Comparison of emission profile of black carbon and carbon monoxide over Eastern India: source apportionment and health risk impact


 In the present study, black carbon (BC) mass concentration and carbon monoxide (CO) combination ratio were calculated simultaneously at two different cities (i.e.,Jamshedpur (JSR) and Kharagpur (KGP)) located in the eastern state of India. The analysis of GIOVANI NASA data indicates the highest concentrations of BC and CO in the Indo-Gangetic Plain (IGP) as well as the eastern part of India. The BC-CO relationship exhibited an excellent positive correlation (r2 = 0.65), while BC-PM2.5 showed a strong positive correlation (r2 > 0.96). On the other hand, the backward air trajectory showed pollutant transport mainly from India's northern part with some contributions from other countries likePakistan, Nepal, Bhutan etc. BC concentration overall health risk assessment was demonstrated as 6.27, 12.43, 11.22 and 25.60 in JSR and 2.02, 4.02, 3.63 and 8.28 in KGP, passive cigarettes comparable concerning the risk of lung cancer, low birth weight, cardiovascular mortality, and percentage lung function decrement of school-aged children.

We have conducted the measurements of ambient air BC, CO, and PM 2.5 concentrations from October 2019 to January 2020 in two different eastern Indian cities to assess their source apportionment and health risk impact. The observations of BC and CO concentrations at JSR and KGP cities will help understand the dominant local sources of carbonaceous aerosols, health risks, and the role of atmospheric conditions over East India.

Geographical Location Of Sampling Sites
The locations of KGP and JSR in India's map and localities images in these two cities are displayed in Fig-1. PM 2.5 , BC and CO concentrations were collected from two different cities in India eastern part. The KGP city (22° 33' N, 87° 32' E) is situated in the state (province) of West Bengal and JSR city (22° 80' N, 86° 20' E) is located in the state of Jharkhand. KGP is the fth most populated and fourth-largest city in the area wise after Kolkata, Durgapur, and Asansol cities of West Bengal. The total area of KGP is about 127 km 2 in the southern part of West Medinipur district and this town is formed with the alluvial tract and Dalma Pahar of Medinipur. It has a tropical savanna climate. The average temperatures are around 22°C and 30°C in winter and summer, respectively. The mean annual precipitation is around 1401 mm. According to the 2011 census, KGP had a population of 293,719. KGP city is surrounded by a railway network, National Highways (NH) network, Vidhyasagar industrial park, Railway Workshop, etc. In Vidhyasagar industrial park, so many small and large industries are situated. JSR city is located over the Chhota Nagpur Plateau (CNP) region in the southern part of Jharkhand state, India. JSR is a densely populated city, and according to the 2011 census, the residents of the city is about 1.3 million. The world-known largest industries, namely the Tata Iron and Steel Company (TISCO),TATA motors and are located in JSR city. The Adityapur Industrial Development Authority (AIDA) region is very close to JSR city, where more than 1001 companies (minor, average, and big enterprises) are located. Air pollutants major sources in these two cities are chie y emissions from industrial activities, transportation discharges, road construction, and town construction.

Measurement of BC mass concentration
Continuous real-time measurement of BC mass concentrations was performed with the Aethalometer (Model AE-33, Magee Scienti c Company, USA) instrument. BC aerosol's mass concentration was deduced from the analysis of seven different wavelengths i.e., 370 nm, 470 nm, 525 nm, 590 nm, 660 nm, 880 nm, and 940 nm. Out of all wavelengths, 880 nm, a light ray from a high energy light-emitting-diode light was transferred through the sample collected on the lter strip. This is a simple and e cient technique to measure BC's ambient air mass concentration associated to the supplementary design alike the coe cient of haze tape sample, particle soot absorption photometer (PSAP), melting oxidation/re ectance, etc. (Allen et al. 1999). This technique is based on attenuation of light due to the mass load of BC particles accumulate on a lter. The air inlet is equipped on the Department of Chemistry rooftop, NIT JSR city, and Railway quarter building at KGP city. Atmospheric air is drawn through the inlet line at the ow rate (~ 5 LPM), which hit on a quartz lter. BC mass concentrations were recorded on the duratation of every 5 minutes. Bestowing to the guideline and literature reviews, 880 nm is the regular wavelength to measure BC mass concentration. BC shows principal absorber of energy at this wavelength and other aerosol components have negligible absorption (Weingartner et al. 2003). 3.2. Measurement of PM 2.5 and CO concentrations PM 2.5 was also examined along with BC and CO concentrations in both the cities. The PM 2.5 sample was collected using a mini volume sampler (Envirotech Model APM 550) from October 2019 to January 2020. The mini sized sampler was operated at a constant ow rate of 16.5 L/m 3 . PTFE lter (47 mm, Merck, catalog no-PM2547050) was used to gather particulate matter (PM). At rst, the lter paper was weighed before and after the sampling and kept in a desiccator.
Weight balance with a single pan-top loading digital weight balance (VWR, Model no: VWR1611-2263: with measuring apartment L×W×H: 162×171×225 mm). Background infection was investigate using operational blanks (unexposed lters), which were processed concurrently with eld samples. Moreover, the sample lter was stored in a desiccator box. These samples were held at 4° C for storage and then weights of lter paper before sampling and after sampling was measured.
Similarly, CO concentration was also measured in both cities. The concentration (mixing ratio) of CO was carried out using a extensive gas lter non-dispersive IR (infrared) gas analyzer (Thermo Scienti c. Model 48C, USA). A Na on has been used to reduce water vapor interferences present in air samples (ambient air). The time resolution and detection limits were 1 min and 30 ppbv for 2 min average, respectively. The equipment baseline signal was determined in the rst 15 min of each hour by supplying zero-air. Before the ambient air measurements, the span calibration was performed carefully.

Health risk assessment
In the current study, health risk estimates of BC pollution were carried out to determine the disease's overall concern due to environmental tobacco smoke (ETS) exposure. Our evaluations are based on the assumptions reported in van der Zee et al. 2016, i.e., 14 daily cigarette utilization as per WHO assessment for smokers in the US as well as North-West Europe. The health risks of BC pollution are approximately equal to passive smoking (Niranjan et al. 2017;Vander et al. 2006). There are mainly three-zone reasons to co-relate the health risk between passive smoking and BC. These zones (a) both hazards have equal exposure through inhalation (b) both hazards have some type of health effects and (c) exposure to both ETS and atmospheric BC pollution is commonly spontaneous (Vander et al. 2006). In the present study, we have assessed the health risk of atmospheric BC pollution to local inhabitants of two different cities in the eastern part of India. In JSR and KGP cities, analogous extents of passive cigarette smoking for potential receptors are comprehended. According to recent scienti c studies, people living in different parts of the world are facing serious health threats like non-cancer (respiration related problems, cardiovascular problems, etc.) and cancer (especially lung cancer) diseases due to exposure to BC (Magalhaes et al. 2018;Kelly et al. 2015). the small particulate size of BC is direct air inhalations from local or regional sources' proximity. Van der et al. (2016) has developed a module by which we can easily calculate the health risk evaluation based on ETS. The ETS values are helpful to estimate the risks of BC exposure related to the following four different health issues. i.e., (i) lung cancer (LC), (ii) low birth weight (LBW), (iii) cardiovascular mortality (CVM), and (iv) percentage lung function decrement of school-aged children (PLFDSC). The links between all the four health issues with both ETS exposure and BC pollution are well established (Kelly et al. 2015;Oberg et al. 2010;WHO 2014). The estimation of health risk primarily depends on relative risks (RRs) relative to a different health issue for air pollutants like ETS exposure and BC pollution; where RR refers to the possibility of growing an illness induced by the exposure to air pollutants (Rothman et al. 2008;WHO 2003). The value of RR BC and RR ETS are derived from detailed, systematic reviews and can be summarized to implement the relevant, yet immature, health risk estimates. The speci ed change in BC concentration and health risk issue was characterized by a meta-analysis of recorded concentration-response functions (CRFs). For a particular health issue (i.e., R), the BC concentration increases by 1 µg m − 3 , equivalent to the number of passively smoked cigarettes (PSC) (Vander et al. 2006). Therefore, R is written as The values of RR ETS and RR BC were taken from van der et al. (2006) and Pani et al. (2020). The assumed number of PSC varies depending on the case. In the case of PLFDSC, the assumed number of PSC per day is 9. For the child of the nonsmoking mother, the assumed number of PSC per day is 7 for CVM and LC as well as for adults about the risk of LBW (Vander et al. 2006). The following equations estimate the equivalent numbers of PSC per day (i.e., NPSC: passive cigarette-equivalence). (3) and ΔBC = [(BC obs ) -(BC bac )] ………… (4) Where, BC obs = Observed Black Carbon Aerosol and BC bac = Background Black Carbon Aerosol.

Source appropriation
Signi cant sources of BC aerosols are incomplete combustions of biofuel burning and fossil fuel in the atmosphere (Petzold et al. 2013). The aethalometer model was used to determine BC's source appropriation (Fuller et al. 2014;Sciare et al. 2011). Although this model identi es broad source categories like wood-burning, tra c emission, fossil fuel, etc. but requires seven different wavelength light absorption data sets (Zotter et al. 2017). This model was the latest and easiest among other methods or models like principal component analysis (PCA) (Thepnuan et al. 2019), Positive matrix factorization (PMF) (Florou et al. 2017), the radiocarbon method (Zhang et al. 2015), the macro-tracer method (Larsen et al. 2012), chemical mass balance (CMB) (Favez et al. 2010), and other specialized models (Belis et al. 2013 (5) From Eq. (5), two cases may arise, Case-I for fossil fuel and case-II for wood burning.
Case-I: -The negative fractional BC values suggest major contributions from the combustion of diesel and petrol (Herich et al. 2011).
Case-II: -The positive fractional BC values suggest major contributions from the forest re, domestic use product like coal, dry leaf, etc. (Wang et al. 2011). We also describe the source appropriation of BC, CO, and PM 2.5 mass concentrations with the help of air backward trajectory.

Results And Discussion
4.1. Variation of BC, CO, and PM 2.5 BC's mass concentrations were measured from October 2019 to January 2020 at two different places in the eastern part of India. The average BC mass concentrations of 10.06 ± 1.59 µgm − 3 at JSR and 5.49 ± 1.15 at KGP were measured during the study period. The variations in monthly mean BC mass concentration along with standard deviation from October 2019 to January 2020 are shown in Fig. 3.a. In JSR, the monthly average BC mass concentrations were 8.99 ± 1.77, 9.73 ± 1.84, 10.81 ± 1.82 and 10.53 ± 0.97 µgm − 3 in October, November, December of 2019 and January 2020, respectively. In KGP, the monthly average BC mass concentrations were 5.05 ± 0.60, 4.95 ± 0.47, 6.67 ± 1.74 and 5.62 ± 0.89 µgm − 3 in October, November, December of 2019 and January 2020, respectively. From sample-to-sample, BC concentrations varied in the ranges of 6.49-12.83 µgm − 3 at JSR and 4.36-10.23 µgm − 3 at KGP. The analysis of satellite (GIOVANI NASA) data reveals much higher loadings of BC aerosols over the Indo-Gangetic Plain (IGP) than other regions of India. It was also demonstrated that the BC mass concentrations were reported to be approximately 3.5 µgm − 3 to 5 µgm − 3 during study period (Fig-2.a).
Simultaneously, CO and PM 2.5 concentrations were also measured from October 2019 to January 2020 in JSR and KGP cities. The average CO concentrations of 913.63 ± 217.85 ppbv at JSR and 507.31 ± 125.06 ppbv at KGP were measured during the study period. The average PM 2.5 concentrations were 176.34 ± 24.40 µgm − 3 at JSR and 107.28 ± 13.60 µgm − 3 at KGP. The monthly mean concentrations of CO and PM 2.5 along with standard deviations are shown in Fig. 3 (Fig-2.b).
The concentrations of BC, CO, and PM 2.5 in JSR were higher than those in KGP. More and more industries are present, dense tra c connectivity, and more vehicles than KGP, where fewer sectors, moderate tra c connectivity, and fewer cars are current.

Health risk assessment
We have attempted to evaluate the health risk assessments of BC in both cities. The health risk assessment summary indicated an equal number of PSC for a particular investigation period, as shown in Table-3. We considered that the day to daily exposure level of BC for the people living in JSR city and KGP city was equivalent to day to day mean BC (balance load concerning the background BC) level. According to previous studies, the estimates were presented for an increment of 1 µgm − 3 in BC concentration. As per Rupakheti et al. (2017), the background BC (BC bac ) concentration level was determined as the 1.25th percentile of the observed BC (BC obs ) concentrations, which are 6.571 µgm − 3 for JSR city and 4.362 µgm − 3 for KGP city. These increments are generally used to explicit relative risks of BC mass concentration of JSR city. The health risk assessment of BC aerosols concentration was demonstrated as 6.27, 12.43, 11.22 and 25.60 passive cigarettes-comparable concerning the risk of CVM, LC, LBW, and PLEDSC, respectively. And in KGP city, the health risk assessment of BC aerosols concentration was notice as 2.02, 4.02, 3.63 and 8.28 passive cigarettes comparable concerning the risk of CVM, LC, LBW, and PLEDSC, respectively. It was noticed that the health risk issue is higher in JSR city as compared to KGP city during the study period. This is because of increased air pollutants like BC, CO, and PM 2.5 in JSR city compared to KGP city.
CO is a very serious air pollutant in the atmosphere. CO affects human health very drastically. It hard bond with hemoglobin (Hb) molecule and forming carboxyhemoglobin (COHb). As a result, the oxygen-carrying capacity of the blood is reduced. Hb's a nity for CO is higher than an a nity for oxygen, i.e., 210 to 300 times higher than its a nity for oxygen.

source appropriation of BC and CO
The aethalometer model was used to determine the major sources of BC in ambient air. While the projected model was characterized by a few selective source-categories like tra c emission and wood-burning. According to SAFAR 2010, the primary sources of BC were coal burning, and it is the highest source of energy that supplies 76% of our requirement in India. The origins of BC aerosols and CO may have the same, but their source apportionment techniques are different. According to a previous study, it was observed that the analysis of BC measured at 370 nm (UV) wavelengths and 880 nm (near-IR) wavelengths were made, which is favorable for the source identi cation of BC mass concentration (Sivastava et al. 2012). There are two types of processes for sources of BC mass concentration. One is anthropogenic activities like biomass burning for agriculture, coal burning, burning of fossil fuel, vehicular movements, and another natural process like volcanic eruptions, forest res, etc. Still, fossil fuel and wood-burning are the major sources. The source differentiates between wood-burning and fossil fuel in different cities were different, as shown in Fig. 6. In JSR city, the fossil fuel contribution was approx. 60 % and wood-burning contribution approx. 40 % toward the source appropriation of BC mass concentration. In KGP city, the fossil fuel contribution was approx. 57.57 % and wood-burning contribution approx. 42.42 % toward the source appropriation of BC mass concentration. Fossil fuel contribution was higher in JSR city as compared to KGP city. It indicates that the tra c load was increased in JSR city than the KGP city of East India.

Backward trajectories analysis
The back trajectories were calculated for both the cities. Backward trajectory analysis helps to understand the sources and transport pathways of air pollutants. It also determines the air ow direction to describe the possible source regions before they reach a speci c target. The trajectories were prepared with the help of Igor software. The trajectories data were taken from the Climate Forecast System, and Meteorological Data Explorer developed by the Centre for Global Environmental Research (CGER), Japan and a global environmental dataset online program National Centers for Environmental Prediction (NCEP). Backward trajectories plots are shown in Fig. 5. The back air trajectory analysis indicates that air masses' transport originates from different places from different heights. It can be noticed that air-borne particulate (maybe air pollutants) is transported from the northern part of India. In the JSR region, air masses originated over the north of Jammu and Kashmir, Delhi, Haryana, Punjab, and Uttar Pradesh before entering the eastern state Bihar and some part Jharkhand. Some trajectories also suggest the transport from the north-east states of India. Transport of air masses originated over neighboring countries like Pakistan, Nepal and Bhutan can also be noticed. In the KGP region, maximum air particulate matter was coming from the northern state, i.e., from Delhi, Haryana, Punjab, Uttarakhand and Uttar Pradesh eastern state Bihar, Jharkhand and some part of West Bengal. It was also seen that air particulate matter again came from the north-east state, i.e., from Arunachal Pradesh, Assam and other states. Air particulate matter was also coming from some other countries Bangladesh, Nepal, and Bhutan. The backward air trajectories were shown in Fig. 6.

Correlation between BC and CO
BC and CO are emitted from incomplete combustion of carbon-based fuels (Wang et al. 2015). The concentrations of both BC and CO in JSR city were higher than those in KGP city. As shown in the scatter plot (Fig-7.b), the concentrations of BC and CO show an excellent positive correlation (r 2 = 0.653) with an average slope (∆BC/∆CO) of 6.125 g BC/g CO. The BC-CO correlation parameters determined for different sites are presented in Table 4. The previous studies reporting good correlations between BC mass concentration and CO concentration are mainly due to proximate of familiar sources such as tra c emission. Emissions from petrol-fueled vehicles are known to be fewer sources of BC and CO compared to dieselfueled cars. An earlier study on automobile exhausts has suggested that light-duty petrol engines emit lesser amounts of BC and CO than heavy-duty vehicles such as diesel trucks (Chen et al. 2001). Far away from the sources, the measurements over the Northern Indian Ocean (Arabian Sea) also suggested a strong positive correlation (r 2 = 0.71) between BC and CO concentrations with a slope of 27.103 g BC/ g CO [49] (Bracero et al., 2002). According to Chen et al. (2001), BC mass concentration and CO concentration are strongly correlated along with an annual average slope of 3.48103 g BC/ g CO [50]. As shown in Fig. 7.a., we observed a strong positive correlation (r 2 = 0.97) between BC and PM 2.5 mass concentrations, suggesting their commons emission sources at both the sites. Figure 4. indicated the variation of BC mass concentration and CO concentration at two different East India cities. As the winter season start, BC mass concentration was starting to increase in both the cities. This is maybe the reason for crop residue burning in the nearest village area of these two cities. Where, Temp. = Temperature (°C), Hum. = Humidity (%), W.S = Wind Speed (km/s) and SD = Standard Deviation. Where, PM 2.5 concentrations in µgm − 3 ; BC mass concentration in µgm − 3 ; and CO concentration in pbbv  Figure 1 Satellite aerial view (Google Earth) of the sampling area and location of two different cities of Jamshedpur (JSR) and Kharagpur (KGP) in the eastern part of India. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.    do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.  Scatterplot of (a) the BC-PM2.5 correlations and (b) the BC-CO correlation during study period at two different cities of East India.