Department of Multimedia and Game Science, Lunghwa University of Science and Technology, 300, Sec. 1, Wanshou Rd., Guishan District, Taoyuan City, 333, Taiwan, ROC.
Department of Economics, Soochow University, 56, Kueiyang St., Sec. 1, Taipei, 100, Taiwan, ROC.
J Environ Manage. 2022 Sep 1;317:115401. doi: 10.1016/j.jenvman.2022.115401. Epub 2022 Jun 1.
This study employed dynamic three-stage network data envelopment analysis (DEA), considering parallel production in the agricultural and industrial sectors, to assess the impact of greenhouse gas emissions on the climate change and natural disaster stages. The results revealed the following: (1) The dynamic overall efficiencies of more countries are decreasing than are increasing. The seven countries with the poorest overall efficiency ranking (Myanmar, Vietnam, Thailand, Bangladesh, the Philippines, Pakistan, and India) are mostly located in Southeast Asia. (2) The number of countries that maintained low efficiency over the long term is greater than those that retained high efficiency over the long term. Myanmar, Mexico, India, the Philippines, Thailand, and Vietnam maintained efficiency scores below 0.5, whereas South Korea, Japan, China, and New Zealand maintained efficiency scores above 0.8. (3) More than one-third of countries exhibited declines in efficiency over time, and half were European countries. Less than one-third of countries maintained their efficiency, and less than one-third of countries gradually improved. (4) Approximately half of the countries' efficiency scores were lower than the global average. The efficiency scores of the industrial sector exhibited a greater room for improvement on the input factors than did those of the agricultural sector. (5) Total factor energy efficiency analysis revealed that methane emissions and CO emissions have a similar level but large room for improvement across countries. Improving input factors in the production stage can ultimately mitigate inefficiencies in the climate change and natural disaster stages. There are still other important factors related to climate change, such as sea surface temperature, forest areas, or air pollution indicators, that could be considered in future research. The occurrence of global disasters could also be discussed in groups according to the region where the countries are located in the future.
本研究采用动态三阶段网络数据包络分析(DEA),考虑农业和工业部门的平行生产,评估温室气体排放对气候变化和自然灾害阶段的影响。结果表明:(1)更多国家的动态综合效率呈下降趋势,而非上升趋势。综合效率排名最差的七个国家(缅甸、越南、泰国、孟加拉国、菲律宾、巴基斯坦和印度)大多位于东南亚。(2)长期保持低效率的国家数量多于长期保持高效率的国家数量。缅甸、墨西哥、印度、菲律宾、泰国和越南的效率得分均低于 0.5,而韩国、日本、中国和新西兰的效率得分均高于 0.8。(3)超过三分之一的国家的效率随时间推移呈下降趋势,其中一半是欧洲国家。不到三分之一的国家保持了效率,不到三分之一的国家逐渐提高了效率。(4)大约一半的国家的效率得分低于全球平均水平。工业部门的效率得分在投入因素方面有更大的改进空间,而农业部门的效率得分则较低。(5)全要素能源效率分析表明,各国的甲烷排放和 CO 排放水平相似,但仍有很大的改进空间。改进生产阶段的投入因素最终可以减轻气候变化和自然灾害阶段的效率低下问题。还有其他与气候变化相关的重要因素,如海面温度、森林面积或空气污染指标,未来的研究中可以考虑这些因素。未来还可以根据各国所在地区将全球灾害的发生情况分组进行讨论。