温室气体减排已成为世界各国的共识,碳足迹分析作为温室气体管理的工具,在过去二十多年来发展迅速,然而国内外现有研究缺乏对其演化发展的归纳总结。因此,本文选取Web of science收录的期刊数据为研究对象,检索出1996—2017年有关碳足迹的相关文献8840篇,并对此进行了定性和定量分析。结果表明:①美国对碳足迹文献的贡献最大,拥有2275篇出版物以及最高的h指数(83)和被引频次(34803);②中国和印度等发展中国家近10年发文量增长显著,都位于全球发文量前十的国家中;③荷兰的h指数占总出版物的比重最大;④加利福尼亚大学是该领域最具生产力的机构,拥有222篇出版物,且国际合作水平显著。最后,论文将碳足迹研究分为三个阶段,基于关键词共现分析,厘清碳足迹研究的热点变化,并预测其未来研究趋势。 相似文献
Digital surface models (DSMs) extracted from very high resolution (VHR) satellite stereo images are becoming more and more important in a wide range of geoscience applications. The number of software packages available for generating DSMs has been increasing rapidly. The main goal of this work is to explore the capabilities of VHR satellite stereo pairs for DSMs generation over different land-cover objects such as agricultural plastic greenhouses, bare soil and urban areas by using two software packages: (i) OrthoEngine (PCI), based on a hierarchical subpixel mean normalized cross correlation matching method, and (ii) RPC Stereo Processor (RSP), with a modified hierarchical semi-global matching method. Two VHR satellite stereo pairs from WorldView-2 (WV2) and WorldView-3 (WV3) were used to extract the DSMs. A quality assessment on these DSMs on both vertical accuracy and completeness was carried out by considering the following factors: (i) type of sensor (i.e., WV2 or WV3), (ii) software package (i.e., PCI or RSP) and (iii) type of land-cover objects (plastic greenhouses, bare soil and urban areas). A highly accurate light detection and ranging (LiDAR) derived DSM was used as the ground truth for validation. By comparing both software packages, we concluded that regarding DSM completeness, RSP produced significantly (p < 0.05) better scores than PCI for all the sensors and type of land-cover objects. The percentage improvement in completeness by using RSP instead of PCI was approximately 2%, 18% and 26% for bare soil, greenhouses and urban areas respectively. Concerning the vertical accuracy in root mean square error (RMSE), the only factor clearly significant (p < 0.05) was the land cover. Overall, WV3 DSM showed slightly better (not significant) vertical accuracy values than WV2. Finally, both software packages achieved similar vertical accuracy for the different land-cover objects and tested sensors. 相似文献
Current country-level commitments under the Paris Agreement fall short of putting the world on a required trajectory to stay below a 2°C temperature increase compared to pre-industrial levels by the end of the century. Therefore, the timing of increased ambition is hugely important and as such this paper analyses the impact of both the short and long-term goals of the Paris Agreement on global emissions and economic growth. Using the hybrid TIAM-UCL-MSA model we consider the achievement of a 2°C target against a baseline of the Nationally Determined Contributions (NDCs) while also considering the timing of increased ambition of the NDCs by 2030 and the impacts of cost reductions of key low-carbon technologies. We find that the rate of emissions reduction ambition required between 2030 and 2050 is almost double when the NDCs are achieved but not ratcheted up until 2030, and leads to lower levels of economic growth throughout the rest of the century. However, if action is taken immediately and is accompanied by increasingly rapid low-carbon technology cost reductions, then there is almost no difference in GDP compared to the path suggested by the current NDC commitments.
Key policy insights
Delaying the additional action needed to achieve the 2°C target until 2030 is shown to require twice the rate of emissions reductions between 2030 and 2050.
Total cumulative GDP over the century is lower when additional action is delayed to 2030 and therefore has an overall negative impact on the economy, even without including climate change damages.
Increased ratcheting of the NDC commitments should therefore be undertaken sooner rather than later, starting in conjunction with the 2023 Global Stocktake.
Early action combined with cost reductions in key renewable energy technologies can reduce GDP losses to minimal levels (<1%).
A 2°C future with technological advancements is clearly possible for a similar cost as a 3.3°C world without these advances, but with lower damages and losses from climate change.