Pre-to-post Diwali air quality assessment and particulate matter characterization of a western coastal place in India

Abstract

Diwali has become an occasion of air and noise pollution, and the release of particulate matter and toxic gases has chronic and acute effects on people and their environment. Thus, an air quality assessment study was done by CSIR-CSMCRI covering the pre-to-post Diwali 2021 period (5 days) in the three locations (traffic, residential, and control) of Bhavnagar. The average 24-h concentration of PM10 (380 µg/m³), PM2.5 (182.2 µg/m³), and SPM (403 µg/m³) was significantly higher during Diwali, exceeding the National Ambient Air Quality Standards (NAAQS). The concentrations of SO₂ and NO₂ were 121.8 µg/m³ and 102.1 µg/m³. Metals like Zn, Al, Pb, and Mn were found in higher concentrations during the study. The air quality index (AQI) was maximum on Diwali, resembling very poor air quality. More elements and oxides were detected in PM2.5 (S, Al, Mg, Ba, and Zn and their oxides) than in PM10 (Fe and S) through WDXRF. Water-soluble anions like SO₄²⁻, Cl⁻, and NO₃⁻ were observed during the study, with a higher SO₄²⁻ (64%) on Diwali. The PM10 morphology and mapping of elements were done using SEM–EDX. Emerging contaminants, specifically phthalate groups, were detected through GCMS. The enrichment factor (EF) showed Zn and Pb originating from anthropogenic activities. The air quality data was validated using a variance test, least significance difference (LSD), correlation, and principal component analysis (PCA). This paper is the first to highlight the air quality assessment during Diwali for a western coastal place in India. It is time to implement regulations on burning firecrackers for pollution reduction, aiming to achieve a sustainable atmosphere.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10661-023-11018-x.

Introduction

Diwali, the festival of light, is celebrated all over India with much pump and ceremony by every community. It brings happiness, love, and prosperity to society. Nowadays, the matter of concern is that the festival of light has been converted into a pollution (both air and noise) inducing event. The primary reason behind the toxicity of this beautiful celebration is the overuse of firecrackers.

Firecrackers consist of four parts: fuel, oxidizers, colorants, and binders. Charcoal and sulfur are used as fuel during fireworks. Oxidizers are used with fireworks since they require a lot of oxygen to ignite. They release free oxygen, which helps in the improvement of explosion. The three most frequently utilized oxidizers are nitrates, chlorates, and perchlorates. The combination of fuel and oxidizers creates a blast during a firework. Gunpowder (a mixture of 5% potassium nitrate, 15% charcoal, and 10% sulfur) is the principal element of firecrackers. Different metals like Na, Ba, Sr, Al, and Cu are used as coloring materials to create yellow, green, purple, white, and blue, respectively (Kulshreshtha et al., 2021). It has been reported that burning firecrackers causes air pollution by producing different toxic gases like sulfur dioxide, carbon dioxide, carbon monoxide, particulate matter (PM10 and PM 2.5), and traces of metals (Wang et al., 2007). According to a report, up to 23–33% of the ambient PM10 is contributed by aerosol from fireworks. As a result, it produces short-term cardiovascular illnesses and chronic exposure diseases, affecting the population (Vijayakumar et al., 2021). Wheezing, respiratory infections, bronchial asthma flare-ups, and chronic obstructive pulmonary disease (COPD) instances have all increased by 30–40% during the Diwali celebration in India (Shah et al., 2019). When fireworks are set off at a greater altitude, the pollutants they release are diluted before they reach people, which can positively impact their health. However, ground-level fireworks have an immediate negative influence on public health (Garaga & Kota, 2018). Not only air pollution but also noise pollution is caused during the Diwali period. Compared to non-festive days, the average noise level in residential and commercial areas increases by 29.6 and 18.1% in Haridwar (Sharma & Joshi, 2010). It has been reported by Mahecha et al. (2012) that during Diwali, the average equivalent noise level in residential and commercial areas of Jaisalmer hiked from 61.94 to 72 dB (A) to 64.68 to 73.74 dB (A), respectively.

Bhavnagar, a small district, is situated in the Saurashtra area of Gujarat. It experiences dry summers (March to mid-June), wet monsoons (mid-June to October), and winters (November to February). Most of the time, Bhavnagar faces air pollution issues due to particulate matter. The people of Bhavnagar welcome every festival; during Diwali, the celebration lasts for 5 days, which alters the ambient air quality due to burning more firecrackers. Based on the above view, CSIR-CSMCRI has carried out an ambient air quality assessment of Bhavnagar (a western coastal place of India) for 5 days (pre-to-post Diwali) based on three strategic locations (identified as traffic, residential, and control sites). The objectives were (i) particulate pollutant (PM10, PM2.5, and SPM) variation; (ii) gaseous pollutant (SO₂, NO₂, NH₃, and O₃) variation; (iii) heavy metal detection (using ICP-MS) in particulate pollutants; (iv) validation of data using statistical tools like correlation, PCA, analysis of variance, and LSD; (v) estimation of air quality index (AQI) for the study period; (vi) elemental and oxides presence (using WDXRF) in particulate pollutants; (vii) determination of water-soluble anions on PM10 filter paper; (viii) SEM–EDX Analysis to map dominant elements presence in particulate pollutants; (ix) emerging contaminants detection (using GCMS) in particulate pollutants; and (x) enrichment factor. This paper offers information in all these dimensions and reports on five days of study covering pre-to-post Diwali. This paper is the first of its kind highlighting the air quality assessment during the mega festival Diwali for a western coastal place in India. Moreover, new findings like elements and oxide analysis from particulate matter using WDXRF, emerging pollutants detection from particulate matter through GCMS, and AQI for Diwali have been addressed in this paper.

Materials and methods

Sampling locations

The air sampling locations during pre to post-Diwali were carried out at three different areas of Bhavnagar, a western coastal place of India. The three locations are categorized into traffic (S1), residential (S2), and control (S3) (Fig. 1), respectively. Two leading commercial establishments, Nirma industry and Alang shipyard (the world's largest shipbreaking yard), are located in the north and south parts of the sampling locations.

Fig. 1.

Topography of air sampling locations during the study: S1, traffic (21° 45′ 32.22″ N 72° 8′ 39.22″ E); S2, residential (21° 45′ 12.24″ N 72°8′ 38.73″ E); S3, control (21° 34′ 32.65″ N 72° 15′ 45.28″ E)

PM10

Particulate Matter (PM₁₀) was monitored using Spectro, respirable dust sampler model (SLE-RDS103). The PM10 was measured by the gravimetric method using Whatman filter paper (20.3 × 25.4 cm). Air is drawn through a filter at a flow rate typically 1132 L/min. The filter collects parts with aerodynamic diameters less than the cut-point of the inlet. The mass of these particles is determined by the difference in filter weights before and after sampling. The concentration of PM₁₀ in the designated size range is calculated by dividing the weight gain of the filter by the volume of Air sampled.

PM2.5

The fine dust sampler model (NPM-FDS, 2.5A) from NETEL (India) Limited measures PM2.5 by a gravimetric method. An electrically powered air sampler takes ambient air into a specifically constructed inertial particle size separator (i.e., cyclones or impactors) where the suspended particulate matter in the PM2.5 size range is separated for collection on a 47-mm polytetrafluoroethylene (PTFE) filter over a microprocessor over a specified sampling period. Each filter is weighed before and after sample collection to determine the net gain due to the particulate matter. The mass concentration in the ambient air is computed as the total mass of collected particles in the PM_2.5 size ranges divided by the actual volume of air sampled and is expressed in μg/m³.

SO₂

The SO₂ was measured by the West and Gaeke method (IS 5182 part 2 method of measurement of air pollution: sulfur dioxide) (CPCB, 2013). Sulfur dioxide from air is absorbed in a potassium tetrachloromercurate (TCM) solution. A dichlorosulphitomercurate complex, which resists oxidation by the oxygen in the air, is formed. Thirty milliliters of absorbing solution was placed by impinger with a 1 L/m flow rate for eight hours. Once formed, this complex is stable to strong oxidants such as ozone and nitrogen oxides; therefore, the absorber solution may be stored for some time before analysis. The complex reacts with pararosaniline and formaldehyde to form the intensely colored pararosaniline methyl sulphonic acid. The absorbance of the solution is measured at 560 nm using a suitable spectrophotometer (model no. CARY 500 scan).

NO₂

The NO₂ was measured by the modified Jacob and Hochheiser method (IS 5182 Part 6 Methods for Measurement of Air Pollution: Oxides of nitrogen) (CPCB, 2013). Air bubbles are passed through a sodium hydroxide and sodium arsenite solution to collect ambient nitrogen dioxide. Reacting the nitrite ion with phosphoric acid, sulfanilamide, and N-(1-naphthyl)-ethylenediamine dihydrochloride (NEDA) and measuring the absorbance of the intensely colored azo-dye at 540 nm, the concentration of nitrite ion produced during sampling is determined colorimetrically using a spectrophotometer (model no. CARY 500 scan).

Heavy metals in PM10

The presence of the heavy metals in PM10 glass fiber filter paper was analyzed by acid digestion using ICP-MS “iCAP-RQ, Thermo Scientific” (CPCB, 2013). Using a stainless steel pizza cutter, an 8″ × 10″ filter was cut into 1″ × 8″ strips. Plastic forceps were used to transfer the filter into a beaker. The extraction solution (3% HNO and 8% HCl) was added to the filter, and the beaker was appropriately covered. The beaker was placed within a fume hood on a hot plate (below 80 °C) and gradually refluxed for 30 min while being covered with a watch glass. From the hot plate, the beakers were removed and left to cool; the beaker walls were cleaned and rinsed with distilled water. Approximately 10 mL of reagent water was added to the leftover filter material in the beaker and was left to stand for at least 30 min. Then, the sample was extracted, filtered, and analyzed for heavy metals present in the filter paper (CPCB, 2013).

Benzene and benzo (a) pyrene

Benzene (C6H6) and benzo(a)pyrene (BaP) were performed in GCMS by soaking filter papers in toluene following the procedure outlined in BIS method IS 5182 (Part-12): 2004 (CPCB, 2013).

Water-soluble anions by IC

A test tube with a stopper that holds 50 mL of ultrapure water and 15 mL of each exposed filter paper was placed in an ultrasonic bath. The soluble components were separated by centrifuging at 2500 rpm for 10 min. The supernatant solution was filtered twice using membrane filters made of nylon and hydrophilized poly(tetrafluoroethylene) with pore diameters of 0.45 m and 0.2 m, respectively, and then refrigerated until analysis for water-soluble anions like Cl⁻, NO₃ ⁻, and SO₄ ²⁻ were studied using an ion chromatograph (Mahapatra et al., 2013), “Model no. DIONEX ICS-5000⁺ DC”.

Noise level monitoring

The noise level was monitored (CPCB, 2015) in selected study areas day and night. The noise level was recorded using HTC SL-13A mini sound meter. The noise level is measured parallel (with 2-h intervals) at all the stations from 6 AM to 10 PM (daytime) and 10 PM to 6 AM (nighttime).

CO and CO₂

CO and CO₂ were measured using the Lutron CO meter (GCO-2008) and Lutron CO2 meter (GC-2028), respectively, at selected study areas.

SEM–EDX analysis

The PM10 Filter paper was examined by FE-SEM coupled with EDX to study the particulate matter’s surface morphology and elemental analysis. The PM10 filter paper was cut and fixed on the stubs with the help of carbon tape. Then the sample was vacuumed and analyzed by the SEM–EDX (model no. JSM-7100F).

Elements and oxides

The presence of elements and oxides in PM10 and PM 2.5 filter paper was examined using WD-XRF (model: Bruker S8 TIGER II). The 1/6th part of exposed PM 10 filter paper was crushed into the finest form using motor pastel (porcelain make) and mixed with boric powder (binding agent) uniformly. The mixture was pressed and turned into a pellet to analyze elements and oxide presence by complete analysis vac-34 mm method. Likewise, the PM 2.5 filter paper was analyzed using disposable sample cups to detect the presence of elements and oxides on the filter papers.

Meteorological parameters

The meteorological data like relative humidity (RH), average temperature (AT), wind speed (WS), and precipitation have been collected from “www.wunderground.com,” for the 5 days of the study period. No precipitation was observed during the study period. The wind rose diagram was plotted using the software WR plot while considering meteorological data like wind speed, wind velocity, and precipitation.

Statistical analysis

To conduct the statistical analysis, SPSS (Version 22) was used (Chanchpara et al., 2021; Mohanty et al., 2015). Analysis of variance with a single factor and the null hypothesis was used to determine whether there is a significant difference between the pre- and post-Diwali period for various air pollutants. The significance of the difference between two pairs of different groups is assessed using the least significant difference (LSD). Instead of calculating t for each pair, we calculated the LSD at the desired significance level (α = 0.05). The PCA was undertaken to elucidate the inter-relationship between different air quality parameters. The mean and standard deviation was calculated using Microsoft Office Excel 2010.

The experimental data were gathered in triplicates, and the average value was interpreted with an error inside ± 5%.

Results and discussion

Diwali is a mega event celebrated nationwide. The general public starts the celebration 2 days before Diwali and continues for the next 2 days. Thus, in our study, we are covering 2 days before and 2 days later, including the day of Diwali, to estimate the ambient air quality of Bhavnagar.

Table 1 represents a comparative study of air pollutants (particulate matter and trace gases) during Diwali across India. The particulate matter (PM10 and PM2.5) is significantly higher than the National Ambient Air Quality Standards (NAAQS) prescribed by the CPCB. The toxic gases like SO₂ and NO₂ of Bhavnagar city and Lucknow are more than the permissible value. From Table 1, we can assume the severity of air pollution occurred due to over-burning firecrackers nationwide during Diwali. CSIR-CSMCRI has carried out an ambient air quality assessment of Bhavnagar during pre-to-post Diwali 2021 (for 5 days), and the average values for various parameters are shown in Table 1; similarly, the results of earlier work for the years 2017 and 2019 of Bhavnagar city have also been represented. Comparatively, the pollutant concentration has been decreasing in recent years, which may be due to increasing awareness of pollution among people or the prolonged impact of COVID-19.

Table 1.

Comparison of various air pollutants during the day of Diwali across India

Study area	Study period	PM10 (µg/m3)	PM2.5 (µg/m3)	SO2 (µg/m3)	NO2 (µg/m3)	O3 (µg/m3)	NH3 (µg/m3)	References
Lucknow city	November 2005	753.3	-	139.1	107.3	-	-	(Barman et al., 2008)
IGI airport, Delhi	November 2012	573	-	-	-	-	-	(Sati & Mohan, 2014)
Bhilai city	November 2012	-	1501.2	-	-	-	-	(Pervez et al., 2016)
Jamshedpur city	October 2014	500.5	-	8.6	73.3	53.3	-	(Ambade, 2018)
Delhi city	November 2015, October 2016	-	308.8, 766.5	-	-	-	-	(Shivani et al., 2019)
Ahmedabad city	October 2017	213.9	82.8	-	-	-	-	(Chhabra et al., 2020)
Bhavnagar city	October 2017	523.8	410.4	80.1	56.7	45.9	56.3*	Earlier study
Prayagraj city	November 2018	158	-	-	-	-	-	(Kulshreshtha et al., 2021)
Bhavnagar city	October 2019	623.3	325.6	156.3	102.5	42.6	98.6*	Earlier study
Lucknow city	November 2020	558	352	44	86	-	-	(Saxena et al., 2022)
Bhavnagar	November 2021	468.9	263.6	135.9	96.8	23.1	96.3*	Present study
NAAQS	-	100	60	80	80	180*	400	(CPCB, 2009)

*1 h. Here, the data represents the concentration of air pollutants observed for the day, i.e., Diwali

Particulate pollutants

When the pollutant concentration in the atmosphere becomes high, it becomes hazardous and causes an acute effect on humans and the environment. The air quality monitoring during pre-to-post Diwali, 2021 is monitored, and the result is shown in Table 2. The 24-h average particulate matter (PM10) concentration was found to be 380 µg/m³ during Diwali and 130.3 µg/m³ in the day 4 (post-Diwali) period. The resulting values were higher than the NAAQS for PM10 particulate matter (100 µg/m³). Similarly, the PM10 concentration during Diwali is much higher than the annual concentrations of coastal cities of Gujarat (ranging from 90 to 140 µg/m³) (CPCB, 2019), which highlights the pollution caused due to burning of firecrackers. The PM₁₀ concentration was five to six times higher than in the pre-Diwali period. The comparative PM10 result from pre-to-post Diwali is shown in Fig. 2. The aerosol is released into the ambient air due to crackers burning and persists in the atmosphere for a long time and enhances the PM10 mass during Diwali. This is the reason why in the post-Diwali period, the PM10 value was found to be higher than in the pre-Diwali period. The average 24-h particulate matter having a size of 2.5 or less was observed to be very high during Diwali compared to the pre-Diwali event. During Diwali, the PM2.5 were valued to be 182.2 µg/m³, which is alarming, very high than the NAAQS, i.e., 60 µg/m³. Similarly, the PM2.5 concentration during Diwali is much higher than the annual concentrations of coastal cities of Gujarat, i.e., < 40 µg/m³ (CPCB, 2019). Moreover, the SPM (suspended particulate matter) concentration was found to be hiked, i.e., 403 µg/m³, during the Diwali event. The trend of PM2.5 and SPM from pre-to-post Diwali is displayed (Fig. 2). Generally, Diwali falls with the start of the winter season where adverse ambient situations like high humidity, decreasing temperature, and calm winds were observed; moreover, decreasing mixing height prevents the distribution of the pollutants.

Table 2.

Pre-to-post Diwali ambient air quality values observed at different locations in 2021

Parameters	Day	S1, traffic	S2, residential	S3, control	Mean	STD	Max	Min
PM10 (µg/m3)	Day 1 (pre-Diwali)	121.5	62.5	38.6	74.2	34.8	121.5	38.6
	Day 2 (pre-Diwali)	112.9	49.8	36.9	66.5	33.2	112.9	36.9
	Day 3 (Diwali)	468.9	358.6	312.6	380.0	65.6	468.9	312.6
	Day 4 (post-Diwali)	168.9	123.5	98.6	130.3	29.1	168.9	98.6
	Day 5 (post-Diwali)	109.6	75.3	42.6	75.8	27.4	109.6	42.6
PM2.5 (µg/m3)	Day 1 (pre-Diwali)	75.6	43.9	24.6	48.0	21.0	75.6	24.6
	Day 2 (pre-Diwali)	69.8	31.5	21.4	40.9	20.8	69.8	21.4
	Day 3 (Diwali)	263.6	126.9	156.2	182.2	58.8	263.6	126.9
	Day 4 (post-Diwali)	89.3	68.6	56.9	71.6	13.4	89.3	56.9
	Day 5 (post-Diwali)	69.4	35.6	26.9	44.0	18.3	69.4	26.9
SPM (µg/m3)	Day 1 (pre-Diwali)	201.3	109.6	65.3	125.4	56.6	201.3	65.3
	Day 2 (pre-Diwali)	235.8	125.6	96.8	152.7	59.9	235.8	96.8
	Day 3 (Diwali)	498.3	385.6	326.9	403.6	71.1	498.3	326.9
	Day 4 (post-Diwali)	265.6	234.8	126.9	209.1	59.5	265.6	126.9
	Day 5 (post-Diwali)	189.8	125.3	115.8	143.6	32.9	189.8	115.8
SO2 (µg/m3)	Day 1 (pre-Diwali)	56.9	38.9	12.6	36.1	18.2	56.9	12.6
	Day 2 (pre-Diwali)	63.5	42.8	11.6	39.3	21.3	63.5	11.6
	Day 3 (Diwali)	135.9	126.8	102.6	121.8	14.1	135.9	102.6
	Day 4 (post-Diwali)	89.6	56.2	35.6	60.5	22.3	89.6	35.6
	Day 5 (post-Diwali)	48.9	41.3	46.8	45.7	3.2	48.9	41.3
NO2 (µg/m3)	Day 1 (pre-Diwali)	48.6	29.6	21.3	33.2	11.4	48.6	21.3
	Day 2 (pre-Diwali)	42.6	36.9	25.6	35.0	7.1	42.6	25.6
	Day 3 (Diwali)	96.8	112.6	96.8	102.1	7.4	112.6	96.8
	Day 4 (post-Diwali)	92.3	86.9	68.3	82.5	10.3	92.3	68.3
	Day 5 (post-Diwali)	52.6	48.6	56.7	52.6	3.3	56.7	48.6
NH3 (µg/m3)	Day 1 (pre-Diwali)	36.3	30.6	28.9	31.9	3.2	36.3	28.9
	Day 2 (pre-Diwali)	23.7	21.5	19.8	21.7	1.6	23.7	19.8
	Day 3 (Diwali)	96.3	78.5	70.3	81.7	10.9	96.3	70.3
	Day 4 (post-Diwali)	57.9	48.2	36.9	47.7	8.6	57.9	36.9
	Day 5 (post-Diwali)	46.7	31.6	30.8	36.4	7.3	46.7	30.8
O3 (µg/m3)	Day 1 (pre-Diwali)	40.3	35.8	20.4	32.2	8.5	40.3	20.4
	Day 2 (pre-Diwali)	36.5	28.9	15.6	27.0	8.6	36.5	15.6
	Day 3 (Diwali)	23.1	26.9	18.6	22.9	3.4	26.9	18.6
	Day 4 (post-Diwali)	56.3	38.1	26.4	40.3	12.3	56.3	26.4
	Day 5 (post-Diwali)	20.5	19.2	15.6	18.4	2.1	20.5	15.6
C6H6 (µg/m3)	Day 1 (pre-Diwali)	0.45	0.88	0.87	0.7	0.2	0.9	0.5
	Day 2 (pre-Diwali)	0.61	3.11	0.92	1.5	1.1	3.1	0.6
	Day 3 (Diwali)	1.83	0.65	1.45	1.3	0.5	1.8	0.7
	Day 4 (post-Diwali)	n/d	2.43	0.05	1.2	1.2	2.4	0.1
	Day 5 (post-Diwali)	1.14	0.03	0.9	0.7	0.5	1.1	0.0
CO (ppm)	Day 1 (pre-Diwali)	n	n	7	n/a	n/a	n/a	n/a
	Day 2 (pre-Diwali)	n	n	10	n/a	n/a	n/a	n/a
	Day 3 (Diwali)	n	n	4.2	n/a	n/a	n/a	n/a
	Day 4 (post-Diwali)	n	n	8	n/a	n/a	n/a	n/a
	Day 5 (post-Diwali)	n	n	6.3	n/a	n/a	n/a	n/a
CO2 (ppm)	Day 1 (pre-Diwali)	n	n	245	n/a	n/a	n/a	n/a
	Day 2 (pre-Diwali)	n	n	375	n/a	n/a	n/a	n/a
	Day 3 (Diwali)	n	n	373	n/a	n/a	n/a	n/a
	Day 4 (post-Diwali)	n	n	315	n/a	n/a	n/a	n/a
	Day 5 (post-Diwali)	n	n	326	n/a	n/a	n/a	n/a
Noise (day) dB (A)	Day 1 (pre-Diwali)	56.5	36	43.2	45.2	8.5	56.5	36.0
	Day 2 (pre-Diwali)	62.5	42.5	36.2	47.1	11.2	62.5	36.2
	Day 3 (Diwali)	60.3	43.2	36.3	46.6	10.1	60.3	36.3
	Day 4 (post-Diwali)	63.2	50.8	36.7	50.2	10.8	63.2	36.7
	Day 5 (post-Diwali)	61.2	41.2	31.9	44.8	12.2	61.2	31.9
Noise (night) dB (A)	Day 1 (pre-Diwali)	62.3	45	55.3	54.2	7.1	62.3	45.0
	Day 2 (pre-Diwali)	60.3	50.5	40.3	50.4	8.2	60.3	40.3
	Day 3 (Diwali)	69.7	50.5	57.5	59.2	7.9	69.7	50.5
	Day 4 (post-Diwali)	68.9	56.3	42.5	55.9	10.8	68.9	42.5
	Day 5 (post-Diwali)	65.7	55.7	43.7	55.0	9.0	65.7	43.7
AT (°C)	Day 1 (pre-Diwali)	28.8
	Day 2 (pre-Diwali)	28.4
	Day 3 (Diwali)	27.7
	Day 4 (post-Diwali)	28.5
	Day 5 (post-Diwali)	28.5
RH (%)	Day 1 (pre-Diwali)	43
	Day 2 (pre-Diwali)	43
	Day 3 (Diwali)	51
	Day 4 (post-Diwali)	60
	Day 5 (post-Diwali)	60
WS (mph)	Day 1 (pre-Diwali)	2
	Day 2 (pre-Diwali)	3
	Day 3 (Diwali)	4
	Day 4 (post-Diwali)	4.6
	Day 5 (post-Diwali)	2.7

Benzo(a)pyrene (BaP) (ng/m³) is not detected in PM10 filter paper

Daily average values are considered for RH and WS. Concentrations of parameters like PM10, PM2.5, SPM, SO₂, NO₂, and C₆H₆ are considered for 24 h, whereas NH₃ and O₃ are considered for 1 h. Noise, the average values were considered

n/d not detected, n/a not applicable, n not done, AT average temperature, RH relative humidity, WS wind speed

Fig. 2.

Variation of particulate air pollutants observed during pre-to-post Diwali 2021

Gaseous pollutants

While burning the firecrackers, trace gases like NO₂, SO₂, O₃, and NH₃ were observed. The ambient 24-h average SO₂ and NO₂ concentration in the atmosphere of Bhavnagar from pre-to-post Diwali, 2021, is given in Table 2. The SO₂ (121.8 µg/m³) and NO₂ (102.1 µg/m³) concentrations during Diwali were higher compared with the NAAQS (80 µg/m³). Similarly, the NO₂ and SO₂ concentrations during Diwali are much higher than the annual concentrations of coastal cities of Gujarat, i.e., < 30 µg/m³ (NO2) and < 25 µg/m³ (SO2) (CPCB, 2019). In the presence of particulate matter, higher SO₂ would create harmful effects. The SO₂ accumulates on the surface of the fine particles and gets the way to enter our body through the lungs. The SO₂ concentration was high during Diwali than NO₂. The SO₂ and NO₂ changing concentrations from pre-to-post Diwali are shown in Fig. 3. Ozone, a greenhouse gas molecule that can attack and irritate the lungs, is one of the byproducts of fireworks. The ultraviolet light generated by chemicals in fireworks is thought to cause the O₃ formation. During the study period, O₃ concentration was observed within the NAAQS, i.e., 180 µg/m³ (Table 2). Likewise, the 1-h NH₃ reading is shown in Table 2, and the highest concentration of NH₃, i.e., 81.7 µg/m³, is observed in the post-Diwali period. During our 5 days of observation from pre-to-post Diwali, the NH₃ concentration was found to be within range. The trend of O₃ and NH₃ values from the pre-to-post Diwali period is shown in Fig. 3.

Fig. 3.

Variation of gaseous air pollutants observed during pre-to-post Diwali 2021

Other pollutants

Benzene concentration during the study period ranged from 0.7 to 1.5 µg/m³ (Table 2), possibly due to vehicular movement and industrial activity. Benzo(a)pyrene (BaP) was not detected during the study period. During the study, the noise level was observed to be higher in the nighttime compared with the day, as the Diwali celebration is at night. The noise on the day of Diwali ranged from 36.3 to 60.3 dB (daytime) and 50.5 to 69.7 dB (nighttime), respectively.

Meteorological observations

The metrological condition plays an important role in pollutant dispersion. The parameters like daily average temperature, relative humidity, and rainfall of the monitoring period (pre-to-post Diwali) are given in Table 2. The wind direction and wind speed during the study period were displayed in the wind rose diagram (Fig. 4) created by using the software WR plot. The major wind direction during pre-to-post Diwali was observed from the northeast and east directions, with speeds ranging from 0.5 to 3.60 m/s (meters per second). The calm wind (having no wind speed) was obtained to be 25% for day 1 (pre-Diwali), 12.50% for day 2 (pre-Diwali), 25% for day 3 (Diwali), 12.50% for day 4 (post-Diwali), and 25% for day 5 (post-Diwali). The lowest wind speed was observed during Diwali, with high humidity and low temperature. The ambient condition affects the dispersion of pollutants by decreasing the mixing height in the atmosphere. This may cause pollutant deposition in the lower atmosphere and hamper public health and the environment.

Fig. 4.

Wind rose highlighting meteorological conditions during pre-to-post Diwali 2021

Metal concentration

The metals like Al, Mn, Zn, Se, Cd, and Pb were observed during the pre-to-post Diwali period. The metals like Zn, Al, Pb, and Mn were found in higher concentrations during the study; 28.87 µg/m³ of Al and 2.15 µg/m³ of Pb were found during Diwali (Table 3). The Zn was high during the 5-day study period, and the highest value was observed in the pre-Diwali period. Likewise, the Pb concentration was higher in the pre-Diwali period than in Diwali, which may be due to the transportation and dispersion of pollutants from vehicular emissions and industrial establishments (like chemical industries in Surat, textile industries in Vadodara, Alang Ship breaking yard in Bhavnagar, and Nirma industry in Bhavnagar) located in the surrounding and eastern part of the sampling stations (Fig. 1); moreover, the flow of wind from east to west during pre-Diwali period played a significant role (Fig. 4). The Pb concentration in Diwali and pre-Diwali (day 2) has exceeded the NAAQS (1 µg/m³). The average 24-h reading of all the detected metals is given in Table 3. Burning crackers and sparklers during Diwali might be the reason for the presence of metals like Al, Zn, Pb, and Mn on PM10 filter paper.

Table 3.

Heavy metal detection in PM10 filter paper through ICP-MS during pre-to-post Diwali 2021

Parameters	Study time	S1, traffic	S2, residential	S3, control	Mean	STD	Max	Min
Al (µg/m3)	Day 1 (pre-Diwali)	8.36	18.80	12.90	13.35	5.23	18.80	8.36
	Day 2 (pre-Diwali)	13.91	2.09	6.53	7.51	5.97	13.91	2.09
	Day 3 (Diwali)	47.29	39.11	0.20	28.87	25.16	47.29	0.20
	Day 4 (post-Diwali)	2.62	18.55	12.90	11.36	8.08	18.55	2.62
	Day 5 (post-Diwali)	18.91	0.37	− 2.05	5.75	11.47	18.91	− 2.05
Mn (µg/m3)	Day 1 (pre-Diwali)	0.33	0.84	0.10	0.42	0.38	0.84	0.10
	Day 2 (pre-Diwali)	1.11	0.33	0.36	0.60	0.44	1.11	0.33
	Day 3 (Diwali)	0.55	0.71	0.10	0.45	0.31	0.71	0.10
	Day 4 (post-Diwali)	0.10	0.71	0.10	0.30	0.35	0.71	0.10
	Day 5 (post-Diwali)	0.33	0.19	0.09	0.20	0.12	0.33	0.09
Cu (µg/m3)	Day 1 (pre-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
	Day 2 (pre-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
	Day 3 (Diwali)	0.22	0.20	n/d	n/a	n/a	0.22	0.20
	Day 4 (post-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
	Day 5 (post-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
Zn (µg/m3)	Day 1 (pre-Diwali)	29.11	65.20	23.36	39.22	22.68	65.20	23.36
	Day 2 (pre-Diwali)	160.35	58.69	132.43	117.16	52.52	160.35	58.69
	Day 3 (Diwali)	88.28	59.55	20.54	56.12	34.00	88.28	20.54
	Day 4 (post-Diwali)	46.04	95.03	74.87	71.98	24.62	95.03	46.04
	Day 5 (post-Diwali)	101.47	23.89	17.75	47.70	46.67	101.47	17.75
Se (µg/m3)	Day 1 (pre-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
	Day 2 (pre-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
	Day 3 (Diwali)	n/d	0.20	n/d	n/a	n/a	0.20	0.20
	Day 4 (post-Diwali)	0.60	n/d	0.20	n/a	n/a	0.60	0.20
	Day 5 (post-Diwali)	0.44	n/d	n/d	n/a	n/a	0.44	0.44
Cd (µg/m3)	Day 1 (pre-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
	Day 2 (pre-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
	Day 3 (Diwali)	0.22	n/d	n/d	n/a	n/a	0.22	0.22
	Day 4 (post-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
	Day 5 (post-Diwali)	n/d	n/d	n/d	n/a	n/a	0.00	0.00
Pb (µg/m3)	Day 1 (pre-Diwali)	0.33	0.56	0.30	0.40	0.14	0.56	0.30
	Day 2 (pre-Diwali)	4.23	1.32	2.66	2.74	1.46	4.23	1.32
	Day 3 (Diwali)	3.52	2.82	0.10	2.15	1.81	3.52	0.10
	Day 4 (post-Diwali)	0.20	1.21	0.20	0.54	0.58	1.21	0.20
	Day 5 (post-Diwali)	1.32	0.09	0.19	0.53	0.68	1.32	0.09

Heavy metals like V, Cr, Co, Ni, As, and Hg are not detected in PM10 filter paper

n/d not detected, n/a not applicable

Statistical analysis

Analysis of variance (ANOVA)

The results obtained during pre-to-post Diwali 2021 were validated using analysis of variance single factor. Particulate and gaseous air pollutants were considered to see the occurrence of significant differences between pre-Diwali (day 1), pre-Diwali (day 2), Diwali (day 3), post-Diwali (day 4), and post-Diwali (day 5). A significant difference (p < 0.05) was observed between air quality parameters like PM10, PM2.5, SPM, SO₂, NO₂, and NH₃, whereas non-significant differences (p > 0.05) were observed between O₃, Pb, and C₆H₆ during pre-to-post Diwali period (Table 4) in whole.

Table 4.

Analysis of variance (ANOVA) for pre-to-post Diwali 2021 air quality parameters

	F value	P value	F critical	Remarks
PM10	21.74	6.4 × 10−5	3.48	Sig
PM2.5	7.40	0.004873	3.48	Sig
SPM	7.93	0.003792	3.48	Sig
SO2	8.42	0.003048	3.48	Sig
NO2	26.01	2.89 × 10−5	3.48	Sig
NH3	20.75	7.85 × 10−5	3.48	Sig
O3	2.28	0.132563	3.48	Non-Sig
Pb	2.87	0.079985	3.48	Non-Sig
C6H6	0.49	0.746024	3.48	Non-Sig

Sig significant, Non-Sig non-significant, α 0.05 (level of significance)

Least significance difference

The least significance difference (LSD) has been applied to know the presence of a significant difference between each pair (between 2 days of data) to draw a better conclusion about the observed result with α = 0.05 (desired level of significance). In the case of PM10, significant differences were observed between four pairs (day 1–day 3, day 2–day 3, day 3–day 4, and day 3–day 5) with a difference of mean values (DMV) of 305.83, 313.5, 249.7, and 304.2 greater than the LSD value of 90.3, respectively. Similar observations are seen in the case of PM2.5, SPM, and SO₂; however, for C₆H₆, non-significance differences were observed (Table 9, supplementary file).

Principal component analysis (PCA)

The PCA used in this study assisted in briefing the data gathered to a smaller set of essential, independent variables. It was used to determine the link within various air quality variables (PM10, PM2.5, SO₂, NO₂, Pb, SPM, NH₃, O₃, C₆H₆, AT, RH, and WS) during the experimental period. The correlation between the above variables is shown in Table 5, where PM10 establishes a positive correlation with PM2.5, SO₂, NO₂, SPM, NH₃, and WS, whereas it shows a negative correlation with AT, highlighting the meteorological influence. Variables like SO₂ positively correlate with NO₂, SPM, NH₃, and WS. Similarly, the above variables were accommodated within three components (Fig. 5). Component I explains 61.86 of the cumulative variance with an eigenvalue of 7.15, including variables (PM10, PM2.5, SO₂, NO₂, SPM, NH₃, and WS), presenting a positive correlation. Component 2 includes positively correlated Pb and C₆H₆, describing 80.27 cumulative variances and 2.29 as an eigenvalue. Component 3 comprises C₆H₆, O₃, and WS and describes 93.57 of cumulative variance and 1.77 as an eigenvalue.

Table 5.

Correlation matrix for various air quality parameters during pre-to-post Diwali 2021

Parameters	PM10	PM2.5	SO2	NO2	Pb	SPM	NH3	O3	C6H6	AT	RH	WS
PM10	1.00
PM2.5	0.99	1.00
SO2	0.99	0.99	1.00
NO2	0.86	0.86	0.90	1.00
Pb	0.37	0.36	0.35	0.10	1.00
SPM	0.99	0.99	0.99	0.89	0.42	1.00
NH3	0.97	0.97	0.97	0.93	0.14	0.96	1.00
O3	-0.21	-0.19	-0.21	0.04	-0.31	-0.17	-0.13	1.00
C6H6	0.33	0.33	0.35	0.30	0.83	0.43	0.17	0.20	1.00
AT	-0.92	-0.91	-0.93	-0.75	-0.66	-0.94	-0.82	0.40	-0.54	1.00
RH	0.10	0.09	0.19	0.53	-0.48	0.14	0.30	0.00	-0.24	-0.03	1.00
WS	0.54	0.53	0.60	0.84	0.16	0.63	0.60	0.36	0.58	-0.51	0.56	1.00

A correlation value > 0.5 is significant at a 0.05 level of significance (2-tailed)

Fig. 5.

Principal component analysis for various air quality parameters during pre-to-post Diwali 2021

Air quality index

Showcasing the data sets of various air pollutants and time series graphs must be more comprehensive to highlight an event’s air quality status. So it is the need of the hour to recognize a simple and effective representation of ambient air quality of a particular area, thereby creating public awareness w.r.t. the health implications caused by air pollution. The air quality index (AQI) is information about the number transformed from various pollutant concentration and associated health breakpoints. Depending on the value of AQI, the color-coded info transmitted to people indicates good, satisfactory, moderately polluted, poor, very poor, and severe air quality. It is estimated by calculating sub-indices of various pollutants (i.e., PM2.5, PM10, SO₂, NO₂, and Pb, considered for calculation), depending upon their health breakpoints (Table 6) and concentration. The air quality index of a particular station is calculated as the maximum of sub-indices, and the associated pollutant sub-index is a predominant parameter. The highest AQI was observed for Diwali (day 3) with PM2.5 as the predominant factor, and simultaneously the AQI was reduced towards day 5, which shows the self-cleaning activity of our nature.

Table 6.

Pre-to-post Diwali air quality index (AQI) of Bhavnagar for the year 2021

PM10, PM2.5, SO₂, NO₂, and Pb are considered for calculating AQI, and the concentration of these parameters is for 24 h

*Green color resembles the “satisfactory” category (AQI range: 51–100)

**Yellow color resembles the “moderately polluted” category (AQI range: 101–200)

***Orange color resembles the “poor” category (AQI range: 201–300)

****Red color resembles the “very poor” category (AQI range: 301–400)

Similarly, the AQI of different stations is also calculated (Table 10, supplementary file) during the pre-to-post Diwali period to see the variation in air quality. On day 1, for the control station (S3), the air quality category is “good” as per AQI, whereas the traffic station (S1) falls under the “moderately polluted” category. On day 2 and day 3, maximum pollution (severe category) was observed for the traffic station, and “very poor” (AQI category) air quality was monitored for residential (S2) and control station on day 3 (Diwali).

Element and oxide analysis using WDXRF

The PM10 filter paper was analyzed to detect the presence of elements and oxides using WDXRF. The elements like Fe, S, and Cl and oxides like SO₃ and Fe₂O₃ were found during the monitoring period of the pre-post-Diwali period. The elements and oxides’ presence on PM10 filter paper was given in Table 11, supplementary file. The elements like Fe and S are used in the manufacturing of firecrackers. Thus, it may be assumed that the overconsumption of firecrackers during the Diwali period is the reason for the appearance of elements and oxides of Fe and S in the ambient air.

Likewise, PM2.5 filter paper was also studied to detect element and oxides occurrence. In PM2.5 filter paper, elements like S, Al, Mg, Ba, and Zn and their respective oxides were found in ambient air during pre-to-post Diwali. The salt of these elements, like S, Al, Mg, Ba, and Zn, are the components of firecrackers (Yilmaz & karaman, 2017). Thus, burning firecrackers could be considered the source of these elements on PM2.5 filter paper. The element and oxides associated with PM2.5 filter paper are shown in Table 12, supplementary file. More presence of elements and oxides was observed in PM2.5 compared with PM10. Therefore PM2.5 is considered to be more hazardous to human health.

Water-soluble anions

The water-soluble anions like SO₄²⁻, Cl⁻, and NO₃⁻ are obtained in the ambient Air of Bhavnagar during the pre-to-post Diwali period, and the results are shown in Fig. 6. The SO₄²⁻ was got to be very high compared to NO₃⁻ and Cl⁻ ions throughout the study. During Diwali, SO₄²⁻ was observed to be high, i.e., (64%), followed by the post-Diwali period (day 4 and day 5). The sparkler and firecrackers contain sulfur which may contribute to the higher sulfate concentration in ambient air. The Cl and NO₃⁻ were found to be maximum in pre-Diwali (Day 2), i.e., 23 and 39%, respectively. The source of these three anions is mostly from firecrackers and vehicular emissions; a more calm and stable atmosphere enriches this inorganic ionic concentration in the ambient air during the study period.

Fig. 6.

Representing the presence of the water-soluble anion in ambient air during pre-Diwali to post-Diwali duration

SEM–EDX analysis

The electronic morphological image and spectra of major elements in PM10 filter papers during the study period are shown in Fig. 7a–c. The presence of particulate pollutants was observed by comparing the image of sampled filter paper with blank filter paper. The elements like C, S, Si, Al, Fe, Zn, and Ba were mainly detected in each sampled filter paper. The “S” presence in the sampled filter paper indicates the presence of sulfate released from burning firecrackers. Silicon (Si) and “C” were found almost in all filter paper. On day 2, the S3 image (Fig. 7b) and other images of the spongy portion are due to carbon particles (Mahapatra et al., 2013). The stable atmosphere hampers pollutant dispersion, which causes a higher pollutant presence even in the post-Diwali period. The presence of Al, Zn, and Ba was used in firecrackers as colorants. Thus, they were found to be observed during the monitoring period. More spectra of elements like Ca, Mg, Na, and K were observed during the pre-to-Diwali period. Firecrackers, vehicular emissions, roadside dust, and industrial zones beside Bhavnagar might contribute to pollutants.

Fig. 7.

Electron image for PM10 to see the attachment of elements during pre-to-post Diwali 2021 study for various stations. a Blank filter paper; day 1, S1; day 1, S2; day 1, S3; day 2, S1; day 2, S2 (color code: Al, red; Si, green, C, blue; S, yellow; Zn and Ti, sky blue; Fe, purple). b Day 2, S3; day 3, S1; day 3, S2; day 3, S3; day 4, S1; day 4, S2 (color code: Al, red; Si, green; C, blue; S, yellow; Zn, Ti, and Ba, sky blue; Fe, purple). c Day 4, S3; day 5, S1; day 5, S2; day 5, S3 (color code: Al, red; Si, green, C, blue; S, yellow; Zn and Ba, sky blue; Fe and Cl, purple)

Emerging pollutant analysis

The PM10 filter paper was analyzed using GC–MS, and some emerging contaminant peaks were recorded. Majorly organic compounds (pthalate group) were detected (Table 7). The pthalates like dibutyl pthalate, diisooctyl phthalate, and bis(2-ethylhexyl) phthalate were obtained. Not only this, 2,4-di-tert-butylphenol an antioxidant, was also found on PM10 filter paper. The highest percentage of 2,4-di-tert-butylphenol was obtained during Diwali. The primary source of these organic compounds may be dust, paint, pharmaceutical industries, and plastic and polymers.

Table 7.

Emerging pollutants identification in PM10 during pre-to-post Diwali 2021 using GCMS

Location		S1, traffic	S2, residential	S3, control
Compound name		(Area %)	(Area %)	(Area %)
Dibutyl phthalate	Day 1 (pre-Diwali)	1.05	0.18	nd
	Day 2 (pre-Diwali)	nd	0.22	1.17
	Day 3 (Diwali)	0.98	8.22	1.09
	Day 4 (post-Diwali)	nd	nd	1.57
	Day 5 (post-Diwali)	nd	nd	1.35
Diisooctyl phthalate	Day 1 (pre-Diwali)	2.63	0.27	2.56
	Day 2 (pre-Diwali)	0.53	nd	nd
	Day 3 (Diwali)	nd	1.06	nd
	Day 4 (post-Diwali)	nd	1.03	3.61
	Day 5 (post-Diwali)	0.74	nd	1.69
Bis(2-ethylhexyl) phthalate	Day 1 (pre-Diwali)	nd	nd	nd
	Day 2 (Pre-Diwali)	nd	nd	2.55
	Day 3 (Diwali)	6	nd	3.97
	Day 4 (post-Diwali)	nd	0.2	nd
	Day 5 (post-Diwali)	nd	nd	nd
2,4-Di-tert-butylphenol	Day 1 (pre-Diwali)	3.18	3.56	2.11
	Day 2 (pre-Diwali)	7.12	3.3	8.39
	Day 3 (Diwali)	10.68	5.47	6.54
	Day 4 (post-Diwali)	nd	0.09	2.27
	Day 5 (post-Diwali)	2.4	nd	nd

Enrichment factor

The enrichment factor (EF) is an approach to knowing the source of contaminants, whether naturally occurring or artificially released due to anthropogenic activity (Sari, 2008). In our work, we have considered Al as a reference element. The enrichment factor can be calculated by using the below-mentioned formula.

$$\frac{\left[E,l,e,m,e,n,t,,i,n,,s,a,m,p,l,e\right]/[Alinsample]}{\left[E,l,e,m,e,n,t,,i,n,,c,r,u,s,t\right]/[Alincrust]}=EnrichmentFactor$$

The enrichment factor of the elements detected on PM10 filter paper is given in Table 8. It has been reported that EF less than “10” represents crustal sources. In contrast, more than “10” show anthropogenic sources. The EF of Mn of the pre-to-post Diwali period was calculated to be less than 10. The EF of Zn and Pb was found to be very high (more than 10) for the monitored periods, signifying that they originate from anthropogenic activities.

Table 8.

Enrichment factor for metals found in particulate matter

Parameters	Study time	Element in the sample (%)	(Element/Al) sample	Element in crust (%)	(Element/Al) crust	EF
Mn (µg/m3)	Day 1 (pre-Diwali)	0.000042	0.031460674	0.085	0.010625	2.96
	Day 2 (pre-Diwali)	0.00006	0.079893475			7.52
	Day 3 (Diwali)	0.000045	0.015587115			1.47
	Day 4 (post-Diwali)	0.00003	0.026408451			2.49
	Day 5 (post-Diwali)	0.00002	0.034782609			3.27
Zn (µg/m3)	Day 1 (pre-Diwali)	0.003922	2.937827715	0.008	0.001	2937.83
	Day 2 (pre-Diwali)	0.011716	15.60053262			15600.53
	Day 3 (Diwali)	0.005612	1.943886387			1943.89
	Day 4 (post-Diwali)	0.007198	6.336267606			6336.27
	Day 5 (post-Diwali)	0.00477	8.295652174			8295.65
Pb (µg/m3)	Day 1 (pre-Diwali)	0.00004	0.029962547	0.002	0.00025	119.85
	Day 2 (pre-Diwali)	0.000274	0.364846871			1459.39
	Day 3 (Diwali)	0.000215	0.07447177			297.89
	Day 4 (post-Diwali)	0.000054	0.047535211			190.14
	Day 5 (post-Diwali)	0.000053	0.092173913			368.70

EF enrichment factor

Conclusion

The outcomes of this study show that during the 5 days of study (pre- to post-Diwali), the ambient air quality of Bhavnagar was worse due to the over-burning of firecrackers and sparkles, with maximum pollution on day 3 (Diwali). The average 24-h concentration of PM10 (380 µg/m³), PM2.5 (182.2 µg/m³), and SPM (403 µg/m³) was significantly higher during Diwali than the NAAQS. The concentrations of SO₂ and NO₂ were 121.8 µg/m³ and 102.1 µg/m³, respectively. The noise was high on the nighttime of the day Diwali (50.5 to 69.7 dB). Metals like Zn, Al, Pb, and Mn were observed from PM10 in higher concentrations during the study. The AQI (value 348) was observed to be maximum on Diwali, indicating air quality to be “very poor” (AQI category). Simultaneously, the AQI was observed to be decreasing on day 5, showing the self-cleansing activity of nature and the dispersion of pollutants. More elements like S, Al, Mg, Ba, and Zn and their respective oxides were detected in PM2.5 compared to PM10, highlighting the hazardousness of fine particles. Water-soluble anions like SO₄²⁻, Cl⁻, and NO₃⁻ were observed during the study. The electron image of particulate matter and elemental mapping (for C, Si, S, Fe, Ba, and Zn) was done using SEM–EDX. Various emerging contaminants, specifically phthalate groups, were detected through GCMS from particulate matter, which may be sourced from dust, building materials, plastic, and polymers. The enrichment factor showed Zn and Pb originating from anthropogenic activities. The air quality data was validated using statistical techniques like analysis of variance, LSD, correlation, and PCA. The release of particulate and gaseous pollutants due to the Diwali celebration persists in the atmosphere for a longer time, affecting public health and damaging the ecosystem. Thus, people should create awareness to celebrate the Diwali festival in an eco-friendly way. It is the need of the hour to implement regulations on burning firecrackers for pollution control and achieving a sustainable atmosphere.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contribution

Amit Chanchpara: Data curation and writing the original draft. Monali Muduli: Data curation and writing the original draft. Vinay Prabhakar: Data curation, review, and editing. Anil Kumar Madhava: Review and editing. Ravikumar Bhagwan Thorat: Review and editing. Soumya Haldar: Review and editing. Sanak Ray: Conceptualization, Visualization, review, editing, and supervision.

Data availability

The data will be made available on request.

Declarations

Competing interests

The authors declare no competing interests.

Ethical approval and consent to participate

The authors declare that they have no known competing financial interests or personal relationships that affect the work reported in this article.

Consent for publication

We do not have any person's data.