Relationships among carbon emissions,economic growth,energy consumption and population growth: Testing Environmental Kuznets Curve hypothesis for Brazil,China, India and Indonesia

This study examines the impacts of income, energy consumption and population growth on CO₂ emissions by employing an annual time series data for the period 1970–2012 for India, Indonesia, China, and Brazil. The study used the Autoregressive Distributed Lag (ARDL) bounds test approach considering both the linear and non-linear assumptions for related time series data for the top CO₂ emitter emerging countries in both the short run and long run. The results show that CO₂ emissions have increased statistically significantly with increases in income and energy consumption in all four countries. While the relationship between CO₂ emissions and population growth was found to be statistically significant for India and Brazil, it has been statistically insignificant for China and Indonesia in both the short run and long run. Also, empirical observations from the testing of environmental Kuznets curve (EKC) hypothesis imply that in the cases of Brazil, China and Indonesia, CO₂ emissions will decrease over the time when income increases. So based on the EKC findings, it can be argued that these three countries should not take any actions or policies, which might have conservative impacts on income, in order to reduce their CO₂ emissions. But in the case of India, where CO₂ emissions and income were found to have a positive relationship, an increase in income over the time will not reduce CO₂ emissions in the country.     

The linkages between deforestation,energy and growth for environmental degradation in Pakistan

This study explores the validation of the Environmental Kuznets Curve (EKC) hypothesis for Pakistan using time series data from 1980–2013 with deforestation as an indicator (dependent variable) for environmental degradation, and four independent variables (economic growth, energy consumption, trade openness, and population) were also examined. The Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration and the VECM–Granger causality test were applied. The results confirmed the existence of cointegration among the variables both in long- and short-run paths. However, the diminishing negative impact of economic growth on deforestation in the long-run confirms the EKC hypothesis for deforestation in Pakistan. Moreover, economic growth and energy consumption Granger cause deforestation. A bidirectional causal effect is detected between economic growth and energy consumption, however, in the long-run, economic growth and trade openness Granger cause energy consumption. This study was designed with several significant tests to ensure the reliability of results for policy use and to contribute to future studies on the environment-growth-energy nexus.     

经济发展对环境质量的影响——环境库兹涅茨曲线国内外研究进展

“环境库兹涅茨曲线 (Environm ental Kuznets Curve)”是指环境破坏与收入水平之间成倒 U形曲线关系 ,即随着经济发展和收入水平的提高 ,环境质量先破坏后好转。 2 0世纪 90年代初 ,揭开了 EKC研究的序幕 ;之后涌现大量实证研究和理论解释模型的探索 ;近年来的研究在前人的基础上视野更加宽阔 ,更注重理论模型的完善。从实证研究、计量模型和解释理论等 3条线索回顾了近年来国内外的主要研究进展 ,认为现有研究在计量模型、数据处理、指标选取等方面虽然取得了巨大进展 ,但仍存在许多不足 ;EKC研究要得到更进一步发展必须突破这些局限     

Analysis of relationship between Beijing's environment and development based on Environmental Kuznets Curve

Urbanization nowadays is a very important driving force for China's social and economic development, but the resource shortage and pollution accompanied have troubled China especially in the urban areas. As the capital of China, Beijing is a mega-city and densely populated. Its development and prosperity is supported by a large amount of material consumption, rendering a severe shortage of natural resources and serious pollution. Underlying the premise of maintaining its development and prosperity, Beijing is facing an enormous challenge in dealing with heavy pollution load. Therefore, it is a very important step to decouple the relationship between economic development and environmental pollution. This paper makes a study on the relationship between the economic growth and pollution load for Beijing based on the analysis of Environmental Kuznets Curves (EKC) which builds an econometric model using data over the period 1990–2014. We found the intensity of most pollutants have arrived at the turning point around 2006 while the total amount of most emissions remain at a high level, this is a favorable initiation for the transforming the development patterns as it has begun to decouple the pollution intensity and economy. Based on the statistics, this paper further analyzes the driving factors behind the active change. We found that the adjustment of industrial structure, a reasonable city planning, powerful measures in pollutants control and technology advance, contribute a lot to the transformation. Especially in the recent years, Beijing and correlative regions took joint measures to prevent and reduce air pollution, which have an apparent functions. Finally, this paper proposes several suggestions for Beijing to decouple the economic growth and environmental pollution load, based on these important conclusions.     

基于环境库兹涅茨曲线的我国大气污染防治重点区域环境空气质量与经济增长关系研究

改革开放以来,中国经济迅猛发展,但大气污染等环境问题日益突出。进入21世纪,我国通过颁布实施多项大气污染防治政策,将京津冀及周边地区、长三角地区、珠三角地区等大气污染较严重的区域划定为重点区域,针对性制定治污措施和实施减排工程,努力推动区域环境空气质量改善。基于2000-2019年我国31个省（自治区、直辖市）（以下简称31个省份）GDP,以及SO₂、PM₁₀、NO₂三项大气污染物浓度数据,利用环境库兹涅茨曲线（EKC,Environmental Kuznets Curve）模型,对31个省份和京津冀及周边地区、长三角地区、珠三角地区的经济增长情况、大气污染物浓度演变以及二者之间的关系进行了系统全面的分析评估。研究结果显示：（1）近年来实施的各项大气污染防治政策,特别是2013年以来颁布实施的《大气污染防治行动计划》《打赢蓝天保卫战三年行动计划》,推动环境空气质量改善的同时,促进了经济发展与环境保护长期关系协调性逐步增强,除NO₂浓度呈U型外,31个省份SO₂浓度、PM₁₀浓度与人均GDP的EKC曲线呈倒U型和倒N型,并处于快速下降阶段。（2）京津冀及周边地区SO₂浓度与人均GDP呈倒U型,且处于快速下降阶段;PM₁₀和NO₂浓度均呈现U型关系,且均处于上升期。（3）长三角地区SO₂、PM₁₀浓度与人均GDP呈现倒U型和U型,但均处于下降阶段;NO₂浓度与人均GDP无相关关系。（4）珠三角地区SO₂、PM₁₀和NO₂浓度与人均GDP均呈现倒U型关系,且均处于下降阶段。为此,建议"十四五"期间我国政府要继续实施新一轮的大气污染防治行动计划,聚焦机动车NO_x污染管控,大力推动NO₂浓度稳步下降,以实现我国环境空气质量持续改善,为统筹经济高质量发展和生态环境高水平保护奠定坚实基础。     

Economic growth and obesity: An interesting relationship with world-wide implications

The prosperity of a country, commonly measured in terms of its annual per capita Gross Domestic Product (GDP), has different relationships with population levels of body weight and happiness, as well as environmental impacts such as carbon emissions. The aim of this study was to examine these relationships and to try to find a level of GDP, which provides for sustainable economic activity, optimal happiness and healthy levels of mean body mass index (BMI). Spline regression analyses were conducted using national indices from 175 countries: GDP, adult BMI, mean happiness scores, and carbon footprint per capita for the year 2007. Results showed that GDP was positively related to BMI and happiness up to ∼$US3000 and ∼$5000 per capita respectively, with no significant relationships beyond these levels. GDP was also positively related to CO₂ emissions with a recognised sustainable carbon footprint of less than 5 tonnes per capita occurring at a GDP of <$US15,000. These findings show that a GDP between $US5 and $15,000 is associated with greater population happiness and environmental stability. A mean BMI of 21-23 kg/m², which minimises the prevalence of underweight and overweight in the population then helps to define an ideal position in relation to growth, which few countries appear to have obtained. Within a group of wealthy countries (GDP > $US30,000), those with lower income inequalities and more regulated (less liberal) market systems had lower mean BMIs.     

Testing environmental Kuznets curve hypothesis: The role of renewable and non-renewable energy consumption and trade in OECD countries

This paper investigates the causal relationships between per capita CO₂ emissions, gross domestic product (GDP), renewable and non-renewable energy consumption, and international trade for a panel of 25 OECD countries over the period 1980–2010. Short-run Granger causality tests show the existence of bidirectional causality between: renewable energy consumption and imports, renewable and non-renewable energy consumption, non-renewable energy and trade (exports or imports); and unidirectional causality running from: exports to renewable energy, trade to CO₂ emissions, output to renewable energy. There are also long-run bidirectional causalities between all our considered variables. Our long-run fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) estimates show that the inverted U-shaped environmental Kuznets curve (EKC) hypothesis is verified for this sample of OECD countries. They also show that increasing non-renewable energy increases CO₂ emissions. Interestingly, increasing trade or renewable energy reduces CO₂ emissions. According to these results, more trade and more use of renewable energy are efficient strategies to combat global warming in these countries.     

CO2, economic growth,and energy consumption in China's provinces: Investigating the spatiotemporal and econometric characteristics of China's CO2 emissions

This study addresses the spatiotemporal variations at play in China's CO₂ emissions, based on an estimation of emission levels in the period 1995–2012 and an provincial analysis of the relationship of CO₂ emissions to economic growth and energy consumption. Using a series of econometric models and data on the combustion of fossil fuels and cement manufacturing, the study first estimated CO₂ emission levels during the study period, exploring their spatiotemporal pattern. The results indicate that both China's total and its per capita CO₂ emissions have increased significantly over the study period, with both measures evidencing a similar evolution (albeit one that is characterized by noticeable regional discrepancies at the provincial level and which displays properties of convergence). From a geographical perspective, we found both total and per capita CO₂ emissionsto be higher in China's eastern region than in the country's central and western regions. Panel data analysis was subsequently undertaken in order to quantify the dynamic casual relationship between economic growth, energy consumption, and CO₂ emissions. The empirical results indicated that the variables were in fact cointegrated and exhibited a long-run positive relationship. The results of further Granger causality tests indicated the existence of a bidirectional positive causality between economic growth and energy consumption, as well as between energy consumption and CO₂ emissions, and a unidirectional positive causality running from economic growth to CO₂ emissions. The findings of this study suggest that China is, in the long run, dependent on carbon energy consumption for its rapid economic growth, a dependency which is the cause of considerable increases in CO₂ emissions. China should therefore make greater efforts to develop low-carbon technologies and renewable energy, and improve energy efficiency in order to reduce emissions and achieve green economic growth.     

Intercountry inequality on greenhouse gas emissions and world levels: An integrated analysis through general distributive sustainability indexes

Up until now, analyses of the inter-country distribution of pollutant emissions have not paid sufficient attention to the implications that, in terms of global sustainability, the combined evolution of the global world average entails. In this context, this paper proposes the use of general distributive sustainability indexes in order to make a comprehensive examination of the international equity factor and also the mean (world) factor in this field. The proposed methodology, which is adapted from the welfare and inequality economics literature, is implemented empirically in order to explore the evolution of the greenhouse gases and its main components: CO₂, CH₄ and N₂O during the period 1990–2012. The main results found are as follows: firstly, typically, the general distributive sustainability associated with the overall greenhouse gases in per capita terms increased over the global period but, contrarily, it seems to decrease since 2000; secondly, typically this last reduction is basically explained by the increase in world mean average, given the clear reduction on cross-country inequalities; thirdly, the analysis of different gases also points out some differences in temporal variations and depending on the index used. These results would seem to be relevant in policy and academic terms.     

基于MFA和DEA的区域经济环境效率评价-以辽宁省为例

对经济与环境效率的科学评价是实现区域可持续发展的前提。运用物质流分析将辽宁省经济系统中数据进行物质化处理,再利用改进的数据包络分析模型对环境和经济效率进行综合评价。结果表明:辽宁省物资消费不主要依赖于进口,向其它地区物质输出量大;环境效率评价的综合效率主要受规模因素影响而显著低于纯技术效率,而整体经济的综合效率却主要受纯技术效率影响而下降。第二产业比重依然偏大的产业结构特征是导致上述结果的主因。进一步改造提升传统产业,发展战略性新兴产业,提高第三产业发展水平,扩大环保规模,促进居民生活质量水平全面提升,将是辽宁省以及与之相似的资源依赖型区域可持续发展的方向。     

海洋生物多样性损害与沿海地区经济增长关系实证研究

海洋生物多样性是海洋生态系统服务的基础,保护海洋生物多样性不仅对维持地球生态系统的功能至关重要,也与人类福祉密切相关。基于沿海11个省区生态系统亚健康程度指标和物种多样性损害指标,运用面板回归模型对中国沿海地区经济增长与海洋生物多样性损害的关系进行实证考察。研究结果表明：(1)海洋生态系统亚健康程度与沿海地区经济增长之间存在显著的线性关系,随着经济增长,典型海洋生态系统亚健康状态占比呈现出持续上升趋势。此外,实施排污费制度和建立海洋自然保护区有利于抑制海洋生态系统的恶化。(2)海洋物种多样性损害与沿海地区经济增长之间存在显著“倒U”型关系,随着经济增长,海洋物种多样性损害呈现先上升后下降的态势,转折点为人均GDP 45145元,目前海南省、广西壮族自治区、河北省未跨过转折点。此外,排污费制度有利于抑制海洋物种多样性损害,而沿海地区目前的产业结构加重了海洋物种多样性损害。根据实证分析结果,海洋生态系统健康尚未出现拐点,沿海地区经济增长如果建立在对生态环境破坏的基础上,则势必会造成生物多样性的损害。因此从规范海域利用方式,完善海岸生态保护红线划定,加强生态系统的监测与管理,保持绿色可持续的...     

Probability functions to build composite indicators: A methodology to measure environmental impacts of genetically modified crops

There is an on-going debate on the environmental effects of genetically modified crops to which this paper aims to contribute. First, data on environmental impacts of genetically modified (GM) and conventional crops are collected from peer-reviewed journals, and secondly an analysis is conducted in order to examine which crop type is less harmful for the environment. Published data on environmental impacts are measured using an array of indicators, and their analysis requires their normalisation and aggregation. Taking advantage of composite indicators literature, this paper builds composite indicators to measure the impact of GM and conventional crops in three dimensions: (1) non-target key species richness, (2) pesticide use, and (3) aggregated environmental impact. The comparison between the three composite indicators for both crop types allows us to establish not only a ranking to elucidate which crop is more convenient for the environment but the probability that one crop type outperforms the other from an environmental perspective. Results show that GM crops tend to cause lower environmental impacts than conventional crops for the analysed indicators.     

基于生物标志物指数法的海洋环境评价方法综述

生物标志物对化学污染物具有“早期预警”功能,在海洋环境评价中应用广泛.以生物标志物为基础的综合指数能够整合多种标志物对环境状况的响应,因而成为评价环境质量的有用工具.这些综合指数方法包括多生物标志物污染指数(MPI)、综合生物标志物响应指数(IBR)、生物效应评价指数(BAI)、生物标志物响应指数(BRI)、健康状态指数(HIS)等.本文从生物标志物指标体系确定、综合指数计算方法、污染程度分级、应用效果等方面对这些评价方法进行综述,并对基于生物标志物指数的海洋环境评价方法存在的问题和改进建议进行了探讨.     

The fuzzy index of ecosystem integrity (FINE): a new index of environmental integrity for transitional ecosystems

The European Water Framework Directive (WFD) (2000/60/EC) requires assessing the ecological quality status of water bodies, and gives great importance to the biological components of the ecosystem. Within this framework, a multimetric, fuzzy-based index for the evaluation of environmental quality (FINE: fuzzy index of ecosystem integrity) has been developed using data from several Italian coastal lagoons, gathered with seasonal frequency at diverse sites in each lagoon. The rationale of FINE is that certain attributes, selected on the basis of established principles of benthic ecology, are fundamental for lagoon ecosystem function. FINE is composed of seven ecosystem attributes (variables) each of which have ecological relevance for lagoon ecosystems. Individually, all these attributes are themselves useful indices of environmental conditions. However, the combination of these attributes into a single fuzzy index, provides a more robust, overall index of the response of the natural communities to environmental perturbations and avoids misleading or ambiguous results. Each variable is not represented by a single numerical value, but by several categories that describe its properties: in the present model we considered a total of seven variables: two with four modalities (low–medium–high–very high), one with three (low–medium–high) and three with two (low–high), plus a qualitative variable (yes–no), that altogether generate 768 rules. FINE is a low-cost, flexible and robust routine index of lagoon ecosystem impairment and could be of particular benefit to environmental managers and policymakers who require tools capable of expressing the degree of degradation or environmental quality of different lagoon habitats. For its relative simplicity in the application, FINE could be a good candidate to assess the environmental quality of Mediterranean transitional ecosystems. Guest editors: A. Razinkovas, Z. R. Gasiūnaitė, J. M. Zaldivar & P. Viaroli European Lagoons and their Watersheds: Function and Biodiversity     

Regional environmental efficiency in China: Analysis based on a regional slack-based measure with environmental undesirable outputs

As the largest developing country, China has been suffering from resource shortage and serious environmental pollution. Evaluation and improvement of the regional environmental efficiency is crucial to pursuing the balance between economic development and environmental protection. This paper used a regional environmental efficiency SBM (slack-based measure) (REES) model which treats environmental pollution as undesirable outputs to evaluate the environmental efficiency of 30 provincial administrative regions (PARs) in China from 2005 to 2011 and investigated the factors affecting environmental efficiency using the Tobit regression model. The results indicate that there is distinct difference in environmental efficiency amongst each PAR. The GDP per capita, industrial structure, innovation capability, environmental awareness of local government and population density have significant positive impacts, while energy intensity exerts a significantly negative effect on environmental efficiency. In order to make more effective policies for improving China’s regional environmental efficiency, the hierarchical cluster analysis was applied to divide the 30 PARs into 3 sub-regions. A number of policy recommendations were provided for improving environmental efficiency according to the characteristics of each sub-region, which are helpful for the Chinese government to achieve the targets of environmental protection along with the economic development in the coming years.     

A review on the potential effects of environmental and economic factors on sheep genetic diversity: Consequences of climate change

Climate change has a significant effect on the productivity of livestock including milk, meat, and reproduction. This could be attributed to the internal diversion of energy resources towards adaptive mechanisms. Among the climate change variables, thermal stress seems to be the major limiting factor in animal agriculture. A better understanding of the effects of climate change-influenced ecological factors on the genetic diversity of livestock species is warranted. Sheep is an ideal livestock species to be used in investigating environmental adaptation due to its wide range of agroecological habitats, genetic and phenotypic variability. There is a heavy reliance on sheep genetic diversity for future animal protein security, but the implications of climate change on their genetic diversity receive less attention.Here, the potential environmental factors influencing natural selection in sheep populations are presented. We argue that prolonged exposure to these factors plays a major role in influencing the development of adaptation traits in indigenous sheep breeds, consequently leading to the alteration of genetic diversity at specific loci. The factors discussed include hot temperatures (heat stress), insufficient water, low quantity and quality of forage, and prevalence of parasites, pests, and diseases. In addition, genetic diversity, some signatures of selection for adaptation and economic angles of selection are also briefly discussed.A better understanding of environmental factors influencing the genetic diversity of sheep populations will inform breeding and management programs and may offer an opportunity for greater production efficiency with low input costs.     

An analysis of succession along an environmental gradient using data from a lawn

Differences in vegetation dynamics over a period of two years along an environmental gradient of shading on a lawn are examined. Communities (groups) recognized by numerical classification are correlated with degree of shading, season and differences between years by means of generalized linear model analysis. More of the variance is explained if environmental position is used instead of degree of shading as spatial distribution of a strongly competitive species (Trifolium repens) is confounded with shading. Transition probabilities are related to environmental position and season. Simulation with Markov matrices for each season and position demonstrate markedly different successions for different positions. These simulations have no predictive value however as accurate estimate of transition probabilities requires knowledge of the state of adjacent quadrats, i.e. individual observations of transition probabilities are not independent.Transition matrices are unlikely to be useful for predictive analysis of succession when spatial pattern is of significance in the community.We thank S. Kendall, S. Witts, A. Howard and C. Helman for their assistance with the data preparation and analysis, and R. Cunningham for advice on statistical analysis.