Ecological vulnerability assessment for ecological conservation and environmental management

Modeling the spatial relationship between landscape services and vulnerability assessment

Even though many studies have been thus far devoted to landscape services (LS) or vulnerability assessment (VA) alone, the relationship between these two concepts has been less investigated. The current study attempts to model the spatial relationship between LS and VA in the Tarhan area (west of Iran). For this purpose, a combination of the analytic hierarchy process (AHP), remote sensing (RS), and geographic information system (GIS) techniques are applied to assess vulnerability. Variogram models and geostatistical simulations are used for mapping and evaluating landscape services. Moreover, the geographically weighted regression (GWR) is operated to predict the relationship between LS and VA. The results indicate that landform and socioeconomic variables are also two main factors shaping variations in VA. As well, the levels of services provided in the possible landscape are affected by the vulnerability. The assessment accordingly establishes that natural and cultural values have significant effects on services, in terms of their spatial distribution and nature. Exploring the relationship between LS and VA correspondingly depicts that VA has a direct influence on the capacity and entity of LS provision (adjusted R2 = 0.67). The outcomes of the study provide a foundation for nature management and conservation, although it is less able to analyze the trade-off between ecosystem degradation and future development trends. The nexus of LS and future ecological processes in an integrated system can be thus the subject of further research.

Dynamic evolution and spatial spillover effect of agricultural green development on eight economic regions in China

Promoting the green development of agriculture is of great significance to realize agricultural and rural modernization in China. Based on the existing research, this paper innovatively explores the dynamic and spatial effects of agricultural green development in the eight newly zoned regions of China's economy. Based on the panel data of 30 provinces in China from 2013 to 2022, this paper selects 20 indicators to measure the level of agricultural green development from five dimensions such as ecological protection, resource conservation, environment-friendly, green supply and economic growth by entropy weight method and uses non-parametric estimation method to analyze the dynamic evolution trend of agricultural green development in the whole country and its eight economic regions. Then, a spatial econometric model is constructed to further explore the influence mechanism and spatial spillover effect of each influencing factor on agricultural green development. The findings demonstrate that the level of agricultural green development in 30 provinces of China continuously improved during the study period, but the dynamic evolution trend characteristics in the whole country and its eight economic regions are not the same. Specifically, the development differences between the whole country, the northeast region, the eastern coast, the southern coast and the northwest region increased, while that between the northern coast, the Yellow River basin and the middle reaches of the Yangtze River first increased and then decreased, and that in the southwestern region gradually narrowed. There is a significant spatial spillover effect on agricultural green development and its influencing factors. Moreover, there is heterogeneity in the influence characteristics and spatial spillover effects of various influencing factors on agricultural green development among the eight economic regions. Therefore, it is proposed that eight economic regions in China should formulate differentiated development strategies, focus on educational and technological innovation etc., and further promote agricultural green development.

A review of social-ecological system vulnerability in desertified regions: Assessment, simulation, and sustainable management

Desertified regions face considerable vulnerability due to the combined effects of climate change and human activities, which threaten regional ecological security and societal development. It is therefore necessary to assess, simulate, and manage the vulnerability of desertified regions from the perspective of the social-ecological system, to support desertification control and sustainable development. This study is a systematic review of the vulnerability of the social-ecological system in desertified regions (SESDR) based on a bibliometric analysis, and a summary of the research progresses in vulnerability assessment, simulation, and sustainable management is provided. It was found that SESDR vulnerability research started relatively late, but has developed rapidly in recent years, with an emphasis on the coupling between natural systems and human activities, and multi-scale interactions and dynamics. Using various indicators at different scales, SESDR vulnerability could be assessed in terms of exposure, sensitivity, and adaptability. Modeling the complex interactions among natural and human factors across multiple scales is essential to simulate the vulnerability dynamics of the SESDR. The sustainable management of SESDR vulnerability focuses on rational spatial planning to achieve the maximum benefits, with the right measures in the right places. Four priority research directions were proposed to develop a better understanding of the mechanisms of vulnerability and smart restoration of desertified land. The findings of this study will enable researchers, land managers, and policymakers to develop a more comprehensive understanding of SESDR vulnerability, thereby enabling them to better address the challenges posed by complex resource and environmental issues.

Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions

Ecosystem state transitions can be ecologically devastating or be a restoration success. State transitions are common within aquatic systems worldwide, especially considering human-mediated changes to land use and water use. We created a transferable conceptual framework to enable multiscale assessments of state resilience and early warnings of state transitions that can inform strategic restorations and avoid ecosystem collapse. The conceptual framework integrated machine learning predictions with ecosystem state concepts (e.g., state classification, gradients of vulnerability, and recovery potential leading to state transitions) and was devised to investigate possible environmental drivers. As an application of the framework, we generated prediction probabilities of submersed aquatic vegetation (SAV) presence at nearly 10,000 sites in the Upper Mississippi River (United States). Then, we used an interpretability method to explain model predictions to gain insights into possible environmental drivers and thresholds or linear responses of SAV presence and absence. Model accuracy was 89% without spatial bias. Average water depth, suspended solids, substrate, and distance to nearest SAV were the best predictors and likely environmental drivers of SAV habitat suitability. These environmental drivers exhibited nonlinear, threshold-type responses for SAV. All the results are also presented in an online dashboard to explore results at many spatial scales. The habitat suitability model outputs and prediction explanations from many spatial scales (4 m to 400 km of river reach) can inform research and restoration planning.

Green shared vision: A bridge between responsible leadership and green behavior under individual green values

The pressure on businesses to be environmentally conscious and focus on sustainable development is accruing due to environmental challenges. Companies are adopting ecological practices and policies to improve their environmentally friendly performance. To achieve this, organizations must substantiate and change the behavior of workers to align their behavior with the organization's ecological objectives. The study endeavors to integrate research on the responsible style of leaders and green behaviors of employees (in-role and extra-role green behaviors) through the mediation of green shared vision and analyze the moderation mechanism of individual green values. For collecting the data, a questionnaire-based survey was conducted among MBA executive program students with at least a year of experience in manufacturing. Out of the 450 questionnaires distributed, only 307 useful responses were obtained. The collected data has been analyzed using SPSS and AMOS. Ethical standards were followed, and participants were assured that their responses would be confidential. The study found that responsible leadership positively impacts green behaviors among employees. This means that when leaders within an organization demonstrate responsible and environmentally conscious behavior, it tends to encourage employees to engage in green behaviors. The study also discovered that a "green shared vision" partially mediates the relationship between responsible leadership and in-role green behavior. In contrast, green shared vision does not mediate the relation between responsible leadership and extra role green behavior. Moreover, this study also finds that the relationship between green shared vision and in-role and extra-role green behavior is strengthened when individual green values moderate it. The study highlights the importance of responsible leadership and the role of green shared values and individual green values in promoting environmentally friendly behavior in the workplace.

Public welfare crowdfunding decision-making of environmental nonprofit organizations based on social responsibility

Sustainable crowdfunding has emerged as a significant factor in the quest for alternative funding streams in recent times. The process has entailed the removal of financial obstacles and intermediaries, facilitating proximity between entrepreneurs' initiatives and fund providers, thereby initiating modifications in conventional investment and profitability criteria. The correlation between corporate social responsibility (CSR) and sustainable business returns is a significant metric that may enhance funding costs. CSR initiatives and crowdfunding possess the potential for mutually beneficial outcomes in terms of fundraising. However, fundraisers encounter obstacles and competition in their efforts to attain their donation objectives. As an illustration, CSR endeavors may provide a chance to raise capital via crowdfunding. Conversely, crowdfunding has the potential to serve as a means of micro-funding various social initiatives that align with a corporation's corporate social responsibility objectives. The present research investigates the correlation between efficacious donation fundraising campaigns in the context of crowdfunding endeavors that hold the possibility of transforming into corporate social responsibility initiatives. The present study investigates the correlation between the initial amount of funds raised on the first day of a fundraising campaign and the target amount of funds sought by the fundraiser, as well as the type of activities involved. The present study utilizes data derived from crowdfunding endeavors in Southeast Asian nations to scrutinize the funds amassed through donations by juxtaposing trends, cultures, and characteristics of fundraisers employing donation-based crowdfunding. The present investigation employs data collected between the period spanning from the beginning of September 2021 to the end of September 2021 in the economies of Southeast Asia, including Singapore, Indonesia, Malaysia, Thailand, and the Philippines. The present investigation utilizes the partial least squares structural equation modeling (PLS-SEM) approach for the estimation of the variables. The findings of the hypothesis indicate that there exists a positive correlation between crowdfunding, environmental nonprofit organizations, organizational profitability, and CSR.

The regional difference, dynamic evolution, and multidimensional inequality of China's ecological environment quality from the concept of ecological resilience

Based on the concept of ecological resilience, this paper systematically constructs an evaluation system of ecological environment quality and dynamically measures the ecological environment quality (EQI) and its dimensional oriented indices: environmental pollution production (PPI), environmental pollution management (PMI), and ecological environment restoration (ERI). Then, the dynamic evolution of EQI, PPI, PMI, and ERI could be analyzed by the kernel density estimation and Markov chain, and the multidimensional inequality and its sources of ecological environment quality are studied by Maasoumi index. The main conclusions are as follows: China's EQI shows a tendency of slow growth despite swings. In terms of dimensional-oriented indices, PPI exhibits a slow decreasing trend, and PMI and ERI exhibit an ongoing upward trend. There are showing signs of sustained improvement of EQI across regions, especially in the southwest and northwest. Meanwhile, EQI has the evolutionary characteristics of increasing internal regional synergy and inter-regional differentiation effects. The multidimensional inequality of EQI shows a downward trend first and then an upward trend, and its contribution decreases in turn with "PPI-ERI-PMI." There are obvious differences in the multidimensional inequality of EQI across regions. The intra-regional inequality is absolutely dominant. The marginal contribution of this paper is to construct an evaluation framework of ecological environment quality based on the concept of ecological resilience and to conduct empirical research on China's ecological environment quality, so as to further explain the spatial distribution, evolutionary path, and formation mechanism of China's ecological environment quality.

Research on the interaction of "tourism development-land use-landscape pattern" since the 1990s in a small karst basin, China

The rapid rise of tourism in the karst regions has promoted the development of the local economy by relying on the unique landforms and landscapes. However, tourism development is often accompanied by land use changes and has an impact on the ecological environment. Exploring the coupling relationship between "tourism development-land use-landscape pattern" is very important for ecologically fragile karst areas. Taking the Yulong River Basin as an example, this research applied 3S technology, spatial analysis based on POIs, and regression analysis to the following: (1) identifying the process and effects of land use change, (2) determining the spatial pattern of tourism land and its correlation with land use change, (3) determining the characteristics and impacts of landscape pattern evolution. As the results suggested: (1) The significant expansion of construction land occupies a large amount of farmland, there is a balanced relationship between farmland and forest land for mutual conversion. (2) The aggregation of tourist land is affected by the trend of tourist behavior and the distribution of scenic spots. There is a significant moderate positive correlation between tourism land and construction land. (3) With the land use change, landscape heterogeneity has improved, but landscape fragmentation is serious and landscape connectivity is reduced. This research provides new evidences for the effect of the rapid development of tourism on land use change and ecological environment and as a reference to future orderly and moderate land development and ecological sustainability in karst regions.

Designing a clean environmental framework for Pakistan: analyzing the nonlinear impact of aggregate demand drivers on CO2 emissions

Aggregate demand in every country is one of the main components of macroeconomics, and Pakistan is no exception. This paper uses a fresh econometric framework to analyze the nonlinear impact of aggregate demand drivers on CO₂ emissions in Pakistan by using a nonlinear ARDL approach over the data period from 1975 to 2019. The linear findings reveal that consumption and government expenditure indicates deteriorating effects on carbon emissions in long run in Pakistan. However, nonlinear findings revealed that positive change in government expenditure and trade has positive effects on carbon emissions. The positive change in investment has a negative significant and meaningful effect on the environment in Pakistan and asymmetric findings are also country-specific. Therefore, this study offers a few important policy implications for theorists, academics, and policymakers of Pakistan as well developing economies.

A paleolimnological context of ecological vulnerability for the freshwater ecosystems of Sable Island National Park Reserve, Canada

Protected areas require long-term monitoring to understand the influence and extent of ecosystem stress to inform management and conservation decisions. As long-term data are not always available, paleolimnological methods offer a way of extending our knowledge of past environmental conditions necessary to use as context for remediation. Here, we examine four sediment cores and additional surface sediments from 14 ponds located on Sable Island National Park Reserve Canada (SINPR), where long-term ecological changes and vulnerability to disturbance are not well defined. We develop a paleolimnological approach to assessing environmental vulnerability through the use of biological indicators (Diptera: Chironomidae), where shifts in the environment are inferred by shifts in chironomid assemblages over time. Analysis of surface sediments show four distinct assemblage types reflecting four different habitat conditions; primarily represented by the presence of Glyptotendipes, Chironomus, Microtendipes, and Dicrotendipes. Differences in habitat conditions through time based on these results are then compared to biostratigraphic analysis of sediment cores from four of the ponds. We found that two ponds had large shifts in chironomids assemblages that were associated with changes in habitat over time, while two others that were not as exposed to the influence of erosion and influx of sand dunes did not. Our findings established a baseline of historical change in SINPR, broadening the scope of long-term monitoring, which is essential for defining goals for management and conservation of the ecological integrity of Sable Island.

Landscape Ecological Risk Assessment Based on Land Use Change in the Yellow River Basin of Shaanxi, China

The Yellow River Basin in Shaanxi (YRBS) has a relatively fragile ecological environment, with severe soil erosion and a high incidence of natural and geological disasters. In this study, a river basin landscape ecological risk assessment model was constructed using landscape ecology principles to investigate the temporal and spatial evolution, as well as the spatial autocorrelation characteristics of landscape ecological risks in the YRBS over a 20-year period. The main findings from the YRBS were that the land use types changed significantly over the span of 20 years, there was spatial heterogeneity of the landscape pattern, and the ecological risk value was positively correlated. The threat of landscape ecological risks in YRBS is easing, but the pressure on the ecological environment is considerable. This study provides theoretical support administrative policies for future ecological risk assessment and protection, restoration measures, and control in the Yellow River Basin of Shaanxi Province.

Fuzzy-Based Ecological Vulnerability Assessment Driven by Human Impacts in China

Human activities have a significant impact on global ecosystems. Assessing and quantifying ecological vulnerability is a fundamental challenge in the study of the ecosystem’s capacity to respond to anthropogenic disturbances. However, little research has been conducted on EVA’s existing fuzzy uncertainties. In this paper, an ecological vulnerability assessment (EVA) framework that integrated the Exposure-Sensitivity-Adaptive Capacity (ESC) framework, fuzzy method, and multiple-criteria decision analysis (MCDA), and took into account human impacts, was developed to address the uncertainties in the assessment process. For the first time, we conducted a provincial-scale case study in China to illustrate our proposed methodology. Our findings imply that China’s ecological vulnerability is spatially heterogeneous due to regional differences in exposure, sensitivity, and adaptive capacity indices. The results of our ecological vulnerability assessment and cause analysis can provide guidance for further decision-making and facilitate the protection of ecological quality over the medium to long term. The developed EVA framework can also be duplicated at multiple spatial and temporal dimensions utilizing context-specific datasets to assist environmental managers in making informed decisions.

Decomposing the asymmetric effects of terrorism and FDI on carbon emission: evidence from fragile economies

Terrorism is a universal phenomenon that creates economic, political, social, and environmental problems. The literature infers that little consideration is delivered to the nexus of terrorism and pollution emissions. To the best of the authors' knowledge, this study is a pioneer that investigates the linear/symmetric and non-linear/asymmetric impacts of foreign direct investment and terrorism on the CO₂ emissions for ten fragile economies. For the empirical task, the study collected data for time 1973 to 2019 and employed ARDL and NARDL approaches. The findings demonstrate an asymmetric association between foreign direct investment (FDI), terrorism, and CO₂ emissions. The findings infer that positive changes in FDI and terrorism have a significant positive impact on CO₂ emissions. However, the negative changes in FDI and terrorism significantly impact CO₂ emissions in most economies. Furthermore, the NARDL approach delivers more explanatory and powerful estimates for selected countries in contrast to the ARDL approach. On the basis of these findings, the study delivers some appropriate policies to combat terrorism.

An improved method of assessing marine utilization impact to describe the man-land relationship for coastal management: a case study of the Laizhou Bay, China

Understanding the level of human impact on the marine environment requires integrated and ecosystem-based assessment. This research proposes a method based on geospatial modeling at the activity level to assess the potential impact of marine utilization on coastal management and conservation. Laizhou Bay in China was selected as a case study. The research identified the spatial distribution of economic sectors and the potential impact of that distribution on important marine ecological management zones. The findings reveal that, from high to low, threats exist in the bay-head, and to the east and west, and that marine ecological zones are over-used for open mariculture because the environmental impact of this activity is believed to be low. This paper reveals the spatial distribution of threats from a variety of marine-area uses on the ecology of Laizhou Bay. The findings provide support for policymakers in the implementation of marine ecological red-line policy and in the management of the utilization of the marine environment.

Spatio-Temporal Characteristics and Influencing Factors of Ecological Risk in China’s North–South Transition Zone

Ecological risks (ERs) are external threats to ecosystem structure and function, and the evaluation of ER is valuable for understanding the extent of the disturbance of ecosystems by human activities. An objective investigation of the spatio-temporal characteristics of ER and its affecting elements can contribute to the improvement of the ecological environment and the sustainable development of regional resources. The Funiu Mountains were chosen as the study area, the ecological risk index was built using landscape interference and landscape separation, and the spatial–temporal properties and scale effect of the ER were assessed. The findings of ER may be separated into four distinct zones to study the variations in ER levels from 2000 to 2015: modest, mild, moderate, and high. Furthermore, geographically weighted regression (GWR) was used to ascertain the degree to which environmental factors impact ER and regional disparities. The results show: (1) Ecological risk assessment was sensitive to scale transformation, and there are variations in the spatial pattern of ER on diverse scale units. With the scale following a 1 km grid to the watershed, Global Moran’s I values dropped from 0.53 to 0.04, and 1 km × 1 km was the most suitable unit. (2) The ecological and environmental quality of the Funiu Mountains improved from 2000 to 2015. The extent of the high ecological risk zone dropped by 398.07 km2, but other types of ecological risk regions rose, owing to the execution of policies aimed at restoring cropland to forests. The ER presented a transitional distribution from a high risk in the surrounding area to low risk in the central area. (3) From the perspective of correlations among the influencing factors, altitude and slope had a negative correlation with other influencing factors, while others were positively correlated. The correlation coefficient between land-use degree and human activities intensity and ER was the highest. Each environmental factor had significant effects on the ERs and spatial variation existed, where the land-use degree and human activities intensity were the main obstacle factors limiting ER improvement. Population density, altitude, slope, and maximum temperature all displayed effects on ER with different directions and intensities.

Spatiotemporal Variations in Grassland Vulnerability on the Qinghai-Tibet Plateau Based on a Comprehensive Framework

Grasslands are globally important for providing essential ecosystem services and maintaining ecological security. Monitoring and assessing grassland vulnerability are critical for developing long-term grassland management policies and strategies. The grassland vulnerability on the Qinghai-Tibet Plateau (QTP) is considered high, but its spatial and temporal variations in response to human activities and climate change are not well understood. In this study, a comprehensive grassland vulnerability index (GVI), which includes natural factors (VNF), environmental disturbances (VED), and socioeconomic impacts (VSI), was developed by using the analytic hierarchy process (AHP), principal component analysis (PCA), and environmental vulnerability distance index (EVDI). Our results showed that the spatial distribution of GVI had obvious heterogeneity, decreasing from northwest to southeast; the regions with serious and extreme vulnerability were mainly concentrated in the north-western alpine steppe and desert steppe. From 2000 to 2018, GVI decreased from 0.61 in 2000 to 0.60 in 2010 and then to 0.59 in 2018, demonstrating a healthy tendency. The normalized difference vegetation index (NDVI), land desertification, and population were the factors that had the most significant impact on VNF, VED, and VSI, respectively. The global Moran’s I index of grassland vulnerability was greater than 0, with a significant positive spatial correlation. The number of High-High and Low-Low units decreased, indicating that the High-High and Low-Low cluster regions tended to be discrete. Moreover, our results suggest that understanding the variations in grassland vulnerability on the QTP is important for regional sustainable development in the context of intensified climate change and human disturbances.

A Comparison of Multi-Criteria Decision Analysis Methods for Sustainability Assessment of District Heating Systems

The sustainability of energy systems is increasingly assessed for development of more resilient, greener district heating (DH) systems. That requires compiling technological, environmental, and economic indicators in a social, political, and institutional context. This work investigates DH system sustainability analysis by five frequently applied multi-criteria decision analysis (MCDA) methods—WSM, TOPSIS, PROMETHEE, ELECTRE and DEA. To compare the sustainability assessment results, a selection of 8 criteria describing 12 DH companies (DHC) was examined. Sensitivity analysis was performed to determine the most credible MCDA method. Criteria weights were changed: (1) individually for evaluation of the range of stability for alternatives (score of DHC performance); (2) individually by a fixed value to compare how each criterion weight change affected the average score of a result; and (3) to compare the AHP weighting method to an equal weight scenario. The results of sensitivity analysis along with literature investigation shows that all methods are suitable for sustainability analyses of DH systems while also having differences in the calculation process and in the interpretation of results. The generalized algorithm for sustainability analysis in the energy sector outlined in this study along with the documented features of the main MCDA methods can be used as a guide for future assessment of energy systems by researchers and industry professionals.

Industry 4.0 and Digitalisation in Healthcare

Industry 4.0 in healthcare involves use of a wide range of modern technologies including digitisation, artificial intelligence, user response data (ergonomics), human psychology, the Internet of Things, machine learning, big data mining, and augmented reality to name a few. The healthcare industry is undergoing a paradigm shift thanks to Industry 4.0, which provides better user comfort through proactive intervention in early detection and treatment of various diseases. The sector is now ready to make its next move towards Industry 5.0, but certain aspects that motivated this review paper need further consideration. As a fruitful outcome of this review, we surveyed modern trends in this arena of research and summarised the intricacies of new features to guide and prepare the sector for an Industry 5.0-ready healthcare system.

Frequency and geospatial vulnerability indices of rainfall and temperature extremes in the Jimma Zone, Ethiopia

Climate extremes are becoming more prevalent and hazardous as global climate change increases. The purpose of this study was to find out how often severe rainfall and temperature events occur, as well as the study area's spatial vulnerability indexes to extremes of both indices. Thirty years of daily rainfall and temperature data from 10 national meteorological stations were used. Four rainfall and eight temperature extremes were extracted using Climpact2 software tools. These variables were calculated for standardized anomaly and vulnerability indices and mapped using ArcMap. The results showed that the spatial variation of climatic extremes in the study area was significantly varied. Avery high rainfall (R95P) and extremely high rainfall (R99P) were widely experienced in the study area's west-south, but in the southeast, similar trends were rare. R95P had a statistically significant growing trend, but R99P did not. The warmest night temperature (TNx) event was widely observed in the east, southeast, and northwest, but the coldest night temperature (TNn) was only found in the eastern part. Extremely cold daytime temperatures (TXn) were more prevalent in the south and southeast of the study area, whereas extremely warm daytime temperatures (TXx) were more prevalent in the north. The number of dry spells (CDD), R95P, R99P, cold spells at night (TN10P), warm spells at night (TN90P), cold spells during the day (TX10P), and warm spells during the day (TX10P) frequency bell curves were skewed to the left side of the histogram. This suggests that the distribution of the variables was not symmetrical due to the fact that the negative anomaly frequencies of the variables were higher than the positive ones. The results of the spatial vulnerability study show that all provinces were vulnerable to the combined effects of climatic extremes, with scores ranging from 0.20 to 0.8, with none of them vulnerable and extremely vulnerable areas. Omo-Nada and Chora-Botor were particularly sensitive to climate change with an average score of 0.61. Only 12 of the 27 severe climate indexes were taken into account in this study, and the remaining 15 extreme indices will have to be investigated further.

Construction and evaluation of a system to measure the coordinated development of the ecological environment and the economy of the construction industry

Based on the core concept of coordinated development of ecological environment and economy, the five-dimensional evaluation indexes including scale expansion, sustained growth, innovation development, green development and open development are constructed. In this paper, the combined weight model of CRITIC-entropy weight method TOPSIS model are used to comprehensively evaluate the coordinated development of ecological environment and economy of construction industry in China's provinces, municipalities and autonomous regions (except Xizang, Hong Kong, Macao and Taiwan) from 2004 to 2017. The results show that: (1) Open development and innovative development are the main factors affecting the coordinated development of ecological environment and economy of construction industry. (2) From 2004 to 2017, the coordinated development level of ecological environment and economy of construction industry in 30 provinces, municipalities and autonomous regions in China has a growing trend. However, at present, the level of coordinated development of the ecological environment and the economy of the construction industry in China is generally low. (3) The level of coordinated development between ecological environment and economy of construction industry in eastern China, northeast China, central China and western China is obviously different, showing a spatial distribution pattern of "the level of development from east to west". On this basis, corresponding policy suggestions are put forward in order to provide reference for promoting the coordinated development of ecological environment and economy in China's construction industry.

An overview of ecological vulnerability: a bibliometric analysis based on the Web of Science database

Ecological vulnerability has become one of the hot issues of ecology and environmental science under global change and sustainable development scenarios. However, no study quantitatively analyzes the global scientific performance and hot research areas in this field by adopting the bibliometric method. Based on 935 pieces of literature retrieved from the Web of Science database, we comprehensively analyzed the research on ecological vulnerability in terms of growth trend, research content, publication journal and country, and co-occurrence network of keywords. The results showed that research on ecological vulnerability had experienced rapid growth since 2000, while ecological vulnerability research at the World Heritage sites was still embryonic. The top two productive countries in ecological vulnerability research were America and China, and the top two productive journals were Ecological Indicators and Regional Environmental Change. Study on ecological vulnerability was mainly classified as empirical evaluation and regional synthesis, whereas theoretical research is rare. Based on the summary of the main progress and achievements in ecological vulnerability research, we proposed five scientific issues that remain to be resolved in the field of ecological vulnerability. Overall, this study could shed light on a comprehensive and systematic understanding of ecological vulnerability and provide directions for future research on ecological vulnerability in a rapidly changing world.

Caring for the environment: measuring the dynamic impact of remittances and FDI on CO2 emissions in China

Various old nexuses are getting new empirical attention in advanced econometric. Therefore, we examine the asymmetric influence of remittances and FDI on CO2 emissions by using the NARDL approach for China from 1981 to 2019. Based on NARDL empirical findings, a negative change in remittances has also positive effects on CO2 emissions in the short and long run. We found that positive and negative change in FDI has also a positive effect on CO2 emissions, while a positive change in FDI is relatively more effective on CO2 emissions than a negative change in FDI in long run. Asymmetry is observed in the only magnitude but not in direction. Our study implies that the China government should redesign the environmentally friendly policies and enforces the foreign investors to role play in environmental quality.

Will the economic growth benefit public health? Health vulnerability, urbanization and COVID-19 in the USA

Economic growth has a significant impact on health vulnerability primarily through the process of urbanization. This paper conducts a pioneer study by analyzing the impact of regional economic growth and urbanization on the public health vulnerability in the 51 states and territories of the USA from 2011 to 2018 with a fixed-effect panel data regression model. We construct an epidemiological vulnerability index (EVI) using regional smoking, diabetes, obesity, and hypertension, collect CDC social vulnerability index (SVI) as state-level public health vulnerability status, and use COVID-19 to test the actual effect of health vulnerability. The preliminary results show that higher regional economic growth is related to lower EVI and SVI, while urbanization is positively associated with regional health vulnerability and the severity of COVID-19 from case rate and death rate. Robustness check with unemployment shows the same result. We conclude that economic growth is related to lower public health vulnerability, and urbanization has negative public health benefits. Our finding indicates an urgent need to balance the externalities generated by economic development and urbanization trends on public health vulnerability by promoting reasonable medical resource distribution, health practices and safety, improving social and environmental justice, and other health management measures.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00168-021-01103-9.

Assessment of sustainability and uncertainties of oil markets: mediating determinants of energy use and CO2 emissions

The current paper investigates the sustainability growth problem in the USA and evaluating the co-integration relationship among all variables, including oil, carbon emission, and consumption of energy. We also determine the impacts of energy consumption on the USA economic growth, government spending, and trade openness. We used the co-integration and popular lag model (ARDL) to find the long-term and short-term relationships between all study variables. The empirical results show that (1) the crude oil prices increase and adverse impact on energy demand and government expenditure during the study periods, and CO₂ emission negatively affects USA economic growth. In addition, (2) the innovative accounting method (ICA) results, we used further research to research the causality between study variables. The empirical results propose that oil prices affect the country's economy responsible for more energy consumption, and the causal effect between consumption of energy and economic growth is not relevant. Wastage of energy allows the system to produce more CO₂ emissions. Model results find that the one-sided causal effects of economic growth and CO₂. We see during the analyses that (CO₂) emissions will negatively impact the country's economy. Therefore, country policymakers are expected to change fossil fuel energy to non-fossil fuel energy as an essential component of the USA's economic growth policies.

Financing for energy efficiency solutions to mitigate opportunity cost of coal consumption: An empirical analysis of Chinese industries

This study measures the energy rebound effects of Chinese energy and coal power use in Chinese energy-intensive industries by using latent class stochastic frontier models like LMDI, and other various econometric estimation approach for coal-supplying regions in China ranging between 1992 and 2018. The findings reveals that China's coal sector's average capacity consumption is 0.81%, with a pattern of first increasing and then decreasing, falling to 0.68% in 2016 specifically. The coal capacity operation rate concerning low as well as depleted regions is generally strong, with limited space for expansion. In 2015 and 2016, the utilization rate of coal production potential in moderate-producing areas fell about 42%. Economic development variables affect the capacity utilization levels of moderate, weak, and depleted generating regions. At the same time, the price volatility cannot induce a practical improvement in the ability utilization rate, which means that China's coal industry is mainly un-marketized. China's energy efficiency increased about 19.98% among 2000 and 2016, while the rapidest expansion pattern has been noted in the eastern province at 39.86%, next to central (11.71%) and western regions (9.59%). The take back impact via the renewable energy and renewable productivity channels is estimated as 12.34% and 25.40%, respectively. Therefore, the take back impact is of significant importance regarding energy preservation, as China's cumulative renewable energy use is equal to China's aggregate energy use. On such findings, recent research also contributed by presenting novel policy implications for key stakeholders.

The asymmetric effects of renewable energy consumption and trade openness on carbon emissions in Sweden: new evidence from quantile-on-quantile regression approach

With the passage of time, the continued burning of fossil fuels is proving to be one of the world's most serious issues. In response, the current research aims to assess the critical linkage between carbon emissions and renewable energy, trade openness, and economic growth in Sweden utilizing a dataset from 1965 to 2019. The study applied the novel quantile-on-quantile regression (QQ) approach to assess this relationship. The main objectives are to address the following questions: (i) What are the effects of trade openness on CO2 emissions in each quantile? (ii) Does renewable energy consumption mitigates CO2 emissions in each quantile? What is the impact of economic growth on CO2 emissions in each quantile? The outcomes from the QQ approach revealed that at low and medium quantiles (0.1-0.6), the effect of trade openness on CO2 emissions is negative. Furthermore, at lower and higher quantiles (0.1-0.90) of combination of renewable energy consumption and CO2 emissions, the effect of renewable energy consumption on CO2 emissions is negative. Finally, at majority of the quantiles, the effect of economic growth on CO2 emissions is negative. Moreover, the present study applied the quantile regression (QR) approach as a robustness check. The findings of the QR validate the findings of the QQR approach. The study proposes that policy-makers in Sweden should place greater emphasis on raising public awareness regarding the issues of renewable energy since it mitigates environmental degradation.

Dynamic effects of fiscal and monetary policy instruments on environmental pollution in ASEAN

This study aims to re-examine the impacts of monetary and fiscal policy on environmental quality in ASEAN countries from 1990 to 2019. We utilized the panel and time series NARDL approach to explore the long-run and short-run estimates at a regional level and country level. ASEAN regional-wise analysis shows that contractionary monetary policy reduces the CO2 emissions, while expansionary monetary policy enhances CO2 emissions in the long run. The long-run coefficient further confirms that expansionary fiscal policy mitigates CO2 emissions in ASEAN. The impact of expansionary monetary and fiscal policy on CO2 emissions is positive and significant, while contractionary monetary and fiscal policy have an insignificant impact on CO2 emissions in the short run. ASEAN country-wise analysis also reported the country-specific estimates for the short and long run. Some policies can redesign in light of these novel findings in ASEAN economies.

Environmental cost of sustainable development and climate change: can SAARC shift some liability with renewable energy and efficiency?

Sustainable development holds the key not to resolve the problems every nation is facing these days but also for long-lasting effects. In the current era of digital age, each nation wants to achieve sustainable development for their future generations. In addition, environmental sustainability is an imperative module to achieve sustainable development. Hence, the present research work scrutinizes the energy efficiency, CO₂ emission, and renewable energy on the sustainable development of SAARC countries through World Bank sample set from 1995 to 2019. The results infer that CO₂ emissions, renewable energy, energy efficiency, GDP, and FDI show a strong correlation with sustainable development in SAARC counties. Furthermore, renewable energy and energy efficiency have been shown to be reliable instruments for reducing CO₂ emissions and achieving sustainable development in SAARC countries. This research will help policymakers take preventative and constructive actions to achieve sustainable development by reducing CO₂ emissions and uplifting the drivers of sustainable development.

The asymmetric associations between foreign direct investment inflows, terrorism, CO2 emissions, and economic growth: a tale of two shocks

Foreign direct investments can exert ambiguous effects on the environmental quality of the host economies. At the same time, terrorism is a worldwide phenomenon that affects human life, FDI inflows, economic growth, and, most importantly, environmental well-being. Hence, it can be expected that there are relationships between terrorism, foreign direct investment inflows, and carbon dioxide emissions. However, in the previous literature, less attention has been given to explore these nexuses. In addition, the possible non-linearities in data are also mostly ignored in the preceding related studies. Against this backdrop, this paper explores the linear and non-linear influences of terrorism and foreign direct investment inflows on carbon dioxide emissions, controlling for energy consumption and economic growth within the model, on carbon dioxide emissions in the context of ten global economies that are most impacted by terrorism. To this end, we used the data from 1973 to 2016 and deployed the linear and non-linear autoregressive distributed lag methods to scrutinize the environmental impacts of the explanatory variables of concern. The results confirmed the presence of non-linearities in the relationships between terrorism, inflows of foreign direct investments, and carbon dioxide emissions. Furthermore, the findings revealed that the positive shocks to terrorism and foreign direct investment inflows significantly deteriorate the environment with a dominating effect. Unlike the previous studies, this current study validates the pollution haven hypothesis for the sample economies. Energy consumption and economic growth  were also evidenced to exacerbate the carbon dioxide emission levels in all selected countries. Based on these results, we recommend that our sample economies should focus on promoting education, employment, economic stability, and public awareness to eradicate terrorism which, in turn, can mitigate the emissions of carbon dioxide further. In addition, stringent environmental regulations on foreign direct investment inflows are required to reduce the adverse environmental effects of such sources of foreign finance. Furthermore, the international firms should be encouraged to invest in cleaner technologies by offering them tax benefits and other financial incentives.

A review study on new aspects of biodemulsifiers: Production, features and their application in wastewater treatment

The effluent produced in refineries is in the form of an oil/water emulsion that must be treated. These emulsions are often stable and a suitable method must be used to separate the oil from the emulsion. Recently, biosurfactants or biodemulsifiers have received much attention to reduce the interfacial tension between two liquids. Biodemulsifiers are produced by microorganisms and have several benefits over chemical demulsifiers such as low-toxic, biodegradability, eco-friendly and easy synthesis. They can eliminate two phases by changing the interfacial forces between the water and oil molecules. Biosurfactants are categorized based on the molecular weight of their compounds (low or high molecular weight). Sophorolipids, lipopeptides rhamnolipids, trehalolipids, glycolipid, lipoproteins, lichenysin, surfactin, and polymeric biosurfactants are several types of biosurfactants, which are produced by bacteria or fungi. This review study provides a deep evaluation of biosurfactants in the demulsification process. To this end, different types of biosurfactants, the synthesis method of various biosurfactants using various microorganisms, features of biosurfactants, and the role of biodemulsifiers in the demulsification process are thoroughly discussed. Also, the impact of various efficient factors like pH, microorganism type, temperature, the oil content in the emulsion, and gravity on biodemulsificaion was studied. Finally, the mechanism of the demulsification process was discussed. According to previous studies, rhamnolipid biodemulsifier showed the highest biodemulsification efficiency (100%) in the removal of oil from an emulsion.

Does digitalization matter in green preferences in nexus of output volatility and environmental quality?

The fact is that output volatility and carbon dioxide (CO2) emissions move together over the period. This empirical study examines the dynamic effect of output volatility on CO2 emissions using the advance nonlinear panel autoregressive distributed lag (ARDL) approach. The empirical analysis is executed for ten high emitters Asian countries covering the period from 1990 to 2019. The findings reveal that positive change in output volatility increases CO2 emissions and negative change in output volatility decreases CO2 emissions in the long run in Asia. The results also show that digitization also positively impacts environmental quality in Asia due to green globalization. The findings are also robust and similar in an alternative indicator of the environment. An important policy is that reducing volatility in output is a suitable way of environmental sustainability, particularly for Asian countries.

Assessing the nexus between financial development and energy finance through demand- and supply-oriented physical disruption in crude oil

Since 1970, numerous governments have established strategic petroleum reserves (SPRs) in relation to oil supply interruptions. In this study, important oil reserves, physical oil supply disruption and social welfare losses due to physical distribution of oil supply have been measured. The physical oil supply disruption has been measured in the form of oil supply vulnerability index and oil volatility index of the South Asian economies. Analysis reveals that the accumulation and drawdown of important national crude oil strategic petroleum reserves where the state wants to optimize individual social welfare while individuals hold over stock optimize their earnings levels. The monetary deciding factors utilize the government's optimum important stockpile policy and simultaneously the amount and economic factors vital for the nongovernment market to actuate the optimum accumulation and nonaccumulation of important fossil fuels stockpile. Additionally, findings show that India is the lowest crude oil insecure country while Afghanistan and Bangladesh are the highest insecure countries in terms of oil supply. India's topmost mark shows a bigger possibility to alter the fossil fuels producers while Afghanistan, Bangladesh, Bhutan and Nepal have the minimum mark corroborating the group as the utmost producer risk exposed nations.

Assessing Ecological Vulnerability under Climate Change and Anthropogenic Influence in the Yangtze River Estuarine Island-Chongming Island, China

Understanding and assessing ecological vulnerability for estuarine islands are important for maintaining estuarine island ecosystem services and its sustainable development. However, due to its complex fresh water-sea-land interaction mechanism and multiple stressors from both climate change and anthropogenic influence, a comprehensive evaluation of ecological vulnerability for estuarine islands has been limited. Therefore, taking the typical estuary island of Chongming Island as an example, we developed a comprehensive evaluation system of ecological vulnerability for an estuarine island ecosystem based on the pressure-state-response (PSR) conceptual model, and explored the spatial and temporal distribution of ecological vulnerability in 2005 and 2015. The results indicated that the main pressures of Chongming Island from saltwater intrusion intensity and land use intensity were mainly distributed in northern coastal areas and eastern areas of wetland; the ecological vulnerability index (EV) of Chongming Island showed a slight decrease from 2005 to 2015; and three categories of towns based on ecological vulnerability assessment for an eco-island planning and environmental management were identified. Our study provides an effective evaluation system of ecological vulnerability for estuarine islands, which could be helpful for planners and decision makers in improving eco-island planning and environmental management.

The environmental sustainability effects of financial development and urbanization in Latin American countries

The present study assesses the impact of urbanization, economic growth, energy consumption, and financial development on CO₂ emissions in Latin American countries using a dataset spanning between 1980 and 2017. The current paper employs utilized panel econometric techniques such as CIDF, panel unit test, the Westerlund panel cointegration, fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and Dumitrescu Hurlin panel causality test to assess these associations. The outcomes from the FMOLS and DOLS estimation reveal that (i) economic growth impacts CO₂ emissions positively, (ii) energy consumption exerts a positive impact on CO₂ emissions, and (iii) urbanization impacts CO₂ emissions positively. Furthermore, the outcomes of the causality test reveal that energy consumption and economic growth can predict CO₂ emissions in Latin countries. The findings highlight the importance of policymakers actively coordinating strategies to address Latin America's severe environmental degradation.

Assessment of the role of trade and renewable energy consumption on consumption-based carbon emissions: evidence from the MINT economies

This research formulates a theoretical framework to investigate the impacts of trade on consumption-based carbon emissions (CCO₂) and also takes into account the influence of financial development and renewable energy use utilizing panel data for Mexico, Indonesia, Nigeria, and Turkey (MINT) nations between 1990 and 2017. The study utilizes a series of second-generation techniques such as Westerlund cointegration, cross-sectional augmented autoregressive distributed lag (CS-ARDL), and augmented mean group (AMG) tests to capture the linkage between CCO₂ emissions and the independent variables. The study aims to answer the following questions: (a) can exports and imports determine CCO₂ emissions in the MINT nations? (b) Is there a long-run association among the variables under investigation? The results of the Westerlund cointegration reveal a long-run association among the variables. The CS-ARDL outcomes indicate that imports and economic growth increase CCO₂ emissions, while renewable energy use and exports decrease CCO₂ emissions. Moreover, the outcomes of the AMG test also give credence to the CS-ARDL results. Our key policy recommendations are that initiatives, rules, and regulatory mechanisms should be implemented that promote the transformation toward renewable energy.

Linking financial development, economic growth, and ecological footprint: what is the role of technological innovation?

The literature analyzing the ecological impacts of financial development (FD) documents mixed results. In addition, very limited researches consider the role of technological innovation in ecological sustainability even though technological innovation is indispensable to achieve technological advancement, which may help in sustainable development and ecological sustainability. Therefore, this work probes the effects of technological innovation, financial development, and economic growth (GDP) on the ecological footprint (EF) controlling urbanization and employing a STIRPAT framework. The analysis of data from West Asia and Middle East nations from 1990 to 2017 revealed cointegration in the model. The long-run coefficients produced by the continuously updated fully modified technique revealed that a 1% upsurge in technological innovation decreases EF by 0.010%. Interestingly, technological innovation is helpful to decrease EF and enhance economic growth in the West Asia and Middle East (WAME) countries. However, a 1% rise in FD boosts the level of EF by 0.0016% inferring that FD stimulates ecological degradation. Likewise, urbanization in the WAME countries raises EF levels and contributes adversely to ecological quality. In addition to this, the study revealed the environmental Kuznets curve hypothesis in the selected countries accounting for technological innovation, FD, and urbanization in the model. The causal analysis provided evidence of unidirectional causality from FD to EF and bidirectional causality between technological innovation and EF. The study recommends more investment in research and development and strong collaboration between the universities and industries to promote the level of technological innovation for both sustainable development and ecological sustainability. In addition, urban sustainability policies are necessary without decreasing the urbanization level.

Stock markets dynamics and environmental pollution: emerging issues and policy options in Asia

The fact is the stock market has an asymmetric effect on macroeconomic variables. In this study, we examine the nonlinear stock market reaction to the environment. This is the first study that considers the possibility of asymmetric effects of stock market on environmental pollution in Asia. This study considers the experiences of Asia economies by using the panel NARDL methodology over the data period from 1995 to 2019. The long-run panel NARDL results showed that the positive change in stock market increases carbon emissions. In adverse, the negative change in stock market significantly mitigates the carbon emissions in Asia. The short-run stock market asymmetric effects continued into the long-run asymmetric effects on the environment in Asia. Thus, policymakers and authorities should initiate to promote green financial activities in Asian stock markets.

Effects of land use transition on ecological vulnerability in poverty-stricken mountainous areas of China: A complex network approach

Poverty-stricken mountainous areas are often subject to ecological vulnerability, and land use transition is a major factor affecting that vulnerability. Land use transition forms a complex network comprised of different land use types which interact with each other and respond to external environment processes, resulting in dynamics. This study develops complex network approach with cascade failure model to quantitatively explore the effects of land use transition on ecological vulnerability from the holistic and dynamic perspective. The study analyzes the characteristics of land use transition, identifying key transition types and simulating their impact on ecological vulnerability in 16 poverty-stricken mountainous counties in western Hubei Province, China, with the following findings. (1) The heterogeneity of change in agricultural land and construction land is significant; from 1990 to 2015, a short-term increase in the amount of agricultural land is followed by a gradual reduction, while the amount of construction land increased continuously. (2) Agricultural land is the dominant output land type, exported mainly to construction land and water area, and construction land is the dominant input land type, imported mainly from agricultural land. Sparse woods, woods, and dryland are the key land use types in the study area. (3) the critical points for maintaining resilience of ecosystem are 80% or higher for cultivated land and 80% or higher for woodland. (4) For the tolerance parameter α, 20% increase in cultivated land and a 10% increase in woodland would enhance ecosystem resilience and reduce its damage degree to corresponding land use transition. These findings are important points of reference for the sustainable management of poverty-stricken mountainous counties in western Hubei Province and in China more generally. They also have policy implications for land resources, especially in terms of the alleviation of poverty and the coordination between ecological protection and economic development.

How energy insecurity leads to energy poverty? Do environmental consideration and climate change concerns matters

The aim of the study is to estimate the nexus between energy insecurity and energy poverty with the role of climate change and other environmental concerns. We used DEA like WP methods and properties of MCDA, a most common form of data envelopment analysis (DEA) to estimate the nexus between constructs. This paper presents a measurement and analysis of G7 countries' energy, economic, social, and environmental performance associated with energy poverty indexes. The study used the multiple, comprehensive, and relevant set of indicators, including energy economics and environmental consideration of energy poverty. The net energy consumption of al G7 economies is equal to 34 percent of the entire world along with the net estimate GDP score of around 50 percent. Using DEA modelling and estimation technique, our research presented valuable insights for readers, theorists and policy makers on energy, environment, energy poverty and climate change mitigation. For this reasons, all these indicators combined in a mathematical composite indicator to measure energy, economic, social, and environmental performance index (EPI). Results show that Canada has the highest EPII score, which shows that Canada's capacity to deal with energy self-sufficiency, economic development, and environmental performance is greater than the other G7 countries. France and Italy rank second and third. Japan comes next with 0.50 EPI scores, while the USA has the lowest average EPI score environment vulnerable even though have higher economic development among the G7 group countries. We suggest a policy framework to strengthen the subject matter of the study.

Evaluating green innovation and performance of financial development: mediating concerns of environmental regulation

This research measures the relationship between green innovation and the performance of financial development by using an econometric estimation during the year of 2000 to 2018 in 28 Chinese provinces. It is intended to explore the relative role of green technological innovation in driving green financial development in the west and central China, as well as how it influences economic growth in these regions. Ordinary least square (OLS) framework was utilized in mainland China to perform empirical studies by using an econometric estimation. This study claims that China has adopted research-based education system, while those for economic growth and expenditure in the regions while the innovation parts results shows that the  tertiary education were 12.42% and 13.53% versus the 10.50% and 10.6% in the eastern area. The research-based education increases the patents in green innovation and boosts the environmental policy. The financial development led to green technological development and innovation. Green innovation and financial development decrease the emissions, and it is apparent that as environmental regulations stimulate technical development, the superiority of human resources increases. The findings indicate that green financing reduces short-term lending, thus limiting clean energy overinvestment, while the long-term loans have little impact on renewable energy overinvestment, and the intermediary effect is unmaintainable. Meanwhile, the green financial growth will reduce renewable energy overinvestment and increase renewable energy investment productivity to certain amount.

Non-oil economic transition for economic and environmental sustainability in Saudi Arabia: a multi-factor analysis under fuzzy environment

In this study, an analysis of Saudi Arabia's economic diversification, particularly non-oil transition, is conducted. Initially, key success factors and sub-factors that provide basis for the analysis are identified through literature survey. Three key factors (economic, labor, and market), twenty-one sub-factors (seven under each factor) are identified. To obtain the relative importance of factors and sub-factors, fuzzy analytical hierarchy process (FAHP) has been used. The economic criterion obtained the highest weight followed respectively by fiscal and labor criteria. The "proportion of Saudis in the workforce" sub-criterion received the highest weight under labor criterion, the "investment-intensive business models" sub-criterion obtained the highest weight under economic criterion, and the "increase non-oil revenue" sub-criterion got the highest weight under fiscal criterion. Overall, increase non-oil revenue sub-criterion (under fiscal criterion) received the highest weight. Later, eight major non-oil sectors are prioritized with respect to criteria and sub-criteria using fuzzy technique for order preference by similarity to the ideal solution. Petrochemicals sector ranked topped in the contribution to achieving non-oil transition. The findings of the study shall enable the government and policymakers to specifically design policies for respective sectors knowing their importance in the transition and subsequently bring a new cycle of prosperity to the Kingdom of Saudi Arabia.

Analysis of income inequality and environmental pollution in BRICS using fresh asymmetric approach

With rapid economic growth, BRICS is facing enormous burdens of carbon emission and severe issues of income inequality. However, behind this economic success, the BRICS economies also face few thoughtful challenges to improve environmental quality by catching up the sustainable development goals. Consequently, the existing empirical research is concerned with the dynamic links between income inequality and CO₂ emissions by using the novel nonlinear ARDL approach, but small attention has been paid to the BRICS in literature. Therefore, we observed that a negative and positive change in income inequality has positive effect on CO₂ emissions in Russia and South Africa in the long run, although a positive change in income inequality has positive effects on CO₂ emissions in Brazil, Russia, and China, while a negative change in income inequality has negative effect on CO₂ emissions in India, Brazil, and Russia in the short run. Hence, the findings value specific attention from policymakers in BRICS economies.

A Long-Term Ecological Vulnerability Analysis of the Tibetan Region of Natural Conditions and Ecological Protection Programs

The combined impacts of drastic natural environment change and increasing human interference are making the uncertainty of the Tibetan Plateau’s ecological vulnerability the world’s largest. In this study, an ecological vulnerability index (EVI) of Tibet in the core area of the Tibetan Plateau was assessed using a selected set of ecological, social, and economic indicators and using a spatial principal component analysis (SPCA) to calculate their weights. The data included Landsat images and socio-economic data from 1990 to 2015 in five-year intervals. The results showed that the total EVI remained at a high vulnerability level, with drastic fluctuation from 1990 to 2000 (a peak in 1995, when there was a sudden increase in light vulnerability, which moved to extreme vulnerability in the next period), and minor fluctuations after 2000, gradually increasing from southeast to northwest. In addition, the spatial analysis showed a distinct positive correlation between the EVI and grassland area (0.33), land use degree (0.15), NDVI (0.14), livestock husbandry output, and a negative correlation in terms of desertification area. The artificial afforestation program (AAP) had a positive significant correlation with NDVI (R2 = 0.88), preventing the environment from becoming more vulnerable. The results provide practical information and suggestions for planners to improve the land use degree in urban areas and the vegetation coverage in pastoral regions of the Tibetan Plateau based on the spatial–temporal heterogeneity patterns of the EVI of Tibet.

Wetland Restoration Planning Approach Based on Interval Fuzzy Linear Programming under Uncertainty

When planning wetland restoration projects, the planting area allocation and the costs of the restoration measures are two major issues faced by decision makers. In this study, a framework based on the interval fuzzy linear programming (IFLP) method is introduced for the first time to plan wetland restoration projects. The proposed framework can not only effectively deal with interval and fuzzy uncertainties that exist in the planning process of wetland restorations but also handle trade-offs between ecological environment benefits and economic cost. This framework was applied to a real-world wetland restoration planning problem in the northeast of China to verify its validity and examine the credibility of the constraints. The optimized results obtained from the framework that we have developed indicate that higher ecological and social benefits can be obtained with optimal restoration costs after using the wetland restoration decision-making framework. The optimal restoration measure allocation schemes obtained by IFLP under different credibility levels can help decision makers generate a range of alternatives, which can also provide decision suggestions to local managers to generate a satisfactory decision-making plan. Furthermore, a comparison was made between the IFLP model and ILP model in this study. The comparison results indicate that the IFLP model provides more information regarding ecological environment and economic trade-offs between the system objective, certainty, and reliability. This framework provides managers with an effective way to plan wetland restoration projects, while transference of the model may help solve similar problems.

CFD-based simulation to reduce greenhouse gas emissions from industrial plants

Greenhouse gas (GHG) pollution is considered one of the challenging concerns in industrial plants, and to emit the appropriate designation in nitrogen oxide reduction, it is required to implement proper numerical simulation procedures. In this study, ANSYS Fluent® software is used as dynamic software to solve heat and mass flow transfer numerically by considering non-structured networks for complex geometries. Dry nitrogen oxide burners have an additional thermocouple to provide an extra fuel pathway to combine with air. Then, standard K-ε is used in the numerical simulations to calculate thermal efficiency in combustion processes for turbulent flow regimes. It can cause the removal of 50% of nitrogen oxide into the atmosphere. Furthermore, by the increase of temperature, nitrogen oxide concentration has been increased in the system. After 1975 K, Fuel has been changed to dry fuel, and therefore nitrogen oxide concentration increased because the steam can provide a relatively non-combustible compound increase than fuel. On the other hand, regarding the water volume increase at inlet steam, nitrogen oxide volume percentage has been decreased dramatically, especially in the first periods of water volume increase. Consequently, when the steam percentage is increased instead of water, nitrogen oxide reduction is increased. Moreover, our simulation results have a proper match with Gibbs energy equilibrium.