Size-segregated particulate matter and its association with respiratory deposition doses among outdoor exercisers in Dhanbad City, India

ABSTRACT

Regular exercise improves physiological processes and yields positive health outcomes. However, it is relatively less known that particulate matter (PM) exposure during outdoor exercises may increase several respiratory health problems depending on PM levels. In this study, the respiratory deposition doses (RDDs) in head airway (HD), tracheobronchial (TB), and alveolar (AL) regions of various PM size fractions (<10, <2.5, and <1 μm; PM₁₀, PM_2.5, and PM₁) were estimated in healthy male and female exercisers in urban outdoors and within house premises. The highest RDDs were found for PM during morning hours in winter compared with remaining periods. RDDs in AL region for males and females, respectively, were 34.7 × 10⁻² and 28.8 × 10⁻² µg min⁻¹ for PM₁₀, 65.7 × 10⁻² and 56.9 × 10⁻² µg min⁻¹ for PM_2.5, and 76.5 × 10⁻² and 66.3 × 10⁻² µg min⁻¹ for PM₁. The RDD values in AL region were significantly higher in PM₁ (27%) compared with PM_2.5 (13%) and PM₁₀ (2%) during exercise in all periods. This result showed that the morning peak hours in winter are more harmful to urban outdoor exercisers compared with other periods. This study also showed that the AL region would have been the main affected zone through fine particle (PM₁) to all the exercisers.

Implications: Size-segregated particle concentrations in urban outdoors and within house premises were measured. The highest respiratory deposition doses (RDDs) were found for PM during morning hours in winter compared with remaining periods. During light exercise, the RDD values in alveolar (AL) region for PM₁₀, PM_2.5, and PM₁ for male exercisers were significantly higher, 20.4%, 15.5%, and 15.4%, respectively, compared with female exercisers during morning peak hours in winter.

Introduction

Physical inactivity poses a significant health risk to individuals, as it increases the likelihood of developing heart disease, diabetes, cancer, and stroke (Blair, 2009). It is estimated that physical inactivity is the fourth most common cause of mortality and contributes to 3.2 million deaths annually (World Health Organization [WHO], 2009). Millions of people daily walk or run on the streets, parks, open terrace, and within house premises as part of their routine exercise. Regular exercise is known to improve physiological processes and is considered key to good health. In many modern societies, exercises have become increasingly popular (Aydin et al., 2014). Several persons undertake outdoor light exercises such as walking, jogging, and cycling during the morning and evening peak hours. Engaging in physical activity requires oxygen intake, with the demand for oxygen increasing as exercise intensity increases. This means that exercising outdoors may increase the number of pollutants inhaled into the respiratory system.

There are three possible reasons exercisers could be at increased health risk of inhaling large amount of air pollutants. Firstly, there is the increasing quantity of pollutants inhaled with an increase in minute ventilation during exercise. Secondly, a larger fraction of pollutants is inhaled through the mouth during exercise, effectively bypassing nasal mechanisms for the filtration of large particles and soluble vapors. Thirdly, the increased airflow carries pollutants deeper into the respiratory tract. Furthermore, pulmonary diffusion capacity has been shown to increase with exercise (Turcotte et al., 1992). Particulate matter (PM) is the one of the six U.S. Environmental Protection Agency (EPA)-regulated air pollutants and is a widespread acknowledged threat to human health (Harrison et al., 2001; Lonati and Giugliano, 2006; WHO, 2006; Brook, 2008; EPA, 2009; Pant and Harrison, 2013; Mehta et al., 2016; Segalin et al., 2017).

Daigle et al. (2003) have reported that PM fraction (especially ultrafine) is greatly deposited in the airways during exercise compared with rest. The total deposition of particles tends to be greater in male compared with female (Oravisjarvi et al., 2011). The greater total deposition with exercise may enhance the adverse PM effects. People exercising in a polluted environment, especially sensitive ones, such as asthmatics, children, and elderly people, are particularly vulnerable to air pollution effects (WHO, 2013). Such exposure can inflame airways and worsen asthmatic responses (Zhao et al., 2016) and trigger health problems or exacerbate existing ones such as asthma (McConnell et al., 2002), cardiovascular disease (Delfino et al., 2005; Berger et al., 2006; Nawrot et al., 2011; Heal et al., 2012), and cancer (Giles et al., 2014), leading to premature death (Beelen et al., 2014). All-cause daily mortality is estimated to increase by 0.2–0.6% per 10 µg m⁻³ of PM₁₀ (PM with aerodynamic diameter <10 μm; WHO, 2006). Long-term exposure to PM_2.5 (PM with aerodynamic diameter <2.5 μm) is associated with an increased cardiopulmonary mortality by 6–13% per 10 µg m⁻³ of PM_2.5 (Pope et al., 2002; Krewski et al., 2009). The exposure to air pollutants has been found to vary with age, gender, time spent in the different microenvironment, meteorological condition, socioeconomic status, and preexisting health conditions (Pope, 2000; Pant et al., 2016).

A recent study conducted in the Dhanbad area stated that PM concentration was higher than the National Ambient Air Quality Standard (NAAQS) prescribed by the Central Pollution Control Board (CPCB) for India (Dubey et al., 2012; Gupta and Elumalai, 2017). This study focuses mainly on the relationship between PM concentration in the urban outdoors and its association with respiratory deposition doses (RDDs) during morning and evening peak hours among male and female exercisers. To the best of the authors’ knowledge, this is the first study of the association between PM concentration and respiratory problems among outside exercisers in Dhanbad City.

Study area and methodology

Measurement site locations and study subjects

The present study was conducted in Dhanbad (23.8°N, 86.45°E) metropolitan area (population around 1.16 million, as per 2011 census) located in the state of Jharkhand, India. It is a part of Chotanagpur Plateau and mainly known as “the Coal Capital of India” and is the third largest city in Jharkhand State (Figure 1). It is among the top 100 fastest-growing cities of the world (Singh et al., 2015). Dhanbad climate is typically hot and tropical type with three distinct seasons, i.e., summer, monsoon, and winter. A detailed description of the study area and climatic condition have been reported by Dubey et al. (2012) and Singh et al. (2016). Dhanbad City includes several major shops, hotels, banks, restaurants, and busy roads. Dhanbad has many small towns located within the city as residential areas. Central Pollution Control Board (CPCB) in consultation with the Ministry of Environment, Forests and Climate Change, Government of India, has declared Dhanbad as a critically polluted area (CPCB, 2009). For the purposes of this study, we have chosen 707 people (414 male and 293 female) who regularly exercise in urban outdoors and 525 people (329 male and 196 female) who reported to be doing exercise within their house premises for physical and respiratory health status. Both of the groups lived in the Dhanbad City.

Figure 1. Map showing the monitoring stations in urban outdoor and within house premise locations in Dhanbad City.

Monitoring parameters, time schedule, and health status

Ten study locations were identified to monitor PM concentration, where exercisers spent their time (urban outdoors and within house premises). These locations were divided into two categories: such as five for urban outdoors and five groups of residences where the exercisers live. Out of 88 residences studied, 74 were apartments whereas 14 visited detached houses, these residences were a double- and a single-story building. All these residences were naturally ventilated through open windows and doors. In Dhanbad City, only few people have air conditioners or heating systems. Most of the residences use liquefied petroleum gas cylinders for cooking purposes. Particulate concentration was monitored with an optical particle counter (Grimm model 1.109; Grimm Aerosol Technik GmbH & Co. KG, Ainring, Germany; Burkart et al., 2010). Temperature and relative humidity were measured by using a portable instrument Q-Trak (TSI model 7575x; Shoreview, MN, USA). The wind speed was recorded by a portable anemometer (Kestrel model 4500; Nielsen-Kellerman, Boothwyn, PA, USA). Ambient meteorological parameter was collected from an automatic weather station installed at Indian Institute of Technology (Indian School of Mines) Dhanbad campus. The coefficients of divergence (CODs) were applied to sites within study areas as a relative measure of PM concentration uniformity (refer to Supplemental Materials).

Monitoring was carried out from 7 November 2013 through 23 February 2014 (31 days in winter) and between 2 April and 22 June 2014 (24 days in summer) in Dhanbad City, during the morning (7:00 a.m. to 11:00 a.m.) and evening (4:00 p.m. to 8:00 p.m.) peak hours. However, in every residence, we have monitored pollutant data within 20–30 min during peak hours. Based on the 24-hr online ambient PM monitoring (online data provided via the regional office of Jharkhand State Pollution Control Board, Dhanbad), the peak hour campaign was performed between 7:00 a.m. and 11:00 a.m. (morning) and between 4:00 p.m. and 8:00 p.m. (evening), shown in Figure S1.

The study assessed the reported respiratory problems of the surveyed exercisers and noted the same through a questionnaire. A questionnaire-based survey and PM monitoring were conducted on the same day. Urban outdoor and within house premise exercisers were screened by an initial questionnaire to identify regular exercise using the question: “Are you regularly doing exercise in the last two years for 30 minutes in morning and evening peak hours?” If the exerciser’s answer was “yes,” then they were considered as regular exercisers and were surveyed the physical and respiratory health status. Those who reported “no” were excluded from this study. Each subject was examined once, and the health symptoms were assessed at the same time during exercise. The exercisers in both groups were in the category of middle-class socioeconomic status (Bairwa et al., 2012).

Estimation of the respiratory deposition doses

We calculated the RDDs for an elderly male and an elderly female during a light exercise and a seated position using eq 1, which is adapted from International Commission on Radiological Protection (ICRP; 1994) and has been used by earlier studies (Azarmi and Kumar, 2016; Kumar and Goel, 2016; Segalin et al., 2017).

(1)

where V_T is the tidal volume (m³ per breath), f is the typical breathing frequency (breath per minute), DF_i is a deposition fraction of a size fraction i, and PM_i was the mass concentration in different size ranges. The DF for head airways was calculated using eq 2, given by Hinds (1999).

(2)

where d_p is particle size in µm and IF is the inhalable fraction as used by ICRP model (eq 3).

(3)

The deposition fraction for the tracheobronchial region is given by eq 4.

(4)

The deposition fraction for the alveolar region is given by eq 5.

(5)

The V_T values and f depend on the person’s gender and physical activity. For light exercise, V_T and f were considered equal to 12.5 × 10⁻⁴ (9.9 × 10⁻⁴) m³ per breath and 20 (21) breaths per minute for male (female), respectively. For seated position, V_T and f were considered equal to 7.5 × 10⁻⁴ (4.6 × 10⁻⁴) m³ per breath and 12 (14) breaths per minute for male (female), respectively (Hinds, 1999).

Student’s t test was used to compare the mean values of age, height, weight, and body mass index (BMI) among outdoor and within house exercisers. Chi-square test was used to test the significance of respiratory symptoms. Linear regression model was used to predict the trend of RDDs in head airway (HD), tracheobronchial (TB), and alveolar (AL) regions with higher or lower (outdoor/within house) concentrations of PM. The RDD values in HD, TB, and AL regions were used as the dependent variable and concentrations of PM fractions as the independent variable. All the calculations were performed using SPSS 20 software package (IBM, Armonk, NY, USA) and Microsoft Excel 2013 (Redmond, WA, USA).

Results and discussion

Physical characteristics and respiratory health status of exercisers

Physical characteristics and respiratory health status of surveyed exerciser groups (male and female) at urban outdoors and within house premises are shown in Table 1. An overwhelming majority of exercisers (male and female) were nonsmokers (86.7 %). A significant difference was observed in physical characteristics (height, weight, and BMI; P < 0.01) between urban outdoor and within house premise exercisers. Outdoor exercisers reported more respiratory symptoms compared with within house exercisers. The most frequently reported were cold (male: 9.18% and female: 8.87%) and headache (male: 9.66% and female: 7.60%) symptoms during the outdoor workout. The most frequent largest respiratory symptoms that were observed for outdoor exercisers may be due to higher PM concentrations in the urban outdoor environment (Kesavachandran et al., 2015). Significant differences were found in the physical characteristics of the exercisers in Dhanbad (P < 0.01). No significant difference in the respiratory symptoms was observed between both of the groups of exercisers (Table 1). Meteorology plays a crucial role in the distribution of particulate pollution; therefore, the meteorological condition is also a threat to urban outdoor exercisers (Branis et al., 2009).

Table 1. Physical characteristics and self-reported respiratory health status of exercisers in Dhanbad.^a

	Urban outdoors		Within house premises
Characteristic	Males	Females	Males	Females
Completed survey (%)	88	72	69	61
Rejected survey (%)	12	28	31	39
Number of exercisers to response (n)	414	293	329	196
Demographic characteristics, mean ± SD (range)
Age (years)	34.8 ± 4.9	31.4 ± 4.6	35.4 ± 4.9^b	33.1 ± 5.0
	(27.4–43.8)	(24.8–41.3)	(25.4–43.5)	(27.4–40.3)
Height (cm)	169.4 ± 2.5	156.1 ± 4.2	168.9 ± 2.0	156.8 ± 6.6
	(165–174)	(150–165)	(167–173)	(146–170)
Weight (kg)	72.5 ± 6.8	53.8 ± 5.2	66.8 ± 8.8	52.2 ± 5.9
	(58.1–82.3)	(45.2–64.3)	(44.2–75.6)	(42.0–64.2)
Body mass index (kg m^−2)	24.5 ± 2.7	22.1 ± 2.69^b	23.3 ± 3.03^b	21.3 ± 2.6
	(20.8–27.7)	(18.8–26.5)	(15.8–26.2)	(16.4–25.3)
Education (years of schooling)	14.3 ± 2.6	13.0 ± 2.6	15 ± 2.9	13.3 ± 2.4
	(10–21)	(10–20)	(12–21)	(10–17)
Nonsmoking (%)	75.3	98.6	74.1	98.8
Respiratory health status, n (%)^#
No symptoms	224 (54.11)	180 (61.43)	213 (64.74)	138 (70.41)
Breathless	21 (5.07)	11 (3.75)	14 (4.26)	5 (2.55)
Cold	38 (9.18)	26 (8.87)	27 (8.21)	15 (7.65)
Cough	26 (6.28)	16 (5.46)	16 (4.86)	9 (4.59)
Cold and cough	36 (8.70)	18 (6.14)	19 (5.78)	11 (5.61)
Cough and breathless	29 (7.00)	19 (6.48)	15 (4.56)	8 (4.08)
Headache	40 (9.66)	23 (7.85)	25 (7.60)	10 (5.10)

^aP < 0.01.

^bP < 0.05.

^#Nonsignificant different in respiratory health status.

Particulate matter variability and role of meteorological condition

The mass concentrations of PM₁₀, PM_2.5, and PM₁ in urban outdoors and within house premises are shown in Table 2. PM was observed at high levels across all monitoring locations compared with the recommended permissible levels for the Indian standard (NAAQS). The PM concentrations show a remarkable microenvironmental variability, with the highest in urban outdoors than observed in the within house premises. The urban outdoors is associated with enhanced anthropogenic emissions from the fossil fuel burning, transportation, and suspended dust. The PM concentrations depict seasonal variability, with the significantly highest during the winter and the lowest during the summer (P < 0.01) (Table 2). The wintertime maxima are associated with fuel combustion, biomass burning, and unfavorable meteorological condition (stagnant weather and temperature inversion during the cold) for pollution dispersion. In addition to accumulation of primary emissions, new particle formation and secondary production could further enhance fine PM abundance (Huang et al., 2014). As a result, the PM concentration minima were observed in summer, due to favorable weather conditions (higher temperature and wind speed) for PM dispersion (Zhang and Cao, 2015).

Table 2. Summary statistics of peak hours (morning and evening) PM concentrations.

	Concentration (µg m^−3)
	Urban outdoors			Within house premises
Monitoring period	PM10 ± SD (min–max)	PM2.5 ± SD (min–max)	PM1 ± SD (min–max)	PM10 ± SD (min–max)	PM2.5 ± SD (min–max)	PM1 ± SD (min–max)
Winter (7 November 2013 to 23 February 2014)
Morning peak hours (7:00 a.m. to 11:00 a.m.)	717 ± 233	296 ± 58	225 ± 36	289 ± 84	138 ± 37	117 ± 23
	(446–991)	(199–431)	(149–314)	(138–429)	(88–229)	(78–197)
Evening peak hours (4:00 p.m. to 8:00 p.m.)	538 ± 92	196 ± 43	134 ± 35	195 ± 69	97 ± 26	72 ± 74
	(320–797)	(105–308)	(70–186)	(104–391)	(58–150)	(44–112)
Summer (2 April to 22 June 2014)
Morning peak hours (7:00 a.m. to 11:00 a.m.)	290 ± 89	117 ± 42	81 ± 28	85 ± 27	58 ± 11	48 ± 9
	(172–538)	(66–177)	(47–125)	(33–121)	(26–88)	(20–77)
Evening peak hours (4:00 p.m. to 8:00 p.m.)	208 ± 45	74 ± 31	49 ± 22	51 ± 18	32 ± 15	25 ± 15
	(133–456)	(54–135)	(36–91)	(27–89)	(17–81)	(13–71)

The PM shows significantly higher concentrations and pronounced diurnal variations during morning peak hours in winter and summer (Figure S2). One reason for the higher morning exposure may be denser traffic during the morning. The PM concentration values reached a minima in the early morning hours (earlier 7:00 a.m.) before human activities start in urban outdoors. There was a slightly steady increasing trend from early morning to 8:00 to 9:00 a.m., followed by decreasing trend until noon. The PM concentration values again increased from noon to the late evening period, depicted in Figure S2. The diurnal variations in these measurements were expected, with temperature and wind speed increasing from sunrise to noon. From noon, these conditions declined until sunset. As expected, the trend in relative humidity was opposite that of the other meteorological parameters, decreasing during daytime and increasing during the evening to nighttime (Figure S3).

Respiratory deposition doses

PM exposure of the exercisers in urban outdoors and within house premises was assessed for the RDD values (HD, TB, and AL regions) for elderly males and females during light exercise and seated position (Figure 2). We observed higher RDD values in males than females for the same physical activity. This result was expected because males have a larger inhalator V_T than females and hence inhale higher concentrations of PM (Hinds, 1999; Azarmi and Kumar, 2016; Segalin et al., 2017). This difference in intakes of males was also largely related to the larger bodies than females; for instance, the males in our study were 13 cm taller and 17 kg heavier than females. However, Jaques and Kim (2000) have reported particle deposition affected by structural and/or geometrical differences of airways. Therefore, study showed higher particle deposition in the females than the males. The RDD values were higher during the light exercise than the seated position, because the activity increases the breathing frequency and hence increases the PM deposition in the respiratory tract (Hinds, 1999).

Figure 2. The levels of respiratory deposition doses (RDDs) of PM fractions in three regions of the exercisers’ respiratory tracts: head airway (HD), tracheobronchial (TB), and alveoli (AL), (a, b) in urban outdoors and (c, d) within house premises during light exercise (a, c) and in seated position (b, d) during morning and evening peak hours in winter and summer seasons. M/W = morning, winter; E/W = evening, winter; M/S = morning, summer; E/S = evening, summer; Me = male; Fe = female.

According to the expressions given in Study Area and Methodology, all particles (100%) are expected to enter the respiratory tract through the nose or mouth. However, as IF decreases with increasing particle diameter, the IF of coarse particle (PM₁₀) is expected to decrease. The deposition of fine particle is more significant in AL regions. RDDs in HD region showed elevated levels during winter morning (due to large increase of PM) to light exercise and seated position people. The RDDs observed (values of female subjects in parentheses) included 14.5 (12.1) µg min⁻¹ for PM₁₀, 4.9 (4.2) µg min⁻¹ for PM_2.5, and 1.5 (1.3) µg min⁻¹ for PM₁ to males and females during the light exercise. However, during seated position the values observed were 5.2 (3.6) µg min⁻¹ for PM₁₀, 1.8 (1.3) µg min⁻¹ for PM_2.5, and 0.58 (0.41) µg min⁻¹ for males and females. The TB region showed 0.27 (0.23) µg min⁻¹ for PM₁₀, 0.43 (0.37) µg min⁻¹ for PM_2.5, and 0.15 (0.13) µg min⁻¹ for PM₁ to males and females during the light exercise. However, during seated position the values observed were 0.10 (0.07) µg min⁻¹ for PM₁₀, 0.16 (0.12) µg min⁻¹ for PM_2.5, and 0.05 (0.04) µg min⁻¹ for PM₁ to males and females. The AL region showed 0.77 (0.66) µg min⁻¹ during light exercise and during seated position the value observed was 0.25 (0.18) µg min⁻¹ for PM₁ to males and females (Figure 2). This result showed that the AL region would have been the main affected zone through fine particle (PM₁) to exercisers. Overall, the RDD values in AL region were significantly higher in PM₁ (27%) compared with PM_2.5 (13%) and PM₁₀ (2%) during exercises (Figure 3).

Figure 3. Percentage distribution of RDD values in HD, TB, and AL regions for (a) PM₁₀, (b) PM_2.5, and (c) PM₁ during exercise. HD = head airway; TB = tracheobronchial; AL = alveolar.

We have compared RDD values between males and females for physical activity during different periods, as shown in Table S1. Higher differences in RDD values were observed in winter morning in males and females during light exercise and seated position in urban outdoors. For example, In AL region, during winter morning, observations (RDD values of female subjects in parentheses) were 0.21 (0.17) µg min⁻¹ for PM₁₀, 0.41 (0.35) µg min⁻¹ for PM_2.5, and 0.32 (0.27) µg min⁻¹ for PM₁, higher for males and females during light exercise. However, during the seated position, observations included 0.07 (0.05) µg min⁻¹ for PM₁₀, 0.15 (0.11) µg min⁻¹ for PM_2.5, and 0.08 (0.07) µg min⁻¹ for PM₁ for males and females. This finding supports the concern that the morning peak hours in winter are more harmful to urban outdoor exercisers compared with other periods. Some researchers have confirmed that outdoor exercise exacerbates several health problems (Carlisle and Sharp, 2001; Kesavachandran et al., 2015; Segalin et al., 2017).

Through the investigations of the RDDs with respect to respiratory symptoms of exercisers in different polluted environments, it is found that positive correlations exist between particulate pollution with various symptoms. In the linear regression analysis, all variables were selected under the condition of 99% confidence interval and predicted health risk in different environments. The higher predicted values of RDDs were found in urban outdoors, which means that the risk of exercisers can increase in outdoor environments (Table 3).

Table 3. Predicted values of HD, TB, and AL regions for outdoor and within house premise exercisers with respect to PM₁₀, PM_2.5, and PM₁.

		HD			TB			AL
PM fraction	Location	Predicted	R^2	SE	Predicted	R^2	SE	Predicted	R^2	SE
PM10	Urban outdoors	5.26	0.65	2.03	0.45	0.59	0.21	0.06	0.78	1.50
	Within house premises	1.87	0.74	0.04	0.17	0.65	0.18	0.004	0.84	0.28
PM2.5	Urban outdoors	1.21	0.64	0.05	1.71	0.74	1.21	1.73	0.65	1.20
	Within house premises	0.58	0.73	0.79	0.81	0.68	0.10	1.38	0.74	0.71
PM1	Urban outdoors	0.49	0.74	0.21	0.87	0.74	0.05	1.46	0.78	0.54
	Within house premises	0.26	0.71	0.24	0.49	0.81	0.04	0.79	0.81	0.35

Note. HD = head airway; TB = tracheobronchial; AL = alveolar.

Based on the study results, it is evident that the location or site at which exercise is done is the deciding factor for increases in RDDs. People doing exercise in urban outdoors inhale the maximum amount of PM compared with other groups. Similarly, the season also has significant impact on RDDs. Winter morning is not the ideal time to do exercise because the highest RDDs were observed during that time and season. These findings were well supported by the health outcome survey and predicted values of RDDs (Table 1 and Table 3) in different environments.

Conclusion

This study shows that the mean values of measured PM concentrations exceeded the NAAQS, India, in urban outdoors and within house premises. The findings suggest that people who exercise outdoors could be exposed to higher PM concentrations. The RDDs in HD, TB, and AL regions of all size-segregated PM were found to be higher for males than for the females during light exercise and seated position, mainly because the respiratory rate is higher in males than females during both activities. During outdoor exercise, there is an increase in the depth of breathing process. The particulates inhaled during breathing settle onto the respiratory tract lining during exercise and do not get exhaled, thereby causing severe respiratory health problems. The loss of respiratory defenses due to continuous exposures to air pollutants may increase the load of the pollutants during exercise. The present study shows that urban outdoor exercise can lead to reduced lung functions among exercisers in the Dhanbad City. Based on the study outcome, it may be advised that outdoor exercise whenever possible in the early morning before 7:00 a.m. is safer and one should try to avoid peak hours. It may be advised that people regularly exercising outdoors restrict such activities during adverse conditions such as winter season or near air pollution sources such as urban roadways. It may also be advised that for regular exercise, asthmatics or those with respiratory problems must restrict exercise to indoors or the gym during adverse conditions such as winter season and urban roadways.

Acknowledgment

The authors acknowledge the Department of Environmental Science and Engineering, Indian Institute of Technology (Indian School of Mines) (IIT [ISM]), Dhanbad, for providing the logistic supports. The authors also acknowledge Jharkhand Space Association Center for sharing meteorological data from the weather station installed in IIT (ISM) campus. The authors also thank sincerely the regional office of Jharkhand State Pollution Control Board, Dhanbad, for providing 24-hr online ambient air quality data. The authors thank Mr. Sanjeet Singh and Mr. Rinkesh Meena (B.Tech. students, batch 2012–2016) in the Department of Environmental Science and Engineering, IIT (ISM), Dhanbad, for their help in conducting a survey.

Supplemental data

Supplemental data for this article can be accessed on the publisher’s website.

Additional information

Notes on contributors

Sunil Kumar Gupta

Sunil Kumar Gupta is a senior research scholar at Department of Environmental Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, India.

Suresh Pandian Elumalai

Suresh Pandian Elumalai is an assistant professor at Department of Environmental Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, India.