Wuetal. Environmental Health (2022) 21:16
Association betweenambient particulate
matter exposure andsemen quality infertile
Wei Wu1,2,3*† , Yiqiu Chen1,2†, Yuting Cheng1,2, Qiuqin Tang4, Feng Pan5, Naijun Tang6, Zhiwei Sun7,
Xinru Wang1,2, Stephanie J. London3 and Yankai Xia1,2*
Background: Several studies have suggested adverse eﬀects of particulate matter (PM) exposure on male reproduc-
tive health; few have investigated the association between PM exposure and semen quality in a large population of
Methods: We evaluated 14 parameters of semen quality in 1554 fertile men in Nanjing from 2014 to 2016. Individual
exposure to particular matter ≤10 μm in diameter (PM10) and ≤ 2.5 μm in diameter (PM2.5) during key periods of
sperm development (0-90, 0-9, 10-14, 15-69, and 70-90 days before semen collection) were estimated by inverse dis-
tance weighting interpolation. Associations between PM exposure and semen quality were estimated using multivari-
able linear regression.
Results: Higher 90-days average PM2.5 was in association with decreased sperm motility (2.21% for total motil-
ity, 1.93% for progressive motility per 10 μg/m3 increase, P < 0.001) and four quantitative aspects of sperm motion
(curvilinear velocity (VCL), straight line velocity (VSL), average path velocity (VAP), and amplitude of lateral head
displacement (ALH), P < 0.01). The association between PM2.5 exposure and semen quality were generally stronger for
the earlier exposure window (70-90 days prior to ejaculation) than for recent exposure (0-9, 10-14, or 15-69 days). In
the subgroup of men who had normal sperm parameters (n = 1019), similar results were obtained. Ninety-days PM10
exposure was associated only with decreased VCL and VAP and was not related to sperm concentration.
Conclusions: Exposure to PM2.5 adversely aﬀects semen quality, speciﬁcally lower sperm motility, in fertile men.
Keywords: Ambient air pollution, PM2.5, PM10, Fertility, Semen quality, Sperm motility
© The Author(s) 2022. Open Access This ar ticle is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the
original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or
other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this
licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco
mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Male factors are responsible for about 50% of infertility in
couples and male infertility is an important public health
issue worldwide . A signiﬁcant decline in human
semen quality has been observed over the past 70 years,
even in fertile men [2, 3]. Exposures that have been asso-
ciated with reduced semen quality include air pollutants,
smoking, and heavy metals [4–6]. e World Health
Organization (WHO) reports that 1.4 billion urban resi-
dents live in areas with air quality that does not meet
WHO air quality guidelines . China has experienced
deterioration of the air quality due to its rapid socioeco-
nomic development. e situation is especially notable in
the Yangtze River Delta, one of the areas in China under-
going most rapid urbanization .
*Correspondence: firstname.lastname@example.org; email@example.com
†Wei Wu and Yiqiu Chen contributed equally to this work.
2 Key Laboratory of Modern Toxicology of Ministry of Education, School
of Public Health, Nanjing Medical University, Nanjing, China
3 Department of Health and Human Services, National Institute
of Environmental Health Sciences, National Institutes of Health, Research
Triangle Park, Durham, USA
Full list of author information is available at the end of the article
Page 2 of 12
Wuetal. Environmental Health (2022) 21:16
A large body of literature documents the association
between ambient air pollution and a range of important
health conditions including cardiovascular and respira-
tory diseases [9–12] and cancers . A growing body
of literature suggests that exposure to ambient air pol-
lutants during pregnancy increases the risk of adverse
birth outcomes [14, 15]. Sentinel animal studies provide
cogent evidence that ambient air pollution exposure can
damage male germ cells . Particulate matter (PM) is
a key component of air pollution and various diseases
are associated with it . Pires etal. showed that ﬁne
particulate matter (PM2.5) levels in Sao Paulo adversely
aﬀects spermatogenesis in mice, but they didn’t investi-
gate the eﬀects of PM10 exposure . During the past
few years, there has been increasing interest in the eﬀects
of air pollution on male reproductive health [19, 20]. In
humans, several studies have reported changes in sperm
parameters, such as sperm mobility and movement, in
relation to exposure to air pollution, providing evidence
for exposure-related reductions in sperm quality [4, 21–
23]. However, the reported eﬀects of PM exposure on the
male reproductive system are inconsistent [19, 24, 25]. A
number of studies have focused on men being evaluated
for infertility, but studies in men known to be fertile are
few. Furthermore, most of these studies focused only on a
few semen parameters. ese limitations may impair the
identiﬁcation of true associations between PM exposure
and semen quality.
Because development of sperm takes approximately
3 months , most studies have analyzed PM exposure
in the 90 days before semen examination [25, 27, 28]. It
is known that the sperm development covers four key
stages before semen ejaculation: 0-9 (epididymal storage),
10-14 (development of sperm motility), 15-69 (spermato-
genesis stage II), and 70-90 days (spermatogenesis stage
I). However, few researchers have considered these diﬀer-
ent exposure stages within the 90-days window [29–31],
and the conclusions are inconsistent.
We therefore investigated the association between
ambient PM (PM2.5 and PM10) exposure, in the 90 days
prior to semen collection and semen quality in a large
population of men in Nanjing, China known to be fertile
and attempted to clarify which stage of sperm develop-
ment is most impacted by PM exposure. Our large cohort
with participants of known fertility would make the
results more representative.
e study population initially consisted of 1607 fer-
tile men from Nanjing Medical University Longitudinal
Investigation of Fertility and the Environment (NMU-
LIFE) study from January 1st, 2014 to December 31st,
2016. e NMU-LIFE was established in September
2010 to examine the eﬀects of environmental and life-
style factors on reproductive health and birth outcomes
in the oﬀspring. e study area of NMU-LIFE locates
in Yangtze River Delta Region, China. Pregnant women
that went for registration at the hospital were identiﬁed
as candidates for the study. Maternity care doctors deter-
mined the eligible individuals. Exclusion criteria included
maternal age < 20 or > 45 years , non-per manent residents
and intention of delivering in other cities. After learn-
ing about the study in details, the woman that agreed
to participate would represent herself and her family
members to sign an informed consent, which meant the
whole family was recruited. e information collected
in NMU-LIFE include the basic information and disease
information of fertile males, pregnant women, and their
children, as well as biospecimen including blood, urine,
semen, placenta and follicular ﬂuid (more detailed infor-
mation about the cohort can be found in supplementary
material). We excluded 21 men without complete semen
reports, 17 with missing examination dates, and 15 with-
out exact addresses, leaving 1554 men for analysis. All of
the 1554 ferile men had fathered at least one healthy child
within the previous year. All male participants in our pre-
sent study were without a history of treatment. e study
was approved by the Institutional Ethics Committee of
Nanjing Medical University. All study participants gave
written informed consent. All activities involving human
subjects were conducted under full compliance with gov-
ernment policies and the Declaration of Helsinki.
We obtained daily average PM air quality indices (AQIs)
and concentrations published daily by the Nanjing Envi-
ronmental Protection Bureau. To make our results
comparable with those from other studies, we chose
concentrations (μg/m3) in our analysis. PM2.5 and PM10
concentrations were continuously measured at nine ﬁxed
state-controlled air quality monitoring stations located
in Nanjing city (Fig.1). Data on daily ambient average
temperature (in Celsius) in Nanjing over the same period
were obtained from the Nanjing Regional Climate Center.
Each participant was interviewed to collect information
including residence address, age, height, weight, ethnic-
ity, education, family income, cigarette smoking and alco-
hol consumption. Body mass index (BMI, in kg/m2) was
calculated as weight in kilograms (kg) divided by height
in meters squared (m2). Participants were asked about
the number of days of abstinence from ejaculation. After
an interview, each participant donated a semen sample
for semen quality analysis.
All semen samples were collected during the second
trimester of pregnancy of the participants’ spouses.
Page 3 of 12
Wuetal. Environmental Health (2022) 21:16
Subjects were instructed to collect semen samples by
masturbation into sterile plastic specimen containers
in a semen collection room. Semen specimens were
allowed to liquefy at 37 °C, and aliquots were analyzed
at approximately 30 min after ejaculation using com-
puter-assisted semen analysis (CASA) in accordance
with guidelines of the WHO 5th Laboratory Manual for
the Examination of Human Semen . Semen volume
was measured using a sterile serological pipette. Sperm
outcomes include semen volume, sperm concentration,
total sperm number, total motility, progressive motility.
Additionally, motility measures are curvilinear veloc-
ity (VCL), straight-line velocity (VSL), linearity (LIN),
average path velocity (VAP), wobble (WOB), straight-
ness (STR), mean angular displacement (MAD), beat
cross frequency (BCF), and amplitude of lateral head
displacement (ALH). VCL indicates the average veloc-
ity of the sperm head along its curved path. VSL indi-
cates the average straight-line velocity of the sperm
head from the initial location to the last location. VAP
indicates the time-averaged velocity of the sperm head
moving along its average trajectory. MAD indicates
the average angle of the sperm head turning along the
curved path. BCF indicates the time-averaged velocity
of the sperm curve trajectory across its average path.
ALH indicates the swaying amplitude of the sperm
head along its average trajectory (Fig.S1).
First, we used XGeocoding software to convert the par-
ticipants’ speciﬁc home address information and the
locations of nine atmospheric monitoring stations in
Nanjing into longitude and latitude values. en we
imported the longitude and latitude data and the aver-
age exposure values of pollutants at diﬀerent stages
into ArcGIS software. e location of nine atmospheric
monitoring stations in Nanjing enables them to eﬀec-
tively monitor air pollution throughout the adminis-
trative area. On that basis, we used an inverse distance
weighting (IDW) modeling method to assign PM2.5 and
PM10 exposure levels for each residence address on each
day using daily pollutant concentrations from air quality
monitoring data between January 1st, 2014 and Decem-
ber 31st, 2016 . IDW interpolation was used as a spa-
tial interpolation method to model the distribution of air
pollutants using data from the ﬁxed monitoring stations.
e process of spermatogenesis includes a series of com-
plex steps including stem cell replication, meiosis, and
spermiogenesis that occur over approximately 74 days
in humans . With several days of epididymal transit
time (3-12 days) and an abstinence interval (controlled
in the analysis), an exposure period of approximately
90 days (a spermatogenic cycle) is regarded as being of
suﬃcient duration to detect eﬀects on any stage of sper-
matogenesis . erefore, concentrations of PM2.5 and
Fig. 1 Spatial distribution of nine ﬁxed ambient air quality monitoring stations and residence addresses of the 1554 participants in Nanjing, China
Page 4 of 12
Wuetal. Environmental Health (2022) 21:16
PM10 were calculated accordingly for the entire 90-day
period and four key periods (0-9, 10-14, 15-69, 70-90 days
before semen collection) preceding sampling .
Basic descriptive statistics were calculated to character-
ize the demographic information, PM exposure, and
semen quality parameters of the study population. We
analyzed the associations between the air pollution vari-
ables and semen parameters using adjusted multivariable
linear regression models and obtained coeﬃcients and
95% conﬁdence interval (CI). Given the non-normal dis-
tribution for semen volume, total sperm number, MAD,
VSL, STR, ALH, and BCF, these data were converted to
base-10 logarithms to meet the normality assumptions of
the statistical analysis.
Selection of covariates was based on biological plausi-
bility and their importance in the literature. We adjusted
all models for age, BMI, ethnicity, education, family
income, smoking status, alcohol consumption, season
of sperm collection, average ambient temperature, and
abstinence period. e average temperature was calcu-
lated as the mean of daily average temperature during
each exposure period.
Participants were further divided into ‘normal’ and
‘abnormal’ semen quality groups based on their semen
volume, sperm concentration, total sperm number and
total motility. e abnormal group (n= 535) was deﬁned
by having at least one of the following abnormal semen
parameters as deﬁned by reference levels from WHO
guidelines: semen volume < 1.5 ml, sperm concentra-
tion < 15 × 106/ml, total sperm number < 39 × 10,6 or
total motility < 40% . Removing this abnormal semen
parameter group left 1019 individuals as the normal
group. e eﬀect estimates were calculated for an incre-
ment of every 10 μg/m3 in average PM concentrations.
In addition, to better characterize exposure-response
associations, we divided PM2.5 exposures into quintiles
based on the distribution among all participants and esti-
mated regression coeﬃcients with the ﬁrst quintile as the
reference level. Eﬀect modiﬁcation by age, BMI, family
income, smoking status, and drinking status was assessed
by calculating product terms. A test for linear trend was
conducted with the use of quintiles of the PM2.5 expo-
sure variables as an ordinal variable.We also performed
stratiﬁed analyses of the association between PM2.5
and semen quality by age (< 35 and ≥ 35 ye ars), BMI
(< 24 and ≥ 24 kg/m2), family income (< 100,000 yuan
and ≥ 100,000 yuan), smoking status (never and former
or current) and alcohol drinking status (never and for-
mer or current). R software version 4.0.2 (R Core Team
R, 2020) was used to perform all statistical analyses. P
values < 0.05 were considered signiﬁcant. To address
multiple testing, we also calculated the false discovery
rate (FDR) using the Benjamini & Hochberg (BH) proce-
dure and the total number of hypotheses tested was 14.
All P values reported were two-sided.
Role ofthefunding source
e funder of the study did not play any role in study
design, data collection, data analysis, data interpreta-
tion, or writing of the report. e corresponding author
had full access to all the data in the study and was ﬁnally
responsible for the decision to submit for publication.
A ﬂowchart of participants in the study is shown in
Fig.S2. Characteristics of the entire group of 1554 fertile
men and the normal (n = 1019) and abnormal (n = 535)
semen quality groups are shown in Table1. e mean
age of men participating in this study was 30.9 (stand-
ard deviation [SD]: 4.2) years and two-thirds had college
or higher education (66.8%). e majority of men were
never smokers (62.3%) and less than half of the subjects
were ever drinkers (44.5%) (Table1).
Table 2 shows the distributions of the semen param-
eters for all participants. e Pearson correlations (r)
between the 14 semen parameters are shown in TableS1.
Total motility and progressive motility were very highly
correlated (r = 0.94) as were straight-line velocity (VSL)
and average path velocity (VAP) (r = 0.96), linearity (LIN)
and wobble (WOB) (r = 0.94) (Table S1). Fig. S3 shows
average daily temperatures in Nanjing between 2014
and 2016. e daily average temperature was as high as
34.1 °C in summer and as low as − 6.6 °C in winter. Aver-
age daily concentrations of PM2.5 and PM10 are plotted in
Fig.2 and Fig.S4 respectively. e daily concentrations
averaged 59.61 μg/m3 for PM2.5 and 101.77 μg/m3 for
PM10 over the study period (January 1st, 2014 - Decem-
ber 31st, 2016, 1098 days). PM2.5 and PM10 were posi-
tively correlated (r = 0.92, P < 0.05). e concentrations
of PM2.5 and PM10 showed clear seasonal variation with
higher levels in winter (maximums of 83.44 μg/m3 for
PM2.5 and 134.82 μg/m3 for PM10) than summer (mini-
mums of 45.19 μg/m3 for PM2.5 and 72.93 μg/m3 for
PM10). During the study period, PM2.5 was above the Chi-
nese 24-h standard (75 μg/m3, Grade II) on over 26% of
days; the rate of exceedance was lower for PM10 (16.7%
of days). TableS2 gives descriptive statistics for estimated
90-days participant exposures to the two pollutants. For
PM2.5, the average 90-days concentration was 60.80 μg/
m3 (SD = 13.30; interquartile range, IQR = 17.9). For
PM10, the average 90-days concentrations was 103.10 μg/
m3 (SD = 20.50; interquartile range, IQR = 34.10).
e results of the regression models for PM2.5 dur-
ing 0-90, 0-9, 10-14, 15-69, 70-90 days before the date of
Page 5 of 12
Wuetal. Environmental Health (2022) 21:16
Table 1 Characteristics of all fertile men participating in the study and the normal and abnormal semen quality groups
Note: SD standard deviation, BMI body mass index
a Group dened by semen volume ≥ 1.5 ml, sperm concentration ≥ 15 × 106/ml, total sperm number ≥ 39 × 10,6 and total motility ≥40%
b Group dened by at least one abnormal semen parameter (semen volume, sperm concentration, total sperm number or total motility)
Characteristic All participants (n= 1554) Normal semen quality group
(n= 1019)aAbnormal semen
Age (years), n (%)
< 35 1279 (82.3) 867 (85.1) 412 (77.0)
≥ 35 275 (17.7) 152 (14.9) 123 (23.0)
Range 17-52 21-50 17-52
Mean (SD) 30.9 (4.2) 30.7 (4.0) 31.4 (4.4)
BMI (kg/m2), n (%)
< 18.5 25 (1.6) 18 (1.8) 7 (1.3)
18.5 - 24.0 643 (41.4) 420 (41.2) 223 (41.7)
24.0 - 28.0 652 (42.0) 426 (41.8) 226 (42.2)
≥ 28.0 234 (15.0) 155 (15.2) 79 (14.8)
Mean (SD) 24.7 (3.3) 24.7 (3.3) 24.6 (3.2)
Ethnicity, n (%)
Han 1507 (97.0) 986 (96.8) 521 (97.4)
Other 47 (3.0) 33 (3.2) 14 (2.6)
Education, n (%)
Middle school and below 19 (1.2) 10 (1.0) 9 (1.7)
High school and secondary school 497 (32.0) 321 (31.5) 176 (32.9)
College degree and above 1038 (66.8) 688 (67.5) 350 (65.4)
Family income, n (%)
< 100,000 558 (35.9) 359 (35.2) 199 (37.3)
100,000 - 200,000 706 (45.4) 480 (47.0) 226 (42.3)
≥ 200,000 290 (18.7) 181 (17.8) 109 (20.4)
Smoking status, n (%)
Never smoker 968 (62.3) 629 (61.7) 339 (63.4)
Ever smoker 586 (37.7) 390 (38.3) 196 (36.6)
Current smoker 500 (32.2) 334 (32.8) 166 (31.0)
Former smoker 86 (5.5) 56 (5.5) 30 (5.6)
Drinking status, n (%)
Never drinker 862 (55.5) 575 (56.5) 287 (53.6)
Ever drinker 692 (44.5) 444 (43.5) 248 (46.4)
Current drinker 597 (38.4) 388 (38.0) 209 (39.1)
Former drinker 95 (6.1) 56 (5.5) 39 (7.3)
Season of sperm collection, n (%)
Spring 457 (29.4) 336 (33.0) 121 (22.6)
Summer 358 (23.0) 225 (22.1) 133 (24.9)
Autumn 371 (23.9) 225 (22.1) 146 (27.3)
Winter 368 (23.7) 233 (22.8) 135 (25.2)
Days of abstinence, mean (SD)
< 3 375 (24.1) 176 (17.3) 199 (37.2)
3 - 5 699 (45.0) 505 (49.5) 194 (36.3)*
≥ 5 480 (30.9) 338 (33.2) 142 (26.5)*
Mean (SD) 3.9 (2.6) 4.1 (2.7) 3.6 (2.4)
Semen volume (ml), mean (SD) 2.7 (1.3) 2.9 (1.2) 2.3 (1.5)*
Sperm concentration (106/ml)c58.3 (37.1-84.4) 63.6 (43.0-87.7) 47.5 (25.6-76.6)*
Total sperm number (106)c142.9 (79.8-231.8) 168.0 (111.9-248.6) 81.9 (34.2-169.6)*
Total motility (%)c56.3 (42.0-69.2) 61.8 (52.2-73.2) 36.0 (26.6-52.6)*
Page 6 of 12
Wuetal. Environmental Health (2022) 21:16
c Values are given as median (P25 - P75)
* P < 0.05 when compared with normal semen quality group
Table 1 (continued)
Table 2 Distribution of semen parameters for the participants (n = 1554)
a ALH amplitude of lateral head displacement, BCF beat cross frequency, LIN linearity, MAD mean angular displacement, SD standard deviation, STR straightness, VAP
average path velocity, VCL curvilinear velocity, VSL straight line velocity, WOB cur vilinear path wobble
Semen parameteraMean (SD) Percentile
10th 25th 50th 75th 90th
Semen volume (ml) 2.7 (1.3) 1.0 2.0 2.0 3.0 5.0
Sperm concentration (106/ml) 62.0 (32.0) 23.3 37.1 58.3 84.4 108.0
Total sperm number (106)172.2 (129.9) 39.6 79.2 142.6 231.3 341.7
Total motility (%) 55.2 (19.3) 28.5 42.0 56.2 69.3 80.0
Progressive motility (%) 43.8 (16.9) 21.9 31.8 44.1 55.9 65.4
VCL (μm/s) 47.7 (8.9) 37.3 42.1 47.2 53.3 59.2
VSL (μm/s) 29.8 (6.1) 23.0 25.8 29.6 33.6 37.6
VAP (μm/s) 33.5 (6.2) 26.4 29.4 33.4 37.5 41.3
BCF (Hz) 5.1 (0.7) 4.3 4.6 5.1 5.5 6.0
ALH (μm/s) 3.6 (1.1) 2.4 2.9 3.6 4.3 4.9
LIN (%) 61.3 (7.5) 52.1 56.2 61.2 66.4 70.8
STR (%) 85.2 (4.1) 80.2 83.0 85.6 88.0 89.8
WOB (%) 70.3 (6.4) 62.6 65.7 70.2 74.6 78.3
MAD (°) 56.6 (7.9) 46.8 52.0 57.2 62.1 65.9
Fig. 2 Distribution of daily PM2.5 in Nanjing between 2014 and 2016. The points in top and bottom graphs indicate daily PM2.5. The straight black
line indicates Chinese 24-h standard (Grade II) for PM2.5 (75 μg/m3)
Page 7 of 12
Wuetal. Environmental Health (2022) 21:16
semen examination in all participants are summarized
in Table 3. For the 0-90 days exposure period, an incre-
ment of 10 μg/m3 in PM2.5 was associated with a 2.21%
decrease in total motility and a 1.93% decrease in pro-
gressive motility. Inverse associations were also seen by
PM2.5 for the sperm motion parameters VCL, VSL, VAP
and ALH (all P < 0.05). No statistically signiﬁcant associ-
ation was observed for semen volume, sperm concentra-
tion, or total sperm number. For the four key periods of
sperm development (0-9, 10-14, 15-69, and 70-90 days),
the associations between PM2.5 exposure and progressive
motility as well as for the motion parameters BCF were
only related to the 70-90 days exposure period.
Table S3 presents the results of regression models of
PM10 exposure and semen quality in all subjects. For
the entire 0-90 days exposure period, PM10 exposure
were signiﬁcantly associated with the velocity param-
eters VCL and VAP, both inverse. Divided into four key
periods of sperm development (0-9, 10-14, 15-69, and
70-90 days), these statistically signiﬁcant inverse associa-
tions were limited to 70-90 days prior to semen collection
(Table S3). e analyses of PM2.5 and PM10 in normal
semen quality males during the entire 0-90 days exposure
period generally yielded similar ﬁndings to the entire
dataset (TablesS4 and S5). As for PM2.5, the coeﬃcients
of total motility and progressive motility were − 1.444
and − 1.370 respectively in the normal group. But the
associations became no statistically signiﬁcant after the
FDR adjustment in the abnormal group.
Table4 shows the results of exposure-response analy-
ses using quintiles of PM2.5 in the 0-90 days before semen
collection and semen quality in all participants. For all
participants, PM2.5 exposure was inversely associated
with total motility and progressive motility. e coef-
ﬁcient of total motility of the highest quintile of PM2.5
concentration compared with the lowest was − 8.42
(95%CI: − 11.98, − 4.86; P-trend < 0.001) for PM2.5 expo-
sure (Table4). In normal semen quality group, the coef-
ﬁcient of total motility of the highest quintile of PM2.5
exposure compared with the lowest was − 5.56 (95%CI:
− 8.79, − 2.33; P-trend = 0.006) (Table S6). It seemed
that the associations were linear as suggested by mono-
tonic trends across quintiles of PM2.5 exposure (P-trend
< 0.05). In abnormal semen quality group, the coeﬃcient
of total motility of the highest quintile of PM2.5 exposure
compared with the lowest was of − 7.35 (95%CI: − 13.16,
− 1.55; P-trend = 0.546) ( Table S7). It indicated that the
association between total motility and PM2.5 exposure
was nonlinear for abnormal semen quality group.
e results of the analyses of PM2.5 in relation to total
sperm motility stratiﬁed by age, BMI, family income,
smoking, and alcohol drinking are summarized in
Table S8. e eﬀect estimates were calculated for an
increment of every 10 μg/m3 in average PM2.5 concentra-
tions. Inverse associations were found in all subgroups
of BMI, family income (P < 0.05). For participants whose
age were over 35 years, who were former or current
smokers and who were former or current drinkers, there
were no obvious correlation between PM2.5 exposure and
total motility (P = 0.180, P = 0.053 and P = 0.195).
As far as we know, there are few studies investigating the
eﬀects of PM exposure on semen quality in a such large
population of men known to be fertile (TableS9). Tak-
ing into account potential confounding factors including
season and temperature, we found that PM2.5 exposure
was negatively associated with sperm motility, both total
and progressive. e inverse associations with PM2.5
exposure were generally stronger during 70-90 lag days
than those associations in the other three periods exam-
ined, which indicated that PM2.5 exposure might reduce
human semen quality by generally inﬂuencing the early
stage of sperm development and sperm motility. PM2.5
carries various environmental pollutants such as heavy
metals which interfere with germ cell function and aﬀect
gene expression . Spermatogenesis goes through
three stages: proliferative phase, meiotic phase, and sper-
matogenic phase. During the proliferative phase, the gene
expression caused by the contaminant is transmitted.
We identiﬁed statistically signiﬁcant ﬁndings but we do
not know if these have clinical signiﬁcance. We note that
although there are men in this population with sperm
parameters that meet a WHO deﬁnition of “abnormal”, all
of these men are fertile. Although we do not have data to
address this question, it is possible that these diﬀerences
in sperm parameters could have subtle eﬀects on fertil-
ity, such as time to pregnancy. e associations between
PM10 and sperm motility were weaker compared with
those for PM2.5, which further implicates PM2.5 speciﬁ-
cally as a reproductive toxicant. No signiﬁcant associa-
tion was found between PM and sperm concentration.
Motility parameters have been reported to be sensi-
tive biomarkers of human reproductive toxicity .
Fertility assessment of men is generally dependent on
the quality assessment of semen by conventional param-
eters such as motility, concentration, and morphology
of spermatozoa. Sperm motility is considered one of
the most important sperm functions that aﬀect natural
conception. Reduced sperm motility causes about 18%
of male infertility and infertility cases . In our study,
we found that PM2.5 was consistently associated with
decreased sperm total motility and progressive motil-
ity, but not sperm concentration. And the coeﬃcients in
total population were higher than in the normal group.
It indicated that the general population was much more
Page 8 of 12
Wuetal. Environmental Health (2022) 21:16
Table 3 Coeﬃcients from linear regression for PM2.5 exposure in relation to semen parameters by exposure period (0 - 90, 0 - 9, 10 - 14, 15 - 69, 70 - 90 days) prior to semen
collection in all participants (n = 1554) expressed as change in the parameter for a 10 μg/m3 increase in exposure
a ALH amplitude of lateral head displacement, BCF beat cross frequency, LIN linearity, MAD mean angular displacement, PM2.5 particulate matter with aerodynamic less than 2.5 μm, CI condence interval, STR straightness,
VAP average path velocity, VCL curvilinear velocity, VSL straight line velocity, WOB curvilinear path wobble
b Results were adjusted for age, BMI, ethnicity, education, smoking status, drinking status, family income, abstinence period, season, and temperature. P value for adjusting FDR using the Benjamini & Hochberg procedure
c Ambient particulate matter exposure of 10-14 days, 15-69 days, 70-90 days were also adjusted
d Ambient particulate matter exposure of 0-9 days, 15-69 days, 79-90 days were also adjusted
e Ambient particulate matter exposure of 0-9 days, 10-14 days, 70-90 days was also adjusted
f Ambient particulate matter exposure of 0-9 days, 10-14 days, 15-69 days was also adjusted
Semen parametera0-90 days 0-9 days 10-14 days 15-69 days 70-90 days
Coecient (×10; 95%
PbCoecient (×10; 95%
Pb, c Coecient (×10; 95%
Pb, d Coecient (× 10;
Pb, e Coecient (×10; 95%
Semen volume (ml) −0.003 (−0.025, 0.018) 0.965 −0.004 (−0.018, 0.010) 0.980 0.002 (−0.013, 0.010) 0.975 −0.002 (−0.023, 0.019) 0.851 0.009 (−0.007, 0.025) 0.324
Concentration (106/ml) 0.178 (−1.342, 1.698) 0.965 −0.127 (−1.105, 0.802) 0.980 −0.333 (−1.136, 0.471) 0.975 1.363 (−0.142, 2.868) 0.152 −0.496 (−1.625, 0.633) 0.419
Total sperm number
(106)0.001 (−0.039, 0.041) 0.965 −0.004 (−0.030, 0.022) 0.980 −0.011 (−0.032, 0.011) 0.975 0.025 (−0.015, 0.065) 0.372 0.003 (−0.033, 0.027) 0.834
Total motility (%) −2.211 (−3.121,
−1.301) < 0.001 −0.194 (−0.782, 0.394) 0.980 −0.216 (−0.698, 0.267) 0.975 −0.981 (−1.886,
−0.077) 0.094 −0.770 (−1.451,
Progressive motility (%) −1.925 (−2.720,
−1.131) < 0.001 −0.135 (−0.650, 0.380) 0.980 −0.090 (−0.512, 0.332) 0.975 −0.893 (−1.685,
−0.102) 0.094 −0.828 (−1.421,
VCL (μm/s) −1.054 (−1.467,
−0.640) < 0.001 −0.202 (−0.470, 0.066) 0.841 −0.011 (−0.208, 0.231) 0.989 −0.714 (−1.125,
−0.302) 0.009 −0.306 (−0.613,
VSL (μm/s) −0.022 (−0.032,
−0.011) < 0.001 −0.005 (−0.011, −0.002) 0.841 −0.001 (−0.006, 0.005) 0.975 −0.014 (−0.025,
−0.004) 0.038 −0.013 (−0.021,
VAP (μm/s) −0.714 (−1.000,
−0.428) < 0.001 −0.165 (−0.350, 0.020) 0.841 −0.016 (−0.135, 0.168) 0.975 −0.469 (−0.752,
−0.185) 0.009 −0.389 (−0.598,
BCF (Hz) 0.0004 (−0.003, 0.010) 0.510 −0.0004 (−0.004, 0.004) 0.980 −0.001 (−0.004, 0.002) 0.975 0.003 (−0.004, 0.009) 0.620 0.006(0.002, 0.011) 0.031
ALH (μm/s) −0.023 (−0.037,
−0.008) 0.005 0.004 (−0.005, 0.014) 0.980 0.0001 (−0.008, 0.008) 0.989 −0.014 (−0.029, 0.0001) 0.112 −0.006 (−0.017, 0.004) 0.312
LIN (%) −0.018 (−0.377, 0.340) 0.965 −0.003 (−0.235, 0.229) 0.980 0.071 (−0.119, 0.262) 0.975 −0.071 (−0.428, 0.285) 0.851 −0.264 (−0.528,
STR (%) −0.001 (−0.003, 0.002) 0.965 0.00002 (−0.002, 0.002) 0.980 0.001 (−0.0004, 0.002) 0.975 0.0003 (−0.003, 0.002) 0.851 −0.002 (−0.004,
WOB (%) −0.005 (−0.301, 0.310) 0.965 −0.009 (−0.207, 0.189) 0.980 0.019 (−0.143, 0.181) 0.975 −0.035 (−0.338, 0.268) 0.851 −0.217 (−0.443,
MAD (°) 0.004 (−0.009, 0.010) 0.965 −0.002 (−0.008, 0.005) 0.980 −0.002 (−0.007, 0.003) 0.975 0.001 (−0.008, 0.011) 0.851 0.006 (−0.002, 0.013) 0.174
Page 9 of 12
Wuetal. Environmental Health (2022) 21:16
sensitive to PM2.5 exposure to some extent. e inverse
associations prompted reduced motility caused by PM2.5
exposure may result in infertility but not absolutely.
Reduced motility would also aﬀect the time to pregnancy
, which needs to be collected and analyzed in further
study. Similar results, a negative correlation between
PM2.5 and sperm motility, were reported by Hammoud
etal. . Lao et al.  did not ﬁnd signiﬁcant asso-
ciations between PM2.5 exposure and sperm motility in
reproductive-age men. Selevan et al.  examined the
relationship between air pollution levels and VSL, VCL,
and LIN, and found that medium levels of air pollution
were negatively associated with VCL, but positively asso-
ciated with LIN. Wu etal. , in a study of 1759 infer-
tile men, reported that decreased sperm concentration
and count, but not sperm motility, were associated with
PM2.5. A recent study explored the association between
PM exposure and semen quality in a cohort of under-
graduate students and suggested that PM10 but not PM2.5
is associated with semen quality . ese conﬂicting
research results may be due to geographic or racial diﬀer-
ences and the diﬀerences in study designs and methods.
In particular, exposure concentrations of pollutants vary
from region to region (TableS8). us, although they
are the same contaminant, their eﬀect on semen quality
varies depending on the amount of individual exposure.
e participants of most previous studies were infertile
men [31, 42, 43], which may cause selection bias. While
in our study, participants were fertile men which could
better represent the general population. Besides, diﬀerent
measures of individual exposure also contribute to the
discrepancy. Lao etal.  used a spatiotemporal model
with high resolution (1 × 1 km) to estimate individual
exposure of PM2.5. Some other studies estimated air pol-
lution exposure at the community level [19, 25]. It may
mask exposure variation and cause misclassiﬁcation.
Smoking has been reported to be detrimental to semen
quality. Sokol et al. found that an increase in O3 lev-
els was associated with a decline in sperm quality, but
they did not look at the eﬀect modiﬁcations of cigarette
smoking on pollution and semen quality . Consider-
ing that the smoking eﬀect may operate concurrently in
the similar pathways , we further analyzed the asso-
ciations between PM2.5 exposure and semen quality by
smoking status. We found signiﬁcant eﬀect modiﬁcations
by smoking in the association between PM2.5 and semen
quality. Furthermore, we noted that our ﬁndings were
seen across age subgroups and drinking status subgroups.
Table 4 Coeﬃcients (95% CIs) from linear regression of PM2.5 exposure during 0 - 90 days before semen collection in relation to semen
parameters in all participants (n = 1554)
The coecients and 95% CIs were estimated using a linear model, adjusting for age, BMI, ethnicity, education, family income, smoking status, drinking status,
abstinence period, season, and temperature. Natural log transformation was applied for some sperm parameters
a ALH amplitude of lateral head displacement, BCF beat cross frequency, CI condence interval, LIN linearity, MAD mean angular displacement, PM2.5 particulate matter
with aerodynamic less than 2.5 μm, STR straightness, VAP average path velocity, VCL curvilinear velocity, VSL straight line velocity, WOB curvilinear path wobble
b P trend value for adjusting FDR using the Benjamini & Hochberg procedure
Semen parameteraQuintile of PM2.5 exposure (range) P trendb
Q1 (28.7-49.6) Q2 (49.7-57.0) Q3 (57.1-64.8) Q4 (64.9-74.0) Q5 (74.1-92.1)
Semen volume (ml) 0 (reference) 0.005 (−0.07, 0.08) −0.04 (−0.13, 0.04) −0.07 (−0.17, 0.01) −0.03 (−0.11, 0.06) 0.583
(106/ml) 0 (reference) 0.12 (−5.11, 5.36)) 2.53 (−3.33, 8.39) −2.18 (−8.18, 3.82) −0.96 (−6.92, 5.00) 0.862
Total sperm number
(106)0 (reference) 0.03 (−0.11, 0.17) 0.06 (−0.10, 0.22) −0.07 (−0.24, 0.09) −0.04 (−0.21, 0.12) 0.583
Total motility (%) 0 (reference) −6.21 (−9.33, −3.08) −4.98 (−8.48, −1.48) −7.00 (−10.58,
−4.86) < 0.001
(%) 0 (reference) −5.04 (−7.76, −2.31) −3.74 (−6.79, −0.69) −4.69 (−7.82, −1.57) −7.41 (−10.52,
−4.30) < 0.001
VCL (μm/s) 0 (reference) −0.03 (−1.46, 1.40) −1.38 (−2.98, 0.22) −1.18 (−2.82, 0.46) −3.24 (−4.82, −1.61) < 0.001
VSL (μm/s) 0 (reference) −0.005 (−0.04, 0.03) −0.01 (−0.05, 0.03) −0.01 (−0.05, 0.03) −0.07 (−0.11, −0.03) < 0.001
VAP (μm/s) 0 (reference) −0.21 (−1.20, 0.77) −0.37 (−1.47, 0.73) −0.47 (−1.60, 0.66) −2.27 (−3.39, −1.15) < 0.001
BCF (Hz) 0 (reference) −0.002 (−0.02, 0.02) −0.02 (−0.04, 0.003) −0.03 (−0.06, −0.01) 0.01 (−0.01, 0.04) 0.611
ALH (μm/s) 0 (reference) 0.01 (−0.04, 0.06) −0.02 (−0.07, 0.03) −0.03 (−0.09, 0.02) −0.06 (−0.11,
LIN (%) 0 (reference) −0.46 (−1.69, 0.76) 0.78 (−0.59, 2.16) 0.83 (−0.58, 2.24) −0.37 (−1.77, 1.03) 0.971
STR (%) 0 (reference) 0.001 (−0.01, 0.01) 0.005 (−0.004, 0.01) 0.01 (−0.01, 0.02) −0.003 (−0.01, 0.01) 0.862
WOB (%) 0 (reference) −0.42 (−1.46, 0.63) 0.56 (−0.61, 1.73) 0.61 (−0.59, 1.81) −0.22 (−1.42, 0.97) 0.986
MAD (°) 0 (reference) −0.0005 (−0.03, 0.03) −0.01 (−0.05, 0.02) −0.01 (−0.03, 0.04) 0.002 (−0.03, 0.04) 0.971
Page 10 of 12
Wuetal. Environmental Health (2022) 21:16
As one of the most signiﬁcant characteristics related
to the fertilizing ability of spermatozoa, motility reﬂects
their viability and structural integrity . However, the
biological mechanisms behind the association between
PM exposure and decreased sperm motility have yet to
be determined. Previous investigations have suggested
that PM exposure is probably associated with increased
oxidative stress due to decreased antioxidant defenses
or excess reactive oxygen species (ROS) production.
Oxidative stress performs an essential role to trigger
cellular pathological process including proliferation,
inﬂammation, and apoptosis . PM2.5 component spe-
cies include elemental carbon, organic compounds like
polycyclic aromatic hydrocarbons (PAHs), and heavy
metals . PM2.5 is mainly deposited within the distal
alveoli after inhalation . Such PM2.5 exposure will
result in ROS generation which then leads to system-
atical oxidative stress and cell impairment. An animal
study has reported that Sertoli cells (SCs) would pro-
duce a large amount of ROS after exposure to PM2.5. e
oxidative stress damage in cells resulted in activation of
the mitogen-activated protein kinases (MAPK) pathway,
increasing SCs apoptosis, then destroying the integrity
of the blood-testis barrier, ﬁnally causing the quality of
semen . Moreover, PAHs and multiple trace elements
in PM2.5 might contribute to poor sperm quality. Human
and animal studies have suggested possible associations
between PAH exposure and male reproductive function
[48, 49]. Izawa etal.  demonstrated inverse associa-
tions between PAH exposures and sperm production,
sperm abnormalities and sperm motility in an animal
study. Our previous study suggested that PAH exposure
contributed to decreased semen quality in a Chinese
population . Adverse inﬂuences of metals such as
cadmium and lead on spermatogenesis have been dem-
onstrated . Further studies are warranted to elucidate
the underlying mechanism as well as the speciﬁc compo-
nents of PM2.5 that may be driving associations.
Some limitations need to be addressed. As in most
studies of health eﬀects of air pollution, we did not meas-
ure exposure directly at the individual level. It is not
accurate to substitute the average exposure of a region
for that of an individual. And we didn’t rule out the
inﬂuence of individual time-activities. However, sam-
pling air pollution at the individual level is not realistic.
Moreover, there is no clear exposure marker to charac-
terize individual exposure levels. Secondly, we estimated
ambient PM2.5 and PM10 using outdoor air monitors,
but indoor environments and time-activity patterns can
also inﬂuence individual and population level exposures.
us, individual exposure is underestimated. In part, it
may weaken the link between ambient particulate mat-
ter exposure and semen quality. irdly, the fertile men
delivered only one semen sample each. However, a pre-
vious study has shown that while a single semen sample
may not be adequate for clinical diagnosis of infertility,
that it should suﬃce for studies aimed at identifying aver-
age diﬀerences in semen quality between individuals .
e associations between PM2.5 and sperm motility both
in men with all normal sperm parameters as well as in
men with at least one abnormal sperm parameter provide
additional evidence that PM2.5 inﬂuences sperm motil-
ity across the population as a whole. Besides, we did not
have the urine or blood sample to detect other exposure
metabolities like endocrine disruptors.
is study has many strengths. One unique feature is
that we examined representative samples from a popula-
tion known to be fertile rather than the infertile popula-
tions from infertility clinics or men of unknown fertility
as in most previous studies [31, 54]. When evaluating
the eﬀects of air pollution on semen quality properly, it
is important to control for confounding factors . We
had information on various potential confounders in
our study. In addition, we used the IDW interpolation to
estimate individual air pollution exposures. Some previ-
ous studies estimated air pollution exposure at the com-
munity level, which could cause misclassiﬁcation and
mask exposure variation . Further, we assessed a wide
range of 14 semen parameters to investigate the associa-
tions between PM exposure and semen quality in a more
comprehensive manner than in most studies.
In conclusion, a robust association was found between
exposure to PM2.5 in speciﬁc window (70-90 days prior to
ejaculation) and reduced sperm motility measures in fer-
tile men. We did not see signiﬁcant associations between
PM2.5 and sperm concentration or count. ese results
indicate that PM2.5 exposure does not reduce the num-
ber of sperm produced but does impact its functional-
ity which could reduce the ability to fertilize the ovum.
Meanwhile, PM10 plays a less important role than PM2.5
in the relationship between PM exposure and sperm
motility. is suggests that PM2.5 is a more meaningful
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12940- 022- 00831-5.
Additional le1: Figure S1. Sperm kinematic parameters measured by
computer assisted semen analysis (CASA). ALH, amplitude of lateral head
displacement; BCF, beat cross frequency; LIN, linearity; MAD, mean angular
displacement; STR, straightness; VAP, average path velocity; VCL, curvilinear
velocity; VSL, straight line velocity; WOB, curvilinear path wobble. Figure
S2. Flowchart of participants in the study. Normal semen quality group
deﬁned by semen volume ≥ 1.5 ml, sperm concentration ≥ 15 × 106/ml,
total sperm number ≥ 39 × 10,6 and total motility ≥40%. Abnormal semen
quality group deﬁned by at least one abnormal semen parameters (semen
volume, sperm concentration, total sperm number or sperm motility).
Page 11 of 12
Wuetal. Environmental Health (2022) 21:16
Figure S3. Distribution of daily temperatures in Nanjing between 2014
and 2016. The points in top and bottom graphs indicate daily tempera-
tures. Figure S4. Distribution of daily PM10 in Nanjing between 2014
and 2016. The points in top and bottom graphs indicate daily PM10. The
straight black line indicates Chinese 24-h standard (Grade II) for PM10
(150 μg/m3). TableS1. Coeﬃcient of correlation between the semen
parameters. TableS2. Distribution of air pollutant exposure for study
subjects. TableS3. Coeﬃcients from linear regression for PM10 exposure
in relation to semen parameters by exposure period (0-90, 0-9, 10-14,
15-69, 70-90 days) prior to semen collection in all participants (n = 1554)
expressed as change in the parameter for a 10 μg/m3 increase in exposure.
TableS4. Coeﬃcients from linear regression for PM2.5 exposure in rela-
tion to semen parameters by exposure period (0-90, 0-9, 10-14, 15-69,
70-90 days) prior to semen collection in normal and abnormal semen
parameters groups expressed as change in the parameter for a 10 μg/
m3 increase in exposure. TableS5. Coeﬃcients from linear regression for
PM10 exposure in relation to semen parameters by exposure period (0-90,
0-9, 10-14, 15-69, 70-90 days) prior to semen collection in normal and
abnormal semen parameters groups expressed as change in the param-
eter for a 10 μg/m3 increase in exposure. TableS6. Coeﬃcients (95% CIs)
from linear regression of PM2.5 exposure during 0-90 days before semen
collection in relation to sperm parameters in normal semen parameters
group expressed as change in the parameter for a 10 μg/m3 increase in
exposure. TableS7. Coeﬃcients (95% CIs) from linear regression of PM2.5
exposure during 0-90 days before semen collection in relation to sperm
parameters in abnormal semen parameters group expressed as change in
the parameter for a 10 μg/m3 increase in exposure. TableS8. Coeﬃcients
from linear regression for PM2.5 exposure in relation to total sperm motility
by categories of age, BMI, income, cigarette smoking and alcohol drinking
expressed as change in the parameter for a 10 μg/m3 increase in exposure.
TableS9. Characteristics and main results of previous studies examined
the association between PM and semen quality.
Wei Wu: Conceptualization, methodology, formal analysis, resources, writing -
original draft preparation, funding acquisition, writing - review & editing. Yiqiu
Chen: Methodology, formal analysis, writing - original draft preparation. Yuting
Cheng: Validation, data curation, formal analysis, visualization. Qiuqin Tang:
Validation, funding acquisition, writing - review & editing. Feng Pan: Resources,
writing - review & editing. Naijun Tang, Zhiwei Sun and Xinru Wang: Resources.
Stephanie J. London: Writing - reviewing and editing, funding acquisition.
Yankai Xia: Resources, supervision, funding acquisition, writing - review & edit-
ing. The author(s) read and approved the ﬁnal manuscript.
This work was supported by the National Key R&D Program of China
(2017YFC0211605), National Natural Science Foundation of China (81673217,
81971405), Major Research Projects in Natural Science of Jiangsu University
(20KJA330001), Medical Research Project of Jiangsu Health and Health Com-
mission (Z2019010), Jiangsu Overseas Visiting Scholar Program for University
Prominent Young & Middle-aged Teachers and Presidents, and the Prior-
ity Academic Program for the Development of Jiangsu Higher Education
Institutions (Public Health and Preventive Medicine). Supported in part by the
Intramural Research Program of the NIH, National Institute of Environmental
Health Sciences (ZO1 ES49019).
Availability of data and materials
The datasets used and/or analysed during the current study are available from
the corresponding author on reasonable request.
Ethics approval and consent to participate
This study was approved by the Institutional Review Board of Nanjing Medical
University, China NJMUIRB (2010) 0028.
Consent for publication
The authors declare that they have no competing interests.
1 State Key Laboratory of Reproductive Medicine, Institute of Applied Toxicol-
ogy, School of Public Health, Nanjing Medical University, 101 Longmian
Avenue, Nanjing 211166, China. 2 Key Laboratory of Modern Toxicology
of Ministry of Education, School of Public Health, Nanjing Medical University,
Nanjing, China. 3 Department of Health and Human Services, National Institute
of Environmental Health Sciences, National Institutes of Health, Research Tri-
angle Park, Durham, USA. 4 Department of Obstetrics, The Aﬃliated Obstetrics
and Gynecology Hospital of Nanjing Medical University, Nanjing Maternity
and Child Health Care Hospital, Nanjing, China. 5 Department of Urology, The
Aﬃliated Obstetrics and Gynecology Hospital of Nanjing Medical University,
Nanjing Maternity and Child Health Care Hospital, Nanjing, China. 6 Depart-
ment of Occupational and Environmental Health, School of Public Health,
Tianjin Medical University, Tianjin, China. 7 Beijing Key Laboratory of Environ-
mental Toxicology, School of Public Health, Capital Medical University, Beijing,
Received: 4 August 2021 Accepted: 7 January 2022
1. Mascarenhas MN, Flaxman SR, Boerma T, Vanderpoel S, Stevens GA.
National, regional, and global trends in infertility prevalence since 1990: a
systematic analysis of 277 health surveys. PLoS Med. 2012;9(12):e1001356.
2. Wang X, Tian X, Ye B, Zhang Y, Zhang X, Huang S, et al. The association
between ambient temperature and sperm quality in Wuhan, China.
Environ Health. 2020;19(1):44.
3. Mao H, Feng L, Yang WX. Environmental factors contributed to circannual
rhythm of semen quality. Chronobiol Int. 2017;34(3):411–25.
4. Mendiola J, Jorgensen N, Andersson AM, Stahlhut RW, Liu F, Swan SH.
Reproductive parameters in young men living in Rochester, New York.
Fertil Steril. 2014;101(4):1064–71.
5. Jurewicz J, Hanke W, Radwan M, Bonde JP. Environmental factors and
semen quality. Int J Occup Med Environ Health. 2009;22(4):305–29.
6. Li CJ, Yeh CY, Chen RY, Tzeng CR, Han BC, Chien LC. Biomonitoring of
blood heavy metals and reproductive hormone level related to low
semen quality. J Hazard Mater. 2015;300:815–22.
7. Gulland A. Air pollution responsible for 600 000 premature deaths world-
wide. BMJ. 2002;325(7377):1380.
8. Cheng Z, Wang S, Jiang J, Fu Q, Chen C, Xu B, et al. Long-term trend of
haze pollution and impact of particulate matter in the Yangtze River
Delta, China. Environ Pollut. 2013;182:101–10.
9. Brook RD, Rajagopalan S, Pope CA 3rd, Brook JR, Bhatnagar A, Diez-Roux
AV, et al. Particulate matter air pollution and cardiovascular disease: An
update to the scientiﬁc statement from the American Heart Association.
10. Chen J, Hoek G. Long-term exposure to PM and all-cause and cause-
speciﬁc mortality: a systematic review and meta-analysis. Environ Int.
11. Landrigan PJ, Fuller R, Acosta NJR, Adeyi O, Arnold R, Basu NN,
et al. The lancet commission on pollution and health. Lancet.
12. Turner MC, Andersen ZJ, Baccarelli A, Diver WR, Gapstur SM, Pope CA
3rd, et al. Outdoor air pollution and cancer: an overview of the cur-
rent evidence and public health recommendations. CA Cancer J Clin.
13. Yang D, Ma M, Zhou W, Yang B, Xiao C. Inhibition of miR-32 activity pro-
moted EMT induced by PM2.5 exposure through the modulation of the
Smad1-mediated signaling pathways in lung cancer cells. Chemosphere.
14. Pedersen M, Giorgis-Allemand L, Bernard C, Aguilera I, Andersen AM,
Ballester F, et al. Ambient air pollution and low birthweight: a European
cohort study (ESCAPE). Lancet Respir Med. 2013;1(9):695–704.
Page 12 of 12
Wuetal. Environmental Health (2022) 21:16
15. Grigg J. Eﬀects of air pollution on fetal development-more than low
birthweight? Lancet Respir Med. 2013;1(9):666–7.
16. Somers CM. Ambient air pollution exposure and damage to male gam-
etes: human studies and in situ ’sentinel’ animal experiments. Syst Biol
Reprod Med. 2011;57(1-2):63–71.
17. Kim KH, Kabir E, K abir S. A review on the human health impact of air-
borne particulate matter. Environ Int. 2015;74:136–43.
18. Pires A, de Melo EN, Mauad T, Nascimento Saldiva PH, de Siqueira
Bueno HM. Pre- and postnatal exposure to ambient levels of urban
particulate matter (PM(2.5)) aﬀects mice spermatogenesis. Inhal Toxicol.
19. Zhou N, Cui Z, Yang S, Han X, Chen G, Zhou Z, et al. Air pollution and
decreased semen quality: a comparative study of Chongqing urban and
rural areas. Environ Pollut. 2014;187:145–52.
20. Carré J, Gatimel N, Moreau J, Parinaud J, Léandri R. Does air pollution play
a role in infertility?: a systematic review. Environ Health. 2017;16(1):82.
21. De Rosa M, Zarrilli S, Paesano L, Carbone U, Boggia B, Petretta M, et al.
Traﬃc pollutants aﬀect fertility in men. Hum Reprod. 2003;18(5):1055–61.
22. Deng Z, Chen F, Zhang M, Lan L, Qiao Z, Cui Y, et al. Association between
air pollution and sperm quality: a systematic review and meta-analysis.
Environ Pollut. 2016;208(Pt B):663–9.
23. Guven A, Kayikci A, Cam K, Arbak P, Balbay O, Cam M. Alterations in
semen parameters of toll collectors working at motorways: does
diesel exposure induce detrimental eﬀects on semen? Andrologia.
24. Rubes J, Selevan SG, Evenson DP, Zudova D, Vozdova M, Zudova Z, et al.
Episodic air pollution is associated with increased DNA fragmentation
in human sperm without other changes in semen quality. Hum Reprod.
25. Selevan SG, Borkovec L, Slott VL, Zudova Z, Rubes J, Evenson DP, et al.
Semen quality and reproductive health of young Czech men exposed to
seasonal air pollution. Environ Health Perspect. 2000;108(9):887–94.
26. Johnson L, Falk GU, Suggs LC, Henderson DJ, Spoede GE, Brown SW,
et al. Heterotopic transplantation as a model to study the regulation of
spermatogenesis; some histomorphological considerations about sperm
decline in man. Contracept Fertil Sex. 1997;25(7-8):549–55.
27. Radwan M, Jurewicz J, Polanska K, Sobala W, Radwan P, Bochenek M, et al.
Exposure to ambient air pollution--does it aﬀect semen quality and the
level of reproductive hormones? Ann Hum Biol. 2016;43(1):50–6.
28. Lao XQ, Zhang Z, Lau AKH, Chan TC, Chuang YC, Chan J, et al. Exposure
to ambient ﬁne particulate matter and semen quality in Taiwan. Occup
Environ Med. 2018;75(2):148–54.
29. Sokol RZ, Kraft P, Fowler IM, Mamet R, Kim E, Berhane KT. Exposure to
environmental ozone alters semen quality. Environ Health Perspect.
30. Hansen C, Luben TJ, Sacks JD, Olshan A, Jeﬀay S, Strader L, et al. The
eﬀect of ambient air pollution on sperm quality. Environ Health Perspect.
31. Wu L, Jin L, Shi T, Zhang B, Zhou Y, Zhou T, et al. Association between
ambient particulate matter exposure and semen quality in Wuhan, China.
Environ Int. 2017;98:219–28.
32. Sharma R, Harlev A, Agarwal A, Esteves SC. Cigarette smoking and semen
quality: a new Meta-analysis examining the eﬀect of the 2010 World
Health Organization Laboratory methods for the examination of human
semen. Eur Urol. 2016;70(4):635–45.
33. Brauer M, Lencar C, Tamburic L, Koehoorn M, Demers P, Karr C. A cohort
study of traﬃc-related air pollution impacts on birth outcomes. Environ
Health Perspect. 2008;116(5):680–6.
34. Clermont Y. The cycle of the seminiferous epithelium in man. Am J Anat.
35. Cooper TG, Noonan E, von Eckardstein S, Auger J, Baker HW, Behre HM,
et al. World Health Organization reference values for human semen
characteristics. Hum Reprod Update. 2010;16(3):231–45.
36. Jenardhanan P, Panneerselvam M, Mathur PP. Eﬀect of environmental
contaminants on spermatogenesis. Semin Cell Dev Biol. 2016;59:126–40.
37. Kwack SJ, Lee BM. Comparative cytotoxicity and sperm motility using a
computer-aided sperm analysis system (CASA) for isomers of Phthalic
acid, a common ﬁnal metabolite of phthalates. J Toxicol Environ Health A.
38. Khosronezhad N, Hosseinzadeh Colagar A, Mortazavi SM. The Nsun7
(A11337)-deletion mutation, causes reduction of its protein rate and
associated with sperm motility defect in infertile men. J Assist Reprod
39. Tang Q, Pan F, Wu X, Nichols CE, Wang X, Xia Y, et al. Semen quality and
cigarette smoking in a cohort of healthy fertile men. Environ Epidemiol.
40. Hammoud A, Carrell DT, Gibson M, Sanderson M, Parker-Jones K, Peterson
CM. Decreased sperm motility is associated with air pollution in Salt Lake
City. Fertil Steril. 2010;93(6):1875–9.
41. Zhou N, Jiang C, Chen Q, Yang H, Wang X, Zou P, et al. Exposures to
Atmospheric PM10 and PM10-2.5 Aﬀect Male Semen Quality: Results of
MARHCS Study. Environ Sci Technol. 2018;52(3):1571–81.
42. Guan Q, Chen S, Wang B, Dou X, Lu Y, Liang J, et al. Eﬀects of particulate
matter exposure on semen quality: a retrospective cohort study. Ecotoxi-
col Environ Saf. 2020;193:110319.
43. Tian XJ, Wang XC, Ye B, Li CL, Zhang Y, Ma L. The eﬀects of exposure to
ozone on sperm quality in Wuhan. Zhonghua Yu Fang Yi Xue Za Zhi.
44. Nagy A, Polichronopoulos T, Gaspardy A, Solti L, Cseh S. Correlation
between bull fertility and sperm cell velocity parameters generated by
computer-assisted semen analysis. Acta Vet Hung. 2015;63(3):370–81.
45. Saﬀari M, Koenig HG, Pakpour AH, Sanaeinasab H, Jahan HR, Sehlo MG.
Personal hygiene among military personnel: developing and testing a
self-administered scale. Environ Health Prev Med. 2014;19(2):135–42.
46. White AJ, Kresovich JK, Keller JP, Xu Z, Kaufman JD, Weinberg CR, et al.
Air pollution, particulate matter composition and methylation-based
biologic age. Environ Int. 2019;132:105071.
47. Liu B, Shen LJ, Zhao TX, Sun M, Wang JK, Long CL, et al. Automobile
exhaust-derived PM(2.5) induces blood-testis barrier damage through
ROS-MAPK-Nrf2 pathway in sertoli cells of rats. Ecotoxicol Environ Saf.
48. Yang P, Chen D, Wang YX, Zhang L, Huang LL, Lu WQ, et al. Mediation
of association between polycyclic aromatic hydrocarbon exposure and
semen quality by spermatogenesis-related microRNAs: a pilot study in an
infertility clinic. J Hazard Mater. 2020;384:121431.
49. Jeng HA, Yu L. Alteration of sperm quality and hormone levels by polycy-
clic aromatic hydrocarbons on airborne particulate particles. J Environ Sci
Health A Tox Hazard Subst Environ Eng. 2008;43(7):675–81.
50. Izawa H, Kohara M, Watanabe G, Taya K, Sagai M. Eﬀects of diesel
exhaust particles on the male reproductive system in strains of mice
with diﬀerent aryl hydrocarbon receptor responsiveness. J Reprod Dev.
51. Xia Y, Zhu P, Han Y, Lu C, Wang S, Gu A, et al. Urinary metabolites of
polycyclic aromatic hydrocarbons in relation to idiopathic male infertility.
Hum Reprod. 2009;24(5):1067–74.
52. Pant N, Kumar G, Upadhyay AD, Patel DK, Gupta YK, Chaturvedi PK.
Reproductive toxicity of lead, cadmium, and phthalate exposure in men.
Environ Sci Pollut Res Int. 2014;21(18):11066–74.
53. Chiu YH, Edifor R, Rosner BA, Nassan FL, Gaskins AJ, Minguez-Alarcon L,
et al. What does a single semen sample tell you? Implications for male
factor infertility research. Am J Epidemiol. 2017;186(8):918–26.
54. Yang P, Wang YX, Chen YJ, Sun L, Li J, Liu C, et al. Urinary polycyclic
aromatic hydrocarbon metabolites and human semen quality in China.
Environ Sci Technol. 2017;51(2):958–67.
55. Jurewicz J, Radwan M, Sobala W, Polanska K, Radwan P, Jakubowski L,
et al. The relationship between exposure to air pollution and sperm
disomy. Environ Mol Mutagen. 2015;56(1):50–9.
Springer Nature remains neutral with regard to jurisdictional claims in pub-
lished maps and institutional aﬃliations.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at