Energy use,blue water footprint,and greenhouse gas emissions for current food consumption patterns and dietary recommendations in the US

This article measures the changes in energy use, blue water footprint, and greenhouse gas (GHG) emissions associated with shifting from current US food consumption patterns to three dietary scenarios, which are based, in part, on the 2010 USDA Dietary Guidelines (US Department of Agriculture and US Department of Health and Human Services in Dietary Guidelines for Americans, 2010, 7th edn, US Government Printing Office, Washington, 2010). Amidst the current overweight and obesity epidemic in the USA, the Dietary Guidelines provide food and beverage recommendations that are intended to help individuals achieve and maintain healthy weight. The three dietary scenarios we examine include (1) reducing Caloric intake levels to achieve “normal” weight without shifting food mix, (2) switching current food mix to USDA recommended food patterns, without reducing Caloric intake, and (3) reducing Caloric intake levels and shifting current food mix to USDA recommended food patterns, which support healthy weight. This study finds that shifting from the current US diet to dietary Scenario 1 decreases energy use, blue water footprint, and GHG emissions by around 9 %, while shifting to dietary Scenario 2 increases energy use by 43 %, blue water footprint by 16 %, and GHG emissions by 11 %. Shifting to dietary Scenario 3, which accounts for both reduced Caloric intake and a shift to the USDA recommended food mix, increases energy use by 38 %, blue water footprint by 10 %, and GHG emissions by 6 %. These perhaps counterintuitive results are primarily due to USDA recommendations for greater Caloric intake of fruits, vegetables, dairy, and fish/seafood, which have relatively high resource use and emissions per Calorie.     

An improvement selection methodology for key performance indicators

Key performance indicators (KPIs) are critical measures for determining the health of a manufacturing plant in relationship to the plant’s goals. In today’s competitive environment, manufacturers cannot be careless about their business; in fact, they must ensure that their KPIs are effective and use them to make improvements when necessary. This paper describes a method for suggesting improvements to a manufacturer’s KPIs, based on the results achieved from a workshop to score the KPI on a number of predefined criteria. The approach uses a prospect theory approach to weight the scoring. Different problem formulations were derived that allow for both recommendations for improvements and the recommendations for disinvestments to over-performing KPIs. The authors applied the developed approach to two workshop outputs, each from independent manufacturers, and the results highlighted the significant difference between the two manufacturers in terms of improvement priorities and KPI assessment. The optimal improvement suggestions were compared to those found through a fast heuristic. It was determined that given the underlying assumptions of the approach that the heuristic solutions were just as adequate as the optimal ones.     

Heat wave vulnerability and exposure mapping for Osaka City,Japan

Heat waves and heat-related stresses are increasing environmental concerns in urban areas. The impact of heat waves is dependent on the intensity and duration of each event and on underlying environmental and socio-demographic factors which influence population vulnerability. In order to develop effective adaptation strategies, it is important to develop a method to clearly identify the most vulnerable areas based on these factors. The purpose of this study is to develop and map a heat wave vulnerability index combined with heat exposure analysis to identify areas where interventions can be targeted. The vulnerability index was derived from a principle component analysis of eight key variables that influence heat wave vulnerability. Eight proxy measures of vulnerability were obtained from 2010 census and land-use data for the 1904 census districts of Osaka City. Three principle components explained >77 % of the variance (age, employment and education; social isolation; density and lack of green space). The components were combined and weighted to produce a vulnerability score for each census district. The vulnerability scores ranged from 0 to 106, were categorised into eight vulnerability levels and were overlaid with fine-scale air temperature observations. The resulting output identified the distribution of population vulnerability and exposure. This assessment of vulnerability, combining exposure and sensitivity components, can provide precedent for efficient, targeted action to be taken to reduce the impact of heat waves at present and under climate change.     

Responding to a policy mandate to collaborate: structuring collaboration in the collaborative forest landscape restoration program

The Collaborative Forest Landscape Restoration Program (CFLRP) aims to expand the pace and scale of forest restoration on national forests in the United States. The program requires candidate projects to develop landscape-scale forest restoration proposals through a collaborative process and continue to collaborate throughout planning, implementation, and monitoring. Our comparative case analysis of the initial selected projects examines how existing collaborative groups draw on past experience of collaboration and the requirements of a new mandate to shape collaborative structures as they undertake CFLRP work. While mandating collaboration appears contrary to what is often defined as an informal and emergent process, mandates can encourage stakeholder engagement and renew commitment to overcome past conflict. Our findings also suggest that a collaborative mandate can lead to increased attention and scrutiny, prompting adjustments to collaborative process and structure. As such, mandating collaboration creates dynamic tensions between past experience and new requirements for collaborative practice.     

Coupling of the Water Cycle with Patterns of Urban Growth in the Baltimore Metropolitan Region,United States

Regional municipal water plans typically do not recognize complex coupling patterns or that increased withdrawals in one location can result in changes in water availability in others. We investigated the interaction between urban growth and water availability in the Baltimore metropolitan region where urban growth has occurred beyond the reaches of municipal water systems into areas that rely on wells in low‐productivity Piedmont aquifers. We used the urban growth model SLEUTH and the hydrologic model ParFlow.CLM to evaluate this interaction with urban growth scenarios in 2007 and 2030. We found decreasing groundwater availability outside of the municipal water service area. Within the municipal service area we found zones of increasing storage resulting from increased urban growth, where reduced vegetation cover dominated the effect of urbanization on the hydrologic cycle. We also found areas of decreasing storage, where expanding impervious surfaces played a larger role. Although the magnitude of urban growth and change in water availability for the simulation period were generally small, there was considerable spatial heterogeneity of changes in subsurface storage. This suggests that there are locally concentrated areas of groundwater sensitivity to urban growth where water shortages could occur or where drying up of headwater streams would be more likely. The simulation approach presented here could be used to identify early warning indicators of future risk.     

Applying Statistical Causal Analyses to Agricultural Conservation: A Case Study Examining P Loss Impacts

Estimating the effect of agricultural conservation practices on reducing nutrient loss using observational data can be confounded by factors such as differing crop types and management practices. As we may not have the full knowledge of these confounding factors, conventional statistical meta‐analysis methods can be misleading. We discuss the use of two statistical causal analysis methods for quantifying the effects of water and soil conservation practices in reducing P loss from agricultural fields. With the propensity score method, a subset of data was used to form a treatment group and a control group with similar distributions of confounding factors. With the multilevel modeling method, data were stratified based on important confounding factors, and the conservation practice effect was evaluated for each stratum. Both methods resulted in similar estimates of the conservation practice effect (total P load reduction avg. ~70%). In addition, both methods show evidence of conservation practices reducing the incremental increase in total P export per unit increase in fertilizer application. These results are presented as examples of the types of outcomes provided by statistical causal analyses, not to provide definitive estimates of P loss reduction. The enhanced meta‐analysis methods presented within are applicable for improved assessment of agricultural practices and their effects and can be used for providing realistic parameter values for watershed‐scale modeling.     

The IPBES Conceptual Framework: An Unhelpful Start

The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) have recently launched themselves as the UN-sanctioned instrument for conserving nature. They seek to establish themselves as the authority in this field alongside the well-known Intergovernmental Panel on Climate Change in climate science. Quickly following or even before recent publication of their conceptual framework in two biology journals, they were already underway building upon it. This headlong push, we believe, is ill advised. We show how the framework is unsound as a foundation for further work—in a number of ways and perhaps even by its authors’ own lights. It is therefore urgent that the IPBES thoroughly and thoughtfully reconsider their framework before too much effort is wasted.     

Determinants of Individual Attitudes Toward Animal Welfare-Friendly Food Products

Animal welfare involves societal and human values, ethical concerns and moral considerations since it incorporates the belief of what is right or what is wrong in animal treatment and care. This paper aims to ascertain whether the different dimensions of individual attitudes toward animal welfare in food choices may be characterized by general human values, as identified by Schwartz. For this purpose, an EU-wide survey was carried out, covering almost 2500 nationally representative individuals from five European countries. Compared with the previous literature this study shows a twofold novelty: (1) it develops a general framework to link individual enduring beliefs and attitudes toward animal welfare attributes in food choices; (2) the framework is analyzed within a broad-based cross-country study. Our empirical results prove that human values related to self-transcendence are strongly associated to overall animal welfare attitudes and especially to those explicitly related to food choices, while values related to the spheres of self-enhancement and conservatism are significantly associated to less sensitive attitudes to animal welfare. Moreover, our results appear to indicate that a determinant of animal welfarism in food choices is potentially associated to individual concerns regarding food safety issues.     

Photovoltaic-thermal (PV/t) panel to minimize electrical and air conditioning energy consumption of a typical office in Beirut

A combined photovoltaic–thermal (PV/t) panel is proposed to produce simultaneously electricity and heat from one integrated unit. The unit utilizes effectively the solar energy through achieving higher PV electrical efficiency and using the thermal energy for heating applications. To predict the performance of the PV/t at a given environmental conditions, a transient mathematical model was developed. The model was integrated in a heating application for a typical office space in the city of Beirut to provide the office needs for electricity, heating during winter season, and dehumidification and evaporative cooling during the summer season. To minimize the yearly office energy (electrical and heat) needs, the PV/t panel cooling air flow rate and the dehumidification regeneration temperature were determined for opimal unit operation. Thermal energy savings of up to 85% in winter and 71% in summer were achived compared to conventional systems at a payback period of 8 years for the panels.