莱州湾南岸海水入侵现状评价

根据莱州湾南岸海水入侵区地下水水质特点,将海水入侵等级划分为4级。同时,选取Cl^-,矿化度,SO4^2-,rHCO3^-/rCl^-,K^-等指标作为评价因子,并分别确定了这5项指标的等级划分范围。然后,运用模糊数学的综合评判方法,对研究区内海水入侵现状做出评价。     

2005/2006年度莱州湾东部的海冰灾害及其影响

莱州湾是水深较浅的半封闭海湾,与外海海水的交换缓慢,受黄河等十几条入海河流汇入的淡水影响使海水的盐度较低.受寒潮影响莱州湾内海冰灾害发生频繁.莱州湾的海冰灾害分5个冰情等级.在冬季气温偏高的年份,莱州湾内形成Ⅰ、Ⅱ级海冰,沿岸一般没有固定冰形成;一般年份形成Ⅲ级海冰,西岸和南岸冰情较严重,有固定冰形成;在冬季气温偏低的年份,形成Ⅳ级或Ⅴ级海冰,南岸、西岸的固定冰宽度较大,有时整个莱州湾海面都分布流冰.2005年末～2006年初在莱州湾东岸形成了一次较严重的海冰灾害,莱州市近海海湾扇贝养殖的经济损失达400万元以上.为减轻未来海冰灾害带来的损失提出了加强海冰灾害的监测和预报技术研究,严格管理近海养殖生产作业,莱州湾沿岸地方政府应制定<海冰灾害应急预案>,建设和完善海冰灾害应急防御体系等防御海冰灾害的对策.     

The impact of physical processes on pollutant transport in Hangzhou Bay

A Lagrangian tracer model is set up for Hangzhou Bay based on Coupled Hydrodynamical Ecological model for Regional Shelf Sea (COHERENS). The study area is divided into eight subdomains to identify the dominant physical processes, and the studied periods are March (the dry season) and July (the wet season). The model performance has been first verified by sea-surface elevation and tidal current observations at several stations. Eight tracer experiments are designed and Lagrangian particle tracking is simulated to examine the impact of physical processes (tide, wind and river runoff) on the transport of passive tracer released within the surface layer. Numerical simulations and analysis indicate that: (1) wind does not change the tracer distribution after 30 days except for those released from the south area of the bay during the wet season; (2) the tide and the Qiantang River runoff are important for particle transport in the head area of the bay; (3) the Changjiang River runoff affects the tracer transport at the mouth of the bay, and its impact is smaller in the dry season than in the wet season. Supported by the Natural Science Foundation of China (No.40576080); National High Technology Research and Development Program of China (863 Program, No. 2007AA12Z182)     

Accumulation of petroleum hydrocarbons and heavy metals in clams （Ruditapes philippinarum） in Jiaozhou Bay, China

Accumulation and distributions of aliphatic and polyaromatic hydrocarbons (PAHs) and heavy metals were measured in tissues of the clam Ruditapes philippinarum collected from 5 sites in Jiaozhou Bay, Qingdao, China. The concentrations of total aliphatic hydrocarbon and PAHs ranged from 570 to 2 574 ng/gdw (gram dry weight) and from 276 to 939 ng/gdw, in the most and least polluted sites, respectively. The bio-accumulation of hydrocarbons and PAHs in the clams appeared to be selective. Aliphatic hydrocarbons were predominantly represented by short chain (<nC₂₃) n-alkanes, suggesting that petroleum hydrocarbons were likely the major contamination source. The selective uptake of 3 and 4 ring PAHs, such as naphthalene, fluorene, phenanthrene, fluoranthene and pyrene, by the clams was probably related to the physiological and bio-kinetic processes that were energetically favorable for uptake of compounds with fewer rings. Accumulation of the metals Cd, Cu, Zn, Pb, Cr, Hg, and As in the clam tissues also showed high variability, ranging from 0.043 to 87 μg/gdw. Among the 7 detected metals, Zn, Cd, Cu, and As had a particularly high potential of accumulation in R. philippinarum. In general, a positive correlation was found between the tissue concentrations and sediment concentrations of hydrocarbons and of some metals. Our study suggests that moderate contamination with polyaromatic hydrocarbons, and low to moderate contamination with metals, currently exists for clam R. philippinarum in Jiaozhou Bay, in comparison with other regional studies. A long-term monitoring program is certainly needed for assessment of the potential ecological influence and toxicity of these contaminants of R. philippinarum in Jiaozhou Bay.     

Three Decades of Sea-Ice Variability in Jiaozhou Bay Revealed by Landsat Observations

In this study, we used Landsat images and meteorological data to examine the spatiotemporal distribution and variability of sea ice in Jiaozhou Bay(JZB) between 1986 and 2016. The results show that JZB is not always covered by sea ice in winter, but in some extreme cases, sea ice has covered more than one-third of the sea area of the bay. Sea ice in JZB has generally formed between January 1 and February 5, primarily along the coast, and gradually expanding to the central area of the bay. Both meteorological and artificial factors have played important roles in modulating the sea ice distribution. We found sea ice coverage to have been strongly correlated with the accumulated freezing-degree days nine days before the occurrence of sea ice(R2 = 0.767). North-northwest surface winds have dominated the freezing period of sea water in the JZB, and wind speed has exerted a more significant influence on the formation of sea ice when the sea ice coverage has been generally small. Additionally, artificial factors began to affect the expansion of sea ice in JZB since 2007. The construction of the Jiao-Zhou-Bay Bridge(JZBB) is believed to have retarded water flow and reduced the tidal prism, thereby leading to the formation of an ice bridge along the JZBB, which effectively prevents the southward expansion of sea ice.     

The differential geography of housing affordability in Sydney: a disaggregated approach

ABSTRACT

Despite extensive studies being devoted to housing affordability in Australia, few have investigated housing affordability at a disaggregated level. This is in spite of the fact that there are existing socio-economic and demographic disparities across different regions of a city. This study aims to fill this gap by examining housing affordability in Sydney, a city that is characterised by diverse demographic and socio-economic mix, from a sub-city perspective. Two dimensions of affordability are assessed from 1991 to 2016: entry-level and ongoing housing affordability. The study finds that entry-level housing remains extremely unaffordable in all regions of Greater Sydney, although the level of unaffordability varies across regions. Specifically, the deterioration in housing affordability is more obvious in low-income regions such as Western Sydney. In addition, the ongoing housing affordability of those who have entered the market improves considerably within 5–10 years, although there are significant variations between different regions. Importantly, residents in low-income regions such as Western Sydney take a longer period to improve their ongoing affordability. The findings of differential geography of housing affordability have some profound policy implications. Policymakers should consider the disparities across different regions by formulating a more targeted and regionally balanced housing policy.     

黄淮海地区乡村人—地—业协调发展格局与机制

乡村在社会中占有重要地位,但乡村衰败目前已成为世界性问题,因此,乡村振兴需破解乡村病问题。现有乡村研究主要关注乡村单一系统、乡村转型或乡村特定问题的研究,对乡村系统自身、乡村各子系统之间关系及其驱动乡村发展逻辑的研究则显匮乏。基于黄淮海地区县域数据,选取乡村人—地—业3个子系统,利用耦合协调度模型刻画了乡村内部系统耦合协调度的空间格局,并对人—地—业驱动乡村发展的内在逻辑进行了探讨。结果发现：① 黄淮海地区大部分县域乡村人—地—业发展处于高水平耦合阶段,在空间格局上形成了4条明显的高值轴带,且乡村系统发展水平呈逐年上升趋势。② 黄淮海地区乡村耦合协调水平整体较高,但大部分处于勉强协调或初级协调阶段,耦合协调水平较高的县域主要集中在经济较发达地区。③ 黄淮海地区乡村耦合协同关系可分为低协调水平—土地发展领先型、中协调水平—人口发展领先型和高协调水平—人业发展引领型3种类型,其中产业在黄淮海地区乡村协调发展中至关重要。④ 乡村人—地—业的协调发展可有效激活“四力”,为乡村可持续发展奠定了基础。本研究为理解乡村系统自身、破解乡村问题及实现乡村可持续发展提供了参考。     

贫困村空间分布及影响因素分析——以乌蒙山连片特困区为例

针对目前贫困分布研究以大尺度为主而缺乏对小尺度的关注和致贫因素分析忽略个体效应或背景效应的不足,基于空间贫困视角,以乌蒙山片区为研究区域、贫困村为研究对象,运用空间点模式分析方法探究贫困村空间分布特征,并设计多层线性回归模型从贫困村和县域两个层面综合定量剖析贫困影响因素。研究发现：① 贫困村的空间聚集特征较为明显,总体分布呈现大分散小集中、散点-极核-轴带-团块并存的空间格局。② 贫困村的贫困程度受多层因素的显著影响。其中,村级影响因素为：人口密度、通路率、劳动力比例、遭受自然灾害频次、安全饮用水比例;县级影响因素为：人均地方生产总值、高中阶段毛入学率、植被覆盖率。③ 农村贫困来源于贫困村与县域的双重作用。因此在精准扶贫工作中,政府及相关部门可针对不同尺度对象有针对性地施策,合理配置扶贫资金。     

大亚湾大鹏澳牡蛎养殖临近海域自养微微型浮游生物种群分布特征

于2013年5月到2014年6月,在大亚湾大鹏澳牡蛎区及邻近海域开展了为期14个月的采样调查,利用高效液相色谱(HPLC)法对表层水体中微微型浮游植物(0.7—2.7μm)光合色素进行测定,并应用色素化学分类软件CHEMTAX对自养微微型浮游生物(aototrophicpicoplankton,APP)功能类群进行分析。结果表明,该海域APP中共检出了15种光合色素,其中青绿藻素(Pras)和玉米黄素(Zea)是微微型色素中浓度最高的2种特征色素,均具有明显的季节变化特征:Pras主要出现在低温季节(牡蛎养殖期),而Zea主要出现在高温季节(非牡蛎养殖期)。CHEMTAX分析表明,大鹏澳海域APP最主要的类群是硅藻、蓝藻和青绿藻,而甲藻、隐藻、定鞭金藻、绿藻和金藻生物量较低。温度和营养盐浓度是影响大鹏澳海域APP的时空分布的重要因素,青绿藻主要出现在低温季节(主要在冬季牡蛎养殖期间),且其生物量与溶解无机氮呈显著正相关;而蓝藻则主要出现在高温季节,与温度呈显著正相关。另外,贝类养殖也是能够影响APP空间分布的重要因素,在大鹏澳海域牡蛎养殖期间,青绿藻生物量在养殖区明显高于非养殖海域。     

Upper ocean high resolution regional modeling of the Arabian Sea and Bay of Bengal

In this paper, effort is made to demonstrate the quality of high-resolution regional ocean circulation model in realistically simulating the circulation and variability properties of the northern Indian Ocean(10°S–25°N,45°–100°E) covering the Arabian Sea(AS) and Bay of Bengal(BoB). The model run using the open boundary conditions is carried out at 10 km horizontal resolution and highest vertical resolution of 2 m in the upper ocean.The surface and sub-surface structure of hydrographic variables(temperature and salinity) and currents is compared against the observations during 1998–2014(17 years). In particular, the seasonal variability of the sea surface temperature, sea surface salinity, and surface currents over the model domain is studied. The highresolution model's ability in correct estimation of the spatio-temporal mixed layer depth(MLD) variability of the AS and BoB is also shown. The lowest MLD values are observed during spring(March-April-May) and highest during winter(December-January-February) seasons. The maximum MLD in the AS(BoB) during December to February reaches 150 m (67 m). On the other hand, the minimum MLD in these regions during March-April-May becomes as low as 11–12 m. The influence of wind stress, net heat flux and freshwater flux on the seasonal variability of the MLD is discussed. The physical processes controlling the seasonal cycle of sea surface temperature are investigated by carrying out mixed layer heat budget analysis. It is found that air-sea fluxes play a dominant role in the seasonal evolution of sea surface temperature of the northern Indian Ocean and the contribution of horizontal advection, vertical entrainment and diffusion processes is small. The upper ocean zonal and meridional volume transport across different sections in the AS and BoB is also computed. The seasonal variability of the transports is studied in the context of monsoonal currents.