Burning of Municipal Solid Waste: An Invitation for Aerosol Black Carbon and PM2.5 Over Mid–Sized City in India

Waste management is the main concern of most cities in developing countries. The proper procedure is needed to reduce Municipal solid waste, that’s why burning is the cheaper way to decrease solid waste. The main aim of this study is to assess the concentration of Black Carbon and PM2.5 during the MSW burning sites in Jamshedpur. The continuous measurement was taken during the burning period in three phases at Industrial, Urban, and Rural waste burning sites having respective average BC concentrations observed as 145 ± 46, 101 ± 33 & 95 ± 33 μg m−3, and PM2.5 as 1391 ± 358, 998 ± 319, 957 ± 313 μg m−3. BC and PM2.5 concentrations show significant diurnal variations with maximum average concentration at the midnight phase due to large temperature fluctuation (lower mixed layer height) in the atmosphere. This evaluation during burning period exceeds regular day estimates by around 5–6 times. The rate distinction of BC by the Aethalometer model indicates that source apportionment of BC is more sensitive in assessing BCBB (biomass burning) with an average fraction of 82% at 880 nm because waste trash burning in the dump yard was mostly solid. Pearson correlation analysis shows strong correlations between BC and PM2.5 concentration that is primarily attributable to well-known nearby sources such as vehicular emissions.


Introduction
Worldwide, the production of municipal solid waste (MSW) is an unavoidable consequence of human activity that directly impacts human health and the environment (Ranjbari et al. 2023). Municipal solid waste is regularly generated waste that is thrown in public places as plastic waste, food waste, and electronic waste. People presently dispose of the waste and their composition making it more complex than before. The diffusion of plastic waste and electronic products nowadays poses a key challenge to cities. The major goal of this article is to outline the exposure of aerosol particles due to the burning of municipal solid waste. The worldwide municipal solid waste generated around 2.02 billion metric tons in 2016 which is expected to increase by about 70% i.e., around 3.4 billion metric tons of municipal solid waste by 2050 (Kaza et al. 2018).
India is among the 3 rd largest MSW producer in the world after USA and China in 2016, with about 52 million tons, which amounts to 1.4 lakh metric tons per day (TPD) . The Waste management activities contain compilation, composting, recycling, landfilling, and incineration/burning. The average collected MSW is around 68% out of these only 19.4% of collected MSW is treated (Kumar et al. 2017). The lack of waste collection and treatment results in the dumping or burning of left waste in most of the cities in India (Singhal and Goel 2021) which consequently emitted aerosol particles into the atmosphere. Various technologies have been carried out for solid waste burning which stimulates efficient clean combustion, store energy, and moderates emission efforts during open burning. The source of waste is produced generally from the place where people reside and collected at the dumping area. Dump sites can pollute the soil, water, and air by process leaching toxic chemicals such as arsenic, mercury, and lead, deteriorating vegetation, and intentionally burning the waste that contributes to global warming. Open burning is the general process to reduce the volume and remove the smell of dumped waste (Gautam et al. 2020a;Estrellan and Iino 2010). The burning of MSW is an incomplete combustion process because of a limited oxygen supply. Moreover, there are no such quality-controlled instruments to improve the quality of ambient air which is generally contaminated due to various poisonous gases such as SO 2 , NO 2 , NO x , volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs) (Krecl et al. 2020). Open waste burning is a global concern that releases mass emissions of deteriorated species in the atmosphere that suffer most of the developed and developing countries like China, India, Japan, etc. In most developing countries, there is a lack of service for the collection of waste. The waste is dumped into the open sites which further reduces the waste by burning it in an uncontrolled way.
The open burning of waste at the disposal sites generates many pollutants which include Particulate Matter (i.e., PM 10 , PM 2.5 , PM 1 , Black Carbon (BC), etc.), greenhouse gases (GHGs), and many other contaminated materials. Generally, pollutants lead inserted into the atmospheric cloud by the combustion of solid waste (Khan et al. 2023;Kumar et al. 2022;Gautam et al. 2020b;Lavric et al. 2004;Zhang et al. 2017). Humans might cause severe health consequences like premature death due to the consumption of fine particulate matter (PM 2.5 ) which was approximately 270,000 inhabitants (Kodros et al. 2016). The waste is majorly diversified which mainly changes the amount and stake of emitted particles (Lemieux et al. 2004). Particulate matter is generally emitted from both natural and manmade sources (Chernyshev et al. 2019). Rapid urbanization in the modern era indicates various infrastructure builds, advanced transport & communication, automation, ammunition for strong defense, and growing industrialization tends to enhance the concentration of PM 2.5 .
BC is one of the most toxic particulate matters found majorly in industrial and urban conditions which is due to the emission of partial combustion of fossil fuels and solid fuels (biomass). It is the subgroup of PM 2.5 whose size diameter is less than equal to PM 2.5 ranging from 10 to 50 nm (Bond et al. 2013). It has a substantial effect globally because it absorbs visible radiation directly from the sun (Pani et al. 2019;Gatari et al. 2019). Due to its increasing concentration in the atmosphere, it acts as a regulatory body to the earth's radiation budget (IPCC 2013) which registered itself as the second most important anthropogenetic agent of the greenhouse effect and climate change after CO 2 (Bond et al. 2013;Liu et al. 2018;Joshi et al. 2016;Tiwari et al. 2016). Climate change is also associated with the worsening of human health to premature death (WHO 2012;Janssen et al. 2012;Louwies et al. 2015;Li et al. 2016;Lin et al. 2019). During the starting decades of the 1980s, the WHO identified the exposure of BC to human health and proposed the first guidelines regarding the permissible limits to health risks on exposure to BC (Targino et al. 2016). Because of its fine size and asymmetric morphology, it easily absorbs carcinogenic/mutagenic impurities like PAHs, and VOCs which penetrate the human respiratory systems (Janssen et al. 2012;Cao et al. 2012). After the deposition into lower respiratory tract, potentially carry toxic chemicals which result in various health effects such as lung cancer, cardiovascular diseases, asthma, bronchitis, neurodegenerative disease, chronic respiratory disease, immature birth, etc. (Atkinson et al. 2015). In this study, the BC and PM 2.5 were monitored during the sampling period in the different waste burning sites. The characterization of BC and PM 2.5 is quite challenging from the emission due to the open waste burning. Apart from these challenges, the efforts were prolonged to evaluate the concentration emitted due to burning. However, the work estimated the real-time BC and PM 2.5 during the municipal waste burning which is a major concern for the country in the present day.

Study Area
The location site, Jamshedpur has coordinates Latitude 22.80º N, and longitude 86.20º E with 159 m height above sea level, which is situated near the bank of the Subarnarekha and Kharkai rivers, along with several water reservoirs like Sitarampur Dam, Satnala Dam, Hudco Dam, etc. The population of the city is roughly around 1,661,439 (http:// world popul ation review. com) and is located in the southern part of the state of Jharkhand, India. The city is surrounded by dense forest of Dalma range. The case distributed nearby localities was observed in the inhabited zone. The climate of the city is tropically humid with maximum temperature of 46℃ in May 2022, minimum temperature of 7℃ in December 2021, which means cumulative annual rainfall is around 137 cm.
The major sources of air pollution in the nearby localities are heavy traffic, industrial activities, and burning of indigestible open waste garbage generated by the locals. The transport of air pollutants radiated by biomass burning might affect the region from the other nearby cities of India and bordering countries. The city covered 156 km 2 of area that includes 4 municipal boards Jamshedpur Notified area committee (JNAC), Mango Municipal Corporation, Jugasalai Municipal Corporation, and Adityapur Municipal Corporation. The Municipal solid waste is collected doorto-door in the residential area. The compost and other nonbiodegradable waste were dumped at the city exterior site where it was being digested or reduced by different chemical compositions. Along with that due to the lack of equipment facilities and advanced digestive techniques for the waste, it was quite convenient to burn this open waste. However, open burning of waste could be prohibited whose complete responsibility should be taken by the municipality.

Monitoring Sites and Measurements
The instruments were deployed at three burning sites: a). At NIT Jamshedpur, Adityapur (Site 1), b). Western Union office, Sakchi (Site 2), and c). B M complex ukri road, Sini (Site 3) (Fig. 1). All three sites were significantly divided into Industrial (S1), Urban (S2), and Rural (S3). The BC and PM 2.5 were monitored during the sampling period i.e., B1 to B12 before monsoon. The site was thoroughly monitored while burning in 3 different phases Morning (B1-B4), Evening (B5-B8), and Midnight (B9-B12). In this study, the MSW burning time was comprised of between 4:00 and 12:00 (morning), 12:00-20:00 (evening), and 20:00-4:00(midnight). For the stable count of concentration of BC, the time interval was noted over 1 min during continuous burning process. Whereas the PM 2.5 was manually counted with interval time of 10 min to reduce the randomness of concentration data.

Measurement of BC Mass Concentration
An Aethalometer (Model No: AE-33, Magee Scientific, Berkeley, USA) was set up on the terrace of the building adjacent to the burning sites. The instruments were situated on the top floor of the building so that the sampling lines are at minimum distance from the inlet (rooftop) to the instrument where the real-time data was observed. BC concentration works on the principle of light absorption at 7-wavelengths (370, 470, 520, 590, 660, 880, and 950 nm). The principle is based on the measurement of the absorbing light beam transmitted through a filter on which the continuous pulling of aerosol is deposited. Sampling was performed for 2 h during the burning periods at a flow rate of 5 L min −1 using a TFE-coated glass fiber filter (T60A20) (Drinovec et al. 2015). The various types of filters influence the loading effect on the filter strip. The TFE filter is sensitive to air in stream humid situations; although the GAW (Global Atmospheric Watch) recommends that the optical properties of aerosol should be observed at stable relative humidity (WMO/GAW, 2003). Dual spot technology followed by the aethalometer AE-33 for the external air bounded with particulate matter that divided into two streams with different flow rates and settles down into two spots of filter tape, which delivers two concurrent measurements of light attenuation (ATN) (Drinovec et al. 2015).

Measurement of PM 2.5
The emission of PM 2.5 concentrations was collected along with BC observing in morning, evening, and midnight phases respectively during sampling periods. The PM 2.5 was monitored with the help of a small volume sampler for particulate matter having Model No. Envirotech APM 550, India. The particulate matter was deposited in the 47 mm PTFE (Polytetrafluoroethylene) filters enclosed in the sampler. The instrument was performed at a flow time of 16.5 L/min for 2 h during the burning period on all monitoring sites. For the determination of PM 2.5 , before the PTFE filter was inserted in the sampler, it was balancing, and after the deposition of particulate matter again it was gone through weighing. The digital weighing balance (VWR, Model no: VWR1611-2263 and Weighing Chamber L × W × H: 162 × 171 × 225 mm) having a single pan top was used to weigh the PTFE filter.

Source Apportionment of Black Carbon
There are several contributing sources of Black Carbon such as diesel sources, cooking, wood, dung cake, coal, gasoline sources, vehicle oil, industrial waste, agricultural waste, etc. which are firmly divided into Biomass burning (BB) and Fossil Fuel combustions (FF). The quantification of the contribution of FF and BB can be easily identified by the Aethalometer Model. The model is utilized for the determining of carbonaceous aerosol (BC) by light absorption of aerosols (Sandradewi et al. 2008) along with many other parameters like exponents (α), absorption angstrom exponents, etc. The other preceding techniques such as Chemical Mass Balance (CMB) method (Favez et al. 2010), Microtracer (Larsen et al. 2012), PMF (Belis et al. 2014), Radiocarbon method (Zhang et al. 2015), specific methods (Briggs and Long 2016), and PCA (Thepnuan et al. 2019) offered different strengths and weakness for the source apportionment studies but the aethalometer model can deliver a robust technique to determine the contributing sources. According to Briggs and Long 2016, the Aethalometer obtains sources at attributing all the BC that is based on the assumptions of angstrom absorption coefficients (AAE). It identifies FF and BB without the requirement of additional data. The Chemical Mass Balance may not identify all the sources but can differentiate between the classifications of sources. The macro tracer method determines the FF and BB sources by assuming the average emission factors. Specialized models may identify the BC from different sources that cannot be easily characterized (Residual BC) (Briggs and Long 2016). The Positive Matrix Factorization (PMF) was implemented in a similar data matrix just before normalizing the result to obtain the objective interpretation between the given sources value. It recognizes the emission sources like wood burning, industrial emissions either fossil fuel or coal burning, traffic emissions, and petroleum product burning by evaluating the wavelength dependency of light absorbed (Zotter et al. 2017;Dumka et al. 2018Dumka et al. , 2019Ambade et al. 2022).
However, the characteristic nearby sources were identified for the MSW burning in Industrial (S1), Urban (S2), and Rural (S3) sites respectively. In the beginning, the BC intensity was collected for the two given wavelengths of 370 nm and 880 nm, the distinct rate of BC can be obtained below: The above-mentioned Eq. (1) may arise two cases. Case I: If the % contribution of BC value was shown negative fraction, then the considerable emission of BC was coming from liquid fuel combustion i.e., Fossil fuel burning (BC FF ) (Herich et al. 2011).
Case II: In this case, the % contribution of BC value was estimated as a positive fraction which indicated that significant emission sources from biomass burning (BC BB ) i.e., wood, coal, forest fire, stubble burning, etc. (Wang et al. 2011).
However, various research article has revealed the usability of the Aethalometer model developed by Magee Scientific for providing proper estimation of different sources either biomass burning of fossil fuel of BC (Crilley et al. 2015;Becerril-Valle et al. 2017;Healy et al. 2017;Zotter et al. 2017).

Variability in BC Mass Concentration Estimates Within MSW Burning Sites
To understand the variation of BC contamination arising due to the burning of MSW sites in different regional conditions, this study compares with previous research in other cities across the world. As the simultaneous burning occurs in the course of morning (B1-B4), evening (B5-B8), and midnight (B9-B12) phases, a different trend was observed for the respective S1, S2, and S3 during the study period. The BC mass concentration was observed to be in the range of 28.9 to 363.7 μg m −3 during the whole burning period as shown in Table 1. The Average BC at 880 nm was observed at 145 ± 46, 101 ± 33, and 95 ± 33 μg m −3 at S1, S2, and S3 respectively ( Table 2). The average concentration of BC was observed higher at S1 as compared to the remaining sites (Fig. 2); this might happen due to the larger industrial accumulated in the dump yard. In the study site S1, the average concentration of BC during the burning period was 129.2, 146.2, and 160.7 μg m −3 in three phases respectively. The concentration of BC was recorded as 92.7, 108, & 104.2 μg m −3 and 93.6, 87.6, & 105.4 in the respective S2 and S3 sites for three consecutive phases. Figure 3 describes the average variation of BC in each burning period (B1-B12) at examined sites. It was noticed from box plot (Fig. 4) and table (Table 1) that the level of pollutants was comparatively higher in the third phase due to reduction of temperature in the atmosphere. During the night, the industrial site (S1) observed larger fluctuation of BC as there was large standard deviation of 58.4 μg m −3 (Table 1). Industrial exposure enhanced the level of BC concentration at midnight. Geographically the BC concentration changes with earth's surface temperature, as the temperature was high from the afternoon to evening; the BC has fallen at evening phase. Mixed Layer Height (MLH) also plays a critical role in understanding the presence of an aerosol particle in the atmosphere. It was referred from several studies that the concentration of BC starts to decrease

Variation in PM 2.5 Concentration During the Waste Burning Sites
The average burning period PM 2.5 concentration was monitored before the monsoon in three different geographical sites. The air sampler was performed for around 2 h in each burning period. The PM 2.5 concentration (diameter of PM less than equal to 2.5 μm) was examined at a range  Table 1. The average PM 2.5 concentration for the sampling sites S1, S2, and S3 was assessed at 1391 ± 358, 998 ± 319, and 957 ± 313 μg m −3 (Fig. 4). Short-term exposure to high concentration PM 2.5 at S1 might be seen due to industrial trash-associated waste burning (Fig. 2). In S1, the average concentration of PM    The previous study in Table 3 for waste burning in Beirut, Lebanon reached high concentrations of 665 and 356 μg m −3 (10 min average) in two respective days with the range of 14.2 to 67.8 μg m −3 based on daily data (Baalbaki et al. 2016). An hourly spike was shown in a study at Iqaluit, Canada, The PM 2.5 was observed at 85 μg m −3 with a daily mean of 4.61 μg m −3 during the burning of a smoldering landfill (Weichenthal et al. 2015). In the National capital territory, Delhi, India, Tiwari et al. (2015) found the PM 2.5 concentration given in mean ± sd as 182.75 ± 114.5 μg m −3 . The study of sampling done on open burning in Chennai, India was seen as 44.49 ± 2.0 μg m −3 (Karthikeyan et al. 2011).

Source Contribution of BC
Aerosol emissions from MSW burning implemented in the monitored site include waste burning accumulated in the marked dump yard. These wastes include residential wastes, domestic garbage, drainage waste, industrial spoilage, animal byproduct, medical and clinical derivatives, etc. Furthermore, these also comprised emissions of Particulate Matter due to open waste burning. The continuous burning might hamper the source contribution of BC emission, so the aethalometer modeling setup has provided the information to the source influencing the BC. The source identification for BC was discussed earlier and selective category was depicted as biomass burning and fossil fuels. The primary source characterization of BC was assessed by calculating the concentration of BC which was deposited in the UV (370 nm) and near IR frequencies (880 nm) (Srivastava et al. 2012). In India, biomass burning is foremost source of BC which coal combustion contributes the most. According to study, coal combustion is preferable as to source of energy that fulfills 76% of total energy consumption in India (SAFAR 2010). The source identification was characterized between BB and FF in a variety of situations i.e., industrial (S1), urban (S2), and rural (S3) atmospheres. The % ratio of FF and BB was estimated at 24. 65: 75.35, 17.5: 82.5, and 10.9: 89.1 in the study sites S1, S2, and S3 respectively (Fig. 5). Green et al. 2013 compared the BC source contributions which were recommended and observed that the relatively greater contribution of FF due to diesel sources at S1 as there was an extent of vehicular movement in the industrially commercial zone. This might also occur due to the byproduct of liquid fuel waste from the various industries trashed in the dump fill stations. In the case of Urban regions i.e., S2, the diesel sources mainly had some extent in the contribution of FF, for the reason of heavy traffic and street crowd, then at S3 (Fujita et al. 2007). However, in case of S3, the lack of vehicular movement in the rural region might reduce the FF contributions. Generally reported studies suggested higher contribution from BB in the winter season for the heating up of climate (Zhang et al. 2013;Favez et al. 2010;Genberg et al. 2011;Gilardoni et al. 2011;Herich et al. 2011Herich et al. , 2014Fig. 6 Diurnal variations of PM 2.5 (a) and BC (b) at the waste burning sites for the entire sampling period Larsen et al. 2012). But it was the case of direct trash burning, so the major contributor holds to biomass burning. In European study, the source apportionment findings for BB were ranging from 6-83% during the wintertime among different geographical locations (Gelencser et al. 2007).

Comparison of BC and PM 2.5 by Pearson Correlation (PC) Analysis
The incomplete combustion of carbon-based fuels releases BC and particular matters (PM 2.5 ) (Klimont et al. 2017). In comparison to urban and rural areas, industrial locations had greater concentrations of BC and PM 2.5 . Figure 6 elaborates nearly similar trends in the diurnal variations of BC and PM 2.5 , which was due to common emission sources i.e., solid waste burning. The amounts of BC and PM 2.5 exhibit an excellent positive correlation across all three sites, as seen in the scatter plot in Fig. 7. Pearson's correlation value was calculated as 0.9516, 0.992, and 0.939 in S1, S2, and S3 respectively. The BC and PM 2.5 correlation parameters determined for different sites are presented in Table 4. Previous research showing strong correlations between BC mass concentration and PM 2.5 concentration is primarily attributable to well-known nearby sources such as vehicular emissions. Compared to diesel-powered cars, emissions from petroleum vehicles are less of a source of BC and PM 2.5 . According to an earlier study on vehicle emissions, light-duty petrol engines release less BC and PM 2.5 than heavy-duty vehicles like diesel trucks (Majewski and Khair 2006 Table 4.

Summary and Conclusions
We have monitored real-time measurements of BC and PM 2.5 to characterize the aerosol particle impacting nearby localities by municipal waste burnings. The measured mean concentrations at three monitoring sites (S1, S2 & S3) of BC, and PM 2.5 were observed as 145, 101 & 95 μg m −3 , and 1391, 998 & 957 μg m −3 . The concentration suggested that there was a large number of particulate matter suspended in the environment. The air pollution data was circulated by public survey to understand the people's behavior towards the waste burning in the study sites. In our study, we observed the range of concentration for the above-mentioned study sites. On average, the atmospheric aerosol pollution at Industrial sites was greater than in urban and rural areas for BC and PM 2.5 . According to the rate distinction coefficient of BC, the study sites were affected largely by emissions due to biomass burning, which might occur because sources come majorly from solid wastes. This might also give clear justification for the increase in PM 2.5 concentration. Particulate matter is generally dense in the evening and midnight when biomass burning dominated over other sources of emission. The continuous monitoring of burning indicated us to ascertain the variability of BC and PM 2.5 . On comparing the measurements, we have concluded that: (a) average BC and PM 2.5 was observed higher in present study as compared to normal days, due to much closer monitoring towards waste burnings, (b) the ratio between BC and PM 2.5 was observed higher because of strong positive correlation indicating BC increases with increase in PM 2.5 as both produced from common emission sources during the waste burning, (c) industrial area supposed to have great extent of waste collection such as solid rubbish, organic waste, automobile waste, iron & steel waste, and also resident domestic waste, So it might have larger emission compare to another region in Jamshedpur, (d) according to the diagnostic ratio analysis of BC, originating sources majorly influenced from biomass burning (75.35-89.1%) due to solid waste burning, however in case of Fossil Fuel (FF) burning, industrial area observed higher FF contribution (24.65%) due to fuel burned and larger utilization of vehicles. The investigation of local views showed that inadequate waste management (i.e., waste garbage left in the paths, burning waste anywhere) can cause serious problems in the green ecosystem in the livelihood. Several burning practices were common to nearby residents and popular materials that were frequently taken for burning were single layer plastics, trashed leaves, paper wastes, etc. Since Jamshedpur is an industrial city, Industries were very common and most of them also took poor management steps toward waste reduction, recycling, and utilization. So, the municipal council should take strict action against these waste-generating industries, and they should also take advanced waste management techniques to make the environment clean.