A life‐cycle assessment model for zero emission neighborhoods

Buildings represent a critical piece of a low‐carbon future, and their long lifetime necessitates urgent adoption of state‐of‐the‐art performance standards to avoid significant lock‐in risk regarding long‐lasting technology solution choices. Buildings, mobility, and energy systems are closely linked, and assessing their nexus by aiming for Zero Emission Neighborhoods (ZENs) provides a unique chance to contribute to climate change mitigation. We conducted a life‐cycle assessment of a Norwegian ZEN and designed four scenarios to test the influence of the house size, household size, and energy used and produced in the buildings as well as mobility patterns. We ran our scenarios with different levels of decarbonization of the electricity mix over a period of 60 years. Our results show the importance of the operational phases of both the buildings and mobility in the neighborhood's construction, and its decline over time induced by the decarbonization of the electricity mix. At the neighborhood end‐of‐life, embodied emissions then become responsible for the majority of the emissions when the electricity mix is decarbonized. The choice of functional unit is decisive, and we thus argue for the use of a primary functional unit “per neighborhood,” and a second “per person.” The use of a “per m²” functional unit is misleading as it does not give credits to the precautionary use of floor area. To best mitigate climate change, climate‐positive behaviors should be combined with energy efficiency standards that incorporate embodied energy, and absolute threshold should be combined with behavioral changes.     

城市住区绿化生态效益及其可控影响因素的量化分析

基于杭州城西2007年1 m×1 m高分辨率航空遥感图像和夏季30 m×30 m LandsatTM数据,应用GIS和遥感图像解译方法定量计算了代表杭州城西30个典型城市住区总体生态效益的归一化植被指数(NDVI),以及各样本住区6个可控生态效益的影响指标(复层结构高度、软硬比、绿化覆盖率、容积率、绿地面积、建筑密度),并采用多元线性回归和对应分析方法得出6个影响因素对绿化生态效益的贡献度排序,以及提升住区生态效益的措施,分析了城市住区生态效益与典型可控影响因素间的定量关系.结果表明:各影响因素对城市住区生态效益贡献度依次为复层结构高度＞软硬比＞绿化覆盖率＞容积率＞绿地面积＞建筑密度;复层结构高度的贡献率远超过其他因素,建筑密度对住区生态效益的影响极微弱.利用对应分析法所得的各影响因素改进二维图,可方便地用来制定提升住区绿化生态效益的决策方案.     

Oral hygiene and periodontal disease in Victorian nursing homes

doi: 10.1111/j.1741‐2358.2010.00448.x
Oral hygiene and periodontal disease in Victorian nursing homes Objective: To investigate oral hygiene and periodontal disease in residents of Victoria nursing homes. Background: The Australian population is ageing with a growing proportion of elderly Australians living in nursing homes. With declining edentulism rates, periodontal disease is becoming more prevalent in this population. Materials and methods: A total of 275 dentate residents from 31 Victorian nursing homes had a questionnaire and clinical examination using the Visual Plaque Index and a modified Community Periodontal Index. Results: Self‐reported oral hygiene habits of residents were poor, with less than one‐third of residents cleaning their teeth twice daily or more. Periodontal health was found to be extremely poor, and the prevalence of 4 mm+ periodontal pockets was 35.6%, with 10.2% having 6 mm+ pockets. Logistic regression found that age, gender, number of teeth present and oral hygiene were all strongly associated with the prevalence of 4 mm+ periodontal pockets. Conclusion: Poor oral hygiene and the presence of significant plaque and calculus were common findings in this study. Periodontal diseases are a significant problem for residents in nursing homes. Addressing this health issue will require improved training for carers and better access to appropriate dental services.     

Residential magnetic and electric fields

A magnetic flux density (MFD) and electric-field (E-field) data-acquisition system was built for characterizing extremely low-frequency fields in residences. Every 2 min during 24-h periods, MFD and E-field measurements were made in 43 homes in King, Pierce, and Snohomish counties of Washington State. The total electrical energy used in each residence during the 24-h measurement period was also recorded, and maps were drawn to scale of the distribution wiring within 43 m (140 ft) of these homes. Finally, on a separate date, field measurements were made in each home during an epidemiological interview. The results of this study can be summarized as follows: 1) 24-h-average MFD measured at two separate points in the family room were correlated, as were a 24-h-average bedroom measurement and the mean of the two family-room measurements. 2) The 24-h-average family-room MFD and E-field measurements were uncorrelated. 3) The 24-h-average total harmonic distortions of family-room MFD and E-fields were less than about 24% and 7%, respectively. 4) Residential MFD exhibited a definite 24-h (diurnal) cycle. 5) The 24-h-average and interviewer-measured MFD were correlated. 6) Residential 24-h-average MFD were correlated with the wiring code developed by Wertheimer and Leeper. 7) An improved prediction of 24-h-average residential MFD was obtained using the total number of service drops, the distance to neighboring transmission lines, and the number of primary phase conductors.     

Estimating the magnitude of the sum of two magnetic fields with uncertain spatial orientations, polarizations, and/or relative phase.

A problem frequently encountered when modeling the power frequency magnetic fields, B and A, produced by two sources is the necessity of estimating the root mean square (rms) magnitude of their sum, i.e., T = /B + A/, when the rms magnitudes, B and A, of the fields are specified by the model, but not necessarily their spatial directions, polarizations, and/or relative phase. The estimator Q = sqrt [B2+A2] was proposed many years ago for this purpose. The accuracy of this estimator is characterized in this paper. If it is known that B and A are approximately linearly polarized and in phase, the maximum bias (i.e., systematic) and random errors for Q used to estimate T are 6.1 and 35%, respectively, when B = A. These errors decrease as the difference between B and A increases. The bias and random errors are, respectively, 3.2 and 26% when B = 2A or A/2 and 0.2 and 5.8% when B = 10A or A/10. If the directions, relative phase, and polarizations of the two fields are unknown, Q has maximum bias and random errors of approximately 2.6 and approximately 23%, respectively, when B = A. These errors decrease to approximately 1.5 and approximately 18% when B =2 A or A/2 and approximately 0.08 and approximately 4.0% when B = 10A or A/10. If B and A are known to be linearly polarized and collinear, but with unknown phase between them, the maximum bias and random errors are 11 and 48%, respectively, when B = A. The errors are 5.1 and 32% when B = 2A or A/2 and 0.2 and 7.0% when B = 10A or A/10. Estimators for T with zero bias can be derived, but they are more complicated and increase overall accuracy very little.     

云南居民区鼠类体外寄生蚤物种多样性调查

【目的】了解云南居民区鼠类寄生蚤的群落结构和空间分布特征。【方法】根据云南不同经纬度、 海拔等自然环境条件, 于2007年4月-2012年11月, 选取云南17个县(市) 居民区作为样区, 系统开展鼠类体外寄生蚤的调查, 运用群落结构指标对居民区鼠类寄生蚤的群落特征和沿环境梯度的空间分布进行研究。【结果】结果显示： 在调查的17个县(市)室内共检获鼠类体外寄生蚤521头, 隶属4科7亚科9属12种。居民区寄生蚤的纬度和垂直分布类似, 低纬度和低海拔范围的种类相对较少, 印鼠客蚤和缓慢细蚤是室内寄生蚤的优势种。相对纬度和海拔较高的区域, 居民区寄生蚤种类增多, 但优势种不突出; 在经度水平分布上, 蚤种类于99°~101°E经度带形成一个高峰, 室内寄生的优势种印鼠客蚤和缓慢细蚤几乎在所有经度带都可见到分布, 显示了较宽的生态幅。另外, 居民区寄生蚤物种丰富度和多样性指数水平分布（纬度）和垂直分布呈现为单峰格局, 总体显示随着纬度和海拔的升高, 先升高后降低的分布特征, 而在另一个水平分布（经度）, 则呈现由西向东呈递减的趋势。【结论】研究认为, 云南居民区蚤类的空间分布表现为独特的地理区域特征, 气候环境、 森林植被和人类生活生产方式通过影响蚤类栖息生境来影响蚤类的分布。     

Assessing Space Heating Demandon a Regional Level: Evaluation of a Bottom‐Up Model in the Scope of a Case Study

The residential sector constitutes a major energy consumer, particularly on account of its needs for space heating. Offering a high leverage potential, this sector is a suitable starting point for greenhouse gas mitigation policies. By providing predictions of the energy demand of building stocks, bottom‐up building energy models represent a first step toward deriving strategies for abatement of detrimental effects related to housing energy use. This article aims at evaluating the performance of a simplified bottom‐up housing energy model. A global sensitivity analysis was performed to study the model's structure and the impact of individual model parameters. Moreover, an extensive final energy consumption data set allowed for an in‐depth comparison of this model with primary data in the scope of a case study in a Swiss municipality. On an individual building scale, the model fails to accurately simulate the energy demand. Deviations can be attributed to a range of factors, such as variability in occupants’ behavior and problems of representativeness in the underlying statistical database. Nevertheless, such under‐ or overestimations level off on an aggregated scale. In particular, the model reproduces the overall characteristics of the residential building stock's heating demand well. It is therefore well suited as a building stock model and provides a promising basis for an extended assessment of housing energy demands. In future research work, we will apply this model to a larger region in order to study various types of settlements from a life cycle perspective and to derive targeted measures aimed at reducing environmental impacts.     

Feasibility of Water Efficiency and Reuse Technologies as Demand‐Side Strategies for Urban Water Management

Potable residential water efficiency and reuse technologies have seen increasing adoption in recent years and have been estimated to reduce demands by up to 50%. In this work, we used an engineering economic model to estimate the technically feasible levelized cost of water provided by seven above‐code water efficiency (i.e., beyond that required by building code) and reuse technologies within the Lower Colorado River Authority (LCRA) in central Texas. Unlike other demand‐side studies of residential water use, we model uncertainty and variation in technology adoption cost and performance; include reuse technologies; and differentiate between new construction and retrofits. We developed a conservation supply curve to compare the levelized cost of efficiency and reuse technologies with conventional supply‐side water management strategies. We estimate that efficiency and reuse in the residential sector can meet 85% of 50‐year projected needs (the difference between projected demand and estimated supplies) for the LCRA service area. We also estimate lower levelized costs for immediate retrofits of most technologies, promoting incentives for early technology adoption. However, efficiency and reuse technology performance demonstrates considerable uncertainty and variability. The fraction of demands met by demand‐side strategies range from around 60% to 100%. Occupancy drives much of the variability because it significantly affects demand. These results promote designing incentives for adoption of water efficiency and reuse technologies based upon use. We find that water‐efficient showerheads and bathroom faucet aerators perform well over a variety of assumptions, indicating that these technologies should be a priority for municipalities seeking water demand reductions.     

Increases in residential and energy development are associated with reductions in recruitment for a large ungulate

Land‐use change due to anthropogenic development is pervasive across the globe and commonly associated with negative consequences for biodiversity. While land‐use change has been linked to shifts in the behavior and habitat‐use patterns of wildlife species, little is known about its influence on animal population dynamics, despite the relevance of such information for conservation. We conducted the first broad‐scale investigation correlating temporal patterns of land‐use change with the demographic rates of mule deer, an iconic species in the western United States experiencing wide‐scale population declines. We employed a unique combination of long‐term (1980–2010) data on residential and energy development across western Colorado, in conjunction with congruent data on deer recruitment, to quantify annual changes in land‐use and correlate those changes with annual indices of demographic performance. We also examined annual variation in weather conditions, which are well recognized to influence ungulate productivity, and provided a basis for comparing the relative strength of different covariates in their association with deer recruitment. Using linear mixed models, we found that increasing residential and energy development within deer habitat were correlated with declining recruitment rates, particularly within seasonal winter ranges. Residential housing had two times the magnitude of effect of any other factor we investigated, and energy development had an effect size similar to key weather variables known to be important to ungulate dynamics. This analysis is the first to correlate a demographic response in mule deer with residential and energy development at large spatial extents relevant to population performance, suggesting that further increases in these development types on deer ranges are not compatible with the goal of maintaining highly productive deer populations. Our results underscore the significance of expanding residential development on mule deer populations, a factor that has received little research attention in recent years, despite its rapidly increasing footprint across the landscape.     

Dynamic Eco-Efficiency Projections for Construction and Demolition Waste Recycling Strategies at the City Level

In this article we have elaborated a consistent framework for the quantification and evaluation of eco‐efficiency for scenarios for waste treatment of construction and demolition (C&D) waste. Such waste systems will play an increasingly important role in the future, as there has been for many years, and still is, a significant net increase in stock in the built environment. Consequently, there is a need to discuss future waste management strategies, both in terms of growing waste volumes, stricter regulations, and sectorial recycling ambitions, as well as a trend for higher competition and a need for professional and optimized operations within the C&D waste industry. It is within this framework that we develop and analyze models that we believe will be meaningful to the actors in the C&D industry. Here we have outlined a way to quantify future C&D waste generation and have developed realistic scenarios for waste handling based on today's actual practices. We then demonstrate how each scenario is examined with respect to specific and aggregated cost and environmental impact from different end‐of‐life treatment alternatives for major C&D waste fractions. From these results, we have been able to suggest which fractions to prioritize, in order to minimize cost and total environmental impact, as the most eco‐efficient way to achieve an objective of overall system performance.