PM10 aerosols were monitored and analyzed for heavy metal concentration at Raipur city Chhattisgarh, India for possible source identification of pollutants. Sampling of PM10 aerosols was carried out by using respirable dust sampler during the year 2016. Daily PM10 average concentrations varied between 122.033 and 197.854 µg/m3, 91.350 and 133.950 µg/m3 and 112.770 and 480.170 µg/m3 in summer, monsoon and winter respectively. Chemical analysis of PM10 samples was carried out for heavy metal determination. Heavy metal (Fe, Mn, Ni and Pb) were analyzed with the help of atomic absorption spectroscopy (AAS) and found in the range of 2.713-36.862, 0.131-9.129. 0.880-4.195 and 0.015-0.321 µg/m3 for Fe, Mn, Pb and Ni respectively. PM10 concentrations shows distinct seasonal variation being twice in winter season than in summer; winter (mean: 241.820 ± 33.912 µg/m3) > summer (mean: 159.512 ± 14.360 µg/m3) > monsoon (mean: 107.480 ± 9.213 µg/m3). The concentration of heavy metal was different in all the seasons depending on their sources. Identification of possible sources was done by principal component analysis (PCA) illustrating industrial activities, soil (crustal) dust and biomass burning as the major sources in the region. The back trajectory analysis of the air masses depicts that the local anthropogenic activities affect the concentration of pollutants at the source. Correlation analysis between the heavy metal concentrations agreed the results obtained by PCA. The work helped in observing the seasonal trend of particulate matter concentrations and in identification of major sources of air pollution in the city.

Purpose The purpose of this study is to monitor suspended particulate matter (SPM), PM2.5 and source apportionment study for the identification of possible sources during the year 2018–2019 at Raipur, India. Design/methodology/approach Source apportionment study was performed using a multivariate receptor model, positive matrix factorization (PMFv5.0) with a view to identify the various possible sources of particulate matter in the area. Back-trajectory analysis was also performed using NOAA-HYSPLIT model to understand the origin and trans-boundary movement of air mass over the sampling location. Findings Daily average SPM and PM2.5 aerosols mass concentration was found to be 377.19 ± 157.24 µg/m³ and 126.39 ± 37.77 µg/m³ respectively. SPM and PM2.5 mass concentrations showed distinct seasonal cycle; SPM – (Winter ; 377.19 ±157.25 µg/m?) > (Summer; 283.57 ±93.18 µg/m?) > (Monsoon; 33.20 ±16.32 µg/m?) and PM2.5 – (Winter; 126.39±37.77 µg/m³) > (Summer; 75.92±12.28 µg/m³). Source apportionment model (PMF) have been applied and identified five major sources contributing the pollution; steel production and industry (68%), vehicular and re-suspended road dust (10.1%), heavy oil combustion (10.1%), tire wear and brake wear/abrasion (8%) and crustal/Earth crust (3.7%). Industrial activities have been identified as major contributing factor for air quality degradation in the region. Practical implications Chemical characterization of aerosols and identification of possible sources will be helpful in abatement of pollution and framing mitigating strategies. It will also help in standardization of global climate model. Originality/value The findings provide valuable results to be considered for controlling air pollution in the region.

Atmospheric aerosol affects local, regional, and global climate by directly absorbing and scattering the incoming and outgoing solar radiation [1], indirectly by altering the cloud microphysical properties [2], and semi-directly by reducing cloud coverage [3]. Aerosols also have an adverse impact on human health -particularly regarding respiratory and cardiovascular diseases [4]. Black carbon (BC) is a strongly light-absorbing component of the atmospheric aerosol, mainly PM 2.5 [5] formed during incomplete combustion of fossil fuels, biofuels, and biomass burning [6]. BC contributes to global warming [7][8] by possibly altering precipitation patterns [9] and melting glaciers due to snow albedo reduction [10]. Due to rapid urbanization and industrialization during the last decade, India and China are the largest BC emitters in the world, contributing 25 to 30% of global emissions of BC Pol. J. Environ. Stud. Vol. 26, No. 4 (2017), 1443-1451 , with 1.55 being the monthly average ratio for nighttime and daytime concentrations. Monthly average diurnal variation showed two distinct peaks, at morning with 39.84 µgm -3 (7:00-8:00 IST (Indian Standard Time)), and at night with 35.55 µgm -3 (00:00 -1:00 IST);and two distinct valleys, with lowest BC concentration (7.11 µgm , consistent with the nighttime average. A clear negative correlation between BC mass concentration and wind speed (r = -0.75), relative humidity (r = -0.30) and temperature (r = -0.19) was observed. The back-trajectory at surface level (50 m and 500 m) mostly originated from northeastern India, and for higher altitude (5,000 m), from Middle-Eastern and Arabian countries, except during the last week of December (Indian Ocean). The ratio and difference between BC mass measured at 370 nm and 880 nm showed biomass burning being the dominant cause at night.

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‘Good Outcomes from evil situation’ this phrase perfectly fits into the COVID-19 circumstances as several restrictions on anthropogenic activities provided an improvement in the ambient air quality status globally. The study deals with the consequences of COVID-19 lockdown on ambient air quality for 2 major industrial cities ( Raipur and Bilaspur) in Central Indian state Chhattisgarh moreover a comparison of air quality data was made with non-lockdown year (2019). The AQI and critical parameters (such as PM10, PM2.5, SO2 and NOx) were acquired form online available source and then analysed for the study period (2019 and 2020). Noteworthy reduction in AQI and concentration of pollutants in Raipur was detected whereas there was reduction in Bilaspur but it was less than Raipur. Evident changes in the level of pollutants (NOx and PM) were observed during the study. Meteorological parameters such as temperature and relative humidity were also examined for Raipur. Statistical analysis between data of meteorological parameters and AQI for capital city Raipur was also carried out.

A 1‐year PM10 sampling campaign from January 2019 to December 2019 is conducted in an urban industrial area Raipur, India. For the development of effective pollution control strategies, quantitative assessment of potentially toxic metals and accurate identification of pollutant sources are essential. The annual average PM10 aerosol mass concentration during the study period is recorded as 187.89 ± 91 µg m−3. PM10 concentrations are found to vary with meteorological parameters such as wind speed, temperature, rainfall, and humidity. Heavy metals including Fe, Mn, Ni, Pb, Zn, Al, Ba, Cr, Sr, Ga, Mg, and V are studied using atomic absorption spectroscopy (AAS). Seasonally, average winter time PM10 concentration (234.86 ± 104.3 µg m−3) is accounted higher as compared to summer (169.02 ± 27.1 µg m−3) and rainy season (106.28 ± 32.6 µg m−3) during the study period. The aerosol sources identified by positive matrix factorization (PMF) model are: iron and steel production (34.7%), vehicular emissions (29.3%), road dust (14.6%), heavy oil/petroleum (14.6%), and coal combustion (6.9%). Among these sources, iron and steel production contributes maximum in PM10 concentrations. The probable source locations are recognized through concentration weighted trajectory (CWT) analysis. The AirQ+ model is used to assess the health effects of regional PM10 concentrations.

Diwali is an important festival of India and a lot of firecrackers bursting take place in every part of the country during festive occasions. Short term effect of firecrackers on ambient air quality was assessed by monitoring suspended particulate matter (SPM) and heavy metal analysis (Fe, Zn, Pb, Mn and Ni) during Diwali festival at an urban-industrial city Raipur, India from 3rd November to 11th November 2018. The daily average SPM concentrations were found about two times higher on 7th November (Diwali-425.64 µg/m3) and 8th November (next day of Diwali- 417.92 µg/m3) as compared to 3rd November (pre Diwali day- 247.56 µg/m3). Heavy metal analysis (Fe, Zn, Pb, Mn and Ni) was carried out using atomic absorption spectroscopy (AAS) and found the same concentration trend in the order of Fe>Zn>Pb>Mn>Ni during day and night time. Significant increment in SPM and heavy metal concentrations has been observed post-Diwali. Back trajectory analysis revealed that trajectories at surface level (50 and 1000 m a.g.l) originated from local sources, depicting local anthropogenic activities like burning of firecrackers and industrial activities as major pollution source. Wind rose diagram depicts higher SPM concentration, when the wind was northeasterly. The present study reveals that pollution levels were considerably increased during Diwali and firecrackers bursting played a major role by contributing to air pollution.

Environmental noise has reached an alarming level and is affecting the exposed population. The noise levels are elevated during the festival season. This study aims to explore the influence of prime festivals on noise levels in an urban area. 18 locations in the Raipur city of Chhattisgarh, India, were selected for conducting the study during the Ganesh Utsav, Dussehra, and Diwali festivals. Study of equivalent noise level (Leq) and other noise parameters Traffic noise index (TNI), Noise Climate (NC), Noise exceeding 10% and (L10) and Noise exceeding 90% of measurement time (L90) were found for all three festivals in the A-weighted decibel scale (dBA). Noise maps from observed levels were prepared using the ArcGIS Inverse Distance Weighted (IDW) interpolation method. Noise levels ranged from 61.4 to 81.3 dBA during Ganesh Utsav, 63.5 to 79.9 dBA during Dussehra, and 70.1 to 81.2 dBA during the Diwali festival. All the locations recorded above 70 dBA during Diwali, whereas nearly 50 percent of the locations recorded above 70 dBA during Ganesh Utsav and Dussehra festivals. The urgent need to control the noise pollution in the Raipur city of Chhattisgarh by making strict rules is very much needed for making the ambient environment clean, green, and healthy.