Comparing future patterns of energy system change in 2 °C scenarios with historically observed rates of change

This paper systematically compares modeled rates of change provided by global integrated assessment models aiming for the 2 °C objective to historically observed rates of change. Such a comparison can provide insights into the difficulty of achieving such stringent climate stabilization scenarios. The analysis focuses specifically on the rates of change for technology expansion and diffusion, emissions and energy supply investments. The associated indicators vary in terms of system focus (technology-specific or energy system wide), temporal scale (timescale or lifetime), spatial scale (regional or global) and normalization (accounting for entire system growth or not). Although none of the indicators provide conclusive insights as to the achievability of scenarios, this study finds that indicators that look into absolute change remain within the range of historical growth frontiers for the next decade, but increase to unprecedented levels before mid-century. Indicators that take into account or normalize for overall system growth find future change to be broadly within historical ranges. This is particularly the case for monetary-based normalization metrics like GDP compared to energy-based normalization metrics like primary energy. By applying a diverse set of indicators alternative, complementary insights into how scenarios compare with historical observations are acquired but they do not provide further insights on the possibility of achieving rates of change that are beyond current day practice.     

A new methodology for building local climate change scenarios: A case study of monthly temperature projections for Mexico City

This paper proposes a new methodology for generating climate change scenarios at the local scale based on multivariate time series models and restricted forecasting techniques. This methodology offers considerable advantages over the current statistical downscaling techniques such as: (i) it provides a better representation of climate at the local scale; (ii) it avoids the occurrence of spurious relationships between the large and local scale variables; (iii) it offers a more appropriate representation of variability in the downscaled scenarios; and (iv) it allows for compatibility assessment and combination of the information contained in both observed and simulated climate variables. Furthermore, this methodology is useful for integrating scenarios of local scale factors that affect local climate. As such, the convenience of different public policies regarding, for example, land use change or atmospheric pollution control can be evaluated in terms of their effects for amplifying or reducing climate change impacts.     

Mathematical and numerical filtration–advection–dispersion model of miscible grout propagation in saturated porous media

The development of a predictive model of behaviour of porous media during injection of miscible grout, taking into account convection, dilution and filtration of grout solution with interstitial water, as well as consolidation aspects, is presented. Model assumptions are reviewed and discussed first. During the establishment of the model, we insist on surface terms and their physical relevance in expressing adsorption effects. Constitutive laws such as Fick's law for diffusive mass transport, hydrodynamic dispersion tensor dealing with miscibility, are modified by taking into account filtration effects. A new surface term appears in mass balance equations as a consequence of filtration. According to the filtration laws used, an initial filtration rate is estimated on the basis of a one‐dimensional experimental campaign. The field equations are discretized by using Galerkin finite element and θ‐scheme standard method. For transport equation, Streamline Upwind Petrov Galerkin method is employed to prevent numerical oscillations. Lastly, confrontation of numerical results with laboratory experiments constitutes a first step to validate the model on a realistic basis. Copyright © 2001 John Wiley & Sons, Ltd.     

尺度效应的叶面积指数产品真实性检验方法

真实性检验是评价遥感反演产品质量和验证遥感应用产品是否准确、真实地反映实际情况的重要途径。叶面积指数(LAI)是表征陆地植被结构和长势的关键参数,全面准确评价和验证LAI产品是产品用于陆面过程模型的前提。本文以MODIS LAI与GLASS LAI产品为研究对象,在尺度效应和尺度转换的基础上,建立了针对非均匀像元的低分辨率LAI产品真实性检验方法。在考虑空间异质性和植被长势差异的情况下,借助中分辨率的遥感影像,分别利用1 km像元平均叶面积指数和反演表观叶面积指数实现了对LAI算法和产品的真实性检验。为了比较作物长势差异和地表非均匀度对产品的影响,本文选择有代表性的河南鹤壁和甘肃张掖两个地区进行两种LAI产品真实性检验研究。研究结果表明,GLASS LAI和MODIS LAI产品均存在明显的低估现象。这并不是产品算法的问题,而是由于地表异质性和非均匀度的影响。在异质性更显著的张掖盈科灌区,低估现象更明显。GLASS LAI产品是多种LAI产品的融合,它的平均LAI比MODIS更接近真实情况,但是LAI的动态范围比MODIS窄。     

融合像素—多尺度区域特征的高分辨率遥感影像分类算法

针对基于像素多特征的高分辨率遥感影像分类算法的"胡椒盐"现象和面向对象影像分析方法的"平滑地物细节"现象,提出了一种融合像素特征和多尺度区域特征的高分辨率遥感影像分类算法。(1)首先采用均值漂移算法对原始影像进行初始过分割,然后对初始过分割结果进行多尺度的区域合并,形成多尺度分割结果。根据多尺度区域合并RMI指数变化和分割尺度对分类精度的影响,确定最优分割尺度。(2)融合光谱特征、像元形状指数PSI(Pixel Shape Index)、初始尺度和最优尺度区域特征,并对多类型特征进行归一化,最后结合支持向量机(SVM)进行分类。实验结果表明该算法既能有效减少基于像素多特征的高分辨率遥感影像分类算法的"胡椒盐"现象,又能保持地物对象的完整性和地物细节信息,提高易混淆类别(如阴影和街道,裸地和草地)的分类精度。     

Optimal liability apportionment in programmatic credit-based emissions trading

The inclusion of Programmes of Activities (PoAs) within the Clean Development Mechanism (CDM) has been limited by the fact that third-party project validators, who determine the eligibility of a CDM Project Activity (CPA), are currently held liable for any certificates that are erroneously issued. As such, validators must replace any credits issued for the relevant CPA. Moreover, the risk associated with the validation of small-scale CPAs is considerably higher than that associated with traditional CDM projects. Using a simple game-theory model to model the interactions between project validators and coordinators, it is shown that shifting liability for certificates that are erroneously included – from the former to the latter – is never optimal, does not provide a strong enough incentive to enforce first-best levels of due care in CPA selection and inclusion, and can induce overprovision in validation efforts. The main problem with such a simple proportionate liability regime is that an increase in incentives for one player automatically leads to a decrease in incentives for the other. Two additional instruments are also considered that would both rectify this problem and improve the environmental integrity of the CDM mechanism.     

PRINCIPAL COMPONENTS REGRESSION FOR ROUTINE MULTICOMPONENT UV DETERMINATIONS: A VALIDATION PROTOCOL

A validation protocol for multicomponent spectroscopic assays based on principal componentsregression is described. Factorial design and hypothesis tests are used to establish the linearity andabsence of interaction between components in the regression model. Testing considers multiple responsevariables simultaneously so that correlation between residuals is properly treated. Assay reproducibilityand sensitivity to related substances are evaluated.     

Present-day climatology and projected changes of warm and cold days in the CNRM-CM3 global climate model

The impact of global warming on the warmest and coldest days of the annual cycle is explored according to an A2 scenario simulated by the CNRM-CM3 climate model in the framework of the IPCC AR4 intercomparison. Given the multi-model spread in IPCC projections, a validation strategy is proposed using the NCEP/NCAR reanalysis. Validation of the late twentieth century model climatology shows that warm and cold model events are slightly too long and infrequent. Although interannual trends in the warm (cold) day occurrence were positive (negative) only for six (three) of the nine considered sub-continental regions, simulated model trends are always positive (negative). This different behaviour suggests that simulated non-anthropogenic decadal variability is small relative to anthropogenic trends. Large-scale synoptic processes associated with European regional warm and cold peaks are also described and validated. Regional cold peaks are better reproduced than warm peaks, whose intensity accuracy is limited by other physical variables. Positive (negative) winter anomalies of sea and land surface temperature lead to summers with severe (weak) temperatures. These inter-annual anomalies are generated by a persistent pressure dipole over Europe. Regarding climate change, warm (cold) events will become more (less) frequent and longer (shorter). The number of warm days will largely rise and the number of cold days will dramatically decrease. The intensity of warm days will be particularly pronounced over Europe, given the projected summer drying in this region. However, according to the limited skill of the CNRM model, these results must be considered with caution.     

Influence of Thermal Effects on the Wind Field Within the Urban Environment

Micrometeorological conditions in the vicinity of urban buildings strongly influence the requirements that are imposed on building heating and cooling. The goal of the present study, carried out within the Advance Tools for Rational Energy Use towards Sustainability (ATREUS) European research network, is the evaluation of the wind field around buildings with walls heated by solar radiation. Two computational fluid dynamics (CFD) codes were validated against extensive wind-tunnel observations to assess the influence of thermal effects on model performance. The code selected from this validation was used to simulate the wind and temperature fields for a summer day in a specific region of the city of Lisbon. For this study, the meteorological data produced by a non-hydrostatic mesoscale atmospheric model (MM5) were used as boundary conditions for a CFD code, which was further applied to analyze the effects of local roughness elements and thermodynamic conditions on the air flow around buildings. The CFD modelling can also provide the inflow parameters for a Heating, Ventilation and Air Conditioning (HVAC) system, used to evaluate the building energy budgets and to predict performance of the air-conditioning system. The main finding of the present three-dimensional analyses is that thermal forcing associated with the heating of buildings can significantly modify local properties of the air flow.