Environmental impacts of household appliances in Europe and scenarios for their impact reduction

Assessing the environmental impact due to consumption of goods and services is a pivotal step towards achieving the sustainable development goal related to responsible production and consumption (i.e. SDG 12). Household appliances plays a crucial role and should be assessed in a systemic manner, namely considering all life cycle stages, technological efficiency, and affluence aspects. The present study assess the impact of such household appliances used in Europe, and tests scenarios of potential impact reduction at various scales. Life cycle assessment is applied to 14 different household appliances (ranging from dishwashers to television devices) selected to build a set of representative products, based on their economic value and diffusion in households in Europe. Related impacts are calculated with the Environmental Footprint method for calculating a Consumer Footprint “appliances” for the baseline year 2010. A number of scenarios encompassing eco-solutions on a technical level, changes in consumption pattern, behavioral changes, as well as the combination of all these aspects are run to estimate the Consumer Footprint related to household appliances for the year 2030, compared against this baseline scenario. The baseline Consumer Footprint is confirming the importance of the use phase in leading the impacts in almost all impact categories. Testing different scenarios concludes that there is a reduction of the impact for most of the categories (with up to 67% for the ozone depletion potential, and still around 35% for the global warming potential), while two of the here examined impact categories (i.e. land-use and mineral resource depletion) show an overall potential that is even negative – i.e. the results of all scenarios are higher than the ones of the 2010 baseline scenario. The increase in purchase and use of such appliances may offset energy efficiency benefits in some of the examined categories. Hence, the assessment of sustainability of appliances consumption should always include several scales, from the efficiency of the products (micro scale), to the improvement of the energy mix (meso scale), up to accounting for socio-economic drivers and patterns of consumption affecting the overall appliances stock (macro scale).     

Environmental impacts of household appliances in Europe and scenarios for their impact reduction

Assessing the environmental impact due to consumption of goods and services is a pivotal step towards achieving the sustainable development goal related to responsible production and consumption (i.e. SDG 12). Household appliances plays a crucial role and should be assessed in a systemic manner, namely considering all life cycle stages, technological efficiency, and affluence aspects. The present study assess the impact of such household appliances used in Europe, and tests scenarios of potential impact reduction at various scales. Life cycle assessment is applied to 14 different household appliances (ranging from dishwashers to television devices) selected to build a set of representative products, based on their economic value and diffusion in households in Europe. Related impacts are calculated with the Environmental Footprint method for calculating a Consumer Footprint “appliances” for the baseline year 2010. A number of scenarios encompassing eco-solutions on a technical level, changes in consumption pattern, behavioral changes, as well as the combination of all these aspects are run to estimate the Consumer Footprint related to household appliances for the year 2030, compared against this baseline scenario. The baseline Consumer Footprint is confirming the importance of the use phase in leading the impacts in almost all impact categories. Testing different scenarios concludes that there is a reduction of the impact for most of the categories (with up to 67% for the ozone depletion potential, and still around 35% for the global warming potential), while two of the here examined impact categories (i.e. land-use and mineral resource depletion) show an overall potential that is even negative – i.e. the results of all scenarios are higher than the ones of the 2010 baseline scenario. The increase in purchase and use of such appliances may offset energy efficiency benefits in some of the examined categories. Hence, the assessment of sustainability of appliances consumption should always include several scales, from the efficiency of the products (micro scale), to the improvement of the energy mix (meso scale), up to accounting for socio-economic drivers and patterns of consumption affecting the overall appliances stock (macro scale).     

Forecasting private consumption: survey‐based indicators vs. Google trends

In this study we introduce a new indicator for private consumption based on search query time series provided by Google Trends. The indicator is based on factors extracted from consumption‐related search categories of the Google Trends application Insights for Search. The forecasting performance of the new indicator is assessed relative to the two most common survey‐based indicators: the University of Michigan Consumer Sentiment Index and the Conference Board Consumer Confidence Index. The results show that in almost all conducted in‐sample and out‐of‐sample forecasting experiments the Google indicator outperforms the survey‐based indicators. This suggests that incorporating information from Google Trends may offer significant benefits to forecasters of private consumption. Copyright © 2011 John Wiley & Sons, Ltd.     

Inferential processes in the construction of scenarios

The process of scenario construction is not yet well understood. Procedures appeal to the ‘disciplined intuition’ of experts. From a psychological perspective, however, generating scenarios represents a most difficult cognitive task. Two cognitive functions involved in this task are discussed: forward inferences and backward inferences. Whereas forward inferences explore the implications of given options and help to identify potential consequences, backward inferences explore the implications of given goals and help identify potential options. The first process leads to an exploratory scenario, the second to an anticipatory scenario. It is argued that the two approaches, applied to the same problem, result in different scenarios, i.e. scenarios that differ in their elements, their structures, their ranges and their ‘holes’. A bi-directional construction method is suggested that balances the drawbacks implied in using one cognitive strategy only (e.g. forward inference) by using complementarily the other strategy (e.g. backward inference). In contrast to other methods proposed in the literature, this method is theoretically derived and can be tested empirically.     

Comparing Small‐ and Large‐Scale Models of Multicategory Buying Behavior

Focusing on the interdependence of product categories we analyze multicategory buying decisions of households by a finite mixture of multivariate Tobit‐2 models with two response variables: purchase incidence and expenditure. Mixture components can be interpreted as household segments. Correlations for purchases of different categories turn out to be much more important than correlations among expenditures as well as correlations among purchases and expenditures of different categories. About 18% of all pairwise purchase correlations are significant. We compare the best‐performing large‐scale model with 28 categories to four small‐scale models each with seven categories. In our empirical study the large‐scale model clearly attains a better forecasting performance. The small‐scale models provide several biased correlations and miss about 50% of the significant correlations which the large scale model detects. Copyright © 2013 John Wiley & Sons, Ltd.     

When and how to use scenario planning: A heuristic approach with illustration

This paper offers a step-by-step analysis of a heuristic approach to scenario planning, taking a managerial perspective. The scenario method is contrasted in general with more traditional planning techniques, which tend to perform less well when faced with high uncertainty and complexity. An actual case involving a manufacturing company is used to illustrate the main steps of the proposed heuristic. Its essence is to identify relevant trends and uncertainties, and blend them into scenarios that are internally consistent. In addition, the scenarios should bound the range of plausible uncertainties and challenge managerial thinking. Links to decision making are examined next, including administrative policies as well as integrative techniques. At the strategic level, a key-success-factor matrix is proposed for integrating scenarios, competitor analysis and strategic vision. At the operational level, Monte Carlo simulation is suggested and illustrated as one useful technique for combining scenario thinking with formal project evaluation (after appropriate translations). The paper concludes with a general discussion of scenario planning, to place it in a broader perspective.     

A new method of scenario analysis for strategic planning

We first present scenario analysis as a qualitative forecasting technique useful for strategic planning. Then we develop an overview of the two classes of methods for scenario analysis described in the literature. Based on both classes, a new method is developed which especially fits the needs of strategic planning. The method can be divided into three stages: 1. Determination of compatible scenarios, 2. Determination of scenario probabilities, and 3. Determination of main scenarios. An example is given to illustrate the method.     

A re‐examination of the excess smoothness puzzle when consumers estimate the income process

The excess smoothness puzzle is explored using a simple version of the permanent income hypothesis. The new feature is that consumers do not know the observed data‐generating process for income. Instead they estimate the income process every period using the past income data and update their income forecasts as new data arrive. Two scenarios are examined: first, where the income has a linear deterministic trend and second, where the income has a constant trend. There is a misspecification bias in the estimate of the marginal propensity to consume (MPC). This bias is of second‐order importance in the first scenario while it is of first‐order importance in the second. We conclude that the second scenario, which may be relevant for less developed countries, may offer a potential solution to the excess smoothness puzzle. Copyright © 2001 John Wiley & Sons, Ltd.     

It starts at home? Climate policies targeting household consumption and behavioral decisions are key to low-carbon futures

Through their consumption behavior, households are responsible for 72% of global greenhouse gas emissions. Thus, they are key actors in reaching the 1.5 °C goal under the Paris Agreement. However, the possible contribution and position of households in climate policies is neither well understood, nor do households receive sufficiently high priority in current climate policy strategies. This paper investigates how behavioral change can achieve a substantial reduction in greenhouse gas emissions in European high-income countries. It uses theoretical thinking and some core results from the HOPE research project, which investigated household preferences for reducing emissions in four European cities in France, Germany, Norway and Sweden. The paper makes five major points: First, car and plane mobility, meat and dairy consumption, as well as heating are the most dominant components of household footprints. Second, household living situations (demographics, size of home) greatly influence the household potential to reduce their footprint, even more than country or city location. Third, household decisions can be sequential and temporally dynamic, shifting through different phases such as childhood, adulthood, and illness. Fourth, short term voluntary efforts will not be sufficient by themselves to reach the drastic reductions needed to achieve the 1.5 °C goal; instead, households need a regulatory framework supporting their behavioral changes. Fifth, there is a mismatch between the roles and responsibilities conveyed by current climate policies and household perceptions of responsibility. We then conclude with further recommendations for research and policy.     

It starts at home? Climate policies targeting household consumption and behavioral decisions are key to low-carbon futures

Through their consumption behavior, households are responsible for 72% of global greenhouse gas emissions. Thus, they are key actors in reaching the 1.5 °C goal under the Paris Agreement. However, the possible contribution and position of households in climate policies is neither well understood, nor do households receive sufficiently high priority in current climate policy strategies. This paper investigates how behavioral change can achieve a substantial reduction in greenhouse gas emissions in European high-income countries. It uses theoretical thinking and some core results from the HOPE research project, which investigated household preferences for reducing emissions in four European cities in France, Germany, Norway and Sweden. The paper makes five major points: First, car and plane mobility, meat and dairy consumption, as well as heating are the most dominant components of household footprints. Second, household living situations (demographics, size of home) greatly influence the household potential to reduce their footprint, even more than country or city location. Third, household decisions can be sequential and temporally dynamic, shifting through different phases such as childhood, adulthood, and illness. Fourth, short term voluntary efforts will not be sufficient by themselves to reach the drastic reductions needed to achieve the 1.5 °C goal; instead, households need a regulatory framework supporting their behavioral changes. Fifth, there is a mismatch between the roles and responsibilities conveyed by current climate policies and household perceptions of responsibility. We then conclude with further recommendations for research and policy.     

Energy demand forecasts with investment constraints

The energy sector in India claims 30% of the available investments. Moreover, oil import bills have the largest share among the total import bills. Thus, macro economic development and energy sector are highly interdependent. Where energy demand is forecasted without these linkages one cannot be sure if investments and imports required for energy sector will be available. The SImulation of MAcroeconomic scenarios (SIMA) model generates macroeconomically consistent energy scenarios from two interlinked submodels i.e. economic and energy submodels. The energy sector is a part of the non-agricultural sector but it is linked to both the agricultural and the non-agricultural sectors. These three sectors compete with each other for the available capital. In a two-step procedure, various energy economy relations are econometrically estimated and then these are solved simultaneously by feeding in the exogenous parameters (population, oil prices, etc.). The scenarios created correspond to 1991–2010. They are the Dynamics As Usual and the High Oil Price scenarios with capital required for phasing in the electricity sector. Energy-related emission levels for pollutants such as CO₂, NO_x and SO₂ emissions are also calculated for each scenario.     

Scenario planning: An investigation of the construct and its measurement

Scenario‐planning academicians and practitioners have been observing for more than three decades the importance of this method in dealing with environmental uncertainty. However, there has been no valid scale that may help organizational leaders to act in practice. Our review of prior studies identifies some problems related to conceptualization, reliability, and validity of this construct. We address these concerns by developing and validating a measure of scenario planning based on Churchill's paradigm (Journal of Marketing Research, 1979, 16, 64–73). Our data analysis follows from a sample of 133 managers operating in the healthcare field in France. To validate our scale, we used three approaches: first, an exploratory factor analysis; second, an examination of psychometric proprieties of all dimensions; and third, a confirmatory factor analysis. The results of this study indicate that scenario planning is a multidimensional construct composed of three dimensions: information acquisition, knowledge dissemination, and scenario development and strategic choices.     

Forecasting vehicle holdings and usage with a disaggregate choice model

A case study in which a three-stage choice model of Canadian household vehicle holdings and usage is used to generate short-run forecasts of changes in household vehicle usage and gasoline consumption in response to a range of energy-related policies. The objectives of this case study are to (1) demonstrate the application of disaggregate choice modelling methods to the generation of policy-relevant forecasts of travel behaviour; (2) draw implications from this forecasting exercise concerning the likely impacts of various energy-related policies; and (3) assess some of the strengths and weaknesses of the current state-of-the-art of forecasting with disaggregate choice models, using the presented study as a case in point.     

Cellular and molecular mechanisms of alcohol-induced osteopenia

Alcoholic beverages are widely consumed, resulting in a staggering economic cost in different social and cultural settings. Types of alcohol consumption vary from light occasional to heavy, binge drinking, and chronic alcohol abuse at all ages. In general, heavy alcohol consumption is widely recognized as a major epidemiological risk factor for chronic diseases and is detrimental to many organs and tissues, including bones. Indeed, recent findings demonstrate that alcohol has a dose-dependent toxic effect in promoting imbalanced bone remodeling. This imbalance eventually results in osteopenia, an established risk factor for osteoporosis. Decreased bone mass and strength are major hallmarks of osteopenia, which is predominantly attributed not only to inhibition of bone synthesis but also to increased bone resorption through direct and indirect pathways. In this review, we present knowledge to elucidate the epidemiology, potential pathogenesis, and major molecular mechanisms and cellular effects that underlie alcoholism-induced bone loss in osteopenia. Novel therapeutic targets for correcting alcohol-induced osteopenia are also reviewed, such as modulation of proinflammatory cytokines and Wnt and mTOR signaling and the application of new drugs.     

Forecasting market potential and market penetration of residential water heater load control programs

This paper presents a model which estimates market potential and forecasts market penetration for one demand-side management (DSM) programwater heater load controlin the service territory of Virginia Power Corporation, a large electric utility in the south-eastern United States. Water heater load control is a voluntary program where customers are paid a monthly incentive to allow the utility to shut off power to their electric water heaters during periods of peak demand. Reducing the level of peak demand through DSM programs is one way for utilities to avoid building new power plants. The current total energy (or demand) impact due to a load control program is the sum of the changes in energy (or demand) for all program participants. The projected energy and demand impact due to a load control program is the average change per participant multiplied by the number of participants or adopters of the program. While it is reasonably straightforward to measure the energy savings resulting from shutting off power to a water heater, the more difficult task for planning purposes is forecasting the number of customers who will actually join the program (i.e. the market penetration) for a given incentive. The customer decision process is divided into three stages: eligibility, awareness, and adoption. The responsiveness of market penetration to changes in advertising and incentive amounts is demonstrated. In addition, the impact of changing advertising and incentive amounts on the percentage of aware customers who adopt the program and on that of eligible customers who become aware of the program is estimated. This model can be used by utility planners and managers to forecast the market penetration of both new and existing load control programs. In addition, it can be employed to estimate the impact of various promotion and marketing schemes on both market potential and market penetration.     

抑郁模型大鼠海马突触的差异蛋白质组学分析

目的通过抑郁模型大鼠海马突触的差异蛋白质组学分析,为抑郁症发病机制研究提供依据。方法根据糖水消耗基线值将40只健康雄性Sprague—Dawley大鼠随机分为慢性轻度不可预见性应激组和对照组（每组20只）。通过CUMS实验模式建立大鼠抑郁模型后,运用蔗糖密度梯度离心法提取两组大鼠的海马突触并用透射电镜进行检测。采用传统的双向凝胶电泳和基质辅助激光解析电离飞行时间串联质谱进行差异蛋白质组学分析。结果在行为学评价中CUMS组大鼠糖水消耗量和偏好度均降低（P〈0．01）,表明大鼠抑郁模型建立成功。通过结合双向凝胶电泳和质谱分析,共得到6个在CUMS组表达上调和10个在CUMS组表达下调的蛋白质,这些蛋白质的功能主要归为四类,即囊泡调节／递质释放／信号转导、能量代谢、细胞骨架、物质代谢。结论通过对抑郁模型大鼠海马突触的比较蛋白质组学分析及后续的蛋白质功能预测,发现了一些与突触传导功能障碍可能相关的蛋白质,从而为抑郁症发病机制的研究提供了有价值的线索。     

A comparison of temperature density forecasts from GARCH and atmospheric models

Density forecasts for weather variables are useful for the many industries exposed to weather risk. Weather ensemble predictions are generated from atmospheric models and consist of multiple future scenarios for a weather variable. The distribution of the scenarios can be used as a density forecast, which is needed for pricing weather derivatives. We consider one to 10‐day‐ahead density forecasts provided by temperature ensemble predictions. More specifically, we evaluate forecasts of the mean and quantiles of the density. The mean of the ensemble scenarios is the most accurate forecast for the mean of the density. We use quantile regression to debias the quantiles of the distribution of the ensemble scenarios. The resultant quantile forecasts compare favourably with those from a GARCH model. These results indicate the strong potential for the use of ensemble prediction in temperature density forecasting. Copyright © 2004 John Wiley & Sons, Ltd.     

The Role of Survey Data in Nowcasting Euro Area GDP Growth

This paper evaluates the impact of new releases of financial, real activity and survey data on nowcasting euro area gross domestic product (GDP). We show that all three data categories positively impact on the accuracy of GDP nowcasts, whereby the effect is largest in the case of real activity data. When treating variables as if they were all published at the same time and without any time lag, financial series lose all their significance, while survey data remain an important ingredient for the nowcasting exercise. The subsequent analysis shows that the sectoral coverage of survey data, which is broader than that of timely available real activity data, as well as their information content stemming from questions focusing on agents' expectations, are the main sources of the ‘genuine’ predictive power of survey data. When the forecast period is restricted to the 2008–09 financial crisis, the main change is an enhanced forecasting role for financial data. Copyright © 2015 John Wiley & Sons, Ltd.     

尺度效应及其节水灌溉策略

根据湖北省漳河灌区不同尺度水分生产率和水分利用情况，本文讨论了灌溉水利用中的尺度效应和传统灌溉效率指标在节水效果评估及水资源调配决策中的局限性。由于节水灌溉的相对性和尺度效应，在采用节水灌溉技术和制定节水灌溉发展策略时，应该分析不同尺度节水的潜力及其相互影响，以保证投资的有效性，并达到田间、灌溉系统和流域尺度真实节水效果的一致。     

Interweaving categories: Styles,paradigms, and models

Analytical categories of scientific cultures have typically been used both exclusively and universally. For instance, when styles of scientific research are employed in attempts to understand and narrate science, styles alone are usually employed. This article is a thought experiment in interweaving categories. What would happen if rather than employ a single category, we instead investigated several categories simultaneously? What would we learn about the practices and theories, the agents and materials, and the political-technological impact of science if we analyzed and applied styles (à la Hacking and Crombie), paradigms (à la Kuhn), and models (à la van Fraassen and Cartwright) simultaneously? I address these questions in general and for a specific case study: a brief history of systematics.