Financial health and economic growth responsiveness as solution to environmental degradation in Pakistan.

This study analyses the impact of GDP per capita, domestic credit, savings, and population on the environment in Pakistan from 1995 to 2019. The country has consistently been ranked eighth, fifth, and eight as an environmentally vulnerable nation from 1998 to 2017, 1999 to 2018, and 2000 to 2019, respectively. Therefore, the study explores the role of environmental awareness as a potential strategy for making peace with nature. Findings of the ARDL bounds testing approach confirm the long-run cointegration among variables of concern. In further assessment, the study determines that increased per capita income is detrimental to environmental quality in the long run. However, in the short run, it shows a favourable impact. On the other hand, domestic credit worsens the environment in the long and short runs. However, savings are positively insignificant in this regard. Furthermore, the total population significantly harms the environment in the long and short run. Fortunately, environmental awareness has emerged as a key solution to environmental degradation in Pakistan. Findings show that an increase in the dissemination of environmental awareness through the Internet, mobile, and landline phones, as well as by increasing education expenditures, mitigates the populations' detrimental impact on the environment and improves environmental quality in the long run.

Evaluating the impacts of renewable energy action plans: A synthetic control approach to the Turkish case.

This paper evaluates the impact of the National Renewable Energy Action Plans (NREAP) that was prepared under the (2009/28/EC) Directive of the European Commission by using Türkiye as a case study. We aimed to reveal the causal impacts of the plan on renewable energy generation based on different technologies such as hydro, wind, and solar, along with the impacts on greenhouse gas emissions. To do this, we used the synthetic control method. The study's outcome indicates that NREAP has served as a promising treatment policy for Türkiye's deployment of renewable energy potential. The total treatment effect is 14%, mainly driven by increases in solar and wind shares, while no significant impact was observed on the hydro share of electricity. Moreover, our analysis found no treatment effect on greenhouse gas emissions, and placebo tests supported the robustness of these results. The analysis did not reveal any evidence of a treatment effect on greenhouse gas emissions.

A hybrid LBP-CNN with YOLO-v5-based fire and smoke detection model in various environmental conditions for environmental sustainability in smart city.

Smart, secure, and environmentally friendly smart cities are all the rage in urban planning. Several technologies, including the Internet of Things (IoT) and edge computing, are used to develop smart cities. Early and accurate fire detection in a Smart city is always desirable and motivates the research community to create a more efficient model. Deep learning models are widely used for fire detection in existing research, but they encounter several issues in typical climate environments, such as foggy and normal. The proposed model lends itself to IoT applications for authentic fire surveillance because of its minimal configuration load. A hybrid Local Binary Pattern Convolutional Neural Network (LBP-CNN) and YOLO-V5 model-based fire detection model for smart cities in the foggy scenario is presented in this research. Additionally, we recommend a two-part technique for extracting features to be applied to YOLO throughout this article. Using a transfer learning technique, the first portion of the proposed approach for extracting features retrieves standard features. The section part is for retrieval of additional valuable information related to the current activity using the LBP (Local Binary Pattern) protective layer and classifications layers. This research utilizes an online Kaggle fire and smoke dataset with 13950 normal and foggy images. The proposed hybrid model is premised on a two-cascaded YOLO model. In the initial cascade, smoke and fire are detected in the normal surrounding region, and the second cascade fire is detected with density in a foggy environment. In experimental analysis, the proposed model achieved a fire and smoke detection precision rate of 96.25% for a normal setting, 93.2% for a foggy environment, and a combined detection average precision rate of 94.59%. The proposed hybrid system outperformed existing models in terms of better precision and density detection for fire and smoke.

An EKC-based modelling of CO2 emissions, economic growth, electricity consumption and trade openness in Serbia.

Understanding the complex interactions between the economy and the environment is crucial for promoting sustainable development and mitigating the negative impact of human activities on the Planet. The importance of this issue for Serbia is evident as the country strives to balance economic growth and environmental protection to ensure a sustainable and resilient future. Therefore, the main objective of this study is to investigate and model the relationship between CO2 emissions, economic growth, electricity consumption, and trade openness in Serbia. Initially, an Autoregressive Distributed Lag (ARDL) model is used to characterize the Environmental Kuznets Curve (EKC) using data from the period from 1995 to 2019, followed by the construction of a bootstrap logistic regression model to predict environmental quality in Serbia. Long-term estimates of the model confirm an inverted U-shaped relationship, where all three variables exert a statistically significant influence on CO2 emissions. In the short run, however, a causal relationship is only observed between electricity consumption and CO2 emissions. The logistic regression results show that all three factors significantly influence environmental quality. The study proposes policy recommendations for Serbia, such as promoting sustainable economic growth, implementing long-term programs to reduce CO2 emissions, reviewing trade policies to prioritize sustainable practices, and investing in renewable energy sources to reduce emissions.

Incorporating Russo-Ukrainian war in Brent crude oil price forecasting: A comparative analysis of ARIMA, TARMA and ENNReg models.

This article investigates the performance of three models - Autoregressive Integrated Moving Average (ARIMA), Threshold Autoregressive Moving Average (TARMA) and Evidential Neural Network for Regression (ENNReg) - in forecasting the Brent crude oil price, a crucial economic variable with a significant impact on the global economy. With the increasing complexity of the price dynamics due to geopolitical factors such as the Russo-Ukrainian war, we examine the impact of incorporating information on the war on the forecasting accuracy of these models. Our analysis shows that incorporating the impact of the war can significantly improve the forecasting accuracy of the models, and the ENNReg model with the inclusion of the dummy variable outperforms the other models during the war period. Including the war variable has enhanced the forecasting accuracy of the ENNReg model by 0.11%. These results carry significant implications regarding policymakers, investors, and researchers interested in developing accurate forecasting models in the presence of geopolitical events such as the Russo-Ukrainian war. The results can be used by the governments of oil-exporting countries for budget policies.

Exploring the impact of public funds and eco-friendly innovations on reducing carbon pollution in North Africa.

The main objective of this study is to examine the impacts of green energy and public investment on the CO2 emissions in North Africa. Moreover, the study also tests the existence of the N-shaped Environmental Kuznets Curve (EKC) hypothesis for North African countries between 1995 and 2018. These factors were analyzed using the Dynamic Ordinary Least Squares (DOLS), Fully Modified Ordinary Least Squares (FMOLS), and Pooled Mean Group (PMG) estimators to obtain estimations of heterogeneous parameters. The outcome of these tests and examinations showed that the N-shaped curve was confirmed. Secondly, The results of the study also demonstrate the effectiveness of renewable energy as an eco-friendly innovation in reducing carbon emissions. This finding highlights the positive impact that renewable energy sources can have in terms of emitting fewer carbon emissions compared to traditional energy sources. Moreover, public investment, which interprets government expenditure, and urbanization contribute to environmental degradation by increasing CO2 emissions in the case of North African countries. Furthermore, the findings also indicated a trade-off effect resulting from the correlation between CO2 emissions and economic development. Based on these findings, the study recommends that economic policymakers in North African countries prioritize transforming the structure of government expenditures to improve environmental quality, optimize the utilization of revenues from non-environmentally friendly energy resources to accelerate the energy transition, increase the exploitation of renewable energy, and promote environmental awareness in society. By implementing these recommendations, North African countries can balance economic growth and environmental quality while reducing their carbon footprint.

Pollution and electricity price in the EU Central and Eastern European countries: a sectoral approach.

Pollution and energy crisis are actual issues in Europe, including the EU Central and Eastern European states. In this context, the objective of this paper is to assess the impact of economic growth and electricity prices for non-household consumers on pollution. The empirical findings reveal the U pattern for energy industry and inverted U pattern for manufacturing in the period 2007-2021 in the EU countries from Central and Eastern Europe. Renewable energy consumption reduces the CO2 and GHG emissions in energy industry. FDI and electricity prices determine the reduction in GHG and CO2 emissions in both sectors. These results are the basis for policy recommendations.

Do farmers' risk perception, adaptation strategies, and their determinants benefit towards climate change? Implications for agriculture sector of Punjab, Pakistan.

Due to global and regional climatic dynamics for a couple of decades, agricultural productivity, rural livelihood, and food security have been badly affected in Pakistan. This study was conducted in Punjab, Pakistan, to explore the farmers' understanding of the impacts of climate change, adaptation strategies, determinants, and benefits on agriculture using data from 1080 respondents. Perceived risks by the farmers in the rice-wheat cropping system and the cotton-wheat cropping system were weed infestation, seed rate augmented, low-quality seeds, infestation of crop diseases and pests, change of cropping pattern, increase of input use, decrease of cropping intensity and productivity, decreasing soil fertility, increasing irrigation frequency, and increase of harvesting time. To alleviate the adverse influences of climate change, the adaptation strategies used by farmers were management of crop and variety, soil and irrigation water, diversification of agriculture production systems and livelihood sources, management of fertilizer and farm operations time, spatial adaptation, access to risk reduction measures and financial assets, adoption of new technologies, institutional support, and indigenous knowledge. Moreover, the results of Binary Logistic Regression indicate that adaptation strategies are affected by different factors like age, education, household family size, off-farm income, remittances, credit access, information on climatic and natural hazards, information on weather forecasting, land acreage, the experience of growing crops and rearing of livestock, tenancy status, tube well ownership, livestock inventory, access to market information, agricultural extension services, and distance from agricultural input/output market. There is a significant difference between adapters and nonadapters. The risk management system may be created to protect crops against failures caused by extreme weather events. There is a need to develop crop varieties that are both high yielding and resistant to climate change. Moreover, cropping patterns should be revised to combat the effects of climate change. To enhance farmers' standard of living, it is necessary to provide adequate extension services and a more significant number of investment facilities. These measures will assist farmers in maintaining their standard of living and food security over the long term to adapt to the effects of climate change based on various cropping zones.

Renewable energy, economic freedom and economic policy uncertainty: New evidence from a dynamic panel threshold analysis for the G-7 and BRIC countries.

This study aims to demonstrate the impact of renewable energy consumption (REC) on environmental degradation using the EKC hypothesis testing for the BRIC and G-7 countries. Two EKC models were created and tested, with Model 2 including REC and other independent variables such as economic freedom (EF) and economic policy uncertainty (EPU), which affect the level of renewable energy consumption and CO2 emissions. Empirical findings indicate that the EKC hypothesis is verified faster in the REC-EF-EPU-based EKC model (Model 2) than in the EF-EPU-based EKC model (Model 1) for G-7 countries since the turning point takes place earlier in Model 2 than in Model 1 with REC. This suggests that renewable energy consumption accelerates the reduction of CO2 emissions. Moreover, this earlier turning point results in lower environmental cleaning costs, less time vesting, and saving resources and money for G-7 countries. However, the study found no evidence supporting the EKC hypothesis for the BRIC countries.

Pollution, political instabilities and electricity price in the CEE countries during the war time.

Pollution, war and energy crisis are the CEE countries' most important global actual issues. Therefore, this study aims to investigate the impact of political stability and electricity price in 11 CEE countries in the period 2007-2021 to anticipate the effect of these factors on pollution in times of political and energy crisis. The common results based on DOLS/FMOLS and CCEMG estimations indicate that political stability enhances CO2 emissions, while higher electricity prices for non-household consumers reduce pollution. An inverted-U pattern was observed in the relationship between growth and pollution, while renewable energy consumption is the most powerful tool to reduce CO2 emissions. These results are the starting point for policy recommendations.

Environmental technology, economic complexity, renewable electricity, environmental taxes and CO2 emissions: Implications for low-carbon future in G-10 bloc.

This study investigates the impact of environmental technological innovation, economic complexity, energy productivity, the use of renewable electricity generation, and environmental taxes on carbon dioxide (CO2) emissions in the G-10 countries for the timeframe from 1995 to 2020. The purpose of the study is to examine the need for a clear plan or strategy to achieve environmental objectives in G-10 countries. In both short-term and long-term projections, the increased use of environment-based technology, economic complexity, and renewable electricity generation has a major positive impact on carbon emission reduction. Moreover, the results demonstrate both unidirectional and bidirectional causality from carbon emissions to renewable energy, electrical generation, and environment-based technologies, respectively. Based on the results, the study proposes a number of concrete policies, such as updating modernized tax systems, increasing tax collection, providing individuals with the means to finance the Sustainable Development Goals through incentive regulations, and making grants from international organizations and the private sector available to finance investments toward the Sustainable Development Goals (SDGs) and carbon neutrality environment targets. This is the study's most significant contribution in order to attain a sustainable and low-carbon future in the G-10 countries, which has policy implications for governments and policymakers.

The relationship between CO2 emissions, economic growth, available energy, and employment in SEE countries.

As a result of a greater worldwide aspiration for wealth and economic progress, increased use of natural resources for diverse industries resulted in increased pollution emissions, mainly carbon dioxide. Energy security, economic stability, job security, biodiversity loss, climate change, and global warming all require reconciliation and resolution now, more than ever before. This paper explores the causal relationship between CO2 emissions, economic growth, available energy, and employment for a panel of eight South-Eastern European countries from 1995 to 2019. We investigate the relationship using panel unit root tests, panel cointegration methods, and panel causality tests. The results show a short-run bidirectional panel causality between CO2 emissions and employment and between available energy and employment. The results further indicate a unidirectional causality from available energy and employment to GDP. The long-run causal relationship results show that the estimated coefficients of the lagged ECT in the CO2 emissions, GDP, and employment equations are statistically significant, implying that these variables could play a significant role in the system's adjustment process as it departs from long-run equilibrium. We also conducted a variance decomposition analysis, which allowed us to compare the extent of the individual factors' contributions to each other over the next 5 years.

Renewable Energy Consumption-Growth Nexus in European Countries: A Sectoral Approach.

The renewable energy consumption plays a significant role in achieving sustainable development, but a sectoral approach is necessary to design the better recommendations for each sector. In this context, the main objective of this paper is to assess the impact of the use of this type of energy on economic growth in 23 European Union (EU) member states in the period 1990-2020. Besides overall renewable energy consumption, different utilisations of this energy are considered: in industry, transport, in commercial and public services, and for residential purposes. The methodological background is built around panel data models that start from a Cobb-Douglas function. The renewable energy consumption is considered an important factor that should generate economic growth. The panel data approach based on causality analysis and Augmented Mean Group and Common Correlated Effects Mean Group estimators suggests that renewable energy use in industry does not determine economic growth, but economic development is a cause for more utilisation of this energy in industry. In addition, more renewable energy consumption in transport enhances economic growth. A high level of economic development can promote the consumption of renewable energies in industrial sectors. In this way, industrial companies can allocate more financial funds to research in the field of renewable energies and can afford to adopt renewable energy sources. Investment in biofuels can contribute to achieving sustainable transport in the EU.

Examining the role of nuclear and renewable energy in reducing carbon footprint: Does the role of technological innovation really create some difference?

The deployment of energy sources is considered the compassion of several United Nations Sustainable Development Goals (SDGs). Countries should keep balance with the three major proportions of the global energy trilemma: energy security, affordability, energy access, and ecological balance to construct a solid basis for competitiveness and prosperity. In this regard, this study examines the influence of nuclear energy, technological innovations, renewable energy, non-renewable energy, and natural resources on carbon footprint in the highest nuclear energy-producing countries from 1990 to 2019. To do this, we developed an inclusive and comprehensive empirical investigation and applied modern econometric approaches. Panel second-generation long-run cointegration advocates long-run associations among the series. The findings reveal that nuclear and renewable energy consumption extensively improve environmental excellence. Conversely, technological innovations and non-renewable energy significantly reduce environmental sustainability. Moreover, natural resources play an adverse role in long-run. The findings of the panel causality test discovered unidirectional causality is running from carbon footprint to nuclear energy. Additionally, bidirectional causality exists between technological innovations, renewables, non-renewables, and natural resources with carbon footprint. This recommends that these nations should integrate energy policy activities and develop energy strategy consistency by harmonizing the vital global nuclear energy aspects to assist a well-calibrated energy structure.

An analysis of the impact of clean and non-clean energy consumption on economic growth and carbon emission: evidence from PIMC countries.

This study empirically estimates the impact of clean and non-clean energy consumption on economic growth and carbon dioxide emissions within the framework of the environmental Kuznets curve and pollution haven hypothesis in the case of PIMC countries from 1980 to 2019. The results of the panel cointegration test proposed by Westerlund (2007) show a long-term equilibrium relationship among the variables of each designated model. The long-term elasticities of economic growth and carbon emission estimated by AMG, CCEMG, and MG estimators indicate that both clean and non-clean energy consumption has a significant impact on economic growth, while carbon emission hinders growth. The results also reveal that economic growth, non-clean energy consumption, and interaction between trade openness and non-clean energy consumption have a driving effect on carbon dioxide emission; however, clean energy consumption is found to reduce carbon emission. In addition, the analysis confirms the existence of the inverted U-shaped environmental Kuznets curve and pollution haven hypothesis in the panel of PIMC economies. Finally, there is a one-way causality from non-clean energy consumption to economic growth, but no such causation exists between clean energy consumption and economic growth. The objective of sustained economic growth with a safe environment may be achieved by encouraging clean energy consumption in the PIMC economies.

Revealing the dynamic effects of fossil fuel energy, nuclear energy, renewable energy, and carbon emissions on Pakistan's economic growth.

The primary goal of this study was to examine the relationship between fossil fuel energy, electricity production from nuclear sources, renewable energy, CO2 emissions, and economic growth in Pakistan. Data ranging from 1975 to 2019 were utilized, and the stationarity of this data was verified through the unit root testing. The dynamic connections between variables were investigated by utilizing the linear autoregressive distributed lag technique. Long-run analysis results uncover that fossil fuel energy, renewable energy use, CO2 emissions, and GDP per capita have a productive relationship with economic progress in Pakistan, whereas electric power consumption, electricity produced from nuclear sources, and energy utilization have an adverse effect on economic growth. Furthermore, the consequences revealed that fossil fuel energy, renewable energy consumption, carbon dioxide emissions, and GDP per capita have a significant linkage to Pakistan's economic growth via short run, whereas we revealed that the variables electric power consumption, electricity produced from nuclear sources, and energy usage have an adversative linkage to Pakistan's economic growth. Feasible progressive policies are required from the Pakistani government to pay more attention for tackling the energy and power sectors' issues in terms of fulfilling the country's energy requirements.

Towards Employee Creativity in the Healthcare Sector: Investigating the Role of Polychronicity, Job Engagement, and Functional Flexibility.

Given the importance of individual level creativity, this paper investigates the influence of employee polychronicity on employee creativity among nurses in the healthcare sector. The current research also tests how job engagement acts as a mediator between employees' polychronicity and creativity. Finally, thepaper analyzes the role of functional flexibility as a moderator that enhances the influence of polychronicity on employee creativity. The current paper presents empirical research, and cross-sectional data were gathered from 457 nurses (Subordinate Staff) and 127 doctors (Supervisors) working in 37DHQ (District Head Quarters) hospitals in Pakistan. Descriptive statistics, correlation, and multiple-regression techniques were applied for analyzing the collected data. The findings proved that the nurses' polychronic attitude increases their creativity. Findings revealed that job commitment plays a mediating role between polychronicity and employee creativity. The findings proved that functional flexibility enhances the link between polychronicity and creativity. This research has contributed to both theory and managerial practice about the interplay of polychronicity, creativity, job engagement, and functional flexibility among nurses. The management in practice should focus on employee attitude, i.e., polychronicity, for improving their creativeness.

Economic complexity, tourism, energy prices, and environmental degradation in the top economic complexity countries: fresh panel evidence.

The study explores the association between economic complexity index (ECI), tourism (TR), gross domestic products (GDP), gross domestic products per capita (GPC), and energy prices indices (EPI) on CO2e using the top 18 economic complexity index countries data from 1990 to 2019. We employ the second-generation cointegration methods and cross-sectionally augmented autoregressive distributed lag (CS-ARDL) to analyze the short- and long-term association also Dumitrescu and Hurlin Granger causality test applied. The results of Pesaran and Yamagata slope heterogeneity and Pesaran CD test confirm the presence of cross-sectional unit relationship and slope heterogeneity across countries, while positive long- and short-term associations were found among ECI, GDP, and CO2e. Also, TR, GPC, and EPI decrease carbon emissions both in the long and short term . Moreover, Augmented Mean Group (AMG) techniques verified and support these findings. The outcomes of the Dumitrescu and Hurlin Granger causality test showed that any policy aim at ECI, TR, GDP, GPC, and EPI has a considerable impact on CO2e. Based on the rigorous empirical analysis, we suggest that economic complexity, tourism, GDP, GPC, and energy prices would help alleviate high economic complexity countries' environmental degradation challenges.

Health education about occupational allergies and dermatoses for adolescents.

BACKGROUND: Occupational dermatoses and allergies are frequent and often affect individuals with atopic dermatitis. Our aim was to inform adolescents about potentially dangerous occupations, risk groups and preventive measures before they started apprenticeships in order to minimize the risk of occupational allergies or skin diseases. METHODS: 1015 high-school students were instructed by two dermatologists/ allergists (Heidelberg) and a teacher (Potsdam) in a 90-minute instructional unit. This included the exemplification of occupational skin hazards and allergies, the identification of at-risk persons, and application of preventive measures. A questionnaire was filled in by the students prior to and at least two weeks after the training. RESULTS: In both regions, the students showed an increase in knowledge after the training, which was statistically significant higher in the Heidelberg region (6.6 points on average vs.4.4 points). 76% of students termed the subject matter as "important", and 67% rated the teaching unit as "very good" or "good". CONCLUSIONS: We demonstrate that students who have not yet chosen a career are highly interested in this subject, that the developed instructional unit is widely accepted, and that it leads to an increase in knowledge. Therefore we suggest nation-wide implementation of this primary prevention measure in high-schools.

Occupational skin diseases in cleaning and kitchen employees: course and quality of life after measures of secondary individual prevention.

BACKGROUND: Cleaning and kitchen employees have an increased risk of suffering from occupational dermatoses. Prevention including improving individual skin care and skin protection behavior, health education, optimizing diagnostics and therapy as well as avoidance of occupational skin disease (BK 5101) is important. PATIENTS AND METHODS: Participants in the courses were patients suspected of having an occupational skin disease. Besides socio-demographic and disease-related data, health-related quality of life (QL) was measured using the SF-36 and Skindex-29. One year later all participants were interviewed by telephone about the course of their skin disease. RESULTS: Out of 212 participants, 84.0 % were female. The mean age was 41.6 (SD = 10.8) years.168 patients (79.2 %) suffered from hand dermatitis,with irritant contact dermatitis being the predominant diagnosis (46.2 %,n = 98). One year later 65.4 % (n = 85) of the patients interviewed still suffered from hand dermatitis.9.2 % (n = 12) had meanwhile quit their job due to the skin disease. QL was impaired in all age groups being lower with increasing age of the patients. CONCLUSIONS: The follow-up confirmed the positive impact of the skin protection courses on patients' skin disease and well-being. Occupational skin diseases impair health-related quality of life in these professions but disease severity does not seem to play a key role.