Perceptions of Ecological Risk Associated with Mountain Pine Beetle (Dendroctonus ponderosae) Infestations in Banff and Kootenay National Parks of Canada

Western Canada is experiencing an unprecedented outbreak of the mountain pine beetle (MPB). The MPB has the potential to impact some of Canada's national parks by affecting park ecosystems and the visitor experience. Controls have been initiated in some parks to lessen the impacts and to prevent the beetle from spreading beyond park boundaries. We examine the perception of ecological risk associated with MPB in two of Canada's national parks, the factors affecting perceptions of risk, and the influence of risk judgments on support for controlling MPB outbreaks in national parks. Data were collected using two studies of park visitors: a mail survey in 2003 and an onsite survey in 2005. The MPB was rated as posing a greater risk to the health and productivity of park ecosystems than anthropogenic hazards and other natural disturbance agents. Visitors who were familiar with MPB rated the ecological and visitor experience impacts as negative, unacceptable, and eliciting negative emotion. Knowledge and residency were the most consistent predictors of risk judgments. Of knowledge, risk, and demographic variables, only sex and risk to ecosystem domains influenced support for controlling the MPB in national parks. Implications for managing MPB in national parks, visitor education, and ecological integrity are discussed.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Socioeconomic Determinants of Health- and Food Safety-Related Risk Perceptions

Individual and societal perceptions of food-related health risks are multidimensional and complex. Social, political, psychological, and economic factors interact with technological factors and affect perceptions in complex ways. Previous research found that the significant determinants of risk perceptions include socioeconomic and behavioral variables. Most of these past results are based on two-way comparisons and factor analysis. The objective of this study was to analyze the significance of socioeconomic determinants of risk perceptions concerning health and food safety. A multivariate approach was used and the results were compared with earlier bivariate results to determine which socioeconomic predictors were robust across methods. There were two major findings in this study. The first was that the results in the multivariate models were generally consistent with earlier bivariate analysis. That is, variables such as household income, number of children, gender, age, and voting preferences were strong predictors of an individual's risk perceptions. The second result was that the gender of the respondent was the only variable found to be robust across all three classes of health and food safety issues across two time periods.     

Psychometric and Demographic Predictors of the Perceived Risk of Terrorist Threats and the Willingness to Pay for Terrorism Risk Management Programs

A 2009 national telephone survey of 924 U.S. adults assessed perceptions of terrorism and homeland security issues. Respondents rated severity of effects, level of understanding, number affected, and likelihood of four terrorist threats: poisoned water supply; explosion of a small nuclear device in a major U.S. city; an airplane attack similar to 9/11; and explosion of a bomb in a building, train, subway, or highway. Respondents rated perceived risk and willingness to pay (WTP) for dealing with each threat. Demographic, attitudinal, and party affiliation data were collected. Respondents rated bomb as highest in perceived risk but gave the highest WTP ratings to nuclear device. For both perceived risk and WTP, psychometric variables were far stronger predictors than were demographic ones. OLS regression analyses using both types of variables to predict perceived risk found only two significant demographic predictors for any threat—Democrat (a negative predictor for bomb) and white male (a significant positive predictor for airline attack). In contrast, among psychometric variables, severity, number affected, and likelihood were predictors of all four threats and level of understanding was a predictor for one. For WTP, education was a negative predictor for three threats; no other demographic variables were significant predictors for any threat. Among psychometric variables, perceived risk and number affected were positive predictors of WTP for all four threats; severity and likelihood were predictors for three; level of understanding was a significant predictor for two.     

Mapping Socioeconomic Exposure for Flood Risk Assessment in Italy

Detailed spatial representation of socioeconomic exposure and the related vulnerability to natural hazards has the potential to improve the quality and reliability of risk assessment outputs. We apply a spatially weighted dasymetric approach based on multiple ancillary data to downscale important socioeconomic variables and produce a grid data set for Italy that contains multilayered information about physical exposure, population, gross domestic product, and social vulnerability. We test the performances of our dasymetric approach compared to other spatial interpolation methods. Next, we combine the grid data set with flood hazard estimates to exemplify an application for the purpose of risk assessment.     

Consortium for Atlantic Regional Assessment: Information Tools for Community Adaptation to Changes in Climate or Land Use

To inform local and regional decisions about protecting short-term and long-term quality of life, the Consortium for Atlantic Regional Assessment (CARA) provides data and tools (for the northeastern United States) that can help decision makers understand how outcomes of their decisions could be affected by potential changes in both climate and land use. On an interactive, user-friendly website, CARA has amassed data on climate (historical records and future projections for seven global climate models), land cover, and socioeconomic and environmental variables, along with tools to help decision makers tailor the data for their own decision types and locations. CARA Advisory Council stakeholders help identify what information and tools stakeholders would find most useful and how to present these; they also provide in-depth feedback for subregion case studies. General lessons include: (1) decision makers want detailed local projections for periods short enough to account for extreme events, in contrast to the broader spatial and temporal observations and projections that are available or consistent at a regional level; (2) stakeholders will not use such a website unless it is visually appealing and easy to find the information they want; (3) some stakeholders need background while others want to go immediately to data, and some want maps while others want text or tables. This article also compares what has been learned across case studies of Cape May County, New Jersey, Cape Cod, Massachusetts, and Hampton Roads, Virginia, relating specifically to sea-level rise. Lessons include: (1) groups can be affected differently by physical dangers compared with economic dangers; (2) decisions will differ according to decision makers' preferences about waiting and risk tolerance; (3) future scenarios and maps can help assess the impacts of dangers to emergency evacuation routes, homes, and infrastructure, and the natural environment; (4) residents' and decision makers' perceptions are affected by information about potential local impacts from global climate change.     

Historical Application of a Social Amplification of Risk Model: Economic Impacts of Risk Events at Nuclear Weapons Facilities

Public perception of risk is being cited as a documented reason to rethink a very contentious congressionally mandated process for siting interim storage and permanent disposal facilities for high-level radioactive waste. Rigorous survey research has shown that the public holds intense, negative images of "nuclear" and "radioactive" technologies, activities, and facilities. Potential host states and opponents claim that these negative images, coupled with an amplification of negative risk events, will potentially stigmatize the area surrounding such facilities and result in significant economic losses. At issue is whether a supporting social amplification of risk model is applicable to communities hosting facilities that are part of the U.S. Department of Energy Nuclear Weapons Complex. An initial assessment of high-profile discrete and cumulative key negative risk events at such nuclear facilities does not validate that there has been stigmatization or substantial social and economic consequences in the host areas. Before any changes to major national policy are implemented, additional research is required to determine if the nearby public's "pragmatic logic," based on practical knowledge and experience, attenuates the link between public opinion and demographic and economic behaviors.     

A national strategic planning model

Can nations choose among several possible futures, or is the future pre-determined on the basis of geographic, demographic, cultural, economic and political features? The author maintains that newly developing patterns may well change the traditional deterministic characteristics of society, and that it is possible for nations to be masters of their own future. This will depend on the development of sophisticated and democratic national planning processes.     

Business in Metropolis: Local Governance of for-Profit Organisations in Finland

European local governments face strong pressures to privatisation and market-based reforms in the near future to combat economic austerity and demands for efficiency. This article shows how Finnish metropolitan city has been able to organise its for-profit activities in the new competitive landscape which requires balancing between political demands, legal restrictions and economic efficiency. The governance of for-profit activities in metropolitan city shows that there is both demand and room for administrative innovation to accommodate past administrative idiosyncrasies to market environment. In conclusion, local governments need to pay attention to their own role in shaping local competitive landscape.     

环境分权、地方政府竞争对绿色技术创新影响的“本地—邻地”效应

随着绿色发展成为五大发展理念之一,各地政府推进绿色技术创新成为降低环境污染和提高增长质量的主要途径。为了考察地方政府环境分权和竞争对绿色技术创新影响的“本地—邻地”效应,本文利用非期望产出EBM模型测度绿色技术创新程度,并将绿色技术创新指数引入动态空间杜宾模型。最后,结合2003-2017年中国省级面板数据进行实证分析。研究发现：(1)绿色技术创新具有显著的路径依赖、空间集聚以及邻近地区的策略竞争效应;(2)环境分权对本地和邻地绿色技术创新的影响呈“U型”变动特征,且现阶段并未跨越分权驱动创新的临界点;(3)环境分权与地方政府竞争的交互效应整体为负,环境行政分权、环境监察分权和环境监测分权等不同类型环境分权采取的策略并不相同;(4)区域环境分权产生的绿色技术创新激励效应存在异质性,中西部地区环境分权对绿色技术创新的激励效果更强。     

“Not in (or Under) My Backyard”: Geographic Proximity and Public Acceptance of Carbon Capture and Storage Facilities

Carbon capture and storage (CCS) is an innovative technical approach to mitigate the problem of climate change by capturing carbon dioxide emissions and injecting them underground for permanent geological storage. CCS has been perceived both positively, as an innovative approach to facilitate a more environmentally benign use of fossil fuels while also generating local economic benefits, and negatively, as a technology that prolongs the use of carbon‐intensive energy sources and burdens local communities with prohibitive costs and ecological and human health risks. This article extends existing research on the “not in my backyard” (NIMBY) phenomenon in a direction that explores the public acceptance of CCS. We utilize survey data collected from 1,001 residents of the coal‐intensive U.S. state of Indiana. Over 80% of respondents express support for the general use of CCS technology. However, 20% of these initial supporters exhibit a NIMBY‐like reaction and switch to opposition as a CCS facility is proposed close to their communities. Respondents’ worldviews, their beliefs about the local economic benefits that CCS will generate, and their concerns about its safety have the greatest impact on increasing or decreasing the acceptance of nearby facilities. These results lend valuable insights into the perceived risks associated with CCS technology and the possibilities for its public acceptance at both a national and local scale. They may be extended further to provide initial insights into likely public reactions to other technologies that share a similar underground dimension, such as hydraulic fracturing.     

A rostering approach to minimize health risks for workers: An application to a container terminal in the Italian port of Genoa

The evolving safety regulation is pushing seaports to comply with safety measures for workers performing heavy loads handling and repetitive movements. This paper proposes a risk-aware rostering approach in maritime container terminals, i.e., it addresses the rostering problem of minimizing and balancing workers’ risk in such terminals. To this end, a mixed integer mathematical programming model incorporating workforce risks is proposed, considering constraints such as the satisfaction of the workforce demand to perform the terminal operations, the worker-task compatibility and restrictions on the sequence of tasks assigned to the same worker. The model has been successfully applied to plan workforce over a six months horizon in a real container terminal located in Northern Italy, the Southern European Container Hub (SECH) in Genoa. As the workforce demand in SECH terminal is available at most two weeks in advance, a rolling horizon planning approach is devised. Experimental tests on real data provided by SECH terminal over a six months planning horizon highlight the effectiveness of the approach - the maximum monthly risk for workers is reduced by 33.9% compared to the current planning – and suitability to other container terminal contexts. Moreover, the model is applicable to a broad range of port situations, and robust enough to need little adaptation.     

Regional Differentials in Unemployment Rates: The Economic Causes

Abstract. Recent studies on the causes that bring about the increase in unemployment rates of the Mezzogiorno area and Italy are mainly based upon demographic and social causes. The aim of this study is to verify if they can be also influenced by economic factors. Through a dynamic model with partial adaptive hypothesis, some ways by which demand affects the differences of regional unemployment rates has been tested. In this respect it has been considered whether variations in economic activity can lead to different growth rates of regional production owing to the different industrial structures; whether the employers are influenced by local factors in varying the occupation when the production increases, and finally in which way the regional unemployment rate depends on the excess of desired, over effective, labour demand. Data base are from 1959 to 1976, and the unemployment rate is referred only to unemployed workers that is the better proxy of the unemployment connected with the economic cycle. The results show a slight reactiveness to demand, both in industrial labour demand and supply in the Mezzogiorno.     

Does federal flood hazard mitigation assistance affect community rating system participation?

With the inexorable march of climate change, increased flooding is inevitable. Understanding the feedback between federal flood mitigation policies and the ways in which local governments build flood resilience is a significant gap in the literature. In particular, the effect that federal flood mitigation grants have on the intensity of local flood mitigation is nonexistent. This work measures flood risk mitigation by using the level of participation in FEMA's Community Rating System (CRS). Communities that participate in the CRS and undertake mitigation are awarded points; more points imply a higher level of participation. Since its inception in 1990, CRS communities have received considerably more federal pre-disaster flood mitigation grants compared to non-CRS communities. This study assesses the effect of federal pre-disaster flood mitigation grants on the level of participation in the CRS program. We use data on Hazard Mitigation Assistance programs and CRS participation data between 2010 and 2015. We link these data to flood risk and socioeconomic information. Our results indicate (i) federal pre-disaster flood mitigation grants do not appear to significantly influence the level of CRS participation, (ii) the effect of flood risk and socioeconomic factors on the level of CRS participation are mixed, and (iii) the current level of CRS participation is influenced by the previous level of CRS participation, which is not tied to federal pre-disaster flood mitigation grant. These findings add to the growing discussions on the drivers and barriers of local flood risk mitigation.     

Crime and Labour Market Opportunities in Italy (1993–2002)

Abstract. This paper investigates the relationship between labour market conditions and crime in Italy accounting for both age and gender in the unemployment measure and considering regional disparities between the North‐Centre and the South of Italy. Using regional data over the period 1993–2002, we study the impact of wages and unemployment on different types of crime. To mitigate omitted variables bias, we control extensively for demographic and socio‐economic variables. Empirical results suggest that unemployment has a large and positive effect on crime rates in southern regions. Our results are robust to model specification, endogeneity, changes in the classification of crimes, and finally, to alternative definitions of unemployment.     

An Integrated Framework for Environmental Multi‐Impact Spatial Risk Analysis

Quantitative risk analysis is being extensively employed to support policymakers and provides a strong conceptual framework for evaluating decision alternatives under uncertainty. Many problems involving environmental risks are, however, of a spatial nature, i.e., containing spatial impacts, spatial vulnerabilities, and spatial risk‐mitigation alternatives. Recent developments in multicriteria spatial analysis have enabled the assessment and aggregation of multiple impacts, supporting policymakers in spatial evaluation problems. However, recent attempts to conduct spatial multicriteria risk analysis have generally been weakly conceptualized, without adequate roots in quantitative risk analysis. Moreover, assessments of spatial risk often neglect the multidimensional nature of spatial impacts (e.g., social, economic, human) that are typically occurring in such decision problems. The aim of this article is therefore to suggest a conceptual quantitative framework for environmental multicriteria spatial risk analysis based on expected multi‐attribute utility theory. The framework proposes: (i) the formal assessment of multiple spatial impacts; (ii) the aggregation of these multiple spatial impacts; (iii) the assessment of spatial vulnerabilities and probabilities of occurrence of adverse events; (iv) the computation of spatial risks; (v) the assessment of spatial risk mitigation alternatives; and (vi) the design and comparison of spatial risk mitigation alternatives (e.g., reductions of vulnerabilities and/or impacts). We illustrate the use of the framework in practice with a case study based on a flood‐prone area in northern Italy.     

Risk Perceptions,General Environmental Beliefs,and Willingness to Address Climate Change

The research reported here examines the relationship between risk perceptions and willingness to address climate change. The data are a national sample of 1225 mail surveys that include measures of risk perceptions and knowledge tied to climate change, support for voluntary and government actions to address the problem, general environmental beliefs, and demographic variables. Risk perceptions matter in predicting behavioral intentions. Risk perceptions are not a surrogate for general environmental beliefs, but have their own power to account for behavioral intentions. There are four secondary conclusions. First, behavioral intentions regarding climate change are complex and intriguing. People are neither nonbelievers who will take no initiatives themselves and oppose all government efforts, nor are they believers who promise both to make personal efforts and to vote for every government proposal that promises to address climate change. Second, there are separate demographic sources for voluntary actions compared with voting intentions. Third, recognizing the causes of global warming is a powerful predictor of behavioral intentions independent from believing that climate change will happen and have bad consequences. Finally, the success of the risk perception variables to account for behavioral intentions should encourage greater attention to risk perceptions as independent variables. Risk perceptions and knowledge, however, share the stage with general environmental beliefs and demographic characteristics. Although related, risk perceptions, knowledge, and general environmental beliefs are somewhat independent predictors of behavioral intentions.     

Determinants and Mapping of Collective Perceptions of Technological Risk: The Case of the Second Nuclear Power Plant in Taiwan

Nuclear power is a highly controversial and salient example of environmental risk. The siting or operating of a nuclear power plant often faces widespread public opposition. Although studies of public perceptions of nuclear power date back to 1970s, little research attempts to explain the spatial heterogeneity of risk attitude toward nuclear power among individuals or communities. This article intends to improve the knowledge about the major factors contributing to nuclear power plant risk perceptions by mapping the geographical patterns of local risk perception and examining the determinants in forming the nature and distribution of the perceived risk among potentially affected population. The analysis was conducted by a case study of the Second Nuclear Power Plant (SNPP) in Taiwan by using a novel methodology that incorporates a comprehensive risk perception (CRP) model into an ethnographic approach called risk perception mapping (RPM). First, we examined the determinants of local nuclear power risk perceptions through the CRP model and multivariate regression analysis. Second, the results were integrated with the RPM approach to map and explain the spatial pattern of risk perceptions. The findings demonstrate that the respondents regard the nuclear power plant as an extremely high‐risk facility, causing them to oppose the SNPP and reject the compensation payment to accept its continuing operation. Results also indicate that perceptions of nuclear power risk were mainly influenced by social trust, psychological and socioeconomic attributes, proximity, and the perceived effects of the SNPP on the quality of everyday life.     

Potential Negative Impacts of Nuclear Activities on Local Economies: Rethinking the Issue

Surveys of public opinion about perceptions of risk associated with the nuclear fuel cycle have shown that the public professes a widespread feeling of dread, a fear of associated stigmas, and a concern about possible catastrophic nuclear accidents. Various interest groups and state governments that oppose congressionally mandated siting of centralized high-level radioactive waste (HLW) storage and disposal facilities are using this negative imagery to create a powerful, emotional obstacle to the siting process. From statistical analyses of images and location preferences, researchers have claimed that possible significant economic losses could potentially accompany the siting of HLW facilities. However, several paradoxes, or self-contradictory statements, apparently exist between the responses expressed in surveys and the actual economic and demographic behavior evidenced in the marketplace. Federal policymakers need to evaluate whether the request for a change in siting policy is based on subjective fear of a potential negative economic effect or on proven negative effects. Empirically observed behavior does not support predicted negative economic effects based on survey responses.     

Optimizing Risk Analysis Relating to External Safety in The Netherlands

Risk analyses in The Netherlands have been optimized so that they now express risks in a numerical form suitable for comparison to national safety standards. This factor is more important to national government than to local authorities; other factors relevant for local authorities are given less emphasis or even completely omitted from the results of the analysis. From a comparison of 16 risk analyses carried out during the last decade, it became clear that in the last 5 years the methods of risk analyses related to external safety have become unified. Results are now presented in terms of individual risk contours and in terms of F-N curves (accident frequency vs. exceeded number of fatalities). This unification seems to be a result of government policy. First, the implementation of the post-Seveso-directive (501/82/EC) in The Netherlands obliges a number of industries to provide the authorities with a quantitative risk assessment. Second, the government has set standards for the maximum permissible risk in residential areas. A unified type of risk analysis is a tool to achieve both these policies. From interviews with local government authorities, however, it has become clear that they need and use some quantitative risk information that is not provided by the unified analysis. They feel they need figures that provide insight into the effects of incidents and into the way effects may change as a result of safety measures. Ultimately, government policy may mean that local officials receive less information than before.