Spatio-temporal assessment of ambient air quality, their health effects and improvement during COVID-19 lockdown in one of the most polluted cities of India

Assessing the impact of the National Clean Air Programme in Uttar Pradesh's non-attainment cities: a prophet model time series analysis

Background

Uttar Pradesh, India's largest state, faces critical pollution levels, necessitating urgent action. The National Clean Air Programme (NCAP) targets a 40% reduction in particulate pollution by 2026. This study assesses the impact of NCAP on 15 non-attainment cities in Uttar Pradesh using the Prophet forecasting model.

Methods

Monthly data on AQI andPM 10 concentrations from 2016 to 2023 were sourced from the Uttar Pradesh Pollution Control Board. Significant changes in mean AQI andPM 10 levels from 2017 to 2023 were evaluated using the Friedman test. Prophet models forecastPM 10 concentrations for 2025-26, with relative percentage changes calculated and model evaluation metrics assessed.

Findings

Most cities exhibited unhealthy air quality. Jhansi had the lowest AQI (72.73) in 2023, classified as 'moderate' by WHO standards. Gorakhpur consistently showed 'poor' AQI levels, peaking at 249.31 in 2019. Western Uttar Pradesh cities such as Ghaziabad, Noida, and Moradabad had significant pollution burdens. Predictions showed Bareilly with over a 70% reduction inPM 10 levels, Raebareli 58%, Moradabad 55%, Ghaziabad 48%, Agra around 41%, and Varanasi 40%, meeting NCAP targets. However, Gorakhpur and Prayagraj predicted increases inPM 10 levels by 50% and 32%, respectively. Moradabad's model showed the best performance with anR 2 of 0.81, MAE of 17.27 μ g / m 3 , and MAPE of 0.10.

Interpretation

ForecastingPM 10 concentrations in Uttar Pradesh's non-attainment cities offers policymakers substantial evidence to enhance current efforts. While existing measures are in place, our findings suggest that intensified provisions may be necessary for cities predicted to fall short of meeting program targets. The Prophet model's forecasts can pinpoint these at-risk areas, allowing for targeted interventions and regional adjustments to strategies. This approach will help promote sustainable development customized to each city's specific needs.

Funding

No funding was issued for this research.

Spatio-temporal distribution and source contributions of the ambient pollutants in Lucknow city, India

Clean air is imperative to the survival of all life forms on the planet. However, recent times have witnessed enormous escalation in urban pollution levels. It is therefore, incumbent upon us to decipher measures to deal with it. In perspective, the present study was carried out to assess PM10 and PM2.5 loading, metallic constituents, gaseous pollutants, source contributions, health impact and noise level of nine-locations, grouped as residential, commercial, and industrial in Lucknow city for 2019-21. Mean concentrations during pre-monsoon for PM10, PM2.5, SO2 and NO2 were: 138.2 ± 35.2, 69.1 ± 13.6, 8.5 ± 3.3 and 32.3 ± 7.4 µg/m3, respectively, whereas post-monsoon concentrations were 143.0 ± 33.3, 74.6 ± 14.5, 12.5 ± 2.1, and 35.5 ± 6.3 µg/m3, respectively. Exceedance percentage of pre-monsoon PM10 over National Ambient Air Quality Standards (NAAQS) was 38.2% while that for post-monsoon was 43.0%; whereas corresponding values for PM2.5 were 15.2% and 24.3%. Post-monsoon season showed higher particulate loading owing to wintertime inversion and high humidity conditions. Order of elements associated with PM2.5 is Co < Cd < Cr < Ni < V < Be < Mo < Mn < Ti < Cu < Pb < Se < Sr < Li < B < As < Ba < Mg < Al < Zn < Ca < Fe < K < Na and that with PM10 is Co < Cd < Ni < Cr < V < Ti < Be < Mo < Cu < Pb < Se < Sr < Li < B < As < Mn < Ba < Mg < Al < Fe < Zn < K < Na < Ca. WHO AIRQ + ascertained 1654, 144 and 1100 attributable cases per 0.1 million of population to PM10 exposure in 2019-21. Source apportionment was carried out using USEPA-PMF and resolved 6 sources with highest percent contributions including road dust re-entrainment, biomass burning and vehicular emission. It is observed that residents of Lucknow city regularly face exposure to particulate pollutants and associated constituents making it imperative to develop pollution abetment strategies.

Two Decades of Air Pollution Health Risk Assessment: Insights From the Use of WHO's AirQ and AirQ+ Tools

Objectives

We evaluated studies that used the World Health Organization's (WHO) AirQ and AirQ+ tools for air pollution (AP) health risk assessment (HRA) and provided best practice suggestions for future assessments.

Methods

We performed a comprehensive review of studies using WHO's AirQ and AirQ+ tools, searching several databases for relevant articles, reports, and theses from inception to Dec 31, 2022.

Results

We identified 286 studies that met our criteria. The studies were conducted in 69 countries, with most (57%) in Iran, followed by Italy and India (∼8% each). We found that many studies inadequately report air pollution exposure data, its quality, and validity. The decisions concerning the analysed population size, health outcomes of interest, baseline incidence, concentration-response functions, relative risk values, and counterfactual values are often not justified, sufficiently. Many studies lack an uncertainty assessment.

Conclusion

Our review found a number of common shortcomings in the published assessments. We suggest better practices and urge future studies to focus on the quality of input data, its reporting, and associated uncertainties.

Exploring the association between long-term MODIS aerosol and air pollutants data across the Northern Great Plains through machine learning analysis

Aerosol optical depth (AOD) and Ångström exponent (AE) are the major environmental indicators to perceive air quality and the impact of aerosol on climate change and health as well as the global atmospheric conditions. In the present study, an average of AOD and AE data from Tera and Aqua satellites of MODIS sensors has been investigated over 7 years i.e., from 2016 to 2022, at four locations over Northern Great Plains. Both temporal and seasonal variations over the study periods have been investigated to understand the behavior of AOD and AE. Over the years, the highest AOD and AE were observed in winter season, varying from 0.75 to 1.17 and 1.30 to 1.63, respectively. During pre-monsoon season, increasing trend of AOD varying from 0.65 to 0.95 was observed from upper (New Delhi) to lower (Kolkata) Gangetic plain, however, during monsoon and post-monsoon a reverse trend varying from 0.85 to 0.65 has been observed. Seasonal and temporal aerosol characteristics have also been analyzed and it has been assessed that biomass burning was found to be the major contributor, followed by desert dust at all the locations except in Lucknow, where the second largest contributor was dust instead of desert dust. During season-wise analysis, biomass burning was also found to be as the major contributor at all the places in all the seasons except New Delhi and Lucknow, where dust was the major contributor during pre-monsoon. A boosting regression algorithm was done using machine learning to explore the relative influence of different atmospheric parameters and pollutants with PM2.5. Water vapor was assessed to have the maximum relative influence i.e., 51.66 % followed by CO (21.81 %). This study aims to help policy makers and decision makers better understand the correlation between different atmospheric components and pollutants and the contribution of different types of aerosols.

Statistical estimation of noise induced hearing loss among the drivers in one of the most polluted cities of India

In the present study, an attempt has been made to assess the impact of vehicular noise upon the 3-wheeler tempo drivers and to know whether there is any relationship between hearing loss and cumulative noise exposure. For this purpose, 3-wheeler tempo drivers (Exposed group) and non-commercial light motor vehicle car drivers (Unexposed group) were chosen as study subjects. Three traffic routes were selected to assess the noise level during waiting and running time in the exposed and unexposed groups. Among all three routes, the highest mean noise level (Leq) was observed on the Chowk to Dubagga route for waiting and en-route noise measurement. It was measured as 84.13 dB(A) and 86.36 dB(A) for waiting and en-route periods of 7.68 ± 3.46 and 31.05 ± 6.6 min, respectively. Cumulative noise exposure was found to be significantly different (p < 0.001) in all age groups of exposed and unexposed drivers. Audiometric tests have been performed over both exposed and unexposed groups. The regression analysis has been done keeping hearing loss among tempo drivers as the dependent variable and age (years) and Energy (Pa2 Hrs) as the independent variable using three different criteria of hearing loss definitions, i.e., World Health Organization, National Institute for Occupational Safety and Health (NIOSH), Occupational Safety and Health Administration criteria. Among these three criteria, the NIOSH criterion of hearing loss best explained the independent variables. It could explain the total variation in dependent variable by independent variable quite well, i.e., 68.1%. The finding showed a linear relationship between cumulative noise exposures (Pa2 Hrs) and the exposed group's hearing loss (dB), i.e., hearing loss increases with increasing noise dose. Based on the findings, two model equations were developed to identify the safe and unsafe noise levels with exposure time.

Statistical and spatio-temporal analyses of noise pollution level and its health impact

Due to rapid urbanization and exponential growth in transportation; traffic noise has become a major area of concern. Noise not only disturbs our day-to-day life but also have severe adverse health effects over humans which further may lead to mortality. This paper focuses on the behavior of noise levels of Lucknow city over a decade and establishes its correlation with impact on human health in terms of annoyance and sleep disturbance. Apart from Leq, different noise parameters like L10, L50, L90, Traffic Noise Index (TNI), Noise Pollution Index (NPI), and Noise Climate (NC) have also been analyzed to understand the variation of noise. At all the locations, the noise level has been found exceeding their prescribed standards during day time and night time except at Amausi. Out of nine locations, TNI was found to be exceeding at three locations during day time and NPI exceeding at one location. However, during night time both values of TNI and NPL were observed within the limit at all the locations. From the noise map of the city during day time and night time, among all sampling locations, Charbagh has been found to be worst affected by noise pollution. A strong positive correlation has been observed among the total population, vehicular count, and day and night time noise data, which directly contribute to a higher percentage of sleep disturbance and annoyance among residents. Due to the increase in noise levels over a period of time, almost four times the population get affected by high annoyance and almost double the population get affected by sleep disturbance.

Spatio-temporal health benefits attributable to PM2.5 reduction in an Indian city

Fine particulate matter (PM_2.5) is linked with a wide spectrum of human health effects and has the highest contribution to total air pollution mortality. This study aims to quantify health benefits of reducing PM_2.5 concentration to World Health Organization standard (annual mean = 10 µg m^-3) for various health endpoints during 2011-2019 period using AirQ+ and BenMAP-CE software packages. Intraurban assessment in Vellore city, India was done by estimating health benefits at ward level. Both software packages estimated annual average all-cause, ischemic heart disease, stroke, and chronic obstructive pulmonary disease health benefits in the range of 919-945, 175-234, 70-152, and 99-175 cases at city level and 15-16, 3-4, 1-3, and 2-3 cases at ward level, respectively. Sensitivity analysis showed that relative risk had a large influence on health benefit estimates. Present study results will play a crucial role in the future air quality and public health policies of Vellore city.

Evaluation of heavy metal contaminants in prepared noodles: source allocation and health risk assessment

In recent years, special attention has been given to emission research that led to the deposition of toxicants from road traffic. Thus, it is imperative to focus on heavy metal (HM) stressors in food items, their source contribution, and health risk assessment providing insight into their spatial role at the population level. In this study, heavy metal in the street vended noodles was studied while correlating the quality of noodle with different environmental origins. The samples were prepared using acid digestion and analysed by flame atomic absorption spectrophotometer, except Hg which was analysed by direct mercury analyser. The results showed that some heavy metals like Cr, Pb, Mn, Cd, and Hg exceed their permissible limits established by the international legislation for food products. In the noodle samples, the concentration of heavy metal ranged from < 0.1 to 0.904 mg/kg for Pb, < 0.09 to 0.843 mg/kg for Ni, < 0.004 to 0.201 mg/kg for Cd, < 0.0001 to 0.004 mg/kg for Hg, < 0.01 to 1.388 mg/kg for Cu, < 0.015 to 8.049 mg/kg for Mn, and < 0.02 to 16.514 mg/kg for Cr. Noodle samples vended on high traffic density streets are directly associated with increased HM content due to atmospheric deposition from the surrounding. Source apportionment study determines that HM contamination belongs to the same source of origin, except Cr. Based on the cluster analysis, these samples fall into three major groups that were further validated by the canonical discriminant function. Health risk prediction by Monte Carlo simulation revealed an elevated non-carcinogenic health hazard risk to consumers with a hazard index (HI) shift from 71 to 75%. Health hazard analysis showed that consumers of high traffic density street vended food are at higher risk of developing health-related issues. This study is important to evaluate the health risk of the population exposed to heavy metals due to ingestion of street vended food.

Correlating the trends of COVID-19 spread and air quality during lockdowns in Tier-I and Tier-II cities of India-lessons learnt and futuristic strategies

The present study focuses on the impact of early imposed lockdowns and following unlocking phases on the status of air quality in six Tier-I and nine Tier-II cities of India as compared to the pre-lockdown measures. Furthermore, the study highlights the possible correlation of air quality index (AQI) with the initial trend of COVID-19 issues including the vaccination cases. Based on the statistical data analysis, we observed that the long-term averages for representing the short-term pre-lockdown conditions can impose a healing effect to the observed anomalies in air pollution data. However, the reduction in air pollution during the imposed lockdown series was only a phenomenal consequence, and the trends started reversing during the later phases of partial unlocking, where the correlation showed reversing trends. Being a yearly averaged parameter, the marginal reductions in the exceedance factor (EF) alone could not dictate air quality compared to the AQI. As there is incoherent variability in the pollutant distributions among the cities during various phases of the study, the trend analysis served as a preferable criterion to choose the preferred sources of variations. Based on the results, the correlation analysis revealed that air quality expressed in terms of AQI can act as an important precursor to estimate the critical phase of COVID-19 spread and the effectiveness of various control measures taken during each phase. Based on our proposed ranking, Kolkata and Patna are ranked first in the Tier-I and Tier-II cities respectively according to their responsiveness to the various institutionalized restrictions in terms of air quality parameters.

Effects of the COVID-19 Lockdown on Air Pollutant Levels and Associated Reductions in Ischemic Stroke Incidence in Shandong Province, China

Background

Local governments in China took restrictive measures after the outbreak of COVID-19 to control its spread, which unintentionally resulted in reduced anthropogenic emission sources of air pollutants. In this study, we intended to examine the effects of the COVID-19 lockdown policy on the concentration levels of particulate matter with aerodynamic diameters of ≤1 μm (PM₁), ≤2.5 μm (PM_2.5), and ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and carbon monoxide (CO) and the potential subsequent reductions in the incidence of ischemic and hemorrhagic stroke in Shandong Province, China.

Methods

A difference-in-difference model combining the daily incidence data for ischemic and hemorrhagic stroke and air pollutant data in 126 counties was used to estimate the effect of the COVID-19 lockdown on the air pollutant levels and ischemic and hemorrhagic stroke incident counts. The avoided ischemic stroke cases related to the changes in air pollutant exposure levels were further estimated using concentration-response functions from previous studies.

Results

The PM₁, PM_2.5, PM₁₀, NO₂, and CO levels significantly decreased by −30.2, −20.9, −13.5, −46.3, and −13.1%, respectively. The O₃ level increased by 11.5% during the lockdown compared with that in the counterfactual lockdown phase of the past 2 years. There was a significant reduction in population-weighted ischemic stroke cases (−15,315, 95% confidence interval [CI]: −27,689, −2,942), representing a reduction of 27.6% (95% CI: −49.9%, −5.3%). The change in the number of hemorrhagic stroke cases was not statistically significant. The total avoided PM₁-, PM_2.5-, PM₁₀-, NO₂-, and CO–related ischemic stroke cases were 739 (95% CI: 641, 833), 509 (95% CI: 440, 575), 355 (95% CI: 304, 405), 1,132 (95% CI: 1,024, 1,240), and 289 (95% CI: 236, 340), respectively.

Conclusion

The COVID-19 lockdown indirectly reduced the concentration levels of PM₁, PM_2.5, PM₁₀, NO₂, and CO and subsequently reduced the associated ischemic stroke incidence. The health benefits due to the lockdown are temporary, and long-term measures should be implemented to increase air quality and related health benefits in the post-COVID-19 period.

Air Quality Measurements in Kitchener, Ontario, Canada Using Multisensor Mini Monitoring Stations

The Region of Waterloo is the third fastest growing region in Southern Ontario in Canada with a population of 619,000 as of 2019. However, only one air quality monitoring station, located in a city park in Kitchener, Ontario, is currently being used to assess the air quality of the region. In September 2020, a network of AQMesh Multisensor Mini Monitoring Stations (pods) were installed near elementary schools in Kitchener located near different types of emission source. Data analysis using a custom-made long-distance scaling software showed that the levels of nitrogen oxides (NO and NO2), ground level ozone (O3), and fine particulate matter (PM2.5) were traffic related. These pollutants were used to calculate the Air Quality Health Index-Plus (AQHI+) at each location, highlighting the inability of the provincial air quality monitoring station to detect hotspot areas in the city. The case study presented here quantified the impact of the 2021 summer wildfires on the local air quality at a high time resolution (15-min). The findings in this article show that these multisensor pods are a viable alternative to expensive research-grade equipment. The results highlight the need for networks of local scale air quality measurements, particularly in fast-growing cities in Canada.

Health impact assessment of air pollutants during the COVID-19 pandemic in a Brazilian metropolis

Studies around the world have revealed reduced levels of atmospheric particulate matter in periods of greatest human mobility restriction to contain the spread of SARS-CoV-2 during the COVID-19 pandemic. The present study aimed to carry out a health impact assessment in Recife, Brazil, hypothesizing a scenario in which the levels of PM₁₀ and PM_2.5 remained, throughout the year, as in the most restrictive period of human mobility. Particular material data (PM₁₀ and PM_2.5) were measured during the pandemic and population and health (mortality, hospital admissions for heart and respiratory problems) data from 2018 were used. We observed a reduction in the concentration of PM_2.5 in up to 43.7% and PM₁₀ up to 29.5% during the period of social isolation in the city of Recife. The reduction in PM_2.5 would avoid 106 annual deaths from non-external causes and 58 annual deaths from cardiovascular diseases. In this scenario, $ 294.88 million would be saved ($ 114.88 million from heart problems and $ 180 million from non-external causes). When considering hospitalizations avoided by the decrease in PM₁₀, we observed 57 fewer hospitalizations for respiratory diseases, 42 for heart diseases and a reduction of 37 deaths due to non-external causes. The reduction in spending on respiratory and cardiovascular hospitalizations would exceed $ 330,000. Therefore, the reduction of particulate matter could prevent hospital admissions, deaths and consequently there would be a reduction in disease burden in developing countries where economic resources are scarce. In this sense, governments should seek to reduce levels of pollution in order to improve the life quality and health of the population.

What medical waste management system may cope With COVID-19 pandemic: Lessons from Wuhan

The global pandemic caused by the 2019 coronavirus (COVID-19) has led to a dramatic increase in medical waste worldwide. This tremendous increase in medical waste is an important transmission medium for the virus and thus poses new and serious challenges to urban medical waste management. This study investigates the response of medical waste management to the COVID-19 pandemic and subsequent changes in Wuhan City based on the most detailed data available, including waste generation, storage, transportation, and disposal. The results show that despite a 5-fold increase in the demand for daily medical waste disposal in the peak period, the quick responses in the storage, transportation, and disposal sectors during the pandemic ensured that all medical waste was disposed of within 24 hours of generation. Furthermore, this paper discusses medical waste management during future emergencies in Wuhan. The ability of the medical waste management system in Wuhan to successfully cope with the rapid increase in medical waste caused by major public health emergencies has important implications for other cities suffering from the pandemic and demonstrates the need to establish resilient medical emergency systems in urban areas.