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Given the economic growth and energy consumption patterns, most countries are striving to solve the problems of CO 2 emissions reduction to achieve sustainable development. This paper employs an improved DEA model to measure energy and environmental efficiency for some selected countries in central and western Europe. In addition, the DEA window evaluation technique is applied to measure cross-sectional efficiency using two inputs (energy consumption, labor force), a desirable output (gross domestic product), and an undesirable output (CO 2 emission) for the period from 2010 to 2014. The study finds that the UK ranks the highest position in term of energy and environmental efficiency. This shows that the UK has more effective policies regarding energy efficiency, consumption, production, import and energy intensity measures for sustainable economic growth as well as environmental protection. Ireland is the second-best country after the United Kingdom. The efficiency scores of the two countries are 0.99 and 0.89 respectively. On the empirical outcomes, this study suggests effective reforms in energy sector for countries with less energy efficiency that are still facing the problem of environmental degradation. •There is an urgent need to balance sustainable development and economic growth. •DEA window technique was applied to measure cross-sectional efficiency. •Ireland is second best country after UK with energy and environmental efficiency. •The market-centric structure would be more useful and advantageous for the society. •We provide recommendations about emission reduction with moderate economic growth. [ABSTRACT FROM AUTHOR]

China is experiencing unprecedented industrialization and urbanization which promotes the rapid growth of iron resource consumption and in-use stock. The material flow analysis (MFA) model and the average use life method were applied to analyze China's iron in-use stock (IIUS), and the IIUS reached 7.07 billion tons in 2016 in the reference scenario. Three driving factors of the intensity of IIUS were analyzed. Among them, the per capita IIUS was rising, and it was 5.11 t/cap in 2016 in the reference scenario. In addition, the per capita crude steel output has stabilized, which was 0.58 t/cap in 2016. The intensity of crude steel use was declining and showed the inverted U-shape. The decoupling indicator was applied to analyze the relationship between IIUS and economic growth. The decoupling of IIUS from economic growth was later than that of actual iron consumption, and the IIUS did not decoupling from economic growth in recent years. The actual iron consumption has continued to decoupling from economic growth since 2010, and the decoupling indicator peaked at 1.76 in 2015. The future per capita IIUS was predicted in different scenario and the relationship between future IIUS and GDP was analyzed. The per capita IIUS will reach saturation in 2030–2040, and the intensity of IIUS also conforms to the inverted U-shape. ● China's actual iron consumption and iron in-use stock (IIUS) were analyzed. ● The driving factors of the intensity of IIUS were quantified. ● The decoupling indicator was first applied to analyze the relationship between IIUS and economic growth. ● China's per capita IIUS will reach saturation in 2030–2040 in different scenarios. [ABSTRACT FROM AUTHOR]

There is a significant challenge in resource management: the perceived trade-off between economic growth and ecosystem conservation. In this study, we integrate a variety of quantitative research methods and models, such as the ecosystem service value (ESV), interval parameter planning (IPP), Dyna-CLUE, and Monte Carlo methods, in an attempt to balance the ESV and economic benefits. The highest system benefits can be obtained, and uncertainty in the ecosystem assessment is considered. Taking the Pearl River Delta as the study area, the results show that when the GDP growth rate is less than 6%, the ESV in 2025 will be higher than the ESV in 2017. An interval approach (upper and lower bounds) is used. For a scenario with a 5% GDP growth rate, the ESV is RMB¥ [1.85, 20.79] × 109, which is more than the ESV of the scenario with a 9% GDP growth rate. When the GDP growth rates are 5% and 9%, the proportions of forestland are [61.5%, 61.7%] and [58%, 58.2%], respectively. Furthermore, spatialization was performed using the Dyna-CLUE model. In 2025, the simulated area of farmland is larger in some small regions with 9% GDP growth rate than it is in regions with 5% GDP growth rate, thus achieving a balance between occupation and compensation of regional farmland. By comparing ecosystem planning under different GDP growth rates, an optimized land-use allocation method can help decision makers balance system benefits and ecological risks, which can provide multiple options and specific locations for decision. Image 1 • A model was built to balance ecosystem services (ES) and economic benefits. • An evaluation system was built to assess the ESV in the lower and upper bounds. • Spatial differences in both ESV and land-use efficiency are considered. • An interval parameter planning (IPP) method and Dyna-CLUE model are integrated. • Decision makers are supported to balance system benefits and ecological risks. [ABSTRACT FROM AUTHOR]