Bacterial compositions in inhalable particulate matters from indoor and outdoor wastewater treatment processes

Journal Pre-proof Bacterial Compositions in Inhalable Particulate Matters from Indoor and Outdoor Wastewater Treatment Processes Miaomiao Liu, Masaru K. Nobu, Jia Ren, Xiaowei Jin, Gang Hong, Hong Yao

PII:

S0304-3894(19)31469-4

DOI:

https://doi.org/10.1016/j.jhazmat.2019.121515

Reference:

HAZMAT 121515

To appear in:

Journal of Hazardous Materials

Received Date:

23 August 2019

Revised Date:

6 October 2019

Accepted Date:

19 October 2019

Please cite this article as: Liu M, Nobu MK, Ren J, Jin X, Hong G, Yao H, Bacterial Compositions in Inhalable Particulate Matters from Indoor and Outdoor Wastewater Treatment Processes, Journal of Hazardous Materials (2019), doi: https://doi.org/10.1016/j.jhazmat.2019.121515

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.

Bacterial Compositions in Inhalable Particulate Matters from Indoor and Outdoor Wastewater Treatment Processes

Miaomiao Liu 1, 2, Masaru K. Nobu 3, Jia Ren 1, Xiaowei Jin 4, Gang Hong 5, Hong Yao 1*

Department of Civil and Environmental Engineering, Beijing Jiaotong University, Beijing,

of

1

China;

Department of Urban Engineering, the University of Tokyo, Tokyo, Japan;

3

Bioproduction Research Institute, National Institute of Advanced Industrial Science and

-p

ro

2

Technology, Tsukuba, Ibaraki, Japan;

China National Environmental Monitoring Center, Beijing, 100012, China;

5

Shijiazhuang Environmental Monitoring Station, Hebei Province, China.

Jo

ur na

Graphical abstract

lP

re

4

of ro -p re lP

Highlights:

Bacterial communities were different in aerosols from indoor and outdoor treatment.

ur na

Aerosolization dominated aerosol bacterial community from indoor sludge treatment. Dispersion governed aerosol bacterial community from outdoor wastewater treatment. Preferentially aerosolized and persistently surviving bacteria were identified.

Jo

Opportunistic pathogenic bacteria were identified in PM2.5 and PM10.

Abstract Wastewater treatment systems are critical microbial sources for urban air and play important roles in public health. In this study, bacterial communities in particulate matters

(PM2.5, PM10) from wastewater/sludge treatment facilities of two full-scale wastewater treatment plants were analyzed by 16S rRNA amplicon sequencing. Compared to the background ambient air, Campylobacteriadeceae, Aeromonadaceae, and Chlostridiaceae were the most enriched bacteria above wastewater treatment facilities. In sludge dewatering facilities, Comamonadaceae, Chitinophagaceae, Caldilineaceae, Mycobacteriaceae, Methylocystaceae,

of

Microbacteriaceae, Cryomorphaceae, and uncultured Class OPB56 were the most enriched. The dynamic bacterial compositions in aerosols were contributed by aerosolization and dispersion.

ro

Principal coordinate analysis and clustering analysis showed that the aerosol bacterial

community from indoor sludge treatment were closely clustered with that of sludge, indicating

-p

that aerosolization dominated the indoor environments. In contrast, aerosols from outdoor

re

wastewater treatment facilities clustered with background ambient aerosols, indicating that outdoor aerosol bacterial communities were mainly governed by dispersion. Aerosolization

lP

factor (the ratio of bacteria abundance in aerosols to those in wastewater/sludge) was used to evaluate the aerosolization potential and survival of bacteria. Rhodocyclaceae, Arcobacter,

ur na

Comamonadaceae, Mycobacterium, and Citrobacter were not only preferentially aerosolized from wastewater/sludge, but also sustainable during dispersion in ambient air. Keywords: aerosol bacterial community; wastewater treatment; sludge dewatering; indoor/outdoor; aerosolization factor

Jo

1. 1. Introduction

The air environment is an important medium involved with public health and ecosystem

sustainability (Cao et al., 2014; Zheng et al., 2015). The urban air environment typically contains gas-form pollutants such as carbon monoxide, nitrogen oxides, sulfur dioxide, and ozone as well as particulate matters (PM). Despite the harsh living conditions in the air such as low moisture,

low nutrients, UV, etc., microbes are vital components of the PM, among which some are involved in respiratory system diseases and atmospheric chemistry (Zhai et al., 2018; Zhang et al., 2016). PM is categorized by size to indicate their different inhale potentials. PM10, which are inhalable coarse particles with nominal mean aerodynamic diameters of less than 10 µm, can reach the extrathoracic and upper tracheobronchial regions, while fine particles, PM2.5 (≤2.5

of

µm), can penetrate and deposit deeper in the tracheobronchial and alveolar regions (Brook et al., 2004). PM larger than 10 µm can be blocked from entering the human body by vibrissa and

ro

therefore is less harmful to health than the inhalable PM2.5 and PM10 (Korzeniewska, 2011). Aerosol microbes originate from both natural sources (soils, plants, water bodies) and

-p

anthropogenic sources such as traffic, coal burning, industries, etc. (Smets et al., 2016).

re

Wastewater treatment plants (WWTP) are important sources of urban microbial aerosols because some wastewater treatment processes can promote the emission of bacteria, such as vigorous

lP

aeration during the aerobic activated sludge process (Brandi et al., 2000) and strong stirring of biomass during sludge concentration and dewatering (Han et al., 2018; Pascual et al., 2003, Yang

ur na

et al., 2019). Culture-dependent methods revealed diverse bacteria in the total PM from WWTPs (Han et al., 2013; Xu et al., 2018). With the development of next-generation sequencing, robust evaluation of aerosol emission from WWTPs can be performed with adequate coverage and depth (Ghosh et al., 2015). Yang et al. (2019) reported the high diversity of bacteria including

Jo

opportunistic pathogens in the total PM (≤100 µm) after different sewage treatment processes. Previous research reported diverse bacterial compositions in six different size ranges (> 7.9 µm, 3.3–7.9 µm, 1.6–3.3 µm, 1.0-1.6 µm, 0.55–1.0 µm, < 0.55 µm) from African dusts using 16S rRNA gene cloning, with high occurrence of clones phylogenetically related to human pathogens in inhalable PM (< 3.3 µm) (Polymenakou et al., 2008). In a wastewater treatment plant,

concentrations of heterotrophic bacteria were found related to particulate sizes at the aerated grit chambers, with the highest bacteria concentration at the size range of 3.3 to 4.7 µm (Katsivela et al., 2017). Although numerous studies have evaluated bacteria in the total PM from WWTPs, bacteria in the inhalable PM2.5 and PM10 need to be studied to determine their aerosolization characteristics, fates, and health hazards.

of

Most studies on aerosolized bacteria from WWTPs have focused on emission loads and microbial communities. However, how bacteria become aerosolized, why certain bacteria are

ro

preferentially aerosolized, and why certain bacteria survive more robustly than others remain unclear but are central to understanding the aerosolization processes and health risks of WWTPs.

-p

The factors defining the dynamic bacterial community in PM samples can be classified into two

re

major processes: (1) bacteria are aerosolized from wastewater/sludge into the local air (aerosolization) and (2) bacteria in the local air diffuse into the ambient air (dispersion), which is

lP

influenced by meteorological factors such as wind and precipitation (Zhen et al., 2017). The aerosolization factor (AF), which is the ratio of the relative abundance of each bacterium in

ur na

PM2.5 and PM10 to that in the bulk water, has been proved to effectively identify taxon-specific aerosolization properties from the freshwater and oceanic water (Hejkal et al., 1980; Michaud et al., 2018). In the present work, AF was used to quantitatively evaluate the two major processes, aerosolization and dispersion, of bacteria in WWTPs.

Jo

In the present study, inhalable PM2.5 and PM10 were collected at outdoor wastewater

and indoor sludge treatment facilities from a full-scale municipal WWTP and a full-scale pharmaceutical WWTP located in Shijiazhuang city, Hebei Province of China. The counterparts of wastewater and sludge samples were collected at the same time to study emission. Bacterial compositions were analyzed by 16S rRNA gene amplicon sequencing (Illumina Miseq, San

Diego, CA, USA) for all samples. The objectives of this study were: (1) to survey the bacterial compositions in PM2.5 and PM10 from municipal and pharmaceutical WWTPs; (2) to understand the aerosolization potential of different bacteria in the WWTP bacterial community; and (3) to determine the fates of aerosolized bacteria in ambient air. 2. Materials and methods

of

2.1. Sample collection for PM2.5, PM10, and wastewater/sludge Aerosol (PM2.5, PM10) and wastewater/sludge samples were collected from 4 locations

ro

at a municipal wastewater treatment plant (WWTP-A) and 3 locations at a pharmaceutical wastewater treatment plant (WWTP-B) in Shijiazhuang City, Hebei Province (Figure 1).

-p

WWTP-A received a daily flow of 500,000 m3, consisting of sewage and treated pharmaceutical

re

wastewater from its upstream. Anaerobic-Anoxic-Oxic process was adopted as the biological secondary treatment technic of WWTP-A. The treatment capacity of WWTP-B was 5,000 m3

lP

day-1, receiving oxytetracycline and penicillin production wastewater, as well as machine washing water and sewage within the plant. In WWTP-B, a sequential batch reactor (SBR) and a

ur na

two-stage submerged biological contact reactor using fiber bundle as the biocarrier were used as the biological process. For WWTP-A, PM2.5 and PM10 were collected above the coarse screening unit (A1), aerated grit chamber (A2), and aeration tank (A3), as well as in the sludge dewatering room (A4). For WWTP-B, aerosol samples were collected above the aeration tank

Jo

(B1), secondary settling tank (B2), and sludge dewatering room (B3). Among all these sampling sites, A1-A3 and B1-B2 were located outdoor, while A4 and B3 were located indoor. At each location, 4 medium-flow continuous filtration air particulate samplers (Qingdao Junray Intelligent Instrument Co., China) were set at the altitude of 1.5 m, two of which were equipped with PM2.5 fractionating inlets and the other two with PM10 fractionating inlets. Ambient air

was drawn through 0.45 µm sterile glass fiber filters (diameter 90 mm, Millipore, Billerica, MA, USA) at a rate of 100 mL/min for 44 h (continuous for 23 h, followed by 4 h rest, then another 21 h), for a total of 260 m3 of air. On the same sampling day, the background aerosol samples of urban ambient air were collected on the top of a 2-story building (height from the ground: 6 m) 10 and 12 km away from WWTP-A and WWTP-B. Each filter with captured biomass was stored

of

in a sterile 50-mL falcon tube. Additionally, grab samples of wastewater (500 mL) and sludge samples (100 g wet weight) were collected from the counterparts of the wastewater (A1-A3, B1-

ro

B2) and sludge (A4, B3) treatment facilities. Two samplings were conducted in two seasons, winter (December 11–12, 2014) and spring (March 7–8, 2016), respectively. We obtained a total

-p

of 14 PM2.5 samples, 14 PM10 samples, and 14 wastewater/sludge samples from WWTP-A and

re

WWTP-B, as well as 4 PM samples from the background ambient air. All samples were transferred to the lab on dry ice and stored at 4 °C until further processing within 24 h.

lP

2.2. Sample pretreatment and DNA extraction

The biomass on the glass fiber filter surface was peeled off using a sterile clip and

ur na

collected into 2-mL sterile tubes to avoid negative matrix effects on the DNA extraction efficiency. DNA extracted from the membrane surface represented the aerosol biomass, as no detectable DNA was obtained from the filter (SYBR-Green real-time qPCR, data not shown). Each wastewater sample (100 mL) was centrifuged at 16,000 ×g for 10 min (at 4°C) for biomass

Jo

collection. For sludge samples, 0.25 g concentrated sludge was weighed. Following pretreatment, MoBio Power Soil DNA isolation kit (MoBio Laboratories, Inc., Carlsbad, CA, USA) was applied to extract genomic DNA extraction from all samples. 2.3. Illumina Miseq sequencing and analysis

For Miseq sequencing, the v3-v4 region of the 16S rRNA gene was amplified with the primer set U515F and U909R, with a specific barcode added to each sample (Narihiro et al., 2015). Polymerase chain reaction (PCR) products were purified using a Promega gel purification kit (Madison, WI, USA) after agarose gel electrophoresis. High-throughput sequencing was performed on the Illumina MiSeq Bulk 2 × 300 nucleotide paired-end sequencing system

of

(Illumina) at the Roy J. Carver Biotechnology Center at University of Illinois at UrbanaChampaign (Champaign, IL, USA). Sequencing data were analyzed using Quantitative Insights

ro

Into Microbial Ecology (qiime2-2018.3) software (Caporaso et al., 2010). Sequences with <98.5% similarities were defined as different OTUs (operational taxonomy units).

-p

Representative sequences were picked from each OTU, followed by taxonomy assignment via

re

blasting with the Greengenes 16S rRNA gene bank. Alpha-diversity (Chao index, observed OTUs, Shannon index, and Simpson’s index) was analyzed based on the OTU numbers and

lP

sequence numbers in each sample. Beta-diversity was analyzed by Jackknife supported Principal Coordinate Analysis with weighted UniFrac. Hierarchical cluster analysis was conducted to

ur na

determine community similarity among samples using unweighted pair group method with arithmetic mean (UPGMA) normalization. Representative OTUs were blasted with known 16S rRNA genes to identify their taxonomy affiliation. To confirm the presence of pathogenic bacteria, OTUs assigned as pathogenic genera or species were constructed into an ARB tree with

Jo

16S rRNA genes of known pathogenic bacteria from arb-silva genebank to illustrate their phylogenetic affiliations (Ludwig et al., 2004). Raw Illumina Miseq sequencing reads were deposited into NCBI Submission Portal with accession no. PRJNA526627. 2.4. Fates of bacteria in PMs: aerosolization characteristics and persistence during dispersion

To evaluate the fates of each bacterium, the aerosolization factor (AF) was calculated as the ratio of the relative abundance of each OTU in PM2.5 and PM10 to that in bulk wastewater/sludge (Eq. 1) (Hejkal et al., 1980; Michaud et al., 2018). For bacteria in the indoor sludge dewatering house, aerosolization is continuous and significant while dispersion after aerosolization is limited. Therefore, if AF is higher than 1, the bacterium is easy to aerosolize or

of

air-enriched, i.e., more enriched in aerosol than in bulk wastewater/sludge. In contrast, if AF is less than 1, the bacterium is not easy to aerosolize. For PM from outdoor wastewater treatment

ro

facilities, not only aerosolization, but also dispersion plays important roles in the bacterial

community because of air flow and wind, among other factors. Thus, AF in outdoor aerosols

relative abundance in WWTP aerosol − background aerosol relative abundance in wastewater/sludge

(Eq. 1)

re

Aerosolization factor (AF) =

-p

reflects the persistent survival of bacteria.

3. Results and Discussion

3.1.1. Alpha-diversity

lP

3.1. Overall bacterial compositions of aerosols and wastewater/sludge

ur na

Alpha-diversity indices, including Shannon index (evenness), Chao 1 (richness), observed OTUs (rarefaction curve), and Simpson’s index of diversity (evenness), were calculated for all aerosol PM samples and wastewater/sludge samples (Figure S1). Similar to in a previous study (Han et al., 2018), PM2.5 and PM10 both showed higher Shannon indices (7.7–

Jo

7.8 for indoor PM from wastewater treatment; 7.2–7.3 for outdoor PM from sludge treatment) than wastewater (5.6–6.4, P = 0.0002) and sludge (4.9–7.1, P = 0.02) (Figure S1-A, E). The richness (Chao 1), observed OTUs, and Simpson’s index of diversity (Figure S1-B–D; F–H) showed similar trends. These results indicate that aerosols from WWTPs are important environmental pools of bacteria.

3.1.2. Bacterial compositions at the phylum level Bacterial compositions at the phylum level are shown in Figure S2. Similar to other reports (Ju et al., 2014; Saunders et al., 2015), Proteobacteria, mainly Alpha-, Beta-, and Gamma-Proteobacteria were the most dominant bacteria in wastewater (57.1 ± 15.8%) and sludge (46.1 ± 0.6%) of sewage wastewater treatment plant WWTP-A, followed by

of

Bacteroidetes (26.7 ± 11.5%). Phyla Firmicutes and Chloroflexi also took up 11.2 ± 1.0% and 11.3 ± 9.2% in the sludge. In indoor PM2.5 and PM10 from sludge dewatering of WWTP-A

ro

collected in Mar-2016, Betaproteobacteria were the most dominant (47.9 ± 2.6%) at higher rates than in sludge (9.9%) (P = 0.005), indicating that these bacteria were enriched in aerosols.

-p

Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes were comparable in PM2.5

re

(12.8 ± 14.1%, 10.2 ± 1.8%, 15.6 ± 10.5%), PM10 (9.7 ± 9.5%, 8.2 ± 0.7%, 12.9 ± 9.5%) and sludge (14.6 ± 11.9%, 16.8 ± 9.8%, 11.3 ± 9.2%). Firmicutes, Actinobacteria, and Chloroflexi in

lP

PM2.5 (4.1 ± 4.4%, 1.9 ± 1.0%, 2.7 ± 1.6%) and PM10 (5.3 ± 5.5%, 3.2 ± 2.9%, 5.4 ± 4.7%) were lower than those in sludge (13.5 ± 10.7%, 6.5 ± 1.7%, 11.2 ± 1.0%) (P < 0.05).

ur na

In outdoor aerosol samples from wastewater treatment units (A1–A3), Firmicutes and Actinobacteria were significantly higher (15.9 ± 6.7% to 23.3 ± 4.7%) than those in wastewater samples (2.6% and 1.6%) (P > 0.05), indicating that these bacteria are either more prone to become aerosolized or more robustly survive in the harsh aerosol environment with low

Jo

humidity, low nutrients, and higher UV exposure (Korzeniewska et al., 2011; Nielsen et al., 2015). In addition, Cyanobacteria reached 6.0 ± 3.0–8.8 ± 3.6% in all outdoor PM samples, which were significantly higher than those in wastewater (0.6 ± 0.9%) (P = 0.0004), likely because of the higher sunlight exposure in air.

In the wastewater and sludge samples from WWTP-B, Bacteroidetes were the most dominant (55.9 ± 13.9%, 44.3 ± 9.0%, respectively), followed by Proteobacteria (30.1 ± 10.8% and 43.7 ± 7.7%, mainly Alpha-, Beta-, and Gamma-). The different bacterial communities in WWTP-B from WWTP-A were attributed to the selection force of high antibiotic residual levels in WWTP-B, which is consistent with previous studies (Zhang et al., 2013). Previous studies

of

reported that penicillin G was 0.15 mg/L and 1.67 µg/L in the influent and secondary effluent (Li et al., 2008), while oxytetracycline was 0.96-11.6 and 0.22-1.46 mg/L in the influent and

ro

secondary effluent, respectively (Liu et al., 2012). In PM2.5 and PM10 from outdoor wastewater treatment processes, Actinobacteria (22.1 ± 7.4%, 20.7 ± 8.0%) and Firmicutes (17.6 ± 6.0%,

-p

18.4 ± 4.5%) were the dominant bacteria, higher than those in wastewater (2.1 ± 1.0% and 1.2 ±

re

1.2%) (P < 0.05), followed by Alphaproteobacteria (15.5 ± 3.6%, 15.6 ± 3.5%) and Gammaproteobacteria (17.6 ± 6.0%, 18.4 ± 4.5%). In PM2.5 and PM10 from the indoor sludge

lP

dewatering facility, Bacteroidetes showed the highest abundance (21.1 ± 9.7%, 22.8 ± 10.4%), which was higher than that in background ambient air (11.5 ± 5.3%, 12.2 ± 4.3%, P = 0.01),

ur na

suggesting a significant impact from the sludge.

3.1.3. Bacterial compositions at the deepest available phylogenetic level The detailed bacterial compositions in wastewater and PM samples are shown in Figure 2. The OTUs were assigned to different phylogenetic level, with some OTUs identified to genus

Jo

and even species while others only to higher levels (phylum, class, order, and family). The bacterial compositions will be illustrated on the family level since most of the abundant OTUs were on this level. In the background ambient aerosols, Pseudomonadales (unknown family) and Planococcaceae were the dominant bacteria in December 2014 (2.4–3.8%) and March 2016 (1.8–8.9%). Sphingobacteriales were highly abundant in December 2014 (5.5–6.7%) but showed

a much lower level (<0.1%) in March 2016. Zhen et al. (2017) reported 12 orders including Pseudomonadales and Bacillales as the most abundant bacteria in urban aerosols, which was attributed to the various sources and significantly affected by meteorological factors that led to a seasonal change. In PM samples from wastewater treatment facilities (coarse screening, A1; aerated grit

of

chamber, A2) of WWTP-A (Dec 2014), Pseudomonadales (unknown family) was the most abundant (5.1–7.8%), followed by Planococcaceae (2.5–3.0%), Clostridiaceae (1.7–2.9%), and

ro

Moraxellaceae (2.2–3.1%). In PM samples from the aeration tank (A3), Streptophyta (unknown family) was the most abundant (7.7% and 19.3% in PM2.5 and PM10, respectively), followed by

-p

Pseudomonadales (unknown family) (2.7–3.4%) and Micrococcaceae (Microbispora rosea)

re

(1.0–1.8%). In PM samples from the sludge dewatering unit (A4), Arcobacter (Campylobacteraceae) were the most abundant (21.7–24.2%), followed by

lP

Porphyromonadaceae (3.4–4.6%) and Comamonadaceae (3.9–4.0%). In March 2016, a drastic temporal change was observed, with Campylobacteraceae, Aeromonadaceae, and

ur na

Peptostreptococcaceae as the most abundant in A1–A3 (1.5–5.6%), while Xanthomonadaceae, Rhodocyclaceae, Nitrosomonadaceae, and Methylophilaceae as the most abundant in A4 (2.1– 22.6%). Compared to a previously studied wastewater treatment plant in Beijing, China, Arcobacter and Aeromonadaceae were shared as the dominant bacteria, while most aerosol

Jo

bacteria were not shared in different WWTPs (Yang et al., 2019). Arcobacter and Comamonadaceae were reported as two of the seven dominant bacteria in the sludge dewatering house in Beijing, China (Han et al., 2018). Different bacterial communities from different studies can be attributed to regional disparity, variations in bacterial sources, and meteorological factors.

In PM2.5 and PM10 from the wastewater treatment facilities (aeration tank, B1; secondary settling tank, B2) of WWTP-B, Streptophyta (unknown family), Pseudomonadales (unknown family), and Planococcaceae were the most abundant bacteria, ranging from 1.2% to 9.2%. Sphingobacteriales (unknown family) were also abundant (PM2.5: 3.9%, PM10: 1.8%) in B2 in March 2016. In PM2.5 and PM10 from the sludge dewatering process (B3), Arcobacter

of

(Campylobacteraceae) was the most abundant (7.3% and 7.8%), followed by Pseudomonadales (unknown family) (4.4% and 2.2%) in December 2014, while Salinibacterium

ro

(Microbacteriaceae), Mycobacterium (Mycobacteriaceae), Chitinophagaceae,

Sphingobacteriales (unknown family), Methylobacteriaceae, Comamonadaceae, and uncultured

-p

phylum OP56 showed high abundance (1.6–8.9%) in March 2016.

re

3.2. Comparison of bacterial communities in aerosols and wastewater/sludge The beta-diversity results obtained by (1) Jackknife-supported principal coordinate

lP

analysis with weighted UniFrac (Figure 3) and (2) UPGMA-normalized clustering of samples based on 16S rRNA gene amplicons (Figure S3) were used to understand the relationships

ur na

between bacterial communities from wastewater treatment processes and those in aerosols (PM2.5 and PM10). Although different microbial distributions were reported in finely differentiated particle size factions of PM (<0.55, 0.55–1, 1–1.6, 1.6–3.3, 3.3–7.9, >7.9 µm) from an African dust event using clone libraries of 16S rRNA genes (Polymenakou et al., 2008), this

Jo

study showed that inhalable PM2.5 and PM10 shared similar bacterial communities (P > 0.05). The bacterial communities of PM2.5 and PM10 from indoor sludge dewatering houses (A4_14_PM2.5, A4_14_PM10, A4_16_PM2.5, A4_16_PM10, B3_16_PM2.5, B3_16_PM10) clustered with sludge (A4_14, A4_16, B3_16, respectively) rather than with background aerosol (Figure 2), indicating that the aerosolization of bacteria from sludge governed the indoor aerosol

bacterial community. For outdoor wastewater treatment facilities, the bacterial communities in PM2.5 and PM10 from both WWTP-A and WWTP-B clustered with the urban ambient aerosols rather than with wastewater, suggesting that the more dominant influence of dispersion than aerosolization made the differences between two different WWTPs negligible. Similarly, Yang et al. (2019) found that sludge was the major source of indoor aerosols, whereas ambient air was

of

the major source of outdoor aerosols. Outdoor PM samples from December 2014 and March 2016 were clustered separately into two groups, showing strong temporal changes which can be

ro

attributed to variations in microbial sources and meteorological factors. Zhen et al. (2017) reported a seasonal change in the microbial communities in ambient aerosols, with

-p

meteorological parameters including rain and wind as the most significant impact factors. Based

re

on these results, it is critical to understand the fates of aerosol bacteria from WWTPs based on their configuration parameters (e.g., indoor or outdoor).

lP

3.3. Fates of aerosol bacteria: aerosolization properties and persistence after dispersion AF is the ratio of bacterial abundance in air to that in the corresponding

ur na

wastewater/sludge and was introduced to evaluate the potential of bacteria to become aerosolized in the air (Michaud et al., 2018). Overall, the AFs of bacteria were similar in PM2.5 (X axis) and PM10 (Y axis), suggesting a universal aerosolization distribution in both inhalable PMs. The outdoor meteorological conditions during sampling days were collected from the official website

Jo

of China Meteorological Administration (https://data.cma.cn) (Table S1). There was no precipitation one week before and during the sampling events, therefore the influence of precipitation was negligible. Since we only have the outdoor meteorological parameters, the indoor conditions were compared with previous literatures. Wind speed (2.2–3.0 m/s) in the outdoor air was found higher than that in indoor sludge dewatering house (0.08–0.37 m/s) (Yang

et al., 2019), implying higher dispersion in the outdoor air than that in the indoor air. Solar radiation was also > 100 times higher in the outdoor air than in the indoor air (Yang et al., 2019), indicating higher sterilization strength by solar ultraviolet in the outdoor air. Based on the differences in meteorological factors in indoor and outdoor air environment, the AFs of bacteria in the indoor sludge treatment facilities (Figure 4) were considered to indicate the aerosolization

of

potential of bacteria because of the dominant effects of aerosolization and minimum influences of spatial diffusion. In contrast, AFs in the outdoor wastewater treatment facilities reflected the

ro

survival of aerosol bacteria after being emitted into the air.

-p

In WWTP-A, 15 bacterial OTUs were found to be easy to aerosolize (Figure 4(a), topright quadrant, AF > 1) in the indoor sludge treatment facilities, among which 3 OTUs including

re

Rhodocyclaceae, Arcobacter (Campylobacteraceae), and Comamonadaceae OTU1 remained air-enriched in the outdoor wastewater treatment facilities (AF > 1 in Figure 4(a) and 4(c), red

lP

color) indicating their preferential aerosolization and persistent survival, while the other 12 OTUs (Thauera (Rhodocyclaceae), Rhodocyclaceae, Arcobacter (Campylobacteraceae),

ur na

Comamonadaceae OTU2, Methylophilaceae, Pseudomonadaceae, Acinetobacter (Moraxellaceae), Citrobacter (Enterobacteriaceae), Xanthomonadaceae, Nitrosomonadaceae, Porphyromonadaceae; in blue) showed lower air enrichment in the outdoor aerosols (AF < 1 in

Jo

Figure 4(c)) after dispersion into ambient air), implying preferential aerosolization but low survival during dispersion. In WWTP-B, 8 easy to aerosolize species were found in the indoor sludge treatment facility (Figure 4(b), top-right quadrant, AF > 1), among which Mycobacterium (Mycobacteriaceae) and Citrobacter (Enterobacteriaceae) remained air-enriched in the outdoor wastewater treatment facilities (AF > 1 in Figure 4(b) and 4(d), in red color), while the others (Salinibacterium (Microbacteriaceae), Sphingobacteriales (unknown family), Methylocystaceae,

Caldilineaceae, OPB56 (unknown family), Comamonadaceae; in blue) were water-enriched above the outdoor treatment facility (AF < 1 in Figure 4(d)). Other OTUs (in green) affiliated with Chitinophagaceae and Sphingobacteriales OTU1 (unknown family) were water-enriched in both WWTP-A and WWTP-B, with Xanthomonadaceae OTU2 and Caldilineaceae waterenriched in WWTP-A and Nitrosomonadaceae, Cryomorphaceae, Porphyromonadaceae water-

of

enriched in WWTP-B. The aerosolization potential of bacteria can be affected by their sizes, morphology,

ro

membrane hydrophobicity, and locations (free or in flocs) (Perrott et al., 2017). Among the easy to aerosolize bacteria in this study, many have been reported to preferentially aerosolize in

-p

previous studies. Multiple strains of Mycobacterium, which have a hydrophobic cell membrane

re

(Chao et al., 2014), were found to be preferentially aerosolized from simulated natural water through a drizzle sprayer (Parker et al., 1983) and from bulk water in a hospital therapy pool by

lP

natural emission (Angenent et al., 2005). Although it has a hydrophilic membrane, Acinetobacter was preferentially aerosolized, likely because of an unknown property that it shares with

ur na

Mycobacterium, considering that they are both involved in sludge foaming and surfactant production (Chao et al., 2014; Guo and Zhang 2012). Arcobacter cryaerophilus was enriched in marine aerosol at the Korean East Sea, although it was not detected in the seawater (Cho and Hwang 2011). Increased levels of Citrobacter were found in urban air near a WWTP (Fannin et

Jo

al., 1985) and aeration remediation facility of a polluted airway (Dueker et al., 2018). After aerosolization, the survival of bacteria in the air is related to environmental factors such as the humidity, temperature, wind speed, solar illumination, and air pressure (Wang et al., 2018; Zhen et al., 2017), as well as the intrinsic properties of bacteria such as their membrane structure, spore-forming ability, etc. (Fernandez et al., 2019; Marthi et al., 1990). In this study,

Salinibacterium (hydrophobic membrane) was preferentially aerosolized (AF > 1) in the indoor aerosol from WWTP-B, similar to many other members of the family of Microbacteriaceae (Dueker and O'Mullan 2014). However, its AF decreased in the outdoor aerosols, indicating a compromised survival during dispersion. These results may help to predict the major bacteria emitted when bacterial communities in wastewater treatment processes are known, especially

of

those health-related bacteria, such as pathogenic species of Mycobacterium which was preferentially aerosolized and persistent in survival (Section 3.4). Notably, this work is based on

ro

the real situation of full-scale wastewater treatment plants, where the operational conditions can vary every time. In future studies, aerosolization properties and dispersion behaviors should be

-p

evaluated under controlled conditions to better understand the mechanisms of these processes.

re

3.4. Pathogenic bacteria

Pathogenic bacteria in aerosols, particularly in inhalable PM, are important health risks

lP

responsible for transmissible bacterial infections (Zhai et al., 2018). Human opportunistic pathogenic bacteria were found in PM2.5 and PM10 from WWTP-A and WWTP-B, including

ur na

Pseudomonas stutzeri and unknown species of Bacillus, Clostridium, Mycobacterium, and Legionella (Table S2–S5). Opportunistic pathogenic bacteria that can infect fish and plants were also found, including Flavobacterium columnare, Flavobacterium succinicans, and Pseudomonas viridiflava (Table S2–S5). However, because Miseq sequencing of the 300-bp 16S

Jo

rRNA gene amplicon has limited sensitivity for identifying species and strains, the pathogenic bacteria strains may not have been accurately identified. Therefore, we constructed an ARB phylogenetic tree to illustrate the similarity of these candidate bacteria to reported pathogenic bacteria (Figure 5). The only confirmed pathogenic bacteria were those with >97% similarity to species Staphylococcus sciuri. This bacterium, which is infectious to human and other animals

(Chen et al., 2009; Nemeghaire et al., 2014), was found in control aerosols (3.0 × 10-5–2.1 × 104

) and WWTP aerosols (1.1 × 10-5–5.8 × 10-4) but not in wastewater/sludge samples, suggesting

that they originated from sources other than the studied WWTPs. 4. Conclusions This study identified the bacterial communities in inhalable aerosols emitted from

of

wastewater and sludge treatment processes. Indoor sludge dewatering facilities significantly affected the bacterial communities in aerosols, which was dominated by aerosolization rather

ro

than dispersion (aerosolization > dispersion). In contrast, outdoor aerosols showed higher

similarity to ambient urban aerosols than those from wastewater, indicating that dispersion after

-p

aerosolization was the governing factor for outdoor aerosols (dispersion > aerosolization).

re

Several bacteria including Rhodocyclaceae, Arcobacter, Comamonadaceae, Mycobacterium, and Citrobacter were both preferentially aerosolized and persistently survived in both indoor and

lP

outdoor air, which should be studied further to determine their long-term behavior and possible health risks. Overall, the bacterial community in inhalable aerosols provides direct information

ur na

for future airborne health risk evaluation from WWTPs.

Declaration of interests

Jo

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Acknowledgement

This work was supported by the National Natural Scientific Foundation of China [NSFC51408032, 2015] and the Fundamental Research Funds for the Central Universities [2016JBZ008, 2016]. We sincerely thank the staffs at Shijiazhuang Environmental Monitoring Station, Hebei Province, China for their great help in sample collection events. Dr. Miaomiao

of

Liu would like to thank China Scholarship Council for the partial sponsorship.

Appendices

ro

Appendix figures and tables include: Figure S1. Schematic plot and sampling sites of aerosols and wastewater/sludge in the full-scale municipal wastewater treatment plant (WWTP-

-p

A) and pharmaceutical wastewater treatment plant (WWTP-B); Figure S2. Alpha diversity of the

re

bacterial communities from aerosol and wastewater/sludge samples of WWTP-A and WWTP-B; Figure S3. Doughnut chart of bacterial composition on the phylum level in aerosol and

lP

water/sludge samples from WWTP-A and WWTP-B, with Proteobacteria divided into Alpha-, Beta-, Delta-, Epsilon-, and Gamma-proteobacteria; Figure S4. Phylogenetic tree of OTUs

ur na

potentially related to pathogenic bacteria constructed with ARB and16S rRNA genes from arbsilva genebank; Table S1. Outdoor meteorological conditions during the sampling time. Table S2. The relative abundances of candidate pathogenic bacteria in aerosols (PM2.5 and PM10) and wastewater/sludge from WWTP-A, collected on Dec-2014; Table S3. The relative abundances of

Jo

candidate pathogenic bacteria in aerosols (PM2.5 and PM10) and wastewater/sludge from WWTP-A, collected on Mar-2016; Table S4. The relative abundances of candidate pathogenic bacteria in aerosols (PM2.5 and PM10) and wastewater/sludge from WWTP-B, collected on Dec-2014; Table S5. The relative abundances of candidate pathogenic bacteria in aerosols (PM2.5 and PM10) and wastewater/sludge from WWTP-B, collected on Mar-2016.

of

ro

-p

re

lP

ur na

Jo

References Angenent, L.T., Kelley, S.T., Amand, A.S., Pace, N.R. Hernandez, M.T., 2005. Molecular identification of potential pathogens in water and air of a hospital therapy pool. Proc. Natl. Acad. Sci. 102(13), 4860-4865.

of

Brandi, G., Sisti, M., Amagliani, G., 2000. Evaluation of the environmental impact of microbial aerosols generated by wastewater treatment plants utilizing different aeration systems. J.

ro

Appl. Microbiol. 88(5), 845-852.

Brook, R.D., Franklin, B., Cascio, W., Hong, Y., Howard, G., Lipsett, M., Luepker, R.,

-p

Mittleman, M., Samet, J., Smith, S.C., 2004. Air pollution and cardiovascular disease A

re

statement for healthcare professionals from the expert panel on population and prevention science of the American Heart Association. Circulation. 109(21), 2655-2671.

lP

Cao, C., Jiang, W., Wang, B., Fang, J., Lang, J., Tian, G., Jiang, J., Zhu, T.F., 2014. Inhalable microorganisms in Beijing’s PM2. 5 and PM10 pollutants during a severe smog event.

ur na

Environ. Sci. Technol. 48(3), 1499-1507.

Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Fierer, N., Pena, A.G., Goodrich, J.K., Gordon, J.I., 2010. QIIME allows analysis of highthroughput community sequencing data. Nat. Methods. 7(5), 335-336.

Jo

Chao, Y., Guo, F., Fang, H.H., Zhang, T., 2014. Hydrophobicity of diverse bacterial populations in activated sludge and biofilm revealed by microbial adhesion to hydrocarbons assay and high-throughput sequencing. Colloids Surface. B. 114, 379-385.

Chen, P.S., Lin, C.K., Tsai, F.T., Yang, C.Y., Lee, C.H., Liao, Y.S., Yeh, C.Y., King, C.C., Wu, J.L., Wang, Y.C., 2009. Quantification of airborne influenza and avian influenza virus in a wet poultry market using a filter/real-time qPCR method. Aerosol Sci. Tech. 43(4), 290-297. Cho, B.C., Hwang, C.Y., 2011. Prokaryotic abundance and 16S rRNA gene sequences detected in marine aerosols on the East Sea (Korea). FEMS Microbiol. Ecol. 76(2), 327-341.

of

Dueker, M.E., French, S., O’Mullan, G.D., 2018. Comparison of Bacterial Diversity in Air and Water of a Major Urban Center. Front. Microbiol. 9, 2868.

ro

Dueker, M.E., O'Mullan, G.D., 2014. Aeration remediation of a polluted waterway increases near-surface coarse and culturable microbial aerosols. Sci. Total Environ. 478, 184-189.

-p

Fannin, K.F., Vana, S.C., Jakubowski, W., 1985. Effect of an activated sludge wastewater

Environ. Microbiol. 49(5), 1191-1196.

re

treatment plant on ambient air densities of aerosols containing bacteria and viruses. Appl.

lP

Fernandez, M.O., Thomas, R.J., Garton, N.J., Hudson, A., Haddrell, A., Reid, J.P., 2019. Assessing the airborne survival of bacteria in populations of aerosol droplets with a novel

ur na

technology. J. Royal Society Interface 16(150), 20180779. Ghosh, B., Lal, H., Srivastava, A., 2015. Review of bioaerosols in indoor environment with special reference to sampling, analysis and control mechanisms. Environ. Int. 85, 254-272. Guo, F., Zhang, T., 2012. Profiling bulking and foaming bacteria in activated sludge by high

Jo

throughput sequencing. Water Res. 46(8), 2772-2782.

Han, Y., Li, L. Liu, J.X., 2013. Characterization of the airborne bacterial community at different distances from the rotating brushes in a wastewater treatment plant by 16S rRNA gene clone libraries. J. Environ. Sci. 25(1), 5-15.

Han, Y., Wang, Y., Li, L., Xu, G., Liu, J., Yang, K., 2018. Bacterial population and chemicals in bioaerosols from indoor environment: Sludge dewatering houses in nine municipal wastewater treatment plants. Sci. Total Environ. 618, 469-478. Hejkal, T.W., Larock, P.A., W, W.J., 1980. Water-to-Air Fractionation of Bacteria. Appl. Environ. Microbiol. 39(2), 335-338.

of

https://data.cma.cn; the official website of China Meteorological Administration. Ju, F., Guo, F., Ye, L., Xia, Y., Zhang, T., 2014. Metagenomic analysis on seasonal microbial

ro

variations of activated sludge from a full‐scale wastewater treatment plant over 4 years. Environ. Microbiol. Rep. 6(1), 80-89.

-p

Katsivela, E., Latos, E., Raisi, L., Aleksandropoulou, V., Lazaridis, M., 2017. Particle size

re

distribution of cultivable airborne microbes and inhalable particulate matter in a wastewater treatment plant facility. Aerobiologia. 33: 297-314.

lP

Korzeniewska, E., 2011. Emission of bacteria and fungi in the air from wastewater treatment plants–a review. Front Biosci. 3, 393-407.

ur na

Li, D., Yang, M., Hu, J., Zhang, Y., Chang, H., Jin, F., 2008. Determination of penicillin G and its degradation products in a penicillin production wastewater treatment plant and the receiving river. Water Res. 42: 307-317. Liu, M., Zhang, Y., Yang, M., Tian, Z., Ren, L., Zhang, S., 2012. Abundance and distribution of

Jo

tetracycline resistance genes and mobile elements in an oxytetracycline production wastewater treatment system. Environ. Sci. Technol. 46: 7551-7557.

Ludwig, W., Strunk, O., Westram, R., Richter, L., Meier, H., Yadhukumar, Buchner, A., Lai, T., Steppi, S., Jobb, G., 2004. ARB: a software environment for sequence data. Nucleic Acids Res. 32(4), 1363-1371.

Marthi, B., Fieland, V., Walter, M., Seidler, R.J., 1990. Survival of bacteria during aerosolization. Appl. Environ. Microbiol. 56(11), 3463-3467. Michaud, J.M., Thompson, L.R., Kaul, D., Espinoza, J.L., Richter, R.A., Xu, Z.Z., Lee, C., Pham, K.M., Beall, C.M., Malfatti, F., 2018. Taxon-specific aerosolization of bacteria and viruses in an experimental ocean-atmosphere mesocosm. Nat. Commun. 9(1), 2017.

of

Narihiro, T., Nobu, M.K., Kim, N.K., Kamagata, Y., Liu, W.T., 2015. The nexus of syntrophy‐ associated microbiota in anaerobic digestion revealed by long‐term enrichment and

ro

community survey. Environ. Microbiol. 17(5), 1707-1720.

Nemeghaire, S., Argudín, M.A., Feßler, A.T., Hauschild, T., Schwarz, S., Butaye, P., 2014. The

-p

ecological importance of the Staphylococcus sciuri species group as a reservoir for resistance

re

and virulence genes. Vet. Microbiol. 171(3), 342-356.

Nielsen, H.L., 2015. First report of Actinomyces europaeus bacteraemia result from a breast

lP

abscess in a 53-year-old man. New Microbes New Infect. 7, 21-22. Parker, B.C., Ford, M.A., Gruft, H., Falkinham III, J.O., 1983. Epidemiology of infection by

ur na

nontuberculous mycobacteria: IV. Preferential aerosolization of Mycobacterium intracellulare from natural waters. Am. Rev. Respir. Dis. 128(4), 652-656. Pascual, L., Pérez-Luz, S., Yáñez, M.A., Santamaría, A., Gibert, K., Salgot, M., Apraiz, D., Catalán, V., 2003. Bioaerosol emission from wastewater treatment plants. Aerobiologia.

Jo

19(3-4), 261-270.

Perrott, P., Turgeon, N., Gauthier‐Levesque, L., Duchaine, C., 2017. Preferential aerosolization of bacteria in bioaerosols generated in vitro. J. Appl. Microbiol. 123(3), 688-697.

Polymenakou, P.N., Mandalakis, M., Stephanou, E.G., Tselepides, A., 2008. Particle size distribution of airborne microorganisms and pathogens during an intense African dust event in the eastern Mediterranean. Environ. Health. Perspect. 116(3), 292. Saunders A M , Albertsen M, Vollertsen J, H, N.P., 2015. The activated sludge ecosystem contains a core community of abundant organisms. ISME J. 10(1), 11–20.

of

Smets, W., Moretti, S., Denys, S., Lebeer, S., 2016. Airborne bacteria in the atmosphere: Presence, purpose, and potential. Atmospheric Environ. 139, 214-221.

ro

Wang, Y., Li, L., Han, Y.P., Liu, J.X., Yang, K.X., 2018. Intestinal bacteria in bioaerosols and factors affecting their survival in two oxidation ditch process municipal wastewater treatment

-p

plants located in different regions. Ecotoxic. Environ. Safety 154, 162-170.

re

Xu, G., Han, Y., Li, L., Liu, J.X., 2018. Characterization and source analysis of indoor/outdoor culturable airborne bacteria in a municipal wastewater treatment plant. J. Environ. Sci. 74,

lP

71-78.

Yang, K.X., Li, L., Wang, Y., Xue, S., Han, Y.P., Liu, J.X., 2019. Airborne bacteria in a

ur na

wastewater treatment plant: Emission characterization, source analysis and health risk assessment. Water Res. 149, 596-606. Zhai, Y., Li, X., Wang, T., Wang, B., Li, C., Zeng, G., 2018. A review on airborne microorganisms in particulate matters: composition, characteristics and influence factors.

Jo

Environ. Int. 113, 74-90.

Zhang, L.L., Jin, X.W., Johnson, A.C., Giesy, J.P., 2016. Hazard posed by metals and As in PM2. 5 in air of five megacities in the Beijing-Tianjin-Hebei region of China during APEC. Environ. Sci. Pollut. Res. 23:17603–17612

Zhang, Y., Xie, J.P., Liu, M.M., Tian, Z., He, Z., van Nostrand, J.D., Ren, L., Zhou, J., Yang, M., 2013. Microbial community functional structure in response to antibiotics in pharmaceutical wastewater treatment systems. Water Res. 47(16), 6298-6308. Zhen, Q., Deng, Y., Wang, Y., Wang, X., Zhang, H., Sun, X., Ouyang, Z.Y., 2017. Meteorological factors had more impact on airborne bacterial communities than air

of

pollutants. Sci. Total Environ. 601, 703-712. Zheng, G., Duan, F., Su, H., Ma, Y., Cheng, Y., Zheng, B., Zhang, Q., Huang, T., Kimoto, T.

ro

Chang, D., 2015. Exploring the severe winter haze in Beijing: the impact of synoptic

weather, regional transport and heterogeneous reactions. Atmos. Chem. Phys. 15(6), 2969-

Jo

ur na

lP

re

-p

2983.

of ro -p re lP

ur na

Figure 1. Schematic plot and sampling sites of aerosols and wastewater/sludge in the full-scale municipal wastewater treatment plant (WWTP-A) and pharmaceutical wastewater treatment plant

Jo

(WWTP-B).

of ro -p re lP ur na Jo Figure 2. Heatmap of microbial compositions in aerosols and wastewater/sludge. The abundance of each OTU in the background aerosol was subtracted from all aerosol samples. Only OTUs with average relative abundance higher than 0.2% in aerosols or higher than 0.4% in wastewater/sludge are shown.

of ro -p re lP ur na

Figure 3. Jackknife supported Principal Coordinate Analysis with weighted UniFrac for the

Jo

bacterial communities in all of the aerosols and wastewater/sludge samples. Each solid circle is one sample. The circles with black edges are PM10. The circles with grey edges are sludge samples (A4, B3).

of ro -p re lP ur na

Figure 4. Aerosolization factors (AF) of major bacteria in PM2.5 and PM10 from indoor and

Jo

outdoor wastewater /sludge treatment facilities of WWTP-A (a, c) and WWTP-B (b, d).

of ro -p re lP ur na Jo

Figure 5. Phylogenetic tree of OTUs potentially related to pathogenic bacteria constructed with ARB and16S rRNA genes from arb-silva database. Bootstrap values are indicated at each branch on 1000 bootstraps. Acidobacteria bacterium Ellin7246 (GenBank Accession NO. AY67341) isolated from soil was used as the outgroup.

of

ro

-p

re

lP

ur na

Jo