Prevalence, Dispersion and Nature of Bioaerosols over a Solid Landfill Site in Central India

Received: February 12, 2023
Revised: April 29, 2023
Accepted: May 8, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Cite this article:

Bhoyar, P.D., Kamdi, P., Bafana, A., Devara, P.C.S., Sivanesan, S., Kumar, A., Krishnamurthi, K. (2023). Prevalence, Dispersion and Nature of Bioaerosols over a Solid Landfill Site in Central India. Aerosol Air Qual. Res. 23, 220431. https://doi.org/10.4209/aaqr.220431

HIGHLIGHTS

• The identification and influence of bioaerosols (fungi and bacteria) on human health was discussed.
• Bacterial bioaerosol concentration was dominant at the Bhandewadi landfill site.
• Bacteria were found to contribute about 75% to 85% of total bioaerosols at the landfill.
• Higher PM_2.5 concentrations at the landfill site as compared to the upwind/downwind locations.
• A total of 23 different fungi and 17 bacteria cases were reported in the present study.

Keywords: Particulate matter, Landfill, Bacteria, Fungi, Human health

1 INTRODUCTION

Bioaerosols consist of aerosols that originated biologically and are ubiquitously present in the environment (Fröhlich-Nowoisky et al., 2016). They are composed of organic materials, such as fungi, bacteria, pollens, particulate matter (PM_2.5, ₁₀), and cell fragments, constituents or by-products, which are viable or non-viable (Dias and Viegas, 2021; Lodish et al., 2000). These particles vary greatly from nanometer-sized viruses to micrometer-sized bacteria, fungal spores and pollen grains (Heikkinen et al., 2004). Dispersion of bioaerosols can be due to convective air current, and they can remain in the atmosphere for long durations due to their small size. Several studies have also observed long-range transport of dust-associated bacteria across continents (Smets et al., 2016; Han et al., 2020). Thus, bioaerosols are ubiquitous like the airborne particulate matter and may play important role in the atmosphere by interacting with other atmospheric constituents. Hence, there role in the understanding and prediction of climate change is currently a center of investigation (Fröhlich-Nowoisky et al., 2016). Significant interactions between bioaerosols, atmospheric pollutants (O₃ and NO₂), and meteorological parameters, such as temperature, humidity, and precipitation, have been reported recently by Cariñanos et al. (2021).

Studies on the origin of bioaerosols and their impacts on human health are sparse (NRC, 2008). Infectious and non-infectious properties of bioaerosols depend on various factors, such as physical composition, aerodynamic diameter, and biological properties (Nasir and Colbeck, 2010; Smets et al., 2016). Few studies have been done in Indian context. Effects of bioaerosol exposure in the human population surrounding an open landfill in Dehradun was studied by Madhwal et al. (2020). Similarly, Patil and Kakde (2017) assessed fungal bioaerosol emission in the vicinity of Deonar landfill site in Mumbai. Bioaerosol concentration showed drastic seasonal fluctuations with the highest concentration in monsoon (July), when rainfall and relative humidity were maximum, and temperature varied between 25°C and 32°C. The least bioaerosol concentration was reported in winter (October). Thus, the authors reported a positive correlation between relative humidity and the concentration of fungal bioaerosols. However, no such study is available in Nagpur city, which is a strategically located and one of the fastest growing economy of India. In the present study, we determined the inhalable (PM_2.5) particulate matter and PM_2.5-associated bioaerosol (bacterial and fungal) concentrations at a Municipal Solid Waste (MSW) landfill site in Nagpur, India. It will help in creating baseline data and determine the need to implement control measures at the landfill site, which are the hotspots of bioaerosol emission. Early assessment will allow planning in advance, which will not be possible once the city is at the peak of its development.

 
2 METHODS

2.1 Study Site Details

Nagpur is located at the center of the Indian peninsula at a height of about 312 m above mean sea level (AMSL). Nagpur is the winter capital and the third largest city of Maharashtra. The total area of Nagpur city is 228 km², while that of Nagpur district is 9892 km². The Nagpur district is geographically located from latitude 21°41′N to 20°35′N and Longitude 78°15′E to 79°45′E (RMC, 2023). The city has a major MSW landfill site at Bhandewadi at the outskirt. Sampling was done at the landfill site and its surrounding based on wind direction. Specifically, surrounding locations within 1 km diameter of the landfill site in upwind and downwind directions were selected (Fig. 1).

Fig. 1. Sampling sites near the landfill at Nagpur, India.

 
2.2 Sampling of PM_2.5 Particles

Sampling was conducted in February 2021 at the landfill site and the surrounding residential areas upwind and downwind of the landfill site. MiniVol portable air sampler (AirMetrics, USA) with 47 mm PTFE (Polytetrafluoroethylene) membrane and flow rate of 5 L min^–1 was used for the sampling of PM_2.5 (fine inhalable particles). The sampling was carried out at 2 locations simultaneously using the above sampler. Thus, the landfill and downwind sites were sampled together during 11–17 February 2021, while landfill and upwind sites were sampled together during 22–28 February 2021. Sampling was carried out for 8 h daily. The sampling strategy was in accordance with the work of Oh et al. (2020). The sampling period was kept 8 h to get an estimate of bioaerosol exposure to the workers at landfill facility performing various jobs (sorting, loading/unloading of waste, transport of trucks to collect and deposit the waste). Sampling was performed during daytime working hours (9:00–17:00 local time). The PTFE membranes were desiccated before use and weighing, and stored or transported in sealed cassettes. The PM_2.5 fraction was estimated gravimetrically using microbalance.

 
2.3 Estimation of PM_2.5-Associated Bioaerosols

Culture-based methods were used for the bioaerosol analysis. Two types of media, namely, PDA (Potato Dextrose Agar: potato extract 4 g L^–1, dextrose 20 g L^–1, agar 15 g L^–1, pH 3.5), and NA (Nutrient Agar: Peptone 5 g L^–1, beef extract 3 g L^–1, NaCl 5 g L^–1, agar 15 g L^–1, pH 7) were used for the cultivation of fungi and bacteria respectively. The filter papers containing PM_2.5 particles were immersed in 5 mL PBS (phosphate-buffered saline) and homogenized for 5 min. The resulting suspension was serially diluted and plated on the above agar plates under aseptic conditions. The plates were then incubated at ambient temperature for a period of 48 h to one week for colonies to grow. The total number of bacteria and fungi in each sample were counted and expressed in terms of CFU (colony forming unit) m^–3. The colony characteristics, i.e., colour, margin, form, elevation, size, shape etc., were also noted by visual observation.

 
2.4 Statistical Analysis

The PM_2.5 and bioaerosol concentrations were compared by t test using MS Excel program.

 
3 RESULTS AND DISCUSSION

MSW landfills give rise to several problems like smell and rodent/animal menace, but bioaerosols are an often overlooked problem originating from them (Yang et al., 2022). Landfill activities lead to generation of particulate matter, such as PM_2.5, which are fine inhalable particles with diameter of 2.5 micrometers and less. They can penetrate into the lungs, damage the alveolar lining, and affect lung function (Xing et al., 2016). Biological agents like bacteria or fungal spores associated with PM_2.5 make them more hazardous and can lead to infections or allergies (Morgado-Gamero et al., 2021). Thus, MSW landfills are hotspots of bioaerosol emission. Very few studies have been done on bioaerosols at landfill sites in India and effect of wind on their dispersal (Madhwal et al., 2020). Majority of such studies have addressed only the fungal bioaerosols (Patil and Kakde, 2017; Srivastava et al., 2021). In this study, we have attempted to address this question at a major landfill site located in Nagpur, India, which has not been studied so far.

 
3.1 Study Site and Sampling Locations

Nagpur is divided into 14 tahsils with a population of 46,53,171 as per the 2011 census with 68.3% population living in urban regions of the district. The general climate of Nagpur is very dry and semi-humid throughout the year except for the monsoon period (RMC, 2023). Approximately 1100–1200 tonnes of solid waste per day is generated in the city (NMC, 2017). The waste is dumped at a major landfill site located at the outskirt of the city (Fig. 1). Sampling was done at the MSW landfill site located at Bhandewadi, Nagpur, and surrounding residential areas. The residential sampling locations were selected based on the wind direction.

To get the average wind direction, 30-year average wind roses of the study month (February) for the Nagpur city were obtained from the Regional Meterological Center, Nagpur (Fig. 2). Wind rose is a graphical representation of the speed and direction of wind at particular location. Fig. 2 shows that the wind was blowing from the North and East direction for the maximum amount of time in February. Thus, NE (North–East) was considered as upwind and SW (South–West) as downwind direction for the sampling. Accordingly, an Anganwadi Kendra situated around 800 m SW from the landfill site was selected as the downwind sampling site. Similarly, a government school situated around 950 m NE from the landfill site was selected as the upwind sampling site. It can be seen from the satellite image of the sampling sites that the study locations are surrounded by human settlements (Fig. 1).

Fig. 2. Wind rose diagram of Nagpur city for the month of February (30-years average).

 
3.2 Estimation of PM_2.5 Concentration

The PM_2.5 measurements were made 8 h daily for 7 days at landfill and downwind sites first, and then landfill and upwind sites later on. Thus, data was collected for 7 days at the upwind and downwind sites, while 14 days data was available for the landfill site. Longer sampling time of 8 h was chosen to increase the volume of air being passed, and subsequently the probability of capturing PM_2.5 and associated bioaerosols. However, long sampling time may lead to loss of bioaerosol culturability (Haig et al., 2016). Thompson et al. (1994) and Wang et al. (2001) noted that apart from the sampling time, bioaerosol viability also depends on other factors like microbial species and humidity. Thus, bioaerosol sampling time is a critical parameter that influences the bioaerosol viability as well as sampling probability. During an investigation of airborne pathogens in a children's hospital of Taiwan, sampling time of 8–24 h was used with airflow rate of 12 L min^–1, indicating that such long sampling times are feasible (Wan et al., 2012). Thus, much longer sampling times are reported in the literature to increase the capture efficiency. In this study, we used a sampling time of 8 h, which may have affected the viability. Hence, the results must be interpreted with this limitation.

The average concentration of PM_2.5 at the landfill site was found to be 250.3 µg m^–3 and it was 125.6 µg m^–3 for the downwind site during 11–17 February 2021. Similarly, the average PM_2.5 concentration for landfill site was found to be 277.8 µg m^–3 and for the upwind site, it was 217.1 µg m^–3 during 22–28 February 2021 (Fig. 3). Thus, the PM_2.5 concentration at the landfill site was comparatively higher than both upwind and downwind sites. The PM_2.5 at upwind site was slightly higher than the downwind site, although the difference was insignificant (p > 0.05). The PM_2.5 level showed slight variation at the landfill site between the 2 sampling periods, but the difference was statistically insignificant (p > 0.05). Similarly, the PM_2.5 at landfill and upwind sites showed insignificant difference (p > 0.05). However, the landfill PM_2.5 was significantly higher than the downwind site (p < 0.05). Overall, the PM_2.5 at upwind site was in between those at landfill and downwind sites, which was unexpected. It may be due to minor renovation work going on near the upwind site or local wind direction deviations from the average direction, which is a very common phenomenon. In comparison, the PM_2.5 level reported at a landfill in Dehradun, India, ranged from 60 to 224 µg m^–3 (Madhwal et al., 2020).

Fig. 3. Daily variation of PM_2.5 concentration over both downwind and upwind directions at the Bhandewadi landfill site.
 

3.3 Estimation of PM_2.5-Associated Bioaerosols

The PM_2.5-associated bioaerosols (bacteria and fungi) were eluted from the collection filter by homogenization in PBS. Several variations of bioaerosol elution methods are reported in the literature as sample loss during elution is a critical consideration. Farnsworth et al. (2006) reported elution efficiency of 105% for B. subtilis from filter samples by hand-shaking. Therkorn et al. (2017) used 2 min vortexing followed by 10 min ultrasonication for elution of bioaerosols from filters. In yet another study by Clark Burton et al. (2005), vortexing for 2 min followed by shaking for 15 min yielded higher elution efficiency of Bacillus globigii than vortexing for 2 min followed by unltrasonication for 15 min. In all, mixing and shaking seem to give an adequate recovery of bioaerosols. Hence, bioaerosols were recovered from the filter by homogenization for 5 min in this study. However, the results must be interpreted with the caution that the bioaerosol recovery may not be complete.

After extraction, the bioaerosols were analyzed by culturing. The resulting colonies on the agar plates were counted and examined morphologically (Fig. 4). It gives a preliminary idea about the microbes. Colony morphological parameters (size, color, edge, elevation, and form/texture) are traditionally used to rapidly differentiate microorganisms. The combination of all parameters is necessary for the best discrimination as microorganisms may vary from each other in a single or multiple morphological parameters (Kowalski and Cramer, 2020). Some studies have tried to develop machine learning models to automatically distinguish microorganisms based on the colony phenotypic differences (Rodrigues et al., 2023). Based on the morphological difference, 23 different fungal colonies were observed from all 3 locations in this study (Table 1). In Table 2, morphologically different bacteria are listed. A total of 17 different bacteria were observed. Even though the colony types of bacteria were less than fungi, the bacterial CFU concentration was higher than fungi in general. The bioaerosol concentrations of bacteria and fungi and their variations are shown in Fig. 5 and Fig. 6. At the landfill site, the average bioaerosol concentration for bacteria and fungi was found to be 10742 CFU m^–3 and 704 CFU m^–3 respectively for the first sampling period. In the second sampling week, bacterial concentration was found to be 13533 CFU m^–3, while the fungal bioaerosol concentration was 2395 CFU m^–3 at the landfill site. In both cases, the concentration of bacteria was found to be more than fungi. Although the bacterial and fungal counts were different for the 2 sampling periods, the difference was not statistically significant. It indicates some temporal variation in the bioaerosol concentration, which may be due to different activities at the landfill site, such as the shifting of waste, clearing land, or due to local meteorological deviations. Yang et al. (2022) reported bacterial and fungal levels of around 33–22778 and 8–450 CFU m^–3 respectively at the Laogang Landfill in China, which is the largest landfill of Asia. In another study, average bacterial and fungal bioaerosols at a landfill site in Dehradun, India, were 3609 and 4582 CFU m^–3, respectively (Madhwal et al., 2020).

Fig. 4. Photograph showing bacterial and fungal colonies on media plates.

Fig. 5. Daily mean variation of (A) bacterial and (B) fungal concentrations at the downwind and landfill sites.

Fig. 6. Daily mean variation of (A) bacterial and (B) fungal concentrations at the upwind and landfill sites.

The average bacterial and fungal counts were 895 and 646 CFU m^–3 at the downwind site, and 712 and 1512 CFU m^–3 at the upwind site, respectively. The bacterial count at the landfill site was consistently higher than the upwind and downwind sites (p < 0.05), while the fungal count did not show significant difference (p > 0.05). On the other hand, the bacterial and fungal counts at the upwind and downwind sites were statistically similar (p > 0.05). The fungal count was unusually higher than the bacterial count at the upwind site, which may be due to the ongoing renovation work there. A higher fungal count than the bacterial count was also reported at the landfill site of Dehradun by Madhwal et al. (2020). The bioaerosol concentrations did not show significant correlation with PM_2.5 level. This is in agreement with the findings of Madhwal et al. (2020), who also reported no statistical correlation of bacterial and fungal aerosols with PM at an open landfill site in Dehradun, India. However, positive correlation has been reported between PM and bioaerosols in other environmental settings. Jeon et al. (2011) showed significant positive correlation of culturable bacterial level with total suspended particles and PM₁₀ during Asian dust events at Seoul, Korea. Similarly, Wei et al. (2020) revealed that bacterial, fungal and endotoxin concentrations were significantly correlated with PM_2.5 at coastal city of Weihai, China. The low correlation between PM_2.5 and bioaerosols observed in this study indicates other non-landfill activity sources of PM in the vicinity or fugitive dust. It may also be due to other meteorological parameters such as air temperature, wind speed, humidity, which are known to significantly impact the bioaerosols prevalence (Hosseini et al., 2021).

The overall trend shows generally higher PM_2.5 and associated bioaerosols at the landfill site. The spread of bioaerosols was significantly low to the downwind site, which may be due to small sampling period. A longer sampling period is needed to estimate the long term spread in the downwind direction. Morgado-Gamero et al. (2021) also reported higher concentrations of bioaerosols at the landfill than in the nearby village during their study of sanitary landfill near Barranquilla, Colombia. The literature study results differ in terms of aerial transport of bioaerosols ranging from 100 m to over 1 km (Breza-Boruta, 2016; Fraczek and Kozdroj, 2016). It may be due to the difference in the landfill design and modernization. Hence, the location of landfill near populations and control measures are important areas needing urgent attention.

 
4 CONCLUSIONS

In the present study, inhalable particulate matter i.e., PM_2.5, and the associated bioaerosol (bacteria and fungi) concentrations were measured at and around a landfill site in Nagpur city. The PM_2.5 and bioaerosol concentrations were found to be generally higher at the landfill site as compared to those at the upwind/downwind locations. A total of 23 different fungi and 17 bacteria were reported in the present study. The study revealed that the bacterial bioaerosol concentration was dominant at the landfill site. Bacteria were found to contribute about 75% to 85% of total bioaerosols at the landfill. On the other hand, the proportion of bacterial bioaerosols was lower at 58% and 32% at downwind and upwind sites respectively. Further study should be carried out to estimate the seasonal variation, identification, and risk assessment of the bioaerosols.

 
ACKNOWLEDGEMENTS

Authors are grateful to the Director, National Environmental Engineering Research Institute, (NEERI), Nagpur, India for providing the infrastructure facilities to carry out the work reported in this paper. Thanks, are also due to the authorities of Amity University Haryana (AUH), Gurugram for their continued support. The first author, PDB, an M. Tech (Atmospheric Technology and Climate Management) student of AUH is thankful to all colleagues, both at NEERI and AUH for their help during the field observations and analysis of data. The second author, PK, is thankful to the Council of Scientific and Industrial Research (CSIR), New Delhi, India, for the financial assistance in the form of Junior Research Fellowship (JRF). KRC No.: CSIR-NEERI/KRC/2023/FEB/HTC/1. Authors are also highly thankful to the Editor and Reviewers for their constructive comments and valuable suggestions which immensely helped to improve the clarity and scientific merit of the original manuscript.