Urban riverbank residents’ evaluation of flood evacuation policies in Winnipeg, Manitoba, Canada

The results of a discrete choice experiment (DCE) as a part of a survey among the urban riverbank residents on the Red River in Winnipeg, Manitoba, Canada, indicated that the risk of over-dike flooding, set at 2 ft above the 1997 flood water level, was a significant determinant of both voluntary and mandatory evacuation, compared to those set at the 1996 or 1997 levels. Mandatory evacuation was more preferred over voluntary evacuation when the likelihood of flooding was at its most severe, and the opposite relationship was the case when the likelihood was low. The notification time for evacuation, suggested as 1, 2, and 4 days, proved to be an insignificant attribute, whereas the respondents indicated significant preference for full flood compensation over an offer of either 80% or 90% flood relief, irrespective of the alternatives of voluntary or mandatory evacuation.     

Use of Small-area Data to Support a Community Agenda in Boston Chinatown

Boston Chinatown is a community that grapples with a constant pressure from the downtown area to build new and larger buildings. The effort to preserve the residential aspect of Chinatown has used data analysis in recent years by forming partnerships with academics. This has allowed for more sophisticated studies of traffic injuries, scientific surveys of residents about environmental health, the measurement of noise levels and the construction of physical and electronic mapping of data. While not the only factor contributing to the community's efforts to question the role of development, these data have added useful tools that reduce, but do not eliminate, the disparity between what the community brings to discussions about the environmental impact of development and what the developers have at their disposal.     

Monitoring and assessment of wetlands using Earth Observation: the GlobWetland project

The overall objective of the Ramsar Convention, signed in 1971, is the conservation and wise use of wetlands by national action and international cooperation as a means to achieving sustainable development. This complex and challenging task requires national, local and international bodies involved in the implementation of the convention to rely on suitable geo-information to better understand wetland areas, complete national inventories, perform monitoring activities, carry out assessments and put in practice suitable management plans based on updated and reliable information. In the last years, Earth Observation (EO) technology has been revealed as a key tool and unique information source to support the environmental community in different application domains, including wetlands' conservation and management. In this context, the European Space Agency (ESA) in collaboration with the Ramsar Secretariat launched in 2003 the "GlobWetland" project in order to demonstrate the current capabilities of Earth Observation technology to support inventorying, monitoring, and assessment of wetland ecosystems. This paper collects the main results and findings of the "GlobWetland" project, providing an overview of the current capabilities and limits of EO technology as a tool to support the implementation of the Ramsar Convention. The project was carried out in collaboration with several regional, national and local conservation authorities and wetland managers, involving 50 different wetlands across 21 countries on four continents. This large range of users provided an excellent test bed to assess the potential of this technology to be applied in different technical, economic and social conditions.     

磨料水射流切割与其它方法切割对金相组织影响的试验研究

本文以２０＃优质碳素结构钢为试件，介绍了磨料水射流切割与其它方法切割对金相组织影响的试验。试验结果表明，磨料水射流切割无热影响区。     

Toward an Understanding of Norm Prevalence: A Comparative Analysis of 20 Years of Research

/ Norms are defined as evaluative standards regarding individual behavior or conditions in a given context. They define what behavior should be, rather than actual behavior. Norm prevalence refers to the proportion of individuals in a population who can articulate a norm in a given evaluation context. This paper empirically examines the prevalence of encounter norms in 56 evaluation contexts. Data for this comparative analysis were obtained from 30 studies that used a single-item question asking recreationists to indicate the highest number of encounters they would tolerate before the experience changed. Four predictor variables were examined: (1) type of resource, (2) type of activity, (3) type of encounter, and (4) question response format. As anticipated, norm prevalence varied by type of resource (backcountry or frontcountry), type of encounter (no conflict versus conflict), and question response format (two-category implicit, two-category explicit, and three-category). These three independent variables explained 64% of the variance in norm prevalence. Also as hypothesized, there was no relationship between type of activity (consumptive or nonconsumptive) and norm prevalence. Implications for future research and management are discussed; it is argued that prevalence is an important characteristic of social norms.     

Chemistry and aerosols in the marine boundary layer: 1-D modelling of the three ACE-2 Lagrangian experiments

Three Lagrangian experiments were conducted during IGAC's second aerosol characterization experiment (ACE-2) in the area between Portugal, Tenerife and Madeira in June/July 1997. During each Lagrangian experiment, a boundary layer air mass was followed for about 30 h, and the temporal evolution of its chemical and aerosol composition was documented by a series of vertical profiles and horizontal box pattern flown by the Meteorological Research Flight research aircraft Hercules C130. The wealth of observational data that has been collected during these three Lagrangian experiments is the basis for the development and testing of a one-dimensional Lagrangian boundary layer model with coupled gas, aqueous, and aerosol phase chemistry. The focus of this paper is on current model limitations and strengths. We show that the model is able to represent the dynamical and chemical evolution of the marine boundary layer, in some cases requiring adjustments of the subsidence velocity and of the surface heat fluxes. Entrainment of a layer rich in ozone and carbon monoxide from a residual continental boundary layer into the marine boundary layer as well as in-cloud oxidation of sulphur dioxide by hydrogen peroxide are simulated, and coherent results are obtained, concerning the evolution of the small, presumably sulphate–ammonia aerosol mode.     

Sensitivity of ecological models to their climate drivers: statistical ensembles for forcing.

Global and regional numerical models for terrestrial ecosystem dynamics require fine spatial resolution and temporally complete historical climate fields as input variables. However, because climate observations are unevenly spaced and have incomplete records, such fields need to be estimated. In addition, uncertainty in these fields associated with their estimation are rarely assessed. Ecological models are usually driven with a geostatistical model's mean estimate (kriging) of these fields without accounting for this uncertainty, much less evaluating such errors in terms of their propagation in ecological simulations. We introduce a Bayesian statistical framework to model climate observations to create spatially uniform and temporally complete fields, taking into account correlation in time and space, spatial heterogeneity, lack of normality, and uncertainty about all these factors. A key benefit of the Bayesian model is that it generates uncertainty measures for the generated fields. To demonstrate this method, we reconstruct historical monthly precipitation fields (a driver for ecological models) on a fine resolution grid for a climatically heterogeneous region in the western United States. The main goal of this work is to evaluate the sensitivity of ecological models to the uncertainty associated with prediction of their climate drivers. To assess their numerical sensitivity to predicted input variables, we generate a set of ecological model simulations run using an ensemble of different versions of the reconstructed fields. We construct such an ensemble by sampling from the posterior predictive distribution of the climate field. We demonstrate that the estimated prediction error of the climate field can be very high. We evaluate the importance of such errors in ecological model experiments using an ensemble of historical precipitation time series in simulations of grassland biogeochemical dynamics with an ecological numerical model, Century. We show how uncertainty in predicted precipitation fields is propagated into ecological model results and that this propagation had different modes. Depending on output variable, the response of model dynamics to uncertainty in inputs ranged from uncertainty in outputs that matched that of inputs to those that were muted or that were biased, as well as uncertainty that was persistent in time after input errors dropped.