Comparison of the association between different ozone indicators and daily respiratory hospitalization in Guangzhou, China.

Background: Epidemiological studies have widely proven the impact of ozone (O3) on respiratory mortality, while only a few studies compared the association between different O3 indicators and health. Methods: This study explores the relationship between daily respiratory hospitalization and multiple ozone indicators in Guangzhou, China, from 2014 to 2018. It uses a time-stratified case-crossover design. Sensitivities of different age and gender groups were analyzed for the whole year, the warm and the cold periods. We compared the results from the single-day lag model and the moving average lag model. Results: The results showed that the maximum daily 8 h average ozone concentration (MDA8 O3) had a significant effect on the daily respiratory hospitalization. This effect was stronger than for the maximum daily 1 h average ozone concentration (MDA1 O3). The results further showed that O3 was positively associated with daily respiratory hospitalization in the warm season, while there was a significantly negative association in the cold season. Specifically, in the warm season, O3 has the most significant effect at lag 4 day, with the odds ratio (OR) equal to 1.0096 [95% confidence intervals (CI): 1.0032, 1.0161]. Moreover, at the lag 5 day, the effect of O3 on the 15-60 age group was less than that on people older than 60 years, with the OR value of 1.0135 (95% CI: 1.0041, 1.0231) for the 60+ age group; women were more sensitive than men to O3 exposure, with an OR value equal to 1.0094 (95% CI: 0.9992, 1.0196) for the female group. Conclusion: These results show that different O3 indicators measure different impacts on respiratory hospitalization admission. Their comparative analysis provided a more comprehensive insight into exploring associations between O3 exposure and respiratory health.

Associations between Different Ozone Indicators and Cardiovascular Hospital Admission: A Time-Stratified Case-Crossover Analysis in Guangzhou, China.

Epidemiological studies reported that ozone (O3) is associated with cardiovascular diseases. However, only few of these studies examined the impact of multiple O3 indicators on cardiovascular hospital admissions. This study aimed to explore and compare the impacts of different O3 indicators on cardiovascular hospital admissions in Guangzhou, China. Based upon the data on daily cardiovascular hospital admissions, air pollution, and meteorological factors in Guangzhou from 2014 to 2018, a time-stratified case-crossover design model was used to analyze the associations between different O3 indicators and cardiovascular hospital admissions. Moreover, the sensitivities of different age and gender groups were analyzed for the whole year and different seasons (i.e., warm and cold). During the warm season, for the single-pollutant model, the odds ratio (OR) value of cardiovascular hospital admissions was 1.0067 (95% confidence interval (CI): 1.0037, 1.0098) for every IQR increase in MDA8 O3 at a lag of five days. The effect of O3 on people over 60 year was stronger than that on the 15-60 years age group. Females were more sensitive than males to O3 exposure. These results provided valuable references for further scientific research and environmental improvement in Guangzhou. Given that short-term O3 exposure poses a threat to human health, the government should therefore pay attention to prevention and control policies to reduce and eliminate O3 pollution and protect human health.

Driving factors behind the continuous increase of long-term PM2.5-attributable health burden in India using the high-resolution global datasets from 2001 to 2020.

Air pollution is the fourth leading global risk factor, whereas in India air pollution is reported as the highest risk factor with millions of premature deaths every year. Despite implementation of several air pollution control plans, PM2.5 levels over India have not noticeably reduced. PM2.5-associated health burdens in India have increased significantly in past decades. A fine resolution (0·01° × 0·01°) analysis of PM2.5-attribulable premature deaths (rather than the coarse-level analysis) may elucidate the reason for this increase and inform and effective start-of-the-art state-level and national emission control strategies. This study quantified the spatiotemporal dynamics of PM2.5-attributable premature deaths from 2001 to 2020 and applied a decomposition analysis to dissect the contribution of various associated parameters, such as PM2.5 concentration, population distribution and disease-specific baseline death rate. Results show significant spatiotemporal variations of PM2.5 and associated health burden in India. During the study period, population weighted PM2.5 value increased from 46.0 to 59.5 µg/m3 and associated non-communicable death increased around 87.6 %, from 1050 [95 % (CI): 880-1210] thousand to 1970 (95 % CI: 1658-2259) thousand. The states of Uttar Pradesh, Bihar, West Bengal, Maharashtra, Rajasthan, and Madhya Pradesh had the highest PM2.5-attributable deaths. In these states, non-accidental deaths increased from 232.1, 112.7, 81.4, 79.1, 66.3 and 58.5 thousand in 2001 to 424.1, 226.7, 156.2, 154.5, 123.3 and 119.7 thousand in 2020. In per capita population (/105 population), the highest PM2.5-attributable deaths were observed in Delhi, Uttar Pradesh, Bihar, Haryana and Punjab. Throughout the study period, demographic changes outweighed the health burden and were responsible for ~62.8 % increase of PM2.5-related non-accidental deaths across India, whereas the change in PM2.5 concentration influenced only 18.7 %. The change in baseline mortality rate impacts differently for the estimation of disease-specific mortality changes. Our findings suggest more dynamic and comprehensive policies at state-specific level, especially for North India is very indispensable for the overall decrease of PM2.5-related deaths in India.

Unprecedented reduction in air pollution and corresponding short-term premature mortality associated with COVID-19 lockdown in Delhi, India.

Countries around the world introduced strict restrictions on movement and activities known as 'lockdowns' to restrict the spread of the novel coronavirus disease (COVID-19) from the end of 2019. A sudden improvement in air quality was observed globally as a result of these lockdowns. To provide insight into the changes in air pollution levels in response to the COVID-19 restrictions we have compared surface air quality data in Delhi during four phases of lockdown and the first phase of the restriction easing period (25 March to 30 June 2020) with data from a baseline period (2018-2019). Simultaneously, short-term exposure of PM2.5 and O3 attributed premature mortality were calculated to understand the health benefit of the change in air quality. Ground-level observations in Delhi showed that concentrations of PM10, PM2.5 and NO2 dropped substantially in 2020 during the overall study period compared with the same period in previous years, with average reductions of ~49%, ~39%, and ~39%, respectively. An overall lower reduction in O3 of ~19% was observed for Delhi. A slight increase in O3 was found in Delhi's industrial and traffic regions. The highest peak of the diurnal variation decreased substantially for all the pollutants at every phase. The decrease in PM2.5 and O3 concentrations in 2020, prevented 904 total premature deaths, a 60% improvement when compared to the figures for 2018-2019. The restrictions on human activities during the lockdown have reduced anthropogenic emissions and subsequently improved air quality and human health in one of the most polluted cities in the world.Implications: I am submitting herewith the manuscript entitled "Unprecedented Reduction in Air Pollution and Corresponding Short-term Premature Mortality Associated with COVID-19 Forced Confinement in Delhi, India" for potential publishing in your journal.The novelty of this research lies in: (1) we utilized ground-level air quality data in Delhi during four phases of lockdown and the first phase of unlocking period (25th March to 30th June) for 2020 as well as data from the baseline period (2018-2019) to provide an early insight into the changes in air pollution levels in response to the COVID-19 pandemic, (2) Chatarize the change of diurnal variation of the pollutants and (3) we assess the health risk due to PM2.5 and O3. Results from ground-level observations in Delhi showed that concentrations of PM10, PM2.5 and NO2 substantially dropped in 2020 during the overall study period compared to the similar period in previous years, with an average reduction of ~49%, ~39%, and ~39%, respectively. In the case of O3, the overall reduction was observed as ~19% in Delhi, while a slight increase was found in industrial and traffic regions. And consequently, the highest peak of the diurnal variation decreased substantially for all the pollutants. The health impact assessment of the changes in air quality indicated that 904 short-term premature deaths (~60%) were prevented due to the decline in PM2.5 and O3 concentrations in the study period. The restrictions on human activities during the lockdown have reduced the anthropogenic emissions and subsequently improved air quality and human health in one of the most polluted cities in the world.

Continuous increases of surface ozone and associated premature mortality growth in China during 2015-2019.

Ambient ozone (O3) pollution has become a big issue in China. Recent studies have linked long- and short-term O3 exposure to several public health risks. In this study, we (1) characterize the long-term and short-term O3-attributed health metric in China from 2015 to 2019; (2) estimate the surface O3 trends; and (3) quantify the long-term and short-term health impacts (i.e. all-cause, cardiovascular and respiratory mortality) in 350 urban Chinese cities. In these 5-years, the national annual average of daily maximum 8 h average (AVGDMA8) O3 concentrations and warm-season (April-September) 4th highest daily maximum 8 h average (4DMA8) O3 concentrations increased from 74.0 ± 15.5 µg/m3 (mean ± standard deviation) to 82.3 ± 12.0 µg/m3 and 167 ± 37.0 µg/m3 to 174 ± 30.0 µg/m3 respectively. During this period, the DMA8 O3 concentration increased by 1.9 ± 3.3 µg/m3/yr across China, with over 70% of the monitoring sites showing a positive upward trend and 19.4% with trends >5 µg/m3/yr. The estimated long-term all-cause, cardiovascular and respiratory premature mortalities attributable to AVGDMA8 O3 exposure in 350 Chinese cities were 181,000 (95% CI: 91,500-352,000), 112,000 (95% CI: 38,100-214,000) and 33,800 (95% CI: 0-71,400) in 2019, showing increases of 52.5%, 52.9% and 54.6% respectively compared to 2015 levels. Similarly, short-term all-cause, cardiovascular and respiratory premature mortalities attributed to ambient 4DMA8 O3 exposure were 156,000 (95% CI: 85,300-227,000), 73,500 (95% CI: 27,500-119,000) and 28,600 (95% CI: 14,500-42,800) in 2019, increases of 19.6%, 19.8% and 21.2% respectively compared to 2015. The results of this study are important in ascertaining the effectiveness of recent emission control measures and to identify the areas that require urgent attention.

Effects of China's current Air Pollution Prevention and Control Action Plan on air pollution patterns, health risks and mortalities in Beijing 2014-2018.

Beijing is one of the most polluted cities in the world. However, the "Air Pollution Prevention and Control Action Plan" (APPCAP), introduced since 2013 in China, has created an unprecedented drop in pollution concentrations for five major pollutants, except O3, with a significant drop in mortalities across most parts of the city. To assess the effects of APPCAP, air pollution data were collected from 35 sites (divided into four types, namely, urban, suburban, regional background, and traffic) in Beijing, from 2014 to 2018 and analyzed. Simultaneously, health-risk based air quality index (HAQI) and district-specific pollution (PM2.5 and O3) attributed mortality were calculated for Beijing. The results show that the annual PM2.5 concentration exceeded the Chinese national ambient air quality standard Grade II (35 µg/m3) in all sites, ranging from 88.5 ± 77.4 µg/m3 for the suburban site to 98.6 ± 89.0 µg/m3 for the traffic site in 2014, but was reduced to 50.6 ± 46.6 µg/m3 for the suburban site, and 56.1 ± 47.0 µg/m3 for the regional background in 2018. O3 was another most important pollutant that exceeded the Grade II standard (160 µg/m3) for a total of 291 days. It peaked at 311.6 µg/m3 in 2014 for the urban site and 290.6 µg/m3 in 2018 in the suburban site. APPCAP led to a significant reduction in PM2.5, PM10, NO2, SO2 and CO concentrations by 7.4, 8.1, 2.4, 1.9 and 80 µg/m3/year respectively, though O3 concentration was increased by 1.3 µg/m3/year during the five-years. HAQI results suggest that during the high pollution days, the more vulnerable groups, such as the children, and the elderly, should take additional precautions, beyond the recommendations currently put forward by Beijing Municipal Environmental Monitoring Center (BJMEMC). In 2014, PM2.5 and O3 attributed to 29,270 and 3,030 deaths respectively, though in 2018 their mortalities were reduced by 5.6% and 18.5% respectively. The highest mortality was observed in Haidian and Chaoyang districts, two of the most densely populated areas in Beijing. Beijing's air quality has seen a dramatic improvement over the five-year period, which can be attributable to the implementation of APPCAP and the central government's determination, with significant drops in the mortalities due to PM2.5 and O3 in parallel. To further improve air quality in Beijing, more stringent regulatory measures should be introduced to control volatile organic compounds (VOCs) and reduce O3 concentrations. Consistent air pollution control interventions will be needed to ensure long-term prosperity and environmental sustainability in Beijing, China's most powerful city. This study provides a robust methodology for analyzing air pollution trends, health risks and mortalities in China. The crucial evidence generated forms the basis for the governments in China to introduce location-specific air pollution policy interventions to further reduce air pollution in Beijing and other parts of China. The methodology presented in this study can form the basis for future fine-grained air pollution and health risk study at the city-district level in China.

Spatio-temporal variations and trends of major air pollutants in China during 2015-2018.

The Chinese government, as a policy response, has continued to invest efforts and resources to implement cost-effective air pollution control technologies and stringent regulation to reduce emissions from the most contributing sectors to protect the environment and public health. The higher density of monitoring stations (> 1600) distributed across China provides a timely opportunity to use them to study in detail the national pollution trends in light of more stringent air pollution control policies. In the present study, air quality datasets comprising hourly concentrations of PM2.5, O3, NO2, and SO2 collected across 1309, 1341, 1289, and 1347 monitoring stations respectively were obtained from the National Environmental Monitoring Centre over 4 years (2015-2018) and trend analysis was performed. Results indicate that the overall annual trends for PM2.5 and SO2 were - 2.9 ± 2.7 and - 3.2 ± 3.2 µg/m3/year, while the winter trends were - 4.8 ± 5.8 and - 6.9 ± 8.4 µg/m3/year respectively across China. The daily maximum 8-h average (DMA8) ozone concentration showed a significant positive trend of 2.4 ± 4.6 µg/m3/year, which was comparatively higher in summer at 4.4 ± 9.0 µg/m3/year. On the other side, NO2 trend is not great in number (- 0.45 ± 2.0 µg/m3/year). Overall, 62.2%, 61.8%, and 20.9% of PM2.5, SO2, and NO2 monitoring stations were associated with a negative trend of ≥ - 2 µg/m3/year. For O3 DMA8 concentrations, 50.7% of the monitoring stations showed a significant positive trend of ≥ 2 µg/m3/year. In light of the Chinese government's increasing impetus on combating air pollution and climate change via new policy regulations, it is important to understand the spatio-temporal distributions and relative contributions of the spectrum of gaseous pollutants to the pollution loads as well as identify changing emission loads across sectors. The results of this study will facilitate the formulation of evidence-based air pollution reduction strategies and policies.

Substantial changes in PM2.5 pollution and corresponding premature deaths across China during 2015-2019: A model prospective.

Long-term exposure to the ambient fine particulate matter (PM2.5) is the major public health risk factor in China. Several past studies have assessed premature mortalities associated with PM2.5 in China at varying levels of temporal and spatial scales using different methodological approaches. However, recently developed global exposure mortality model [GEMM NCD + LRI and GEMM 5-COD] provides a much more sophisticated methodology in capturing mortality due to PM2.5-exposure than the commonly accepted integrated exposure-response (IER) model, which this study applied to China. This study provides a comparative assessment of the excess long-term PM2.5-attributed nonaccidental deaths as well as cause-specific deaths for 349 cities in mainland China during five years (from 2015 to 2019) and compares the results with the spatial resolution scale of 0.1° × 0.1° across overall China. The results demonstrate that the national annual average PM2.5 concentration declined from 51.9 ± 18.2 µg/m3 in 2015 to 39.0 ± 13.2 µg/m3 in 2019, and the overall annual negative trend was around -3.1 ± 2.2 µg/m3/year [-5.6 ± 3.4%/year] across China. Consequently, the number of PM2.5-related deaths decreased by 383 thousand [95% CI: 331-429] to 1755 thousand [95% Confidence Interval: 1470-2025; GEMM NCD + LRI]; 315 thousand [95% CI: 227-370] to 1380 thousand [95% CI: 948-1740; GEMM 5-COD] and 125 thousand [95% CI: 64-140] to 876 thousand [95% CI: 394-1262; IER] in 2019, derived from the pre-established models (GEMM and IER). The estimate PM2.5-attributed death with a spatial resolution of 0.1° × 0.1° was 2419 thousand [95% CI: 2041-2771; GEMM NCD + LRI], 1918 thousand [95% CI: 1333-2377; GEMM 5-COD] and 1162 thousand [95% CI: 534-1611; IER] in 2015, which is about 11-16% higher value than the city-level health risk assessment study. The estimated deaths by GEMM NCD + LRI and GEMM 5-COD were 104% and 61% higher than the estimated by IER, highlighting that total premature mortalities associated with PM2.5 were substantially left behind based on the pre-existing model. The "other noncommunicable diseases" mortality, which IER method doesn't account for, was 375 thousand in 2019, 68 thousand less than in 2015. Such significant mortality was previously overlooked in estimation methods, which should now be considered for the air pollution-related policy development in China. The high number of premature deaths in central and northern parts of China, calls for the need for the Government to quickly impose even more stringent and effective pollution control measures.

Ozone pollution in Chinese cities: Assessment of seasonal variation, health effects and economic burden.

The ground-level ozone (O3) concentration in the urban regions of China has become an increasingly noticeable environmental problem in recent years. Many epidemiological studies have reported the association between O3 pollution and mortality, only a few studies have focused on the O3-related mortality and corresponding economic effects at the Chinese city and province level. This study reports the seasonal variation of ground-level O3 in 338 cities of China during the year 2016 and evaluates its effect on premature mortality and economic loss. It further illustrates the differences in cause-specific mortality outcomes of the log-linear and linear model, two of the prominently used methods for estimating health effects. In 2016, the annual average daily maximum 8-h O3 concentration in China ranged between 74 and 201 µg/m3 (138 ±â€¯24.7 µg/m3). 30% of the total population was exposed to >160 µg/m3 O3 concentration (Chinese national ambient air quality standard) and about 67.2% urban population lived in exposure above the WHO recommended O3 concentrations (100 µg/m3). The estimated national O3-attributable mortality was 74.2 × 103 (95% CI: 16.7×103-127×103) in the log-linear model, whereas, the total O3-related mortality using the linear model was 69.6 × 103 (95% CI: 16.2 × 103-115 × 103). The exposure to O3 caused a nationwide economic loss of about 7.6 billion US$ (range: 1.7-12.9) in 2016. This study uniquely provides most comprehensive coverage of the Chinese cities for O3 associated mortality utilizing ground level measurement data for 2016 and presents a measurable assessment to the policymakers of China for streamlining their efforts on air quality improvement and O3 containment.

PM2.5-related health and economic loss assessment for 338 Chinese cities.

China is in a critical stage of ambient air quality management after global attention on pollution in its cities. Industrial development and urbanization have led to alarming levels of air pollution with serious health hazards in densely populated cities. The quantification of cause-specific PM2.5-related health impacts and corresponding economic loss estimation is crucial for control policies on ambient PM2.5 levels. Based on ground-level direct measurements of PM2.5 concentrations in 338 Chinese cities for the year 2016, this study estimates cause-specific mortality using integrated exposure-response (IER) model, non-linear power law (NLP) model and log-linear (LL) model followed by morbidity assessment using log-linear model. The willingness to pay (WTP) and cost of illness (COI) methods have been used for PM2.5-attributed economic loss assessment. In 2016 in China, the annual PM2.5 concentration ranged between 10 and 157 µg/m3 and 78.79% of the total population was exposed to >35 µg/m3 PM2.5 concentration. Subsequently, the national PM2.5-attributable mortality was 0.964 (95% CI: 0.447, 1.355) million (LL: 1.258 million and NPL: 0.770 million), about 9.98% of total reported deaths in China. Additionally, the total respiratory disease and cardiovascular disease-specific hospital admission morbidity were 0.605 million and 0.364 million. Estimated chronic bronchitis, asthma and emergency hospital admission morbidity were 0.986, 1.0 and 0.117 million respectively. Simultaneously, the PM2.5 exposure caused the economic loss of 101.39 billion US$, which is 0.91% of the national GDP in 2016. This study, for the first time, highlights the discrepancies associated with the three commonly used methodologies applied for cause-specific mortality assessment. Mortality and morbidity results of this study would provide a measurable assessment of 338 cities to the provincial and national policymakers of China for intensifying their efforts on air quality improvement.

Estimating premature mortality attributable to PM2.5 exposure and benefit of air pollution control policies in China for 2020.

In past decade of rapid industrial development and urbanization, China has witnessed increasingly persistent severe haze and smog episodes, posing serious health hazards to the Chinese population, especially in densely populated cities. Quantification of health impacts attributable to PM2.5 (particulates with aerodynamic diameter≤2.5µm) has important policy implications to tackle air pollution. The Chinese national monitoring network has recently included direct measurements of ground level PM2.5, providing a potentially more reliable source for exposure assessment. This study reports PM2.5-related long-term mortality of year 2015 in 161 cities of nine regions across China using integrated exposure risk (IER) model for PM2.5 exposure-response functions (ERF). It further provides an estimate of the potential health benefits by year 2020 with a realization of the goals of Air Pollution Prevention and Control Action Plan (APPCAP) and the three interim targets (ITs) and Air Quality Guidelines (AQG) for PM2.5 by the World Health Organization (WHO). PM2.5-related premature mortality in 161 cities was 652 thousand, about 6.92% of total deaths in China during year 2015. Among all premature deaths, contributions of cerebrovascular disease (stroke), ischemic heart disease (IHD), chronic obstructive pulmonary disease (COPD), lung cancer (LC) and acute lower respiratory infections (ALRIs) were 51.70, 26.26, 11.77, 9.45 and 0.82%, respectively. The premature mortality in densely populated cities is very high, such as Tianjin (12,533/year), Beijing (18,817/year), Baoding (10,932/year), Shanghai (18,679/year), Chongqing (23,561/year), Chengdu (11,809/year), Harbin (9037/year) and Linyi (9141/year). The potential health benefits will be 4.4, 16.2, 34.5, 63.6 and 81.5% of the total present premature mortality when PM2.5 concentrations in China meet the APPCAP, WHO IT-1, IT-2, IT-3 and AQG respectively, by the year 2020. In the current situation, by the end of year 2030, even if Chines government fulfills its own target to meet national ambient air quality standard of PM2.5 (35µg/m3), total premature mortality attributable to PM2.5 will be 574 thousand across 161 cities. The present methodology will greatly help policy makers and pollution control authorities to further analyze cost and benefits of air pollution management programs in China.

Burden of disease attributed to ambient PM2.5 and PM10 exposure in 190 cities in China.

Particulate air pollution is becoming a serious public health concern in urban cities of China. Association of disability-adjusted life years (DALYs) and economic loss with air pollution-related health effects demand quantitative analysis for correctional measures in air quality. This study applies an epidemiology-based exposure-response function to obtain the quantitative estimate of health impact of particulate matter PM2.5 and PM10 across 190 cities of China during years 2014-2015. The annual average concentration of PM2.5 and PM10 is 57 ± 18 µg/m3 (ranging from 18 to 119 µg/m3) and 97.7 ± 34.2 µg/m3 (ranging from 33.5 to 252.8 µg/m3), respectively. Based on the present study, the total estimated annual premature mortality due to PM2.5 is 722,370 [95% confidence interval (CI) = 322,716-987,519], 79% of which accounts for adult cerebrovascular disease (stroke) and ischemic heart disease (IHD). The premature mortality in megacities is very high, such as Chongqing (25,162/year), Beijing (19,702/year), Shanghai (19,617/year), Tianjin (13,726/year), and Chengdu (12,356/year). PM10 pollution has caused 1,491,774 (95% CI = 972,770-1,960,303) premature deaths (age >30) in China. Further, 3,614,064 cases of chronic bronchitis (CB); 13,759,894 cases of asthma attack among all ages; 191,709 COPD-related hospital admission (HA) cases; 499,048 respiratory-related HA; 357,816 cerebrovascular HA; and 308,129 cardiovascular-related HA due to PM10 pollution have been estimated during 2014-2015. Chongqing, Beijing, Baoding, Tianjin, and Shijiazhuang are the top five contributors to pollution-related mortality, accounting for 3.10, 2.71, 2.49, 2.20, and 2.02%, respectively, of the total deaths caused by PM10 pollution. The total DALYs associated with PM2.5 and PM10 pollution in China is 7.2 and 20.66 million in 2014-2015, and mortality and chronic bronchitis shared about 93.3% of the total DALYs for PM10. During this period, the economic cost of health impact due to PM10 is approximately US$304,122 million, which accounts for about 2.94% of China's gross domestic product (GDP). Megacities are expected to contribute relatively more to the total costs. The present methodology could be used as a tool to help policy makers and pollution control board authorities, to further analyze costs and benefits of air pollution management programs in China.

Disability-adjusted life years and economic cost assessment of the health effects related to PM2.5 and PM10 pollution in Mumbai and Delhi, in India from 1991 to 2015.

Particulate air pollution is becoming a serious public health concern in urban cities in India due to air pollution-related health effects associated with disability-adjusted life years (DALYs) and economic loss. To obtain the quantitative result of health impact of particulate matter (PM) in most populated Mumbai City and most polluted Delhi City in India, an epidemiology-based exposure-response function has been used to calculate the attributable number of mortality and morbidity cases from 1991 to 2015 in a 5-year interval and the subsequent DALYs, and economic cost is estimated of the health damage based on unit values of the health outcomes. Here, we report the attributable number of mortality due to PM10 in Mumbai and Delhi increased to 32,014 and 48,651 in 2015 compared with 19,291 and 19,716 in year 1995. And annual average mortality due to PM2.5 in Mumbai and Delhi was 10,880 and 10,900. Premature cerebrovascular disease (CEV), ischemic heart disease (IHD), and chronic obstructive pulmonary disease (COPD) causes are about 35.3, 33.3, and 22.9% of PM2.5-attributable mortalities. Total DALYs due to PM10 increased from 0.34 million to 0.51 million in Mumbai and 0.34 million to 0.75 million in Delhi from average year 1995 to 2015. Among all health outcomes, mortality and chronic bronchitis shared about 95% of the total DALYs. Due to PM10, the estimated total economic cost at constant price year 2005 US$ increased from 2680.87 million to 4269.60 million for Mumbai City and 2714.10 million to 6394.74 million for Delhi City, from 1995 to 2015, and the total amount accounting about 1.01% of India's gross domestic product (GDP). A crucial presumption is that in 2030, PM10 levels would have to decline by 44% (Mumbai) and 67% (Delhi) absolutely to maintain the same health outcomes in year 2015 levels. The results will help policy makers from pollution control board for further cost-benefit analyses of air pollution management programs in Mumbai and Delhi.