Investigating the association between air pollutants' concentration and meteorological parameters in a rapidly growing urban center of West Bengal, India: a statistical modeling-based approach

Examining the relationship between atmospheric pollutants and meteorological factors in Asansol city, West Bengal, India, using statistical modelling

Meteorological conditions significantly impact ambient air quality in urban environments. This study focuses on Asansol, known as the "Coal City" and the "Industrial Heart of West Bengal," a notable hotspot for air pollution. Despite its significance, limited research has addressed the influence of meteorological factors on key air pollutants in this urban area. From January 2019 to December 2023, this investigation explores the relationships between meteorological parameters (including atmospheric temperature, relative humidity, rainfall, wind speed) and the concentrations of crucial air pollutants (PM2.5, PM10, NO2, SO2). Temporal trends in air pollutant concentrations are also analysed. The Spearman correlation method is used to establish associations between pollutant concentrations and meteorological variables, while multiple linear regression (MLR) models are employed to assess meteorological factors and potential impact on pollutant concentrations. The analysis reveals a decreasing trend in pollutant concentrations in Asansol. Temperature exhibits negative correlations with all pollutants in all seasons except for a positive correlation during the monsoon. Rainfall consistently displays significant negative correlations with pollutants in all seasons. Relative humidity is negatively correlated with pollutants in all seasons, and wind speed, except during the post-monsoon season, shows negative correlations with all pollutants. Linear models excel in predicting particulate matter concentrations but perform poorly in predicting gaseous contaminants. Accounting for seasonal fluctuations and meteorological parameters, this research enhances the accuracy of air pollution forecasting, contributing to a better understanding of air quality dynamics in Asansol and similar urban areas.

Decoding seasonal variability of air pollutants with climate factors: A geostatistical approach using multimodal regression models for informed climate change mitigation

In response to changes in climatic patterns, a profound comprehension of air pollutants (AP) variability is vital for enhancing climate models and facilitating informed decision-making in nations susceptible to climate change. Earlier research primarily depended on limited models, potentially neglecting intricate relationships and not fully encapsulating associations. This study, in contrast, probed the spatiotemporal variability of airborne particles (CO, CH4, SO2, and NO2) under varying climatic conditions within a climate-sensitive nation, utilizing multiple regression models. Spatial and seasonal AP data were acquired via the Google Earth Engine platform, which indicated elevated AP concentrations in primarily urban areas. Remarkably, the average airborne particle levels were lower in 2020 than in 2019, though they escalated during winter. The study employed linear regression, Pearson's correlation (PC), Spearman rank correlation models, and Geographically Weighted Regression (GWR) models to probe the relationship between pollutant variability and climatic elements such as rainfall, temperature, and humidity. Across all seasons, APs showed a negative correlation with rainfall while displaying positive correlations with temperature and humidity. The GWR and PC models produced the most reliable results from all the models employed, with the GWR model superseding the rest. Moreover, heightened aerosol levels were detected within a rainfall range of 600 mm/season, a temperature range of 25-30 °C, and humidity levels of 75 %-85 %. Overall, this study emphasizes the growing levels of APs in correlation with meteorological changes. By adopting a comprehensive approach and considering multiple factors, this research provides a more sophisticated understanding of the relationship between AP variability and climatic shifts.

Community Health Risk Awareness and Knowledge of Air Pollution in Annadale, Polokwane Local Municipality, Limpopo Province, South Africa

Background

Exposure to air pollution has detrimental effects on the elderly, women, people with pre-existing medical conditions, people living in poverty and children. The aim of the study was to investigate the extent of community awareness and knowledge on the health risks associated with exposure to air pollution. The study was conducted at Annadale residential area locally known as Ladanna surrounded by industrial areas and located in Polokwane Local Municipality under Capricorn District Municipality in Limpopo Province, South Africa.

Methods

A cross-sectional study design was used for the study, using self-administered questionnaires. The questionnaire was pre-tested on 10 respondents at Emdo Park (Extension 29) in Polokwane from 02 to 06 February 2021 and another fifteen respondents were pre-tested at Lesedi Park. A simple random sampling technique was used to select 376 respondents. Systematic sampling method was applied to select the households. SPSS version 26 was used to analyze data. Data was presented in the form of frequencies and percentages. Spearman rank correlation was used to measure the degree of association between 2 variables. A Chi-square test was used to compare the groups between the categorical variables. Multivariate Logistic Regression Model was used to assess associations of knowledge/awareness outcomes and sociodemographic characteristics with odds ratios (ORs) and 95% confidence intervals (Cls) presented.

Results

Of 376 respondents, 221 (59%) were males and 154 (41%) females. The majority 113 (70%) of respondents were those between the age group 23 and 47 years and 353 (94%) were aware that if they don't protect themselves against polluted air, they may get sick, with age and educational status associated with their awareness (P < .05). About 361 (96%) knew what air pollution is and 188 (50%) think the air they breathe in Annadale is moderate. A total number of 278 (74%) said they feel sick/uncomfortable when the quality of air is bad. About 293 (78%) knew that people are exposed to air pollution by breathing contaminated air and 237 (63%) identified sewage smell as the main cause of air pollution. Internet 199 (53%) and television 177 (47%) were identified as the main source of information Those who were not aware of actions implemented to reduce air pollution were 180 (48%). Based on the results of the study, respondents' level of knowledge in Annadale was poor (71%) and their awareness was good (87%).

Conclusions

It is crucial that air pollution risk communication strategies be implemented to empower residents and improve the level of knowledge on the dangers of exposure to polluted air.

Quantifying the impact of lockdown measures on air pollution levels: A comparative study of Bhopal and Adelaide

This research study presents an in-depth comparison of air quality in Bhopal, India, and Adelaide, Australia, focusing on the impact of COVID-19 restrictions. Utilizing air quality data from 2019 to 2022, the research analyzed the concentrations of pollutants like PM2.5, PM10, NO2, and O3, during pre-lockdown, lockdown, and post-lockdown periods. The findings demonstrate a significant reduction in PM2.5and PM10 levels during lockdown in cities such as Delhi and Haryana in India, and various Chinese cities, while also highlighting complex sources of air pollution like bushfires in regions like Sydney, Australia. In contrast, the study revealed nuanced trends in Bhopal and Adelaide, influenced by local geographical, climatic, and anthropogenic factors. Bhopal exhibited a notable decrease in PM10 and PM2.5levels, but inconsistent patterns in NO2 and CO, while Adelaide experienced marginal changes. The study emphasizes the temporary effectiveness of lockdowns and underscores the need for region-specific, sustainable air quality management strategies. Future implications include considerations for regional specificities, broader atmospheric chemistry, and international collaboration. The research provides valuable insights for urban air quality policy formulation, stressing a data-driven, long-term approach.

Air pollution status and attributable health effects across the state of West Bengal, India, during 2016-2021

Air pollution is one of the most significant threats to human safety due to its detrimental health consequences worldwide. This study examines the air pollution levels in 22 districts of West Bengal from 2016 to 2021, using data from 81 stations operated by the West Bengal Pollution Control Board (WBPCB). The study assesses the short- and long-term impacts of particulate matter (PM) on human health. The highest annual variation of PM10 was noted in 2016 (106.99 ± 34.17 μg/m3), and the lowest was reported in 2020 (88.02 ± 13.61 μg/m3), whereas the highest annual variations of NO2 (μg/m3) were found in 2016 (35.17 ± 13.55 μg/m3), and lowest in 2019 (29.72 ± 13.08 μg/m3). Similarly, the SO2 level was lower (5.35 μg/m3) in 2017 and higher in 2020 (7.78 μg/m3). In the state, Bardhaman, Bankura, Kolkata, and Howrah recorded the highest PM10 concentrations. The monthly and seasonal variations of pollution showed higher in December, January, and February (winter season) and lowest observed in June, July, and August (rainy season). The southern part of West Bengal state has recorded higher pollution levels than the northern part. The short- and long-term health impact assessment due to particulate matter shows that the estimated number of attributable cases (ENACs) for incidence of chronic bronchitis in adults and prevalence of bronchitis in children were 305,234 and 14,652 respectively. The long-term impact of PM2.5 on human health ENACs for mortality due to chronic obstructive pulmonary disease for adults, acute lower respiratory infections in children aged 0-5, lung cancer, and stroke for adults were 21,303, 12,477, 25,064, 94,406, and 86,272 respectively. This outcome assists decision-makers and stakeholders in effectively addressing the air pollution and health risk concerns within the specified area.

The interplay between air pollution, built environment, and physical activity: Perceptions of children and youth in rural and urban India

The role of physical inactivity as a contributor to non-communicable disease risk in children and youth is widely recognized. Air pollution and the built environment can limit participation in physical activity and exacerbate non-communicable disease risk; however, the relationships between perceptions of air pollution, built environment, and health behaviours are not fully understood, particularly among children and youth in low and middle-income countries. Currently, there are no studies capturing how child and youth perceptions of air pollution and built environment are associated with physical activity in India, thus, this study investigated the association between perceived air pollution and built environment on moderate-to-vigorous physical activity (MVPA) levels of Indian children and youth. Online surveys captured MVPA, perception of air pollution as a problem, built environment factors, as well as relevant sociodemographic characteristics from parents and children aged 5-17 years in partnership with 41 schools across 28 urban and rural locations during the Coronavirus disease lockdowns in 2021. After adjusting for age, gender, and location, a significant association was found between the perception of air pollution as a problem and MVPA levels (β = -18.365, p < 0.001). Similarly, the perception of a high crime rate was associated with lower MVPA levels (β = -23.383, p = 0.002). Reporting the presence of zebra crossings, pedestrian signals, or attractive natural sightings were associated with higher MVPA levels; however, this association varied across sociodemographic groups. These findings emphasize the importance of addressing air pollution and improving the built environment to facilitate outdoor active living, including active transportation, among children and youth - solutions that are particularly relevant not only for preventing non-communicable disease risk but also for climate change mitigation.