A Preliminary Study of Response Patterns and Environmental Drivers of Coastal Airborne Microbial Communities During an Ulva prolifera Green Tide

Coastal green tides may alter nearshore bioaerosols through coupled marine, atmospheric, and meteorological processes, yet their effects on airborne microbial communities remain poorly resolved. Atmospheric samples were collected in Aoshan Bay, Qingdao, China, during five phases of the Ulva prolifera green tide in 2019 (pre-bloom, 19 April; early bloom, 15 June; middle bloom, 15 July; late bloom, 6 August; post-bloom, 30 August); seawater samples were collected at one nearshore site on each of the five sampling dates, with microbial sequencing performed for the middle-bloom (15 July) and late-bloom (6 August) phases. Bacterial and fungal communities were characterized; although bioaerosols may also contain microalgae and viruses, this study profiled only the bacterial and fungal fractions, using bacterial 16S rRNA gene (V3-V4 region) and fungal internal transcribed spacer (ITS2) amplicon sequencing and evaluated together with meteorological variables, air-pollutant concentrations, and 72-h backward air-mass trajectories. Proteobacteria dominated the airborne bacterial assemblages (81.28–97.83%), with Sphingomonas as the most abundant genus (47.85–89.84%). Basidiomycota and Ascomycota dominated the fungal assemblages, whereas Cryptococcus and Alternaria were the major fungal genera. Community richness and composition varied across bloom phases. Chytridiomycota was undetected before the bloom (0%), appeared after bloom onset, and reached its highest relative abundance during the middle phase (8.19%). Spatial patterns indicated joint terrestrial and marine influences, although bacterial communities in seawater and air remained highly dissimilar. Temperature, relative humidity, particulate matter, ozone, and air-mass origin were associated with changes in microbial diversity and composition. These findings provide an observational baseline for coastal bioaerosol dynamics during a macroalgal green tide, extending the HAB–bioaerosol literature—which has focused predominantly on cyanobacterial blooms—to a large green macroalga. Bacteria and fungi showed contrasting environmental responses: bacterial richness increased with temperature, whereas fungal diversity declined. Greater compositional similarity between seawater and air for fungi than for bacteria suggests differential environmental filtering at the air–sea interface and implies that multiple source pathways—direct aerosolization, sea-surface release, and in-situ atmospheric production—may differentially shape the two domains. Given the single-date-per-phase sampling design, the absence of sequenced laboratory contamination controls, and the lack of absolute abundance data, these results should be regarded as preliminary and hypothesis-generating, underscoring the need for ASV-level source tracking, controlled chamber experiments, and replicated multi-year designs in future assessments of bloom–atmosphere interactions.

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Publication Details

Journal
Atmosphere
Published
2026-08-24
DOI
https://doi.org/10.3390/atmos17090818
Primary Topic
Indoor Air Quality and Microbial Exposure
Type
article
Field-Weighted Citation Impact
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article

A Preliminary Study of Response Patterns and Environmental Drivers of Coastal Airborne Microbial Communities During an Ulva prolifera Green Tide

Xuedong Zhou, Xiaosong Wang, Fenghua Wei, Bin Wang et al.
Atmosphere
Indoor Air Quality and Microbial Exposure
article

A Preliminary Study of Response Patterns and Environmental Drivers of Coastal Airborne Microbial Communities During an Ulva prolifera Green Tide

Xuedong Zhou, Xiaosong Wang, Fenghua Wei, Bin Wang, Yan Wu
article en

Abstract

Coastal green tides may alter nearshore bioaerosols through coupled marine, atmospheric, and meteorological processes, yet their effects on airborne microbial communities remain poorly resolved. Atmospheric samples were collected in Aoshan Bay, Qingdao, China, during five phases of the Ulva prolifera green tide in 2019 (pre-bloom, 19 April; early bloom, 15 June; middle bloom, 15 July; late bloom, 6 August; post-bloom, 30 August); seawater samples were collected at one nearshore site on each of the five sampling dates, with microbial sequencing performed for the middle-bloom (15 July) and late-bloom (6 August) phases. Bacterial and fungal communities were characterized; although bioaerosols may also contain microalgae and viruses, this study profiled only the bacterial and fungal fractions, using bacterial 16S rRNA gene (V3-V4 region) and fungal internal transcribed spacer (ITS2) amplicon sequencing and evaluated together with meteorological variables, air-pollutant concentrations, and 72-h backward air-mass trajectories. Proteobacteria dominated the airborne bacterial assemblages (81.28–97.83%), with Sphingomonas as the most abundant genus (47.85–89.84%). Basidiomycota and Ascomycota dominated the fungal assemblages, whereas Cryptococcus and Alternaria were the major fungal genera. Community richness and composition varied across bloom phases. Chytridiomycota was undetected before the bloom (0%), appeared after bloom onset, and reached its highest relative abundance during the middle phase (8.19%). Spatial patterns indicated joint terrestrial and marine influences, although bacterial communities in seawater and air remained highly dissimilar. Temperature, relative humidity, particulate matter, ozone, and air-mass origin were associated with changes in microbial diversity and composition. These findings provide an observational baseline for coastal bioaerosol dynamics during a macroalgal green tide, extending the HAB–bioaerosol literature—which has focused predominantly on cyanobacterial blooms—to a large green macroalga. Bacteria and fungi showed contrasting environmental responses: bacterial richness increased with temperature, whereas fungal diversity declined. Greater compositional similarity between seawater and air for fungi than for bacteria suggests differential environmental filtering at the air–sea interface and implies that multiple source pathways—direct aerosolization, sea-surface release, and in-situ atmospheric production—may differentially shape the two domains. Given the single-date-per-phase sampling design, the absence of sequenced laboratory contamination controls, and the lack of absolute abundance data, these results should be regarded as preliminary and hypothesis-generating, underscoring the need for ASV-level source tracking, controlled chamber experiments, and replicated multi-year designs in future assessments of bloom–atmosphere interactions.

AtmosphereVol. 17(9)
Shandong University (CN)
Life below water
Openalex Percentile: Top 11%
Indoor Air Quality and Microbial Exposure
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