Elite cues,media coverage,and public concern: an integrated path analysis of public opinion on climate change, 2001–2013

To analyze the factors affecting US public concern about the threat of climate change between January 2002 and December 2013, data from 74 separate surveys are used to construct quarterly measures of public concern over global climate change. Five factors should account for changes in levels of concern: extreme weather events, public access to accurate scientific information, media coverage, elite cues, and movement/countermovement advocacy. Structural equation modeling indicates that elite cues, movement advocacy efforts, weather, and structural economic factors influence the level of public concern about climate change. While media coverage exerts an important influence, it is itself largely a function of elite cues and economic factors. Promulgation to the public of scientific information on climate change has no effect. Information-based science advocacy has had only a minor effect on public concern, while political mobilization by elites and advocacy groups is critical in influencing climate change concern.     

Local air pollution and global climate change taxes: a distributional analysis for the case of Spain

Global climate change measures are difficult to implement. In this context, local air pollution measures may play an important role in the political agenda since their effects are felt more immediately by citizens. Distributional implications are one of the main barriers for implementing environmental policies. This paper explores the distributional implications of air pollution taxes and compares them to climate change taxes. For the comparison, both tax schemes were set to yield the same revenue. Methodologically, the study uses a top–down approach linking a macro model to a micro model. We find that taxes on local air pollutants are more regressive than those levied on CO₂. This is because the goods implicitly taxed have a greater weight in the consumer basket of low-income groups, even if the tax revenues are recycled. Furthermore, the revenue-neutral recycle scheme increases both taxes efficiency, but, at the same time, can increase regressivity.     

胶合竹材GluBam甲醛释放影响因素的气候箱实验与分析

胶合竹材GluBam的甲醛释放情况是现代竹结构住宅环保性的一个重要方面,也是竹结构住宅推广中最受关注的指标之一。采用1 m3气候箱对温度、相对湿度和封边情况与GluBam的甲醛释放量和释放速率的相关关系进行了测试,并以一阶单衰减模型为基础提出了GluBam的甲醛释放分析模型。测试和分析结果表明:GluBam板材在各模拟条件下甲醛浓度峰值均小于规范要求;初始甲醛释放量E0和衰减率常数k可以用来评价GluBam的甲醛释放特征;GluBam的醛释放量和释放速率随环境温度和湿度增加而显著增大,且温度因素的影响更大;封边处理可以有效降低GluBam板材的甲醛释放量。     

Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree‐Ring Chronologies1

Anderson, SallyRose, Glenn Tootle, and Henri Grissino‐Mayer, 2012. Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree‐Ring Chronologies. Journal of the American Water Resources Association (JAWRA) 48(4): 849‐858. DOI: 10.1111/j.1752‐1688.2012.00651.x Abstract: Soil moisture is an important factor in the global hydrologic cycle, but existing reconstructions of historic soil moisture are limited. We used tree‐ring chronologies to reconstruct annual soil moisture in the Upper Colorado River Basin (UCRB). Gridded soil moisture data were spatially regionalized using principal components analysis and k‐nearest neighbor techniques. We correlated moisture sensitive tree‐ring chronologies in and adjacent to the UCRB with regional soil moisture and tested the relationships for temporal stability. Chronologies that were positively correlated and stable for the calibration period were retained. We used stepwise linear regression to identify the best predictor combinations for each soil moisture region. The regressions explained 42‐78% of the variability in soil moisture data. We performed reconstructions for individual soil moisture grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained more variance in the datasets. Reconstructed soil moisture data was standardized and compared with standardized reconstructed streamflow and snow water equivalent data from the same region. Soil moisture and other hydrologic variables were highly correlated, indicating reconstructions of soil moisture in the UCRB using tree‐ring chronologies successfully represent hydrologic trends.     

Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins1

Jin, Xin and Venkataramana Sridhar, 2012. Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins. Journal of the American Water Resources Association (JAWRA) 48(2): 197‐220. DOI: 10.1111/j.1752‐1688.2011.00605.x Abstract: In the Pacific Northwest, warming climate has resulted in a lengthened growing season, declining snowpack, and earlier timing of spring runoff. This study characterizes the impact of climate change in two basins in Idaho, the Spokane River and the Boise River basins. We simulated the basin‐scale hydrology by coupling the downscaled precipitation and temperature outputs from a suite of global climate models and the Soil and Water Assessment Tool (SWAT), between 2010 and 2060 and assess the impacts of climate change on water resources in the region. For the Boise River basin, changes in precipitation ranged from ?3.8 to 36%. Changes in temperature were expected to be between 0.02 and 3.9°C. In the Spokane River region, changes in precipitation were expected to be between ?6.7 and 17.9%. Changes in temperature appeared between 0.1 and 3.5°C over a period of the next five decades between 2010 and 2060. Without bias‐correcting the simulated streamflow, in the Boise River basin, change in peak flows (March through June) was projected to range from ?58 to +106 m³/s and, for the Spokane River basin, the range was expected to be from ?198 to +88 m³/s. Both the basins exhibited substantial variability in precipitation, evapotranspiration, and recharge estimates, and this knowledge of possible hydrologic impacts at the watershed scale can help the stakeholders with possible options in their decision‐making process.     

System Dynamics to Sustainable Water Resources Management in the Eastern Snake Plain Aquifer Under Water Supply Uncertainty1

Abstract: Water supply uncertainty continues to threaten the reliability of regional water resources in the western United States. Climate variability and water dispute potentials induce water managers to develop proactive adaptive management strategies to mitigate future hydroclimate impacts. The Eastern Snake Plain Aquifer in the state of Idaho is also facing these challenges in the sense that population growth and economic development strongly depend on reliable water resources from underground storage. Drought and subsequent water conflict often drive scientific research and political agendas because water resources availability and aquifer management for a sustainable rural economy are of great interest. In this study, a system dynamics approach is applied to address dynamically complex problems with management of the aquifer and associated surface‐water and groundwater interactions. Recharge and discharge dynamics within the aquifer system are coded in an environmental modeling framework to identify long‐term behavior of aquifer responses to uncertain future hydrological variability. The research shows that the system dynamics approach is a promising modeling tool to develop sustainable water resources planning and management in a collaborative decision‐making framework and also to provide useful insights and alternative opportunities for operational management, policy support, and participatory strategic planning to mitigate future hydroclimate impacts in human dimensions.     

A case study of REDD+ challenges in the post‐2012 climate regime: The scenarios approach

The REDD+ (Reducing Emissions from Deforestation and Forest Degradation) partnership works to promote the reduction of greenhouse gas (GHG) emissions by protecting forests in developing countries through positive incentives. It is regarded as an essential component of the post‐2012 climate regime to stabilize GHG emissions and engage developing countries in worldwide mitigation endeavours. This study focuses on the gap between agricultural revenue and REDD+ compensation through the construction of several scenarios that explore the impacts of possible carbon price ranges.Three scenarios that reflect different potential policies are examined: (1) current carbon trading; (2) carbon trading with all forestry activities; and (3) carbon trading with all countries participating gradually over the coming decades. Data for developing the scenarios were obtained through a case study in central Kalimantan, Indonesia, by interrogating the potential for revenue by expanding agricultural land. The results indicate that REDD+ payments could not effectively compensate land users for their opportunity cost of deforestation, making it difficult for the governments to ensure that REDD+ money “reaches the ground” in terms of balancing the agricultural revenue of land users.     

Generation of Monthly Precipitation Under Climate Change for the Upper Blue Nile River Basin,Ethiopia1

Abstract: This work develops a methodology to project the future precipitation in large river basins under limited data and climate change while preserving the historical temporal and spatial characteristics. The computationally simple and reliable conditional generation method (CGM) is presented and applied to generate reliable monthly precipitation data in the upper Blue Nile River Basin of Ethiopia where rain‐fed agriculture is prevalent. The results showed that the temporal analysis with the CGM performs better to reproduce the historical long‐term characteristics than other methods, and the spatial analysis with the CGM reproduced the historical spatial structure accurately. A 100‐year time series analysis using the outcomes of the six general circulation models showed that precipitation changes by the 2050s (2040 through 2069) can be ?7 to 28% with a mean increase of about 11%. The seasonal results showed increasing wet conditions in all seasons with changes of mean precipitation of 5, 47, and 6% for wet, dry, and mild seasons, respectively.     

边坡变形时序非线性判定及混沌预测研究

以探讨边坡变形性质及混沌预测可行性为目的,基于混沌理论利用相空间重构技术对其变形时间序列进行混沌特征判定,试验显示变形系统具有混沌特性,可用混沌相关理论进行研究;基于混沌相空间重构技术,笔者构建了多种混沌预测模型进行混沌预计研究,分析各类模型的工程实际应用效果;针对单次监测时序预测精度较低的问题,提出累加时序预测方案,训练结果显示,短期预测精度变形累计值基本控制在5%以内,高程值预测相对误差均低于1%,预测精度较高,可以用于工程实际。     

Evaluation of a healthcare safety climate measurement tool

Problem

Psychometrically validated measurement tools are needed to evaluate an organization's safety climate. In 2000, Gershon and colleagues published a new healthcare safety climate measurement tool to determine its relationship to safe work behavior (Gershon, R., Karkashian, C., Grosch, J., Murphy, L., Escamilla-Cejudo, A., Flanagan, P., et al. (2000). Hospital safety climate and its relationship with safe work practices and workplace exposure incidents. American Journal of Infection Control, 28, 211-21). The present study evaluated the psychometric properties of the Gershon tool when modified to address respiratory rather than bloodborne pathogen exposures.

Method

Medical practitioners, nurses, and nurse aides (n = 460) were surveyed using the modified Gershon tool. Data were analyzed by factor analysis and psychometric properties of the tool evaluated.

Results

Eight safety climate dimensions were extracted from 25 items (Cronbach's alpha range: 0.62 - 0.88). Factor extractions and psychometric properties were reasonably consistent with those of the Gershon tool.

Impact on Industry

The Gershon safety climate tool appears to have sufficient reliability and validity for use by healthcare decision makers as an indicator of employee perceptions of safety in their institution.