Every country intends to enhance national production by achieving sustainable development. The purpose of this study is to examine whether there exists any long-run association among environmental deterioration measured by territorial emissions in CO2, demographic factors (total population, population density, and urban population) and some other variables, namely, energy use, per capita income, energy intensity, and industrial value added for the 16 countries from the Middle East and North African (MENA) over 1990-2018. We implemented the generalized method of moments (GMM), fully modified ordinary least square (FMOLS), robust least square estimators, and panel Granger causality techniques for estimation. The empirical estimates reveal that there exists a long run cointegration among the series. Results also exhibit that energy use, per capita income, energy intensity, industrial value added, population density, total population, and urban population have positive effects on CO2 emissions. Furthermore, in each panel, there is bi-directional causality between population density and CO2 emissions, total population and CO2 emissions, and urban population and CO2 emissions. These findings suggest that the policymakers need not exclusively to focus on the transformation of rural labor from an agricultural-based model to urban regions with powerful, dominant industry and services sectors but also related to the changing of rural establishments into urban spaces is required. These changes in demographics involve changes in the demand for additional transportation services, food, shelter, clothing, and other necessities.
An exponential rise in global pollution and industrialization has led to significant economic and environmental problems due to the insufficient application of green technology for the chemical industry and energy production. Nowadays, the scientific and environmental/industrial communities push to apply new sustainable ways and/or materials for energy/environmental applications through the so-called circular (bio)economy. One of today's hottest topics is primarily valorizing available lignocellulosic biomass wastes into valuable materials for energy or environmentally related applications. This review aims to discuss, from both the chemistry and mechanistic points of view, the recent finding reported on the valorization of biomass wastes into valuable carbon materials. The sorption mechanisms using carbon materials prepared from biomass wastes by emphasizing the relationship between the synthesis route or/and surface modification and the retention performance were discussed towards the removal of organic and heavy metal pollutants from water or air (NOx, CO2, VOCs, SO2, and Hg0). Photocatalytic nanoparticle-coated biomass-based carbon materials have proved to be successful composites for water remediation. The review discusses and simplifies the most raised interfacial, photonic, and physical mechanisms that might take place on the surface of these composites under light irradiation. Finally, the review examines the economic benefits and circular bioeconomy and the challenges of transferring this technology to more comprehensive applications.
The tourism industry is vulnerable to a range of economic and political factors, which can have both short-term and long-term impacts on tourist arrivals. The study aims to investigate the temporal dynamics of these factors and their impact on tourist arrivals. The method employed is a panel data regression analysis, using data from BRICS economies over a period of 1980-2020. The dependent variable is the number of tourist arrivals, while the independent variables are geopolitical risk, currency fluctuation, and economic policy. Control variables such as GDP, exchange rate, and distance to major tourist destinations are also included. The results show that geopolitical risk and currency fluctuation have a significant negative impact on tourist arrivals, while economic policy has a positive impact. The study also finds that the impact of geopolitical risk is stronger in the short term, while the impact of economic policy is stronger in the long term. Additionally, the study shows that the effects of these factors on tourist arrivals vary across BRICS countries. The policy implications of this study suggest that BRICS economies need to develop proactive economic policies that promote stability and encourage investment in the tourism industry.
Australia is one of the largest nations in the globe in terms of land area and is home to numerous animals alongside unique and unusual climates and immense forests and oceans. Despite having a very tiny population, the nation is an extremely valuable ecological territory. Unfortunately, due to several changes in land use, habitat loss and deterioration-particularly in light of the recent severe bush fires exacerbated by climate change-the environmental issues in Australia have got the attention of many academics. Therefore, this paper seeks to assess the association between Australia's energy use, [Formula: see text] emission, trade liberalization, industrialization and economic growth from 1990 to 2018. An autoregressive distributed lag and a vector error correction model (VECM) are employed to take care of possible endogeneity and the long-run association. Our results demonstrated that economic growth and energy use have positive and statistically significant effects on emissions of [Formula: see text], but trade liberalization has a significantly adverse influence on emissions of [Formula: see text] both in the long and short term. Granger test in VECM uncovered single-direction Granger interrelationships among trade liberalization and industrialization, as well as among industrialization and carbon dioxide. When attempting to implement effective energy policies, Australian policymakers should first take into account the prominent role played by energy usage and trade liberalization in promoting economic development and impeding environmental health.
Microalgae CO2 sequestration has gained considerable attention in the last three decades as a promising technology to slow global warming caused by CO2 emissions. To provide a comprehensive and objective analysis of the research status, hot spots, and frontiers of CO2 fixation by microalgae, a bibliometric approach was recently chosen for review. In this study, 1561 articles (1991-2022) from the Web of Science (WOS) on microalgae CO2 sequestration were screened. A knowledge map of the domain was presented using VOSviewer and CiteSpace. It visually demonstrates the most productive journals (Bioresource Technology), countries (China and USA), funding sources, and top contributors (Cheng J, Chang JS, and their team) in the field of CO2 sequestration by microalgae. The analysis also revealed that research hotspots changed over time and that recent research has focused heavily on improving carbon sequestration efficiency. Finally, commercialization of carbon fixation by microalgae is a key hurdle, and supports from other disciplines could improve carbon sequestration efficiency.
The building sector is one of the major contributors to greenhouse gas (GHG) emissions, which may impede the achievement of Malaysia's intended nationally determined contribution (INDC) by 2030. Therefore, this paper is aimed at identifying the underlying factors that affect working adults' willingness to pay (WTP) premium prices for green buildings. Data were collected from a total of 1198 respondents and analyzed using structural equitation modeling partial least square (SEM-PLS) to measure the willingness to pay for green buildings among working adults in Malaysia. The findings reveal that environmental literacy affects environmental belief as well as awareness of consequences among working adults in Malaysia. The findings also reveal that incentives for green building buyers have a significant impact on perceived behavioral control, while awareness of consequences has a significant influence on ascription of responsibility. However, the results reveal that awareness of consequences does not influence buyers' willingness to pay for green buildings. Moreover, the ascription of responsibility and perceived behavioral control have a significant effect on willingness to pay for green buildings. The findings of this study will help the concerned authorities to take appropriate steps to promote willingness to pay for green buildings, which will contribute significantly to the realization of INDC by 2030 as part of the Paris Agreement.
The current production and conception have impacted the environmental hazards. Green innovation (GI) is the ideal solution for sustainable production, consumption, and ecological conservation. The objective of the study is to compare comprehensive green innovation (green product, process, service, and organization) impact on firm financial performance in Malaysia and Indonesia, along with the first study to measure the moderation role of the corporate governance index. This study has addressed the gap by developing the green innovation and corporate governance index. Collected panel data from the top 188 publicly listed firms for 3 years and analyzed it using the general least square method. The empirical evidence demonstrates that the green innovation practice is better in Malaysia, and the outcome also shows that the significance level is higher in Indonesia. This study also provides empirical evidence that board composition has a positive moderation relationship betwixt GI and business performance in Malaysia but is insignificant in Indonesia. This comparative study provides new insights to the policymakers and practitioners of both countries to monitor and manage green innovation practices.
Dissolved oxygen is an ecologically critical variable with the prevalence of hypoxia one of the key global anthropogenic issues. A study was carried out to understand the causes of low dissolved oxygen in Brunei Bay, northwest Borneo. Hypoxia was widespread in bottom waters in the monsoonal dry season with dissolved oxygen
Global warming and the dreadful climate condition in China demands the sustainable energy transition and production that must be far away from coal-based energy production. The present article, thereby, intends to assess the effectiveness of environmental knowledge and green supply chain practices on sustainable energy production. The study also introduces green behavior and green leadership as a moderator to evaluate the proposed relationship. Primary data has been collected and assessed by PLS-SEM. The findings reveal that environmental knowledge, green purchases, and internal environmental management (IEM) have a positive association with sustainable energy production (SEP) in China. The outcomes also indicate that green behavior significantly moderates among environmental knowledge, green purchases, and SEP, and green leadership significantly moderates among IEM and SEP in China. The research guides the policymakers in establishing policies related to SEP using green behavior, GSC practices, and environmental knowledge.
This paper examines the impact of green credit (GC) on digital technology innovation based on Chinese enterprises using panel data from 1990 to 2016. The study collected panel data from the 40 Chinese firms listed on the Beijing and Wuhan stock markets. Manufacturing companies were selected because they mainly contribute to green credit from pre- and post-policy periods. First, in the "two high and one surplus" sectors, the application of China's Green Credit 2012 could significantly increase total factor digital technology innovation by 1.21%. Results show a considerable drop in the variable values of digital technology innovation, 61.3%; green credit policy, 10.45%; leverage, 21.0%; and green innovation, 85.4%. The results of the absolute value of standard error after matching is much lower than 20.0%, demonstrating that the variable features of the two sets of samples are similar. In conclusion, GC's impact on the FDI of capital was asymmetrical, reflecting various impacts on businesses with various types of property rights and sizes.
Eco-innovations are widely considered the best possible solution to fight the menace of environmental degradation. Therefore, in this analysis, we try to examine the impact of eco-innovations and environmental entrepreneurship on SME performance in China from 1998 to 2020. In order to get the short- and long-run estimates, we have employed the QARDL model that can estimate across various quantiles. The findings of the QARDL model confirm the positive impact of eco-innovations in increasing the number of SMEs in the long run, as the estimates attached to eco-innovations are positive and significant across most quantiles. Similarly, the estimates attached to financial development and institutional quality are positively significant across most quantiles. However, in the short run, the results are inconclusive for almost all variables. As far as the asymmetric impact of eco-innovations on SMEs is concerned, it is confirmed both in the short and long run. However, the asymmetric impacts of financial development and institutional quality on SMEs are only confirmed in the long run. Based on the results, important policy suggestions are discussed.
As the negative repercussions of environmental devastation, such as global warming and climate change, become more apparent, environmental consciousness is growing across the world, forcing nations to take steps to mitigate the damage. Thus, the current study assesses the effect of green investments, institutional quality, and political stability on air quality in the G-20 countries for the period 2004-2020. The stationarity of the variables was examined with the Pesaran (J Appl Econ 22:265-312, 2007) CADF, the long-term relationship between the variables by Westerlund (Oxf Bull Econ Stat 69(6):709-748, 2007), the long-run relationship coefficients with the MMQR method proposed by Machado and Silva (Econ 213(1):145-173, 2019), and the causality relationship between the variables by Dumitrescu and Hurlin (Econ Model 29(4):1450-1460, 2012) panel causality. The study findings revealed that green finance investments, institutional quality and political stability increased the air quality, while total output and energy consumption decreased air quality. The panel causality reveals a unidirectional causality from green finance investments, total output, energy consumption and political stability to air quality, and a bidirectional causality between institutional quality and air quality. According to these findings, it has been found that in the long term, green finance investments, total output, energy consumption, political stability, and institutional quality affect air quality. Based on these results, policies implications were proposed.
Bike-sharing service has become a popular sustainable means of transportation due to its direct impact on traffic congestion, energy consumption, the environment, and people's quality of life. Existing literature suggests that sustainable consumption can be promoted by engaging consumers with green products. This study examined drivers and the outcome of consumer engagement with bike-sharing services based on the technology acceptance model (TAM). A survey was conducted to collect the data from the users of the bike-sharing service in Kuala Lumpur. Structural equation modelling was used to analyse the data and find the relationship between variables. The empirical analyses showed that perceived ease of use and perceived usefulness of the bike-sharing service positively impact all facets of consumer engagement with bike-sharing service, which subsequently influences the continuance usage intention of bike-sharing service. The findings of this study offer useful insights that could enhance the consumption of bike-sharing service. This study also offers some guidelines to transportation practitioners, policymakers, and urban planners regarding promoting healthy and sustainable travel behaviour among urban commuters through bike-sharing service.
Environmental pollution has been a major concern for researchers and policymakers. A number of studies have been conducted to enquire the causes of environmental pollution which suggested numerous policies and techniques as remedial measures. One such major source of environmental pollution, as reported by previous studies, has been the garbage resulting from disposed hospital wastes. The recent outbreak of the COVID-19 pandemic has resulted into mass generation of medical waste which seems to have further deteriorated the issue of environmental pollution. This necessitates active attention from both the researchers and policymakers for effective management of medical waste to prevent the harm to environment and human health. The issue of medical waste management is more important for countries lacking sophisticated medical infrastructure. Accordingly, the purpose of this study is to propose a novel application for identification and classification of 10 hospitals in Iraq which generated more medical waste during the COVID-19 pandemic than others in order to address the issue more effectively. We used the Multi-Criteria Decision Making (MCDM) method to this end. We integrated MCDM with other techniques including the Analytic Hierarchy Process (AHP), linear Diophantine fuzzy set decision by opinion score method (LDFN-FDOSM), and Artificial Neural Network (ANN) analysis to generate more robust results. We classified medical waste into five categories, i.e., general waste, sharp waste, pharmaceutical waste, infectious waste, and pathological waste. We consulted 313 experts to help in identifying the best and the worst medical waste management technique within the perspectives of circular economy using the neural network approach. The findings revealed that incineration technique, microwave technique, pyrolysis technique, autoclave chemical technique, vaporized hydrogen peroxide, dry heat, ozone, and ultraviolet light were the most effective methods to dispose of medical waste during the pandemic. Additionally, ozone was identified as the most suitable technique among all to serve the purpose of circular economy of medical waste. We conclude by discussing the practical implications to guide governments and policy makers to benefit from the circular economy of medical waste to turn pollutant hospitals into sustainable ones.
Identification of contaminant sources in rivers is crucial for river protection and emergency response. This study presents an innovative approach for identifying river pollution sources by using Bayesian inference and cellular automata (CA) modeling. A general Bayesian framework is proposed that combines the CA model with observed data to identify unknown sources of river pollution. To reduce the computational burden of the Bayesian inference, a CA contaminant transport model is developed to efficiently simulate pollutant concentration values in the river. These simulated concentration values are then used to calculate the likelihood function of available measurements. The Markov chain Monte Carlo (MCMC) method is used to produce the posterior distribution of contaminant source parameters, which is a sampling-based method that enables the estimation of complex posterior distributions. The suggested methodology is applied to a real case study of the Fen River in Yuncheng City, Shanxi Province, Northern China, and it estimates the release time, release mass, and source location with relative errors below 19%. The research indicates that the proposed methodology is an effective and flexible way to identify the location and concentrations of river contaminant sources.
This study contributes to develop a hierarchical framework for assessing the strategic effectiveness of waste management in the construction industry. This study identifies a valid set of strategic effectiveness attributes of sustainable waste management (SWM) in construction. Prior studies have neglected to develop a strategic effectiveness assessment framework for SWM to identify reduce, reuse, and recycle policy initiatives that ensure waste minimization and resource recovery programs. This study utilizes the fuzzy Delphi method to screen out nonessential attributes in qualitative information. This study initially proposes a set of 75 criteria; after two rounds of assessment, consensus regarding 28 criteria is achieved among experts, and the 28 criteria are validated. Fuzzy interpretive structural modeling divides the attributes into various elements. The modeling constructs a six-level model that depicts the interrelationships among the 28 validated criteria as a hierarchical framework, and it finds and ranks the optimal drivers for practical improvement. This study integrates the best-worst method to measure the weights of different criteria in the hierarchical strategic effectiveness framework. The findings reveal that waste management operational strategy, construction site waste management performance, and the mutual coordination level are the top aspects for assessing strategic effectiveness in the hierarchical framework. In practice, the waste reduction rate, the recycling rate, water and land usage, the reuse rate, and noise and air pollution levels are identified to assist policymakers in evaluation. The theoretical and managerial implications are discussed.
Waste electrical and electronic equipment or e-waste has recently emerged as a significant global concern. This waste contains various valuable metals, and via recycling, it could become a sustainable resource of metals (viz. copper, silver, gold, and others) while reducing reliance on virgin mining. Copper and silver with their superior electrical and thermal conductivity have been reviewed due to their high demand. Recovering these metals will be beneficial to attain the current needs. Liquid membrane technology has appeared as a viable option for treating e-waste from various industries as a simultaneous extraction and stripping process. It also includes extensive research on biotechnology, chemical and pharmaceutical, environmental engineering, pulp and paper, textile, food processing, and wastewater treatment. The success of this process depends more on the selection of organic and stripping phases. In this review, the use of liquid membrane technology in treating/recovering copper and silver from industrial e-waste leached solutions was highlighted. It also assembles critical information on the organic phase (carrier and diluent) and stripping phase in liquid membrane formulation for selective copper and silver. In addition, the utilization of green diluent, ionic liquids, and synergist carrier was also included since it gained prominence attention latterly. The future prospects and challenges of this technology were also discussed to ensure the industrialization of technology. Herein, a potential process flowchart for the valorization of e-waste is also proposed.
This study empirically investigates the effect of meat consumption on greenhouse gas emissions (carbon dioxide, methane, and nitrous oxide) in the USA. The impact of meat consumption on greenhouse gas emissions is examined by controlling for economic growth and energy consumption. The empirical analysis finds that all these variables are cointegrated for the long run. Moreover, meat consumption aggravates greenhouse gas emissions. Specifically, meat consumption (except for beef) has a U-shaped relationship with carbon emissions and an inverted U-shaped relationship with methane and nitrous oxide emissions. The causality analysis indicates a unidirectional causality running from meat consumption to greenhouse gas emissions. These empirical findings indicate that the US livestock sector has the potential to become more environmentally friendly with careful policy formulation and implementation.
South and Southeast Asia is by far the most populous region in Asia, with the greatest number of threatened species. Changes in habitat are a major contributor to biodiversity loss and are more common as a result of land-use changes. As a result, the goal of this study is to use negative binomial regression models to investigate habitat change as one of the important drivers of biodiversity loss in South and Southeast Asian countries from 2013 to 2018. According to the negative binomial estimates, the findings for the habitat change measures are quantitatively similar for the impacts of agricultural land and arable land on biodiversity threats. Agricultural and arable land both have a positive impact on biodiversity loss. We found that, contrary to our expectations, the forest area appears to have an unexpected direct influence on the number of threatened species. A higher number of threatened species is associated with rising per capita income, human population and a low level of corruption control. Finally, the empirical findings are consistent across taxonomic groups, habitat change measures and Poisson-based specifications. Some policy implications that could mitigate biodiversity loss include educating and promoting good governance among the population and increase the conservation effort to sustain green area and national forest parks in each country.
Asthma is a chronic inflammatory disease primarily characterized by inflammation and reversible bronchoconstriction. It is currently one of the leading causes of morbidity and mortality in the world. Oxidative stress further complicates the pathology of the disease. The current treatment strategies for asthma mainly involve the use of anti-inflammatory agents and bronchodilators. However, long-term usage of such medications is associated with severe adverse effects and complications. Hence, there is an urgent need to develop newer, novel, and safe treatment modalities for the management of asthma. This has therefore prompted further investigations and detailed research to identify and develop novel therapeutic interventions from potent untapped resources. This review focuses on the significance of oxidative stressors that are primarily derived from both mitochondrial and non-mitochondrial sources in initiating the clinical features of asthma. The review also discusses the biological scavenging system of the body and factors that may lead to its malfunction which could result in altered states. Furthermore, the review provides a detailed insight into the therapeutic role of nutraceuticals as an effective strategy to attenuate the deleterious effects of oxidative stress and may be used in the mitigation of the cardinal features of bronchial asthma.