Cost of economic growth: Air pollution and health expenditure

Synthesis of satellite and ground data provide unique perspectives for discovering the air pollution patterns: A case study in Guangdong Province, China

Existing studies have analyzed the spatio-temporal patterns of air pollutants by combining ground and satellite measurements, primarily for cross-validation purposes. However, the unique characteristics and discrepancies between satellite and ground measurements have rarely been leveraged to understand pollution patterns and identify air pollution sources. To our best knowledge, this study is the first to utilize these discrepancies to holistically analyze the spatial and temporal patterns and investigate local biomass-burning effects on the five typical air pollutants: particulate matter (PM2.5)/aerosol optical depth (AOD), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and ozone (O3). Guangdong (GD) province was selected as a case study due to its complex air pollution sources and patterns. Ground-based analysis from 2015 to 2023 shows significant decreases in PM2.5, CO, NO2, and SO2, and a significant increase in O3 in urban areas, indicating the efficacy of stringent air pollution control policies. However, satellite analysis shows significant downtrend only in AOD, while the trends of other pollutants are almost negligible, which are likely to be evidence of industrial migration. Both measurements exhibit regular seasonal patterns for all air pollutants. In-depth time-series comparisons between ground and satellite data reveal seasonal consistency for NO2 but noticeable discrepancies for both AOD and CO, which could be attributed to urban-rural differences and local versus transported pollution sources. Spatially, AOD and NO2 exhibits the most significant regional discrepancies, followed by SO2 and CO, with higher values observed over Pearl River Delta (PRD) compared to non-PRD regions. O3 is more evenly distributed, showing more pronounced seasonal variations than regional differences. The synergetic use of satellite and ground measurements collectively verifies the significant local biomass-burning effects on the five pollutants. These findings can aid in developing more targeted air pollution control policies.

Public health impacts of air pollution from the spatiotemporal heterogeneity perspective: 31 provinces and municipalities in China from 2013 to 2020

Air pollution has long been a significant environmental health issue. Previous studies have employed diverse methodologies to investigate the impacts of air pollution on public health, yet few have thoroughly examined its spatiotemporal heterogeneity. Based on this, this study investigated the spatiotemporal heterogeneity of the impacts of air pollution on public health in 31 provinces in China from 2013 to 2020 based on the theoretical framework of multifactorial health decision-making and combined with the spatial durbin model and the geographically and temporally weighted regression model. The findings indicate that: (1) Air pollution and public health as measured by the incidence of respiratory diseases (IRD) in China exhibit significant spatial positive correlation and local spatial aggregation. (2) Air pollution demonstrates noteworthy spatial spillover effects. After controlling for economic development and living environment factors, including disposable income, population density, and urbanization rate, the direct and indirect spatial impacts of air pollution on IRD are measured at 3.552 and 2.848, correspondingly. (3) China's IRD is primarily influenced by various factors such as air pollution, economic development, living conditions, and healthcare, and the degree of its influence demonstrates an uneven spatiotemporal distribution trend. The findings of this study hold considerable practical significance for mitigating air pollution and safeguarding public health.

Cleaner heating policies contribute significantly to health benefits and cost-savings: A case study in Beijing, China

Cleaner heating policies aim to reduce air pollution and may bring about health benefits to individuals. Based on a fixed-effect model focusing on Beijing, this study found that after the onset of air pollution, daily clinic visits, hospitalization days, and hospitalization expenses increased several days after the occurrence of air pollution. These hospitalization changes were observed in males and females and three different age groups. A difference-in-differences (DID) model was constructed to identify the influences of cleaner heating policies on health consequences. The study revealed that the policy positively affects health outcomes, with an average decrease of 3.28 thousand clinic visits for all diseases. The total hospitalization days and expenses tend to decrease by 0.22 thousand days and 0.34 million CNY (Chinese Yuan), respectively. Furthermore, implementing the policy significantly reduced the number of daily clinic visits for respiratory diseases, asthma, stroke, diabetes, and chronic obstructive pulmonary diseases (COPDs).

Knowledge, attitudes and practices about air pollution and its health effects in 6th to 11th-grade students in Colombia: a cross-sectional study

Introduction

Globally, air pollution is the leading environmental cause of disease and premature death. Raising awareness through environmental education and adequate communication on air quality could reduce the adverse effects. We aimed to assess the knowledge, attitudes, and practices (KAP) regarding air pollution and health and determine the factors associated with these KAP in children and adolescents.

Methods

In 2019-2020, a cross-sectional study was conducted on 6th-11th grade high school students in five municipalities in Colombia. Variables collected included: age, sex, private or public school, any medical history, emergency room visits due to respiratory symptoms in the last year, and whether students played sports. The main exposure was the School Environmental Project. The outcomes were the KAP scale [0% (the lowest score) to 100% (the highest score)]. The factors associated with KAP levels were evaluated with independent mixed regressions due to the multilevel structure of the study (level 1: student; level 2: school), and the exponential coefficients (95% confidence interval-CI) were reported.

Results

Among 1,676 students included, 53.8% were females. The median knowledge score about air pollution and its health effects was 33.8% (IQR: 24.0-44.9), 38.6% knew the air quality index, 30.9% knew the air quality alerts that occurred twice a year in these municipalities and 5.3% had high self-perceived knowledge. Positive attitudes, pro-environmental practices, being female, grade level, attending a private school, having respiratory diseases, and the school environmental project importance were associated with higher knowledge scores. The median attitudes score was 78.6% (IQR: 71.4-92.9). Pro-environmental attitudes were associated with knowledge-increasing, being female, attending a private school, and the school environmental project. The median pro-environmental practices score was 28.6% (IQR: 28.6-42.9). During air quality alerts, 11.6% had worn masks, 19% had reduced the opening time of windows and 15.9% avoided leaving home. Pro-environmental practices were associated with knowledge-increasing and attitudes-increasing, and lower practices with higher grade levels, visiting a doctor in the last year, and practicing sports.

Discussion

Children and adolescents have low knowledge scores and inadequate pro-environmental practices scores regarding air pollution. However, they demonstrate positive attitudes towards alternative solutions and express important concerns about the planet's future.

Spatiotemporal changes in fine particulate matter and ozone in the oasis city of Korla, northeastern Tarim Basin of China

Air pollution is a serious environmental health concern for humans and other living organisms. This study analyzes the spatial and temporal characteristics of air pollutant concentrations, changes in the degree of pollution, and the wavelet coherence of the air quality index (AQI) with pollutants in various monitoring stations. The analysis is based on long-term time series data (January 2016 to December 2023) of air pollutants (PM2.5, PM10, and O3) from Korla, an oasis city in the northeastern part of the Tarim Basin, China. The concentrations of PM2.5, PM10, and O3 in Korla showed a cyclical trend from 2016 to 2023; PM10 concentrations exhibited all-season exceedance and PM2.5 exhibited exceedance only in spring. PM2.5 and PM10 showed a seasonal distribution of spring > winter > fall > summer; O3 concentrations showed a seasonal distribution of summer > spring > fall > winter. Strong positive wavelet coherence between PM and Air Quality Index (AQI) data series suggests that the AQI data series can effectively characterize fluctuating trends in PM concentrations. Moreover, PM10 levels IV and VI were maintained at approximately 10%, indicating that sand and dust have a substantial influence on air quality and pose potential threats to the health of urban inhabitants. Based on the results of this study, future efforts must strengthen relative countermeasures for sand prevention and control, select urban greening species with anti-pollution capabilities, rationally expand urban green spaces, and restrict regulations for reducing particulate matter emissions within city areas.

Mitigating air pollution benefits multiple sustainable development goals in China

Achieving the United nations 2030 Sustainable Development Goals (SDGs) remains a significant challenge, necessitating urgent and prioritized strategies. Among the various challenges, air pollution continues to pose one of the most substantial threats to the SDGs due to its widespread adverse effects on human health and ecosystems. However, the connections between air pollution and the SDGs have often been overlooked. This study reveals that out of the 169 SDG targets, 71 are adversely impacted by air pollution, while only 6 show potential positive effects. In China, two major atmospheric nitrogen pollutants, ammonia and nitrogen oxides, resulted in an economic loss of 400 billion United States Dollar (USD) in 2020, which could be reduced by 33% and 34% by 2030, respectively. It would enhance the progress towards SDGs in China by 14%, directly contributing to the achievement of SDGs 1 to 6 and 11 to 15. This improvement is estimated to yield overall benefits totaling 119 billion USD, exceeded the total implementation cost of 82 billion USD with ammonia as the preferential mitigation target. This study underscores the importance of robust scientific evidence in integrated policies aimed at aligning improvements in environmental quality with the priorities of sustainable development.

Fresh evidence of the impact of economic complexity, health expenditure, natural resources, plastic consumption, and renewable energy in air pollution deaths in the USA? An empirical approach

Most plastic waste generated from plastic consumption cannot be recycled and is destroyed by burning. As a result of burning plastics, microplastics spread into the atmosphere, increasing air pollution. Respiratory diseases and chronic health problems are caused by air pollution. Approximately 7 million people die each year due to pollution-related ailments. Therefore, it is crucial to provide empirical evidence rather than approximate estimates of the role of plastic consumption in air pollution-related deaths. Also, understanding the causes of air pollution-related deaths and demonstrating the policies' effectiveness will provide valuable insights for policymakers, the international community, and researchers. This study investigates the effects of plastic consumption, health expenditures, natural resources, economic complexity, and renewable energy on air pollution deaths in the USA from 1995 to 2019 using the novel Fourier Augmented ARDL method. The findings show that plastic consumption, health expenditures, natural resources, and economic complexity increase air pollution deaths, while renewable energy decreases it. Such findings imply that plastic consumption is an essential determinant of air pollution-related mortality, that health policy must be reconsidered, that efficient use of resources is important and that sophisticated economic structures do not always produce the desired results. Overall, policymakers should review health policies to reduce deaths from air pollution and take measures to support green growth using renewable energy and economic complexity tools.

Does new energy demonstration city policy curb air pollution? Evidence from Chinese cities

China has embarked on realizing a green-oriented energy structure transition with a series of policy tools. In 2014, the National Energy Administration launched a new energy demonstration city (NEDC) policy, but its effect on air pollution mitigation has not been fully examined. By employing the Difference-in-difference strategy, this study examines the effect of the NEDC policy on air pollution mitigation with Chinese prefecture-level city data. The results reveal that the NEDC policy can significantly lead to a 0.13-unit drop in SO2 emissions. The NEDC policy curbs pollution by stimulating green investments, promoting green technology innovation, advancing resource allocation efficiency, and reducing energy consumption. The effect of the NEDC policy appears to be heterogeneous under different conditions. Furthermore, this phenomenon is more conspicuous in prefectures led by older officials, where the age incentives nearing the promotion golden age threshold amplify the effects of air pollution mitigation, while those nearing retirement years exacerbate such effects. Notably, the interaction effect between environmental regulations and the NEDC policy on air pollution mitigation is elucidated. Moreover, positive spatial spillover effects extending to neighboring regions are identified, underscoring the imperative of regional collaboration and technological diffusion. Based on the findings above, several policy implications are proposed.

Application of machine learning in atmospheric pollution research: A state-of-art review

Machine learning (ML) is an artificial intelligence technology that has been used in atmospheric pollution research due to their powerful fitting ability. In this review, 105 articles related to ML and the atmospheric pollution research are critically reviewed. Applications of ML in the prediction of atmospheric pollution (mainly particulate matters) are systematically described, including the principle of prediction, influencing factors and improvement measures. Researchers can improve the accuracy of the prediction model through three main aspects, namely considering the geographical features of the study area into the model, introducing the physical characteristics of pollutants, matching and optimizing ML models. And by using interpretable ML tools, researchers are able to understand the mechanism of the model and gain in-depth information. Then, the state-of-art applications of ML in the source apportionment of atmospheric particulate matter and the effect of atmospheric pollutants on human health are also described. In addition, the advantages and disadvantages of the current applications of ML in atmospheric pollution research are summarized, and the application perspective of ML in this field is elucidated. Given the scarcity of source apportionment applications and human health research, standardized research methods and specialized ML methods are required in atmospheric pollution research to connect these two disciplines.

Consequences of Information and Communication Technologies and Environmental Degradation on Health Expenditure

This study aims to examine how the subcomponents and overall measurement of ecological footprint, as well as the use of information and communication technologies, affect health expenditures. For this study, the sample group consisted of the top 25 countries with the highest ecological footprint for the period 2000 to 2021. System GMM estimation results demonstrate that economic growth and ecological footprint have a positive impact on health expenditures. Covid-19 dummy variables, have a statistically significant and positive effect on health expenditures. On the other hand, information and communication technologies has a statistically significant but negative effect on health expenditures. The estimation results show that the Covid-19 pandemic increased health expenditures. Looking at the effect of subcomponents of environmental degradation on health expenditures, all subcomponents have a statistically significant and positive effect on health expenditures. It is seen that the most effective variable is forest products. The variable that has almost the same impact as the footprint of forest products is the carbon footprint. Carbon footprint has significant and positive impact on health expenditures, followed by fishing grounds cropland, grazing land, built-up land. The results of the study indicate which forms of pollution should be given priority by policymakers in order to prevent an increase in health expenditure resulting from environmental degradation.

Effect of inoculum type, packing material and operational conditions on the biofiltration of a mixture of hydrophobic volatile organic compounds in air

The emission of volatile organic compounds (VOCs) into the atmosphere causes negative environmental and health effects. Biofiltration is known to be an efficient and cost-effective treatment technology for the removal of VOCs in waste gas streams. However, little is known on the removal of VOC mixtures and the effect of operational conditions, particularly for hydrophobic VOCs, and on the microbial populations governing the biofiltration process. In this study, we evaluated the effect of inoculum type (acclimated activated sludge (A-AS) versus Rhodococcus erythropolis) and packing material (mixture of compost and wood chips (C + WC) versus expanded perlite) on the removal of a mixture of hydrophobic VOCs (toluene, cyclohexane and hexane) in three biofilters (BFs), i.e., BF1: C + WC and R. erythropolis; BF2: C + WC and A-AS; and BF3: expanded perlite and R. erythropolis. The BFs were operated for 374 days at varying inlet loads (ILs) and empty bed residence times (EBRTs). The results showed that the VOCs were removed in the following order: toluene > cyclohexane > hexane, which corresponds to their air-water partitioning coefficient and thus bioavailability of each VOC. Toluene is the most hydrophilic VOC, while hexane is the most hydrophobic. BF2 outperformed BF1 and BF3 in each operational phase, with average maximum elimination capacities (ECmax) of 21 ± 3 g toluene m-3 h-1 (removal efficiency (RE): 100 %; EBRT: 82 s), 11 ± 2 g cyclohexane m-3 h-1 (RE: 86 ± 6 %; EBRT: 163 s) and 6.2 ± 0.9 g hexane m-3 h-1 (RE: 96 ± 4 %; EBRT: 245 s). Microbial analysis showed that despite having different inocula, the genera Rhodococcus, Mycobacterium and/or Pseudonocardia dominated in all BFs but at different relative abundances. This study provides new insights into the removal of difficult-to-degrade VOC mixtures with limited research to date on biofiltration.

Medical cost of environmental pollution: evidence from the Chinese Social Survey

Environmental pollution impairs residents' health, while the pursuit of health is highly correlated to medical costs. Understanding how environmental pollution affects medical costs is closely linked to the welfare of society. Based on theoretical analysis, this paper uses data from 5112 households of the Chinese Social Survey (CSS) in 2019, constructs a composite indicator to quantify environmental pollution using respondents' evaluations, and empirically investigates the causal effect of environmental pollution on household medical cost and the mechanism. The conclusions are shown as follows. First, environmental pollution can increase household medical costs, and this estimation result still holds after dealing with the endogeneity problem and other robustness tests. Second, there is heterogeneity in the impact of environmental pollution on household medical costs, households in the upper socioeconomic class, with heavy pension burdens or with strong health insurance coverage are more sensitive to environmental pollution and incur relatively higher household medical costs. Third, environmental pollution reduces residents' satisfaction with their spiritual life, which adversely affects their physical and mental health and can increase household medical costs. Residents' satisfaction with their spiritual life is an important mechanism for environmental pollution to affect household health care expenditures. Therefore, governments should enhance the enforcement of environmental protection and governance, strengthen the awareness of green issues and health education, and increase the supply of facilities for leisure and sports, thus reducing medical costs due to environmental pollution and easing the medical burden of residents.

The impact of air pollution on outpatient medical service utilization and expenditure in a clean air city

BACKGROUND

Although there's increasing research on the health effects of air pollution in China, its direct influence on health-related expenditures, particularly during less severe pollution episodes, is still not well-understood. This study aims to quantify impact of three air pollutants (sulfur dioxide, nitrogen dioxide, and particulate matter) on individual healthcare spending in a city with relatively clean air.

METHODS

Using transaction-level medical social insurance data and temperature inversion as the instrumental variable, we estimate the current and cumulative effects of air pollutants on outpatient visits and medical expenses in an eastern city in China.

RESULTS

We find a significantly positive effect on outpatient visits for 15-day moving average, and a significantly positive effect on outpatient expenditure for 25-day moving average. Therefore, the cumulative effect of pollutants on medical expenditure should not be ignored. The effects on total outpatient expenditure are larger for the elderly and men. The cumulative pollution exposure increases the visits to respiratory department but also increases the expenditure on non-respiratory diseases in the long term.

CONCLUSION

Our findings provide empirical evidence that even for cities with good air quality, further improvements can improve patients' quality of life and lessen the expenditure burden on medical insurance.

Prediction of Pollutant Concentration Based on Spatial-Temporal Attention, ResNet and ConvLSTM

Accurate and reliable prediction of air pollutant concentrations is important for rational avoidance of air pollution events and government policy responses. However, due to the mobility and dynamics of pollution sources, meteorological conditions, and transformation processes, pollutant concentration predictions are characterized by great uncertainty and instability, making it difficult for existing prediction models to effectively extract spatial and temporal correlations. In this paper, a powerful pollutant prediction model (STA-ResConvLSTM) is proposed to achieve accurate prediction of pollutant concentrations. The model consists of a deep learning network model based on a residual neural network (ResNet), a spatial-temporal attention mechanism, and a convolutional long short-term memory neural network (ConvLSTM). The spatial-temporal attention mechanism is embedded in each residual unit of the ResNet to form a new residual neural network with the spatial-temporal attention mechanism (STA-ResNet). Deep extraction of spatial-temporal distribution features of pollutant concentrations and meteorological data from several cities is carried out using STA-ResNet. Its output is used as an input to the ConvLSTM, which is further analyzed to extract preliminary spatial-temporal distribution features extracted from the STA-ResNet. The model realizes the spatial-temporal correlation of the extracted feature sequences to accurately predict pollutant concentrations in the future. In addition, experimental studies on urban agglomerations around Long Beijing show that the prediction model outperforms various popular baseline models in terms of accuracy and stability. For the single-step prediction task, the proposed pollutant concentration prediction model performs well, exhibiting a root-mean-square error (RMSE) of 9.82. Furthermore, even for the pollutant prediction task of 1 to 48 h, we performed a multi-step prediction and achieved a satisfactory performance, being able to achieve an average RMSE value of 13.49.

China's air quality improvement strategy may already be having a positive effect: evidence based on health risk assessment

Aiming to investigate the health risk impact of PM2.5 pollution on a heavily populated province of China. The exposure response function was used to assess the health risk of PM2.5 pollution. Results shows that the total number of premature deaths and diseases related to PM2.5 pollution in Shandong might reach 159.8 thousand people based on the new WHO (2021) standards. The health effects of PM2.5 pollution were more severe in men than in women. Five of the 16 cities in Shandong had higher health risks caused by PM2.5 pollution, including LinYi, HeZe, JiNing, JiNan, and WeiFang. PM2.5 pollution resulted in nearly 7.4 billions dollars in healthy economic cost, which accounted for 0.57% of GDP in Shandong in 2021. HeZe, LiaoCheng, ZaoZhuang, and LinYi were the cities where the health economic loss was more than 1% of the local GDP, accounted for 1.30, 1.26, 1.08, and 1.04%. Although the more rigorous assessment criteria, the baseline concentration was lowered by 30 μg/m3 compared to our previous study, there was no significant increase in health risks and economic losses. China's air quality improvement strategy may already be having a positive effect.

The impacts of air pollution on immigrants' settlement intention in China

This paper investigates the impacts of air pollution on immigrants' willingness to settle in China. We construct a theoretical model that discusses how air pollution impacts immigrants' willingness to return home and move to other cities and illustrates how air pollution decreases the settlement intention of immigrants. The empirical results show that urban air pollution decreases immigrants' settlement intention. Robustness checks using multi-methods and multi-measures of settlement intention and air pollution support this conclusion. Air pollution has heterogeneous impacts on immigrants' settlement intentions. From the individual level, air pollution decreases the settlement intention for immigrants with 30-60 years old, middle-income migrants, and rural migrants. From the city level, air pollution decreases the settlement intention of immigrants in the eastern region, developed cities, and cities with high and low air pollution.

Exploring the relationship between air quality and health shocks to the elderly: A retrospective cross-sectional study in China

Methods

We selected 5,172 microdata on individuals from the China Health and Retirement Longitudinal Study (CHARLS) 2018. The binary logit model, the ordered logit model, and the stepwise regression were employed to compare the effects of air pollution on self-rated health (SRH) and activities of daily living (ADL) in an elderly population. The effects on health shocks were explored in different age groups, different gender groups, different regions and different sources of pollutants, respectively.

Results

We found that air pollution significantly increased the risk of health shocks in the elderly population, especially in the 60–69 year age group, and the eastern/central region, where NO2 and O3 were important pollutant sources.

Conclusion

Targeted management of the environment is necessary to improve the health status of China's elderly population. In addition, paying attention to the health status of vulnerable populations is needed to achieve social equity.

Formation mechanism of residents' intention to purchase commercial health insurance: the moderating effect of environmental pollution perception

Aim

With the development of the social economy, commercial health insurance in China has gradually been recognized by residents, but it is still in the initial stage of the market. To identify influencing factors of residents' intention to purchase commercial health insurance and to explore the influencing mechanism and heterogeneity of intention, this study aimed to reveal the formation mechanism of intention to purchase commercial health insurance.

Methods

This study introduced water and air pollution perceptions as moderating variables and, constructed a theoretical framework combining the stimulus-organism-response model and the theory of reasoned action models. The structural equation model was developed, and multigroup analysis and moderating effect analysis were carried out.

Results

The results show that advertising marketing and the behavior of relatives and friends positively influence cognition. Cognition, as well as advertising marketing and behavior of relatives and friends, has a positive impact on attitude. Furthermore, purchase intention is positively affected by cognition and attitude. Both gender and residence play a significant moderating role in influencing purchase intention. Air pollution perceptions positively moderate the path from  attitude to purchase intention.

Conclusion

The validity of the constructed model was verified and could be used to predict the willingness of residents to purchase commercial health insurance. Furthermore, policy recommendations to promote the further development of commercial health insurance were proposed. This study provides a valuable reference for insurance companies to expand the market and for the government to improve commercial insurance policies.

Improved air quality from China's clean air actions alleviates health expenditure inequality

Clean air actions aimed at improving air quality in China have brought about significant health benefits, thereby generating substantial savings in air-pollution-related healthcare spending. Yet, uneven regional air quality improvements and economic developments may alter existing inequality in health expenditures in the context of scarce healthcare resources. Here, we developed an econometric model that resolves individual characteristics at the city level to examine the disparity of public health expenditures in air quality improvements across regions differing in economic development and healthcare coverages and projected a range of future health expenditure savings under different air quality targets. We find that of the estimation on four air-pollution-related diseases (COPD, LRI, IHD, and stroke) in 98 cities over the year 2015-2017, a decline of 8.26 % in average hospitalization days and 10.21 % in hospitalization expenses was achieved, leading to a reduction of 8.09 % in total health expenditures as the implementation of clean air actions. Improved air quality has declined health expenditure inequality in low-middle cities and cities with imbalanced healthcare coverage. For example, the total expenses for the four diseases declined significantly in the low (-11.31 %) and medium (-7.34 %) per capita GDP groups, as well as a remarkable decline in the fewer medical resources. Health savings in some future scenarios are significant, showing substantial health expenditure savings under different air quality targets, but the savings will be greatly offset by an aging society. For example, In the Low-Level Improvement Pathway of air quality targets with aging (LLIPA scenario), health expenditure savings will be about 3537, 464, and 311 million CNY in the eastern, central, and western regions in 2035, respectively. Our findings thus highlight the importance of strengthening air pollution control policies and considering the equality of alleviating regional public health costs.

Spatiotemporal Evolution and Drivers of Total Health Expenditure across Mainland China in Recent Years

A substantially growing health expenditure has become an important global issue. Thus, how and why health expenditure is rising should be urgently investigated in systematic research. The Bayesian space-time model and the Bayesian least absolute shrinkage and selection operator (LASSO) model were employed in this study to investigate the spatiotemporal trends and influence patterns of total health expenditure per capita (THEPC) and total health expenditure (THEE) as a share of the gross domestic product (GDP) on the Chinese mainland from 2009 to 2018. The spatial distribution of THEE as a share of GDP in mainland China has shaped a distinct geographical structure with the characteristic of 'west high/east low'. Its local increasing trends formed a geographical structure that exhibited a 'north high/south low' feature. The heterogeneity of the influence patterns of health expenditure was observed from east to west across China. Natural environmental factors, such as air pollution and green coverage, along with changes in dietary structures, have increasingly influenced the growth of health expenditures.

The vertical distribution and potential sources of aerosols in the Yangtze River Delta region of China during open straw burning

To explore the impact of open straw burning on air quality in the Yangtze River Delta (YRD) and surrounding areas, three key cities in the YRD, namely Hefei, Nanjing, and Shanghai, were selected to observe changes in aerosol characteristics. Based on Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations from May to June 2021, the spatial-temporal distribution and potential sources of aerosol were studied. During the observation period, aerosol optical depth (AOD) in Shanghai was 55.15 % and 29.50 % higher than that in Hefei and Nanjing, respectively. For Shanghai, aerosols accumulated at night, and the aerosol extinction could reach 1.3 km^-1 in the morning. The aerosol variations in Hefei and Nanjing were consistent due to the relative conformity of the surrounding environmental conditions (R = 0.84). The vertical distribution of aerosol in all three cities had the same Gaussian shape. The aerosol lifted layers in Nanjing and Shanghai were higher than that in Hefei, with heights of 0.2-0.8 km and 0.2-0.6 km, respectively. The averaged aerosol extinctions for these two cities were 0.34 km^-1 and 0.49 km^-1, respectively. Pollution source analysis was conducted based on wind field trajectory, satellite observation, and model simulation, taking Hefei as the recipient. The results showed that western Shandong Province, northern Anhui Province, northern Jiangxi Province, central Jiangsu Province, and the central YRD were the most important aerosols sources for Hefei. The contributions of central and southern Jiangsu Province were significantly higher than those of other potential sources, with a WCWT_AOD (Meteoinfo concentration weight trajectory) between 1.2 and 3.0. The influence of fine particles produced by open biomass burning inside the YRD was significantly higher than that outside the region (outside contribution: 36.6 %). Regarding the influence between YRD cities, more aerosols were transported from Shanghai to Hefei and Nanjing, with similar transport contributions between Nanjing and Hefei.

Assessment of air quality before and during the COVID-19 and its potential health impacts in an arid oasis city: Urumqi, China

As a key node city of the "Silk Road Economic Belt" Urumqi has been listed as one of the ten most polluted cities in the world, posing a serious threat to the urban environment and residents' health. This study analyzed the air quality before and during the COVID-19 (Coronavirus disease 2019) pandemic and its potential health effects based on the data of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃_8h levels from 10 air quality monitoring stations in Urumqi from January 1, 2017, to December 31, 2021. As per the results, the concentrations of the air pollutants PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃_8h in Urumqi from 2017 to 2021 showed a cyclical trend, and the implementation of COVID-19 prevention and control measures could effectively reduce the concentration(ρ) of air pollutants. The mean value of ρ(PM_2.5) decreased from 2017 to 2021, whereas ρ(O₃_8h) showed a waveform change trend (increased in 2017-2018, decreased in 2018-2020, and increased after 2020). Meanwhile, the maximum annual average values of ρ(PM_2.5) and ρ(O₃_8h) for the six monitoring stations during 2017-2021 occurred at sites S2 (74.37 µg m^-3) and S6 (91.80 µg m^-3), respectively; rapid industrialization had a greater impact on PM_2.5 and O₃_8h concentrations compared to commercial and residential areas. In addition, the air quality index data series can characterize the fluctuation trend of PM_2.5. The high pollution levels (Class IV and V) of the air pollutants PM_2.5 and O₃_8h in Urumqi have been decreasing annually, and good days can account for 80-95% of the total number of days in the year, indicating that the number of days with a potential threat to residents' health is gradually decreasing. Therefore, more attention should be paid in controlling and managing air pollution in Urumqi.

The impact of municipal solid waste sorting policy on air pollution: Evidence from Shanghai, China

Municipal solid waste (MSW) sorting not only reduces the total quantity of domestic waste but also has positive effects on urban air quality. In this study, using a careful identification strategy and air quality data at the monitoring station level in Shanghai, we estimate the causal effect of the MSW sorting policy on urban air quality. The results show that after the MSW sorting policy was implemented, the air quality index (AQI), nitrogen dioxide (NO2) and carbon monoxide (CO) decreased significantly by 2.71%, 2.07% and 3.62%, respectively. We also find a positive spillover effect from the Shanghai MSW sorting policy on the air quality of adjacent cities. The implementation of this policy has triggered changes in residents' behaviors. However, the government needs further efforts to maintain the sustainability of MSW sorting policies.

Air pollution and refraining from visiting health facilities: a cross-sectional study of domestic migrants in China

BACKGROUND

Local environmental factors are associated with health and healthcare-seeking behaviors. However, there is a paucity in the literature documenting the link between air pollution and healthcare-seeking behaviors. This study aimed to address the gap in the literature through a cross-sectional study of domestic migrants in China.

METHODS

Data were extracted from the 2017 China Migrants Dynamic Survey (n = 10,051) and linked to the official air pollution indicators measured by particulate matter (PM_2.5 and PM₁₀) and air quality index (AQI) in the residential municipalities (n = 310) of the study participants over the survey period. Probit regression models were established to determine the association between air pollution and refraining from visiting health facilities after adjustment for variations in the predisposing, enabling and needs factors. Thermal inversion intensity was adopted as an instrumental variable to overcome potential endogeneity.

RESULTS

One unit (µg/m³) increase in monthly average PM_2.5 was associated with 1.8% increase in the probability of refraining from visiting health facilities. The direction and significance of the link remained unchanged when PM_2.5 was replaced by AQI or PM₁₀. Higher probability of refraining from visiting health facilities was also associated with overwork (β = 0.066, p = 0.041) and good self-related health (β = 0.171, p = 0.006); whereas, lower probability of refraining from visiting health facilities was associated with short-distance (inter-county) migration (β=-0.085, p = 0.048), exposure to health education (β=-0.142, p < 0.001), a high sense of local belonging (β=-0.082, p = 0.018), and having hypertension/diabetes (β=-0.169, p = 0.005).

CONCLUSION

Air pollution is a significant predictor of refraining from visiting health facilities in domestic migrants in China.

The effects of economic growth on carbon dioxide emissions in selected Sub-Saharan African (SSA) countries

This research article concerns a study of economic growth influences on carbon dioxide emissions in 20 selected Sub Saharan African (SSA) countries. The study also intends to reexamine energy consumption, tourism sector and population effect on carbon dioxide emissions. The empirical research applies panel linear regression model for the data obtained in these 20 SSA countries throughout 2000 to 2020. The empirical estimation techniques employed in the analysis consist of pooled ordinary least square (OLS), fixed effects model (FEM), random effects model (REM) and robust fixed model, including diagnostic tests such as endogeneity, heteroscedasticity and other measurements. The empirical analysis using the robust fixed effects model has established significant associations between economic growth, energy consumption, tourism sector and population on carbon dioxide emissions in SSA countries between 2000 and 2020. This study has established that a 1% increase in economy growth increases the carbon dioxide emission level by approximately 0.02%. A study has identified that SSA countries' energy consumption, especially from oil, will only contaminate air quality. A study confirmed that international tourist arrivals are one of the factors that significantly caused air quality reduction among SSA countries. However, increasing population and future international agreements and protocols could also mean that carbon emissions can potentially cause less environmental degradation in the region.

Is the key-treatment-in-key-areas approach in air pollution control policy effective? Evidence from the action plan for air pollution prevention and control in China

The "Action Plan for Air Pollution Prevention and Control from 2013 to 2017" (APAPPC) establishes the key treatment for key areas in Beijing-Tianjin-Hebei and its surroundings (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) in China. Is the key-treatment-in-key-areas approach effective? Except the targeted pollutants, does there exist the synergistic effects of other air pollutants? Are there differences between the north and the south about the effectiveness of this approach? To answer these new and key questions, this study uses the difference-in-difference (DID) model to evaluate whether it is more effective to implement key treatment policies for two targeted pollutants, PM_2.5 and PM_coarse (PM_2.5-PM₁₀), and verifies the synergistic emission-reduction effects of the policies on eight other emissions: SO₂, NO_X, VOC, CO, NH₃, BC, OC, and CO₂. At the same time, the policy effects are evaluated nationwide, in the north, and in the south using data from 2008 to 2017. The results show the following: (1) The APAPPC's establishment of the key treatment in key areas significantly reduces PM_2.5 and PM_coarse by 7.25 % and 10.49 %, respectively, compared with non-key areas nationwide. (2) The key-treatment-in-key-areas policy has synergistic effects on six other emissions: SO₂, NO_X, CO, BC, OC, and CO₂. (3) If viewing the north and the south separately, BTH beats other counterparts in the north by a large margin, while there is no significant difference among provinces and/or areas in the south. This margin is much larger than the one between key areas and other provinces nationwide. Therefore, this paper suggests that key treatment policies in key areas should continue to be implemented, especially for cities that have not dropped, but rather increased, their PM_2.5 concentrations. Additionally, air pollution goals should incorporate China's carbon peaking and neutrality goals to reduce air pollutants and greenhouse gas emissions.

The nexus among ICT, institutional quality, health expenditure, and carbon emission: a case study from Saudi Arabia

The most essential component of human capital is health capital; however, expenditures on health are gaining attention from practitioners, policymakers, and researchers. Accordingly, this study determined the dynamic association between health expenditures (HEP), economic growth (ECGW), carbon emissions (COEM), information and communication technology (ICT), institutional quality (IQ), and energy consumption (EC) in the context of Saudi Arabia. The autoregressive distributed lag and vector error correction model was employed to identify the dynamic linkages among under-considered variables by using data of 1995-2019. The empirical analysis indicated that COEM, ECGW, and EC have a positive influence on HEP, while ICT and IQ have a negative effect on HEP. There is bidirectional causality is identified between COEM, ICT, IQ, and EC, while one-way long-run causality is recognized from HEP and ECGW to these variables. Moreover, two-way short-run causality is identified between ICT and EC, whereas one-way causality is recognized from HEP and COEM to ICT. This study empirically established the essential role of IQ and ICT to enhance air quality and decrease the HEP. Consequently, policymakers should strengthen the institution and implement advanced ICTs to provide a healthy economy.

Environmental decentralization, environmental public service, and public health: evidence from 289 cities in China

Effective supply of environmental public services (EPS) is important to guarantee the mitigation of residential pollution exposure risk. This study analyzes the impact of the supply efficiency of EPS on residential health through the sample of 289 cities in China by fixed-effect model and threshold regression model. The results show that: (1) Improving the efficiency of EPS can significantly increase the efficiency of pollution control, and improve the environmental quality and health level of residents. (2) Improving the efficiency of EPS can have a greater positive effect on residents' health in areas with high-level population aging, poor medical condition, and low population density. (3) Environmental decentralization weakens the positive effect of EPS on residential health. Giving more power of environmental management to local governments may be detrimental to pollution control. Therefore, differentiated strategies of EPS should be developed to realize the equalization of basic public services with healthcare and environmental protection. It is necessary to strengthen central environmental supervision and establish resident offices for environmental supervision.

The threshold and spatial effects of PM2.5 pollution on resident health: evidence from China

Health capital investment is an integral aspect of human capital investment, and it is vitally important to improve residents' health by encouraging them to maintain insurance. This paper estimates the potential impact of particulate pollution (PM2.5) on health insurance buyers at the city level. Using PM2.5 as a representative air pollution indicator, we construct a threshold panel model and a spatial econometric model based on 2000-2019 panel data from 256 Chinese cities and the health production function to examine the impact mechanism through which PM2.5 pollution causes changes in the number of health insurance buyers. The results indicate that higher PM2.5 pollution significantly increases health insurance buyers in China. Considering the threshold effect, per capita GDP has a nonlinear relationship with an increasing marginal effect on the higher number of health insurance buyers. Due to spatial spillover effects, PM2.5 pollution has an additional impact on the number of health insurance buyers, indicating that a lack of awareness of the spatial correlation will result in underestimating the impact of PM2.5 pollution on residents' health. The robustness of adjacency and geographic distance matrices demonstrates that the regression results are robust and reliable. The findings of this study provide a practical reference for health insurers' development and policymakers' pollution control efforts.

Assessing the emission consequences of an energy rebound effect in private cars in Israel

The UN Sustainable Development Goal, SDG 7.3, is to double the global rate of improvement in energy efficiency by 2030. To meet this and other energy targets, countries encourage the development and adoption of energy-efficient products. An extensively researched phenomenon in this context is the energy rebound effect, especially in transportation. However, the direct relationship between the energy rebound effect and car emission levels has barely been investigated. Understanding this relationship is important, because energy-related emissions are closely linked to mortality, morbidity, and climate change. We assess the emission consequences in the private car market in Israel of a rebound effect associated with a policy promoting energy-efficient cars. We find that the baseline rebound before introduction of the policy was 40%. In the following three periods marked by policy changes, it grew to 54%, 69%, and 88%. Using household data with specific car characteristics and usage, we calculate the added greenhouse gas (GHG) emission consequences of this rebound by the end of the studied period to be about 5% of the country's per-capita target. Notably, estimates for the emission consequences using "average car" values were almost twice as high. The reason for this gap derives from the co-dependance between car usage and car efficiency. We discuss the implications of this gap in meeting emission goals.

Can national environmental protection supervision and control have a lasting impact on corporate production efficiency? - an empirical study based on the multi-phase difference-in-difference model

National environmental protection supervision and control has become essential means to regulate the environmental behavior of enterprises. Furthermore, the optimization, promotion, and sustainability of relevant policies are key topics of inquiry. Taking the implementation of national environmental protection supervision policies as the time series, this paper studies the impact of national environmental protection supervision and control on corporate production efficiency. It uses the multi-phase difference-in-difference (DID) method and explores the sustainability of said policies. Results indicate that, first, national environmental protection supervision and control can considerably enhance corporate production efficiency, and green technology innovation plays a vital role as an intervening variable. Second, national environmental protection supervision and control can only boost the increase in corporate production efficiency in the short term, and the impact will no longer be noticeable in the third year. This paper provides a decision-making basis for constantly boosting and revising national environmental protection supervision and control policies and stimulating green technology innovation.

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.

Corporate Non-Financial Reporting in the UK: Diversions from the EU Sustainability Reporting Framework

In late 2019, the European Union presented the EU Green Deal, which targets climate neutrality by 2050. Under the EU Green Deal’s Corporate Sustainability Reporting Directive (CSRD), a clear sustainability reporting and assurance framework was proposed as a significant aspect of the EU Sustainable Finance Package in 2021. However, because of its exit from the EU in 2020, the UK will cease to adopt EU legislations and will have to produce its own laws to achieve climate neutrality. Against this backdrop, the purpose of this paper is to explore how best to improve the non-financial reporting mechanism in the UK, in order to assist the UK in transitioning to a more sustainable economy. This paper investigates the unique challenges for non-financial reporting in the UK caused by Brexit, and the significance and effectiveness of risk-based regulation approach in the UK. The paper proposes a ‘really responsive’ industry-based non-financial reporting framework for the UK to address its unique challenges.

Transportation, Environmental Degradation, and Health Dynamics in the United States and China: Evidence From Bootstrap ARDL With a Fourier Function

Transportation and environmental degradation, with indirect and direct effects, play a significant role in determining the health of a nation's citizens. This study uses bootstrap ARDL with a Fourier function to examine transportation, environmental degradation, and health dynamics in the United States and China. In the long run, the results support the cointegration relationship between transportation, environmental degradation, and health in both countries. The results show the contingency of the causality where a negative impact of transportation on environmental degradation exists in the United States while a positive impact exists in China. The effect of environmental degradation on health is negative in the United States while a positive effect exists in China. Regarding the causal direction between the variables of interest, the implications provide policymakers in developing strategy and policy for sustainable development.

Exploring the Dynamic Nexus Among Economic Growth, Industrialization, Medical Technology, and Healthcare Expenditure: A PMG-ARDL Panel Data Analysis on Income-Level Classification Along West African Economies

This article explored the dynamic nexus among economic growth, industrialization, medical technology, and healthcare expenditure in West Africa while using urbanization and aged population as control variables. West African countries were sub-sectioned into low-income (LI) and lower-middle-income (LMI) countries. Panel data extracted from the World Development Indicators (WDI) from 2000 to 2019 were used for the study. More modern econometric techniques that are vigorous to cross-sectional dependence and slope heterogeneity were employed in the analytical process in order to provide accurate and trustworthy results. The homogeneity test and cross-sectional dependency test confirmed the studied panels to be heterogeneous and cross-sectionally dependent, respectively. Moreover, the CADF and CIPS unit root tests showed that the variables were not integrated in the same order. This, thus, leads to the employment of the PMG-ARDL estimation approach, which unveiled economic growth and urbanization as trivial determinants of healthcare expenditure in the LI and LMI panels. However, the results affirmed industrialization as a major determinant of healthcare expenditure in the LI and LMI panels. Additionally, medical technology was confirmed to decrease healthcare expenditure in the LMI panel, whereas in the LI panel, an insignificant impact was witnessed. Also, the aged population was found to intensify healthcare expenditure in both the LI and LMI panels. Lastly, on the causal connection between the series, the outcome revealed a mixture of causal paths among the variables in all the panels. Policy recommendations have therefore been proposed based on the study's findings.

Labor agglomeration and urban air pollution: research on labor force based on skill heterogeneity in China

Labor agglomeration with heterogeneous skills has different effects on urban air pollution. Based on the panel data of 263 prefecture level cities in China from 2006 to 2019, this paper constructs a Spatial Durbin Model to explore the impact of skill heterogeneous labor agglomeration and the interaction between skill heterogeneous labor agglomeration on urban air pollution. The results show that there is a positive U-shaped relationship between high-skilled labor agglomeration, low-skilled labor agglomeration, and urban air pollution. From the perspective of restraining urban air pollution, high-skilled labor agglomeration is stronger than low-skilled labor agglomeration. Under the influence of high skilled labor agglomeration, the inhibitory effect of low-skilled labor agglomeration on urban air pollution is enhanced. High-skilled labor agglomeration and low-skilled labor agglomeration reduce the degree of urban air pollution by promoting the improvement of urban innovation level. Based on this, this paper puts forward some policy suggestions, such as further promoting urban labor agglomeration, formulating reasonable urban population management policies, strengthening labor exchange and learning, and carrying out labor knowledge and skills training.

Does Air Pollution Affect Prosocial Behaviour?

Air pollution has become a serious issue that affects billions of people worldwide. The relationship between air pollution and social behaviour has become one of the most widely discussed topics in the academic community. While the link between air pollution and risk-averse and unethical behaviours has been explored extensively, the relationship between air pollution and prosocial behaviour has been examined less thoroughly. Individual blood donation is a typical form of prosocial behaviour. We examined the effect of air pollution on prosocial behaviour using the Poisson regression quasi-maximum likelihood (PQML) based on the panel data related to air pollution and blood donations. We also employed a set of control variables and robustness checks. The findings indicate that air pollution does not affect whole blood donation, although it does affect component blood donation. We also find that the effect of air pollution on blood donation is heterogeneous in terms of gender, age, and other factors. These results show that the relationship between air pollution and prosocial behaviour is limited. Not all types of prosocial behaviour are affected by air pollution, perhaps because air pollution affects only specific psychological motivations and because different types of prosocial behaviour have different motivations.

Does Public Health Influence Economic Performance? Investigating the Role of Governance and Greener Energies for the Case of China

In the last few decades, the world has faced some natural issues, due to which economic growth faces a severe threat. Natural disasters like pandemic outbreaks and man-made disasters like pollution emissions are very frequent in the current times, which also influenced the economic growth, where the institutes could play a primary role in economic growth stimulation. This study aims to analyze the association of public health expenditures, institutional quality, renewable energy, and economic performance in China. This study uses quarterly data covering the period from 1996Q1 to 2020Q4 and employs various time-series estimating approaches. The Augmented Dickey-Fuller estimates asserted that all the variables are stationary at first difference. Also, the Bayer-Hanck combined cointegration validates that all the variables are cointegrated. Employing the three long-run estimators, i.e., Fully Modified Ordinary Least Square, Dynamic Ordinary Least Square, and canonical cointegrating regression, the results asserted public health expenditures and institutional quality (including government efficiency and political stability) significantly enhances economic performance in China. Whereas two indicators of corruption control and regulatory quality do not play any significant role in promoting the economic performance of China. On the contrary, renewable energy is found negatively associated with economic performance. Also, the Pair-wise Granger causality validates mixed causal associations between the study variables. As a developing and fossil energy-dependent economy, this study provides relevant policy implications for maintaining economic growth and rebalancing economic performance in China.

Theoretical Model and Actual Characteristics of Air Pollution Affecting Health Cost: A Review

BACKGROUND

The impact of environmental pollution (such as air pollution) on health costs has received a great deal of global attention in the last 20 years.

METHODS

This review aims to summarize the theoretical analysis model of air pollution affecting health costs, and further explore the actual characteristics of the impact of air pollution on health costs. The following main databases were taken into account: Web of Science Core Collection, Medline, SCOPUS, PubMed, and CNKI (China). As of 30 March 2021, we retrieved a total of 445 papers and ended up with 52 articles.

RESULTS

This review mainly expounds clarification of the concept of air pollution and health costs, the theoretical model and the actual characteristics of air pollution affecting health costs. In addition, it also discusses other related factors affecting health costs.

CONCLUSION

Our conclusion is that, while academic research on the relationship between air pollution and health costs has made some progress, there are still some shortcomings, such as insufficient consideration of individual avoidance behavior and rural-urban and international mobility. Therefore, the simple use of the original data obtained in the statistical yearbook of the health cost caused by air pollution is also the reason for the errors in the empirical results. In addition, the choice of proxy variables of environmental pollution by scholars is relatively simple, mainly focusing on air pollutants, while the impact of water quality or soil pollution safety on health costs is becoming increasingly prominent, and will become the focus of future research.

Mindful Application of Digitalization for Sustainable Development: The Digitainability Assessment Framework

Digitalization is widely recognized as a transformative power for sustainable development. Careful alignment of progress made by digitalization with the globally acknowledged Sustainable Development Goals (SDGs) is crucial for inclusive and holistic sustainable development in the digital era. However, limited reference has been made in SDGs about harnessing the opportunities offered by digitalization capabilities. Moreover, research on inhibiting or enabling effects of digitalization considering its multi-faceted interlinkages with the SDGs and their targets is fragmented. There are only limited instances in the literature examining and categorizing the impact of digitalization on sustainable development. To overcome this gap, this paper introduces a new Digitainability Assessment Framework (DAF) for context-aware practical assessment of the impact of the digitalization intervention on the SDGs. The DAF facilitates in-depth assessment of the many diverse technical, social, ethical, and environmental aspects of a digital intervention by systematically examining its impact on the SDG indicators. Our approach draws on and adapts concepts of the Theory of Change (ToC). The DAF should support developers, users as well policymakers by providing a 360-degree perspective on the impact of digital services or products, as well as providing hints for its possible improvement. We demonstrate the application of the DAF with the three test case studies illustrating how it supports in providing a holistic view of the relation between digitalization and SDGs.

Assessing the impact of digital financial inclusion on PM2.5 concentration: evidence from China

Digital finance as a new technology-driven business model shortens the distance between borrowers and lenders. Economic research finds that digital finance promotes economic efficiency by reducing transaction costs, information asymmetry, and inequality. Digital finance is an energy-intensive industry; therefore, increased efficiency in the industry should yield environmental benefits. We examine the externality of digital finance on air pollution. By analyzing data on digital financial inclusion and fine particulate matter concentration in China, we demonstrate using a dynamic panel data model that the development of digital finance damages the environment. However, after incorporating a threshold effect into a kink model, we determine that digital finance reduces pollution when its development exceeds a certain level. The results suggest that a high level of digital finance development not only increases economic growth but also improves air quality; this result provides novel insight into the relationship between economic growth and the environment.

Study of the spatio-temporal variation of environmental sustainability at national and provincial levels in China

Environmental problems create a significant barrier for China in achieving its Sustainable Development Goals (SDGs). Assessing environmental sustainability is critical for China to meet the SDGs. Few studies, however, have looked into environmental sustainability in China. This research created a systematic and comprehensive environmental sustainability framework in line with the SDGs (SDG 6, SDG 11, SDG 12, SDG 13, SDG 14, SDG 15). From 2010 to 2018, we used a Constant Elasticity of Substitution (CES) model to assess China's spatio-temporal variation in environmental sustainability at the national and provincial levels. We also evaluated the results with changes to the substitution elasticity value, validating the feasibility of the proposed calculation method. Our results show that the scores of SDG 6, SDG 11, SDG 12, SDG 13, and SDG 15 experienced an increasing trend, while SDG 14 experienced a decline. China's Environmental Sustainability Index (ESI) scores indicate that China's overall environmental sustainability has been improved over time. At the provincial level, the ESI scores of all provinces increased at different levels from 2010 to 2018. The results of this paper may facilitate improvements in environmentally-related SDGs in China's provinces, and help realize China's sustainable development.

Nexus Between Economic Efficiency, Healthcare, and Environmental Expenditures: A Perspective of BRI Countries

Public health and the environment are the most essential pillars, and play a vital role in the economy. In order to better public health, the economic and environmental atmosphere must be stable and clean, respectively. Thus, this paper emphasizes on nexus between economic, public health, and the environment. Therefore, the objective of this paper is whether healthcare and environmental expenditures affect economic efficiency and vice versa. So, this study evaluates the performance of the country's economic efficiency and investigates the effect of healthcare and environmental expenditures for 62 Belt and Road Initiative countries for the period from 1996 to 2020. Suitable input-output variables are employed under the framework of DEA-window and Malmquist Index Productivity, and Stochastic Frontier Analysis (SFA). In addition, this study estimates the relationship between economic efficiency, healthcare, and environmental expenditures by fixed and random effects models. Therefore, the analytical outcomes reveal that countries are economically efficient. On the contrary, SFA estimation concludes that countries are found to be inefficient, because higher variation is exists in efficiency change compared to technological efficiency change and total factor productivity change on average. In addition, it is worth notable that healthcare and environmental expenditures improve the country's economic efficiency. Furthermore, public health is also influenced by economic efficiency. Thus, this study suggests that countries should better utilize given resources and invest a specific portion of national income in order to improve economic efficiency.

The impact of environment degrading factors and remittances on health expenditure: an asymmetric ARDL and dynamic simulated ARDL approach

This paper investigates the impact of CO₂ emissions, air pollution (PM2.5) exposure, foreign remittances, energy consumption, renewable energy consumption, trade openness, and gross domestic product per capita on health expenditure in a panel of the 27 highest emitting countries from 2000 to 2019. Focusing on objectives, panel ARDL, and dynamic simulated ARDL models are used to examine the short-run and long-run impact of the variables on health expenditure. An asymmetric or nonlinear ARDL model is used to test the asymmetric effect of CO₂ emissions, air pollution exposure, and foreign remittance inflows on health expenditure. The results show that environment-degrading factors, remittances, and GDP per capita significantly impact health expenditure. There is an asymmetric effect of remittances, CO₂ emissions, and air pollution (PM2.5) exposure on health expenditure. Based on the results, the study suggests policymakers should make policies regarding environment-degrading elements as these factors cause huge increases in health spending in a country. Consumption of renewable energy helps reduce health expenditure as it does not cause environmental degradation, irrespective of other forms of energy, and it is suggested that policies relating to foreign remittance inflows should be encouraged and made efficient.

How Air Quality Affect Health Industry Stock Returns: New Evidence From the Quantile-on-Quantile Regression

This paper discusses the asymmetric effect of air quality (AQ) on stock returns (SR) in China's health industry through the quantile-on-quantile (QQ) regression method. Compared to prior literature, our study provides the following contributions. Government intervention, especially industrial policy, is considered a fresh and essential component of analyzing frameworks in addition to investors' physiology and psychology. Next, because of the heterogeneous responses from different industries to AQ, industrial heterogeneity is thus considered in this paper. In addition, the QQ method examines the effect of specific quantiles between variables and does not consider structural break and temporal lag effects. We obtain the following empirical results. First, the coefficients between AQ and SR in the health service and health technology industries change from positive to negative as AQ deteriorates. Second, AQ always positively influences the health business industry, but the values of the coefficients are larger in good air. In addition, different from other industries, the coefficients in the health equipment industry are negative, but the values of the coefficients change with AQ. The conclusions provide important references for investors and other market participants to avoid biased decisions due to poor AQ and pay attention to government industrial policies.

Assessing a fossil fuels externality with a new neural networks and image optimisation algorithm: the case of atmospheric pollutants as confounders to COVID-19 lethality

This paper demonstrates how the combustion of fossil fuels for transport purpose might cause health implications. Based on an original case study [i.e. the Hubei province in China, the epicentre of the coronavirus disease-2019 (COVID-19) pandemic], we collected data on atmospheric pollutants (PM2.5, PM10 and CO2) and economic growth (GDP), along with daily series on COVID-19 indicators (cases, resuscitations and deaths). Then, we adopted an innovative Machine Learning approach, applying a new image Neural Networks model to investigate the causal relationships among economic, atmospheric and COVID-19 indicators. Empirical findings emphasise that any change in economic activity is found to substantially affect the dynamic levels of PM2.5, PM10 and CO2 which, in turn, generates significant variations in the spread of the COVID-19 epidemic and its associated lethality. As a robustness check, the conduction of an optimisation algorithm further corroborates previous results.

Air pollution and life expectancy in Europe: Does investment in renewable energy matter?

This study examines the relationship between health and air pollution using a novel approach that allows differentiation between potential and observed health. It also permits an analysis of those factors that may contribute towards reducing any differences between the latter concepts. To this end, a panel data from 29 European countries for the periods 2005 and 2018 is used. Results indicate that the main pollutants affecting European countries, namely NOx, PM10 and PM2.5 have a negative impact on life expectancy at birth, while investment in renewable energies has a positive effect. Several conclusions can be drawn from these results. Firstly, if the aim is to minimize the detrimental effects of the global production of goods and services on air quality, a greater investment in renewable energies as compared to other more polluting ones, is called for. In turn, this would contribute to an improvement in the general health of citizens and the planet thereby increasing overall potential life expectancy. Secondly, NOx gases seem to be the ones that most affect the population's mean potential life expectancy. Results indicate that with regard to particulate matters, those with a diameter of less than 2.5 μm, are the ones that have the greatest impact on the health of European citizens, more so than larger particles (with a diameter between 10 and 2.5 μm).

Traffic-induced atmospheric pollution during the COVID-19 lockdown: Dispersion modeling based on traffic flow monitoring in Turin, Italy

The COVID-19 pandemic, as a worldwide threat to public health, has led many governments to impose mobility restrictions and adopt partial or full lockdown strategies in many regions to control the disease outbreak. Although these lockdowns are imposed to save public health by reducing the transmission of the virus, rather significant improvements of the air quality in this period have been reported in different areas, mainly as a result of the reduction in vehicular trips. In this research, the city of Turin in the northern part of Italy has been considered as the study area, because of its special meteorology and geographic location in one of the most polluted regions in Europe, and also its high density of vehicular emissions. A Lagrangian approach is applied to illustrate and analyze the effect of imposing full lockdown restrictions on the reduction of traffic-induced air pollution in the city. To do this, the real-time traffic flow during the lockdown period is recorded, and by utilizing CALPUFF version 7, the dispersion of PM_2.5, Total Suspended Particulate (TSP), Benzo(a)pyrene (BaP), NO_x, and Black Carbon (BC) emitted from all circulating vehicles during and before the lockdown period are compared. Results indicate that the concentration of pollutants generated by road traffic sources (including passenger cars, busses, heavy-duty vehicles, light-duty vehicles, mopeds, and motorcycles) reduced at least 70% (for PM_2.5) up to 88.1% (for BaP) during the studied period. Concentration maps show that the concentration reduction varied in different areas of the town, mainly due to the characteristics and strength of the emission sources and the geophysical features of the area.

Evolution of Romania's Economic Structure and Environment Degradation - An Assessment Through LMDI Decomposition Approach

Purpose

This paper studies the relationships between air pollutants (PM₁₀, PM_2.5, N₂O) and different diseases (tumors, skin and respiratory) and the factors influencing air pollutant emissions in Romania.

Methods

The methods are Toda-Yamamoto procedure of non-causality Granger test, grey relational analysis and logarithmic mean Divisia index method (LMDI).

Results

Air pollutants intensities dropped significantly over 2008–2017 period due to structural changes. The only economic activity that showed an increase both in volume and intensity of air pollutants, despite a downward trend of farming activities output is agriculture. Technology improvements play a significant role in mitigation of PM_2.5 emissions and a moderate role in mitigation of PM₁₀ emissions. For N₂O emissions technology used contributed to an increase of N₂O intensities.

Conclusion

Health policy makers should address the issue of technology improvements and mitigation of agriculture emissions to improve health of individuals and air quality.