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Air quality monitoring (PM2.5, CO, NOx, SO2 and EC/OC) was carried out at highway toll plazas, municipality toll plazas and control sites (n = 23) in the National Capital Region of Delhi, to determine the exposure of toll plaza workers to air pollution and its effect on lung function. Lung function indices (n = 45) were also measured for these workers. The results reveal the high level of air pollution at almost all locations with PM2.5 values exceeding the national permissible limit except at a few control sites. Observed reduction in lung function indices was significant over years of occupational exposure even after adjusting for age, amongst non-smoking outdoor workers. This study found pollutant concentrations were highest at municipality toll plazas with minimum protective work area. The paper suggests measures to reduce the exposure of outdoor workers. [ABSTRACT FROM AUTHOR]

The rapid urbanization and industrialization in many parts of the world have made air pollution a global public health problem. A study conducted by the Swiss organization IQAir indicated that 22 of the top 30 most polluted cities in the world are in India. This creates the problem of air pollution, which is very relevant to India as well. Exposure to air pollutants has both acute (short-term) and chronic (long-term) impacts on health. Among the major air pollutants, particulate matter 2.5 (PM2.5) is the most harmful, and its long-term exposure can impair lung functions. Pollutant concentrations vary temporally and are dependent on the local meteorology and emissions at a given geographic location. PM2.5 forecasting models have the potential to develop strategies for evaluating and alerting the public regarding expected hazardous levels of air pollution. Accurate measurement and forecasting of pollutant concentrations are critical for assessing air quality and making informed strategic decisions. Recently, data-driven machine learning algorithms for PM2.5 forecasting have received a lot of attention. In this work, a spatiotemporal analysis of air quality was first performed for Hyderabad, indicating that average PM2.5 concentrations during the winter were 68% higher than those during the summer. Following that, PM2.5 modelling was done using three different techniques: multilinear regression, K-nearest neighbours (KNN), and histogram-based gradient boost (HGBoost). Among these, the HGBoost regression model, which used both pollution and meteorological data as inputs, outperformed the other two techniques. During testing, the model acquired an amazing R² value of 0.859, suggesting a significant connection with the actual data. Additionally, the model exhibited a minimum Mean Absolute Error (MAE) of 5.717 μg/m³ and a Root Mean Square Error (RMSE) of 7.647 μg/m³, further confirming its accuracy in predicting PM2.5 concentrations. In our investigation, we discovered that the HGBoost3 model beat other PM2.5 modelling models by having the lowest error and the highest R² value. This study made a substantial addition by incorporating the spatiotemporal relationship between air pollutants and meteorological variables in predicting air quality. This method has the potential to improve the creation of more precise air pollution forecast models. [ABSTRACT FROM AUTHOR]

There is extensive evidence linking air pollution exposure to physical health. Less is known about the mental health impacts of poor air quality, especially in developing countries. We use data from India and estimate the causal impact of air pollution exposure on feeling sad, experiencing cognitive difficulties, and feeling unable to control and cope with important things in life. We instrument for air pollution exposure using the annual number of nighttime thermal inversions and show that air pollution exposure in the previous calendar year significantly worsens mental health in the current year. We examine potential mechanisms and find that air pollution exposure negatively impacts self-reported physical health, worsens respiratory conditions, and increases the likelihood of experiencing sleeping difficulties. Accounting for mental health impacts of pollution exposure is critical to accurately estimating the true health costs of air pollution and designing optimal environmental policy. [ABSTRACT FROM AUTHOR]

The present study reports short-term impact of poor air quality on cardiovascular and respiratory morbidity rate in Delhi. The data on monthly count of patients visiting Out Patient Department (OPD) and hospital admission due to respiratory and cardiovascular illnesses from hospitals along with daily air quality data from air quality monitoring stations of Central Pollution Control Board (CPCB), Government of India, across Delhi were collected for the period 2008 to 2012. A semi-parametric Quasi-Poisson regression model was used to examine the association of high pollution episodes with relative risk of hospital OPD visit and hospital admission due to respiratory and cardiovascular diseases. This study has confirmed the substantial adverse health effects due to air pollution across criterion air pollutants. The study reports the short-term effects of air pollution on morbidity from a time-series study first time in India. The study findings illustrate the evidence of adverse health impact of air pollution from India to the global pool and can influence the policy makers to implement better air quality management system for Indian cities. Abbreviations: OPD: Out Patient Department; IPD: Inpatient Department; RD: Respiratory Disease; CVD: Cardiovascular Disease; COPD: Chronic Obstructive Pulmonary Disease; CPCB: Central Pollution Control Board; NAAQMP: National Ambient Air Quality Monitoring Programme; NAAQS: National Ambient Air Quality Standards; RR; Relative Risk; IMD: Indian Meteorological Department; PM10: Particulate Matter less than 10 μm in aerodynamic diameter; SO2: Sulphur dioxide; NO2: Nitrogen dioxide; CO: Carbon Monoxide; O3: Ozone; DCE: Delhi College of Engineering; GTB Hospital: Guru Teg Bahadur Hospital; VPCH: Vallabhbhai Patel Chest Hospital; RMLH: Ram Manohar Lohia Hospital; SJH: Safdarjung Hospital; LNJPH: Lok Narayan Jai Prakash Hospital; GTBH: Guru Teg Bahadur Hospital; AH: Ambedkar Hospital; HRH: Hindu Rao Hospital; ESIH: ESI Hospital; SGRH: Sir Ganga Ram Hospital [ABSTRACT FROM AUTHOR]

The continuous infrastructural and economic development exerted pressure on the environmental conditions of the North Maharashtra region. The air quality of North Maharashtra region was analysed for the identification of hot spots and safe zones of ambient air quality. The result shows air pollution at some part of North Maharashtra region. The levels of particulate matter were above the prescribed limits especially at Bhusawal, Dhule and Jalgaon Urban centres. The traces of polyaromatic hydrocarbons were also observed in the urban centres of study area. The binary ratios of the persistent prevailing polycyclic aromatic hydrocarbon (PAH)'s show great correlation with the vehicular exhaust in the study region. The higher levels of pollutants in the study region were recorded in the post-monsoon season. The present study is first of its kind in the North Maharashtra region and an attempt has been made to analyse the anthropogenic sources and concentration of air pollutants in the area. The air pollutants reduce the defence system of human body and lead into severe health consequences like damage of lung tissues with escalation in the existing respiratory and cardiovascular diseases. [ABSTRACT FROM PUBLISHER]