Characteristics and sources of carbonaceous aerosols in a semi-arid city: Quantifying anthropogenic and meteorological impacts.

Carbonaceous aerosols have great adverse impacts on air quality, human health, and climate. However, there is a limited understanding of carbonaceous aerosols in semi-arid areas. The correlation between carbonaceous aerosols and control measures is still unclear owing to the insufficient information regarding meteorological contribution. To reveal the complex relationship between control measures and carbonaceous aerosols, offline and online observations of carbonaceous aerosols were conducted from October 8, 2019 to October 7, 2020 in Hohhot, a semi-arid city. The characteristics and sources of carbonaceous aerosols and impacts of anthropogenic emissions and meteorological conditions were studied. The annual mean concentrations (± standard deviation) of fine particulate matter (PM2.5), organic carbon (OC), and elemental carbon (EC) were 42.81 (±40.13), 7.57 (±6.43), and 2.25 (±1.39) µg m-3, respectively. The highest PM2.5 and carbonaceous aerosol concentrations were observed in winter, whereas the lowest was observed in summer. The result indicated that coal combustion for heating had a critical role in air quality degradation in Hohhot. A boost regression tree model was applied to quantify the impacts of anthropogenic emissions and meteorological conditions on carbonaceous aerosols. The results suggested that the anthropogenic contributions of PM2.5, OC, and EC during the COVID-19 lockdown period were 53.0, 15.0, and 2.36 µg m-3, respectively, while the meteorological contributions were 5.38, 2.49, and -0.62 µg m-3, respectively. Secondary formation caused by unfavorable meteorological conditions offset the emission reduction during the COVID-19 lockdown period. Coal combustion (46.4% for OC and 35.4% for EC) and vehicular emissions (32.0% for OC and 50.4% for EC) were the predominant contributors of carbonaceous aerosols. The result indicated that Hohhot must regulate coal use and vehicle emissions to reduce carbonaceous aerosol pollution. This study provides new insights and a comprehensive understanding of the complex relationships between control strategies, meteorological conditions, and air quality.

Causes of the unexpected slowness in reducing winter PM2.5 for 2014-2018 in Henan Province.

Toughest-ever clean air actions in China have been implemented nationwide to improve air quality. However, it was unexpected that from 2014 to 2018, the observed wintertime PM2.5 (particulate matter with an aerodynamic diameter of less than 2.5 µm) concentrations showed an insignificant decrease in Henan Province (HNP), a region in the west of the North China Plain. Emission controls seem to have failed to improve winter air quality in HNP, which has caused great confusion in formulating the next air improvement strategy. We employed a deweathering technique to decouple the impact of meteorological conditions. The results showed that the deweathered PM2.5 trend was -3.3%/yr in winter from 2014 to 2018, which had a larger decrease than the observed concentrations (-0.9%/yr), demonstrating that emission reduction was effective at improving air quality. However, compared with the other two megacity clusters, Beijing-Tianjin-Hebei (BTH) (-8.4%/yr) and Yangtze River Delta (YRD) (-7.4%/yr), the deweathered decreasing trend of PM2.5 for HNP remained slow. The underlying mechanism driving the changes in PM2.5 and its chemical components was further explored, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Model simulations indicated that nitrate dominated the increase of PM2.5 components in HNP and the proportions of nitrate to total PM2.5 increased from 22.4% in January 2015 to 39.7% in January 2019. There are two primary reasons for this phenomenon. One is the limited control of nitrogen oxide emissions, which facilitates the conversion of nitric acid to particulate nitrate by ammonia. The other is unfavourable meteorological conditions, particularly increasing humidity, further enhancing nitrate formation through multiphase reactions. This study highly emphasizes the importance of reducing nitrogen oxide emissions owing to their impact on the formation of particulate nitrate in China, especially in the HNP region.

How Do COVID-19 Risk, Life-Safety Risk, Job Insecurity, and Work-Family Conflict Affect Miner Performance? Health-Anxiety and Job-Anxiety Perspectives.

The coronavirus pandemic (COVID-19) has created challenging working conditions in coal-production activities. In addition to the massive loss of resources for miners, it has had a devastating impact on these individuals' mental health. Based on the conservation of resources (COR) theory and a resource-loss perspective, this study examined the impact of COVID-19 risk, life-safety risk, perceived job insecurity, and work-family conflict on miners' job performance. Moreover, this study investigated the mediating role of job anxiety (JA) and health anxiety (HA). The study data were collected through online structured questionnaires disseminated to 629 employees working in a coal mine in China. The data analysis and hypothesis generation were conducted using the structural equation modeling (partial least squares) method. The results demonstrated that the perception of COVID-19 risk, life-safety risk, job insecurity, and work-family conflict negatively and significantly impacted miners' job performance. In addition, JA and HA negatively mediated the relationships between the perception of COVID-19 risk, life-safety risk, perceived job insecurity, work-family conflict, and job performance. The findings of this study can give coal-mining companies and their staff useful insights into how to minimize the pandemic's effects on their operations.

Impact of primary emission variations on secondary inorganic aerosol formation: Prospective from COVID-19 lockdown in a typical northern China city.

Hourly observations in northern China city of Taiyuan were performed to compare secondary inorganic aerosol (SIA) reaction mechanisms, and emission effects on SIA during the pre-lock and COVID-19 lock days. Emission control implemented and meteorological conditions during lock days both caused beneficial impact on air quality. NO2 showed the highest decrease ratio of -49.5%, while the relative fraction of NO3- in PM2.5 increased the most (2.7%). Source apportionment revealed the top three contributors to PM2.5 were secondary formation (SF), coal combustion (CC), and vehicle exhaust (VE) during both pre-lock and lock days. EC lock/pre were all lower than 1, suggesting the overall reduction of primary emissions during lock days, while the higher ratio of (SIA/EC) lock/pre (1.01-1.36) indicated the enhanced secondary formation in lock days. The ratio of SIA of pollution to clean days during lock periods considerably higher by 23.7% compared with that in pre-lock periods, which was indicated SIA secondary formation was more pronounced and contributed great to pollution days in lock periods though secondary formation existed in pre-lock and lock periods. Enhanced secondary formation of NO3- and SO42- during lock days might be mainly due to the increased in aqueous and gas-phase reactions, respectively. Except for SF, high contribution of VE and CC were also important for high SIA concentration in pre-lock and lock days, respectively. The decreased contribution of VE weakens its contribution to SIA formation, indicating the effectiveness of VE emission control, as confirmed during the COVID-19 pandemic. This study highlights the aqueous and gas-phase reactions for nitrate and sulfate, respectively, which contributed to heavy pollution, as well as indicated the important role of VE on SIA formation, suggesting the urgent need to further strengthen controls on vehicle emissions.

Influence of the COVID-19 pandemic on causes for the development of carbon monoxide intoxications.

Introduction: Several causes can lead to carbon monoxide (CO) intoxication. A first-line treatment option for such intoxications is hyperbaric oxygenation (HBO2) therapy. The COVID-19 pandemic has been changing everyday life in Germany since March 2020, mainly caused by statutory provisions. Our aim was to review whether these changes have an influence on the causes and frequency for the development of CO intoxication. Methods: We retrospectively analyzed the data of patients who were treated for CO intoxication in our institution between April 2019 and March 2021. Besides demographic data, we compared the overall number and documented causes for each CO intoxication in the period of April 2020 to March 2021 with the period between April 2019 and March 2020. Results: After applying inclusion and exclusion criteria, 139 patients were included. We found a significant decrease in the overall number of patients who needed treatment since the beginning of the COVID-19 pandemic. However, the share of CO intoxication caused by the indoor use of coal stoves, coal barbecue, or suicide attempts increased. In contrast, the share of cases caused by apartment or house fire, smoking waterpipe, or gas stoves decreased. Conclusion: The COVID-19 pandemic and the associated restrictions lead to a significant reduction in the number of patients in need for HBO2 therapy due to CO-Intoxication. The causes leading to CO intoxication also changed since the beginning of the COVID-19 pandemic. We observed a shift toward causes related to the indoor use of coal-fired stoves and barbecues as well as suicide attempts.

Excess mortality in Mountain Areas of Emilia Romagna Region during the first months of SARS-CoV-2 pandemic: a "canary in the coal mine"?

BACKGROUND: Because of their remoteness, Mountain Communities (MC) have been considered at advantage when dealing with infectious diseases. However, earlier reports have identified MC among the hotspots for early spreading of COVID-19 pandemic. METHODS: Crude mortality rates (CMR) and Excess mortality rates (EMR) were calculated for 97 municipalities from MC in the Emilia Romagna Region, and resulting estimates were compared to the Parent Provinces. Notification and mortality rates for COVID-19 were also retrieved, and correlated with EMR estimates. RESULTS: During 2020, a CMR of 150.3/100,000 (95% Confidence Interval [95%CI] 117-185.4) was identified, with substantial heterogeneities between the 8 provinces of Emilia Romagna Region that were included in the analyses. A pooled EMR of +20.3% (95%CI 10.6-30.1) for MC and 19.9% (95%CI 9.5-30.3) was identified. The monthly estimates were quite heterogenous across the various provinces, ranging between -79.7% and +307.4% during the assessed timeframe. Higher estimates were identified in the months of March and April in MC, and during the months of April and May for Parent Provinces. In bivariate analysis, EM in MC was positively correlated with estimates in the parent province (Spearman's r = 0.201, p = 0.049), and also with notification rates for COVID- (i.e. Piacenza, Parma, Reggio Emilia, Modena, Bologna, Ravenna, Rimini, and Forlì Cesena) (r = 0.225, p = 0.045), and particularly with mortality rates for COVID-19 at provincial level (r = 0.372, p < 0.001). CONCLUSIONS: In summary, the study highlights that small geographical and population size, along with remoteness, did not play a substantial advantage for MC against the spread and mortality rate of COVID-19. On the other hand, as the surge of EM in MC anticipated a similar habit in Parent Provinces of several weeks, improved surveillance interventions are also urgently in need. (www.actabiomedica.it).

Impact of COVID-19 lockdown on carbonaceous aerosols in a polluted city: Composition characterization, source apportionment, influence factors of secondary formation.

Carbonaceous fractions throughout the normal period and lockdown period (LP) before and during COVID-19 outbreak were analyzed in a polluted city, Zhengzhou, China. During LP, fine particulate matters, elemental carbon (EC), and secondary organic aerosol (SOC) concentrations fell significantly (29%, 32% and 21%), whereas organic carbon (OC) only decreased by 4%. Furthermore, the mean OC/EC ratio increased (from 3.8 to 5.4) and the EC fractions declined dramatically, indicating a reduction in vehicle emission contribution. The fact that OC1-3, EC, and EC1 had good correlations suggested that OC1-3 emanated from primary emissions. OC4 was partly from secondary generation, and increased correlations of OC4 with OC1-3 during LP indicated a decrease in the share of SOC. SOC was more impacted by NO2 throughout the research phase, thereby the concentrations were lower during LP when NO2 levels were lower. SOC and relative humidity (RH) were found to be positively associated only when RH was below 80% and 60% during the normal period (NP) and LP, respectively. SOC, Coal combustion, gasoline vehicles, biomass burning, diesel vehicles were identified as major sources by the Positive Matrix Factorization (PMF) model. Contribution of SOC apportioned by PMF was 3.4 and 3.0 µg/m3, comparable to the calculated findings (3.8 and 3.0 µg/m3) during the two periods. During LP, contributions from gasoline vehicles dropped the most, from 47% to 37% and from 7.1 to 4.3 µg/m3, contribution of biomass burning and diesel vehicles fell by 3% (0.6 µg/m3) and 1% (0.4 µg/m3), and coal combustion concentrations remained nearly constant. The findings of this study highlight the immense importance of anthropogenic source reduction in carbonaceous component variations and SOC generation, and provide significant insight into the temporal variations and sources of carbonaceous fractions in polluted cities.

Forecasting of energy consumption by G20 countries using an adjacent accumulation grey model.

This paper studies an adjacent accumulation discrete grey model to improve the prediction of the grey model and enhance the utilization of new data. The impact of COVID-19 on the global economy is also discussed. Two cases are discussed to prove the stability of the adjacent accumulation discrete grey model, which helped the studied model attain higher forecasting accuracy. Using the adjacent accumulation discrete grey model, non-renewable energy consumption in G20 countries from 2022 to 2026 is predicted based on their consumption data from 2011 to 2021. It is proven that the adjacent accumulation exhibits sufficient accuracy and precision. Forecasting results obtained in this paper show that energy consumption of all the non-renewable sources other than coal has an increasing trend during the forecasting period, with the USA, Russia, and China being the biggest consumers. Natural gas is the most consumed non-renewable energy source between 2022 and 2026, whereas hydroelectricity is the least consumed. The USA is the biggest consumer of Nuclear energy among the G20 countries, whereas Argentina consumed only 0.1 Exajoules of nuclear energy, placing it at the end of nuclear energy consumers.

Variation of pollution sources and health effects on air pollution before and during COVID-19 pandemic in Linfen, Fenwei Plain.

Stringent pollution control measures are generally applied to improve air quality, especially in the Spring Festival in China. Meanwhile, human activities are reduced significantly due to nationwide lockdown measures to curtail the COVID-19 spreading in 2020. Herein, to better understand the influence of control measures and meteorology on air pollution, this study compared the variation of pollution source and their health risk during the 2019 and 2020 Spring Festival in Linfen, China. Results revealed that the average concentration of PM2.5 in 2020 decreased by 39.0% when compared to the 2019 Spring Festival. Organic carbon (OC) and SO42- were the primary contributor to PM2.5 with the value of 19.5% (21.1%) and 23.5% (25.5%) in 2019 (2020) Spring Festival, respectively. Based on the positive matrix factorization (PMF) model, six pollution sources of PM2.5 were indicated. Vehicle emissions (VE) had the maximum reduction in pollution source concentration (28.39 µg· m-3), followed by dust fall (DF) (11.47 µg· m-3), firework burning (FB) (10.39 µg· m-3), coal combustion (CC) (8.54 µg· m-3), and secondary inorganic aerosol (SIA) (3.95 µg· m-3). However, the apportionment concentration of biomass burning (BB) increased by 78.7%, indicating a significant increase in biomass combustion under control measures. PAHs-lifetime lung cancer risk (ILCR) of VE, CC, FB, BB, and DF, decreased by 44.6%, 43.2%, 34.1%, 21.3%, and 2.0%, respectively. Additionally, the average contribution of meteorological conditions on PM2.5 in 2020 increased by 20.21% compared to 2019 Spring Festival, demonstrating that meteorological conditions played a crucial role in located air pollution. This study revealed that the existing control measures in Linfen were efficient to reduce air pollution and health risk, whereas more BB emissions were worthy of further attention. Furthermore, the result was conducive to developing more effective control measures and putting more attention into unfavorable meteorological conditions in Linfen.

Machine learning analysis on the impacts of COVID-19 on India's renewable energy transitions and air quality.

India is severely affected by the COVID-19 pandemic and is facing an unprecedented public health emergency. While the country's immediate measures focus on combating the coronavirus spread, it is important to investigate the impacts of the current crisis on India's renewable energy transition and air quality. India's economic slowdown is mainly compounded by the collapse of global oil prices and the erosion of global energy demand. A clean energy transition is a key step in enabling the integration of energy and climate. Millions in India are affected owing to fossil fuel pollution and the increasing climate heating that has led to inconceivable health impacts. This paper attempts to study the impact of COVID-19 on India's climate and renewable energy transitions through machine learning algorithms. India is observing a massive collapse in energy demand during the lockdown as its coal generation is suffering the worst part of the ongoing pandemic. During this current COVID-19 crisis, the renewable energy sector benefits from its competitive cost and the Indian government's must-run status to run generators based on renewable energy sources. In contrast to fossil fuel-based power plants, renewable energy sources are not exposed to the same supply chain disruptions in this current pandemic situation. India has the definite potential to surprise the global community and contribute to cost-effective decarbonization. Moreover, the country has a good chance of building more flexibility into the renewable energy sector to avoid an unstable future.

Solid fuel use, socioeconomic indicators and risk of cardiovascular diseases and all-cause mortality: a prospective cohort study in a rural area of Sichuan, China.

BACKGROUND: Estimates indicate that household air pollution caused by solid fuel burning accounted for about 1.03 million premature mortalities in China in 2016. In the country's rural areas, more than half the population still relies on biomass fuels and coals for cooking and heating. Understanding the health impact of indoor air pollution and socioeconomic indicators is essential for the country to improve its developmental targets. We aimed to describe demographic and socioeconomic characteristics associated with solid fuel users in a rural area in China. We also estimated the risk of cardiovascular disease and all-cause mortality in association with solid fuel use and described the relationship between solid fuel use, socioeconomic status and mortality. We also measured the risk of long-term use, and the effect of ameliorative action, on mortality caused by cardiovascular disease and other causes. METHODS: We used the China Kadoorie Biobank (CKB) site in Pengzhou, Sichuan, China. We followed a cohort of 55 687 people over 2004-13. We calculated the mean and standard deviation among subgroups classified by fuel use types: gas, coal, wood and electricity (central heating additionally for heating). We tested the mediation effect using the stepwise method and Sobel test. We used Cox proportional models to estimate the risk of incidences of cardiovascular disease and mortality with survival days as the time scale, adjusted for age, gender, socioeconomic status, physical measurements, lifestyle, stove ventilation and fuel type used for other purposes. The survival days were defined as the follow-up days from the baseline survey till the date of death or 31 December 2013 if right-censored. We also calculated the absolute mortality rate difference (ARD) between the exposure group and the reference group. RESULTS: The study population had an average age of 51.0, and 61.9% of the individuals were female; 64.8% participants (n = 35 543) cooked regularly and 25.4% participants (n = 13 921) needed winter heating. With clean fuel users as the reference group, participant households that used solid fuel for cooking or heating both had a higher risk of all-cause mortality: hazard ratio (HR) for: cooking, 1.11 [95% confidence interval (CI) 1.02, 1.26]; heating, 1.34 (95% CI 1.16, 1.54). Solid fuel used for winter heating was associated with a higher risk of mortality caused by cerebrovascular disease: HR 1.64 (95% CI 1.12, 2.40); stroke: HR 1.70 (95% CI 1.13, 2.56); and cardiovascular disease: HR 1.49 (95% CI 1.10, 2.02). Low income and poor education level had a significant correlation with solid fuel used for cooking: odds ratio (OR) for income: 2.27 (95% CI 2.14, 2.41); education: 2.34 (95% CI 2.18, 2.53); and for heating: income: 2.69 (95% CI 2.46, 2.97); education: 2.05 (95% CI 1.88, 2.26), which may be potential mediators bridging the effects of socioeconomic status factors on cardiovascular disease and all-cause mortality. Solid fuel used for cooking and heating accounted for 42.4% and 81.1% of the effect of poor education and 55.2% and 76.0% of the effect of low income on all-cause mortality, respectively. The risk of all-cause mortality could be ameliorated by stopping regularly cooking and heating using solid fuel or switching from solid fuel to clean fuels: HR for cooking: 0.90 (95% CI 0.84, 0.96); heating: 0.76 (95% CI 0.64, 0.92). CONCLUSIONS: Our study reinforces the evidence of an association between solid fuel use and risk of cardiovascular disease and all-cause mortality. We also assessed the effect of socioeconomic status as the potential mediator on mortality. As solid fuel use was a major contributor in the effect of socioeconomic status on cardiovascular disease and all-cause mortality, policies to improve access to clean fuels could reduce morbidity and mortality related to poor education and low income.

Key factors affecting carbon prices from a time-varying perspective.

For humankind to sustain a livable atmosphere on the planet, many countries have committed to achieving carbon neutralization. Countries mainly reduce carbon emissions by regulations through a carbon tax or by establishing a carbon market using economic stimuli. In this paper, we use the least absolute shrinkage and selection operator (LASSO) method to select the key determinants of a carbon market and then use the Markov switching vector autoregression (MSVAR) model to study the market's driving factors and analyze its time-varying characteristics. The results show that there are perceptible time-varying characteristics and notable differences among markets. During COVID-19, energy factors had a long-term shock on the carbon market, economic factors had a short-term shock on the carbon market, and the economic recession has led to fluctuations in the carbon market. In addition, through MSVAR, the results show that the energy market has a negative effect on the carbon market, and the stock market has a positive effect on the carbon market. In periods of low volatility, compared with the natural gas market and coal market, the oil market has a stronger shock on the carbon market. In periods of high volatility, the coal market has a stronger shock on the carbon market. In terms of emission reduction, countries around the world would be wise to change their energy consumption structure, reduce coal use, and shift to a cleaner energy consumption structure.

Response of PM2.5-bound elemental species to emission variations and associated health risk assessment during the COVID-19 pandemic in a coastal megacity.

The coronavirus (COVID-19) pandemic is disrupting the world from many aspects. In this study, the impact of emission variations on PM2.5-bound elemental species and health risks associated to inhalation exposure has been analyzed based on real-time measurements at a remote coastal site in Shanghai during the pandemic. Most trace elemental species decreased significantly and displayed almost no diel peaks during the lockdown. After the lockdown, they rebounded rapidly, of which V and Ni even exceeded the levels before the lockdown, suggesting the recovery of both inland and shipping activities. Five sources were identified based on receptor modeling. Coal combustion accounted for more than 70% of the measured elemental concentrations before and during the lockdown. Shipping emissions, fugitive/mineral dust, and waste incineration all showed elevated contributions after the lockdown. The total non-carcinogenic risk (HQ) for the target elements exceeded the risk threshold for both children and adults with chloride as the predominant species contributing to HQ. Whereas, the total carcinogenic risk (TR) for adults was above the acceptable level and much higher than that for children. Waste incineration was the largest contributor to HQ, while manufacture processing and coal combustion were the main sources of TR. Lockdown control measures were beneficial for lowering the carcinogenic risk while unexpectedly increased the non-carcinogenic risk. From the perspective of health effects, priorities of control measures should be given to waste incineration, manufacture processing, and coal combustion. A balanced way should be reached between both lowering the levels of air pollutants and their health risks.

Impact Measurement of COVID-19 Lockdown on China's Electricity-Carbon Nexus.

Lockdown measures to prevent the spread of coronavirus disease 2019 (COVID-19) resulted in the plummeting of China's overall electric-power demand and production. To date, power generation remains one of the largest carbon dioxide (CO2) emitting sectors of China on account of its high carbon intensity. Within this context, our study seeks to measure the impacts of COVID-19 lockdown on the electricity-power related carbon footprints on both generation and consumption sides. Built on statistical data of electricity generation and consumption released by the National Bureau of Statistics of China (NBSC), we calculate he nationwide electricity related CO2 emission changes in regional, economic-sectoral and technological dimensions during January-April 2020, when the strictest lock-down measures were taken in China and compare the results with the same months of the year prior. Our results show that both east and central China power grids witnessed drastic reduction (15.0% and 13.8%) in electricity-generation caused CO2 emissions; and the biggest falls of provincial-scale electricity-generation CO2 emission took place in Hubei (27.3%). Among China's electricity production mix, coal remains the biggest CO2 emitter and contributed 95.7% of the overall nationwide reduction. The most significant decline of the nationwide consumptive-electricity carbon footprint was by 10.1% in February, with the secondary economic sector the biggest contributor.

No COVID-19 climate silver lining in the US power sector.

Recent studies conclude that the global coronavirus (COVID-19) pandemic decreased power sector CO2 emissions globally and in the United States. In this paper, we analyze the statistical significance of CO2 emissions reductions in the U.S. power sector from March through December 2020. We use Gaussian process (GP) regression to assess whether CO2 emissions reductions would have occurred with reasonable probability in the absence of COVID-19 considering uncertainty due to factors unrelated to the pandemic and adjusting for weather, seasonality, and recent emissions trends. We find that monthly CO2 emissions reductions are only statistically significant in April and May 2020 considering hypothesis tests at 5% significance levels. Separately, we consider the potential impact of COVID-19 on coal-fired power plant retirements through 2022. We find that only a small percentage of U.S. coal power plants are at risk of retirement due to a possible COVID-19-related sustained reduction in electricity demand and prices. We observe and anticipate a return to pre-COVID-19 CO2 emissions in the U.S. power sector.

The impact of coal combustion, nitrous oxide emissions, and traffic emissions on COVID-19 cases: a Markov-switching approach.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread to more than 200 countries with a current case fatality ratio (CFR) of more than 2% globally. The concentration of air pollutants is considered a critical factor responsible for transmitting coronavirus disease among the masses. The photochemical process and coal combustions create respiratory disorders that lead to coronavirus disease. Based on the crucial fact, the study evaluated the impact of nitrous oxide (N2O) emissions, coal combustion, and traffic emissions on COVID-19 cases in a panel of 39 most affected countries of the world. These three air pollution factors are considered to form a lethal smog that negatively affects the patient's respiratory system, leading to increased susceptibility to coronavirus worldwide. The study used the Markov two-step switching regime regression model for obtaining parameter estimates. In contrast, an innovation accounting matrix is used to assess smog factors' intensity on possibly increasing coronavirus cases over time. The results show that N2O emissions, coal combustion, and traffic emissions increase COVID-19 cases in regime-1. On the other hand, N2O emissions significantly increase coronavirus cases in regime-2. The innovation accounting matrix shows that N2O emissions would likely have a more significant share of increasing coronavirus cases with a variance of 33.902%, followed by coal combustion (i.e., 6.643%) and traffic emissions (i.e., 2.008%) over the time horizon. The study concludes that air quality levels should be maintained through stringent environmental policies, such as carbon pricing, sustainable urban planning, green technology advancement, renewable fuels, and pollution less accessible vehicles. All these measures would likely decrease coronavirus cases worldwide.

The "celebrity canary in the coal mine for the coronavirus": An examination of a theoretical model of celebrity illness disclosure effects.

RATIONALE: On March 11, 2020, actor Tom Hanks announced via social media that he had been diagnosed with COVID-19. Previous research has found celebrity illness disclosures to influence behavior, but during the uncertainty of a pandemic, the effects of such a disclosure were unclear. OBJECTIVE: To test the proposed Celebrity Illness Disclosure Effects (CIDE) model, demonstrating how an illness disclosure, communicated through mediated and interpersonal channels, may shape willingness to engage in prevention behaviors. METHODS: We conducted an online survey (N = 587) 24 hours after Hanks' COVID-19 disclosure. RESULTS: Findings revealed that celebrity-related perception variables predicted illness-related cognitions and emotions\, which were associated with willingness to enact prevention behaviors. Greater willingness to seek information, stronger perceptions of COVID as a threat, and stronger perceptions of efficacy for dealing with COVID after learning of Hanks' diagnosis predicted stronger willingness to enact prevention behaviors. However, anxiety about COVID predicted lower willingness to enact prevention behaviors. CONCLUSIONS: The CIDE model can serve as a guide for future research in this area. The results can help scholars who aim to better understand the phenomena around celebrities and health communication as well as policymakers who hope to ride the wave of star power to improved public health outcomes.

Household pollution and COVID-19: irrelevant association?

Evidence supports the link between air pollution and coronavirus disease 2019 (COVID-19). Therefore, exposure to indoor pollution (IDP) is likely to be associated with the disease. The poor, refugees, and migrant workers who live in feeble conditions are the most vulnerable. The pandemic has caused many people to remain indoors, especially at-risk individuals (e.g., the elderly, diabetics, obese, cardiac, and chronic lung disease patients). Home isolation may be an underlying factor to other health problems among these populations if the place where they are socially isolating is not adequately ventilated. Therefore, understanding the consequences of the relationship between IDP and the COVID-19 pandemic is essential.

Decrease in Ambient Fine Particulate Matter during COVID-19 Crisis and Corresponding Health Benefits in Seoul, Korea.

Both domestic emissions and transported pollutants from neighboring countries affect the ambient fine particulate matter (PM2.5) concentration of Seoul, Korea. Diverse measures to control the coronavirus disease 2019 (COVID-19), such as social distancing and increased telecommuting in Korea and the stringent lockdown measures of China, may reduce domestic emissions and levels of transported pollutants, respectively. In addition, wearing a particulate-filtering respirator may have decreased the absolute PM2.5 exposure level for individuals. Therefore, this study estimated the acute health benefits of PM2.5 reduction and changes in public behavior during the COVID-19 crisis in Seoul, Korea. To calculate the mortality burden attributable to PM2.5, we obtained residents' registration data, mortality data, and air pollution monitoring data for Seoul from publicly available databases. Relative risks were derived from previous time-series studies. We used the attributable fraction to estimate the number of excessive deaths attributable to acute PM2.5 exposure during January to April, yearly, from 2016 to 2020, and the number of mortalities avoided from PM2.5 reduction and respirator use observed in 2020. The average PM2.5 concentration from January to April in 2020 (25.6 µg/m3) was the lowest in the last 5 years. At least -4.1 µg/m3 (95% CI: -7.2, -0.9) change in ambient PM2.5 in Seoul was observed in 2020 compared to the previous 4 years. Overall, 37.6 (95% CI: 32.6, 42.5) non-accidental; 7.0 (95% CI: 5.7, 8.4) cardiovascular; and 4.7 (95% CI: 3.4, 6.1) respiratory mortalities were avoided due to PM2.5 reduction in 2020. By considering the effects of particulate respirator, decreases of 102.5 (95% CI: 89.0, 115.9) non-accidental; 19.1 (95% CI: 15.6, 22.9) cardiovascular; and 12.9 (95% CI: 9.2, 16.5) respiratory mortalities were estimated. We estimated that 37 lives were saved due to the PM2.5 reduction related to COVID-19 in Seoul, Korea. The health benefit may be greater due to the popular use of particulate-filtering respirators during the COVID-19 crisis. Future studies with daily mortality data are needed to verify our study estimates.