水环境退化经济损失的计量方法及其应用

水环境退化较难以市场价格方式体现,是绿色GDP核算的一大难点.分析了影响水环境退化的社会经济因素、自然因素,在此基础上,构建了水环境退化的计量模型,并将社会经济发展的阶段性特征、水资源供需矛盾、降水补给变异特征和水质状况纳入模型中,采用不同参数进行描述,以保证模型的逻辑完备性和计算的简洁性.在湖州市绿色GDP核算过程中,采用该模型分别计算各县区2001-2004年水环境退化的经济损失.这些损失与当地水资源供需矛盾、水污染状况、社会经济发展等因素变化状况相符,准确反映了湖州市水环境退化的实际状况.结果表明,水环境退化的经济损失,除水污染程度外,还受到社会经济因素和降水补给等自然因素的影响.      

典型软垫家具材料火灾特性的小尺寸实验研究

本文借助锥型量热计对制作软垫家具的材料进行小尺寸实验,获得了典型软垫家具面料、聚氨酯海绵填料及其组合件的燃烧性能参数。通过对实验获得参数的分析比较,认为面料对组合件燃烧特性的影响大,仅使用阻燃布就可以明显改善组合的火灾特性。     

Experimental research of LNG accidental underwater release and combustion behavior

Evaluating potential hazards caused by accidental LNG release from underwater pipelines or vessels is a significant consideration in marine transportation safety. The aim of this study was to capture the dynamic behavior of LNG jet released under water and to analyze its vapor dispersion characteristics and combustion characteristics on the water surface during different release scenarios. Controlled experiments were conducted where LNG was jet released from a cryogenic storage tank. The dynamic process of LNG being jet released from orifices of different sizes and shapes, as well as the rising plume structure, were captured by a high-speed camera. The leakage flow rate and pipeline pressure were recorded by a flow meter and pressure gauge, respectively. The concentration distribution that emanated from the water surface was measured utilizing methane sensors in different positions with various wind speeds. The flame combustion characteristics of LNG vapor clouds, which immediately ignited upon the enclosed water tank, were also recorded. Additionally, the mass burning rate of the flame on the water surface was evaluated, and a new correlation between the ratio of flame length and width was established. The results indicated a large dimensionless heat release rate (Q*) and a continuous release flow rate in a limited burning area. This study could provide greater understanding of the mechanisms of LNG release and combustion behavior under water.     

城市燃气事故生命损失风险可接受标准研究

为提高我国城市燃气风险管理水平,帮助风险管理者科学地分配维护资源,探讨提出了我国城市燃气事故生命损失风险可接受标准;采用AIR指标法确定了个人风险可接受标准范围为(2.397 3×10-7,4.794 7×10-7);运用F-N曲线法结合ALARP原则,确定了社会风险可接受标准,最大可接受风险的截距为4.794 7×10-7,可忽略风险的截距为4.794 7×10-8;利用生活质量指数推导模型,计算了达到城市燃气事故可忽略风险水平的最优安全投入成本;基于风险动态原则,分析提出了风险可接受标准的更新办法。研究结果表明:我国城市燃气行业可接受风险水平低于煤矿、大坝、化工等危险行业的可接受风险水平;虽然我国城市燃气事故死亡率逐年降低,但要达到可忽略的风险水平,每年还需大量安全资金投入。     

三峡库区消落带农用坡地磷素径流流失特征

消落带是三峡库区重要的生态交错带,但自发农用和无序开发可能会造成更多的氮磷流失,进而加剧三峡库区水体富营养化。通过对库区连续3 a的定位监测（2011~2013年）,研究了三峡库区消落带农用坡地的磷素流失特征。结果表明：次降雨事件中常规施肥处理的地表径流、壤中流总磷平均浓度分别为0.848±0.153、0.140±0.006 mg/L,其中地表径流中磷的形态以颗粒态为主,壤中流以溶解态的生物可利用磷为主。常规施肥下,地表径流、壤中流磷素年均流失通量分别为0.236±0.004、0.100±0.003 kg·hm 2,地表径流、壤中流磷素流失通量分别占总流失通量的70.2%、29.8%,地表径流是坡地磷素流失的主要途径,但壤中流也是不可忽视的重要途径。与常规施肥处理相比,减量施肥处理地表径流、壤中流磷素流失量分别降低了45.3%、40.0%。建议采取减量施肥的方式,以降低营养盐负荷,保护水环境。     

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.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

Target Gap of Emission Reduction for China:Analysis based on Elastic Decoupling

The present paper analyzes historically the relationship between carbon emission and economic development by different stages through adopting elastic decoupling methods and Tapio evaluation criteria along with a comparison with the national Five Year Plans. The analysis shows that the influencing factors to the relationship between carbon emission and economy in China are different, and economic development and carbon emission have less connection in the recent 30 years of reform and opening-up in China. It is a difficult task to realize the promise that we will reduce carbon emission by 40%-50% in 2020 based on the data from historical experience and different expectations for economic development from economists. Through constructing the calcula- tion model of carbon emission intensity gap according to different development scenarios, the analysis shows that economic growth, infrastructure investment and further development of industrial-ization are the main drivers to the increase of carbon emission, technological progress, and particularly, the reduction of energy consumption is the primary means to reduce carbon emission in China. It is imperative to transform the economic growth pattern, and it is a grand task to perform and there is a long way to go for China to maintain economic growth and reduce carbon intensity.     

台风灾害债券设计——基于广东省数据的实证研究

台风作为全球发生频率最高,影响最严重的一种自然灾害,对我国的影响也非常严重。在巨灾风险证券化、巨灾债券已成为巨灾保险业大趋势的背景下,发展我国台风灾害债券具有重要的现实意义。以我国受台风灾害影响最严重的省份——广东省为研究对象,收集了其近30年相关台风损失数据,利用非寿险精算技术分析其台风的损失分布和次数分布,在此基础上利用CAMP模型和现金流分析对广东省的台风灾害债券做了初步设计。     

Modeling potential herbicide loss to surface waters on the Swiss plateau

Lack of sufficiently detailed data often limits the applicability of complex transport-reaction models for estimating potential herbicide loss to surface waters. Therefore, there is also a need for simple models that are easy to apply but still capture the main features of the underlying processes.In this study, a simple regression model was developed to assess the vulnerability of catchments in the Swiss Plateau to diffuse herbicide loss to surface waters. The model is designed as a screening tool to rank the catchments in a relative sense and not to calculate Predicted Environmental Concentrations (PEC) of pesticides. The main goal is to capture two dominating factors controlling diffuse herbicide transport into streams and rivers. These factors are herbicide application and fast flow processes that are mainly responsible for herbicide transport. In a first step vulnerability of sites to herbicide loss is estimated based on site-specific conditions irrespective of actual herbicide application. In the second step, this vulnerability assessment is combined with actual herbicide application data to estimate the potential herbicide loss.The fast flow index (FFI), derived from discharge data using a base flow separation method, was applied as a proxy for the amount of fast flow occurring. The influence of catchment attributes (including topographic, climatic and soil data) on the FFI was analyzed using a multiple regression approach based on data from 57 catchments of the Swiss Plateau. By combining regression analysis with mechanistic knowledge, a two factor non-linear model based on river density and soil permeability as dominant input factors was selected as the best model for FFI prediction given the available data. Higher dimensional models had to be excluded because the strong correlation between the potential input factors led to unrealistic dependences while only minimally improving the quality of the fit.The spatial pattern of the predicted FFI as a measure for the vulnerability to diffuse herbicide losses shows a clearly increasing trend from the western to the eastern part of the Swiss Plateau and towards the pre-alpine/alpine regions in the south.In general the pattern of herbicide use corresponds to site conditions typical of a low FFI. However, the spatial analysis revealed exceptions, namely areas in which high actual herbicide use coincides with a high FFI.Despite the uncertainties in the model, this simple approach seems to be useful for supporting site-adapted agricultural practice whenever the higher accuracy of more detailed models is not required or too expensive to achieve. In addition, in combination with data on actual herbicide application, it can support the design of monitoring strategies by identifying critical areas of actual herbicide loss.