The carbonate-free fraction of 20 surface sediments collected from the ultraslow-spreading Southwest Indian Ridge(SWIR) was studied by grain size analysis and mineralogical analysis with X-ray powder diffraction(XRD),stereo microscopy and scanning electron microscopy(SEM). The characteristics of the carbonate-free fraction of the sediments were obtained, and related influential factors were discussed. The results show that the mean grain size of this fraction is in 1.96Φ–8.19Φ, with poorly sorting and unimodal, bimodal or irregular bimodal distribution patterns. Four grain size end members of the fraction are derived with the End Member Model method. The finest end member EM1 shows a significant contribution of terrigenous materials of the aeolian input and sediment carried by the bottom current. End member EM2 with medium size mainly reflects sediment of a siliceous bioclast origin. EM3 and EM4 are interpreted as representing the coarser volcanic materials related to bedrock weathering or volcanic activities. Multi-provenance is the dominant factor controlling the grain size pattern of the carbonate-free fraction of the sediments in that area. In addition, sediment transport processes such as the bottom current and wind are the minor factors that influence the grain size distribution of the carbonate-free fraction sediments. 相似文献
To address the limitations of manually selecting aids to navigation (AtNs) on charts, a method for automatically selecting AtNs based on their spatial influence domains (SIDs) is proposed. First, the associations between the spatial attributes of an AtN are analyzed. Second, an SID of the AtN is defined, and a model of the SID is constructed based on the associations between the spatial attributes. Third, the importance of the location of the AtN is weighted based on the SID model. Fourth, an algorithm to automatically select AtNs based on the maximum coverage of the SIDS of preselected AtNs is developed. Finally, several AtNs are selected automatically using the algorithm. The experimental results demonstrate that (1) the proposed method can automatically select AtNs and the results comply with the requirements; (2) the automatic selection can eliminate the human-induced errors or the inconsistent results of manual selections from different operators; and (3) the efficiency of the proposed method is higher than that of current manual methods. 相似文献
Upon completion, China’s national emissions trading scheme (C-ETS) will be the largest carbon market in the world. Recent research has evaluated China’s seven pilot ETSs launched from 2013 on, and academic literature on design aspects of the C-ETS abounds. Yet little is known about the specific details of the upcoming C-ETS. This article combines currently understood details of China’s national carbon market with lessons learned in the pilot schemes as well as from the academic literature. Our review follows the taxonomy of Emissions Trading in Practice: A Handbook on Design and Implementation (Partnership for Market Readiness & International Carbon Action Partnership. (2016). Retrieved from www.worldbank.org): The 10 categories are: scope, cap, distribution of allowances, use of offsets, temporal flexibility, price predictability, compliance and oversight, stakeholder engagement and capacity building, linking, implementation and improvements.
Key policy insights
Accurate emissions data is paramount for both design and implementation, and its availability dictates the scope of the C-ETS.
The stakeholder consultative process is critical for effective design, and China is able to build on its extensive experience through the pilot ETSs.
Current policies and positions on intensity targets and Clean Development Mechanism (CDM) credits constrain the market design of the C-ETS.
Most critical is the nature of the cap. The currently discussed rate-based cap with ex post adjustment is risky. Instead, an absolute, mass-based emissions cap coupled with the conditional use of permits would allow China to maintain flexibility in the carbon market while ensuring a limit on CO2 emissions.