How economic policy uncertainty and geopolitical risk affect environmental pollution: does renewable energy consumption matter?

Climate change traps heat, affecting various species in previously dry areas. Climate change brought on by emissions of greenhouse gases exacerbates problems such as severe storms, earthquakes, epidemics, and food distribution. The group of developed and developing countries, the world's biggest carbon emitters and most significant economies, is expertly planning to lessen its environmental challenges and contribute to achieving Sustainable Development Goals 7 and 13 set by the United Nations. This study uses the novel econometric methodologies of the dynamic ordinary least square (DOLS) estimator, the augmented mean group (AMG) estimator, and the fully modified ordinary least square (FMOLS) estimate to examine the influence of economic policy uncertainty, renewable energy consumption, geopolitical risk, non-renewable energy consumption, and economic growth on ecological footprint from 2000 to 2021. The results reveal that the variables are co-integrated; REC reduces carbon emissions, EPU, geopolitical risk, and economic growth contribute to increasing carbon emissions, while urbanization improves carbon emission. Finally, the results suggest that the developed and developing economies can progress toward SDGs 7 and 13 by using renewable energy, lowering the geopolitical risk, effectively handling policy uncertainty, and reducing urbanization.

Examining the relationship between fiscal decentralization, renewable energy intensity, and carbon footprints in Canada by using the newly constructed bootstrap Fourier Granger causality test in quantile.

Current paper studies the nexus between fiscal decentralization, renewable energy intensity, and carbon footprints in Canada. Preliminary empirical findings strictly reject the preposition of data normality and highlight that the observed nexus is quantile dependent. Additionally, our test looks for systematic deviations from zero in the causality at a certain quantile and frequency. In particular, we consider the bootstrap Fourier Granger causality test in quantile. At each frequency, we test the sample causality against the distribution of the median causality across frequencies estimated for that process, which may disclose the misleading causal link in previous studies using only traditional Granger causality. Our results show a negative one-way Granger causality from fiscal decentralization to carbon footprints (quantiles: 0.1-0.9) and renewable energy intensity to carbon footprints, respectively (quantiles: 0.1-0.9). Herein, results show a positive one-way Granger causality through fiscal decentralization to renewable energy intensity (quantiles: 0.3-0.7). These conclusions are used to formulate policy suggestions.

Partial Infarction of Cecal Wall Presenting as Acute Appendicitis.

Acute appendicitis is one of the most common causes of acute abdomen in children and young adults, with differential diagnoses involving several surgical, medical as well as obstetrics and gynecology (OB-GYN)-related conditions. Cecal wall necrosis is not usually included in the differential diagnosis of acute appendicitis, mainly because of the rare nature of the condition and the relatively low level of awareness among surgeons. We present a case of isolated cecal wall necrosis presenting as acute appendicitis. It involves a 42-year-old male patient who presented to the emergency department (ED) of our hospital with abdominal pain for three days. The pain was felt over the right lower quadrant and was associated with nausea, vomiting, and anorexia. The case was diagnosed as acute appendicitis and the patient was taken to the operating room (OR). Upon entering the abdomen, necrosis of the anterolateral wall of the cecum was discovered with a normal appendix. Resection of the cecum was performed, followed by ileocolic anastomosis. The patient was discharged in good condition after 10 days of hospital stay. This case report highlights the importance of considering cecal wall necrosis in patients presenting with right lower quadrant abdominal pain who display atypical signs and symptoms of appendicitis; we also wish to promote awareness among surgeons about this rare condition.

A Systematic Review of Barriers in Adoption of Environmental Management Accounting in Chinese SMEs for Sustainable Performance.

Small- and medium-sized enterprises (SMEs) play an important role in sustainable development not only for their significant contribution to China's economy but also for their large share of total discharged pollutants. Despite the widely acknowledged importance and benefits of environmental management accounting (EMA), the level of adoption and implementation of EMA practice is still weak within SMEs in many countries, especially in China. The current systematic review aims to identify the barriers affecting the Chinese SMEs for adopting EMA practices along with the critical success factors required for adopting EMA practices by SMEs and their top management for ensuring sustainable corporate environmental performance in China. The study is carried out following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. In total, 73 articles were found to be eligible to be included in the systematic review, which was published on EMA in small- and medium-sized enterprises in China. Our study aims to document barriers to the adoption of EMA among Chinese SMEs. The review concluded that strict legislation and the availability of flexible financing options for SMEs can promote the adoption of EMA by SMEs. The establishment of environmental reporting systems and auditing mechanisms can further increase the utilization of EMA by small and medium firms. Barriers to EMA adoption can be mitigated after careful consideration of the current situation in SMEs. Documentation of significant barriers may help to form supportive policies which ultimately add to the efforts toward climate change mitigation.

The Outcomes of Organizational Cronyism: A Social Exchange Theory Perspective.

The current research examines the possible outcomes of cronyism like organizational deviance (OD), organizational cynicism (OCy), and counterproductive work behavior and also investigates the mediating variable violation of psychological contract (VPC) among cronyism and its possible outcomes. Many studies have investigated the presence of organizational cronyism (OC) at the workplace and its impacts on certain variables. However, the outcomes observed in this study, i.e., OD, OCy, and counter-productive work behavior were not empirically investigated previously as per researchers' knowledge. The second gap this study fills is the mediating effect of VPC between the studied variables. Thirdly, the study was conducted in Azad Jammu and Kashmir, Pakistan, which is almost the first attempt to investigate this phenomenon in Azad Jammu and Kashmir. Data were collected from the employees working under different ministries of Azad Jammu and Kashmir, Pakistan like education, forest, sports, information, local government, finance, and tourism. The data from 350 employees were collected through convenience sampling. The data collection process was conducted at two distinct time lags. Results show that OC significantly and positively relates with OD, OCy, and counter-productive work behavior, whereas VPC mediates the relationship among OC and OD, OC, and counter-productive work behavior. Employees enjoying special favors from the leadership seem to be more dedicated toward the organization than the employees who do not have this favor, and the ultimate result is negative for the organization.

Investigating the existence of asymmetric environmental Kuznets curve and pollution haven hypothesis in China: Fresh evidence from QARDL and quantile Granger causality.

This study aims to analyze the asymmetric long-run relationship between economic growth (EG), foreign direct investment (FDI), and carbon emissions (CO2) within the context of the environmental Kuznets curve (EKC) and the pollution haven hypothesis (PHH) in China. Employing the quarterly data from 1982Q1 to 2018Q4, we have used novel techniques to meet the stated objectives of our study, named quantile ARDL and quantile Granger causality. The study provides novel outcomes using the advanced quantile ARDL and quantile Granger causality tests. The significant implication of this method is that it provides locational asymmetry. We find strong evidence of the EKC and PHH for China based on the empirical results of linear and nonlinear ARDL models. Similarly, findings of quantile Granger causality validate the bidirectional relationship among all variables in upper and lower quantiles. Moreover, the results of the Wald test confirm the asymmetric long-run relationship between FDI and carbon emissions (CO2). Thus, legal measures must be enhanced, accepted, rigorously imposed, and monitored in all provinces to assure a further reduction in carbon emissions. This study will be conducive for the policymakers to combat environmental contamination concerning economic growth and FDI inflow in China.

When would the dark clouds of financial inclusion be over, and the environment becomes clean? The role of national governance.

On one side, the rapid progress in financial development boosts economic growth. On the other hand, it forces both the developed and emerging countries to play the role of good governance that help save the environment. The current study aims to identify the role of national governance in the relationship between financial inclusion and ecological footprints. To attain the study's objective, we use a novel method of moments quantile regression (MMQR) on a panel data set of 65 countries from 2004 to 2017. The empirical outcomes reveal that financial inclusion has a significant positive and heterogeneous impact on ecological footprints. This effect varies across quantiles, and when moving from lower to upper quantiles, the impact of financial inclusion on environment escalates. National governance plays an important role to moderate the relationship between financial inclusion and ecological footprint negatively. Moreover, GDP and REC display a significant positive and negative influence on ecological footprints, respectively. We obtain similar and robust findings from the alternative panel estimation techniques, including FMOLS, FEOLS, and DOLS. The policy implications from this research can be considered to achieve sustainable and eco-friendly environmental goals.

Climate indicators and COVID-19 recovery: A case of Wuhan during the lockdown.

The world needs to get out of the COVID-19 pandemic smoothly through a thorough socio-economic recovery. The first and the foremost step forward in this direction is the health recovery of the people infected. Our empirical study addresses this neglected point in the recent research on COVID-19 and specifically aims at exploring the impact of the environment on health recovery from COVID-19. The sample data are taken during the lockdown period in Wuhan, i.e., from 23rd January 2020 to 8th April 2020. The recently developed econometric technique of Quantile-on-Quantile regression, proposed by Shin and Zhu (2016) is employed to capture the asymmetric association between environmental factors (TEMP, HUM, PM2.5, PM10, CO, SO2, NO2, and O3) and the number of recovered patients from COVID-19. We observe significant heterogeneity in the association among variables across various quantiles. The findings suggest that TEMP, PM2.5, PM10, CO, NO2, and O3 are negatively related to the COVID-19 recovery, while HUM and SO2 show a positive association at most quantiles. The study recommends that maintaining a safe and comfortable environment for the patients may increase the chances of recovery from COVID-19. The success story of Wuhan, the initial epicenter of the novel coronavirus in China, can serve as an important case study for other countries to bring the outbreak under control. The current study could be conducive for the policymakers of those countries where the COVID-19 pandemic is still unrestrained.

Asymmetric and time-varying linkages between carbon emissions, globalization, natural resources and financial development in China.

In the real world, economic covariates follow asymmetric and time-varying patterns. Therefore, it is imperative to integrate these effects while estimating environmental and economic relationships. Although prevailing literature reveals various emissions-deriving and eliminating factors, however, there is a dearth of empirical evidence that estimates the asymmetric and time-varying effect of globalization, natural resources, and financial development from a multidimensional perspective in China. In doing so, we employ the nonlinear autoregressive distributed lag (NARDL) and cross-wavelet modeling framework to explore the long- and short-run nonlinear and time-variant association between globalization, natural resources, financial development, and carbon emissions from 1980 to 2017. The NARDL method has the benefit of discriminating the long-term and short-term asymmetric carbon emission responses due to a positive and negative shock in our primary variables of interest. Mainly, the findings of NARDL estimations confirm that positive shocks in globalization and financial developments have a significant positive impact on carbon emissions, whereas negative shock in natural resources has a significant positive impact on carbon emissions. Similarly, the outcomes of continuous wavelet transformation and wavelet transformation coherence confirm the causal linkages between covariates; however, this effect varies across different time and frequency domains. These results imply that environmental researchers should consider asymmetric transmission channels and time-frequency associations among variables to devise long-term sustainable policies.

A Framework for Malicious Traffic Detection in IoT Healthcare Environment.

The Internet of things (IoT) has emerged as a topic of intense interest among the research and industrial community as it has had a revolutionary impact on human life. The rapid growth of IoT technology has revolutionized human life by inaugurating the concept of smart devices, smart healthcare, smart industry, smart city, smart grid, among others. IoT devices' security has become a serious concern nowadays, especially for the healthcare domain, where recent attacks exposed damaging IoT security vulnerabilities. Traditional network security solutions are well established. However, due to the resource constraint property of IoT devices and the distinct behavior of IoT protocols, the existing security mechanisms cannot be deployed directly for securing the IoT devices and network from the cyber-attacks. To enhance the level of security for IoT, researchers need IoT-specific tools, methods, and datasets. To address the mentioned problem, we provide a framework for developing IoT context-aware security solutions to detect malicious traffic in IoT use cases. The proposed framework consists of a newly created, open-source IoT data generator tool named IoT-Flock. The IoT-Flock tool allows researchers to develop an IoT use-case comprised of both normal and malicious IoT devices and generate traffic. Additionally, the proposed framework provides an open-source utility for converting the captured traffic generated by IoT-Flock into an IoT dataset. Using the proposed framework in this research, we first generated an IoT healthcare dataset which comprises both normal and IoT attack traffic. Afterwards, we applied different machine learning techniques to the generated dataset to detect the cyber-attacks and protect the healthcare system from cyber-attacks. The proposed framework will help in developing the context-aware IoT security solutions, especially for a sensitive use case like IoT healthcare environment.

Assessing Public Willingness to Wear Face Masks during the COVID-19 Pandemic: Fresh Insights from the Theory of Planned Behavior.

Face masks are considered an effective intervention in controlling the spread of airborne viruses, as evidenced by the 2009's H1N1 swine flu and 2003's severe acute respiratory syndrome (SARS) outbreaks. However, research aiming to examine public willingness to wear (WTW) face masks in Pakistan are scarce. The current research aims to overcome this research void and contributes by expanding the theoretical mechanism of theory of planned behavior (TPB) to include three novel dimensions (risk perceptions of the pandemic, perceived benefits of face masks, and unavailability of face masks) to comprehensively analyze the factors that motivate people to, or inhibit people from, wearing face masks. The study is based on an inclusive questionnaire survey of a sample of 738 respondents in the provincial capitals of Pakistan, namely, Lahore, Peshawar, Karachi, Gilgit, and Quetta. Structural equation modeling (SEM) is used to analyze the proposed hypotheses. The results show that attitude, social norms, risk perceptions of the pandemic, and perceived benefits of face masks are the major influencing factors that positively affect public WTW face masks, whereas the cost of face masks and unavailability of face masks tend to have opposite effects. The results emphasize the need to enhance risk perceptions by publicizing the deadly effects of COVID-19 on the environment and society, ensure the availability of face masks at an affordable price, and make integrated and coherent efforts to highlight the benefits that face masks offer.

Tellurium Triggered Formation of Te/Fe-NiOOH Nanocubes as an Efficient Bifunctional Electrocatalyst for Overall Water Splitting.

The electrocatalyzed oxygen and hydrogen evolution reactions (OER/HER) are the key constituents of water splitting toward hydrogen production over electrolysis. The development of stable non-noble nanomaterials as bifunctional OER/HER electrocatalysts is the foremost bottleneck to commercial applications. Herein, the fabrication of Te-modulated FeNiOOH nanocubes (NCs) by a novel tailoring approach is reported, and the doping of Te superbly modulated the local electronic structures of Fe and Ni. The Te/FeNiOOH-NC catalyst displays better mass and electron transfer ability, exposure of plentiful OER/HER edge active centers on the surface, and a modulated electronic structure. Accordingly, the as-made Te/FeNiOOH-NC catalyst reveals robust OER activity (overpotential of 0.22 V@10 mA cm-2) and HER activity (overpotential of 0.167 V@10 mA cm-2) in alkaline media. Considerably, this bifunctional catalyst facilitates a high-performance alkaline water electrolyzer with a cell voltage of 1.65 V at 10 mA cm-2. This strategy opens up a new way for designing and advancing the tellurium dopant nanomaterials for various applications.

Impact of novel coronavirus (COVID-19) on daily routines and air environment: evidence from Turkey.

Turkish people are facing several problems because of the novel coronavirus (COVID-19), as the pandemic has brought about drastic changes to their daily routines. This study mainly investigates the impact of this pandemic on the daily routines of Turkish. It also unveils how COVID-19 affects the air environment. The adopted methods for data collection are based on open-ended questions and Facebook interviews as per recommended by QSR-International (2012). The sample of this study comprises of Turkish students as well as professional workers. The findings of the research show that there are eighteen different results of COVID-19 that have been identified according to the Turkish people's daily routines. Results reveal that increasing unemployment, decrease in air contamination, high stress and depression, a slowdown in the economic growth, and the tourism industry are profoundly affected due to the COVID-19 in Turkey. Furthermore, on the one hand, the consequences of the pandemic are segregated into social problems and psychological issues in daily routines. On the other hand, they have shown a positive impact on the air environment. This study concludes that, amid the COVID-19 pandemic, the lives of the people in Turkey are subject to deterioration, while the air environment of Turkey is gradually improving.

Dynamic interactive links among sustainable energy investment, air pollution, and sustainable development in regional China.

This research investigates the dynamic interactive associations among sustainable investment in the energy sector, air pollution, and sustainable development. To this end, it employs a "one-step" system-generalized method of moments (GMM) and "one-step" differential-GMM estimators, covering the period between 1996 and 2017. In this context, it utilizes the simultaneous equations of the dynamic panel data model for panel data of 27 Chinese provinces and municipalities. We have developed a new model of sustainable development, which incorporates sustainable investment in the energy sector and air pollution to offer a robust theoretical foundation for considering the underlying relations. The system-GMM estimator is used for the full data set; however, differential-GMM is utilized for the subsets of data, in order to tackle the small sample bias problem. The empirical outcomes provide several vital insights in that they yield mixed findings for the aggregated sample and subsets of data. For example, a two-way causal relationship occurs for all the panels, except the central part (medium development regions), between sustainable investment in the energy sector and sustainable development. Contrary to this, causality runs from air pollution to sustainable investment in the energy sector in a full data set and the central part (medium dev.). Nevertheless, the opposite is true in the case of the eastern part (most developed regions) of China. Still, the same relationship runs in either direction in the case of the western part (least developed regions). On the other way around, the feedback hypothesis of causality is confirmed, across all the samples, between air pollution and sustainable development. Hence, sustainable development and air pollution are overwhelmingly interdependent, in the country as well as the province and municipality level of the Chinese economy.

Asymmetric nexus between urban agglomerations and environmental pollution in top ten urban agglomerated countries using quantile methods.

The rapid urbanization growth has not only improved the living standards of people but also raised concerns for environmental sustainability over the globe. In this regard, the issue of excessive urban concentration or over-agglomeration in metropolitan areas is nowadays the prime concern for urban planning and building energy-efficient and eco-friendly infrastructures. In response to rising interest in the dynamic linkage between urban concentration and environment, the current research empirically examines the crucial nexus between urban agglomerations and environmental degradation in top ten urban agglomerated countries in the world from 1960Q1 to 2014Q4. The current research is the pioneer empirical work in the area of urbanization by applying recently developed and innovative methods of quantile-on-quantile (QQ) approach and quantile Granger causality in relatively less explored area of urban agglomeration at the cross-country level. Our mainstream findings indicate that urban agglomeration has a strong positive effect on CO2 emissions in most of our sample countries, and this effect is more pronounced in higher quantiles of respective variables. These results imply that excessive levels of urban concentration in big cities cause environmental degradation, which could be attributed to extreme population density, overcrowding, traffic congestion and extensive demand for energy consumption. However, some countries such as Israel, Paraguay and Columbia exhibit overall declining and negative trends about the relationship between urban agglomerations and CO2 emissions. Moreover, quantile Granger causality results confirm the previous findings of QQ regression and verify the existence of bidirectional causal nexus between urban agglomerations and CO2 emissions in the majority of the lower, middle and upper quantiles in our selected top ten countries except for Kuwait. However, the unidirectional causal relationship also exists for several countries for extreme lower, middle and extremely higher quantiles. Our findings extend the previous work on agglomeration-environment nexus by determining the asymmetric magnitude of linkage between these two variables demanding cautious and individual-focused policies for urban planning and environmental sustainability.

Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market.

In the wake of recent pandemic of COVID-19, we explore its unprecedented impact on the cryptocurrencies' market. Specifically, we check how the changing intensity of the COVID-19 represented by the daily addition in new infections worldwide affects the daily returns of the top 10 cryptocurrencies according to the market capitalization. The results from Quantile-on-Quantile Regression (QQR) approach reveal that the changing intensity levels of the COVID-19 affect the Bearish and the Bullish market scenarios of cryptocurrencies differently (asymmetric impact). Additionally, there are differences between these currencies in their responses to the changing levels of this pandemic's intensity. Most of the currencies absorbed the small shocks of COVID-19 by registering positive gains but failed to resist against the huge changes except Bitcoin, ADA, CRO, and up to some extent Ethereum. Our results reveal new and asymmetric dynamics of this emerging asset class against an extremely stressful and unpredictable event (COVID-19). Moreover, these results are robust to the use of alternative proxy (COVID-19 deaths) for pandemic intensity. Our findings help to improve investors and policymakers' understanding of the cryptocurrencies' market dynamics, especially in the times of extremely stressful and unseen events.

Co-variance nexus between COVID-19 mortality, humidity, and air quality index in Wuhan, China: New insights from partial and multiple wavelet coherence.

The worldwide outbreak of COVID-19 disease has caused immense damage to our health and economic and social life. This research article helps to determine the impact of climate on the lethality of this disease. Air quality index and average humidity are selected from the family of climate variables, to determine its impact on the daily new cases of COVID-19-related deaths in Wuhan, China. We have used wavelet analysis (wavelet transform coherence (WTC), partial (PWC), and multiple wavelet coherence (MWC), due to its advantages over traditional time series methods, to study the co-movement nexus between our selected data series. Findings suggest a notable coherence between air quality index, humidity, and mortality in Wuhan during a recent outbreak. Humidity is negatively related to the COVID-19-related deaths, and bad air quality leads to an increase in this mortality. These findings are important for policymakers to save precious human lives by better understanding the interaction of the environment with the COVID-19 disease.

Effects of climatological parameters on the outbreak spread of COVID-19 in highly affected regions of Spain.

The coronavirus (COVID-19) pandemic is infecting the human population, killing people, and destroying livelihoods. This research sought to explore the associations of daily average temperature (AT) and air quality (PM2.5) with the daily new cases of COVID-19 in the top four regions of Spain (Castilla y Leon, Castilla-La Mancha, Catalonia, and Madrid). To this end, the authors employ Pearson correlation, Spearman correlation, and robust panel regressions to quantify the overall co-movement between temperature, air quality, and daily cases of COVID-19 from 29 February to 17 July 2020. Overall empirical results show that temperature may not be a determinant to induce COVID-19 spread in Spain, while the rising temperature may reduce the virus transmission. However, the correlation and regression findings illustrate that air quality may speed up the transmission rate of COVID-19. Our findings are contrary to the earlier studies, which show a significant impact of temperature in raising the COVID-19 spread. The conclusions of this work can serve as an input to mitigate the rapid spread of COVID-19 in Spain and reform policies accordingly.

Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach.

The present study examines the asymmetrical effect of temperature on COVID-19 (Coronavirus Disease) from 22 January 2020 to 31 March 2020 in the 10 most affected provinces in China. This study used the Sim & Zhou' quantile-on-quantile (QQ) approach to analyze how the temperature quantities affect the different quantiles of COVID-19. Daily COVID-19 and, temperature data collected from the official websites of the Chinese National Health Commission and Weather Underground Company (WUC) respectively. Empirical results have shown that the relationship between temperature and COVID-19 is mostly positive for Hubei, Hunan, and Anhui, while mostly negative for Zhejiang and Shandong provinces. The remaining five provinces Guangdong, Henan, Jiangxi, Jiangsu, and Heilongjiang are showing the mixed trends. These differences among the provinces can be explained by the differences in the number of COVID-19 cases, temperature, and the province's overall hospital facilitations. The study concludes that maintaining a safe and comfortable atmosphere for patients while COVID-19 is being treated may be rational.

The nexus between COVID-19, temperature and exchange rate in Wuhan city: New findings from partial and multiple wavelet coherence.

This study attempts to document the nexus between weather, COVID-19 outbreak in Wuhan and the Chinese economy. We used daily average temperature (hourly data), daily new confirmed cases of COVID-19 in Wuhan, and RMB (Chinese currency) exchange rate to represent the weather, COVID-19 outbreak and the Chinese economy, respectively. The methodology of Wavelet Transform Coherence (WTC), Partial Wavelet Coherence (PWC) and Multiple Wavelet Coherence (MWC) is employed to analyze the daily data collected from 21st January 2020 to 31st March 2020. The results have revealed a significant coherence between the series at different time-frequency combinations. The overall results suggest the insignificance of an increase in temperature to contain or slow down the new COVID-19 infections. The RMB exchange rate and the COVID-19 showed an out phase coherence at specific time-frequency spots suggesting a negative but limited impact of the COVID-19 outbreak in Wuhan on the Chinese export economy. Our results are contrary to many earlier studies which suggest a significant role of temperature in slowing down the COVID-19 spread. These results can have important policy implications for the containment of COVID-19 spread and macro-economic management with respect to changes in the weather.