A study of stability of the seafloor foundation on a gently sloping continental shelf

Abstract

The possibility of seafloor failure under external loadings on a gently sloping continental shelf is controlled, to a large extent, by the geotechnical characters of subbottom sediments (e.g., shear strength, compressibility, and liquefaction potential) and structural factors (e.g., sedimentary stratification). By means of undis‐turbing coring, in‐situ acoustic measurement, and subbottom profiling, the authors conducted an investigation into the seafloor instabilities and possibilities of sediment slope failure within the continental shelf off the Pearl River mouth, which is one of the most important areas for offshore development in the northern South China Sea. Based on in‐situ and laboratory measurements and tests for sediment physical properties, static and dynamic behavior, and acoustic characteristics, the analyses indicate: (1) subbottom sediments that originated from terrigenous clay during the Pleistocene are compact and overconsolidated, and the mean sound velocity in such sediments is relatively high; (2) the maximum vertical bearing capacity of subbottom sediments is efficiently conservative on the safe side for dead loads of light structures, and the trench walls are stable enough while trenching to a depth of about 2 m below the seafloor under still water; and (3) it is quite improbable that the subbottom sediments liquefy under earthquake (M ≤ 6) or storm wave loading.     

Regional inequality,spatial spillover effects,and the factors influencing city-level energy-related carbon emissions in China

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation (Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club’ agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.     

Discrimination of Seafloor Sediment Properties by VWA

Analytical results of sound velocity and spectrum for seafloor sediment ore obtained by VWA (velocity-wave-amplitude) discrimination technique. Based on velocity-wave-amplitude, an understanding is gained of the physical condition and structural characteristics of seafloor sediment, which is combined with other geological information of the sedimentary layer to synthetically discriminate the properties of seafloor sediment. Experimental results show that, by using the relationship between sound velocity, wave form envelope, amplitude shape and size, and such parameters as sedimentary structure, microstructure, bedding, grain composition, mineral composition, and physical-mechanics, etc., the basic properties of the shallow surface seafloor sediment in the experimental sea area can be discriminated and the burial depth of traces of ancient marine transgression and regression events in the borehole cores of seafloor sediment can be divided, thus making an attempt of and contribution to the practice of acoustically remote-sensing and telemetering seafloor sediment.     

Physical Properties of Sediments on the Northern Continental Shelf of the South China Sea

Using physical (acoustical engineering mechanics and scanning electron microscope) and other technical methods, is study makes a comprehensive analysis of the structural characteristics and engineering mechanics properties of sediments, the sediment structure, microstructure and their classification characteristics and in the light of the physical-mechanical characteristic parameters, the relations between the grain contact, grain accumulation, and porosity with the physical-mechanical characteristics of sediment, and reports the relationship between the acoustic physical parameters and the stress-strain properties of sediment. Results show that there are six structural types in the shelf seabed sediment of the northern South China Sea, among which, the mixed contact structural type sediment has a higher compressive strength and a higher sound velocity than others, and that in the shallow seabed there exists a mesoscale structure with high and low velocity layers.     

美国对伊朗石油禁运与全球能源安全

2018年6月美国针对伊朗启动了史上最严厉的石油禁运政策,要求所有国家于11月停止从伊朗进口石油,否则相关国家和企业都将面临美国的经济制裁,并无意给予任何国家豁免权。当前,中国、日本、韩国、印度和欧盟等世界重要的石油进口国已经做出回应,除中国明确拒绝美国的单边制裁继续保持与伊朗的石油贸易外,其他主要石油进口国都大量削减从伊朗的石油进口。沙特阿拉伯等石油生产国也承诺通过石油增产来维护全球能源市场的稳定,以支持美国对伊朗的制裁。在经济全球化的大趋势下,美国对伊朗的石油禁运,势必引发全球能源市场的动荡,改变全球石油政治格局以及相关利益方的石油权益。这些方面会涉及到全球油价的波动、不同国家的石油安全与应对政策、世界能源贸易稳定与地缘政治格局的变动等。长期关注能源地缘政治的专家学者围绕美国对伊朗的石油禁运可能产生的影响发表观点,专家们认为美国此举是战略两难的困境,短期内对将会引起世界石油短缺及油价波动,甚至可能导致OPEC减产协议崩溃,改变世界主要进口国的进口规模以及来源结构,但对世界石油市场的长期影响有限。伊朗将寻求打折出售原油、替代港口出口以及多元化出口3条生存路径,目前最大的隐患是伊朗或将封锁霍尔木兹海峡,但是此举目前可能性不大。伊朗石油禁运具有长期性和复杂性,对中国既是机遇也是挑战,中国在“一带一路”倡议下与伊朗保持正常的石油贸易是双赢的选择,但需要谨慎对待由此引发的能源地缘政治的风险,提升能源安全应对的措施。期待各方观点对伊朗石油禁运引发的能源地缘政治格局以及中国的能源安全的解析,能够为相关政策制定者提供理论借鉴。     

中国县域住宅价格的空间差异特征与影响机制

以2014年中国2872个县级单元的住宅平均单价为基本数据,通过空间自相关和核密度函数分析中国住宅价格的差异格局、空间关联特征和分布形态,构建“住宅价格等级金字塔”;根据“需求+供给+市场”的三维理论视角建立包括5大住宅价格差异影响因素在内的价格模型,采用地理探测器分析全国及其区域子市场的影响因素强度差异,并探索其影响机制。结果表明：① 中国区域住宅价格呈现以行政等级性为主、空间集聚性为辅的双重差异格局,其空间关联与集聚性显著;② 中国住宅价格呈现出房价越高,区域越少,所居住城镇人口越少的“金字塔式”等级分布特征。③ 租房户比例、流动人口规模、住房支付能力、住房市场活跃度、土地成本是中国住宅价格差异的5个核心影响因素,不同行政等级子市场的影响因素作用强度各异。     

Uncertainty in the prediction and management of CO2 emissions: a robust minimum entropy approach

Natural Hazards - CO2 emission control is one of the most vital parts of environment management. China owns the largest CO2 emission in the world. For the sake of clarifying China’s emission...     

中国城市碳排放强度的空间溢出效应及驱动因素

采用核密度估计、空间自相关、空间马尔科夫链和面板分位数回归等方法对1992-2013年全国283个城市碳排放强度的空间溢出效应和驱动因素进行了分析。① 核密度估计结果表明,中国城市碳排放强度总体均值下降,差异在逐步缩小。② 空间自相关Moran's I指数表明城市碳排放强度存在显著的空间集聚性且空间集聚性在逐渐增强,但空间集聚水平的变化逐年缩小。③ 空间马尔科夫链分析结果表明：第一,中国城市碳排放强度存在马太效应,低强度与高强度的城市在相邻年份转移过程中呈现维持初始状态的特征。第二,城市碳排放“空间溢出”效应明显,且不同区域背景下溢出效应存在异质性,即若与碳排放强度低的城市为邻,该城市的碳强度能够增加向上转移的概率,反之亦然。④ 面板分位数结果显示：在碳排放强度低的城市,经济增长、技术进步、适当的人口密度起到减排作用;外商投资强度与交通排放是使碳强度增大的主要因素。在碳排放强度高的城市,人口密度是重要的减排因素,技术进步暂时没起减排作用;工业排放、粗放式的资本投资以及城市土地蔓延则是碳强度上升的主要因素。     

基于超效率SBM模型的中国城市碳排放绩效时空演变格局及预测

由CO₂排放所引起的气候变化是当今社会所关注的热点话题,提高碳排放绩效是碳减排的重要途径。目前关于碳排放绩效的研究多从国家尺度和行业尺度进行探讨,由于能源消耗统计数据有限,缺乏城市尺度的研究。基于遥感模拟反演的1992—2013年中国各城市碳排放数据,采用超效率SBM模型对城市碳排放绩效进行测定,构建马尔可夫和空间马尔可夫概率转移矩阵,首次从城市尺度探讨了中国碳排放绩效的时空动态演变特征,并预测其长期演变的趋势。研究表明,中国城市碳排放绩效均值呈现波动中稳定上升的趋势,但整体仍处于较低的水平,未来城市碳排放绩效仍具有较大的提升空间,节能减排潜力大;全国城市碳排放绩效空间格局呈现“南高北低”特征,城市间碳排放绩效水平的差异性显著;空间马尔科夫概率转移矩阵结果显示,中国城市碳排放绩效类型转移具有稳定性,且存在“俱乐部收敛”现象,地理背景在中国城市碳排放绩效类型转移过程中发挥重要作用;从长期演变的趋势预测来看,中国碳排放绩效未来演变较为乐观,碳排放绩效随时间的推移而逐步提升,碳排放绩效分布呈现向高值集中的趋势。因此未来中国应继续加大节能减排力度以提高城市碳排放绩效,实现国家节能减排目标;同时不同地理背景的邻域城市之间应建立完善的经济合作联动机制,以此提升城市碳排放绩效水平并追求经济增长与节能减排之间协调发展,从而实现低碳城市建设和可持续发展。     

Spatiotemporal evolution of urban carbon emission performance in China and prediction of future trends

Climate change resulting from CO_2 emissions has become an important global environmental issue in recent years.Improving carbon emission performance is one way to reduce carbon emissions.Although carbon emission performance has been discussed at the national and industrial levels,city-level studies are lacking due to the limited availability of statistics on energy consumption.In this study,based on city-level remote sensing data on carbon emissions in China from 1992–2013,we used the slacks-based measure of super-efficiency to evaluate urban carbon emission performance.The traditional Markov probability transfer matrix and spatial Markov probability transfer matrix were constructed to explore the spatiotemporal evolution of urban carbon emission performance in China for the first time and predict long-term trends in carbon emission performance.The results show that urban carbon emission performance in China steadily increased during the study period with some fluctuations.However,the overall level of carbon emission performance remains low,indicating great potential for improvements in energy conservation and emission reduction.The spatial pattern of urban carbon emission performance in China can be described as"high in the south and low in the north,"and significant differences in carbon emission performance were found between cities.The spatial Markov probabilistic transfer matrix results indicate that the transfer of carbon emission performance in Chinese cities is stable,resulting in a"club convergence"phenomenon.Furthermore,neighborhood backgrounds play an important role in the transfer between carbon emission performance types.Based on the prediction of long-term trends in carbon emission performance,carbon emission performance is expected to improve gradually over time.Therefore,China should continue to strengthen research and development aimed at improving urban carbon emission performance and achieving the national energy conservation and emission reduction goals.Meanwhile,neighboring cities with different neighborhood backgrounds should pursue cooperative economic strategies that balance economic growth,energy conservation,and emission reductions to realize low-carbon construction and sustainable development.