Influence of localized sources and meteorological conditions on dry-deposited particles: A case study of Gabès, Tunisia.

This study investigates the spatial and temporal variations of dry-deposited particles on the surface (by turbulence or gravity) in various sites within Gabès city and its surroundings, South-eastern Tunisia. Monthly samples were collected from five distinct locations: suburban-industrial (S2), suburban-residential (S3), and urban sites (S1, S4, and S5). The average monthly particle deposition flows ranged from 7.35 ± 4.24 g/m2 to 14.41 ± 6.09 g/m2, with the suburban-industrial site (S2) exhibiting the highest deposition rates. They are lower than the reference value of 30 g/m2 in the AFNOR NF-X43-007, but much higher than the Swiss OPair standard (6 g/m2). Compared to the German standard (TALUFT; 10.5 g/m2), only S2 showed significant exceedances. Hierarchical cluster analysis revealed notable statistical affinities among the study sites. Heavy metal analysis indicated fluctuating concentrations across sites, with Zn being the most abundant, followed by Pb, Cu, Ni, and Cd. The enrichment factor (EF) and geoaccumulation index (Igeo) suggested varying degrees of contamination and pollution, highlighting the impact of anthropogenic sources. The findings underscore the need for targeted mitigation strategies to address particle deposition and heavy metal contamination in Gabès and similar regions globally.

Assessing variability and hydrochemical characteristics of groundwater fluoride contamination and its associated health risks in East Singhbhum district of Jharkhand, India.

Groundwater pollution caused by fluoride is a significant concern for the global population owing to its toxicity, which has negative health consequences. Industrial discharges, agricultural practices, and improper waste disposal are primary concerns in evaluating the degree of fluoride contamination in the selected districts of Eastern India. In a targeted area sampling approach, exactly 196 samples were collected during pre- and post-monsoon, and precise fluoride detection was performed using Ion-Selective Electrodes. Fluoride levels in pre-monsoon water were observed within a range of 0.02 to 2.7 mg/L, with an average abundance of 0.4 ± 0.50. In post-monsoon, the concentration ranged from 0.02 to 4.7 mg/L (mean 0.53 ± 0.60). The study found that 97 % of groundwater samples had acceptable fluoride levels within the 1.5 mg/L limit during pre and post-monsoon. Moreover, approximately 87 % of the samples exhibit fluoride content below the 1 mg/L limit. The hazard quotient was observed to be 0.17 to 0.58 in adults, 0.23 to 0.79 in children and 0.36 to 1.26 in infants during pre-monsoon, whereas 0.05 to 0.55 in adults, 0.12 to 0.74 in children and 0.11to 1.19 in infants during post monsoon. The above data indicates that infants had the highest risk of fluoride exposure, with a significant negative correlation between fluoride and calcium ions. Fluoride had minimal to no link with other ions, a modest positive correlation with sulfate, and a weak negative relationship with overall hardness and alkalinity across both seasons. The present study contributes towards the identification of fluoride levels in various areas, making society aware of water contamination and its health impacts.

Temporal dynamics of urban air pollutants and their correlation with associated meteorological parameters: an investigation in northern Indian cities.

This study delves into the intricate dynamics of air pollution in the rapidly expanding northern regions of India, examining the intertwined influences of agricultural burning, industrialization, and meteorological conditions. Through comprehensive analysis of key pollutants (PM2.5, PM10, NO2, SO2, CO, O3) across ten monitoring stations in Uttar Pradesh, Haryana, Delhi, and Punjab, a consistent pattern of high pollution levels emerges, particularly notable in Delhi. Varanasi leads in SO2 and O3 concentrations, while Moradabad stands out for CO levels, and Jalandhar for SO2 concentrations. The study further elucidates the regional distribution of pollutants, with Punjab receiving significant contributions from SW, SE, and NE directions, while Haryana and Delhi predominantly face air masses from SE and NE directions. Uttar Pradesh's pollution sources are primarily local, with additional inputs from various directions. Moreover, significant negative correlations (p < 0.05) between PM10, NO2, SO2, O3, and relative humidity (RH) underscore the pivotal role of meteorological factors in shaping pollutant levels. Strong positive correlations between PM2.5 and NO2 (0.71 to 0.93) suggest shared emission sources or similar atmospheric conditions in several cities. This comprehensive understanding highlights the urgent need for targeted mitigation strategies to address the multifaceted drivers of air pollution, ensuring the protection of public health and environmental sustainability across the region.

Satellite or ground-based measurements for air pollutants (PM2.5, PM10, SO2, NO2, O3) data and their health hazards: which is most accurate and why?

Air pollution is growing at alarming rates on regional and global levels, with significant consequences for human health, ecosystems, and change in climatic conditions. The present 12 weeks (4 October 2021, to 26 December 2021) study revealed the different ambient air quality parameters, i.e., PM2.5, PM10, SO2, NO2, and O3 over four different sampling stations of Delhi-NCR region (Dwarka, Knowledge park III, Sector 125, and Vivek Vihar), India, by using satellite remote sensing data (MERRA-2, OMI, and Aura Satellite) and different ground-based instruments. The ground-based observation revealed the mean concentration of PM2.5 in Dwarka, Knowledge park III, Sector 125, and Vivek Vihar as 279 µg m-3, 274 µg m-3, 294 µg m-3, and 365 µg m-3, respectively. The ground-based instrumental concentration of PM2.5 was greater than that of satellite observations, while as for SO2 and NO2, the mean concentration of satellite-based monitoring was higher as compared to other contaminants. Negative and positive correlations were observed among particulate matter, trace gases, and various meteorological parameters. The wind direction proved to be one of the prominent parameter to alter the variation of these pollutants. The current study provides a perception into an observable behavior of particulate matter, trace gases, their variation with meteorological parameters, their health hazards, and the gap between the measurements of satellite remote sensing and ground-based measurements.

Abundance, distribution and composition of microplastics in sediment and fish species from an Urban River of Bangladesh.

Microplastics (MPs) are a growing concern due to its ubiquitous presence and exceptional stability. We examined the abundance, dispersion, and attributes of MPs in the sediment and fish species of the Turag River in Bangladesh, which separated the industrial city Gazipur from the Mega-city Dhaka. Collected samples were digested and the chemical structure was identified using ATR-FTIR spectroscopy. The concentration of MPs in the sediment ranged from 10 to 35 particles kg-1, with a mean abundance of 19.2 ± 2.44 particles kg-1and MPs of the fragment type account for 34 % of all. The majority of MPs were discovered in the 3-5 mm size range. MPs concentrations in freshwater fish gut from the Turag River ranged from 0.63 ± 0.18 to 7.0 ± 1.1 microplastics individual-1. Fiber was found to be the most commonly ingested MPs type (43 %), followed by fragments (41 %), film (12 %), and foam (4 %). The most common type of MPs was transparent (34 %) followed by red (28 %), white (20 %), green (9 %) and black (8 %). The results showed that demersal (1.87 ± 0.39 items individual-1) and benthopelagic (1.5 ± 0.26 items individual-1) fish species had more MPs than pelagic fish (0.63 ± 0.18 items individual-1) species. Polypropylene (PP) was found to be the most dominant polymer type in the sediment sample, and PS (39 %) in the fish sample. Polyethylene (PE) was discovered to be 30 % and PP 25 % in sediment and fish samples, respectively. Other commonly detected polymer types include polyamide (PA), polystyrene (PS), cellulose acetate (CA), and polyethylene terephthalate (PET). In different sampling sites along the Turag River, the pollution load index (PLI) of MPs contamination was found to be in the risk level category I. The PLI values reflected the city's anthropogenic influence. The findings of the study could be used to establish a baseline for MPs pollution in Bangladesh's vast freshwater ecosystem.

Internet of Things (IoT) based automated sanitizer dispenser and COVID-19 statistics reporter in a post-pandemic world.

Purpose: Coronavirus is among the deadliest viruses of the 21st century. There is still a Coronavirus epidemic that affects most countries worldwide today. To prevent future outbreaks and protect public health, it is essential to invest in research and innovation on vaccines, treatments, diagnostic tests, public health infrastructure, and emergency response planning. Additionally, we need to work on mitigation strategies and take a comprehensive and multidisciplinary approach to prevent and fight against the virus. Methods: For the purpose of preventing the spread of microbial organisms, it is essential to take advantage of automatic sanitizer dispensers by deploying them in public places. This is one of the most feasible and effective ways to ensure that people have easy access to hand sanitizer and can reduce the spread of germs. Results: The proposed solution is a contactless sanitizer dispenser with an integrated temperature monitoring system, as well as an alert system for users who exhibit the symptom of infection. Moreover, the proposed solution has added advantage of interfacing with an electronic door so that we can easily implement it at the entrance of a public building/public transportation. This dispenser will also collect data that can be used to identify a symptomatic user and alert the appropriate authorities for safe quarantine. In addition, it is also used to monitor usage metrics, record user entries, and conduct statistical surveys using the ThinkSpeak platform. Conclusions: The proposed model could be a feasible solution to prevent the entry of infected persons and asymptomatic carriers indoors. This can be achieved by implementing automated temperature screening before allowing entry into the building. This can help identify individuals who are potentially infected with the virus and prevent them from entering the premises and potentially spreading the disease to others. Overall, the proposed model is a comprehensive and practical solution that can help to prevent the entry of infected persons and asymptomatic carriers indoors and help to keep the public safe.

Pollution free UV-C radiation to mitigate COVID-19 transmission.

The high rate of transmission of the COVID-19 virus has brought various types of disinfection techniques, for instance, hydrogen peroxide vaporization, microwave generating steam, UV radiation, and dry heating, etc. to prevent the further transmission of the virus. The chemical-based techniques are predominantly used for sanitization of hands, buildings, hospitals, etc. However, these chemicals may affect the health of humans and the environment in unexplored aspects. Furthermore, the UV lamp-based radiation sanitization technique had been applied but has not gained larger acceptability owing to its limitation to penetrate different materials. Therefore, the optical properties of materials are especially important for the utilization of UV light on such disinfection applications. The germicidal or microorganism inactivation application of UV-C has only been in-use in a closed chamber, due to its harmful effect on human skin and the eye. However, it is essential to optimize UV for its use in an open environment for a larger benefit to mitigate the virus spread. In view of this, far UV-C (222 nm) based technology has emerged as a potential option for the sanitization in open areas and degradation of microorganisms present in aerosol during the working conditions. Hence, in the present review article, efforts have been made to evaluate the technical aspects of UV (under the different spectrum and wavelength ranges) and the control of COVID 19 virus spread in the atmosphere including the possibilities of the human body sanitization in working condition.

Waste management beyond the COVID-19 pandemic: Bibliometric and text mining analyses.

The outbreak of the COVID-19 pandemic has significantly increased the demand for personal protective equipment, in particular face masks, thus leading to a huge amount of healthcare waste generated worldwide. Consequently, such an unprecedented amount of newly emerged waste has posed significant challenges to practitioners, policy-makers, and municipal authorities involved in waste management (WM) systems. This research aims at mapping the COVID-19-related scientific production to date in the field of WM. In this vein, the performance indicators of the target literature were analyzed and discussed through conducting a bibliometric analysis. The conceptual structure of COVID-19-related WM research, including seven main research themes, were uncovered and visualized through a text mining analysis as follows: (1) household and food waste, (2) personnel safety and training for waste handling, (3) sustainability and circular economy, (4) personal protective equipment and plastic waste, (5) healthcare waste management practices, (6) wastewater management, and (7) COVID-19 transmission through infectious waste. Finally, a research agenda for WM practices and activities in the post-COVID-19 era was proposed, focusing on the following three identified research gaps: (i) developing a systemic framework to properly manage the pandemic crisis implications for WM practices as a whole, following a systems thinking approach, (ii) building a circular economy model encompassing all activities from the design stage to the implementation stage, and (iii) proposing incentives to effectively involve informal sectors and local capacity in decentralizing municipal waste management, with a specific focus on developing and less-developed countries.

Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?

The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM2.5: 67 µg m-3 (lockdown) versus 81 µg m-3 (pre-lockdown); PM10: 171 µg m-3 versus 235 µg m-3; CO: 0.9 mg m-3 versus 1.1 mg m-3) except ozone which increased during the lockdown period (57 µg m-3 versus 39 µg m-3). The variation in pollutant concentrations revealed that PM2.5, PM10 and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.

Exposure and health: A progress update by evaluation and scientometric analysis.

Several hands are now working worldwide to reduce exposure to air pollution, especially in developing nations. Future steps should be determined and classified as possible research solutions and gaps from the massive bulk of research output. Therefore, a scientometric approach has been applied using VOSviewer to show an accurate picture and trend in the mentioned area "Air pollution exposure and health," and its signify issues. According to the proposed study, complete 26,859 documents were retrieved from the database (ISI Web of Science) related to air pollution exposure and health effects during 2018-2022. The mapping analysis is been conducted on the country's collaboration, co-authorship, institutional collaboration, and co-occurrence of keywords. The data collected shows the information about published articles (upward trend) over the years. Based on the citations and publication database, countries like China and the USA play a prominent role in air pollution exposure and health-related research. The study clearly defines the 3 domains of research and 4 major themes that have been currently focused. The case studies related to pollution and its impact on climate and health, studies involving chemical characteristics and management practices, also Hazardous health effects, theme like association of air pollutants, chemical composition and characterization of aerosols, health impacts due to exposure and modelling and analytical approach have been the most researched topics in the past 5 years. The developing and developed countries might potentially change the research network and work structure in order to obtain advancement in the field of Air pollution and enhance measures on exposure and health. The following research attempts to provide insights to the researchers and health sectors by straightening out developments up to date and raveling the research gaps that are needed to be addressed regarding Air pollution health and exposure.

Is safe distance enough to prevent COVID-19? Dispersion and tracking of aerosols in various artificial ventilation conditions using OpenFOAM.

The current COVID-19 pandemic has underlined the importance of learning more about aerosols and particles that migrate through the airways when a person sneezes, coughs and speaks. The coronavirus transmission is influenced by particle movement, which contributes to the emergence of regulations on social distance, use of masks and face shield, crowded assemblies, and daily social activity in domestic, public, and corporate areas. Understanding the transmission of aerosols under different micro-environmental conditions, closed, or ventilated, has become extremely important to regulate safe social distances. The present work attempts to simulate the airborne transmission of coronavirus-laden particles under different respiratory-related activities, i.e., coughing and speaking, using CFD modelling through OpenFOAM v8. The dispersion coupled with the Discrete Phase Method (DPM) has been simulated to develop a better understanding of virus carrier particles transmission processes and their path trailing under different ventilation scenarios. The preliminary results of this study with respect to flow fields were in close agreement with published literature, which was then extended under varied ventilation scenarios and respiratory-related activities. The study observed that improper wearing of mask leads to escape of SARS-CoV-2 containminated aerosols having a smaller aerodynamic diameter from the gap between face mask and face, infecting different surfaces in the vicinity. It was also observed that aerosol propagation infecting the area through coughing is a faster phenomenon compared to the propagation of coronavirus-laden particles during speaking. The study's findings will help decision-makers formulate common but differentiated guidelines for safe distancing under different micro-environmental conditions.

Wildfire-induced pollution and its short-term impact on COVID-19 cases and mortality in California.

Globally, wildfires have seen remarkable increase in duration and size and have become a health hazard. In addition to vegetation and habitat destruction, rapid release of smoke, dust and gaseous pollutants in the atmosphere contributes to its short and long-term detrimental effects. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has emerged as a public health concern worldwide that primarily target lungs and respiratory tract, akin to air pollutants. Studies from our lab and others have demonstrated association between air pollution and COVID-19 infection and mortality rates. However, current knowledge on the impact of wildfire-mediated sudden outburst of air pollutants on COVID-19 is limited. In this study, we examined the association of air pollutants and COVID-19 during wildfires burned during August-October 2020 in California, United States. We observed an increase in the tropospheric pollutants including aerosols (particulate matter [PM]), carbon monoxide (CO) and nitrogen dioxide (NO2) by approximately 150%, 100% and 20%, respectively, in 2020 compared to the 2019. Except ozone (O3), similar proportion of increment was noticed during the peak wildfire period (August 16 - September 15, 2020) in the ground PM2.5, CO, and NO2 levels at Fresno, Los Angeles, Sacramento, San Diego and San Francisco, cities with largest active wildfire area. We identified three different spikes in the concentrations of PM2.5, and CO for the cities examined clearly suggesting wildfire-induced surge in air pollution. Fresno and Sacramento showed increment in the ground PM2.5, CO and NO2 levels, while San Diego recorded highest change rate in NO2 levels. Interestingly, we observed a similar pattern of higher COVID-19 cases and mortalities in the cities with adverse air pollution caused by wildfires. These findings provide a logical rationale to strategize public health policies for future impact of COVID-19 on humans residing in geographic locations susceptible to sudden increase in local air pollution.

Spatially Resolved Distribution, Sources, Exposure Levels, and Health Risks of Heavy Metals in <63 µm Size-Fractionated Road Dust from Lucknow City, North India.

In the present study, a total of 64 road dust samples were collected from five different functional areas (residential, commercial, parks, high-traffic, and industrial) in urban Lucknow to assess the accumulation, distribution, and health risk of heavy metals (HMs) (i.e., Fe, Mn, Zn, Cu, Pb, Cd, As, Cr and Ni). Acid digestion methods were used to analyze HMs, followed by inductively coupled plasma-mass spectrometry (ICPMS). The ascending frequency of HMs was Cd < As < Ni < Cr < Pb < Cu < Zn < Mn < Fe for all different functional areas. Almost all HMs exceed the limits of Indian natural soil background values (INSB) across all functional areas. The pollution assessment results reveal that the urban road dust of Lucknow is highly enriched with Zn and Pb, causing deterioration of dust quality. The spatial distribution of HMs shows that road dust found in the central and southwestern zones of the Lucknow urban area are more contaminated than in other areas. The ecological risk assessment demonstrates that Cd was the highest risk contributor, followed by Pb, Zn and Cu. The result of the health risk assessment i.e., the cumulative hazard index (HI) and the cumulative lifetime cancer risk (LCR), reveal that children (mean HIchildren = 1.26, LCRchildren = 0.000187) are more vulnerable to HM exposure than adults (HIadults = 0.14, LCRadults = 0.0000804). For carcinogenic and non-carcinogenic risk, ingestion appears to be the major pathway of HM exposure in both age groups. It is alarming that all studied four carcinogenic HMs were found in concentrations higher than 1 × 10-6 (the permissible limit for humans). This indicates slight chances of developing cancer for both age groups in all functional areas.

IoT-Enabled smart mask to detect COVID19 outbreak.

Introduction: Internet of Things (IoT) has dominated various sectors over human effort with its liberal dimensions of innovations. Shielding various utilizations in terms of extensity, IoT integrated with the cloud has obtained a far-reaching spectrum. Backgrounds: Nevertheless, the SARS-CoV-2 has become an imperil, at the present moment causing remarkable demands on health technologies across the globe and gravely snarling the entire world populace. Whilst, the front-runners are striving enormously to uncover this virus, in the event of medications and evolving vaccines, it is also imperative to explore the existing systems dealing with medical emergence, mitigating its spread, and supremely the planning for thwarting this virus. The extant passive face masks provide effective and feasible protection by screening all the air particles entering the nasal passage. Methodology: This paper aims to enucleate a new "smart mask" paradigm for telehealth. As the vital health parameters like temperature, respiratory rate(RR), and heart rate(HR) are being easily affected by this deadly virus, this paper envisions a wearable mask equipped with an active sensor (LM35 temperature sensor) that would continuously monitor these health parameters of the person wearing the mask and provide real-time analysis of the data through the cloud. Result: This proposed methodology also incorporates a vigilant system that would alert the person, if the necessary physical distance is not maintained. Besides, this application provides a person with a detailed record of his health, sending doctors and hospitals for teleconsultation. Conclusion: Experimental results from a functional prototype have proved it a constructive low-cost system.

Air pollution in five Indian megacities during the Christmas and New Year celebration amidst COVID-19 pandemic.

Urban air quality and COVID-19 have been considered significant issues worldwide in the last few years. The current study highlighted the variation in air pollutants (i.e., PM2.5, PM10, NO2, and SO2) profile between Christmas and new year celebrations in 2019, 2020, and 2021. It can be seen that the concentration of selected air pollutants shows a substantially higher concentration in celebration periods in all reported years. The results indicate that air pollutants values are always higher than permissible limits. This observation indicates that people gather and reunite during Christmas and new year celebrations than the preceding years (2020 and 2021) amidst the pandemic. In the pandemic year, a higher margin enhanced the transportation and firework-induced air pollutant load in urban city Jodhpur, Rajasthan. In all states, a significant tendency was observed to retain the concentration profile of air pollutants in baseline concentration for almost more than one week after the celebration. This study addresses the pandemic situation, but it also dealt with the air pollutant parameter that brings down the sustainable quality of the environment due to the high usage of private vehicles, and crackers. In addition, a study on COVID-19 (cases and death rate) indicates a clear picture of the increasing trend after the event in probably all states. Thus, this approach suggested that stringent law enforcement is needed to ameliorate gatherings/reunions and pollution levels due to such events.

Addressing the relevance of COVID-19 pandemic in nature and human socio-economic fate.

COVID-19 or Coronavirus (SARS-COV-2) is a pandemic calamity that has locked people in their own houses. The effect of SARS-COV-2 disease has caused a decrease in the economy as businesses, transportation, aviation, and industries have been halted. Many people have died, and many are trying to survive this pandemic. As we all know, the virus of SARS-COV-2 can be transmitted through physical contact, and the government has taken up specific measures like closing up schools and colleges, closing up malls/markets/public places, and imposing lockdown in cities. It is expected that these measures can result in a decreased infection rate. On the one hand, SARS-COV-2 Has halted economic or developmental growth, but on the other hand, our nature i. e. our earth, is being provided with such conditions that it can restore its losses. Air quality has been improved in the lock down time. The emission level of different gases and particulate matters have slowed down in the Covid period. Water bodies have been clean and more transparent and propagate wildlife and fisheries. Due to the SARS-COV-2 lockdown, businesses and industries have halted, impacting the financial needs of many people around the world. The worry about surviving this pandemic and the financial crisis leads them to mental and emotional distress. This review article summarized the emergence of SARS-COV-2 disease and its role on human physical and psychological health. We also described the positive and negative effects of SARS-COV-2 on climate, environmental, and air quality with upcoming challenges for governments and populations around the world.

Heavy metal concentration and its distribution analysis in urban road dust: A case study from most populated city of Indian state of Uttarakhand.

The present work reports pollution level and spatial distribution of heavy metals (HMs) i.e. Iron (Fe), Manganese (Mn), Zinc (Zn), Copper (Cu), Lead (Pb), Chromium (Cr), Nickel (Ni), and Arsenic (As) in road dust of Dehradun city, Uttarakhand, India. Seventy samples in triplicates were collected from different land-use areas categorized as residential, commercial, national highways, and silent zones. The Concentrations of studied HMs were determined by the acid digestion method followed by inductively coupled plasma-mass spectrometry (ICP-MS). Pearson's significant correlation analysis is used to evaluate the relationship between heavy metal (HM) concentration and principal components analysis (PCA) was used for source identification of HMs in road dust. The average concentration of Mn, Zn, Cu, Pb, and Ni found higher when compared to the Indian soil background values. Among all studied HMs, Pb and Zn were found the most contaminated HMs in road dust. The degree of contamination shows the highest contamination of HMs found in commercial zones followed by National highways. The pollution load index (PLI) was found higher than 1 in all monitored 70 locations, showing the deterioration in the quality of road dust over the Dehradun city due to HMs. The principal component analysis result suggests that PC1 (Fe, Zn, Cu, and Ni) mainly comes from vehicular pollution, including tire wear and brake pad wear particles and corrosion of metallic components. PC2 (Mn and As) primarily comes from fossil fuel burning and pesticides and fertilizers containing Mn and As compounds. PC3 (Pb and Cr) mainly comes into road dust via fuel and lubrication oil residues and chrome-based paints. Spatial distribution maps of the HM concentration reveal that the city's central and eastern zone is the primary hotspot of high HM concentration, which links these zones to high vehicular volume and high population pressure.

The influence of meteorological variables and lockdowns on COVID-19 cases in urban agglomerations of Indian cities.

Coronavirus has been identified as one of the deadliest diseases and the WHO has declared it a pandemic and a global health crisis. It has become a massive challenge for humanity. India is also facing its fierceness as it is highly infectious and mutating at a rapid rate. To control its spread, many interventions have been applied in India since the first reported case on January 30, 2020. Several studies have been conducted to assess the impact of climatic and weather conditions on its spread in the last one and half years span. As it is a well-established fact that temperature and humidity could trigger the onset of diseases such as influenza and respiratory disorders, the relationship of meteorological variables with the number of COVID-19 confirmed cases has been anticipated. The association of several meteorological variables has therefore been studied in the past with the number of COVID-19 confirmed cases. The conclusions in those studies are based on the data obtained at an early stage, and the inferences drawn based on those short time series studies may not be valid over a longer period. This study attempted to assess the influence of temperature, humidity, wind speed, dew point, previous day's number of deaths, and government interventions on the number of COVID-19 confirmed cases in 18 districts of India. It is also attempted to identify the important predictors of the number of confirmed COVID-19 cases in those districts. The random forest model and the hybrid model obtained by modelling the random forest model's residuals are used to predict the response variable. It is observed that meteorological variables are useful only to some extent when used with the data on the number of the previous day's deaths and lockdown information in predicting the number of COVID-19 cases. Partial lockdown is more important than complete or no lockdown in predicting the number of confirmed COVID-19 cases. Since the time span of the data in the study is reasonably large, the information is useful to policymakers in balancing the restriction activities and economic losses to individuals and the government.