Search

Studying and analyzing energy consumption and structural changes in Pakistan's major economic sectors is crucial for developing targeted strategies to improve energy efficiency, support sustainable economic growth, and enhance energy security. The logarithmic mean Divisia index (LMDI) method is applied to find the factors' effects that change sector-wise energy consumption from 1990 to 2019. The results show that: (1) the change in mixed energy and sectorial income shows a negative influence, while energy intensity (EI) and population have an increasing trend over the study period. (2) The EI effects of the industrial, agriculture and transport sectors are continuously rising, which is lowering the income potential of each sector. (3) The cumulative values for the industrial, agricultural, and transport sectors increased by 57.3, 5.3, and 79.7 during 2019. Finally, predicted outcomes show that until 2035, the industrial, agriculture, and transport incomes would change by -0.97%, 13%, and 65% if the energy situation remained the same. Moreover, this sector effect is the most crucial contributor to increasing or decreasing energy consumption, and the EI effect plays the dominant role in boosting economic output. Renewable energy technologies and indigenous energy sources can be used to conserve energy and sectorial productivity., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Bai, Raza. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Financial subsidies and tax incentives play essential roles in the innovation efficiency of enterprises. This paper selects Chinese listed NEV enterprises from 2010 to 2022 as a research sample and investigates various impacts under various circumstances. We find that both financial subsidies and tax incentives can promote the innovation efficiency of NEV enterprises. Compared to financial subsidies, tax incentives are more effective; the interaction between financial subsidies and tax incentives has a weaker impact on the innovation efficiency of NEV enterprises. Both financial subsidies and tax incentives have more potent innovation effects on enterprises with higher financing constraints. In addition, financial subsidies and tax incentives have a stronger innovation efficiency effect on private enterprises than state-owned enterprises. Further research shows that marketization and market distortion affect the innovation efficiency of NEV enterprises. This study provides a new perspective for understanding the effects of financial subsidies, tax incentives, and innovation efficiency of NEV enterprises, and the conclusions and suggestions are relevant references for the government to improve the quality of policy-making., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Binhua Qian. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study intends to test the connection between fiscal decentralization, energy demand dynamics, and energy poverty status from the context of China. The study has collected large datasets ranging from 2001 to 2019 to justify the empirical findings. The long-run analysis economic techniques were considered and applied for this. The results indicated that a 1% adverse change in energy demand dynamics causes 13% of energy poverty. Supportively, a 1% positive rise in energy supply to fulfill energy demand reduces energy poverty by 9.4% in the study context. Moreover, empirical findings show that a 7% rise in fiscal decentralization accelerates 19% fulfillment in energy demand and mitigates energy poverty up to 10.5%. We demonstrate that if enterprises can only alter their technology choices in the long run, the short-run reaction of energy demand must be less than the long-run response. Second, we demonstrate that the elasticity of demand approaches its long-run level exponentially at the rate defined by the capital depreciation rate and the economy's growth rate, using a putty-clay model with induced technical development. According to the model, it takes more than 8 years for half of the long-run impact of induced technological change on energy consumption to be realized in industrialized nations once the carbon price is implemented. This research document also gives multiple policy directions for policy developers., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The energy products of oil and gas majors have contributed significantly to global greenhouse gas emissions (GHG) and planetary warming over the past century. Decarbonizing the global economy by mid-century to avoid dangerous climate change thus cannot occur without a profound transformation of their fossil fuel-based business models. Recently, several majors are increasingly discussing clean energy and climate change, pledging decarbonization strategies, and investing in alternative energies. Some even claim to be transforming into clean energy companies. Given a history of obstructive climate actions and "greenwashing", there is a need to objectively evaluate current and historical decarbonization efforts and investment behavior. This study focuses on two American (Chevron, ExxonMobil) and two European majors (BP, Shell). Using data collected over 2009-2020, we comparatively examine the extent of decarbonization and clean energy transition activity from three perspectives: (1) keyword use in annual reports (discourse); (2) business strategies (pledges and actions); and (3) production, expenditures and earnings for fossil fuels along with investments in clean energy (investments). We found a strong increase in discourse related to "climate", "low-carbon" and "transition", especially by BP and Shell. Similarly, we observed increasing tendencies toward strategies related to decarbonization and clean energy. But these are dominated by pledges rather than concrete actions. Moreover, the financial analysis reveals a continuing business model dependence on fossil fuels along with insignificant and opaque spending on clean energy. We thus conclude that the transition to clean energy business models is not occurring, since the magnitude of investments and actions does not match discourse. Until actions and investment behavior are brought into alignment with discourse, accusations of greenwashing appear well-founded., Competing Interests: The authors have declared that no competing interests exist.

Estimates of global economic damage caused by carbon dioxide (CO 2 ) emissions can inform climate policy 1-3 . The social cost of carbon (SCC) quantifies these damages by characterizing how additional CO 2 emissions today impact future economic outcomes through altering the climate 4-6 . Previous estimates have suggested that large, warming-driven increases in energy expenditures could dominate the SCC 7,8 , but they rely on models 9-11 that are spatially coarse and not tightly linked to data 2,3,6,7,12,13 . Here we show that the release of one ton of CO 2 today is projected to reduce total future energy expenditures, with most estimates valued between -US$3 and -US$1, depending on discount rates. Our results are based on an architecture that integrates global data, econometrics and climate science to estimate local damages worldwide. Notably, we project that emerging economies in the tropics will dramatically increase electricity consumption owing to warming, which requires critical infrastructure planning. However, heating reductions in colder countries offset this increase globally. We estimate that 2099 annual global electricity consumption increases by about 4.5 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in global mean surface temperature (GMST), whereas direct consumption of other fuels declines by about 11.3 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in GMST. Our finding of net savings contradicts previous research 7,8 , because global data indicate that many populations will remain too poor for most of the twenty-first century to substantially increase energy consumption in response to warming. Importantly, damage estimates would differ if poorer populations were given greater weight 14 ., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Based on the data of China's outward foreign direct investment (OFDI) in energy sector to 133 countries from 2005 to 2014, this paper uses a gravity model to investigate the impact of "intimate" relations on China's OFDI locations in energy sector. We find that the "intimate" relations have significant effects on China's OFDI locations in energy sector, namely: bilateral senior leaders' visits, institutional distance, genetic distance, and immigration. Holding other factors fixed, for each one more bilateral senior leaders' visit between China and the host country, China's OFDI in energy sector for the host country will increase by 5.44%. If the genetic distance from China and host country increases by 1%, China's OFDI in energy sector will fall by 1.69%. For every 1% increase in the institutional distance between China and host country, China's energy OFDI will decrease by 1.09%. For every 1% increase in a country's immigration to China, China's energy OFDI will increase by 0.46%. Further, after distinguishing developed and developing countries, we find that compared with developed countries, "intimate" relations have greater impacts on China's energy OFDI in developing countries. Finally, based on the dominance analysis, considering China's "intimate" relations with countries along the "Belt and Road" and current locations of China's OFDI, we find that China should further expand energy investment in countries along the "Belt and Road"., Competing Interests: The authors have declared that no competing interests exist.

This study uses the improved Cobb-Douglas two-factor production function model to explore the potential relationship between economic growth and energy consumption through the multiple co-integration test on the panel data of China from 1985 to 2018. The results show that there is a positive long-term balance between energy consumption and economic growth: economic growth of 1%, total energy consumption growth of 1.53%, which means that economic growth needs higher energy support in the former short term. At the same time, the error correction term will converge energy consumption to a long-term equilibrium state with an adjustment intensity of 134.59%. From the results of variance decomposition, we can also see that as the number of periods increases, the part of real economic growth explained by energy consumption gradually increases., Competing Interests: The authors have read the journal’s policy and have the following competing interests: JL is an employee of China Datang Corporation Ltd., Beijing, China. BC is an employee of State Power Investment Group Corporation, Beijing, China. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products associated with this research to declare.

In recent years, the environmental problems caused by excessive carbon emissions from energy sources have become increasingly serious, which not only aggravates the climate change caused by the greenhouse effect but also seriously restricts the sustainable development of Chinese economy. An attempt is made in this paper to use energy consumption method and input-output method to study the carbon emission structure of China's energy system and industry in 2015 from two perspectives, namely China's energy supply side and energy demand side, by taking into account the two factors of energy invest in gross capital formation and export. The results show that neglecting these two factors will lead to underestimation of intermediate use carbon emissions and overestimation of final use carbon emissions. On energy supply side, the carbon emission structure of China's energy system is still dominated by high-carbon energy (raw coal, coke, diesel, and fuel oil, etc.), accounting for more than 70% of total energy carbon emissions; on the contrary, the natural gas such as clean energy accounts for only 3.45% of total energy carbon emissions, indicating that the energy consumption structure optimization and emission reduction gap of China's energy supply side are still substantial. On energy demand side, the final use (direct consumption by residents and government) produces less carbon emissions, while the intermediate use (production by enterprises) produces more than 90% of the total energy carbon emissions. Fossil energy, power sector, heavy industry, chemical industry, and transportation belong to industries with larger carbon emissions and lower carbon emission efficiency, while agriculture, construction, light industry, and service belong to industries with fewer carbon emissions and higher carbon emission efficiency. This means that the optimization of industrial structure is conducive to slowing down the growth of energy carbon emissions on the demand side., Competing Interests: The authors have declared that no competing interests exist.

Climate change has become intertwined with the global economy. Here, we describe the contribution of inertia to future trends. Drawing from thermodynamic principles, and using 38 years of available statistics between 1980 to 2017, we find a constant scaling between current rates of world primary energy consumption [Formula: see text] and the historical time integral W of past world inflation-adjusted economic production Y, or [Formula: see text]. In each year, over a period during which both [Formula: see text] and W more than doubled, the ratio of the two remained nearly unchanged, that is [Formula: see text] Gigawatts per trillion 2010 US dollars. What this near constant implies is that current growth trends in energy consumption, population, and standard of living, perhaps counterintuitively, are determined by past innovations that have improved the economic production efficiency, or enabled use of less energy to transform raw materials into the makeup of civilization. Current observed growth rates agree well with predictions derived from available historical data. Future efforts to stabilize carbon dioxide emissions are likely also to be constrained by the contributions of past innovation to growth. Assuming no further efficiency gains, options look limited to rapid decarbonization of energy consumption through sustained implementation of at least one Gigawatt of renewable or nuclear power capacity per day. Alternatively, with continued reliance on fossil fuels, civilization could shift to a steady-state economy, one that devotes economic production exclusively to maintining ongoing metabolic needs rather than to material expansion. Even if such actions could be achieved immediately, energy consumption would continue at its current level, and atmospheric carbon dioxide concentrations would only begin to balance natural sinks at concentrations exceeding 500 ppmv., Competing Interests: The authors have declared that no competing interests exist.

In energy economics literature, we found few studies on the association between environmental quality energy consumption and financial development. The current study is an attempt to contribute in literature by examining the link between carbon dioxide (CO 2 ) emissions, financial development, energy consumption, and economic growth, in South East Asian economies for the period 1980-2017 using annual time series data. For empirical analysis, Bound tests for cointegration and error correction approach are used. The estimated results confirm that financial development has positive impact on environmental quality. On the other hand, in the long run, the rise in energy consumption economic growth and trade openness is unfavorable for environment quality. Our results confirm U-shaped relationship between economic growth and environmental quality that is a proof of environmental Kuznets curve (EKC). Additionally, the government needs to design different modes of energy consumption to solve the problem of environmental degradation. Moreover, the major conclusion extends new insight for authority to make a comprehensive trade and financial policies to improve environmental quality.

In recent decades, climate change and environmental pollution have been at the center of global environmental debates. Nowadays, researchers have turned their attention to the linkage between real output and environmental quality and test the environmental Kuznets curve. Majority of the studies focus on a single pollutant aspect and measure the deterioration of the environment through carbon emission (CO 2 ) only. In contrary, the current study uses a comprehensive proxy, ecological footprint, to measure the environmental quality of the sixteen Central and Eastern European Countries (CEECs). The aim of this paper is to discover the impact of financial development, economic growth, and energy consumption (renewable and non-renewable) on the environment. In addition, for the first time, the current study includes biocapacity and human capital in the growth-energy-environment nexus in the case of CEECs. In doing so, we used annual data of sixteen CEE countries in perspective of the One Belt One Road (OBOR) initiative and cover the period of 1991-2014. For reliable findings, this study focuses on second-generation econometric approaches to check stationarity, cross-sectional dependency, and co-integration among the model parameters. The long-run estimations of the "Dynamic Seemingly Unrelated-co-integration Regression" (DSUR) signify that the effect of economic growth on ecological footprint is not stable and validate N-shaped relationship for cubic functional form between per capita income and ecological footprint (environmental quality). Empirical evidence divulges that financial development and energy use significantly contribute to environmental degradation while renewable energy improves environmental quality by declining ecological footprint significantly. Moreover, the significant effects of biocapacity and human capital are positive and negative on the ecological footprint, respectively. In robustness check through the "Feasible Generalized Least Square" (FGLS) and "Generalized Method of Moment" (GMM) models, we found consistent result. Lastly, the "Dumitrescu-Hurlin (D-H) Panel Causality Test" demonstrates that two-way causal relationship exists between EF and GDP, EF and FD, EF and EU, EF and BC, and EF and HC, while one-way causality is running from RE to EF. This study puts the present scenario of CEE economies in front of the policymakers and suggests that they should consider the vital role of renewable energy and human capital to get sustainability.

Much of the Earth's biosphere has been appropriated for the production of harvestable biomass in the form of food, fuel and fibre. Here we show that the simplification and intensification of these systems and their growing connection to international markets has yielded a global production ecosystem that is homogenous, highly connected and characterized by weakened internal feedbacks. We argue that these features converge to yield high and predictable supplies of biomass in the short term, but create conditions for novel and pervasive risks to emerge and interact in the longer term. Steering the global production ecosystem towards a sustainable trajectory will require the redirection of finance, increased transparency and traceability in supply chains, and the participation of a multitude of players, including integrated 'keystone actors' such as multinational corporations.

Quantitative analysis on decoupling between economic output, carbon emission, and the driving factors behind decoupling states can serve to make the economy grow without increasing carbon emission in China's transport sector. In this work, we investigate the decoupling states and driving factors of decoupling states in the transport sector of China's four municipalities (Beijing, Shanghai, Tianjin, and Chongqing) through combining the Tapio decoupling approach with the decomposition technique. The results show that (i) the decoupling state of Beijing, Shanghai, and Tianjin improved; Beijing stabilized in weak decoupling; Shanghai and Tianjin appeared to have strong decoupling, but the decoupling state of Chongqing deteriorated from decoupling to negative decoupling. (ii) The energy-saving effect was the primary contributor to decoupling in these four municipalities, promoting transport's economic growth strongly decouple from carbon emission. The economic scale effect was not optimized enough in Chongqing, facilitating expansive coupling, and expansive negative decoupling emerged. But it had a rather positive impact on decoupling process in Beijing, Shanghai and Tianjin, promoting economic growth to weakly decouple from carbon emission. (iii) The carbon-reduction effect promoted strong decoupling, which emerged in Shanghai's transport sector, more so than in the other three municipalities, in which weak decoupling emerged. Finally, several relevant policy recommendations were offered to promote the decoupling of carbon emission from economic growth and low-carbon transport.

Objective: To evaluate the " Energía, la justa " program, aimed at reducing energy poverty in the city of Barcelona, from the point of view of the target population and the workers involved in the intervention., Methods: A qualitative, descriptive and exploratory pilot study was carried out, with a phenomenological approach. Twelve semi-structured interviews were conducted: to three users, three energy agents who performed interventions in the homes, and six professionals who participated in the program coordination. A thematic content analysis was carried out using Atlas-ti software . Interviews were conducted between October 2016 and March 2017., Results: Trust in a contact person (e.g. social workers) facilitated the participation, although there were difficulties reaching people who had illegal energy supplies, immigrant women or immigrants who subrent properties. Regarding implementation, home visits, energy efficiency advice and the relationship with energy agents were the best assessed aspects. However, not being able to carry out reforms in deteriorated dwellings was considered a limitation. The program also contributed to raise awareness on energy rights, to save on utility bills and to generate tranquility and social support., Conclusions: Programs such as this one can promote energy empowerment and improve psychosocial status. However, strategies with a gender and equity perspective should be considered to reach other vulnerable groups.

The developing countries and emerging economies are crucially contributing to global economic development, energy transition, and climate governance. This paper employs panel cointegration technique to investigate the long-run relationship between carbon emissions and five impacting factors (per capita GDP, primary energy consumption, international trade, fossil proportion, and quadratic per capita GDP) in 50 representative developing countries during 1995-2017. The empirical findings confirm the existence of long-run equilibrium, and the regressing coefficients of fully-modified OLS (FMOLS) indicate that (a) impacting features of the inverted U-shaped curve of Environmental Kuznets Curve (EKC) theory appear in a few countries, such as Mexico, Croatia, Kazakhstan, Iran, Algeria, Indonesia, and Thailand; (b) the energy consumption has statistically positive and significant impacts on boosting the carbon emissions; (c) the negative effect of international trade emerges in the developing nations enjoying trade surpluses; and (d) fossil energy share poses a mixed impact. This paper reveals that the vast and inspiring contribution of developing countries to global carbon emission reduction should attract more international attention and assistance.

This paper searches the role of financial sector development in energy sector and therefore in climate changes in the case of developing and developed countries. Panel data ranging from 1960 to 2014 on an annual basis has been selected from 176 countries. Results suggest that carbon dioxide emissions in developed and developing countries are in long-term equilibrium relationship with financial sector; trade and finance sectors have long-term significant impacts on carbon emissions and therefore carbon emissions converge to their long-term equilibrium levels through the channels of finance and trade sectors. Impulse response analyses proved that finance and trade sectors have negative (reducing) impact on the emission levels in the case of developed economies while they have positive impact in the case of developing economies. These sectors exert significant effects on energy consumption of countries as well. Results confirm that developed countries are more successful in energy conservation policies compared to developing countries. Therefore, authorities in developing countries need to implement conservation policies effectively by mainly encouraging and supporting investments in alternative energy uses in order to prevent increases in emission levels through expansion in financial and trade sectors.

Smart energy meters generate real time, high frequency data which can foster demand management and response of consumers and firms, with potential private and social benefits. However, proper statistical techniques are needed to make sense of this large amount of data and translate them into usable recommendations. Here, we apply Functional Data Analysis (FDA), a novel branch of Statistics that analyses functions-to identify drivers of residential electricity load curves. We evaluate a real time feedback intervention which involved about 1000 Italian households for a period of three years. Results of the FDA modelling reveal, for the first time, daytime-indexed patterns of residential electricity consumption which depend on the ownership of specific clusters of electrical appliances and an overall reduction of consumption after the introduction of real time feedback, unrelated to appliance ownership characteristics., Competing Interests: The authors have declared that no competing interests exist.

Distributed power grids generally contain multiple diverse types of distributed generators (DGs). Traditional particle swarm optimization (PSO) and simulated annealing PSO (SA-PSO) algorithms have some deficiencies in site selection and capacity determination of DGs, such as slow convergence speed and easily falling into local trap. In this paper, an improved SA-PSO (ISA-PSO) algorithm is proposed by introducing crossover and mutation operators of genetic algorithm (GA) into SA-PSO, so that the capabilities of the algorithm are well embodied in global searching and local exploration. In addition, diverse types of DGs are made equivalent to four types of nodes in flow calculation by the backward or forward sweep method, and reactive power sharing principles and allocation theory are applied to determine initial reactive power value and execute subsequent correction, thus providing the algorithm a better start to speed up the convergence. Finally, a mathematical model of the minimum economic cost is established for the siting and sizing of DGs under the location and capacity uncertainties of each single DG. Its objective function considers investment and operation cost of DGs, grid loss cost, annual purchase electricity cost, and environmental pollution cost, and the constraints include power flow, bus voltage, conductor current, and DG capacity. Through applications in an IEEE33-node distributed system, it is found that the proposed method can achieve desirable economic efficiency and safer voltage level relative to traditional PSO and SA-PSO algorithms, and is a more effective planning method for the siting and sizing of DGs in distributed power grids.

Extended stochastic impact by regression on population, affluence, and technology model incorporating ridge regression was used to analyze the driving mechanism of energy-related CO 2 emissions in Kazakhstan during 1992-2014. The research period was divided into two stages based on GDP of Kazakhstan in 1991 (85.70 × 10 9 dollars), the first stage (1992-2002), GDP < 85.70 × 10 9 dollars, the stage of economic recovery; the second stage (2003-2014), GDP > 85.70 × 10 9 dollars, the stable economic development stage. The results demonstrated that (1) population scale and the technological improvement were the dominant contributors to promote the growth of the CO 2 emissions during 1992-2014 in Kazakhstan. (2) Economic growth and industrialization played more positive effect on the increase of the CO 2 emissions in the stable economic development stage (2003-2014) than those in the stage of economic recovery (1992-2002). The proportion of the tertiary industry, the trade openness, and foreign direct investment were transformed from negative factors into positive factors in the stable economic development stage (2003-2014). (3) Due to the over-urbanization of Kazakhstan before the independence, the level of urbanization continued to decline, urbanization was the first factor to curb CO 2 emissions during 1992-2014. Finally, some policy recommendations are put forward to reduce energy-related carbon emissions.

This study focuses to investigate the relationship between globalization and the ecological footprint for Malaysia from 1971 to 2014. The results of the Bayer and Hanck cointegration test and the ARDL bound test show the existence of cointegration among variables. The findings disclose that globalization is not a significant determinant of the ecological footprint; however, it significantly increases the ecological carbon footprint. Energy consumption and economic growth stimulate the ecological footprint and carbon footprint in Malaysia. Population density reduces the ecological footprint and carbon footprint. Further, financial development mitigates the ecological footprint. The causality results disclose the feedback hypothesis between energy consumption and economic growth in the long run and short run.

This paper investigates the impact of tourism investments on energy efficiency across the transportation and residential sectors of 32 Organization for Economic Co-operation and Development economies. Using annual data from 1995 to 2012, we employ various panel econometric techniques to achieve the study objectives. Given the nature of variables, the paper applies panel autoregressive distributed lag models to estimate the long-run elasticities of energy intensity. The long-run estimates confirm that tourism investments play an essential role in improving energy efficiency across the transportation and residential sectors. Furthermore, the results show that both the foreign direct investment inflows and trade openness also play a considerable role in reducing energy uses across these sectors. Finally, the findings suggest that the tourism investments Granger cause energy efficiency of transportation and residential sectors in the short-run. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth., Competing Interests: The authors have declared that no competing interests exist.

With the revitalization of the old industrial bases in Northeast China, the development of the energy industry is particularly significative. The purpose of this paper is analyzing the decoupling of carbon emissions and placing emphasis on Liaoning's energy industry. The researchers used the logarithmic mean Divisia index (LMDI) decompose model to take into account carbon emissions in each energy industry and used the Tapio decoupling model from 2000 to 2015 to seek the decoupling states. The main completion of this study are as follows: (1) The EGH and OPC industry are the dominating components of the carbon emissions of the energy industry. The coal and crude oil accounted for 95% of energy industrial consumption; there is great potential for electricity to replace coal and crude oil. (2) The direction of the changes in economic growth, investment structure, investment dependence, and energy structure is the same as industrial carbon emissions. Meanwhile, energy intensity and energy technology are the opposite during the period. (3) The CMW and PGE industry occurred strong decoupling between carbon emissions and economic output since 2005; there is weak decoupling state in other industry. And the PGE and OPC industry occurred recessive coupling and weak negative decoupling between carbon emissions and energy intensity except 2011 and 2012.

The role of energy cannot be passed over in the process of economic growth and development in any economy. China consumes colossal quantity of energy; thus, the central objectives of this study is to empirically evaluate the linkages among energy use, environment by CO 2 emissions, human health by health expenditures, Foreign Direct Investment (FDI) inflows, and real GDP per capita used for economic growth over the period of 1995-2016 for China. The nature of the data directed to employ the Canonical cointegrating regression (CCR) method for unknown parameter estimation. Four equations have estimated namely for FDI, health, environment, and economic growth. The result for China during the period under the study reveals that energy consumption has significant positive impact on FDI, health, environment, and economic growth. The study results suggest that policy makers need to chalk out effective policy for effective utilization of energy so as to encourage permissible economic growth and development in China.

This research seeks to enhance the current literature by exploring the nexus among environmental contamination, economic growth, energy use, and foreign direct investment in 6 selected sub-Saharan African nations for a time of 34 years (1980-2014). By applying panel unit root (CADF and CIPS, cross-sectional independence test), panel cointegration (Pedroni and Kao cointegration test, panel PP, panel ADF), Hausman poolability test, and an auto-regressive distributed lag procedure in view of the pooled mean group estimation (ARDL/PMG), experimental findings disclose that alluding to the related probability values, the null hypothesis of cross-sectional independence for all variables is rejected because they are not stationary at levels but rather stationary at their first difference. The variables are altogether integrated at the same order I(1). Findings revealed that there is a confirmation of a bidirectional causality between energy use and CO 2 in the short-run and one-way causality running from energy use to CO 2 in the long run. There is additionally a significant positive outcome and unidirectional causality from CO 2 to foreign direct investment in the long run yet no causal relationship in the short run. An increase in energy use by 1% causes an increase in CO 2 by 49%. An increase in economic growth by 1% causes an increment in CO 2 by 16% and an increase in economic growth squared by 1% diminishes CO 2 by 46%. The positive and negative impacts of economic growth and its square approve the EKC theory. To guarantee sustainable economic development goal, more strict laws like sequestration ought to be worked out, use of sustainable power source ought to be stressed, and GDP ought to be multiplied to diminish CO 2 by the utilization of eco-technology for instance carbon capturing, to save lives and also to maintain a green environment.

Climate change has become a global phenomenon due to its threat to sustainable development. However, economic development plays a complementary role in both climate change and sustainability. Thus, the environmental Kuznets curve hypothesis is critical to climate change policy formulation and development strategies. Accordingly, this study examined the validity of environmental Kuznets curve hypothesis by investigating the relationship between economic growth, energy consumption, financial development, and ecological footprint for the period from 1977 to 2013 in 11 newly industrialized countries. For this purpose, the study employed both augmented mean group (AMG) estimator and heterogeneous panel causality method which are suitable for dependent and heterogeneous panels. The results of the estimator show that there is an inverted U-shaped relationship between economic growth and ecological footprint. According to the causality test results, it is concluded that there is bi-directional causality between economic growth and ecological footprint., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Energy is a foundation for a city to create economic wealth, satisfy people's desires, and achieve benefits. However, the increasing mismatch between energy supply and demand and the worsening of environmental pollution have highlighted the importance of improving urban energy performance, so the number of studies related to urban energy performance evaluation is increasing. Based on describing the authors, numbers, regional sources, and themes of these studies, this paper reviews and analyzes the conceptions, evaluation indicators, influencing factors, evaluation methods, and evaluation systems related to urban energy performance. Most countries have expressed concern about this topic. Researchers in China, Belgium, and the USA have had the most achievements and collaborations. The concept of urban energy performance further extends to a comprehensive performance. It is measured based on an input-output process. In addition to the original evaluation indicators, new desirable outputs and undesirable outputs are included. Industrial structure, energy price, population density, home car ownership, climate factors, Gini coefficient, health expenditure level, and unemployment rate are regarded as influencing factors. Therefore, a new framework of evaluation indicators and influencing factors is constructed. Stochastic frontier analysis (SFA) and data envelopment analysis (DEA) are commonly used to evaluate. With changes in conceptions, evaluation indicators, and influencing factors, the evaluation method should rather focus on measuring multiple input-output variables, determining the evaluation results and the impacts of factors at the same analysis stage, and highlighting policy orientations. As an important management tool, the evaluation system would continue to be studied and developed.

Energy cooperation has been emphasized strongly in the Belt and Road (B&R) initiative. Therefore, the energy efficiency of China has attracted much attention from experts. However, relevant studies are still insufficient. This paper analyzes the total factor energy efficiency (TFEE) and its influencing factors of 17 B&R key regions from 2005 to 2015. We use the ratio of target energy input and actual energy input to calculate the regional TFEE under environmental constraints. The Malmquist index and the Tobit model are applied to investigate the internal and external influences of TFEE. Measurement analysis shows that the TFEE of the B&R key regions has not improved in recent years and it is unbalanced during the study period. Regions in the east area have the highest TFEE; regions in the west area have the second high TFEE; and regions in the north area have the lowest TFEE. Regression analysis shows that for the B&R key regions, technical changes, coal consumption, research and development, and environmental pollution have mainly negative effects on TFEE; pure efficiency changes, scale efficiency changes, economic structure, opening up, and government finance have mainly positive effects on TFEE. Finally, precise policy implications are proposed.

This paper investigated the impact of urbanization on residential energy consumption (REC) in China by taking cognizance of the levels of income, urbanization and urban density. Threshold analyses were employed to investigate the nonlinear relationships based on the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) framework using a balanced panel dataset of 29 provinces of China over the period of 1998-2014. The common correlated effects mean group estimator (CCEMG) was used to address time-series cross-section (TSCS) issues. The results confirmed the existence of the nonlinear relationship between urbanization and REC in China. The impact of urbanization on REC varied at different economic development levels and urbanization levels. Specifically, urbanization decreased REC at the stage that per capita disposable income of urban residents (PDI) less than 2615 USD, while it increased REC at the stage that PDI higher than 2615 USD. Similarly, urbanization decreased REC at the stage that urbanization rate lower than 55.31% and increased REC after urbanization rate exceeded 55.31%. This study did not find evidence to support the urban environmental transition theory, indicating there was still no region in China had stepped into the win-win stage of urbanization and energy consumption. Furthermore, the nonlinear impact of urban density on REC was estimated and the results indicated that urban density exerted a positive effect on REC when urban density was lower than 808 inhabitants per square kilometer, while it was no longer relevant to REC after that threshold point. Based on these results, the corresponding countermeasures and suggestions to achieve low-carbon urbanization were put forward.

Certain sectors and paths along supply chains play a critical role in climate change mitigation. We develope a consumption-based framework, which combines input-output analysis, a power-of-pull approach and structural path analysis, and applied it to supply chain networks derived from 2010 and 2012 Jing-Jin-Ji interregional input-output tables. The aim of this study is to identify (1) the key economic sectors for controlling carbon emissions and their changes, (2) the critical directions from a carbon-pulling sector to the emissions of key economic sectors, and (3) the paths with the largest carbon emissions flux in these critical directions. Our results show that the key sectors are from Hebei and Tianjin, more concentrated in Hebei. Most sectors have the largest pulling power over their own carbon emissions, and within-region connections dominated in the emission network, with a stronger tie between Beijing and the other two regions. Critical paths along carbon-pulling directions are located in tiers 0 and 1. Our framework can provide new insight into the creation of carbon emissions control policies., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

This paper explores the direct impact of new technology on the energy intensity in China. The autoregressive distributed lag (ARDL) bounds test approach to cointegration is utilised over the extended period of 1985-2013. The variables found cointegrated and confirm the long-run association among all the underlying vectors. Furthermore, the results of long- and short-run analysis reveal that new technology spurs energy intensity in China. A 1% increase in technological innovation boosts energy intensity by 0.4% and 0.03% in the long and short run, respectively. The findings suggest that the establishment of smart grids and solar energy parks followed by the reforms in energy sector is yet to achieve plausible efficiency in China. The existing investment and innovation policy reforms are insufficient to assist the energy sector to cope up with the country's exceptional economic growth trend. Unlike other studies, this paper accommodates structural break in the series. During sensitivity analysis, the model is found stable. Hence, the findings possess important policy implications for China and open up new discussion in the field.

This study examines the relationship between energy consumption and economic growth based on three models in China covering the period of 1982-2015. From the Ng-Perron (NP) and Zivot-Andrews (ZA) unit root test, each variable has no unit root in the first difference. Based on Johansen multivariable co-integration test and autoregressive distributed lag (ARDL) bounds test, the co-integrating relationship existed between selected variables. Moreover, dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), and ARDL estimates are used to estimate the coefficients of each variable, which presents that any increasing of each kinds of energy sources can increase China's economic growth in the long term. Additionally, the vector error correction model (VECM) Granger causality test based on three models is investigated. Some implications based on the empirical results are given.

Pollutant abatement systems are widely applied in the coal-fired power sector, and the energy consumption is considered an important part of the auxiliary power. An energy consumption analysis and assessment model of pollutant abatement systems in a power unit was developed based on the dynamic parameters and technology. The energy consumption of pollutant abatement systems in a 1000-MW coal-fired power unit that meets the ultra-low emission limits and the factors of operating parameters, including unit load and inlet concentration of pollutants, on the operating power were analyzed. The results show that the total power consumption of the pollutant abatement systems accounted for 1.27% of the gross power generation during the monitoring period. The wet flue gas desulfurization (WFGD) system consumed 67% of the rate, whereas the selective catalytic reduction (SCR) and electrostatic precipitator (ESP) systems consumed 8.9% and 24.1%, respectively. The power consumption rate of pollutant abatement systems decreased with the increase of unit load and increased with the increase of the inlet concentration of pollutants. The operation adjustment was also an effective method to increase the energy efficiency. For example, the operation adjustment of slurry circulation pumps could promote the energy-saving operation of the WFGD system., Implications: The application of pollutant abatement technologies increases the internal energy consumption of the power plant, which will lead to an increase of power generation costs. The real-time energy consumption of the different pollutant abatement systems in a typical power unit is analyzed based on the dynamic operating data. Further, the influence of different operating parameters on the operating power of the system and the possible energy-saving potential are analyzed.

The Central American nations of Guatemala, Honduras and Nicaragua are among the poorest in the Americas. While the fraction of population dependent on solid fuels has declined in these nations over the last 25 years, the number of people using them has risen. Here, we first assess current patterns of cooking energy use in these nations. We then apply a discrete model of household cooking choices and demand to simulate future pathways of clean cooking uptake and the outlook for achieving target 7.1 of the Sustainable Development Goals (SDG), which aims to ensure universal access to affordable, reliable and modern energy services by 2030. We find that by 2030, ensuing income growth is likely to enable 90% of urban populations in these nations to switch to using modern cooking energy services. However, without supporting policies, between 40% to 50% of rural Guatemalans and Hondurans, while over two-thirds of rural Nicaraguans, are likely to find clean fuels or stoves unaffordable in 2030. A targeted subsidy on modern fuels, like liquid petroleum gas (LPG), is the most effective policy mechanism we studied that could provide such support. A 50% subsidy policy on LPG targeted to the rural and urban poor population could, by 2030, make cooking with LPG affordable to an additional 7.3 million people in these countries. We estimate that such a policy would cost about $250 million per year and would have negligible greenhouse gas emissions impacts. Such a policy could also have significant health benefits, preventing about 8,890 premature deaths annually from reduced exposure to cooking-related household pollution in 2030., Competing Interests: The authors have declared that no competing interests exist.

This paper estimates the efficiency of the power generation sector in the USA by using Window Data Envelopment Analysis (W-DEA). We integrate radial and non-radial efficiency measurements in DEA using the hybrid measure while we extend the proposed model by considering good and undesirable outputs as separable and non separable. Then in the second stage, we perform parametric and non-parametric econometric techniques in order to model the relationship between the calculated environmental efficiencies and economic growth in attaining sustainability. Our empirical findings indicate a stable N-shape relationship between environmental efficiency and regional economic growth in the case of global and total pollutants but an inverted N-shape in the case of local pollutants. This implies that attention is required when considering local and global pollutants and the extracted environmental efficiency scores. A clear message to policy makers and government officials is that climate change which calls for economic, environmental and social concern should be analyzed according to its dispersion and regional dimension., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

During the last decade, Central Europe became a cynosure for the world for its unparalleled public support for renewable energy. For instance, the production of electricity from purpose-grown biomass received approximately twice the amount in subsidies as that produced from biowaste. Moreover, the guaranteed purchase price of electricity from solar panels was set approximately five times higher than that from conventional sources. This controversial environmental donation policy led to the devastation of large areas of arable land, a worsening of food availability, unprecedented market distortions, and serious threats to national budgets, among other things. Now, the first proposals to donate the purchase price of electric vehicles (and related infrastructure) from national budgets have appeared for public debate. Advocates of these ideas argue that they can solve the issue of electricity overproduction, and that electric vehicles will reduce emissions in cities. However, our analysis reveals that, as a result of previous scandals, environmental issues have become less significant to local citizens. Given that electric cars are not yet affordable for most people, in terms of local purchasing power, this action would further undermine national budgets. Furthermore, while today's electromobiles produce zero pollution when operated, their sum of emissions (i.e. global warming potential) remains much higher than that of conventional combustion engines. Therefore, we conclude that the mass usage of electromobiles could result in the unethical improvement of a city environment at the expense of marginal regions.

We investigated the impact of a sustainable development technology on the macroeconomic variables in a small economy utilizing a case study with a stochastically improving energy saving technology and a stochastically increasing energy price. The results show the technological displacement effects of energy saving technology are stronger, but there are more ambiguous instantaneous returns to physical capital. However, the energy saving technology's displacement effects might not affect the conditions under which the Harberger-Laursen-Metzler (HLM) effect holds. The effects of rising energy prices on bonds are stronger, and there are more ambiguous instantaneous returns, but the conditions under which the HLM effect holds are different., Competing Interests: References

This paper argues computable general equilibrium model and assess impact of energy taxation on economy, environmental and public health quality in Tianjin. In order to investigate different energy taxation based on medical cost and labor loss, the computable general equilibrium model integrating with input-output table and social accounting matrix (SAM) was constructed. The medical expense caused by air pollution of Tianjin in 2007 is 396 million yuan and death for 18104 people, which accounted for the total GDP and population 0.754‰ and 1.6‰, respectively. The results show that the enery taxes levy can improve the GDP, but it is only slightly. The energy taxes have adverse impact on energy sector because that the energy cost is increased. The scale of production is reduced, and the capital and labor resources are transferred to low energy consumption low emissions sector. The energy tax levy can reduce air pollutants concentration and improve air environmental quality. The PM 10 , SO 2 and NO 2 concentration in the energy taxes 5%-30% was reduced by 0.24%-0.24%, 0.09-0.52% and 0.29%-0.52% respectively. The medical expense has little impact on GDP, but labor loss has a certain effect on GDP. For higher energy taxes rate, the health effects on GDP can reach 0.06%-0.16%. This simultaneous economic and environmental improvement and health effect would thus have positive implications regarding energy taxes of the country., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months.

This study examines the three-way linkage relationships between CO 2 emission, energy consumption and economic growth in Malaysia, covering the 1975-2015 period. An autoregressive distributed lag approach was employed to achieve the objective of the study and gauged by dynamic ordinary least squares. Additionally, vector error correction model, variance decompositions and impulse response functions were employed to further examine the relationship between the interest variables. The findings show that economic growth is neither influenced by energy consumption nor by CO 2 emission. Energy consumption is revealed to be an increasing function of CO 2 emission. Whereas, CO 2 emission positively and significantly depends on energy consumption and economic growth. This implies that CO 2 emission increases with an increase in both energy consumption and economic growth. Conclusively, the main drivers of CO 2 emission in Malaysia are proven to be energy consumption and economic growth. Therefore, renewable energy sources ought to be considered by policy makers to curb emission from the current non-renewable sources. Wind and biomass can be explored as they are viable sources. Energy efficiency and savings should equally be emphasised and encouraged by policy makers. Lastly, growth-related policies that target emission reduction are also recommended.

Municipal infrastructure is a fundamental facility for the normal operation and development of an urban city and is of significance for the stable progress of sustainable urbanization around the world, especially in developing countries. Based on the municipal infrastructure data of the prefecture-level cities in China, municipal infrastructure development is assessed comprehensively using a FA (factor analysis) model, and then the stochastic model STIRPAT (stochastic impacts by regression on population, affluence and technology) is examined to investigate key factors that influence municipal infrastructure of cities in various stages of urbanization and economy. This study indicates that the municipal infrastructure development in urban China demonstrates typical characteristics of regional differentiation, in line with the economic development pattern. Municipal infrastructure development in cities is primarily influenced by income, industrialization and investment. For China and similar developing countries under transformation, national public investment remains the primary driving force of economy as well as the key influencing factor of municipal infrastructure. Contribution from urbanization and the relative consumption level, and the tertiary industry is still scanty, which is a crux issue for many developing countries under transformation. With economic growth and the transformation requirements, the influence of the conventional factors such as public investment and industrialization on municipal infrastructure development would be expected to decline, meanwhile, other factors like the consumption and tertiary industry driven model and the innovation society can become key contributors to municipal infrastructure sustainability.

Future energy systems will be determined by the increasing relevance of solar and wind energy. Crude oil and gas prices are expected to increase in the long run, and penalties for CO 2 emissions will become a relevant economic factor. Solar- and wind-powered electricity will become significantly cheaper, such that hydrogen produced from electrolysis will be competitively priced against hydrogen manufactured from natural gas. However, to handle the unsteadiness of system input from fluctuating energy sources, energy storage technologies that cover the full scale of power (in megawatts) and energy storage amounts (in megawatt hours) are required. Hydrogen, in particular, is a promising secondary energy vector for storing, transporting, and distributing large and very large amounts of energy at the gigawatt-hour and terawatt-hour scales. However, we also discuss energy storage at the 120-200-kWh scale, for example, for onboard hydrogen storage in fuel cell vehicles using compressed hydrogen storage. This article focuses on the characteristics and development potential of hydrogen storage technologies in light of such a changing energy system and its related challenges. Technological factors that influence the dynamics, flexibility, and operating costs of unsteady operation are therefore highlighted in particular. Moreover, the potential for using renewable hydrogen in the mobility sector, industrial production, and the heat market is discussed, as this potential may determine to a significant extent the future economic value of hydrogen storage technology as it applies to other industries. This evaluation elucidates known and well-established options for hydrogen storage and may guide the development and direction of newer, less developed technologies.

Objective: To evaluate associations between changing energy prices and US hospital patient outcomes., Methods: Generalized estimating equations were used to analyze relationships between changes in energy prices and subsequent changes in hospital patient outcomes measures for the years 2008 through 2014. Patient outcomes measures included 30-day acute myocardial infarction, heart failure, and pneumonia mortality rates, and 30-day acute myocardial infarction, heart failure, and pneumonia readmission rates. Energy price data included state average distillate fuel, electricity and natural gas prices, and the US average coal price. All of the price data were converted to 2014 dollars using Consumer Price Index multipliers., Results: There was a significant positive association between changes in coal price and both short-term ( P = 0.029) and long-term ( P = 0.017) changes in the 30-day heart failure mortality rate. There was a similar significant positive association between changes in coal price and both short-term ( P <0.001) and long-term ( P = 0.002) changes in the 30-day pneumonia mortality rate. Changes in coal prices also were positively associated with long-term changes in the 30-day myocardial infarction readmission rate ( P < 0.001). Changes in coal prices ( P = 0.20), natural gas prices ( P = 0.040), and electricity prices ( P = 0.040) were positively associated with long-term changes in the 30-day heart failure readmission rate., Conclusions: Changing energy prices are associated with subsequent changes in hospital mortality and readmission measures. In light of these data, we encourage hospital, health system, and health policy leaders to pursue patient-support initiatives, energy conservation programs, and reimbursement policy strategies aimed at mitigating those effects.

In the U.S., the total amount of municipal solid waste is continuously rising each year. Millions of tons of solid waste and scum are produced annually that require safe and environmentally sound disposal. The availability of a zero-cost energy source like municipal waste scum is ideal for several types of renewable energy technologies. However, the way the energy is produced, distributed and valued also contributes to the overall process sustainability. An economic screening method was developed to compare the potential energy and economic value of three waste-to-energy technologies; incineration, anaerobic digestion, and biodiesel. A St. Paul, MN wastewater treatment facility producing 3175 "wet" kilograms of scum per day was used as a basis of the comparison. After applying all theoretically available subsidies, scum to biodiesel was shown to have the greatest economic potential, valued between $491,949 and $610,624/year. The incineration of scum yielded the greatest reclaimed energy potential at 29billion kilojoules/year., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The global atmospheric warming due to increased emissions of carbon dioxide (CO2) has attracted great attention in the last two decades. Although different CO2 capture and storage platforms have been proposed, the utilization of captured CO2 from industrial plants is progressively prevalent strategy due to concerns about the safety of terrestrial and aquatic CO2 storage. Two utilization forms were proposed, direct utilization of CO2 and conversion of CO2 to chemicals and energy products. The latter strategy includes the bioelectrochemical techniques in which electricity can be used as an energy source for the microbial catalytic production of fuels and other organic products from CO2. This approach is a potential technique in which CO2 emissions are not only reduced, but it also produce more value-added products. This review article highlights the different methodologies for the bioelectrochemical utilization of CO2, with distinctive focus on the potential opportunities for the commercialization of these techniques., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

When in port, ships burn marine diesel in on-board generators to produce electricity and are significant contributors to poor local and regional air quality. Supplying ships with grid electricity can reduce these emissions. We use two integrated assessment models to quantify the benefits of reducing the emissions of NOX, SO2, PM2.5, and CO2 that would occur if shore power were used. Using historical vessel call data, we identify combinations of vessels and berths at U.S. ports that could be switched to shore power to yield the largest gains for society. Our results indicate that, depending on the social costs of pollution assumed, an air quality benefit of $70-150 million per year could be achieved by retrofitting a quarter to two-thirds of all vessels that call at U.S. ports. Such a benefit could be produced at no net cost to society (health and environmental benefits would be balanced by the cost of ship and port retrofit) but would require many ships to be equipped to receive shore power, even if doing so would result in a private loss for the operator. Policy makers could produce a net societal gain by implementing incentives and mandates to encourage a shift toward shore power.

The objective of the study is to examine the impact of environmental indicators and air pollution on "health" and "wealth" for the low-income countries. The study used a number of promising variables including arable land, fossil fuel energy consumption, population density, and carbon dioxide emissions that simultaneously affect the health (i.e., health expenditures per capita) and wealth (i.e., GDP per capita) of the low-income countries. The general representation for low-income countries has shown by aggregate data that consist of 39 observations from the period of 1975-2013. The study decomposes the data set from different econometric tests for managing robust inferences. The study uses temporal forecasting for the health and wealth model by a vector error correction model (VECM) and an innovation accounting technique. The results show that environment and air pollution is the menace for low-income countries' health and wealth. Among environmental indicators, arable land has the largest variance to affect health and wealth for the next 10-year period, while air pollution exerts the least contribution to change health and wealth of low-income countries. These results indicate the prevalence of war situation, where environment and air pollution become visible like "gun" and "bullet" for low-income countries. There are required sound and effective macroeconomic policies to combat with the environmental evils that affect the health and wealth of the low-income countries.

In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry., (© 2015 Authors; published by Portland Press Limited.)