Increasing Pollution Levels Research Articles

Study of Airflow Dynamics and Particle Transport in the Upper Respiratory System using Numerical Simulation

The increase in pollution levels in recent years has increased the prevalence of pulmonary diseases. The accumulation of pollutant particles in the pulmonary tract is speculated to be one of the major reasons for the increase in chronic cases. This necessitates the study of the mechanism of particle deposition in human airways to develop better drug delivery systems. Aerosolized forms of drugs are commonly used to treat pulmonary diseases. The current study employed computational fluid dynamics (CFD) and discrete element method (DEM) techniques to study airflow patterns and particle deposition phenomena. An idealized 3D CAD model was developed based on available literature. A discretized finite-volume model was tested to ensure an independent solution. A user-defined function (UDF) was used to simulate realistic breathing dynamics for the respiration cycle. The aerosol particles of the calculated volume were mixed into the airflow domain. The analysis was conducted using ANSYS FLUENT CFD solver. This study found several regions of high turbulence in the upper human airways, with secondary flow structures exhibiting bifurcations and the glottal region. The study also found that the oral cavity and oropharynx regions with higher turbulence intensity had a concentrated deposition of particles. Most of the aerosol particles (5μm) were transported into the alveolar sacs, where they were absorbed into the bloodstream. The oral cavity and oropharynx have the highest pressure and particle deposition efficiency, while the trachea plays a crucial role in particle deposition during inhalation due to weak oscillatory flows and turbulence, especially in the tracheal region and lower respiratory tract. The oral cavity has the highest efficiency at 7.32%, while the trachea has the lowest at 0.4%. The overall deposition efficiency across all regions is 9.078%.This study did not account for the breakup of aerosol particles. Aerosol particles can break apart due to airflow and collisions, affecting their size and deposition efficiency. Ignoring this breakup could lead to inaccurate results, making accurate dosimetry essential for inhalation studies

Can low-carbon pilot policies reduce air pollution levels?

This paper explores the impact of China’s low-carbon pilot policy on air pollution levels. Employing a difference-in-difference approach based on propensity score matching, we find that the policy significantly reduced air pollution in the pilot cities. However, we also uncover a negative spillover effect, with neighboring cities experiencing increased pollution levels. After controlling for this spillover, the policy’s impact on air pollution decreases. Heterogeneity analysis reveals that the policy’s effectiveness varies across time and location, with more pronounced effects in coastal and southern regions and on non-statutory holidays. These findings highlight the complexity of environmental policy impacts and underscore the need for comprehensive, regionally tailored approaches to air pollution control.

A critical review on Shwasahara Mahakashaya in relation to Tamaka Shwasa

India is having rapid expansion, development and urbanization resulting into increased pollution levels leading to rise in respiratory illness. Bronchial asthma is one of the chronic respiratory diseases. Acharya Charaka has described five types of Shwasa Roga, Tamaka Shwasa is one of them. Charaka has elaborated etiopathogenesis, clinical features and treatment of Tamaka Shwasa. Shwasahara Mahakashaya is one of the unique composition of drugs explained by Acharya Charaka. It consists of ten Dravya’s, most of them tend to have Vata-Kaphaghna properties. Vitiated Vata- Kapha Dosha are responsible factors for pathogenesis of Tamaka Shwasa. The researches on pharmacological effect of this Dravya have shown Anti-inflammatory, Anti-histaminic, Anti-asthmatic properties.

Analysis of Mangrove vegetation health index by implementing NDVI classification method based on Landsat image data: Case study from Zuari Estuary Goa, India

Mangrove ecosystems are among the most productive and biologically complex ecosystems in the world providing many ecosystem services for human wellbeing, hence they have an outstanding relevance ecologically and economically. Mangrove habitats are temporarily inundated and often located in inaccessible regions. In Goa, fringing mangroves are distributed in Zuari and Mandovi estuaries based on topography and environmental conditions. These estuarine regions are used as inland waterways for transportation of iron ore, tourism, infrastructure development like bridges, jetties, highways, resorts and hotels, residential apartments, restaurants, small roads etc. Zuari estuary is located at lat. 15°25'N and long. 73°59'E on the central west coast of India. The images were downloaded from United States Geological Survey website (USGS). The radiometric and geometric corrections were made to reduce the undesirable noise component and changes in the amount of incoming radiance from sensors. Anderson level 1 classification was used for the classification purpose. The mangroves were digitized using hybrid classification method. For mangrove demarcation Google Earth Pro and visual interpretation techniques were used. Normalised Difference Vegetation Index (NDVI) analysis was adapted to perceive the health status of mangroves covers in the study area. The NDVI results were divided into three categories: (0.00-0.15 Stressed), (0.15-0.30 Moderately healthy), (0.30-0.47 Very healthy). Rhizophora and 01sp. each of Aegiceras, Bruguiera, Kandelia, Acanthus and Excoecaria along with mangrove associates like Acrosticum, Clerodendron, Salvadora, Ipomoea and Derris. Sonneretia alba and Avicennia marina were found to be dominating followed by Rhizophora mucronata. Stressed patches of mangroves can be attributed to the human interference from the surrounding regions, changes in water salinity, increase in pollution levels due to mining activities (transportation of iron ore from barges), infrastructure development etc. Moderately healthy and very healthy patches of mangroves may be associated with suitable ecological and natural conditions favouring healthy growth and also lack of anthropogenic interference and awareness about the importance of mangroves.

Do clean fuel and trade-openness reduce environmental degradation in China: evidence from asymmetric model

IntroductionThis study investigates the relationship between economic growth, clean fuel utilization, trade, and environmental pollution. By focusing on the potential of clean fuels and trade in reducing pollution, this research aims to understand their role in promoting environmental sustainability in China from 1990 to 2020.MethodsThe study employs the Nonlinear Autoregressive Distributed Lags (NARDL) approach to analyze time series data. This method enables the decomposition of impacts from clean fuels and trade on pollution levels, facilitating an understanding of their distinct contributions to environmental outcomes.ResultsFindings indicate that economic growth is associated with an increase in pollution levels, while clean fuel usage exhibits a modest but significant reduction effect. Nonetheless, the relatively small coefficients highlight the need for a greater share of clean fuels in China’s energy mix. Additionally, trade shows a significant negative relationship with pollution emissions, with data reflecting a gradual decline in pollution over time.DiscussionThese results underscore the benefits of clean fuel adoption and trade promotion as effective measures for mitigating pollution. However, they also highlight the necessity for stronger regulatory policies, public awareness initiatives, and investments in sustainable technologies to ensure China’s long-term environmental sustainability.

Evaluating the advancement of sustainable development objectives in recently industrialized nations by tying gold prices, fossil fuel prices, and energy use

Rapid industrialization in recently industrialized countries (NICs) has exacerbated environmental degradation, raising urgent concerns about how energy consumption, gold prices, and fossil fuel prices contribute to this growing issue. This study aims to evaluate the asymmetric relationships between these factors and environmental degradation across 10 NICs, including Brazil, India, South Korea, Mexico, Indonesia, Turkey, Thailand, South Africa, Malaysia, and the Philippines, from 1995 to 2023. Using the CS-ARDL model, our study demonstrates that while energy costs and renewable energy consumption reduce environmental degradation, gold prices and fossil fuel consumption significantly increase ecological harm. Additionally, the study employs FGLS, CS-DL, AMG, and Driscoll-Kray to verify the robustness of these findings. Notably, the Environmental Kuznets Curve (EKC) hypothesis holds true in these economies. Key results show that a 1 % increase in renewable energy use decreases emissions by 0.7 %, while a 1 % rise in gold prices correlates with a 0.5 % increase in pollution levels. These findings underscore the need for NICs to implement green investments, promote renewable energy, and initiate structural reforms to ensure sustainable development.

About Air Quality Assessment using Time Series Analysis Techniques on Air Particles Data

This study investigates the dynamics of air pollution caused by particulate matter (PM10 and PM2.5) in Omsk, Russia. Data collected from the Sensor.Community network between 2021 and 2023 were analyzed using time series analysis methods. The findings reveal a subtle weekly seasonality in the data, potentially attributed to fluctuations in industrial activity and traffic patterns throughout the week. Additionally, a concerning trend of deteriorating air quality was identified, characterized by increasing annual average concentrations of PM10 and PM2.5. The study employed various time series analysis techniques, including Empirical Cumulative Distribution Function (ECDF), Seasonal and Trend decomposition using Loess (STL), and autocorrelation function (ACF) analysis. These methods allowed for the visualization and examination of data distribution, trend identification, and seasonality detection. Furthermore, the Mann-Kendall test confirmed a statistically significant trend of increasing pollution levels over the three-year period. To enhance the accuracy of spatial analysis, data interpolation was performed using kriging with a Gaussian model. This method, compared to simple interpolation, provides a more precise assessment of the spatial distribution of pollutants. The study also implemented Long Short-Term Memory (LSTM) for forecasting hourly pollution values. LSTM exhibited promising results, demonstrating its potential for developing early warning systems, particularly when combined with meteorological data such as wind forecasts. The results highlight the need for effective measures to mitigate air pollution in Omsk and emphasize the importance of utilizing data from diverse sources, including official air quality monitoring stations, to ensure accuracy and reliability in air quality assessments.

Interplay of Foreign Direct Investment, Remittances, and Economic Growth: Insights from SAARC Countries

The current study focuses on finding and analyzing the nexus between remittances, foreign direct investment, and economic growth in SAARC countries. This study uses secondary balanced data of selected SAARC countries for the years 2000 to 2019. This study uses gross domestic product i.e., GDP, which serves as the proxy of economic growth, as the dependent variable. The core independent variables of this study include (FDI) foreign direct investment and remittances (RMTN). Additionally, gross capital formation (GCF) and carbon dioxide emissions (CO2) are the other two independent variables in this study. For the proxy for environmental degradation the study uses data of CO2 emissions. The data is collected from the world development indicators, WDI. The study focuses on how all the independent variables affect the growth of economy in selected SAARC countries which include Pakistan, India, Bangladesh, Sri Lanka, and Nepal. The study applies cross sectional dependence test, panel cointegration test, unit root tests, and PARDL (panel auto regressive distributed lag model), also called pooled mean group methodology, to obtain empirical estimates. The results of PARDL show that FDI, RMTN, and GCF are all positively and significantly related to GDP. This means that GDP or alternatively economic growth, is improving with rise in FDI, RMTN, and GCF in selected SAARC countries. The results show that CO2 emissions have a negative significant impact on GDP i.e., increase in pollution levels is harmful for the growth of the selected economies.

Can environmental taxes and green technological investment ease environmental pollution in China?

This study examines the complex relationship between environmental taxation, green technology, green investment, real GDP, and environmental pollution by employing the Nonlinear autoregressive distributive lag model for China. The findings indicate that environmental tax policies have significant short- and long-term effects, with positive shocks leading to pollution reductions. The positive and negative shocks to green investment increase pollution levels in the long run. Moreover, the real GDP displays pollution reductions in the short run. The results provide valuable insights into China's environmental and economic situation and offer policy recommendations. These findings were confirmed using the Wald test. The findings emphasize China's need for stronger environmental taxes, green technology adoption, evaluated green investments, and sustainable economic growth to achieve cleaner production and environmental sustainability.

중국 환경보호정책의 효과성 분석: 시(市) 단위 패널자료를 중심으로

This study explores the effect of China's environmental protection policies on environmental pollution. In order to investigate the actual effect of environmental policies implemented in 31 provincial capitals of China and explore the relationship between environmental pollution and economic growth, panel analysis was carried out. The Panel's analysis shows that environmental policies can reduce pollution levels and economic growth can increase pollution levels. These results suggest that China should strengthen its environmental protection policy in the future. For example, in the field of industry, the focus is on upgrading governance equipment and technology, and strengthening supervision and punishment. In terms of transportation, strict emission standards are established, public transportation and new energy tools are developed, and path planning is optimized. In the economic field, preferential policies should be adopted to promote green industries and eliminate industries with serious pollution. Urban planning should be rationalized and green areas should be increased. At the same time, raise awareness of environmental protection and encourage the public to participate in environmental protection activities.

Contribution of ethnicity, area level deprivation and air pollution to paediatric intensive care unit admissions in the United Kingdom 2008–2021

There is emerging evidence on the impact of social and environmental determinants of health on paediatric intensive care unit (PICU) admissions and outcomes. We analysed UK paediatric intensive care data to explore disparities in the incidence of admission according to a child's ethnicity and the degree of deprivation and pollution in the child's residential area. Data were extracted on children <16 years admitted to UK PICUs between 1st January 2008 and 31st December 2021 from the Paediatric Intensive Care Audit Network (PICANet) database. Ethnicity was categorised as White, Asian, Black, Mixed or Other. Deprivation was quantified using the 'children in low-income families' measure and outdoor air pollution was characterised using mean annual PM2.5 level at local authority level, both divided into population-weighted quintiles. UK population estimates were used to calculate crude incidence of PICU admission. Incidence rate ratios were calculated using Poisson regression models. There were 245,099 admissions, of which 60.7% were unplanned. After adjusting for age and sex, Asian and Black children had higher relative incidence of unplanned PICU admission compared to White (IRR 1.29 [95% CI: 1.25-1.33] and 1.50 [95% CI: 1.44-1.56] respectively), but there was no evidence of increased incidence of planned admission. Children living in the most deprived quintile had 1.50 times the incidence of admission in the least deprived quintile (95% CI: 1.46-1.54). There were higher crude admission levels of children living in the most polluted quintile compared to the least (157.8 vs 113.6 admissions per 100,000 child years), but after adjustment for ethnicity, deprivation, age and sex there was no association between pollution and PICU admission (IRR 1.00 [95% CI: 1.00-1.00] per 1μg/m3 increase). Ethnicity and deprivation impact the incidence of PICU admission. When restricting to unplanned respiratory admissions and ventilated patients only, increasing pollution level was associated with increased incidence of PICU admission. It is essential to act to reduce these observed disparities, further work is needed to understand mechanisms behind these findings and how they relate to outcomes. There was no direct funding for this project. HM was funded by an NIHR Academic Clinical Fellowship (ACF-2022-18-017).

Metal(loid) uptake and physiological response of Coix lacryma-jobi L. to soil potentially toxic elements in a polluted metal-mining area

Coix lacryma-jobi L. is a traditional medicinal plant in east Asia and is an important crop in Guizhou province, southwest China, where there are elevated levels of soil mercury and arsenic (As). Exposure to multiple potentially toxic elements (PTEs) may affect plant accumulation of metal(loid)s and food safety in regions with high geological metal concentrations. Field experiments were conducted to study the effects of PTEs on metal(loid) accumulation and physiological response of C. lacryma in different plant parts at three pollution levels. Total root length, number of root tips, number of branches, and number of root crosses increased with increasing pollution level, with increases in highly polluted areas of 44.2, 57.0, 79.6, and 97.2%, respectively, compared to lightly polluted areas. Under multi-element stress the activity of C. lacryma antioxidant oxidase showed an increase at low and medium PTE concentrations and inhibition at high concentrations. The As contents were all below the maximum limit of cereal food contaminants in China (GB 2762-2022, As < 0.5 mg kg−1). The stems had high Tl bioconcentration factors but the translocation factors from stem to grain were very low, indicating that the stems may be a key plant part restricting Tl transport to the grains. C. lacryma increased root retention and reduced the transport effect, thus reducing metal accumulation in the grains. C. lacryma adapted to PTE stress through root remodeling and enhanced antioxidant enzyme activities.

Corporate Carbon Footprint: Evaluating Environmental Risks and Incentives in the Era of Climate Finance

To fight climate change and reduce their increasing pollution levels, developing nations must have access to worldwide public climate funds. In the view of developing nations, meeting their commitments to reduce emissions under the Paris Agreement depends on receiving funding for climate-related initiatives. According to earlier studies, financing developing nations may help them meet their climate targets. The most recent data on climate money and NDCs are used in this research to examine the subject from a practical standpoint. Two research approaches were used in this study to investigate the impact of climate funding on the objectives of recipient nations. Data indicated that it was excellent regardless of the size of the effect. Developing nations’ attempts to reduce emissions were more affected than those of the least developed nations, especially those with economies centred on tiny islands. This paper outlines how to solve the issue, but it is just the beginning. By informing their handling of climate money, investors can gain poorer nations’ confidence, according to this research.

Assessment of Soil Contamination with Heavy Metals and Arsenic in the City of Komsomolsk-on-Amure

Research and assessment of soil contamination with heavy metals and arsenic in Komsomolsk-on-Amur have been carried out. High levels of soil contamination with heavy metals have been found — toxicants of hazard classes 1 and 2, among which the largest participation of zinc, lead, copper and cadmium has been recorded. It has been noted that the high content of arsenic in soils may be due to both technogenic influence and natural features of the area under study. A comparison has been made of the contents of heavy metals and arsenic in the soils of the city of Komsomolsk-on-Amur with the local natural background and technogenic background concentrations of other industrial cities in Russia and China. Two main technogenic geochemical anomalies (zones of increased pollution levels) associated with the main industrial hubs of the city have been identified.

Estimating thresholds of natural vegetation for the protection of water quality in South African catchments

Many of South Africa's current water quality problems have been attributed to diffuse pollution derived from poorly regulated land use/land cover (LULC) transformations. To mitigate these impacts, the preservation of an adequate amount of natural vegetation within catchment areas is an important management strategy. However, it is not clear how much natural vegetation cover is required to provide adequate levels of protection, nor at which scale(s) this strategy would be most effective. To investigate the possibility of estimating minimum thresholds of natural vegetation required to protect water resources, regression analysis was used to model relationships between water quality (measured using Nemerow's Pollution Index) and metrics of natural vegetation at multiple scales across a sample of sub-catchments located along the western, southern, and south-eastern coast of South Africa. With conspicuous outliers removed, the models were able to explain up to 82 % of the variability in the relationship between land use and water quality. Moreover, a statistically significant, nonlinear, and inverse relationship was found between proportions of natural vegetation cover and pollution levels. This relationship was strongest when measured (1) across the whole catchment and (2) within a 200 m riparian buffer zone. The models further indicated that approximately 80 to 90 % natural vegetation cover was necessary at these scales to maintain water quality at ecologically acceptable levels. Additional nonlinear thresholds estimated using breakpoint analysis suggested that if proportions of natural vegetation fall below 45 % (across the whole catchment) and 60 % (within a 200 m riparian buffer zone) a dramatic increase in pollution levels can be expected. The estimated thresholds are recommended as guidelines that can be used to inform integrated land and water resources management strategies aimed at protecting water quality in the study area. Likewise, the methods described are recommended for the estimation of similar thresholds in other regions.

Impact of injection pressure on the performance, emissions, and combustion of a common rail direct injection engine fueled with quaternary blends

The scarcity and rising costs of fossil fuels, coupled with increasing pollution levels, have prompted the exploration of innovative biofuel blends. While binary and ternary fuels have been studied extensively in proportions of 5–20%, replacing up to 30–40% of fossil fuel dependency without significant engine modifications remains a challenge. One potential solution is to investigate an optimal quaternary blend (QB) through experimental methods. This study investigates the impact of increased injection pressure (IOP) and quaternary fuel blends on a common rail direct injection (CRDI) engine's performance and emissions. Different blends, including diesel fuel, vegetable oil, mahua methyl ester and normal-butanol, were tested to replace 30–40% of diesel and enhance combustion, reduce exhaust emissions and improve overall performance. Experiments used a 1-cylinder CRDI engine at high IOPs (400, 500, 600 and 700 bar). Results at 600 bar IOP showed that the optimal blend, QB3–QB4, increased brake thermal efficiency (BTE) by 9% and reduced brake-specific fuel consumption (BSFC) by approximately 11% compared to other blends. Emissions at 600 bar included a 16% reduction in hydrocarbons (HC) and a 24% decrease in carbon monoxide (CO) at full load. However, nitrogen oxide (NOx) emissions slightly increased with higher IOP. Significantly employing the QB3–QB4 blend at 600 bar improved control over HC, CO and smoke emissions. Overall, performance was enhanced and comparable to conventional diesel fuel, with only a minor increase in NOx emissions.

A Systematic Review for Indoor and Outdoor Air Pollution Monitoring Systems Based on Internet of Things

Global population growth and increasing pollution levels are directly related. The effect does not just apply to outdoor spaces. Likewise, the low indoor air quality is also having a negative impact on the health of the building residents. According to the World Health Organization, indoor air pollution is a leading cause of 1.6 million premature deaths annually. Tackling this public health issue, due to the direct relationship between air pollution levels and mortality and morbidity rates as well as overall comfort, is mandatory. Many companies have begun to build inexpensive sensors for use in Internet of Things (IoT)-based applications to pollution monitoring. The research highlights design aspects for sustainable monitoring systems including sensor types, the selected parameters, range of sensors used, cost, microcontrollers, connectivity, communication technologies, and environments. The main contribution of this systematic paper is the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. Firstly, the IEEE database had the highest contribution to this research (48.51%). The results showed that 87.1%, 66.3%, and 36.8% of studies focused on harmful gas monitoring, thermal comfort parameters, and particulate matter levels pollution, respectively. The most studied harmful gases were CO2, CO, NO2, O3, SO2, SnO2, and volatile organic compounds. The cost of the sensors was suitable for people with limited incomes and mostly under USD 5, rising to USD 30 for specific types. Additionally, 40.35% of systems were based on ESP series (ESP8266 and ESP32) microcontrollers, with ESP8266 being preferred in 34 studies. Likewise, IoT cloud and web services were the preferred interfaces (53.28%), while the most frequent communication technology was Wi-Fi (67.37%). Indoor environments (39.60%) were the most studied ones, while the share for outdoor environments reached 20.79% of studies. This is an indication that pollution in closed environments has a direct impact on living quality. As a general conclusion, IoT-based applications may be considered as reliable and cheap alternatives for indoor and outdoor pollution monitoring.

Role of resources rent, research and development, and information and communication technologies on CO2 emissions in BRICS economies

The continuous increase in pollution levels has become a severe threat to the globe, and practitioners are trying their best to deal with environmental challenges to attain for attaining the targets of sustainable development goals (SDGs). Under the environmental aspects, the world has introduced numerous solutions to become clean and green while the problem remains intact. Therefore, this study is an attempt that investigate the impact of natural resources rent, research & development expenditures (R&D), information and communication technologies, and renewable energy consumption on carbon emissions under the framework of the STIRPAT model for BRICS economies during 1998–2021 by using CS-ARDL method. The empirical outcome shows that economic growth (EG), urbanization, and natural resources increase environmental pollution. On the other hand, R&D expenditures, renewable energy and digitalization support the sustainability theme. Furthermore, this study uses the Augmented Mean Group, Common Correlated Effect Mean Group and Panel Quantile Regression to validate the prior outcomes. Finally, the inverted connection between natural resource rents and emissions is validated in BRICS economies. Based on the empirical outcomes, this study suggests policy implications for attaining the targets of SDG-13 (climates change), SDG-07 (affordable and clean energy), SDG-08 (decent economic growth), SDG-09 (innovations, research and development), SDG-11 (sustainable cities and societies), and SDG-12 (responsible consumption).

Recent progress in defect-engineered metal oxides for photocatalytic environmental remediation.

Rapid industrial advancement over the last few decades has led to an alarming increase in pollution levels in the ecosystem. Among the primary pollutants, harmful organic dyes and pharmaceutical drugs are directly released by industries into the water bodies which serves as a major cause of environmental deterioration. This warns of a severe need to find some sustainable strategies to overcome these increasing levels of water pollution and eliminate the pollutants before being exposed to the environment. Photocatalysis is a well-established strategy in the field of pollutant degradation and various metal oxides have been proven to exhibit excellent physicochemical properties which makes them a potential candidate for environmental remediation. Further, with the aim of rapid industrialization of photocatalytic pollutant degradation technology, constant efforts have been made to increase the photocatalytic activity of various metal oxides. One such strategy is the introduction of defects into the lattice of the parent catalyst through doping or vacancy which plays a major role in enhancing the catalytic activity and achieving excellent degradation rates. This review provides a comprehensive analysis of defects and their role in altering the photocatalytic activity of the material. Various defect-rich metal oxides like binary oxides, perovskite oxides, and spinel oxides have been summarized for their application in pollutant degradation. Finally, a summary of existing research, followed by the existing challenges along with the potential countermeasures has been provided to pave a path for the future studies and industrialization of this promising field.

Influence of meteorological variables and air pollutants on fog/smog formation in seven major cities of Indo-Gangetic Plain.

The Indo-Gangetic Plains (IGP) of the Indian subcontinent during winters experience widespread fog episodes. The low visibility is not only attributed to meteorological conditions but also to the increased pollution levels in the region. The study was carried out for Tier 1 and Tier II cities of the IGP of India, including Kolkata, Amritsar, Patiala, Hisar, Delhi, Patna, and Lucknow. This work analyzes data from 1990 to 2023 (33years) employing the Mann-Kendall-Theil-Sen slope to determine the trends in fog occurrences and the relation between fog and meteorological parameters using multiple linear regressions. Furthermore, identifying the most relevant fog (visibility)-impacting factors from a set of both meteorological factors and air pollutants using step-wise regression. All cities indicated trend in the number of foggy days except for Kolkata. The multiple regression analysis reveals relatively low associations between fog occurrences and meteorological factors (30 to 59%), although the association was stronger when air pollution levels were considered (60 to 91%). Relative humidity, PM2.5, and PM10 have the most influence on fog formation. The study provides comprehensive insights into fog trends by incorporating meteorological data and air pollution analysis. The findings highlight the significance of acknowledging meteorological and pollution factors to understand and mitigate the impacts of reduced visibility. Hence, this information can guide policymakers, urban planners, and environmental management agencies in developing effective strategies to manage fog-related risks and improve air quality.