Estimation of health benefits from air quality improvement using the MODIS AOD dataset in Seoul, Korea

Benefits of Short-term Premature Mortality Reduction Attributed to PM2.5 Pollution: A Case Study in Long an Province, Vietnam

PM2.5 pollution exposure is the leading cause of disease burden globally, especially in low- and middle-income countries, including Vietnam. Therefore, economic damage in this context must be quantified. Long An province in the Southern Key Economic (SKE) region was selected as a research area. This study aimed to evaluate PM2.5-related human health effects causing early deaths attributable to respiratory, cardiovascular, and circulatory diseases in all ages and genders. Health end-points and health impact estimation, economic loss model, groups of PM2.5 concentration data, data of exposed population, data of baseline premature mortality rate, and data of health impact functions were used. Hourly PM2.5 concentration data sets were generated specifically using the coupled Weather Research and Forecasting Model (WRF)/Community Multiscale Air Quality Modelling System (CMAQ) models. Daily PM2.5 pollution levels considered mainly in the dry season (from January to April 2018) resulted in 12.9 (95% CI - 0.6; 18.7) all-cause premature deaths per 100,000 population, of which 7.8 (95% CI 1.1; 7.1), 1.5 (95% CI - 0.2; 3.1), and 3.6 (95% CI - 1.5; 8.5) were due to respiratory diseases (RDs; 60.54%), cardiovascular diseases (CVDs; 11.81%), and circulatory system diseases (CSDs; 27.65%) per 100,000 population, respectively. The total economic losses due to acute PM2.5 exposure-related premature mortality cases reached 62.0 (95% CI - 2.7; 89.6) billion VND, equivalent to 8.3 (95% CI - 0.4; 12.0) million USD. The study outcomes contributed remarkably to the generation and development of data sources for effectively managing ambient air quality in Long An.

Chronic and acute health effects of PM2.5 exposure and the basis of pollution control targets

Ho Chi Minh City (HCMC) is changing and expanding quickly, leading to environmental consequences that seriously threaten human health. PM2.5 pollution is one of the main causes of premature death. In this context, studies have evaluated strategies to control and reduce air pollution; such pollution-control measures need to be economically justified. The objective of this study was to assess the socio-economic damage caused by exposure to the current pollution scenario, taking 2019 as the base year. A methodology for calculating and evaluating the economic and environmental benefits of air pollution reduction was implemented. This study aimed to simultaneously evaluate the impacts of both short-term (acute) and long-term (chronic) PM2.5 pollution exposure on human health, providing a comprehensive overview of economic losses attributable to such pollution. Spatial partitioning (inner-city and suburban) on health risks of PM2.5 and detailed construction of health impact maps by age group and sex on a spatial resolution grid (3.0 km × 3.0 km) was performed. The calculation results show that the economic loss from premature deaths due to short-term exposure (approximately 38.86 trillion VND) is higher than that from long-term exposure (approximately 14.89 trillion VND). As the government of HCMC has been developing control and mitigation solutions for the Air Quality Action Plan towards short- and medium-term goals in 2030, focusing mainly on PM2.5, the results of this study will help policymakers develop a roadmap to reduce the impact of PM2.5 during 2025-2030.

Climatology and landscape determinants of AOD, SO2 and NO2 over Indo-Gangetic Plain

Indo-Gangetic Plains (IGP) experiences high loading of particulate and gaseous pollutants all year around and is considered to be the most polluted regions of India. Understanding the effect of landscape determinants on air pollution in IGP regions is crucial to make its environment sustainable. We examined satellite retrievals of OMI NO₂ and SO₂, and MODIS AOD to analyse the long-term trend, spatio-seasonal pattern and dynamics of aerosols, NO₂ and SO₂ over three IGP regions, namely Upper Indo-Gangetic plain (UIGP), Middle Indo-Gangetic plain (MIGP) and Lower Indo-Gangetic plain (LIGP) over the period 2005-2019. IGP experienced an overall increment in AOD (R² = 0.63) and SO₂ (R² = 0.67) values, with LIGP (AOD, R² = 0.8 & SO₂, R² = 0.8) experiencing the largest rate of enhancement. The levels of NO₂ (R² = 0.2) experienced a decrement after 2012 (owing to implementation of vehicle emission policy) except in MIGP, with UIGP (R² = 0.23) exhibiting the largest rate of decrement. Seasonal heterogeneity in the nature of sources was observed over IGP regions. AOD (0.61 ± 0.1) and NO₂ value (3.82 ± 0.98 × 10¹⁵ molecules/cm²) were found highest during post-monsoon in UIGP owing to crop residue burning activity. The value of NO₂ (3.8 ± 1.4 × 10¹⁵ molecules/cm²) in MIGP was found highest during pre-monsoon due to high consumption of coal in power plants for summer cooling demand. The highest SO₂ level (0.09 ± 0.06 DU) was observed during post-monsoon in UIGP, as a large number of brick kilns are fired during this period. Correlations among landscape determinants and pollutants revealed that topography is the dominant variable that affect the spatial pattern of AOD compared to vegetation and land use. Lower elevation tends to have high AOD values compared to higher elevation. Vegetation-AOD relationship showed an inverse association in IGP regions and is influenced by factors such as seasonal meteorology and size of the airborne particles. Vegetation possesses positive relationship with SO₂ and NO₂, implying no pollution abatement effect on SO₂ and NO₂ pollutants. Built-up change has deteriorating effect as well as quenching effect on pollutants. Increase in built terrain have deteriorated the air quality in UIGP whereas it favored in suppressing the aerosol level in LIGP.

Health impact assessment and evaluation of economic costs attributed to PM2.5 air pollution using BenMAP-CE

Air pollution is considered the most prominent public health. Economically, air pollution imposes additional costs on governments. This study aimed to quantify health effects and associated economic values of reducing PM_2.5 air pollution using BenMAP-CE in Qom in 2019. The air quality data were acquired from Qom Province Environmental Protection Agency, and the population data were collected from Qom Province Management and Planning Organization website. The number of deaths due to Stroke, Chronic Obstructive Pulmonary Disease, Lung Cancer, and Ischemic Heart Disease attributable to PM_2.5 were estimated using BenMAP-CE based on two control scenarios, 2.4 and 10 μg/m³, known as scenarios I and II, respectively. The associated economic effect of premature deaths was assessed by value of a statistical life (VSL) approach. The annual average of PM_2.5 concentration was found to be 16.32 μg/m³ (SD: 9.93). A total of 4694.5 and 2475.94 premature deaths in scenarios I and II were found to be attributable to PM_2.5 in overall, respectively. The total associated cost was calculated to be 855.91 and 451.40 million USD in scenarios I and II, respectively. The total years of life lost due to PM_2.5 exposure in 2019 was 158,657.06 and 78,351.51 in scenarios I and II, respectively. The results of both health and economic assessment indicate the importance of solving the air pollution problem in Qom, as well as other big cities in Iran. The elimination of limitations, such as insufficient local data, should be regarded in future studies.

Comparison of PM2.5 in Seoul, Korea Estimated from the Various Ground-Based and Satellite AOD

Based on multiple linear regression (MLR) models, we estimated the PM2.5 at Seoul using a number of aerosol optical depth (AOD) values obtained from ground-based and satellite remote sensing observations. To construct the MLR model, we consider various parameters related to the ambient meteorology and air quality. In general, all AOD values resulted in the high quality of PM2.5 estimation through the MLR method: mostly correlation coefficients >~0.8. Among various polar-orbit satellite AODs, AOD values from the MODIS measurement contribute to better PM2.5 estimation. We also found that the quality of estimated PM2.5 shows some seasonal variation; the estimated PM2.5 values consistently have the highest correlation with in situ PM2.5 in autumn, but are not well established in winter, probably due to the difficulty of AOD retrieval in the winter condition. MLR modeling using spectral AOD values from the ground-based measurements revealed that the accuracy of PM2.5 estimation does not depend on the selected wavelength. Although all AOD values used in this study resulted in a reasonable accuracy range of PM2.5 estimation, our analyses of the difference in estimated PM2.5 reveal the importance of utilizing the proper AOD for the best quality of PM2.5 estimation.

Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor?

Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-temporal characteristics. However, long-time sequences and detailed AOD information can not be provided due to currently limited monitoring technology. In this paper, a daily AOD product, MODIS-based Multi-angle Implementation of Atmospheric Correction (MAIAC), is deployed to analyze the spatio-temporal characteristics in Xinjiang Uygur Autonomous Region from 2000 to 2019. In addition, the importance of influencing factors for AOD is calculated through Random Forest (RF) Model and the propagation trajectories of pollutants are simulated through Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Spatio distribution of AOD presents a tendency that AOD value in northern Xinjiang is low while the value in southern Xinjiang is high. Regions with high AOD values are mainly concentrated in Tarim Basin. AOD in southern Xinjiang is the highest, followed by that in eastern Xinjiang and AOD value in northern Xinjiang is the lowest. Seasonal variation of AOD is significant: Spring (0.309) > summer (0.200) > autumn (0.161) > winter (0.158). Average AOD value in Xinjiang is 0.196. AOD appears wavy from 2000 to 2014 with its low inflection point (0.157) appearing in 2005, and then increases, reaching its peak in 2014 (0.223). The obvious downward tendency after 2014 shows that the use of coal to natural gas (NG) conversion project improves the conditions of local environment. According to RF Model, NG contributes most to AOD. HYSPLIT Model reveals that aerosol in southern Xinjiang is related to the short-distant carriage of dust aerosol from the Taklimakan Desert. Aerosol there can affect Inner Mongolia through long-distant transport. Blocked by the Tianshan Mountains, fine dust particles can not cross the Tianshan Mountains to become a factor contributing to AOD in northern Xinjiang.

Review on pollution damage costs accounting

Although the concept of damage cost accounting is already well-studied and applied, its application to pollution still lacks of an integrated accounting framework, while the spatial-temporal variability of accounting results has not been fully discussed. To fill this gap, this review frames the existing models and their limitations into static and dynamic categories, outlining the characteristics of different methods, which consider both human and non-human damages caused by pollution. Existing data sources, that could be used for accounting purposes, are detailed. Finally, this work discusses the relevance of spatial scales for the computation process, in order to obtain a more detailed information support for environmental policies for future compensatory actions. Conclusions highlights the need to develop a more comprehensive database of exposure-response relationships and to incorporate system alternatives into models to achieve a more accurate damage assessment.

Efficiency in reducing air pollutants and healthcare expenditure in the Seoul Metropolitan City of South Korea

This study analyzes efficiency in the reduction of air pollutants and the associated healthcare costs using a stochastic frontier cost function panel data approach. For the empirical analysis, we use monthly data covering 25 districts in the Seoul metropolitan city of South Korea observed over the period January 2010 to December 2017. Our results show large variations in air pollution and healthcare costs across districts and over time and their efficiency in reducing air pollutants. The study concludes that efforts are needed to apply the World Health Organization's air quality standards for designing and implementing location-specific customized policies for improving the level of air quality and its equal distribution, provision of health services, and improved efficiency in improving air quality standards. The study identifies a number of determinants of air pollutants and efficiency enhancement which provide useful pointers for policymakers for addressing the current environmental problems in South Korea.

Air Pollution Health Risk Assessment (AP-HRA), Principles and Applications

Air pollution is a major public health problem. A significant number of epidemiological studies have found a correlation between air quality and a wide variety of adverse health impacts emphasizing a considerable role of air pollution in the disease burden in the general population ranging from subclinical effects to premature death. Health risk assessment of air quality can play a key role at individual and global health promotion and disease prevention levels. The Air Pollution Health Risk Assessment (AP-HRA) forecasts the expected health effect of policies impacting air quality under the various policy, environmental and socio-economic circumstances, making it a key tool for guiding public policy decisions. This paper presents the concept of AP-HRA and offers an outline for the proper conducting of AP-HRA for different scenarios, explaining in broad terms how the health hazards of air emissions and their origins are measured and how air pollution-related impacts are quantified. In this paper, seven widely used AP-HRA tools will be deeply explored, taking into account their spatial resolution, technological factors, pollutants addressed, geographical scale, quantified health effects, method of classification, and operational characteristics. Finally, a comparative analysis of the proposed tools will be conducted, using the SWOT (strengths, weaknesses, opportunities, and threats) method.

Model for assessing health damage from air pollution in quarrying area - Case study at Tan Uyen quarry, Ho Chi Minh megapolis, Vietnam

Vietnam has a great demand for stone exploitation for the development of the country's infrastructure, reaching 181 million m³ in 2020. Mining activities are always accompanied by environmental pollution, negatively affecting public health. To accurately assess the level of pollution, as well as quantify the effect of air pollution on human health, a number of structures, methods, and models provide tools to assess the benefits of this control for public health and related economic values. However, there has been no research in Vietnam applied specifically to this type of stone exploitation. This study offers a model to evaluate the economic damage caused by dust exposure from activities related to quarrying, overcoming the lack of continuous monitoring data. The area selected for research is Binh Duong province, in the Ho Chi Minh megapolis, Vietnam, which has two construction quarries, Thuong Tan and Tan My, with a current annual production of approximately 4–5 million m³. The calculation results show that the damage to human health is estimated at approximately 9,643 billion dong a year, equivalent to 15.03 million USD. In addition, if the standard criteria are tightened, damage will continue to increase. This study also analyses some of the difficulties and limitations in the modelling process.

Pollution Weather Prediction System: Smart Outdoor Pollution Monitoring and Prediction for Healthy Breathing and Living

Air pollution has been a looming issue of the 21st century that has also significantly impacted the surrounding environment and societal health. Recently, previous studies have conducted extensive research on air pollution and air quality monitoring. Despite this, the fields of air pollution and air quality monitoring remain plagued with unsolved problems. In this study, the Pollution Weather Prediction System (PWP) is proposed to perform air pollution prediction for outdoor sites for various pollution parameters. In the presented research work, we introduced a PWP system configured with pollution-sensing units, such as SDS021, MQ07-CO, NO2-B43F, and Aeroqual Ozone (O₃). These sensing units were utilized to collect and measure various pollutant levels, such as PM2.5, PM10, CO, NO₂, and O₃, for 90 days at Symbiosis International University, Pune, Maharashtra, India. The data collection was carried out between the duration of December 2019 to February 2020 during the winter. The investigation results validate the success of the presented PWP system. In the conducted experiments, linear regression and artificial neural network (ANN)-based AQI (air quality index) predictions were performed. Furthermore, the presented study also found that the customized linear regression methodology outperformed other machine-learning methods, such as linear, ridge, Lasso, Bayes, Huber, Lars, Lasso-lars, stochastic gradient descent (SGD), and ElasticNet regression methodologies, and the customized ANN regression methodology used in the conducted experiments. The overall AQI values of the air pollutants were calculated based on the summation of the AQI values of all the presented air pollutants. In the end, the web and mobile interfaces were developed to display air pollution prediction values of a variety of air pollutants.

Association between long-term exposure to air pollutants and cardiopulmonary mortality rates in South Korea

Background

The association between long-term exposure to air pollutants, including nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂), ozone (O₃), and particulate matter 10 μm or less in diameter (PM₁₀), and mortality by ischemic heart disease (IHD), cerebrovascular disease (CVD), pneumonia (PN), and chronic lower respiratory disease (CLRD) is unclear. We investigated whether living in an administrative district with heavy air pollution is associated with an increased risk of mortality by the diseases through an ecological study using South Korean administrative data over 19 years.

Methods

A total of 249 Si-Gun-Gus, unit of administrative districts in South Korea were studied. In each district, the daily concentrations of CO, SO₂, NO₂, O₃, and PM₁₀ were averaged over 19 years (2001–2018). Age-adjusted mortality rates by IHD, CVD, PN and CLRD for each district were averaged for the same study period. Multivariate beta-regression analysis was performed to estimate the associations between air pollutant concentrations and mortality rates, after adjusting for confounding factors including altitude, population density, higher education rate, smoking rate, obesity rate, and gross regional domestic product per capita. Associations were also estimated for two subgrouping schema: Capital and non-Capital areas (77:172 districts) and urban and rural areas (168:81 districts).

Results

For IHD, higher SO₂ concentrations were significantly associated with a higher mortality rate, whereas other air pollutants had null associations. For CVD, SO₂ and PM₁₀ concentrations were significantly associated with a higher mortality rate. For PN, O₃ concentrations had significant positive associations with a higher mortality rate, while SO₂, NO₂, and PM₁₀ concentrations had significant negative associations. For CLRD, O₃ concentrations were associated with an increased mortality rate, while CO, NO₂, and PM₁₀ concentrations had negative associations. In the subgroup analysis, positive associations between SO₂ concentrations and IHD mortality were consistently observed in all subgroups, while other pollutant-disease pairs showed null, or mixed associations.

Conclusion

Long-term exposure to high SO₂ concentration was significantly and consistently associated with a high mortality rate nationwide and in Capital and non-Capital areas, and in urban and rural areas. Associations between other air pollutants and disease-related mortalities need to be investigated in further studies.

Health benefits on cardiocerebrovascular disease of reducing exposure to ambient fine particulate matter in Tianjin, China

With the development of the industrialization level in China, high concentrations of fine particulate matter (≤ 2.5 μg/m³ in aerodynamic diameter (PM_2.5)) could have a great impact on the health of the population. Our study is to quantify the health benefits on cardiocerebrovascular disease of reducing exposure to PM_2.5 in Tianjin, China. We obtained the data on cardiovascular disease (CVD), ischemic heart disease (IHD), and cerebrovascular disease (CD) mortalities to quantify the association between CVD, CD, and IHD mortalities and PM_2.5 and calculate health and economic benefits when the annual average concentration of PM_2.5 was reduced to National Ambient Air Quality Standard (NAAQS) and World Health Organization (WHO) guidelines by using our concentration response (C-R) functions. There were 435.22 (95% CI 253.86 to 616.57) all-cause, 130.22 (95% CI 66.34 to194.09) IHD, and 204.07 (95% CI 111.66 to 296.47) CD deaths attributed to PM_2.5 and the economic benefits obtained by preventing all-cause, IHD, and CD mortalities were equivalent to be 2.79%, 0.83%, and 1.31% of Baodi's GDP in Tianjin in 2017, respectively. PM_2.5 concentration was positive with all-cause, IHD, and CD mortalities in rural, suburban, and urban area of Tianjin, China. Meanwhile, the number of avoidable deaths and economic cost of reducing PM_2.5 concentrations to NAAQS and WHO guidelines was highest in the rural area.

Retrieval of Fine-Resolution Aerosol Optical Depth (AOD) in Semiarid Urban Areas Using Landsat Data: A Case Study in Urumqi, NW China

The aerosol optical depth (AOD) represents the light attenuation by aerosols and is an important threat to urban air quality, production activities, human health, and sustainable urban development in arid and semiarid regions. To some extent, the AOD reflects the extent of regional air pollution and is often characterized by significant spatiotemporal dynamics. However, detailed local AOD information is ambiguous at best due to limited monitoring techniques. Currently, the availability of abundant satellite data and constantly updated AOD extraction algorithms offer unprecedented perspectives for high-resolution AOD extraction and long-time series analysis. This study, based on the long-term sequence MOD09A1 data from 2010 to 2018 and lookup table generation, uses the improved deep blue algorithm (DB) to conduct fine-resolution (500 m) AOD (at 550 nm wavelength) remote sensing (RS) estimation on Landsat TM/OLI data from the Urumqi region, analyzes the spatiotemporal AOD variation characteristics in Urumqi and combines gray relational analysis (GRA) and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to analyze AOD influence factors and simulate pollutant propagation trajectories in representative periods. The results demonstrate that the improved DB algorithm has a high inversion accuracy for continuous AOD inversion at a high spatial resolution in urban areas. The spatial AOD distribution in Urumqi declines from urban to suburban areas, and higher AODs are concentrated in cities and along roads. Among these areas, Xinshi District has the highest AOD, and Urumqi County has the lowest AOD. The seasonal AOD variation characteristics are distinct, and the AOD order is spring (0.411) > summer (0.285) > autumn (0.203), with the largest variation in spring. The average AOD in Urumqi is 0.187, and the interannual variation generally shows an upward trend. However, from 2010 to 2018, AOD first declined gradually and then declined significantly. Thereafter, AOD reached its lowest value in 2015 (0.076), followed by a significant AOD increase, reaching a peak in 2016 (0.354). This shows that coal to natural gas (NG) project implementation in Urumqi promoted the improvement of Urumqi’s atmospheric environment. According to GRA, the temperature has the largest impact on the AOD in Urumqi (0.699). Combined with the HYSPLIT model, it was found that the aerosols observed over Urumqi were associated with long-range transport from Central Asia, and these aerosols can affect the entire northern part of China through long-distance transport.

PM2.5-Related Health Economic Benefits Evaluation Based on Air Improvement Action Plan in Wuhan City, Middle China

On the basis of PM_2.5 data of the national air quality monitoring sites, local population data, and baseline all-cause mortality rate, PM_2.5-related health economic benefits of the Air Improvement Action Plan implemented in Wuhan in 2013–2017 were investigated using health-impact and valuation functions. Annual avoided premature deaths driven by the average concentration of PM_2.5 decrease were evaluated, and the economic benefits were computed by using the value of statistical life (VSL) method. Results showed that the number of avoided premature deaths in Wuhan are 21,384 (95% confidence interval (CI): 15,004 to 27,255) during 2013–2017, due to the implementation of the Air Improvement Action Plan. According to the VSL method, the obtained economic benefits of Huangpi, Wuchang, Hongshan, Xinzhou, Jiang’an, Hanyang, Jiangxia, Qiaokou, Jianghan, Qingshan, Caidian, Dongxihu, and Hannan District were 8.55, 8.19, 8.04, 7.39, 5.78, 4.84, 4.37, 4.04, 3.90, 3.30, 2.87, 2.42, and 0.66 billion RMB (1 RMB = 0.1417 USD On 14 October 2019), respectively. These economic benefits added up to 64.35 billion RMB (95% CI: 45.15 to 82.02 billion RMB), accounting for 4.80% (95% CI: 3.37% to 6.12%) of the total GDP of Wuhan in 2017. Therefore, in the process of formulating a regional air quality improvement scheme, apart from establishing hierarchical emission-reduction standards and policies, policy makers should give integrated consideration to the relationship between regional economic development, environmental protection and residents’ health benefits. Furthermore, for improving air quality, air quality compensation mechanisms can be established on the basis of the status quo and trends of air quality, population distribution, and economic development factors.