1.01E−08 1.11E−08 1.57E−08 1.28E−02 1.04E−02 5.19E−03
B-good 3.66E−02 2.99E−02 1.49E−02 2.90E−08 3.17E−08 4.51E−08 3.66E−02 2.99E−02 1.49E−02
B-slight pollution 5.90E−02 4.81E−
02 2.40E−02 4.67E−08 5.11E−08 7.26E−08 5.90E−02 4.81E−02 2.40E−02
B-moderate pollution 1.04E−01 8.49E−02 4.24E−02 8.24E−08 9.02E−08 1.28E−07 1.04E−01 8.49E−02 4.24E−02
B-heavy pollution 5.03E−02 4.10E−02 2.05E−02 3.98E−08 4.36E−08 6.19E−08 5.03E−02 4.10E−02 2.05E−02

36708 Environ Sci Pollut Res (2019) 26:36698–36709
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