Characterization of size segregated fungal bioaerosols in and around a Sugar Mill of Western Uttar Pradesh, India

doi:10.21203/rs.3.rs-2407544/v1

Suspended particles of biological origin that comprising of virus, animal debris, fungal spores known as bioaerosols have become a major concern in the past decades. The present study reports the concentration and size distribution of fungal bioaerosol in around a sugar mill situated in the Muzaffarnagar region of Uttar Pradesh, India. The sampling was performed in the winter months when the mill used to be operational mode. The highest mean fungal concentration was observed at the cutter site (4022 ± 321 cfu/m³) and lowest at storage site (832 ± 85 cfu/m³). The maximum and minimum concentration of fungal bioaerosol was observed during January (3090 ± 174 cfu/m³⁾ and March (629 ± 69 cfu/m³) respectively. During the entire sampling period the fine fraction of fungal bioaerosol was observed to be significantly high at all the sites, whereas coarse fraction was lower. The association between fine and coarse fractions of bioaerosols showed a very strong positive relationship. The levels of fungal bioaerosol and their association with the meteorological parameters in sugar mill were also conducted. A positive association with the relative humidity and wind speed were observed at significant level p<0.05 whereas a negative relation was observed with temperature at p < 0.05. The lifetime average daily dose was calculated for both inhalation and dermal, among them LADD_inhalation is ~5 times over LADD_dermal. The health risk index was observed as <1 for both inhalation and dermal route whereas HI_inhalation value was 10⁵ times higher than the HI_dermal value. The dominant fungus found in the air of examined dwellings was Penicillium spp., Aspergillus spp., Cladosporium spp., and Alternaria spp., which occurred predominantly at all the sites during the months of the sampling period.

Bioaerosol

Sugar mill

Coarse-fine size

Fungi

Air pollution is a known cause of respiratory and other multiple adverse health diseases. Atmospheric Particulate Matters (PM_2.5, PM₁₀) are typically known as an indicator of air pollution worldwide (WHO, 2005). In India, the number of deaths counted 1.67 million ascribed to air pollution in the year 2019 (Pandey et al., 2021). The inhalable fraction of particulate matter, especially fine (PM_2.5) considered as one of the most air quality degrading pollutants (Hosseini et al., 2021). An added hazard of particulate pollution can be related to a microbial fractions which are highly variable, complex and contributes (25% - 30%) to the mass fraction of particulate matter (Gupta et al., 2021; Hosseini et al., 2021). The suspended particles of biological origin that comprise a living organism (bacteria, fungi, and viruses) or derived from a living organism (cell fragments, pollen, etc.) are commonly known as bioaerosols (Ghosh et al., 2013; Srivastava et al., 2021). They can be of natural origin, including organic dust, bacteria, dust-mite, insect parts, or their derived metabolites like endotoxins, mycotoxins, etc. Whereas the anthropogenic origin may be due to air conditioning equipment, driers, humidifiers, etc. (Jones & Harrison, 2004).

Bioaerosols vary in size range from ~ 0.05 to 100 microns (Ferguson et al., 2021). The resuspension, spreading, and settling depend upon the size range of airborne microorganisms (Nasir et al., 2012; Aggarwal et al., 2016). Various climatic factors viz; relative humidity, temperature, wind speed, and direction (Jones & Harrison, 2004) and solar radiations (Aggarwal et al., 2016), may affect the concentration of the bioaerosol in a particular environment. Further, adequate air exchange rate (Soleimani et al., 2016), presence of moisture content in building material (Foarde et al., 1993), and anthropogenic activities (Abdel Hameed et al., 2009), are equally important and may significantly impact the composition of bioaerosol concentration. Among the microorganisms, the varieties of airborne fungi are widely distributed in nature and nearby 10% of the people have shown allergic response to fungi (Pasanen et al., 1996; Nayak et al.,1998). Fungal spores are 100 to 1000 times more than other bioaerosols (Araujo and Cabral, 2010) and the size range of fungal spores typically varies from 0.25 to 8 micron (Jones & Harrison, 2004; Soleimani et al., 2016), which contribute nearly 2 to 5 % of PM₁₀ (Srivastava et al.., 2021).

The different type and number of airborne fungal bioaerosol of a region vary as per the locally present sources, change in seasons, time of the day, the vegetation and seasonal crops that provides the compost material which favors the abundant growth of fungi in the atmosphere irrespective of the human interferences (Nayak et al., 1998; Nasir et al., 2012). The concentration and exposure duration may cause a serious range of allergic diseases related to the skin, eyes, ears, gastrointestinal tract and respiratory system (Faridi et al., 2016; Sandeep et al., 2020). Such incidences are more prominent in industrial areas than residential and commercial areas (Kumar et al.,2021). For instance, the inhalation of industrial and agricultural specks of dust is considered as the principal cause of respiratory allergy in occupational areas (Dutkiewicz, 2011).

Industrialization is viewed as the foundation of advancement procedures because of its significant contribution to the socio-economic development (Poddar et al., 2017). India is the leading developing country in terms of industrialization in different sectors and has been considered the first or original home of sugarcane and sugar. Sugar mills are primarily situated in the rural areas that give approx. 0.5 million employment and involves 6 million sugarcane farmers in sugarcane cultivation and harvesting activities (Solomon, 2014). India ranks second after Brazil and occupies a major cane area of 4.39 million hectares with over 300 million tons of sugarcane production annually (Felix et al., 2021). After textiles, India's second biggest agro-based industry is the sugar industry, with a noteworthy contribution to the rural economy (Felix et al., 2021). In India over 500 sugar mills are in operation which involves different management structures and owners (private, public, and cooperative) (ISMA, 2021). The state of Uttar Pradesh (UP) and Maharashtra account for ~60% of India's total production of sugar and western region of UP is a major producer of sugarcane (Solomon, 2011).

The rural population directly or indirectly involved in the sugar industries are exposed to significant amount of pollution generated within and around the mills. Besides, many studies have been conducted on fungal bioaerosol emission from landfill sites (Srivastava et al., 2021), academic institution (Gupta et al., 2021), waste paper and cardboard recycling industries (Baghani et al., 2021), Museum (Awad et al., 2019), sewage treatment plants (Maharia et al., 2015), coir factory (Nayar et al., 2007), sawmill (Jothish and Nayar, 2004), whereas no such studies have been carried out on sugar mill. By considering the lacunae of the bioaerosol data from the sugar mill, the study was designed to assess the fungal bioaerosol concentration in different sites, determining the effects of meteorological factors and assessment of health hazards associated with the exposed workers within the mill.

2.1. Study area

The present investigation was done at a sugar mill located (29.47° N, 77.70° E) in the western Uttar Pradesh region of India that is also Known as Harit Pradesh (Green Belt). The zone is famous for its sugarcane-based agriculture which occupies 70-75% area of this district. Owing to the distinctive cropping pattern, the region is considered as the largest sugar-producing state of India, which is why the region is known as the "Sugar-bowl of India" (Verma et al., 2021). Sampling was carried in Mansurpur which is situated in the rich belt of cane and thus sufficient cane is available for crushing (Umar et al., 2006). The total population of western Uttar Pradesh is more than 71 million (Census of India, 2011). The region enjoys a sub-tropical climate with moderately cold winters and very hot summer. Average temperature varies from 1 to 4° C in January and 43 to 47° C during May (Umar et al., 2006).

2.2. Description of the sampling sites

The sampling was conducted at seven various sites in and around the sugar mill, located in the Muzaffarnagar district of Western Uttar Pradesh. The sugar mill was established in 1985 and began its operations with a crushing capacity of 8000 Metric tons of cane per day. The area of the mill is 14.5 hectares and is surrounded by agricultural lands, residential areas, and a marketplace. Around 625 workers and 34000 families are associated with this sugar mill. The sampling sites are illustrated in Figure 1. Among total seven sites, five indoor sites were selected considering the probability of occurrence of bioaerosols in comparatively high concentration. The selected sites were processing unit (i.e., crushing, mill, bagasse), heavy working sites (i.e., packing and storage). The other two sites market and residential were in the close vicinity of the sugar mill.

2.3. Bioaerosol sampling methodology

Fungal bioaerosol sampling at different sites was carried out from December 2019 to March 2020 using Anderson's six-stage cascade impactor, manufactured by Tisch Environment USA. The different size fractions simulate the deposition pattern in various part of the human respiratory system. The six-stages of the sampler was clubbed and further divided into coarse and fine size particles, stages 1-3 and stages 4-6 were clubbed as coarse and fine size particles respectively. The sampling period was selected as to fall during the operative phase of the mill. Samples were taken from each site for 2 minutes at a prescribed flow rate of 28.3 L/min. This time is considerably standardized time to acquire the required number of colony-forming units. The sampler was operated at respirable height of 1-2 meters above the floor to simulate the location of the breathing zone in humans (Huang, 2002). A total of 504 plates of different sized fungal bioaerosols were obtained. In addition, the meteorological parameters were monitored using Envirometer at different sites.

2.4. Culture media

Fungal bioaerosols were collected over Petri plates (90 mm) containing sterile media of Rose Bengal Chloramphenicol Agar (RBCA) for detection and enumeration. In air sampling, RBCA is more suitable for both, counts and the number of mold genera (Mentese et al., 2017). In addition, Potato Dextrose Agar, media was utilized for the isolation of some selected fungi that helps in identifying a macroscopic view more specifically.

2.5. Bioaerosol characterization

In the present study, the exposed Petri plates were subsequently incubated in an inverted position for 5-6 days at 25⁰C with regular monitoring for the fast-growing fungal colonies. After the desired duration of agar incubation, various macroscopically visible growth of microorganisms on a solid culture medium counted as a number of colonies. The number of colonies also called as Colony forming unit (CFU). CFU is typically known as the number of microorganisms that can replicate to form colonies. Finally, bioaerosol concentration in terms of cfu/m³was estimated using the following formula (Wang et al., 2018). The images of the Petri plates showing PDA isolates are given in Supplementary Figure S1.

Where, Flow rate = 28.3 liter/min = 0.0283 m³/min

2.6. Identification of culturable bioaerosol

The fungal identification was accomplished with the help of a light microscope. All fungal spores from exposed slides were examined, and identified with a magnification of 40X and 100X. Firstly, a tiny portion of the fungal colony was picked from the isolated Petri plates with the assistance of a sterilized inoculum loop and put onto a slide that contains 4% of NaCl. A small drop of lactophenol cotton blue stain was added instantly and left for 1-2 min. Finally, the examining area was covered with a sterile coverslip (Jothish & Nayar, 2004; Lal et al., 2017). Identification was based on visual interpretations of typical morphological characters. Such as by comparing the fungal spores of the sample with the existing literature, accessible pictures on the internet and published papers (Maharia & Srivastava, 2014).

2.7. Health Risk Assessment

To assess the health risk, Lifetime Average Daily Dose (LADDs) was calculated using the documented methods of the United States Environmental Protection Agency (U.S.EPA, 2011). As per the observed concentration at the sugar mill site, exposure of the workers via dermal contact (through the skin), and inhalation was calculated using following equations:

LADD _inhalation = (C × IR × ET × EF)/ (AT × BW_t) …………………………........…...Eq. (i)

LADD_dermal = (C × ESA× SAF × DAF× ET × EF)/ (AT × BW_t) ….…………………. Eq. (ii)

C is the concentration at exposure (cfu/m³), IR shows the rate of inhalation as 19.02 (m³ day^-1) (Li et al., 2013), ET represents exposure time (year) considered as 15 years for this study following earlier studies carried out by Masih et al. 2017 and USEPA, 2011. EF represents exposure frequency (days year^-1) which is equivalent to 300 days after deducting mill off days and official leave days (USEPA, 2011), AT is an average lifetime (year) and calculated as 70 x 365 days and BW_t is the body weight in kg. In Equation (ii), ESA means exposed skin area as 0.215 (m²) (Li et al., 2013), SAF is the skin adherence factor equivalent to 0.07 (kg (m³.d)^-1) (Li et al., 2013), and DAF signifies dermal absorption factor considered as 0.001 (Li et al., 2013).

To understand the non-carcinogenic health risk, hazard quotient (HQ) was calculated as the ratio of lifetime average daily dose (LADD_inhalation or LADD_dermal) cfu (kg d)^-1 to the reference dose for chronic exposure (RfD) cfu (kg d)^-1 (Baghani et al., 2020).

3.1. Fungal bioaerosol concentrations

The mean concentration and variation of fungal bioaerosol at various sampling sites in the Mansurpur sugar mill is provided in Figure 2. The highest mean fungal concentration was observed at the cutter site (4022 ± 321 cfu/m³), followed by the bagasse (2026 ± 157 cfu/m³) and mill sites (1897± 152 cfu/m³). At packing, market, and residential sites, obtained concentrations were 1116 ± 117, 1411 ± 125, and 1313 ± 115 cfu/m³respectively. Whereas the lowest mean fungal concentration was observed at the storage site, i.e., 832 ± 85 cfu/m³^,during the sampling period. Additionally, the cutter site contributed 1.12, 0.99, 2.60, 3.83, 1.85, and 2.06 times more load to the fungal bioaerosol as compared with that of the mill, bagasse, packing, storage, market, and residential sites, respectively.

One of the reasons for maximum concentration at cutter site could be due to fact that it is crowded with humans, tractors, bullock carts, etc. They usually keep standing in queue to unload their sugarcane. Pushing tons of sugarcane could increase the emission of bioaerosol at this site. Furthermore, the persistent human activity that releases the enormous number of microbes along with organic droplets while talking, wheezing, and coughing, possess protection to the microbes present in the air and enhance their survival at that particular site for a longer duration (Balyan et al., 2020). Additionally, at the mill site, the high concentration could be due to the presence of huge installed machines, conveyor belts, rake carrier (carrying fiberized sugarcane) and tunnels, which might have influenced/enhanced the fungal concentration. Whereas, the high bioaerosol concentration at the bagasse site is likely due to the generation of a huge amount of bagasse, i.e., 2320 tons per day or 97 tons per hour. This site consists of dry fibrous organic waste material from the sugarcane and decomposed organic litter that may act as a host for various pathogenic fungal bioaerosol. The previous studies conducted at different sites have reported the availability of nutrients and other environmental factors that affect the growth of fungi (Balyan et al., 2019). The low fungal bioaerosol loading at the storage site (where 10,000 Tons of sugar bags are stored) could be on account of a clean, open, and wide area. This site includes an active ventilation system. The past study reveals that the availability of a proper ventilation system provides an adequate amount of air exchange and is reason for the low bioaerosol concentration (Faridi et al., 2015).

3.2. Variation of fungal bioaerosol during the study period

Spatial variation of fungal bioaerosol concentration over the different months at various sampling sites is given in Figure 3.The obtained concentrations were high in January and low in March month at all the sampling sites. The maximum fungal bioaerosol concentration was observed at the cutter site (6834 ± 241 cfu/m³), followed by the mill (3918 ± 189 cfu/m³), and bagasse sites (3365 ± 185 cfu/m³). Whereas the minimum concentration was obtained during March month at the residential site (333 ± 39 cfu/m³). A low concentration was observed at the storage site during all the months. The spatial variation of fungal bioaerosol concentration levels were in following order: Cutter Site > Mill Site > Bagasse Site > Residential Site > Market Site > Packing Site > Storage Site. Further, the cutter site, which is highly polluted, contributes 2.19 times more than the less polluted site, such as the storage site. The detail of the monthly mean concentration of fungal bioaerosol at all the seven sites is listed in Table 1.

As, winter season is categorized by low temperatures, moderate relative humidity, less rainfall (Nayak et al., 1998), and usually lowest mixing height which favors the agglomeration of suspended particles present in the ambient air and thus the higher fungal load (Lal et al., 2017; Jothish & Nayar, 2004). Further, the absence of rain washout due to less rainfall throughout the winter months intensifies the growth of fungi (Nayak et al., 1998). The above-mentioned reasons might be the cause of the higher number of fungal bioaerosol concentrations at all the sampling sites during January month. The present study’s results are similar to the work performed by Agarwal et al. 2016, Huang et al. 2002 and Wu et al. 2000,according to the reported data, the highest fungal bioaerosol concentrations were observed during the winter season, while a study carried out at the historical museum, Egyptby Awad et al. 2020reported a high concentration of fungal bioaerosol during summer and lowest in fall. Another study was done in a largely industrialized region of Iran reported that maximum fungal microorganisms occurred in June and lowest during March month (Hosseini et al., 2021). Hence, geographical, meteorological, and other favourable conditions of a specific location promote the survival and growth of microbial organisms suspended in the air (Srivastava et al., 2021; Awad et al., 2020).

In addition, the concentration observed during January month is 5 times more than that of March month. The present study revealed that the highest fungal concentrations at all the sites were observed in January and February month which is in close proximity with the results of the previous study conducted in a coir, sawmill, chlor-alkali and flour mill, that had obtained the maximum spore count in winter months due to low rainfall, moderate temperature, and relatively high humidity, favouring fungal sporulation (Nayar et al., 2007; Jothish & Nayar, 2004; Nayak et al., 1998; Misra and Jamil, 1991). In this study, the meteorological parameters, suitable growth substrate, and crushed sugarcane, especially at the cutter site might have provided the growth of fungi.

3.3. Distribution of size-segregated fungal bioaerosol concentration

The bioaerosol stages are divided into two broad categories, fine (3.3 to < 0.65 microns (stage 4-6)) and coarse (3.3 to >7 micron (stage 1-3)) bioaerosols. The idea was basically to understand the variation (monthly and spatial) of bioaerosol that may perhaps differ on changing the size range. Figure 4 and Figure 5reveal that the maximum concentration of fungal bioaerosol was still high in January month at site 1 (Cutter), followed by site 2 (Mill) and site 3 (Bagasse). Further, minimum concentrations in all months were observed at site 5 (storage) and site 7 (residential) during March for both fine and coarse size fractions. Hence, the site didn't play any major role in the distribution of size segregated fungal bioaerosol.

To understand the dependence of fine and coarse size fungal bioaerosol with each other, regression analyses were carried out for each month. Considering fine as an independent and coarse as a dependent variable. Regression analyses results illustrate that fine bioaerosol controls the variation of coarse bioaerosol as shown in Supplementary Figure S2. It may be observed from the plots that there is a good regression between fine and coarse size, in all four months at a level of significance p ≤ 0.05. The R²and p values are 0.8029 and 0.0063, 0.9587 and 0.0001, 0.845 and 0.0034 and, 0.6779 and 0.0228 for December, January, February, and March months respectively.

3.4. Statistical analysis of fungal bioaerosol

In the present work, the box plot has also been plotted as box plot in (Figure 6)represents the fungal bioaerosol concentration (cfu/m³) at various sampling sites. Further, the Fligner- Killeen test was performed to test the homogeneity of variances that showed a chi-square value of 17.739, and p-value of 0.006918, a significant difference was observed in the variance of all sampling sites (p < 0.05). Kruskal Wallis test was also performed for fungal bioaerosol concentrations at various sampling sites, which showed the statistic value of the chi-square test as 8.0172. However, the obtained p values (p = 0.2368) were not significant. Hence, no multivariate analysis was performed. Thus, Parametric One-Way ANOVA (Analysis of Variance) tests were applied for further analysis, followed by Tukey's multiple comparison test (Tukey's HSD) in order to acquire the comparative analysis of the fungal mean concentration in various sampling sites. One-Way ANOVA was carried out for fungal bioaerosol concentration, which showed a p-value of 0.0098 as provided in Supplementary Table S1. A significant difference was seen in the mean fungal bioaerosol concentration between other sampling sites at p < 0.05.

Thebox plot (Figure 7)represents the fungal concentration (cfu/m³) in different months. The Fligner- Killeen test was done to test the homogeneity of variances which represents a chi-square test statistic as 6.4232, and a p-value as p = 0.09274. Additionally, the Kruskal Wallis test was performed on fungal bioaerosol concentration in different sampling months, and the results of the test showed a chi-squared test statistic as 15.473, which was found to be significant at p = 0.001454 (p < 0.05). Therefore, Parametric One-Way ANOVA tests were applied for further analysis, followed by Tukey's multiple comparison test (Tukey's HSD) to compare the mean concentration of fungal bioaerosol in various sampling months. The result of the One-Way ANOVA test, showed a p-value of 0.006665 for fungal bioaerosol concentration has been shown in Supplementary Table S2. A significant difference was observed between the mean fungal bioaerosol concentration and different sampling months at p < 0.05. The outliers can be explained owing to the presence of relatively high relative humidity and low temperature throughout the sampling period at the cutter site which favours the growth of fungi with respect to other sites. As far as concentration relation with meteorological parameters is concerned, it may be noted that sites (cutter, mill, and bagasse) with higher relative humidity (as shown in Table 2) have more fungal bioaerosol concentration. Conversely, storage sites that have the minimum concentration with lowest level relative humidity amongst all. In an earlier study carried out by Baghani et al. 2020 similar results were found.

3.5. Inter-relationship between fungal bioaerosol concentration and meteorological parameters

Microclimatic conditions widely vary at different sites. The presence or absence of a ventilation system, i.e., the number of windows and doors, may affect bioaerosol load at a particular site. In the present study, the lowest temperature and high relative humidity were both associated with the cutter site, i.e., 19 ± 5 °C and 73 ± 21%, respectively, as compared to other sites. To validate whether there is any significant relationship among the meteorological parameters with the mean fungal bioaerosol concentration (cfu/m³), the Pearson correlation coefficient (r) test was performed. The p-value was calculated, and the correlation between the mean fungal bioaerosol concentration (cfu/m³), and wind speed (m/s), relative humidity (%), and temperature (°C) were estimated at the significance level of p < 0.05 for the sampling period. The results analyzed indicated that wind speed (m/s) and the concentration of fungal bioaerosol are positively correlated at p < 0.05 (p = 0.003 and r = 0.921). Additionally, the results of correlation analysis calculated for relative humidity (%) and concentration of fungal bioaerosol showed a positive correlation at p < 0.05 (p = 0.004 and r = 0.912) whereas a negative correlation for temperature was observed at p < 0.05 (p = 0.002 and r = - 0.927). This suggests that all the meteorological factors are significantly related to airborne fungi and play a major role in their occurrence and sustenance.

According to Awad et al., 2019, the interaction between daily variation in temperature, relative humidity, sunlight, wind speed, air stream passage, geographical factors and anthropogenic activities may synergistically affect fungal bioaerosol concentration over a particular location. Low temperature and relatively high relative humidity appear to favour the growth of fungal bioaerosol. Our result conforms with the reports of similar strong correlations between various meteorological parameters and concentrations of fungal bioaerosol, which includes relative humidity and temperature in a cardboard and waste paper recycling factory in Iran (Baghani et al., 2020). It is also in close similarity with some other works, done by Awad et al. 2019 on indoor fungal pollution in a historical museum in Egypt, Patil and Kakde in 2017 on a landfill site in Mumbai as well as on landfill site in Barranquilla by Gamero et al. in 2018. Whereas, a study conducted at various sites in Delhi (Lal et al., 2017) reported no consequent association between relative humidity and temperature with fungal bioaerosol.

3.6. Correlation matrix between different stages

Correlation matrix of fungal bioaerosol concentration was developed to test the degree of association between different stages during the sampling period. The p-value was calculated, and the significance level was set at p < 0.01 and p < 0.05. The results were analyzed using a 2-tailed test. Table 2 shows the strong correlation between different stages of fungal bioaerosol with each other, where color codes varying from yellow to dark green represent a strong correlation. The strong relationship between different stages means that change in fungal bioaerosol concentration in one stage is strongly correlated with the changes in the fungal bioaerosol concentration in other stages.

Therefore, in accordance with statistics, all the stages are significantly correlated with each other, except stage 6, which is not significantly correlated with other stages. Table 2 showed thata strong correlation exists between different stages during the sampling period. The correlation and r values between the stages are as follows: stage 1 and 2 (r = 0.953); stage 1 and 3 (r = 0.912); stage 1 and 5 (r = 0.937); stage 4 and 5 (r = 0.900), whereas good correlation exists among stage 1 and 4 (r = 0.811); stage 2 and 5 (r = 0.818); stage 2 and 4 (r = 0.875); stage 2 and 3 (r = 0.863); stage 3 and 4 (r = 0.894); and lastly, stage 5 and 6 (r = 0.849). Hence, a conclusion can be drawn from the correlations as mentioned above that stage 1 has the maximum number of correlations with other stages followed by stages 2, 3, and 4. However, in contrast to this, stages 5 and 6 do not have a significant correlation with other stages. The possible reason for such a correlation pattern might be due to the fact that the spores of fungi are mostly kept attached with various size fractions of particulate matter. Thereby, they stay separated as per their size fraction in various stages of the air sampler. The present study confers that the most dominant spores of fungi exist in size range varying from stages 1 to 5, and a low concentration of spores was detected in stage 6.

This goes well with the fungal bioaerosol study conducted by Maharia and Srivastava, 2015 and Kumar et al. 2021 that reported a similar correlation and distribution of fungal bioaerosol in the range of stages 1 to 5.

3.7. Health risk assessment

The risk to human health owing to the exposure of fungal bioaerosol generated in and around the sugar mill was evaluated as per the USEPA guidelines. The calculations were performed using the mean fungal bioaerosol concentration during the sampling period. The health index (HI) for HI_inhalation and HI_dermal values were calculated as 4.83 x 10^-12 and 3.82 x 10^-7, respectively. Further, the observed HI_inhalation value was 10⁵ higher than that of the HI_dermal value. The higher HI_inhalation indicated that the primary route of bioaerosols intake by workers was through the inhalation route. The findings of some other works are similar to the present work. For instance, the study conducted by Li et al. 2013 and Wang et al. 2018 at the wastewater treatment plant in Xi'an and Tianjin, China, respectively, observed that on-site workers are mainly exposed through inhalation. However, the present study results are inconsistent with the study conducted at the irrigation of municipal wastewater site (Carlander et al., 2009). According to their results, ingestion plays a crucial and predominant role when compared to another exposure pathways. The comparison of findings of this study with the other carried out studies representing Mean Health Quotient (HQ) for dermal and inhalation are shown in Table 3.

It was also found that the lifetime average daily dose (LADD_dermal) was highest at the cutter site (1.52 x 10^-4cfu (kg d)^-1), whereas lowest at the storage site (3.15 x 10^-5 cfu (kg d)^-1). Furthermore, the maximum exposure due to lifetime average daily dose (LADD_inhalation) was observed at the cutter site (192.482 cfu (kg d)^-1) and minimum at the storage site (39.827 cfu (kg d)^-1). Thus, it can be the inference that LADD_inhalation is ~5 times over LADD_dermal. As shown in Figure S3 and S4,the trend of both LADD_dermal and LADD_inhalation values for the sampling sites are as follows: Cutter site > Bagasse site > Mill site > Market site > Residential site > Packing site > Storage site.

According to the previous studies, HI >1 or HQ>1, indicate the potential risk or harmful health effects such as carcinogenic effects. While, HI <1 or HQ <1, suggests acceptable hazard risk levels such as non-carcinogenic effects, which are not of great concern since the dose level is lesser than the reference dose (RfD) (Dehghani et al., 2018; Baghani et al., 2020; USEPA, 2011b, Deng et al., 2014).In the present study, both HQ and HI calculated were observed to be less than unity (HQ and H >1), which suggests an "acceptable hazard risk level".

The risk assessment carried out at the sugar mill provides a valuable perspective in order to understand the potential risks of bioaerosol emitted from the sugar mill. Although the calculation of risk indices is based on the absolute data, there could be a possibility that present results might underestimate the risk of the workers. However, the significant exposure time for a longer duration, less awareness about safety measures and improper food nutrition may develop various visible health symptoms among workers.

Lastly, the "Heat Map" was also generated to represent the variation of extent of health risk quotient factor related to fungal bioaerosol at different sampling sites during the whole sampling period. It is illustrated in Figure 8. The color code expressed the extent of risk exposure as the red color shows a prominent and maximum index, whereas the green color shows fewer prevailing effects. This includes lifetime exposure of fungal bioaerosol through LADD_inhalation + LADD_dermalpathways. The different colors were generated on the basis of the observed Z-score of the fungal bioaerosols at different sampling sites in the mill among all the sampling periods.

3.8. Fungal identification

Total 8 airborne fungal species from sampled bioaerosol were identified from all the sites of sugar mill during the sampling period. They are given in supplementary Table S3. Cladosporium one of the genera found is commonly observed in food products and dead plants. It may easily grow in cold weather conditions and damped areas. It is mostly known to cause asthma and allergic reactions in human beings. Cladosporium genera also secrete secondary metabolites, i.e., mycotoxins. Emodin and Cladosporin are the most common among all the types of secreted mycotoxin by Cladosporium species. The most common infections caused by Cladosporium species in humans are chromoblastomycosis which is a chronic infection of the skin and subcutaneous tissue i.e., the deepest layer of the skin (Ogórek et al., 2012).

Further, Aspergillus niger is a common fungus known to produce aflatoxins which is a classic mycotoxin example. It is known as highly toxic to many animals and humans. In humans, ingestion of aflatoxin has been associated with liver cancer along with Hepatitis B as a risk factor, and inhalation causes lung cancer and other lung-related diseases (Diba et al., 2007). Penicillium is predominantly found in food, grains, soil, indoor house dust, and damped buildings.Previous studies reported that numerous hypersensitivity pneumonitis epidemics are caused by Penicillium species (Larone et al., 1995). Aspergillus oryzae does not produce aflatoxins or any other toxic metabolites (Gomi, 2014). Fusarium causes keratomycosis (infection of the cornea) (Balajee et al., 2009). Rhizopus is an agent of mucormycosis that includes rhinocerebral mucormycosis, gastrointestinal, mucocutaneous, pulmonary & disseminated infections in immunocompetent patients (Hoog et al., 2000). Curvularia has been widely known to cause allergic fungal sinusitis (Hoog et al., 2000). Trichoderma inhalation causes lung infection, allergic reactions and asthma (Misra and Jamil, 1991). Alternaria infects crops worldwide and have been known to cause allergic rhinitis when inhaled (Thomma et al., 2003).

Penicillium, Alternaria and Aspergillus were the most abundant inside the sugar mill, whereas the Cladosporium was found outdoor. The presence of Penicillium, Aspergillus, and Cladosporium, in abundance, indicates an allergic environment for humans.

The present study was carried out to evaluate the size segregated fungal bioaerosol concentrations and associated health risks among the workers of the sugar mill in the Muzaffarnagar district of Western Uttar Pradesh. The mean fungal bioaerosol concentration varied significantly across the different months, highest was in January and lowest in the month of March. In addition to the sugar mill activities (unloading, cutter, processing, packing and storage), inhabitants and meteorological parameters (such as relative humidity, wind speed and temperature), influenced the bioaerosol emissions. The presence of significantly high bioaerosol concentration was observed at the cutter site throughout the sampling period. Furthermore, maximum and minimum bioaerosol concentrations were observed in January and March month at the sugar mill site, respectively. The dominant size range of fungal bioaerosol concentration was observed in stages 4 which is having the cut-off diameter of 2.1–3.3 µm, synonyms to the secondary bronchi of the human respiratory system. It indicates that the health of sugar mill workers who stayed inside the mill for a prolonged time might be at high risk. The HQ and HI were both observed to be less than 1, which indicates an acceptable hazard level. Nevertheless, the present study highlights the importance of reducing the fungal bioaerosol emission in the sugar mill by improving the ventilation system, usage of N95 masks, gloves, and other safety objects are advisable to reduce risk levels. Eight fungal genera were identified from the sugar mill site. Out of them, one was harmless, while three and five were immunotoxic and allergic, respectively. Penicillium, Aspergillus, Fusarium, Alternaria and Cladosporium were observed to be most abundant at all the sampling sites. Thus, the present study suggests that appropriate training and awareness campaigns, routine/regular monitoring for the presence of bioaerosol load in the mill region considering human dwellers as more sensitive to the areas are highly recommended.

Acknowledgement

Author are thankful to IARI- IIFSR and to Mr. Sarad Raz Khan, Quality control (Head of the Department) of the sugar mill, who helped unconditionally throughout the whole field study.

Conflict of interest

Authors declared that there is no conflict of interest.

Funding Declaration

No funding was received to support the present work

Author Contribution

ST collected the data and wrote major portions of the manuscript
AS helped in data collection and writing the manuscript

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Table 1. The monthly mean value of various air parameters over sampling site (Avg. ± SD)

Sampling sites	Parameters	December (n=3)	January (n=3)	February (n=3)	March (n=3)
Site 1	Fungi (cfu/m³)	2628 ± 112	6834 ± 241	5398 ± 845	1229 ± 85
	Temp (°C)	15	13.3	22	24.1
	RH (%)	89	90	68	46
	Ws (m/s)	1.89	2.5	3.05	1.9
Site 2	Fungi (cfu/m³)	1079 ± 87	3918 ± 189	2156 ± 278	436 ± 52
	Temp (°C)	16.2	14.9	24	26.2
	RH (%)	66	81	58	33
	Ws (m/s)	0.8	1.5	0.56	0.4
Site 3	Fungi (cfu/m³)	1053 ± 118	3365 ± 185	3073 ± 232	614 ± 91
	Temp (°C)	16.8	15.3	23.2	24.7
	RH (%)	80	72	82	36
	Ws (m/s)	0.98	1.2	1.77	0.8
Site 4	Fungi (cfu/m³)	913 ± 190	1732 ± 107	1016 ± 92	802 ± 80
	Temp (°C)	18.4	17.1	24.5	25.7
	RH (%)	51	60	46	40
	Ws (m/s)	0.11	0.1	0.25	0.33
Site 5	Fungi (cfu/m³)	641 ± 67	1092 ± 102	989 ± 106	607 ± 63
	Temp (°C)	19.7	17.9	25.8	26.7
	RH (%)	49	57	36	38
	Ws (m/s)	0.33	0.25	0.33	1.1
Site 6	Fungi (cfu/m³)	1564 ± 170	2063 ± 172	1636 ± 88	380 ± 71
	Temp (°C)	15.7	16.3	24.3	27.7
	RH (%)	75	64	40	28
	Ws (m/s)	1	0.9	1.2	1.6
Site 7	Fungi (cfu/m³)	338 ± 54	2624 ± 221	1959 ± 145	333 ± 39
	Temp (°C)	19.8	16.5	23.8	28.2
	RH (%)	45	68	58	30
	Ws (m/s)	0.23	1.1	1.88	0.34

Site 1: Cutter, Site 2: Mill, Site 3: Bagasse, Site 4: Packing, Site 5: Storage, Site 6: Market, Site 7: Residential

Table 2. Correlation matrix between different stages for fungal bioaerosol. **Significant correlation at p < 0.01, i.e., 99% and *Significant correlation at p < 0.05, i.e., 95%

Table 3. The Comparison of findings of Mean HQ_dermal and Mean HQ_inhalaion of this study and other related studies.

Sampling Sites	Mean HQ_dermal	Mean HQ_inhalaion	References
Tehran, Iran^a	6.93 x 10^-9	7.24 x 10^-3	Baghani et al., 2020
Xi`an, China^b	1.22 x 10^-7 – 1.21 x 10^-11	1.08 x 10^-3 – 6.37 x 10^-7	Li et al., 2013
Tianjin, China^c	72.91 x 10^-4 – 13.73 x 10^-4	72.91 x 10^-4 – 13.73 x 10^-4	Wang et al., 2018
Taranto, Italy^d	1.672 x 10^-8	5.123 x 10^-5	Cangialosi et al., 2008
Present study^e	3.82 x 10 ^-7	4.83 x 10 ^-6	This study

HQ: Hazard Quotient

a: Waste Paper and Cardboard Recycling Factory (Tehran), Iran

b: Wastewater of Treatment Plant of Xi'an, China

c: Wastewater Treatment Plant, Tianjin, China

d: Municipal Solid Waste Incineration Plant (MSWIP), Taranto, Italy

e: This study

Supplementary Figures S1-S2 are not available with this version

Supplementary Tables S1-S3 are not available with this version

No competing interests reported.

Characterization of size segregated fungal bioaerosols in and around a Sugar Mill of Western Uttar Pradesh, India

Status:

Journal Publication

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Abstract

Figures

Introduction

Materials And Methods

2.1. Study area

2.2. Description of the sampling sites

2.3. Bioaerosol sampling methodology

2.4. Culture media

2.5. Bioaerosol characterization

Results And Discussions

3.1. Fungal bioaerosol concentrations

3.2. Variation of fungal bioaerosol during the study period

3.3. Distribution of size-segregated fungal bioaerosol concentration

3.5. Inter-relationship between fungal bioaerosol concentration and meteorological parameters

3.7. Health risk assessment

Conclusions

Declarations

References

Tables

Supplementary Figures

Supplementary Tables

Additional Declarations

Status:

Journal Publication

Version 1