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Abstract For 118 million residential housing units in the U.S., there is currently a gap between the potential energy savings that can be achieved through the use of existing energy efficiency technologies, and the actual level of energy savings realized, particularly for the 37% of housing units that are considered residential rental properties. Additional quantifiable benefits are needed beyond energy savings to help further motivate residential property owners to invest in energy efficiency upgrades. This research focuses on assessing the adoption of energy efficient upgrades in U.S. residential housing and the impact on rental prices. Ten U.S. cities are chosen for analysis; these cities vary in size across multiple climate zones, and represent a diverse set of housing market conditions. Data was collected for over 159,000 rental property listings, their characteristics, and their energy efficiency measures listed in rental housing postings across each city. Following an extensive data quality control process, over thirty different types energy efficient features were identified. The level of adoption was determined for each city, ranging from 5.3% to 21.6%. Efficient lighting and appliances were among the most common, with many features doubling as energy efficient and other desirable aesthetic or comfort improvements. Then using propensity score matching and conditional mean comparison methods, the relative impact on rent charged in each city was calculated, which ranged from a 6% to 14.1% increase in rent for properties with energy efficient features, demonstrating a positive economic impact of these features, particularly for property owners. This was further subdivided into five types of energy efficiency upgrade and three housing types. Single family homes generally demanded higher premiums with energy efficient features, however there was not a consistent pattern across the types of efficient upgrades. The results of this work demonstrate that investment in energy efficient technologies has quantifiable benefits for rental property owners in the U.S. beyond just energy savings. This methodology and results can also be used in other cities and by property owners, utility companies, or others, ultimately encouraging further investment and positive economic impact in residential energy efficiency and in turn improving energy and resource conservation in the building sector.

This article presents a model of development, civil war and climate change. There are multiple interactions. Economic growth reduces the probability of civil war and the vulnerability to climate change. Climate change increases the probability of civil war. The impacts of climate change, civil war and civil war in the neighbouring countries reduce economic growth. The model has two potential poverty traps – one is climate-change-induced and one is civil-war-induced – and the two poverty traps may reinforce one another. The model is calibrated to sub-Saharan Africa and a double Monte Carlo analysis is conducted in order to account for both parameter uncertainty and stochasticity. Although the IPCC Special Report on Emission Scenarios (SRES) is used as the baseline, thus assuming rapid economic growth in Africa and convergence of African living standards to the rest of the world, the impacts of civil war and climate change (ignored in SRES) are sufficiently strong to keep a number of countries in Africa in deep poverty with a high probability.

Abstract Kenya has made considerable policy efforts to expand its renewable energy portfolio to meet energy demand and mitigate greenhouse gas (GHG) emissions. Development of proper policies requires a robust framework for analyzing the benefits of renewable energy investments. Towards this end, this study applied a choice experiment analysis to determine how attributes (type of energy, ownership, impact on environment, distance and visibility, community job creation, and yearly renewable energy tax) impact the public willingness to pay for renewable energy development in Kenya. A nationwide survey of 1020 households was conducted in nine counties using conditional logit (MNL) and random parameter logit (RPL) frameworks. The results reveal that the Kenyan public places a high value on environmental impact, followed by type of renewable energy and community job creation, respectively. On the other hand, respondents do not place much emphasis on ownership or distance and visibility. Policy simulation suggests that while renewable energy adoption is highly valued by households, the total willingness to pay is not enough to cover the higher capital cost for the development of various renewable energy technologies.

Dans cet article, nous étudions l'utilisation du flux de lots dans les problèmes de planification de flowhop sans permutation. L'objectif est de minimiser le makepan soumis aux contraintes de flowhop standard, mais où il est maintenant autorisé de réorganiser les tâches entre les machines. En outre, les tâches peuvent être divisées en sous-lots gérables, une stratégie connue sous le nom de flux de lots. Les expériences informatiques montrent que le flux de lots réduit le makepan jusqu'à 43% pour un large éventail de cas par rapport au cas où aucun fractionnement de tâches n'est appliqué. Les avantages augmentent à mesure que le nombre d'étapes du processus de production augmente mais atteignent une limite. Au-delà d'un certain point, la division des tâches en sous-lots supplémentaires n'améliore pas la solution. En este documento investigamos el uso de la transmisión de lotes en problemas de programación de Flowshop sin permutación. El objetivo es minimizar el makepan sujeto a las restricciones estándar de Flowshop, pero donde ahora se permite reordenar trabajos entre máquinas. Además, los trabajos se pueden dividir en sublotes manejables, una estrategia conocida como transmisión de lotes. Los experimentos computacionales muestran que la transmisión de lotes reduce el makepan hasta un 43% para una amplia gama de instancias en comparación con el caso en el que no se aplica la división de trabajos. Los beneficios crecen a medida que aumenta el número de etapas en el proceso de producción, pero alcanzan un límite. Más allá de cierto punto, la división de trabajos en sublotes adicionales no mejora la solución. In this paper we investigate the use of lot streaming in non-permutation flowshop scheduling problems.The objective is to minimize the makespan subject to the standard flowshop constraints, but where it is now permitted to reorder jobs between machines.In addition, the jobs can be divided into manageable sublots, a strategy known as lot streaming.Computational experiments show that lot streaming reduces the makespan up to 43% for a wide range of instances when compared to the case in which no job splitting is applied.The benefits grow as the number of stages in the production process increases but reach a limit.Beyond a certain point, the division of jobs into additional sublots does not improve the solution. في هذه الورقة، نتحقق من استخدام تدفق اللوت في مشاكل جدولة ورشة التدفق غير القابلة للتحويل. الهدف هو تقليل فترة التشغيل وفقًا لقيود ورشة التدفق القياسية، ولكن حيث يُسمح الآن بإعادة ترتيب الوظائف بين الآلات. بالإضافة إلى ذلك، يمكن تقسيم الوظائف إلى أقسام فرعية يمكن التحكم فيها، وهي استراتيجية تعرف باسم تدفق اللوت. تظهر التجارب الحاسوبية أن تدفق اللوت يقلل من فترة التشغيل إلى 43 ٪ لمجموعة واسعة من الحالات عند مقارنتها بالحالة التي لا يتم فيها تطبيق تقسيم الوظائف. تنمو الفوائد مع زيادة عدد المراحل في عملية الإنتاج ولكنها تصل إلى حد. بعد نقطة معينة، لا يؤدي تقسيم الوظائف إلى أقسام فرعية إضافية إلى تحسين الحل.

AbstractThe Environmental Kuznets Curve hypothesis suggests that, as a country's national income grows, environmental degradation subsides as the population demands a cleaner environment. On the other hand, critics of the Environmental Kuznets Curve claim that many polluting industries simply relocate offshore, where environmental compliance is less costly. They then export their products back to their previous home countries. This is known as the Pollution Haven hypothesis. This article demonstrates how pollution havens can falsely give the appearance of an Environmental Kuznets Curve by analysing lead emissions from the US automotive tyre manufacturing industry.

SummaryEnvironmentally extended multiregional input‐output (EE MRIO) tables have emerged as a key framework to provide a comprehensive description of the global economy and analyze its effects on the environment. Of the available EE MRIO databases, EXIOBASE stands out as a database compatible with the System of Environmental‐Economic Accounting (SEEA) with a high sectorial detail matched with multiple social and environmental satellite accounts. In this paper, we present the latest developments realized with EXIOBASE 3—a time series of EE MRIO tables ranging from 1995 to 2011 for 44 countries (28 EU member plus 16 major economies) and five rest of the world regions. EXIOBASE 3 builds upon the previous versions of EXIOBASE by using rectangular supply‐use tables (SUTs) in a 163 industry by 200 products classification as the main building blocks. In order to capture structural changes, economic developments, as reported by national statistical agencies, were imposed on the available, disaggregated SUTs from EXIOBASE 2. These initial estimates were further refined by incorporating detailed data on energy, agricultural production, resource extraction, and bilateral trade. EXIOBASE 3 inherits the high level of environmental stressor detail from its precursor, with further improvement in the level of detail for resource extraction. To account for the expansion of the European Union (EU), EXIOBASE 3 was developed with the full EU28 country set (including the new member state Croatia). EXIOBASE 3 provides a unique tool for analyzing the dynamics of environmental pressures of economic activities over time.