海洋四水团混合的定量化分析和方法比较及其在东海西南海区的应用

通过构造理想的四水团混合模型,对传统温-盐二指标图解和三指标钜阵求解分析水团混合的方法进行比较,认为三指标估算结果更接近真实值.但温、盐数据因为易得且准确性好,所以传统方法仍具有一定的实用价值.在东海西南海区的应用中,检验了天然放射性226Ra核素作为第三个指标的可行性,并对实际水团混合情况进行了评估.证实黑潮次表层水在夏季顺陆坡边缘爬升后沿底部向岸运移,并在近岸涌升,是东海陆架区营养盐外源补充的一个重要动力.     

HPLC-三重四级杆质谱法测定医疗废水中抗生素残留

采用固相萃取/高效液相色谱-三重四级杆质谱法同时测定医疗废水中的20种超痕量抗生素残留,通过优化试验条件,使方法在100μg/L～100μg/L范围内线性良好,方法检出限为024ng/L～122ng/L。空白水样和实际水样3个质量浓度水平的加标回收率分别为80.2%～108%和75.8%～114%,6次测定结果的RSD分别为2.4%～8.4%和1.7%～8.1%。将该方法用于测定重庆市2家三甲医院医疗废水中的超痕量抗生素残留,结果有11种抗生素检出,其余均为未检出。     

铁路运输含硫原油过程中H_2S挥发规律模拟试验研究

以塔河12区含硫原油为研究对象,通过模拟铁路运输原油工况,研究罐内原油中H_2S挥发规律.结果表明,铁路运输过程中原油里H_2S析出浓度与时间的关系近似为6次多项式,并建证了H_2S浓度随时间变化的曲线方程;对影响罐内原油中H_2S挥发的2个主要因素罐内原油温度和罐车振动强度进行了分析.结果表明,罐内原油温度是原油中H_2S挥发的主要影响因素,升高罐内原油温度可以明显增加H_2S的挥发浓度.加大罐车振动强度对原油中H_2S挥发有促进作用,但不明显.     

真空条件下高分辩质谱对不同煤质热解释放CO2分析

煤的热解机理和热解物质的形成与释放特征是煤田火灾研究领域的重要基础问题.本文以淮北不同煤种(烟煤,无烟煤,天然焦)为研究对象,在高真空条件下对样品进行热解,利用分子泵即时将热解气体产物抽入高分辨质谱检测器,在线分析热解过程中CO2的释放规律.研究结果表明:天然焦热解过程中产生的CO2,主要是样品和体系中残留以及吸附在煤微孔隙中O2分子反应生成;烟煤和无烟煤热解产生的CO2,主要是其内部含氧官能团在受热过程中分解形成,为不同煤种自燃发火防治提供资料.     

江苏苏中3市的沿江岸线资源开发利用变化及驱动因素

长江是我国重要的黄金水道,其岸线资源有着丰富的开发利用价值。近年来,苏中地区长江岸线资源利用发展迅速。因此,选取苏中扬州、泰州、南通3市为研究对象,基于2002年和2008年的长江岸线利用状况数据,对比分析了3市岸线发展变化的规律。研究表明:2002年以来,苏中3市的岸线利用率大幅提高;新增岸线中工业岸线占比最大,港口岸线和生活服务岸线次之;工业岸线和生活服务岸线的增幅最为显著;各类型岸线的增加主要来源于未利用岸线,已有岸线类型的转换主要流向工业岸线和未利用岸线。港口建设需求、沿江基础工业化进程加快、港产城融合发展、规划和政策引导等是岸线利用变化的重要驱动力。     

人类活动对川东平行岭谷区岩溶地下水化学性质季节变化的影响

以川东平行岭谷区典型岩溶槽谷--北碚槽上为研究区域,通过对8月和11月的岩溶地下水水化学性质研究,发现槽上岩溶地下水的化学性质呈现明显的季节性：电导率、矿化度、SO42-浓度及HCO3-浓度都是8月大于11月,与气温和降水量的变化相对应,也与人类在8月份对土地利用的强度大于在11月份对土地利用的强度相对应。研究区地下水的化学性质与人类活动对土地利用的季节差异具有比较明显的对应关系,为进一步认识岩溶地下水的时间变化规律提供科学数据,也有利于认识人类活动对生态环境产生的影响,从而采取更加合理的措施来治理和保护岩溶地区有限的地下水资源,满足人们的生活和生产需要。     

长江中游城市群经济与生态成本空间演化模式分析

综合运用变异系数、泰尔指数及ESDA-GIS多种方法,在充分考虑传统经济影响因子的基础上,尝试引入经济发展生态成本指标,分析长江中游城市群经济综合发展水平与生态成本的空间匹配及演化模式。研究表明:经济综合发展水平高低聚集特征明显,空间极化现象是导致区域经济发展不平衡的主要原因;生态成本空间集聚现象以高高集聚和低低集聚为主,且呈现出高高集聚减少、低低集聚增多的现象,生态成本消耗有所改善;2001~2012年长江中游城市群市域经济综合发展水平与生态成本表现出越来越显著的差异化空间格局,呈现出由低经济综合发展水平-低生态成本过渡到高经济综合发展水平-高生态成本,进而发展到高经济综合发展水平-低生态成本的空间匹配模式的阶段性特征;高经济综合发展水平-高生态成本的经济发展模式仍在大部分城市中存在,经济与生态空间协调发展的潜力仍然很大。     

崇明东滩不同部位的季节性沉积研究

2002年4月至2003年4月,通过对崇明东滩南部、中部和北部的标志桩观测以及实地观测分析,发现崇明东滩在一年中不同季节冲淤变化过程存在很大差异：春季到夏季,南部以冲刷为主,中部和北部以淤积为主;夏季到秋季,南部和中部以淤积为主,北部表现为冲刷;秋季到冬季,南部、中部和北部都以冲刷为主;头一年冬季到次年春季,南部和北部以淤积为主,中部则表现为冲刷。在同一观测路线上,不同季节高、中、低潮滩冲淤也存在一定差异。通过对沉积物粒度、水体含沙量等指标的测试,并借助潮差等资料,探究了影响潮滩季节性沉积的因素,发现潮滩季节性沉积与潮滩基础地貌、水体含沙量、水动力、潮流等有密切关系;但在不同部位不同季节,各因素对潮滩冲淤影响程度各不相同。     

Design considerations for environmental sustainability in high density development: a case study of Hong Kong

This study has indicated that there is close relationship between development density and environmental quality; therefore, it is necessary to decide the form of development carefully beforehand. The form of development is shaped either by new development or urban renewal which is a major tactic nowadays adopted by the Hong Kong Government to improve the living condition of the citizens and the quality of the built environment. This study is limited to urban renewal and aims to find out the major urban design considerations for sustaining the environment. Through a questionnaire survey carried out in Hong Kong, the opinions of architects, planners, property development managers, and local citizens were sought and evaluated, and critical design factors for enhancing environmental sustainability of urban renewal projects are highlighted. The results derived from factor analysis indicated that certain design considerations should be incorporated for sustaining the urban environment. “Land Use Planning”, “Quality of Life”, “Conservation & Preservation”, “Integrated Design”, “Provision of Welfare Facilities”, and “Conservation of Existing Properties” were believed to be the significant underlying factors for achieving environmental sustainability of local urban renewal projects. Readers should send their comments on this paper to: BhaskarNath@aol.com within 3 months of publication of this issue.     

Use of a food web model to evaluate the factors responsible for high PCB fish concentrations in Lake Ellasjøen, a high Arctic Lake

Background, aim, and scope

Lake Ellasjøen, located in the Norwegian high arctic, contains the highest concentrations of polychlorinated biphenyls (PCBs) ever recorded in fish and sediment from high arctic lakes, and concentrations are more than 10 times greater than in nearby Lake Øyangen. These elevated concentrations in Ellasjøen have been previously attributed, in part, to contaminant loadings from seabirds that use Ellasjøen, but not Øyangen, as a resting area. However, other factors, such as food web structure, organism growth rate, weight, lipid content, lake morphology, and nutrient inputs from the seabird guano, also differ between the two systems. The aim of this study is to evaluate the relative influence of these factors as explanatory variables for the higher PCB fish concentrations in Ellasjøen compared with Øyangen, using both a food web model and empirical data.

Methods

The model is based on previously developed models but parameterized for Lakes Ellasjøen and Øyangen using measured data wherever possible. The model was applied to five representative PCB congeners (PCB 105, 118, 138, 153, and 180) using measured sediment and water concentrations as input data and evaluated with previously collected food web data.

Results

Modeled concentrations are within a factor of two of measured concentrations in 60% and 40% of the cases in Lakes Ellasjøen and Øyangen, respectively, and within a factor of 10 in 100% of the cases in both lakes. In many cases, this is comparable to the variability associated with the data as well as the efficacy of the predictions of other food web model applications.

Discussion

We next used the model to quantify the relative importance of five major differences between Ellasjøen and Øyangen by replacing variables representing each of these factors in the Ellasjøen model with those from Øyangen, in separate simulations. The model predicts that the elevated PCB concentrations in Ellasjøen water and sediment account for 49%–58% of differences in modeled fish PCB concentrations between lakes. These elevated sediment and, to a lesser extent, water concentrations in Ellasjøen are due to PCB loadings from seabird guano. However, sediment–water fugacity ratios of PCBs are consistently greater in Ellasjøen compared with Øyangen, which suggests that internal lake processes also contribute to differences in sediment and water concentrations. We hypothesize that the nutrients associated with guano influence sediment–water fugacity ratios of PCBs by increasing the stock of pelagic algae. As both these algae and the guano settle, their organic carbon content is degraded faster than PCBs, which causes an extra magnification step in Ellasjøen before these detrital particles are consumed by benthic organisms, which are in turn consumed by fish. The model predicts that the remaining ～50% of the differences in PCB concentrations observed between the fish of these lakes are due to other subtle differences in their food web structures.

Conclusions

In conclusion, based on the results of a food web model, we found that the most dominant factors influencing the higher PCB fish concentrations in Lake Ellasjøen compared with Øyangen are the higher sediment and water concentrations in Ellasjøen, caused by seabird guano. Together, sediment and water are predicted to account for 49%–58% of differences in fish concentrations between lakes. Although seabird guano provides a source of nutrients to the lake, in addition to contaminants, empirical data and indirect model results suggest that nutrients are not leading to decreased bioaccumulation, in contrast to what has been observed in temperate, pelagic food webs.

Recommendations and perspectives

The results of this study emphasize the importance of considering even small differences in food web structure when comparing bioaccumulation in two lakes; although the food web structures of Ellasjøen and Øyangen differ only slightly, the model predicts that these differences account for most of the remaining ～50% of the differences in PCB fish concentrations between the two lakes. This study further demonstrates the utility of food web models as we were able to predict and tease apart the influence of various factors responsible for the elevated concentrations in the fish from Lake Ellasjøen, which would have been difficult using the field data alone.