基于因子分析法优选河流水体中氮浓度预测方法的研究

定量的河流水体中氮浓度预测方法有很多种,如何优选出预测精度较高的方法一直是学术界多年来致力于研究的重点。本研究采用因子分析法对预测方法的精度评价指标进行分析,并建立了预测方法精度的评价模型,对回归分析法、神经网络法、灰色系统法和增长率统计法4种水体氮浓度预测方法进行综合评估,优选出精度较高的河流水体氮浓度预测模型——BP神经网络预测模型。结果表明,此评估模型对类似研究具有一定的参考价值,能为选择出合适的河流水体氮浓度预测方法提供依据。     

厌氧氨氧化ASBR中亚硝氮和氨氮降解规律研究

采用生物膜ASBR反应器,研究了厌氧氨氧化反应过程中亚硝氮与氨氮降解速度的变化规律。结果表明,降解过程主要分为2个阶段:速度上升期(0~30 min)和速度下降期(30~150 min)。一阶指数衰减模型的模拟结果表明,20 min以后亚硝氮、氨氮降解速度逐渐减少,亚硝氮降解速度始终高于氨氮降解速度,但是两者差值随时间逐渐减少。     

基于品牌创建模型的主题公园可持续发展研究

通过对主题公园研究文献的综述分析,指出主题公园研究中品牌化研究较为匮乏.而中国主题公园近二十年的发展历程表明,主题公园存在的生命周期短暂性现象的主要原因是缺乏品牌创新.从生命周期及可持续发展的视角,提出了以品牌为核心的主题公园运营模式,以此为指导构建了包括概念层、主体层以及基础层三个层面的主题公园品牌创建模型,即通过对动态市场的研究,设计、宣传和推广自身的原创品牌,在获得相应的品牌价值之后,将品牌价值向外延伸,通过系统内各部分的紧密合作,获得主题公园可持续发展的内在驱动力.最后,着重从原创品牌的构建、品牌价值的延伸和保障因素兰方面,提出了基于品牌创建模型的主题公园可持续发展策略.该策略表明:主题公园必须在丰厚的文化内涵和更高的游客体验价值基础上强化自身品牌的构建和发展,在品牌站稳于市场时要适当适度地进行品牌价值延伸,这才能保证主题公园经营的可持续发展.     

人口与消费对碳排放影响的分析模型与实证

从消费压力人口视角探讨碳排放问题,有利于正确判断和把握气候变化压力的人文因素,以及人口与消费可持续发展的动力学机制.本文通过对STIRPAT模型的扩展,应用岭回归方法计量分析人口、消费及技术因素对碳排放的影响.对我国1980至2007年碳排放情况的统计实证结果表明,扩展的STIRPAT模型对中国国情有较高的解释力.居民消费水平、人口城市化率、人口规模三个因素对我国碳排放总量的变化影响明显;现阶段我国居民消费水平与人口结构变化对碳排放的影响力已高于人口规模变化的影响力,居民消费水平与消费模式等人文因素的变化有可能成为我国碳排放的新的增长点;技术进步因素在此模型中对我国该阶段碳排放的解释力有限,表明我国未来通过技术进步减缓碳排放的潜力巨大.     

上海市能源利用碳排放足迹研究

能源利用是人类生存的基础和前提,对其碳足迹及生态压力进行研究具有重要意义.本文运用碳排放足迹的相关含义及研究方法,计算得出1995-2006年上海市能源利用的总碳足迹、各能源类型和产业类型的碳足迹、碳足迹的产值和生态压力值.并以此为基础,利用岭回归函数进行STIRPAT模型拟合,进一步研究经济发展与碳排放足迹之间的关系,最后提出适应性的管理策略.研究结果表明:①总碳足迹从1995年的1.05 hm~2/人上升到2006年的1.36 hm~2/人,呈现波动上升的趋势;②1995-2006年各能源利用的碳足迹及其分配率均以煤炭最大,石油次之,天然气最小,且煤炭利用的碳足迹分配率逐年下降,石油与天然气与之相反;③2001-2006年第一、二产业的碳足迹变化不明显,而第三产业与产业总碳足迹呈明显上升趋势;④能源利用的碳足迹产值从1995年的1.79万元/hm~2增加至2006年的3.79万元/hm~2,碳足迹的生态压力也从1995年的129.6上升至2006年的231.8;⑤能源利用碳足迹与经济增长关系的模型拟合研究结果中没有出现环境库兹涅茨曲线,进一步证实能源利用对环境所造成的压力增大.     

我国城市居民健康状况及影响因素研究

随着中国城市化、工业化快速推进,城市居民的健康日益受到环境、外部压力等因素的影响,加上生活方式和健康观念方面的原因,城市居民健康状况的改善缓慢.利用2006年中国健康与营养调查(CHNS)截面数据,描述了我国城市居民的健康及其分布状况,利用Ordered Probit模型分析了影响城市居民的健康状况的各类因素.结果发现:家庭状况、生活习惯、就医决策、医疗保险等因素均影响城市居民的健康水平;尤其是在收入、工作等经济因素之外,健康观念、就医决策和保险覆盖等社会和制度因素亦对城市居民个人健康产生影响.同时,通过逐步回归控制相关变量的方法,检验了Grossman模型的适用性,同时也检验了影响因素作用机制的稳定性.在总结研究结论与不足的基础上,提出了应从经济,社会和制度三个层面全面促进城市居民健康的综合改革框架.     

Emissions of biogenic VOC from forest ecosystems in central Europe: Estimation and comparison with anthropogenic emission inventory

This paper describes a method of estimating emission fluxes of biogenic volatile organic compounds (BVOCs) based on the approach proposed by Guenther et al. (1995) and the high-resolution Corine land-cover 2000 database (1 × 1 km resolution). The computed emission fluxes for the Czech Republic (selected for analysis as being representative of a heavily cultivated, central European country) are compared with anthropogenic emissions, both for the entire country and for individual administrative regions. In some regions, BVOC emissions are as high as anthropogenic emissions; however, in most regions the BVOC emissions are approximately 50% of the anthropogenic emissions. The yearly course of BVOC emissions (represented by monoterpenes and isoprene) is presented, along with the spatial distribution of annual mean values. Differences in emission distributions during winter (January) and summer (June) are also considered.     

Tracking nitrogen losses in a greenhouse crop rotation experiment in North China using the EU-Rotate_N simulation model

Vegetable production in China is associated with high inputs of nitrogen, posing a risk of losses to the environment. Organic matter mineralisation is a considerable source of nitrogen (N) which is hard to quantify. In a two-year greenhouse cucumber experiment with different N treatments in North China, non-observed pathways of the N cycle were estimated using the EU-Rotate_N simulation model. EU-Rotate_N was calibrated against crop dry matter and soil moisture data to predict crop N uptake, soil mineral N contents, N mineralisation and N loss. Crop N uptake (Modelling Efficiencies (ME) between 0.80 and 0.92) and soil mineral N contents in different soil layers (ME between 0.24 and 0.74) were satisfactorily simulated by the model for all N treatments except for the traditional N management. The model predicted high N mineralisation rates and N leaching losses, suggesting that previously published estimates of N leaching for these production systems strongly underestimated the mineralisation of N from organic matter.     

Implications of high altitude desert dust transport from Western Sahara to Nile Delta during biomass burning season

The air over major cities and rural regions of the Nile Delta is highly polluted during autumn which is the biomass burning season, locally known as black cloud. Previous studies have attributed the increased pollution levels during the black cloud season to the biomass or open burning of agricultural waste, vehicular, industrial emissions, and secondary aerosols. However, new multi-sensor observations (column and vertical profiles) from satellites, dust transport models and associated meteorology present a different picture of the autumn pollution. Here we show, for the first time, the evidence of long range transport of dust at high altitude (2.5-6 km) from Western Sahara and its deposition over the Nile Delta region unlike current Models. The desert dust is found to be a major contributor to the local air quality which was previously considered to be due to pollution from biomass burning enhanced by the dominant northerly winds coming from Europe.     

An Objective Multiattribute Analysis Approach for Allocation of Scarce Irrigation Water Resources1

Zardari, Noor ul Hassan, Ian Cordery, and Ashish Sharma, 2010. An Objective Multiattribute Analysis Approach for Allocation of Scarce Irrigation Water Resources. Journal of the American Water Resources Association (JAWRA) 46(2):412-428. DOI: 10.1111/j.1752-1688.2009.00410.x Abstract: In this study, end user (farmer) and decision maker (water allocator) opinions were surveyed and a conjoint analysis (CA) based method was applied to the quantitative and qualitative data to assess the utility associated with each attribute that plays a role in forming the final thinking of the water users. The application of CA for estimating the utility for each attribute level is a novel approach, which helps provide a formal, objective basis for assigning relative scales for each attribute interval within a multiattribute decision-making model. The utilities (part-worths) obtained from the CA have a cardinal scale and were found to be comparable within and across the attributes. A farmers’ survey on five water allocation attributes was completed from 62 farmers and their opinions on the relative importance of attributes were elicited for a subarea of the Indus River Basin. The CA method was then applied to the survey data and the utilities for each attribute level were determined. This allowed, for instance, decisions to be made, which take account of the perceived value of the water and of the availability of local labor to work on the farm. Finally, these interval scales were used within the specification of the ELECTRE multiattribute decision-making method to provide a complete and objective ranking of nine irrigation districts so that the best decisions on water allocation could be made.