Effect of spatial variability of cross‐correlated soil properties on bearing capacity of strip footing

Geotechnical engineering problems are characterized by many sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for a probabilistic analysis that considers the spatial variability of cross‐correlated soil properties is presented and applied to study the bearing capacity of spatially random soil with different autocorrelation distances in the vertical and horizontal directions. The approach integrates a commercial finite difference method and random field theory into the framework of a probabilistic analysis. Two‐dimensional cross‐correlated non‐Gaussian random fields are generated based on a Karhunen–Loève expansion in a manner consistent with a specified marginal distribution function, an autocorrelation function, and cross‐correlation coefficients. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses was performed to study the effects of uncertainty due to the spatial heterogeneity on the bearing capacity of a rough strip footing. The simulations provide insight into the application of uncertainty treatment to geotechnical problems and show the importance of the spatial variability of soil properties with regard to the outcome of a probabilistic assessment. Copyright © 2009 John Wiley & Sons, Ltd.     

A shale gas revolution for China?

The question of whether China is on the verge of a ‘shale gas revolution’ is examined. This has potentially significant consequences for energy policy and climate change mitigation. Contrary to the optimistic reading of some commentators, it argues that various technological, environmental, political, regulatory and institutional factors will constrain the growth of China's shale gas market and that such a revolution might in any event have consequences that are at best mixed, at worst antithetical to climate change mitigation.Policy relevanceChina's reserves of unconventional gas have the potential to transform energy policy, as has occurred in the US, resulting in the substitution of shale gas for coal in the energy mix. Because gas emits only approximately half the GHG per unit as coal, such a move would have important implications for climate policy. However, substantial obstacles stand in the way of the ‘energy revolution’ that some policy analysts see China as embarking upon. The need to acknowledge these obstacles, particularly those relating to regulation and governance (and whether or to what extent they can be overcome), is an issue of profound importance to the future of climate and energy policy.     

A stability analysis of a conduit flow model for lava dome eruptions

Periodic variations in magma discharge rate and ground deformation have been commonly observed during lava dome eruptions. We performed a stability analysis of a conduit flow model by Barmin et al. [Barmin, A., Melnik, O., Sparks, R.S.J., 2002. Periodic behavior in lava dome eruptions. Earth and Planetary Science Letters 199 (1-2), 173–184], in which the periodic variations in magma flow rate and chamber pressure are reproduced as a result of the temporal and spatial changes of the magma viscosity controlled by the kinetics of crystallization. The model is reduced to a dynamical system where the time derivatives of the magma flow rate (dQ/dt) and the chamber pressure (dP/dt) are functions of Q and P evaluated at a shifted time t − t_?. Here, the time delay t_? represents the time for the viscosity of fluid particle to increase in a conduit. The dynamical system with time delay is approximated by a simple two-dimensional dynamical system of Q and P where t_? is given as a parameter. The results of our linear stability analyses for these dynamical systems indicate that the transition from steady to periodic flow depends on nonlinearities in the steady state relation between Q and P. The steady state relation shows a sigmoidal curve in Q − P phase plane; its slope has negative values at intermediate flow rates. The steady state solutions become unstable, and hence P and Q oscillate periodically, when the negative slope of the steady state relation ([dP/dQ]_S) exceeds a critical value; that is [dP/dQ]_S < − t_?γ/(2V_ch), where V_ch is the chamber volume and γ is an elastic constant which is related to the rigidity of chamber wall. We also found that the period and the pattern of oscillation of the conduit flow primarily depend on a quantity defined by LV_ch/r⁴, where L is the conduit length and r is the conduit radius.     

Correlation study between ground motion intensity measure parameters and deformation demands for bilinear SDOF systems

The correlation between ground motion intensity measures （IM） and single-degree-of-freedom （SDOF） deformation demands is described in this study. Peak ground acceleration （APG）, peak ground velocity （VPG）, peak ground displacement （DPG）, spectral acceleration at the first-mode period of vibration [As（T1）] and ratio of VPG to APG are used as IM parameters, and the correlation is characterized by correlation coefficients p. The numerical results obtained by nonlinear dynamic analyses have shown good correlation between As（T1） or VPG and deformation demands. Furthermore, the effect of As（T1） and VPG as IM on the dispersion of the mean value of deformation demands is also investigated for SDOF systems with three different periods T=0.3 s, 1.0 s, 3.0 s respectively.     

历史文献中气候信息的评价

本文对我国史料中所载气候信息进行了评价。结论是:①对于史料所载的某一气候事件,我们将其状态分辨取越细,所获取的信息越少;②在分析过程中,对误差要求低些,所获取的信息反而高些;③就已记录的气候事件而言,官方组织的记载所提供的气候信息最多,私人笔札次之,方志类书最次。     

Separate and interactive effects of eutrophication and climate variables on the ecosystem elements of the Gulf of Riga

There is currently a critical knowledge gap in how eutrophication and climate variables separately and interactively impact the dynamics of marine ecosystems. Based on long-term monitoring data we quantified the separate and combined impacts of nutrient loading, temperature, salinity, and wind conditions on zooplankton, zoobenthos and fish inhabiting a brackish water ecosystem in the Gulf of Riga. Changes in zoobenthos communities and herring stock were largely explained by climate variables. Zooplankton species were related to both eutrophication and climate variables, and models combining all environmental variables explained additional variation in zooplankton data compared to the separate models of climate and eutrophication. This suggests that zoobenthos communities and herring stock are largely driven by weather conditions, whereas the combined effect of weather and nutrient loads are likely the cause for dynamic zooplankton communities in the Gulf of Riga.     

Consistency Problem with Tracer Advection in the Atmospheric Model GAMIL

The radon transport test, which is a widely used test case for atmospheric transport models, is carried out to evaluate the tracer advection schemes in the Grid-Point Atmospheric Model of IAP-LASG （GAMIL）. Two of the three available schemes in the model are found to be associated with significant biases in the polar regions and in the upper part of the atmosphere, which implies potentially large errors in the simulation of ozone-like tracers. Theoretical analyses show that inconsistency exists between the advection schemes and the discrete continuity equation in the dynamical core of GAMIL and consequently leads to spurious sources and sinks in the tracer transport equation. The impact of this type of inconsistency is demonstrated by idealized tests and identified as the cause of the aforementioned biases. Other potential effects of this inconsistency are also discussed. Results of this study provide some hints for choosing suitable advection schemes in the GAMIL model. At least for the polax-region-concentrated atmospheric components and the closely correlated chemical species, the Flux-Form Semi-Lagrangian advection scheme produces more reasonable simulations of the large-scale transport processes without significantly increasing the computational expense.     

Uncertainty assessment for watershed water quality modeling: A Probabilistic Collocation Method based approach

Watershed water quality models are increasingly used in management. However, simulations by such complex models often involve significant uncertainty, especially those for non-conventional pollutants which are often poorly monitored. This study first proposed an integrated framework for watershed water quality modeling. Within this framework, Probabilistic Collocation Method (PCM) was then applied to a WARMF model of diazinon pollution to assess the modeling uncertainty. Based on PCM, a global sensitivity analysis method named PCM-VD (VD stands for variance decomposition) was also developed, which quantifies variance contribution of all uncertain parameters. The study results validated the applicability of PCM and PCM-VD to the WARMF model. The PCM-based approach is much more efficient, regarding computational time, than conventional Monte Carlo methods. It has also been demonstrated that analysis using the PCM-based approach could provide insights into data collection, model structure improvement and management practices. It was concluded that the PCM-based approach could play an important role in watershed water quality modeling, as an alternative to conventional Monte Carlo methods to account for parametric uncertainty and uncertainty propagation.     

Geostatistical Simulation of Regionalized Pore-Size Distributions Using Min/Max Autocorrelation Factors

In many fields of the Earth Sciences, one is interested in the distribution of particle or void sizes within samples. Like many other geological attributes, size distributions exhibit spatial variability, and it is convenient to view them within a geostatistical framework, as regionalized functions or curves. Since they rarely conform to simple parametric models, size distributions are best characterized using their raw spectrum as determined experimentally in the form of a series of abundance measures corresponding to a series of discrete size classes. However, the number of classes may be large and the class abundances may be highly cross-correlated. In order to model the spatial variations of discretized size distributions using current geostatistical simulation methods, it is necessary to reduce the number of variables considered and to render them uncorrelated among one another. This is achieved using a principal components-based approach known as Min/Max Autocorrelation Factors (MAF). For a two-structure linear model of coregionalization, the approach has the attractive feature of producing orthogonal factors ranked in order of increasing spatial correlation. Factors consisting largely of noise and exhibiting pure nugget–effect correlation structures are isolated in the lower rankings, and these need not be simulated. The factors to be simulated are those capturing most of the spatial correlation in the data, and they are isolated in the highest rankings. Following a review of MAF theory, the approach is applied to the modeling of pore-size distributions in partially welded tuff. Results of the case study confirm the usefulness of the MAF approach for the simulation of large numbers of coregionalized variables.     

Funding low carbon cities: local perspectives on opportunities and risks

There are compelling reasons for policy makers to be interested in the low-carbon agenda. More than half of the world's population lives in, and more than half of the world's economic output comes from, cities. Up to 70% of global carbon emissions can also be attributed to consumption that takes place in cities. Recent research has shown that cost-effective investments in low-carbon options could deliver a 40% reduction in GHG emissions from cities by 2020, while also providing wider economic benefits such as enhanced competitiveness and increased employment. As yet, however, investments in low-carbon cities have not been made at scale due mainly to the scale of the finance required, local government budgetary constraints, and perceptions about their costs and benefits. With a focus on the UK, a contemporary account is provided of what local authorities see as the major financial risks associated with funding low-carbon cities. Practical proposals – which also have more general relevance to the future financing of low-carbon cities around the world – are offered on how local authorities, in conjunction with central government, the private sector, and institutional investors, can effectively manage these risks.

Policy relevance

Cities house more than half of the world's population, generate more than half of the world's economic output, and produce between 40% and 70% of all anthropogenic GHG emissions. In the UK, 70% of such emissions are under the influence of its local authorities. Thus, one of the key public policy challenges for the low-carbon transition is how it should be financed. There are several obstacles and related risks to this transition, including financial and legal obstacles and the differing views and perceptions of stakeholders. These can be attenuated, somewhat, by national government support at scale, local authority leadership, and cooperation between other authorities and the private sector, and the development of tools and guidance to reduce transaction costs.