*Article* **Mixed-Unit-Model-Based and Quantitative Studies on Groundwater Recharging and Discharging between Aquifers of Aksu River**

**Jiyu Huang, Yanyan Ge \* and Sheng Li**

The Key Laboratory of Geodynamic Processes and Metallogenic Prognosis of the Central Asian Orogenic Belt College of Geology and Exploration Engineering, Xinjiang University, Urumchi 830017, China<EMAIL_ADDRESS>(J.H<EMAIL_ADDRESS>(S.L.)

**\*** Correspondence<EMAIL_ADDRESS>
**Abstract:** The confined aquifer in the Aksu River Basin is the main aquifer for drinking water within the area. In this study, the unconfined aquifer and the confined aquifer in the Aksu River Basin were divided into different water circulation units through analysis of their flow field. After the hydrochemistry and isotope characteristics of each unit were analyzed, these data were used as water volume quantitative information of the aquifer according to the mixed-unit model. With this quantitative information, the transformation relationship between the unconfined aquifer and the confined aquifer, the recharging source, recharging amount, recharging proportion, and discharging amount of the confined aquifer were revealed. The results showed that the confined aquifer receives a recharge of 21.48 × 106 m3/a from the unconfined aquifer. The recharging sources of the confined aquifer in the middle and upper stream of the Aksu River mainly included side recharging and leakage recharging from the unconfined aquifer, while the confined aquifer received little recharging from unconfined aquifer downstream of the Aksu River and did not receive recharging from the unconfined aquifer in the southeast of the basin. Additionally, drainage methods of the confined aquifer were mainly lateral flowing and artificial well-group pumping. The side discharging volume through the whole area was 15.67 × 106 m3/a, and the artificial pumping volume was 21.20 × 106 m3/a. The confined aquifer was in a negative balance state from the middle-upper stream to the downstream. The downstream confined aquifer and its unconfined aquifer had a plane laminar flow movement, and the unconfined aquifer provided very little recharging to the confined one, which was further enhanced by the artificial well pumping and caused an accumulating negative balance state of the downstream aquifer.

**Keywords:** confined aquifer; unconfined aquifer; transformation; mixed-unit method; Aksu River Basin

### **1. Introduction**

#### *1.1. Research Status*

As the source of life, water is inseparable from human survival and development. Although there are many water resources, groundwater with stable volume and excellent quality has become an important water resource for agriculture, animal husbandry, industry, and cities. As an indispensable resource for human society, in arid and semi-arid areas with limited precipitation and a small, unevenly distributed surface water resource, the effect of recharging and drainage of groundwater is significant [1,2] and has attracted the attention of many scientists in different fields.

Therefore, in the early 1950s, the United Nations Educational, Scientific and Cultural Organization (UNESCO) began to study the groundwater cycle [3], and the International Association of Hydrogeologists (IAH) also actively carried out many large-scale academic projects on groundwater circulation [4,5]. In China, water resource is the largest and most rigid constraint for production and life throughout the arid area in the northwest. Today,

**Citation:** Huang, J.; Ge, Y.; Li, S. Mixed-Unit-Model-Based and Quantitative Studies on Groundwater Recharging and Discharging between Aquifers of Aksu River. *Sustainability* **2022**, *14*, 6936. https://doi.org/ 10.3390/su14116936

Academic Editors: Alban Kuriqi and Luis Garrote

Received: 7 May 2022 Accepted: 1 June 2022 Published: 6 June 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

when we vigorously promote the construction of ecological civilization, we need to insist on using water to plan cities, land, populations, and production. Therefore, the efficient and reasonable development, and sustainable utilization, of groundwater resources are particularly important.

Many methods, such as hydrodynamic methods [6,7], hydrochemical methods [8–10], and environmental isotope methods [11,12] have been reported for studying the relationship between groundwater recharging and discharging.

The hydrodynamic method is based on groundwater chemical dynamics theories, according to the calculation and analysis of hydrochemical indicators (component activity and the mineral saturation index) and limited pumping-test data, five hydrogeological parameters (the permeability coefficient, K; the water conductivity coefficient, T; the actual velocity of groundwater, U; its penetration velocity, v; and the groundwater age, t) and can be used to quantitatively analyze and study all hydrogeological conditions [13,14]. The chemical composition of groundwater is usually controlled by many factors, such as the composition of precipitation, the geological structure, the mineral composition, and the hydrogeological processes of the aquifer. The continuous interaction between groundwater and its surrounding media also changes its chemical composition. Therefore, according to the relative concentration of the main ions in precipitation, surface water, and groundwater from different aquifers, information on the geochemical process in aquifers can be obtained to analyze the law and control mechanism of groundwater evolution, as well as the possible groundwater-evolution path from the recharging area to the discharging area [15–17]. Recently, isotope technology, as a new type of technology, has been developed in hydrogeology to effectively trace the change in water bodies and environment very sensitively, and thus, to record historical information about the evolution of the water cycle [18–20]. Since the 1950s, synthetic isotopes and environmental isotopes have been used to study issues related to hydrology and hydrogeology [21–24]. Many scientists worldwide have used these isotope methods to solve problems related to groundwater recharging resources, surface water transformation, surface-water runoff rate, and the age of surface water. Some scientists have further applied water-chemistry information to groundwater numerical models, used isotopes to trace and determine the recharging resource of groundwater, and calculated the amount of groundwater recharging [25–27]. In the 1990s, quantitative mathematical models became very mature. As one of these mature mathematical models, the mixed-unit model, with water-chemistry data and isotope data, can be used to quantitatively calculate the recharging rate and recharging amount of an aquifer in a specific space [28–31]. These results will be used in studies on groundwater cycles to provide a reliable basis for the rational development and utilization of groundwater resources in the arid area of Northwest China with limited hydrogeological work and low precision.

#### *1.2. Purpose of the Research*

The Aksu River Basin has four independent rivers from west to east: Aksu River, Kekeya River, Tailan River, and Karayuergun River. The Aksu River is one of the typical large rivers in the northern margin of the Tarim Basin with two major tributaries in its upper stream: the tributary of the Toshigan River on the west and the tributary of the Kumara River on the north. The Toshigan River originates from the Aksai River in the Atbash Mountains of Kyrgyzstan, the Kumarak River comes from the Khan Tengri Peak of the Tianshan Mountains, and both of them recharge rivers with water from snow-melting of glaciers and from precipitation. Twelve km to the south, the Aksu River divides into the Xinda River and the Laoda River. The Laoda River merges into the Xinda River again in Bawutulak, flows south, and enters the Tarim River in Xiaojiake. Its main stream is 132 km long and its drainage area is 63,100 km2. The Kekya River originates from the Kochikal Basili Glacier and the Ishtarji Glacier. It goes through the Duolang Canal and merges into the Xinda River in Georgia, and has a total length of 82 km. Both the Tailan River and the Karayuergun River originate from the southern foot of Tuomuer Peak in the South Tianshan Mountains and are independent water systems.

As the Aksu River Basin is located at the southern foot of the Tianshan Mountains and has a dry climate with limited rainfall, the population and agricultural production are currently mainly concentrated in its oasis zone with the confined aquifer as an important water source. Many scientists have studied and provided information on the transformation relationship between river and groundwater (mostly unconfined aquifers). However, the recharging and discharging relationships, and the circulation mode of the confined aquifer are not currently understood.

In this study, based on data from the unconfined aquifer and confined aquifer flow fields in the basin, samples of river water, the unconfined aquifer, and the confined aquifer were systematically collected. After their water chemistry and isotope distribution characteristics were analyzed, the mixed-unit method was used to quantify these data, and thus, to reveal the recharging source and circulation mode of the confined aquifer.


**1. Introduction**

Test procedures are published by the World Health Organization (WHO) on the use of the WHO insecticide susceptibility bioassay (or WHO tube bioassay) to monitor the resistance in adult mosquitoes to a range of insecticides commonly used for mosquito control [1]. Resistance monitoring using this approach relies on the collection of wild female adult mosquitoes or wild larvae, which are then reared to adulthood in a test facility. They are then exposed to a discriminating concentration (DC) of insecticide on a treated filter paper so that their knockdown and mortality can be scored.

The WHO tube bioassay is a simple direct response-to-exposure test. The test kit was developed in 1958 to test for the emergence of resistance to organochlorine and organophosphate insecticides following widespread resistance to organochlorine insecticides [2]. It was designed to expose a defined number of adult mosquitoes of known ages and physiological statuses to an insecticide impregnated on a filter paper for a standard exposure time (1 h).

While the WHO test procedures provide parameters for some key environmental conditions which should be kept constant while carrying out the bioassay, during insecticide resistance monitoring there are multiple potential sources of (non-resistance-associated) variability, which can influence the result of the bioassay. During a recently concluded formal WHO multicenter study to establish species-specific discriminating concentrations and procedures for new and existing insecticides, WHO tube and WHO bottle assays (an adaptation of the Centre for Disease Control (CDC) bottle bioassay developed to align end points with those of the WHO tube test) were used to generate concentration response data in multiple testing centers for a range of insecticides and multiple *Anopheles* and *Aedes* species, so that DCs could be established and validated. Within this extensive dataset, a substantial degree of variation was seen both within and between centers performing replicate assays using the same standardized methodologies [3].

One of the sources of variability in data generated when using the WHO tube bioassay methodology is the mosquitoes being tested. When using the method in the field to screen for resistance in the target population of an intervention, wild-caught adult mosquitoes should be used so that any differences in susceptibility may more closely reflect the changes in intrinsic resistance level seen for a particular intervention, and the sampled populations will be representative samples of the wild vector population in terms of age distribution and genetic variability. However, the age distribution, blood feeding status, nutritional status, and gravidity will vary between samples and potentially reduce the comparability of the results between tests and between sites. This differs from the mosquito populations that DCs are established on. Moreover, while operators using this methodology should ensure that they follow the guidance for the selection of mosquitoes for testing, it is still possible to accidentally include mosquitoes that fall outside these parameters (e.g., older than 2–5 days, males, partially blood-fed) when testing with wild-caught mosquitoes. Instead of wild-caught mosquitoes, F1 progeny of wild-caught mosquitoes can be used; although this requires facilities to rear and test the mosquitoes, there is greater control over the rearing conditions than for wild-caught mosquitoes.

Larval rearing conditions in laboratories have been shown to have an impact on bioassay results. Overcrowding or poor diet reduce insecticide tolerance by reducing size and fitness, for example [4,5]. Any impact on longevity because of larval rearing conditions could impact the outcome on mosquito survival. Poor mosquito survival could lead to high control mortality and more discarded tests (control mortality > 20%); this will affect the feasibility of testing. Larval rearing may also be more important for insecticides such as chlorfenapyr, where the effect of the compound is impacted by metabolism, though the correlation between longevity and size is not always positive [6]. In contrast, when the WHO tube bioassay is employed for research, a well-characterized (and ideally susceptible, so that resistance levels do not have to be maintained) laboratory strain can be used alongside the mosquito strain of interest. The benefit of this is that the researcher knows the rearing conditions of their laboratory strain and the resistance status and background

of the strain, while this is not the case for field-caught mosquitoes, this well-characterized susceptible reference strain can be tested alongside as a comparator.

The effect of time-of-day of testing on bioassay results is not well-explored in the literature, but *Anopheles* typically bite at night when they may be more metabolically active, and so susceptibility testing may yield differential results if conducted during the day than during the night. Most testing is carried out during the day, so this is unlikely to be a significant source of variability of the data currently being generated using the WHO tube bioassay method. It is good practice, however, to conduct resistance-monitoring assays at the same time of day each time and report the testing time alongside the data to aid interpretation, as it has been shown that time of day can impact metabolic detoxification and insecticide resistance in *Anopheles gambiae* [7]. Chlorfenapyr (while not validated for use in the WHO tube bioassay) is also strongly affected by a temperature of <25 ◦C [3].

Mosquito age has been shown to affect insecticide resistance, with mosquitoes older than 10 days post-emergence showing increased susceptibility to insecticides [8]. As well as age of mosquito, the nutritional status of adults can also affect the response to insecticide exposure. Machani et al. showed that the ingestion of a blood meal increased insecticide susceptibility [9]. Further to this, it has also been shown that lowering the temperature during insecticide susceptibility testing below the recommended 27 ± 2 ◦C can strongly affect insecticide tolerance [10]. As part of a study conducted in a Ugandan field insectary, which lacked environmental controls but where temperature and humidity were monitored, a strong and highly statistically significant decline in *A. gambiae* mortality was detected as humidity increased [11]. In light of this, it is important to be as consistent as possible when performing susceptibility bioassays and, where it is not possible to control the conditions fully, at least to understand the effect external factors can have on the outputs from this testing and report the environmental conditions alongside the data so that the results can be interpreted accordingly.

The WHO test procedures for monitoring Insecticide susceptibility have been reviewed and updated multiple times since their original publication in 1958, and some methodological details have changed between versions. We therefore set out to review the current literature to identify which test procedures are being referenced when using this method, what data and methodological detail is being reported when this method is used, and where data gaps lie for this methodology. We aimed to achieve this by looking for parameters in the test procedures which leave room for interpretation and using a literature search to explore how these parameters can influence the results of the bioassay. Parameters which were not clearly defined or supported with evidence and where evidence is not already available in the literature were chosen to be explored experimentally. In doing this, we hope to suggest additional guidance on the optimum method for performing the WHO tube bioassay, as well as the key information required for the reporting of insecticide resistance data, thus producing more robust data and reporting it in a way that supports more meaningful interpretations.

#### **2. Materials and Methods**

#### *2.1. Test Procedures Review*

Thirteen WHO documents containing details outlining how to perform the WHO tube bioassay or the rationale behind the bioassay parameters, both published test procedures and meeting reports were reviewed to extract specific methodological details outlined in the test procedures. For each of these documents, the specifics and justifications for the methodological details outlined below were noted for each document and then compared.


*Edited by Theo van de Ven and Louis Godbout*

This book on cellulose, the second in a series of three, deals with the many applications of cellulose, both established ones and those that are emerging. It shows the richness in the way cellulose can be modified to serve a large variety of functions, varying from medical, pharmaceutical and bioelectronics applications. We hope that with these examples the imagination of the reader is stimulated and may him- or herself attempt to find new, fascinating applications of cellulose.

ISBN 978-953-51-1191-7

Cellulose - Medical, Pharmaceutical and Electronic Applications

Photo by micro\_photo / iStock


**Tympanostomy Tube Placement for Otitis Media with Effusion in Children with Cleft Lip and Palate Tympanostomy Tube Placement for Otitis Media with Effusion in Children with Cleft Lip and Palate**

Chin‐Lung Kuo and An‐Suey Shiao Chin‐Lung Kuo and An‐Suey Shiao Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/67122

#### **Abstract**

The condition of cleft lip/palate (CLP) in children is psychologically stressful for family members and debilitating for the patients themselves. These children must undergo a series of major invasive surgeries following birth, including cleft lip repair surgery, cleft palate repair surgery, bone grafting surgery, and dental implant surgery. Unfortunately, the clinical significance of otitis media with effusion (OME), a complication associated with CLP, is often overlooked, and very few studies have explored this condition in depth. This chapter reviews pathogenesis, clinical manifestations, consequences, exami‐ nation, and diagnosis related to OME in children with CLP. Controversies surrounding the treatment of OME in CLP children are also discussed. We also provide a flowchart for management guidance in OME in children with CLP.

**Keywords:** otitis media, middle ear effusion, cleft lip and palate, conductive hearing loss, grommet tube, children


**Author details**

Ulrike Cihak-Bayr1 \*, Robin Jisa2 and Friedrich Franek1

\*Address all correspondence to<EMAIL_ADDRESS>
© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**255**

*Wear Protective Effects of Tribolayer Formation for Copper Based Alloys in Sliding Contacts…*

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[10] Equey S, Houriet A, Mischler S. Wear and frictional mechanisms of copper-based bearing alloys. Wear 2011;273:9-16. DOI: 10.1016/j.

[11] Perret J, Boehm-Courjault E, Cantoni M, Mischler S, Beaudouin A, Chitty W, et al. EBSD, SEM and FIB characterisation of subsurface deformation during tribocorrosion of stainless steel in sulphuric acid. Wear 2010;269:383-93. DOI: 10.1016/j.

[12] Mola J. Considerations in the Design of Formable Austenitic Stainless Steels Based on Deformation-Induced Processes. Austenitic Stainl. Steels - New Asp., InTech; 2017. DOI: 10.5772/

[13] Zhao C, Zhou J, Mei Q, Ren F. Microstructure and dry sliding wear behavior of ultrafine-grained Co-30 at% Cr alloy at room and elevated temperatures. J Alloys Compd 2019;770:276-84. DOI: 10.1016/j.

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*DOI: http://dx.doi.org/10.5772/intechopen.94210*

[2] Marini D, Cunningham D, Corney JR. Near net shape manufacturing of metal: A review of approaches and their evolutions. Proc Inst Mech Eng Part B J Eng Manuf 2018;232:650-69. DOI:

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**3.3** *Fusarium* **toxins**

*Mycotoxins and Food Safety*

contaminated with aflatoxin [40].

**3.2 Ochratoxin A**

aflatoxin production at 24° C, and no production at temperatures below 13°C or above 42°C and relative humidity below 70% [30]. Heat processing, such as ultrahigh-temperature (UHT) treatment, pasteurization, roasting, and baking, and also cold storage do not affect aflatoxin in foods since they are fairly stable and resistant [31, 32]. Approximately more than 14 various chemical forms of AF are present in nature; however, the most dangerous ones are aflatoxins B1, B2, G1, and G2 [33]. The nomenclature of aflatoxins with these letters is based on the color they exhibit under ultraviolet radiation (B, blue, and G, green) [34]. Various food products especially grown in hot and humid regions of the world are susceptible to fungal invasion and aflatoxin production, including groundnuts, maize, various spices, tree nuts, cottonseed, pistachios, copra, wheat, rice, etc. [25]. AFB1 is converted into metabolized AFM1 and excreted in milk in both human and lactating animals [35]. The European Commission, Codex Alimentarius Commission, Germany, Turkey, Switzerland, France, Sweden, Belgium, Argentina, Iran, and Honduras have regulated an acceptable limit for AFM1 at 50 ng/L for infants, for raw, pasteurized, and UHT milk. On the other hand, the United States, Brazil, China, Bulgaria, Czech Republic, Kuwait, and Serbia have accepted 500 ng/L level for AFM1 [31]. Aflatoxin contamination causes huge economic and critical health problem due to their high toxicity. For example, aflatoxin contamination is estimated to cause damages to the corn industry in the United States ranging from US \$ 52.1 million to US \$ 1.68 billion [36]. They are carcinogenic, hepatotoxic, and teratogenic, decrease immune systems, poison the body through respiratory, and can directly affect the structure of DNA [37]. Of all the human health effects associated with aflatoxin exposure, the weight of evidence is strongest for aflatoxin-related liver cancer and secondarily of the synergism between aflatoxin exposure and chronic HBV infection in liver cancer risk [38]. In 1974, there was an outbreak of hepatitis due to aflatoxin in India, resulting in an estimated 106 deaths [22]. In 2004 the largest outbreak was ever recorded, where 317 people became ill and 125 people died because of consumption moldy maize which early harvested and stored improper harvested condition [39]. In 2013, countries in Europe, including Romania, Serbia, and Croatia, reported that nationwide milk was

Ochratoxin A (OTA) is a natural mycotoxin produced mainly by fungal type of *Aspergillus* and *Penicillium* under optimum environmental conditions and storage especially tropical and subtropical regions such as Eastern and South Europe, Canada, and South America [41, 42]. There are three types of ochratoxins, namely A, B, and C. Especially, OTA is known as the most common and important one for public and animal health. Although people are exposed to OTA by inhalation or dermal contact, various foods are the main source of exposure to OTA including maize, sorghum, wheat, rice, barley, rye, bread, oats, flour, pasta, grapes, infant cereals, apples, peaches, strawberries, pears, oranges, figs, mangoes, wine, tomatoes, coffee beans, watermelons, nuts, rapeseed, sesame seeds, spice, soybeans, cocoa, peanuts, chickpeas, milk and milk-based baby formulae, eggs, cheese, yam, potatoes, garlic, onions, fish, pork, poultry, jerky, and dried beans [43]. Recently, the presence of OTA has been detected in bottled water [44], plant food supplement, and food coloring agent [45]. According to the European Commission report, the estimated adult exposure to OTA is as follows: 44% cereals, 10% wine, 9% coffee, 7% beer, 5% cacao, 4% dried fruits, 3% meat, 3% spices, and 15% others [46]. For the first time in 1970, the presence of OTA was detected in human blood in Balkans [47]. In the review of Malir et al., published data on OTA in human blood samples from healthy persons were compiled, and concentrations higher than 1.0 g/L were observed in several countries [48].

**48**

*Fusarium* toxins are secondary metabolites synthesized by toxigenic molds including *Fusarium oxysporum*, *F. culmorum*, *F. roseum*, and *F. graminearum* [50]. Fumonisins (FBs), zearalenone (ZEA), trichothecenes, deoxynivalenol (DON), and nivalenol (NIV) are the most common *Fusarium* mycotoxin groups [51]. Recently fusaproliferin (FUS), beauvericin (BEA), enniatins (ENNs), and moniliformin (MON) are discovered but less studied [52]. *Fusarium* disease outbreak on cereal products such as wheat, barley, and maize causes worldwide economic losses due to yield loss and reduced grain quality, for example, losses in the United States of \$ 1–20 million in a normal year and \$31–46 million in a year [53]. *Fusarium* mycotoxin has both acute and chronic toxic effects and been shown to cause a wide variety of toxic effects in animals [54]. Spontaneous outbreaks of *Fusarium* mycotoxicosis have been reported in Europe, Asia, Africa, New Zealand, and South America. Moreover, chronic intake of these mycotoxins is reported on a regular and more widespread basis due to their global occurrence [55]. *Fusarium* mycotoxin limits specified in unprocessed cereals, milling products, and cereal foodstuffs are 200–1750 μg/kg for DON, 20–400 μg/kg for ZEN, and 200–4000 μg/kg for the sum of B1 + B2 fumonisins (FB1 + FB2 combined) according to the European Commission (19 December 2006).

#### *3.3.1 Fumonisin*

Fumonisins are generated by various fungal species such as *Fusarium verticillioides* and *F. proliferatum* also by *A. niger* and were discovered in 1988 in South Africa [56, 57]. Nowadays 28 types of fumonisin have been identified that are divided into four groups, fumonisins A (A1, A2, and A3), fumonisins B (B1, B2, and B3), fumonisins C (C4, C3, and C1), and fumonisins P (P1, P2, and P3), but the most important group of fumonisins is the B group, which contains fumonisins B1 (FB1), B2 (FB2), B3 (FB3) [58].

The International Agency for Research on Cancer (IARC) identified FB1 as possibly carcinogenic to humans (group 2B). Recent studies reported that FB1 causes an increased prevalence of esophageal and liver cancer in humans [59]. Furthermore, this mycotoxin has been found to have toxic effects against several organs (nervous and cardiovascular systems, liver, lung, kidney) in animals [60]. Fumonisins are largely found in corn and corn-based foods and also FB1 in rice, beer, sorghum, cowpea seeds, triticale, beans, asparagus, and soybeans [61].

#### *3.3.2 Zearalenone (ZEA)*

Zearalenone (ZEA), known as an estrogenic mycotoxin, is a secondary metabolite produced by *Fusarium* species such as *F. graminearum*, *F. culmorum*, *F. cerealis*, *F. equiseti*, *F. crookwellense*, and *F. semitectum* (mainly *F. culmorum* and *F. graminearum*) [62]. The main contamination source of ZEA is cereal-based foods such as maize, sorghum, wheat, rice, barley, oats, and also nuts, soybean, and sesame [63].

Several in vivo studies found that ZEA disrupts hormonal balance due to its similarity to naturally occurring estrogens [64]. The mycotoxin has high affinity for estrogen receptors, causing reproduction and fertility disorders in mammals [65]. In addition, it is known that progressive exposure to endocrine-modulatory compound has been linked with carcinogenesis in human [64]. According to the European Food Safety Authority (EFSA) report in 2014, the bioavailability of toxin is up to 80% in human and animals such as rats, rabbits, and pigs [66]. Moreover, recent works report ZEA is metabolized in the liver and has shown hepatotoxic, immunotoxic, carcinogenic, and nephrotoxic effect in animal tests [67–69]. As this mycotoxin possesses such consumer health risks, the European Union (EU) has prescribed the limits of ZEA (20–350 μg/kg) for various processed and unprocessed cereals [66].


**5.1 Safe**

To experience safe care, people would experience care that is free from any unintended injury, harm, or error. Falls are a common unintended injury people experience. Over three million aging adults fall each year. Over eight hundred thousand are hospitalized because of a fall [43]. Preventing falls for safety becomes an unmet need. Therefore, one may begin to study the primary reasons why falls occur and determine an innovation to prevent falls that is not currently available.


*Article* **The Effect of Abiotic Factors on Abundance and Photosynthetic Performance of Airborne Cyanobacteria and Microalgae Isolated from the Southern Baltic Sea Region**

**Kinga Wi´sniewska 1 , Sylwia Sliwi ´ ´ nska-Wilczewska 2,\* , Anita Lewandowska 1 and Marta Konik 3**

**Abstract:** Cyanobacteria and microalgae present in the aquatic or terrestrial environment may be emitted into the air and transported along with air masses over long distances. As a result of staying in the atmosphere, these organisms may develop a greater tolerance to stressful factors, but this topic is still relatively unknown. The main aim was to show an autecological characteristic of some airborne microalgae and cyanobacteria strains by a factorial laboratory experiment approach, including changes in irradiance, temperature, and salinity conditions. The additional purpose of this work was also to present part of the Culture Collection of Baltic Algae (CCBA) collection, which consists of airborne algae (AA) isolated from the atmospheric air of the southern Baltic Sea region. Altogether, 61 strains of airborne cyanobacteria and microalgae from the southern Baltic Sea region were isolated from May 2018 to August 2020. Selected microorganisms were tested in controlled laboratory conditions to identify their response to different irradiance (10–190 μmol photons m−2 s−1), temperature (13–23 ◦C), and salinity conditions (0–36 PSU). The highest numbers of cells (above 30 × 105 cell mL−1) were recorded for cyanobacterium *Nostoc* sp., and for diatoms *Nitzschia* sp., *Amphora* sp., and *Halamphora* sp. We found that for cyanobacterium *Nostoc* sp. as well as for green alga *Coccomyxa* sp. the maximum cell concentrations were recorded at the salinity of 0 PSU. Moreover, cyanobacteria *Planktolyngbya contorta*, *Pseudanabaena catenata*, *Leptolyngbya foveolarum*, *Gloeocapsa* sp., and *Rivularia* sp. were able to grow only at a salinity of 0 PSU. On the other hand, in the range of 16–24 PSU, the highest cell numbers of examined diatoms have been identified. Our research provided that deposited airborne microalgae and cyanobacteria showed full colonization potential. The present experiment suggests that the adaptive abilities of microorganisms, in particular those producing toxins, may contribute to the spread in the future. Thus, it may increase human exposure to their negative health effects. Any distinctive adaptations of the genera give them an additional competitive advantage and a greater chance for territorial expansion.

**Keywords:** environmental stress; abiotic stressors; chlorophyll fluorescence; growth; photosynthetic pigments; plant physiology

#### **1. Introduction**

Cyanobacteria and microalgae present in the aquatic or terrestrial environment can be emitted into the air and transported along with air masses over long distances [1–3]. As of today, it is known that the cyanobacteria and microalgae present in the air play a role in processes occurring in the air and in global climate change [4,5]. Through absorbing and dispersing solar radiation, these species affect the radiation budget of the Earth and

**Citation:** Wi´sniewska, K.; Sliwi ´ ´ nska-Wilczewska, S.; Lewandowska, A.; Konik, M. The Effect of Abiotic Factors on Abundance and Photosynthetic Performance of Airborne Cyanobacteria and Microalgae Isolated from the Southern Baltic Sea Region. *Cells* **2021**, *10*, 103. https://doi.org/10.3390/ cells10010103

Received: 16 November 2020 Accepted: 7 January 2021 Published: 8 January 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

may also form ice-nucleating particles and cloud condensation nuclei [3,4,6,7]. There are also scientific reports that cyanobacteria and microalgae can, after the aerosolization process, invade the human respiratory tract and constitute a serious health risk [1,8–11]. Bioaerosols may be emitted from the water surface with the air bubbles and spray, which is correlated with the wind speed and wave conditions. The mechanisms of the emission of cyanobacteria and microalgae to the air are complex processes and were described in detail in several reviews [3–5]. Nevertheless, in both aerobiology and phycology, these microorganisms are the least understood [12,13].

The conditions in the atmosphere are certainly not favorable for the presence of cyanobacteria and microalgae. Bioaerosols, including cyanobacteria and microalgae present in the air, are exposed to stress factors such as temperature, humidity, oxidative stress, nitrogen starvation, radiation, and osmotic stress [2–5]. There is a theory suggesting that this stress is an evolutionary force that causes selection pressure and hence affects the spread and evolution of organisms [2]. The atmospheric survival capability depends on the adaptability of cyanobacteria and microalgae to changing environmental conditions [2,3,5]. The stress response is of great importance to their capability to colonize new habitats and to survive. Certain cyanobacteria can form sheath and mucilage, while microalgae form resistant stages [5,14]. They also tolerate demanding environmental conditions: irradiance, temperature, and humidity gradients [3,5,14,15]. According to Tesson et al. [5] and Jewson et al. [16], there is a possibility that microalgae may change the stage of life e.g., into dormant cells, during their stay in unfavorable weather conditions. Therefore, further investigation of the physiological modifications that affect airborne microalgae as they disperse is essential. Mathematical models exist to help understand the emission and transport of bioaerosols in the atmosphere, but do not provide information on the biological consequences for the organisms concerning survival, vitality, and metabolic activity [2]. Hence, the knowledge about these adaptations is still insufficient and requires environmental research and laboratory experiments.

The emergence of new phytoplankton species and changes in their taxonomical composition indicate changes in biodiversity in the Baltic Sea [17]. Ojaveer et al. [17] emphasize that the causes of biodiversity change are not yet fully understood, and the impact of biodiversity changes on the Baltic Sea ecosystem cannot be determined yet. The authors clarify that the possibility of introduction and acclimatization of new phytoplankton organisms to the Baltic Sea is enhanced by global patterns related to climate change [17]. Thus, the goal of our study was to indicate from which regions of the Baltic Sea the isolated airborne microalgae are originated. In addition, our research was aimed at demonstrating their potential for expansion range and the possibility of an invasion into other regions of the Baltic Sea and even further aquatic ecosystems. The study will extend the knowledge of algal biodiversity and help to preserve the microbial and biological resources of the region. Thus, cyanobacteria and microalgae strains from CCBA AA will help to investigate the biodiversity of the atmospheric environment, and through isolation, collection, and maintenance of new strains they can give information about their potentially negative impact on human health.

#### **2. Results and Discussion**

#### *2.1. Characterization of Airborne Cyanobacteria and Microalgae Strains*

Altogether, 61 strains of airborne cyanobacteria and microalgae belonging to 14 orders and 4 phyla from the southern Baltic Sea region were isolated from May 2018 to August 2020 (Figure 1). In scientific studies, the number of recorded organisms is given, but usually, they are not isolated and cultivated [3]. One of the largest amounts of cyanobacteria and microalgae in the air was recorded by Brown et al. [18] and it was 62 species. The success of the study was attributed to the diverse methods used by the authors to sample by using vehicle, aircraft, and normally-exposed Petri dishes at many sites. According to a review study conducted by Wi´sniewska et al. [3], *Chlorella* sp. was the most common Chlorophyte in these bioaerosol studies, while *Chlorococcum* sp. was another that appeared

regularly. Among the analyzed phylum, Cyanobacteria *Phormidium* sp. was the most common Cyanobacteria; however, *Lyngbya* sp., *Nostoc* sp. and *Anabaena* sp. were also frequently noted. On the other hand, *Navicula* sp. and *Nitzschia* sp. were the most commonly found Bacillariophyta [3]. A detailed analysis of the number of blue-green algae and microalgae identified in the air on a global scale was described by Wi´sniewska et al. [3]. Analyzing the number of isolated strains, it was shown that cyanobacteria (Cyanophyta) occurred in June, July, August, and September 2018–2019 (Figure 1, Table S1). The highest number of cyanobacteria isolates were recorded in August (12 strains) and in June (11 strains). Among the isolated strains, cyanobacteria belonging to the orders Nostocales and Synechococcocales dominated in the study period. The green algae (Chlorophyta) were isolated from May 2018 to September 2020. The largest number of green algae strains were isolated in July (9 strains). The isolated green algae were also characterized by the highest diversity (6 orders). Green algae belonging to the orders Chlorellales and Sphaeropleales were the most numerous. In June and September 2018–2019, four diatom species (Bacillariophyta) belonging to 3 orders (Naviculales, Thalassiophysales, and Bacillariales) were also isolated. In addition, one strain belonging to Klebsormidiales (Charophyta) was isolated in September 2019, and one strain belonging to Eustigmatales (Ochrophyta) in November 2019. There have been months when individual strains could not be isolated, e.g., due to not enough organisms in the sample (Figure 1, Table S1).

**Figure 1.** The number of airborne cyanobacteria and microalgae strains belonging to orders isolated in the study period (2018–2020).

As the largest number of isolated strains was recorded in the summer (June–August), it was decided to select three strains of cyanobacteria, green algae, and diatoms belonging to different orders for further research. In this study, we undertook the characterization of three strains of airborne cyanobacteria: *Nostoc* sp. (CCAA 03), *Synechococcus* sp. (CCAA 14), *Aphanothece* sp. (CCAA 48), green algae (B): *Oocystis* sp. (CCAA 20), *Coccomyxa* sp. (CCAA 21), *Kirchneriella* sp. (CCAA 38), and diatoms (C): *Nitzschia* sp. (CCAA 17), *Amphora* sp. (CCAA 34), *Halamphora* sp. (CCAA 47), which were the most abundant in aerosols of the Baltic Sea region. The listed organisms, depending on their preferences, can occur in various environments, from marine, through brackish, to freshwaters. However, the exact classification is often related to the species or strain of the microorganism [19].

It was shown that with the same initial value (OD750 = 0.1), the tested strains differed in the absorbance spectrum (Figure 2). Apart from the visible peaks of chlorophyll *a* (Chl *a*), which have approximate absorbance maxima of 430 nm and 662 nm, phycobilin pigments (Phyco) are visible in cyanobacteria. Absorption peaks for phycoerythrin (PE)

in the visible light spectrum are measured at 498 and 565 nm. Phycocyanin (PC) has a single absorption peak at 621 nm. In green algae, there is also a peak for chlorophyll *b* (Chl *b*), which has approximate maxima of 453 nm and 642 nm. While in diatoms there is a characteristic peak for chlorophyll *c* (Chl *c*), the absorption maxima of which are around 450, 581, and 629 nm. Cyanobacteria and microalgae have a variety of different pigments that can absorb energy from a wide range of wavelengths [20]. However, when an absorbance spectrum is performed on living organisms, the peaks may overlap, masking the view of the individual pigments. A more adequate way to characterize live strains is to perform a flow cytometer measurement. Thus, it can easily distinguish and identify selected airborne cyanobacteria and microalgae. It has been shown that depending on photosynthetic pigments, small organisms (*Synechococcus* sp. and *Aphanothece* sp.) are visible by the low signal intensity at 640 nm and 480 nm on the cytogram, while larger-sized organisms (*Nitzschia* sp., *Oocystis* sp.) and filamentous *Nostoc* sp. were marked by the high signal intensity at 640 nm and 480 nm on the cytogram (Figure 2). It is worth noticing that based on our observations, only the strains within the groups can be differentiated (although for green algae it would be difficult for accurate separation in a mixed sample). Some organisms from the same group (green algae, cyanobacteria, diatoms) with a different structure and cell size may not be ideal and separated.

**Figure 2.** Left-hand panel—PAR absorbance spectra determined for the airborne cyanobacteria (**A**): *Nostoc* sp. (CCAA 03), *Synechococcus* sp. (CCAA 14), *Aphanothece* sp. (CCAA 48), green algae (**B**): *Oocystis* sp. (CCAA 20), *Coccomyxa* sp. (CCAA 21), *Kirchneriella* sp. (CCAA 38), and diatoms (**C**): *Nitzschia* sp. (CCAA 17), *Amphora* sp. (CCAA 34), *Halamphora* sp. (CCAA 47) at an optical density (OD750) = 0.1; right-hand panel—cytograms obtained using a BD Accuri C6 Plus flow cytometer. FL3 detectors (red fluorescence) read fluorescence emissions excited by the blue laser (480 nm), whereas the FL4 detector (orange fluorescence) reads emissions excited by the red laser (640 nm).

Organisms obtained for the algae collections are usually isolated from seas and different inland waters [21,22]. This research focused on the isolation of airborne cyanobacteria and microalgae. At the moment, little data are allowing to determine the differences in the physiology of strains obtained from the air and the water samples [23]. However, it can be assumed that differences within one species may exist [21,24]. A great advantage of isolating cyanobacteria and microalgae from the atmosphere is the fact that it enables us to obtain species unusual for a given water reservoir or area because these organisms can be introduced from remote areas. The transport distance depends on the size and shape of particles. The large and heavy particles are dragging by the wind at a shorter distance. Small cells may be transported on hundreds of kilometers and then be deposited [1,4,5]. Studies are confirming the influence of meteorological parameters such as wind speed, air masses direction, air temperature, and humidity on the diversity of cyanobacteria and microalgae from the air [25,26]. However, the determination of their source of origin focuses on the use of the backward trajectories of air masses and the analysis of the taxonomic composition of potential sources location [3,26]. The isolation of species from the air can significantly enrich collection cultures of cyanobacteria and microalgae with organisms from distant regions. To the best of our knowledge, there is no significant algal culture collection maintaining airborne cyanobacteria and microalgae except for our newly established airborne algae (AA) collection, which is part of the Culture Collection of Baltic Algae (CCBA).

#### *2.2. The Cell Concentration of Airborne Strains under Different Culture Conditions*

The Baltic Sea is relatively shallow and small (the average depth of the Baltic Sea is 52.3 m, the maximum—459 m, and the area is approximately 415,266 km2) with limited water exchange through the narrow and shallow Danish Straits. Photosynthetically active radiation may fluctuate between 389 and 2117 μmol photons m−2 s−1 during the day [27]. Many different habitats and marine species are affected by pollution, fishing, physical modification, and other human activities, making the sea a harsh place for organisms to live [28,29]. The unique feature of the Baltic Sea is that there are areas where freshwater, brackish, and marine species occur [30]. Climatic diversity within the Baltic Sea shows the wide fluctuation in many physical and chemical parameters such as river runoff, salinity, sea level, and sea ice. Its salinity increases from east to west and north to south, from almost freshwater conditions in the northern Gulf of Bothnia, with salinity fluctuaing between 1–3 PSU, to almost oceanic conditions in the northern Kattegat, with salinity within the range 18–30 PSU. Sea surface temperature in the Proper Baltic varies from 1–2 ◦C in February up to 17–18 ◦C in August [30]. In such a variable ecosystem as the Baltic Sea region, autotrophic organisms should show the ability to adapt quickly, which is crucial for their survival and the possibility of settling in new areas. The future climate changes leading to global warming may favor the development of picocyanobacterial—the smallest cell-size cyanobacteria (0.2–2 μm) [31]—which under high temperatures achieve the maximum abundance [32,33]. Our research, conducted between 2018 and 2020 in the southern Baltic Sea region, showed that the increasing intensity of light and temperature had a positive effect on the cell concentration of the studied cyanobacterium *Nostoc* sp., and for diatoms *Nitzschia* sp., *Amphora* sp., and *Halamphora* sp.

In this study, the concentration of cyanobacteria and microalgae cells were determined under different irradiance and temperature conditions (Figure 3). In general, it was shown that both irradiance and temperature significantly affected the number of cells of examined airborne cyanobacteria (ANOVA, *p* < 0.001, *p* < 0.001, *p* < 0.01, for *Nostoc* sp., *Synechococcus* sp., and *Aphanothece* sp., respectively), green algae (ANOVA, *p* < 0.001, *p* < 0.05, *p* < 0.001, for *Oocystis* sp., *Coccomyxa* sp., and *Kirchneriella* sp., respectively), and diatoms (ANOVA, *p* < 0.001, *p* < 0.001, *p* < 0.001, for *Nitzschia* sp., *Amphora* sp., and *Halamphora* sp., respectively; Table S2). ANOVA results also showed that for each airborne strain, the effect of temperature on the cell concentration was higher than the influence of irradiance and the interaction of both factors simultaneously. It is worth mentioning here that irradiance had

no significant effect on *Coccomyxa* sp. (ANOVA, *p* > 0.5; Table S2). *Coccomyxa* sp. is resistant to enduring particularly harsh environmental conditions, e.g., grown under a low and high temperature and even high irradiance [34]. Its low variability of cells number indicates a good adaptation of the harsh conditions during emissions from the water reservoir and transport in the atmosphere.

**Figure 3.** The number of cells (N × 105 mL−1) obtained after 7 days of experiment for airborne cyanobacteria: *Nostoc* sp. (**Aa**), *Synechococcus* sp. (**Ab**), and *Aphanothece* sp. (**Ac**); airborne green algae: *Oocystis* sp. (**Ba**), *Coccomyxa* sp. (**Bb**), and *Kirchneriella* sp. (**Bc**); airborne diatoms: *Nitzschia* sp. (**Ca**), *Amphora* sp. (**Cb**), and *Halamphora* sp. (**Cc**) under different irradiance (μmol photons m−2 s−1) and temperature (◦C) conditions.

It was shown that for cyanobacterium *Nostoc* sp., green algae *Oocystis* sp. and *Kirchneriella* sp., and for all tested diatoms, the increase in light and temperature had a positive effect on the cell numbers in the cultures. In turn, cyanobacterium *Synechococcus* sp. showed growth inhibition in the highest tested irradiance. Moreover, picocyanobacteria *Synechococcus* sp. and *Aphanothece* sp. showed a significant increase in cell concentration with increasing temperature (Figure 3A). This indicates that in the future *Aphanothece* sp. and also *Synechococcus* sp. may become dominant in the Baltic Sea region and other aquatic ecosystems. Thus, if a new organism inhabits a given area, there is a high probability that if it acclimates there, it can show allelopathic effects on organisms already present there. The minimum number of cells was obtained for *Kirchneriella* sp. at 13 ◦C and 10 μmol photons m−2 s−1 (0.45 × 105 cell mL−1; Figure 3B). The highest number of cells (71.66 × 105 cell mL−1) was noted for *Halamphora* sp. at 190 μmol photons m−2 s−1 and 23 ◦C (Figure 3C). *Halamphora* sp., isolated from the Baltic Sea, has a wide temperature range of 15–25 ◦C, but a 30 ◦C-preferring strain has also been isolated. By higher temperatures, the authors noted a decrease in photosynthesis [35]. Moreover, high numbers of cells (above 30 × 105 cell mL−1) were also recorded for diatoms *Nitzschia* sp. and *Amphora* sp. and for

cyanobacterium *Nostoc* sp. (Figure 3) The latest research on airborne microalgae proves that these organisms have several adaptations, like better UV tolerance, that distinguish them from microalgae present in water [23]. Better adaptation of these organisms to stress treatment can give them the advantage to settle in new areas and become invasive species. It indicates that, after entering the appropriate environment, these species will easily attain substantial biomass and even become the dominant species in this aquatic ecosystem. It is worth noting here that *Nostoc* sp. is an important CyanoHABs species [36,37], as well as *Nitzschia* sp. as a Red Tide organism [38]. The presence of microorganisms that produce toxins in the air, and their ability to spread and acclimate to new environmental conditions is of particular importance in terms of its impact on human health [3].

Assessing the origin of microorganisms that are present in the air in small amounts is a difficult task. It is often based solely on the analysis of the backward air masses trajectory. Hence it is worth enriching them with laboratory experiments such as the analysis of the number of organisms under different salinity conditions. To estimate the region of origin of airborne cyanobacteria and microalgae, additional experiments have been performed to determine the effect of salinity on the cells' number (Figure 4). In our work, we used different salinity of culture medium to isolate new strains of airborne cyanobacteria and microalgae. Based on our observations, we have shown that most of the CCAA strains grow satisfactorily at the salinity medium of 8 PSU. However, there are several strains (*Planktolyngbya contorta* CCAA11, *Pseudanabaena catenata* CCAA12, *Leptolyngbya foveolarum* CCAA15, *Gloeocapsa* sp. CCAA18, *Pseudanabaena catenata* CCAA19, and *Rivularia* sp. CCAA 49) that grow at 0 PSU salinity.

In general, one-way ANOVA tests showed that salinity significantly affected the number of cells of examined airborne cyanobacteria (*p* < 0.001, for all), green algae (*p* < 0.001, for all), and diatom (*p* < 0.001, for all; Table S3). It was found that for cyanobacterium *Nostoc* sp. (Figure 4A) as well as for green alga *Coccomyxa* sp. (Figure 4B) the maximum cell concentration was recorded at the salinity of 0 PSU (24.15 × 105 cell mL−1 and 3.82 × 105 cell mL−1, respectively). It is worth mentioning here that *Coccomyxa* sp. did not grow at salinity above 16 PSU, despite numerous information related to their wide tolerance to harsh environmental conditions including salinity [34]. Moreover, the highest cell numbers of tested diatoms were found in the range of 16–24 PSU (21.14 × 105 cell mL−1 for *Nitzschia* sp., 15.52 × 105 cell mL−1 for *Amphora* sp., and 20.32 × 105 cell mL−1 for *Halamphora* sp.; Figure 4C).

Our measurements have shown that salinity has also a significant impact on the concentration of cells of individual species of algae and cyanobacteria. It was found that for cyanobacterium *Nostoc* sp. as well as for green alga *Coccomyxa* sp. the maximum cell concentrations were recorded at the salinity of 0 PSU (Figure 4A,B). Moreover, cyanobacteria *Planktolyngbya contorta*, *Pseudanabaena catenata*, *Leptolyngbya foveolarum*, *Gloeocapsa* sp., and *Rivularia* sp. belonging to the CCAA were able to grow only at a salinity of 0 PSU (data not shown). It suggests that these species come from freshwater communities. Research conducted by Woelfel et al. [27] indicates that salinity did not strongly influence the growth of diatoms, they also have a high tolerance to low salinity. In contrast, diatoms isolated from the air had the highest cell numbers found in the range of 16–24 PSU; however, all of them had lower tolerance to 0 PSU (Figure 4C). According to Potapova [39], the disparity in salt content between coastal and inland waters was considered a significant barrier that only a few diatom lineages were able to cross in one direction, from marine to freshwater habitat. These findings indicate that the airborne diatoms may come from the western part of the Baltic Sea [17]. Surprisingly, it was found that the picocyanobacteria *Synechococcus* sp. and *Aphanothece* sp. showed a similar abundance in the whole range of tested salinity. Considering their small cell size and their ability to be transported with aerosols over long distances, this property may give them an advantage in colonizing new water areas even with various salinity. The HYSPLIT air mass trajectories model [40,41] let us determine whether the given cyanobacteria and microalgae present in the air were brought from near or far, land or sea source areas [1,3]. We noted that only in the case of *Nitzschia* sp.

and *Aphanothece* sp. Did the analysis of the backward trajectories of air masses indicated their transport from over the land (Figure S1e). When analyzing the salinity preferences of selected strains, with the highest abundance by 4 PSU, it can be also concluded that *Aphanothece* sp. had a terrestrial origin. The preference for *Aphanothece* sp. to freshwater is confirmed by literature data [42]. In addition, Dembowska [43] showed the presence of *Aphanothece* sp. in the waters of lakes (Iławskie Lake District) over which the mass of air passed through.

**Figure 4.** The number of cells (N × 105 mL−1) obtained after 7 days of experiment for airborne cyanobacteria (**A**): *Nostoc* sp. (CCAA 03), *Synechococcus* sp. (CCAA 14), *Aphanothece* sp. (CCAA 48), green algae (**B**): *Oocystis* sp. (CCAA 20), *Coccomyxa* sp. (CCAA 21), *Kirchneriella* sp. (CCAA 38), and diatoms (**C**): *Nitzschia* sp. (CCAA 17), *Amphora* sp. (CCAA 34), *Halamphora* sp. (CCAA 47) under different salinity conditions.

In all other cases, the analysis of taxa origin was much more difficult because the air masses passed through the Southern Baltic Proper first and then through the land. In the case of *Synechococcus* sp., *Oocystis* sp., *Coccomyxa* sp., and *Halamphora* sp., the air masses flowed over the measuring station all the way from the North Sea (Figure S1b). Analyzing salinity preferences in combination with the backward trajectories of air masses, it is most likely that only *Halamphora* sp. could have arrived from the distant Kattegat region (Figure S1a).

#### *2.3. Effect of Irradiance and Temperature on Pigments Content*

The autecology of airborne cyanobacteria and microalgae was characterized by the changes in composition and proportion of photosynthetic pigments, i.e., Chl *a*, Chl *b*, Chl *c*, and Phyco under different irradiance (μmol photons m−2 s−1) and temperature ( ◦C) conditions. As Chl *a* is the main photosynthetic pigment, and Car is responsible for protecting the microorganisms and is a variable when cells are under stress, they are presented in Figures 5 and 6. While additional pigments (Phyco, Chl *b*, Chl *c*) were presented in the Supplementary Materials Figure S2.

**Figure 5.** Changes in Chl *a* content (pg cell−1) obtained after 7 days of experiment for airborne cyanobacteria: *Nostoc* sp. (Aa), *Synechococcus* sp. (**Ab**), and *Aphanothece* sp. (**Ac**); airborne green algae: *Oocystis* sp. (**Ba**), *Coccomyxa* sp. (**Bb**), and *Kirchneriella* sp. (**Bc**); airborne diatoms: *Nitzschia* sp. (**Ca**), *Amphora* sp. (**Cb**), and *Halamphora* sp. (**Cc**) under different irradiance (μmol photons m−2 s−1) and temperature (◦C) conditions.

It was found that irradiance and temperature as well as their interaction significantly affected the Chl *a* content in *Nostoc* sp., *Synechococcus* sp., and *Aphanothece* sp. (ANOVA, *p* < 0.001, *p* < 0.001, and *p* < 0.001, respectively), as well as Car content (ANOVA, *p* < 0.001, *p* < 0.001, and *p* < 0.001, respectively). ANOVA indicated that for examined cyanobacteria, the effect of irradiance on cell-specific pigments content was higher than the effect of temperature and the interaction of both factors (Table S4). It was shown that the cellspecific pigments content (Chl *a*, Car) for *Nostoc* sp. and *Synechococcus* sp. decreased with increasing irradiance (Figures 5 and 6). On the other hand, for *Aphanothece* sp. a decrease in Chl *a* (Figure 5(Ac)) and Car content (Figure 6(Ac)) with increasing irradiance was shown. The highest content of the studied pigments was found in *Synechococcus* sp., while the lowest was in *Aphanothece* sp. The highest content of Chl *a* (Figure 5(Ab)) and Car (Figure 6(Ab)) was recorded in *Synechococcus* sp. At the lowest irradiance (10 μmol photons m−2 s−1) and the lowest temperature (13 ◦C), which is respectively 5.77 pg cell−1 and 4.69 pg cell−1.

**Figure 6.** Changes in Car content (pg cell−1) obtained after 7 days of experiment for airborne cyanobacteria: *Nostoc* sp. (**Aa**), *Synechococcus* sp. (**Ab**), and *Aphanothece* sp. (**Ac**); airborne green algae: *Oocystis* sp. (**Ba**), *Coccomyxa* sp. (**Bb**), and *Kirchneriella* sp. (**Bc**); airborne diatoms: *Nitzschia* sp. (**Ca**), *Amphora* sp. (**Cb**), and *Halamphora* sp. (**Cc**) under different irradiance (μmol photons m−2 s−1) and temperature (◦C) conditions.

Irradiance and temperature, as well as their interaction, were found to significantly affect the Chl *a* content in tested strains of green algae (ANOVA, *p* < 0.001, for *Oocystis* sp., *p* < 0.001, for *Coccomyxa* sp., and *p* < 0.001, for *Kirchneriella* sp.), and Car content (ANOVA, *p* < 0.001, for all). For Chl *a*, and Car content, the effect of temperature for *Oocystis* sp. And *Coccomyxa* sp. Was higher than the effect of irradiance and the interaction of both factors (Table S5). In turn, the Chl *a* and Car of *Kirchneriella* sp. Was more affected by irradiance than by temperature. It was shown that the cell-specific pigments content (Chla *a* and Car) for the analyzed green algae decreased with increasing irradiance at 13 ◦C and 23 ◦C. On the other hand, at the temperature of 18 ◦C, the content of the analyzed pigments remained at a similar level. The lowest Chla *a*, and Car content were recorded for *Coccomyxa* sp. On the other hand, it was demonstrated that *Kirchneriella* sp. Had the highest concentration of cell-specific pigments content was compared to examined green algae. The highest content of Chla *a* (Figure 5(Bc)) and Car (Figure 6(Bc)) was recorded at irradiance 10 μmol photons m−2 s−1 and temperature 18 ◦C, which were 12.84 pg cell−1 and 10.33 pg cell−1 respectively.

Both irradiance and temperature significantly affected also the cell-specific Chl *a* content of *Nitzschia* sp., *Amphora* sp., and *Halamphora* sp. (ANOVA, *p* < 0.001, for all),

as well as Car content (ANOVA, *p* < 0.001, for all). ANOVA indicated that the effect of irradiance on pigments content was higher than the effect of temperature and of the relationship of both factors (Table S6). It was shown that the cell-specific pigments content for the analyzed diatoms decreased with increasing irradiance (Figures 5C and 6C). In general, the lowest cell-specific pigment content for the analyzed diatoms was recorded at 190 μmol photons m−2 s−1 and 23 ◦C. The highest content of Chla *a* and Car was recorded for *Amphora* sp., which in the light of 10 μmol photons m−2 s−1 and temperature of 18 ◦C was equal to 0.85 pg cell−1 and 1.90 pg cell−1 respectively. Moreover, it was also shown that *Amphora* sp. had the highest concentration of cell-specific pigment content compared to other diatoms.

For many cyanobacteria and microalgae, the high light intensity is an unfavorable environmental factor [44], which organisms can respond to by, for example, changing the concentration of pigments in cells [23,32,45]. Generally, the factorial experiments performed in this study showed a negative effect of the increasing irradiance on the content of the cell-specific pigment for the analyzed airborne cyanobacteria and microalgae, obtaining the highest contents at 10 μmol photons m−2 s−1 and the lowest for 190 μmol photons m−2 s−1. It was shown that only the cell-specific Phyco content for *Aphanothece* sp. increased with increasing light (Figure S2). High Chl *a* content in low light may indicate that airborne cyanobacteria and microalgae may deposit in highly shaded waters and continue to grow intensively [46]. The increased chlorophyll content found in microalgae grown at low light intensity is possibly due to light/shaded adaptations that enhance the use of light energy [47]. It is also worth noting that in the cases of cyanobacteria and diatoms, irradiance has a stronger effect on pigments than temperature.

Moreover, under low irradiance, the greatest increase of Phyco in cyanobacterial cells was noted (Figure S2), which additionally confirms the ability of these species to appear in shaded waters [48,49]. It can be because photoaclimatization occurs when photosynthetic pigments are reduced with the increase of irradiation intensity [50]. Thus, in the case of isolated in the region of the southern Baltic Sea airborne cyanobacteria and microalgae, except *Aphanothece* sp., the photoaclimatization ability was noted, which proves the ability to adapt to changing environmental conditions. It is also worth mentioning here that stressful factors such as high light intensity favor the accumulation of Car pigments that have a protective function. The latest research on airborne green-algae has shown that these organisms accumulate high levels of carotenoids in such stressful conditions [23]. However, in the present study, this phenomenon was not observed, which may suggest that the isolated microorganisms adapted to these conditions and were not under stress. According to the "Everything small is everywhere" hypothesis, not much can be done to prevent airborne microalgae and cyanobacteria to colonize new regions, when the environmental factors change. Thus, such experiments are especially important for estimating future effects in a changing environment.

#### *2.4. Effect of Irradiance and Temperature on the Maximum PSII Quantum Efficiency*

The effect of irradiance and temperature on changes in the maximum quantum efficiency of PSII photochemistry (*F*v/*F*m parameter) of airborne cyanobacteria and microalgae strains was also determined. It was found that irradiance and temperature, as well as their interaction significantly affected the *F*v/*F*m of tested cyanobacteria (ANOVA, *p* < 0.001, for all), green algae (ANOVA, *p* < 0.001, for all), and diatoms (ANOVA, *p* < 0.001, for *Amphora* sp., and *Halamphora* sp., respectively). It was also shown that irradiance and temperature had no significant effect on *Nitzschia* sp. (ANOVA, *p* > 0.05; Table S7). Generally, ANOVA indicated that for tested airborne cyanobacteria, green algae, and diatoms the effect of temperature on the *F*v/*F*m parameter was higher than the effect of irradiance and the interaction of both factors (Table S7).

It was shown that for the tested cyanobacteria, an increase in the *F*v/*F*m value with increasing temperature was noted. In turn, a decrease in *F*v/*F*m with increasing irradiance was also recorded. The highest values of *F*v/*F*m among the examined cyanobac-

teria, as in the case of the number of cells, were recorded for *Nostoc* sp. The highest value of the Fv/Fm parameter, equal to 0.76, for this cyanobacterium, occurred under 100 μmol photons m−2 s−1 and 23 ◦C (Figure 7A). In general, for green algae and diatoms, a decrease in *F*v/*F*m was recorded with increasing irradiance (Figure 7B,C). The greatest differences were recorded for *Coccomyxa* sp. at 13 ◦C. In such conditions, the decrease of this parameter from 10 to 190 μmol photons m−2 s−1 was more than 1.2-fold (Figure 7B). Moreover, green algae were characterized by the highest values of the *F*v/*F*m parameter compared to cyanobacteria and diatoms. For *Oocystis* sp. and *Kirchneriella* sp. the *F*v/*F*m always exceeded the value of 0.8 (Figure 7B). In turn, the lowest *F*v/*F*m value (0.12) among all the analyzed strains was recorded for *Aphanothece* sp. at irradiance 190 μmol photons m−2 s−1 and temperature 13 ◦C (Figure 8A).

**Figure 7.** Changes in the maximum PSII quantum efficiency (*F*v/*F*m) obtained after 7 days of experiment for airborne cyanobacteria: *Nostoc* sp. (**Aa**), *Synechococcus* sp. (**Ab**), and *Aphanothece* sp. (**Ac**); airborne green algae: *Oocystis* sp. (**Ba**), *Coccomyxa* sp. (**Bb**), and *Kirchneriella* sp. (**Bc**); airborne diatoms: *Nitzschia* sp. (**Ca**), *Amphora* sp. (**Cb**), and *Halamphora* sp. (**Cc**) under different irradiance (μmol photons m−2 s−1) and temperature (◦C) conditions.

The chlorophyll *a* fluorescence measurements may indicate changes in photosystem II (PSII) activity by calculating the maximum quantum yield of PSII (*F*v/*F*m) [51]. On the basis of our research, we determined that the studied airborne cyanobacteria and microalgae showed differences in the functioning of the maximum quantum yield of PSII, depending on the environmental factors. In general, for cyanobacteria, green algae, and diatoms, a decrease in the maximum quantum yield of PSII was recorded with increasing light. It was shown that for the tested cyanobacteria, an increase in the maximum quantum yield of PSII with increasing temperature was noted. The green algae were characterized by the highest values of the *F*v/*F*m parameter compared to cyanobacteria and diatoms. In turn, the lowest *F*v/*F*m value among all the analyzed strains was recorded for *Aphanothece* sp. The appropriate composition of photosynthetic pigments, which is responsible for the proper functioning of the photosynthesis mechanism, enables airborne cyanobacteria and microalgae to grow under the control of changing environmental conditions and to colonize different water bodies [20].

**Figure 8.** Photographs of airborne cyanobacteria (**A**): *Nostoc* sp. (CCAA 03; (**a**)), *Synechococcus* sp. (CCAA 14; (**b**)), *Aphanothece* sp. (CCAA 48; (**c**)), green algae (**B**): *Oocystis* sp. (CCAA 20; (**a**)), *Coccomyxa* sp. (CCAA 21; (**b**)), *Kirchneriella* sp. (CCAA 38; (**c**)), and diatoms (**C**): *Nitzschia* sp. (CCAA 17; (**a**)), *Amphora* sp. (CCAA 34; (**b**)), *Halamphora* sp. (CCAA 47; (**c**)) used in this study. Scale bar = 10 μm.

#### **3. Materials and Methods**

#### *3.1. Culture Conditions*

All airborne cyanobacteria and microalgae were collected between 2018 and 2020 at a research station in Gdynia, located 1 km from the coastal zone of the Gulf of Gda ´nsk, southern Baltic Sea region [1]. Algae have been identified by were identified using keys and world literature [52–58]. The taxonomic composition was analyzed under a Nikon Eclipse 80i microscope at a magnification of 10 and 100×. A list of species isolated in the study period is shown in Table S1 (in Supplementary Material). The factorial experiments were conducted on airborne cyanobacterial strains: *Nostoc* sp. (CCAA 03), *Synechococcus* sp. (CCAA 14), *Aphanothece* sp. (CCAA 48), green algae strains: *Oocystis* sp. (CCAA 20), *Coccomyxa* sp. (CCAA 21), *Kirchneriella* sp. (CCAA 38), and diatoms strains: *Nitzschia* sp. (CCAA 17), *Amphora* sp. (CCAA 34), *Halamphora* sp. (CCAA 47) (Figure 8).

The strains isolated from the air over the Baltic Sea region are maintained as unialgal cultures in the Culture Collection of Baltic Algae (Airborne Algae—AA) at the Institute of Oceanography, University of Gda ´nsk, Poland. Tests on the "batch cultures" were carried out in 25-mL glass Erlenmeyer flasks containing sterilized F/2 medium [59]. The strains were incubated under a 16:8 h light:dark cycle at three PAR irradiances (10, 100, and 190 μmol photons m−2 s−1), at three temperatures (13 ◦C, 18 ◦C, and 23 ◦C), and salinity of 8 PSU. For the experiment determining the abundance of the tested strains under the influence of different salinity, ten different F/2 mediums (in the range of 0 to 36 PSU) were made. These mediums were obtained by dissolving the appropriate amount of Tropic Marin Sea Salt in a specific volume of distilled water. The salinity of the medium was measured by a salinometer (inoLabCond Level 1, Weilheim in Oberbayern, Germany).

The initial number of cells in all conducted experiments was 105 cells per mL. The test cultures were grown in three replicates and were incubated for one week. After that time in the exponential growth phase, the cells concentration, pigments content, as well as photosynthesis performance, were measured in each replicate.

#### *3.2. Calculation of Cell Density*

Cell density was calculated using linear regression models based on cell concentration (N mL−1) and optical density (OD). Calculation of the cell number was conducted using the procedure described by Sliwi ´nska-Wilczewska et al. [ ´ 60] with a BD Accuri C6 Plus flow cytometer (BD Biosciences, San Jose, CA, USA) or by Sliwi ´nska-Wilczewska et al. [ ´ 61] with a light microscope (Nikon Eclipse 80i, Nikon, Tokyo, Japan) and the Bürker counting chamber for filamentous cyanobacteria. This method makes it possible to determine the correlation coefficients and the linear correlations between the number of cells and OD. The cell concentrations in the test cultures were estimated on the basis of calibration curves (Table S8).

#### *3.3. Air Masses Trajectories*

For each sampling day, using 6-h intervals, the air mass 48 h backward trajectory was obtained using the HYSPLIT model (NOAA Air Resources Laboratory, College Park, MD, USA) [40,41]. HYSPLIT is a complete system for computing basic trajectories of air parcels for dynamic simulations of dispersion and deposition. The three standard air mass (500, 1000, and 1500 m AGL) arrival heights were used to test the location of air mass overlap. By tracking the path of air masses at a given time 48h before sampling, this information helps to determine the source of both chemical and biological air pollution.

#### *3.4. Determination of the Chlorophyll, Carotenoids, and Phycobiliproteins Content*

The concentration of chlorophyll (Chl *a*) for tested cyanobacterial and microalgal strains was calculated according to Jeffrey and Humphrey [62]. The concentration of carotenoids (Car) was calculated using the formula employed by Strickland and Parsons [63]. After 7 days of incubation, 20 mL of culture was filtered using 0.45 μm filters (Macherey-Nagel MN GF-5, Dueren, Germany). Chl *a* and Car were extracted with cold 90% acetone in the dark for 2 h at −20 ◦C. To remove cell debris and filter particles the pigment extract was centrifuged at 12,000× *g* rpm for 2 min (Sigma 2-16P, Osterode am Harz, Germany). The extinction was determined at 750 nm, 665 nm, and 480 nm with a UV-VIS Multiskan GO spectrophotometer (Thermo Scientific, Waltham, MA, USA) and using 1 cm glass cuvette.

Phycobiliproteins (Phyco) were extracted for tested cyanobacterial strains according to Stewart and Farmer [64]. After 7 days of incubation, 20 mL of culture was filtered using 0.45 μm filters (Macherey-Nagel MN GF-5, Dueren, Germany). Each filter was thoroughly homogenized in a medium consisting of 0.25 M Trizma Base, 10 mM disodium EDTA, and 2 mg/mL lysozyme. The pH of the medium was adjusted to 5.0 through the addition of hydrochloric acid (concentrated HCl). Homogenates were incubated in darkness for 2 h at 37 ◦C and then for 20 h at 2 ◦C. To remove cell debris and filter particles, the pigment extract was centrifuged at 12,000× *g* rpm for 2 min (Sigma 2-16P, Osterode am Harz, Germany). The absorbance of the pigment extract was measured at 565 nm, 620 nm, 650 nm, and 750 nm with a Multiskan GO spectrophotometer (Thermo Scientific, Waltham, MA, USA) and using a 1 cm glass cuvette. The concentration of Phyco was calculated according to Tandeau de Marsac and Houmard [65].

#### *3.5. Determination of the Chlorophyll a Fluorescence*

The measurement of the chlorophyll fluorescence of airborne cyanobacteria and microalgae was conducted after 7 days of the experiment according to the method described by Sliwi ´nska-Wilczewska et al. [ ´ 24]. Fluorescence parameter *F*v/*F*m (where *F*v—the difference between the maximum and minimum fluorescence and *F*m—the maximum fluorescence) [51] was analyzed using pulse amplitude modulated (PAM) fluorometer (FMS1, Hansatech, King's Lynn, United Kingdom). Illumination was provided by a 594 nm amber modulating beam with 4 step frequency control. Cyanobacterial and microalgal materials were placed in the leaf clip on the 13 mm glass fiber filter (Whatman GF/C, Saint Louis, MO, USA). The actinic light was the same as the one used for the growth of algal cells to provide optimal conditions for photosynthetic activity. Saturation pulses (4500 μmol photons m−2 s−1) of 0.7 s duration were used for all airborne cyanobacterial and microalgal species. All samples were dark-adapted for 5 min before measurements.

#### *3.6. Statistical Analyses*

To test the influence of a light intensity, temperature, and their interaction on studied parameters the two-way ANOVA was used. One-way ANOVA was used to test the effect of salinity on the number of cells of tested strains on the last day of the experiment. Levels of significance were: \* *p* < 0.05; \*\* *p* < 0.01; \*\*\* *p* < 0.001. All data are reported as means ± standard deviations (SD). The statistical analyses were performed using Statistica® 13.1 software (TIBCO Software Inc., StatSoft, Kraków, Poland). The heat maps were performed using RStudio 1.3.1056 software (Boston, MA, USA).

#### **4. Conclusions**

Transport of bioaerosols with air masses may play important role in microbial dispersal, and thus maintaining the diversity of water systems [5,66]. To date, the invasiveness of new species has been closely connected to their transfer from the basin to the basin along with the ballast waters. Almost all known harmful algal bloom species have been reported in viable form from this source [67]. However, nowadays research on airborne algae confirms that these organisms can be carried far distances from their source of origin [1,5,68], thus it is worth testing their preferences and backward trajectories in order to estimate their source. Our research has shown that cyanobacteria *Nostoc* sp. as well as green alga *Coccomyxa* sp. may come from freshwater communities. On the other hand, the highest cell numbers of analyzed diatoms were found in the range of 16–24 PSU. These findings indicate that the airborne diatoms may come from the western part of the Baltic Sea. Moreover, analyzing salinity preferences in combination with the backward trajectories of air masses, it is most likely that only *Halamphora* sp. could have arrived from the distant Kattegat region. It was found that the picocyanobacteria *Synechococcus* sp. and *Aphanothece* sp. showed a similar abundance in the whole range of tested salinity. Considering picocyanobacterial small cell size and their ability to be transported with aerosols over long distances, this property may give them an advantage in colonizing new water areas even with various salinity conditions. We also found that cyanobacterium *Nostoc* sp., and diatom *Nitzschia* sp., a well-known bloom-forming species, can quickly reach significant biomass and even become the dominant species in the aquatic ecosystem as they showed the highest numbers of cells under favorable light, temperature, and salinity conditions. The present experiment suggests that the adaptive abilities of microorganisms, in particular those producing toxins, may contribute to the spread in the future. Thus, it may increase human exposure to their negative health effects.

Airborne cyanobacteria and microalgae still remain a group of poorly understood organisms due to difficulties in their extraction and isolation. Moreover, the increase in the number of alien and invasive species is becoming an increasingly serious problem in the world. Therefore, it is necessary to carefully examine the physiology and autecology of airborne organisms and their ability to inhabit distant water bodies. Isolating and creating a collection of cyanobacteria and microalgae has great potential. These organisms can later be used in environmental studies, education, or biotechnology [21]. In addition, the isolation of individual strains allows their use in laboratory conditions exploring the relationships between organisms present in the natural environment [21]. Thanks to this, the complex relationships that occur in nature can be better understood.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/2073-4 409/10/1/103/s1. Figure S1: 48-h air mass backward trajectory analysis from HYSPLIT model (Draxler and Hess, 1998, NOAA Air Resources Laboratory, US) for the date of sampling; Figure S2: Changes in Phyco (A; pg·cell−1), Chl *b* (B; pg·cell−1), and Chl *c* (C; pg·cell−1) content obtained after 7 days of experiment for airborne cyanobacteria; Table S1: A list of species from the southern Baltic Sea region isolated in 2018-2020.; Table S2: Two-way factorial ANOVA of cells concentration measured in tested airborne cyanobacteria and microalgae growing at different temperatures (◦C) and irradiance (μmol photons m−2 s−1); Table S3: One-way ANOVA of cells concentration measured in tested airborne cyanobacteria and microalgae growing at different salinities (PSU); Table S4: Twoway factorial ANOVA of cell-specific Chl *a*. Car. and Phyco content measured in tested airborne cyanobacteria growing at different temperatures (◦C) and irradiance (μmol photons m−2 s−1); Table S5: Two-way factorial ANOVA of cell-specific Chl *a*. Car. and Chl *b* content measured in tested airborne green algae growing at different temperatures (◦C) and irradiance (μmol photons m−2 s−1); Table S6: Two-way factorial ANOVA of cell-specific Chl *a*. Car. and Chl *c* content measured in tested airborne diatoms growing at different temperatures (◦C) and irradiance (μmol photons m−2 s−1); Table S7: Two-way factorial ANOVA of *F*v/*F*m parameter measured in tested airborne cyanobacteria and microalgae growing at different temperatures (◦C) and irradiance (μmol photons m−2 s−1); Table S8: Linear regression and correlation coefficients (r) used to calculate the number (*N*) of studied airborne cyanobacteria, green algae, and diatoms cells in cultures based on optical density (OD) measurements.

**Author Contributions:** Conceptualization, K.W., S.S.-W., M.K., A.L.; methodology, K.W., S. ´ S.-W.; ´ formal analysis, K.W., S.S.-W.; investigation, K.W., S. ´ S.-W.; data curation, K.W., S. ´ S.-W., M.K.; writing— ´ original draft preparation, K.W., S.S.-W., M.K., A.L.; supervision, A.L. All authors have read and ´ agreed to the published version of the manuscript.

**Funding:** This research was funded by BMN grant number 539-O160-B432-20 and NCN PRELUDIUM 17 (UMO-2019/33/N/ST10/00585).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data is contained within the article or supplementary material.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

*Article*


*2.1. Gum Extraction*

Gums were extracted from cold-pressed oil by-products (chia seed, flaxseed, and rocket seed) according to the procedure described by Naji-Tabasi et al. [19]. The gums were removed from the by-products by soaking with water followed by ethanol precipitation. Five hundred by-products are weighed and added to 10 L of distilled water and mixed with a magnetic heated stirrer at 80 ◦C for 2 h to obtain gel structures that come out of the byproducts. The extracted gum solution from the byproducts was passed through to the sieve and then purified by mixing with three volumes of 96% ethanol to precipitate gum and left in the oven at 30 ◦C for 1 day to dry. The seed gums are dried, packaged at 4 ◦C, and stored in dry conditions.


*Article* **Public Voice via Social Media: Role in Cooperative Governance during Public Health Emergency**

#### **Yang Yang and Yingying Su \***

School of Management, Harbin Institute of Technology, Harbin 150001, China<EMAIL_ADDRESS>**\*** Correspondence<EMAIL_ADDRESS>Tel.: +86-188-4558-5002

Received: 31 July 2020; Accepted: 16 September 2020; Published: 18 September 2020

**Abstract:** With the development of the Internet, social networking sites have empowered the public to directly express their views about social issues and hence contribute to social change. As a new type of voice behavior, public voice on social media has aroused wide concern among scholars. However, why public voice is expressed and how it influences social development and betterment in times of public health emergencies remains unstudied. A key point is whether governments can take e ffective countermeasures when faced with public health emergencies. In such situation, public voice is of great significance in the formulation and implementation of coping policies. This qualitive study uses China's Health Code policy under COVID-19 to explore why the public performs voice behavior on social media and how this influences policy evolution and product innovation through cooperative governance. A stimulus-cognition-emotion-behavior model is established to explain public voice, indicating that it is influenced by cognitive processes and public emotions under policy stimulus. What is more, as a form of public participation in cooperative governance, public voice plays a significant role in promoting policy evolution and product innovation, and represents a useful form of cooperation with governments and enterprises to jointly maintain social stability under public health emergencies

**Keywords:** public voice; public health emergency; social media; policy evolution; product innovation; cooperative governance