The feasibility and importance of considering climate change impacts in building retrofit analysis

Impacts of climate change on U.S. building energy use by using downscaled hourly future weather data

Today, there is a great deal of emphasis on reducing energy use in buildings for both economic and environmental reasons. Investors strongly encourage the insulating of buildings. Buildings without cooling systems can lead to a deterioration in thermal comfort, even in transitional climate areas. In this article, the effectiveness of natural ventilation in a passive cooling building is analyzed. Two options are considered: cooling with external air supplied to the building by fans, or by opening windows (automatically or by residents). In both cases, fuzzy controllers for the cooling time and supply airflow control are proposed and optimized. The analysis refers to a typical Polish single-family building. Simulations are made with the use of the EnergyPlus program, and the model is validated based on indoor temperature measurement. The calculations were carried out for different climate data: standard and future (warmed) weather data. Research has shown that cooling with external air can effectively improve thermal comfort with a slight increase in heating demand. However, to be able to reach the potential of such a solution, fans should be used.

A fresh look at weather impact on peak electricity demand and energy use of buildings using 30-year actual weather data

Buildings are subject to many uncertainties ranging from thermophysical performance to user activity. Climate change is an additional source of uncertainty that complicates building performance evaluation. This study aims to quantify the share of uncertainties stemming from building factors, user behavior, and climate uncertainty from boilers, chillers, fans, pumps, total HVAC systems, and total site energy use. A novel method combining Monte Carlo analysis and ANOVA is proposed to partition uncertainties from building energy simulation results under different climate change scenarios. The Monte Carlo method is used to generate distributions of building and user factors as building simulation inputs. Then, simulation results under current and future climate conditions are post-processed using a three-way ANOVA technique to discretize the uncertainties for a reference office building in Philadelphia, PA. The proposed method shows the share in percentages of each input factor (building, user, and climate) in the total uncertainty of building energy simulation output results. Our results indicate that the contribution of climate uncertainty increases from current conditions to future climate scenarios for chillers, boilers, fans, and pumps’ electricity use. User parameters are the dominant uncertainty factor for total site energy use and fans’ electricity use. Moreover, boiler and HVAC energy use are highly sensitive to the shape and range of user and building input factor distributions. We underline the importance of selecting the appropriate distribution for input factors when partitioning the uncertainties of building performance modeling.

Impact of climate change on building energy use in different climate zones and mitigation and adaptation implications

Hourly air temperature projection in future urban area by coupling climate change and urban heat island effect

William Solecki,1,a Cynthia Rosenzweig,2,a Reginald Blake,3,a Alex de Sherbinin,4 Tom Matte,5 Fred Moshary,6 Bernice Rosenzweig,7 Mark Arend,6 Stuart Gaffin,8 Elie Bou-Zeid,9 Keith Rule,10 Geraldine Sweeny,11 and Wendy Dessy11 1City University of New York, CUNY Institute for Sustainable Cities, New York, NY. 2Climate Impacts Group, NASA Goddard Institute for Space Studies, Center for Climate Systems Research, Columbia University Earth Institute, New York, NY. 3Physics Department, New York City College of Technology, CUNY, Brooklyn, NY; Climate Impacts Group, NASA Goddard Institute for Space Studies. 4 Center for International Earth Science Information Network (CIESIN), Columbia University, Palisades, NY. 5New York City Department of Health and Mental Hygiene, New York, NY. 6NOAA CREST, City College of New York, CUNY, New York, NY. 7CUNY Environmental Crossroads, City College of New York, CUNY, New York, NY. 8Center for Climate Systems Research, Columbia University Earth Institute, New York, NY. 9Department of Civil & Environmental Engineering, Princeton University, Princeton, NJ. 10Princeton Plasma Physics Laboratory, Princeton, NJ. 11New York City Mayor’s Office of Operation, New York, NY

Over the past three decades research on energy use in buildings has become significant due to increasing scientific and political pressure on issues concerning global warming and climate change. As part of the impact by climate change, tropical nations are faced with several challenges in achieving energy savings, particularly the energy consumption behaviour of building occupants, with very little research coming from Africa. Previous research has shown that variations due to occupant behaviour is substantial. To address these challenges in line with the objectives of some of the UN Sustainable Development Goals (SDGs) (namely, clean and sustainable energy, as well as climate action) in residential buildings, this paper explores the perceptions of stakeholders by identifying the barriers which affect energy use from different cultural perspectives. Qualitative data were collected using semi-structured telephone interviews with experts in the energy and construction fields in Nigeria. The purpose of the interviews was to provide an insight into residential energy consumption behaviour and the barriers faced in the adoption of sustainable energy sources. The results were analysed using an energy cultural framework. An analysis of the results shows that continuous awareness of energy saving behavioural change, government subsidies for renewable energy, government checks, and the standardization of energy-efficient appliances imported into the country can improve people’s trust regarding sustainable choices and can promote efficient energy use. The outcome from this work is expected to give a better understanding of energy use behaviour and inform future energy policies and interventions related to household energy saving.

The use of energy in buildings is a complex problem, but it can be reduced and alleviated by making appropriate decisions. Therefore, architects face a major and responsible task of designing the built environment in such a way that its energy dependence will be reduced to a minimum, while at the same time being able to provide comfortable living conditions. Today, architects have many tools at their disposal, facilitating the design process and simultaneously ensuring proper assessment in the early stages of building design. The purpose of this book is to present ongoing research from the universities involved in the project Creating the Network of Knowledge Labs for Sustainable and Resilient Environments (KLABS). This book attempts to highlight the problem of energy use in buildings and propose certain solutions. It consists of nine chapters, organised in three parts. The gathering of chapters into parts serves to identify the different themes that the designer needs to consider, namely energy resources, energy use and comfort, and energy efficiency. Part 1, entitled “Sustainable and Resilient Energy Resources,” sets off by informing the reader about the basic principles of energy sources, production, and use. The chapters give an overview of all forms of energies and energy cycle from resources to end users and evaluate the resilience of renewable energy systems. This information is essential to realise that the building, as an energy consumer, is part of a greater system and the decisions can be made at different levels. Part 2, entitled “Energy and Comfort in the Built Environment”, explain the relationship between energy use and thermal comfort in buildings and how it is predicted. Buildings consume energy to meet the users’ needs and to provide comfort. The appropriate selection of materials has a direct impact on the thermal properties of a building. Moreover, comfort is affected by parameters such as temperature, humidity, air movement, air quality, lighting, and noise. Understanding and calculating those conditions are valuable skills for the designers. After the basics of energy use in buildings have been explained, Part 3, entitled “Energy Saving Strategies” aims to provide information and tools that enable an energy- and environmentally-conscious design. This part is the most extensive as it aims to cover different design aspects. Firstly, passive and active measures that the building design needs to include are explained. Those measures are seen from the perspective of heat flow and generation. The Passive House concept, which is explained in the second chapter of Part 3, is a design approach that successfully incorporates such measures, resulting in low energy use by the building. Other considerations that the following chapters cover are solar control, embodied energy and CO2 emissions, and finally economic evaluation. The energy saving strategies explained in this book, despite not being exhaustive, provide basic knowledge that the designer can use and build upon during the design of new buildings and existing building upgrades. In the context of sustainability and resilience of the built environment, the reduction of energy demand is crucial. This book aims to provide a basic understanding of the energy flows in buildings and the subsequent impact for the building’s operation and its occupants. Most importantly, it covers the principles that need to be taken into account in energy efficient building design and demonstrates their effectiveness. Designers are shaping the built environment and it is their task to make energy-conscious and informed decisions that result in comfortable and resilient buildings.

Climate change, caused by increased emissions produced by human activities, can make a building deviate from its original design and disrupt building energy operations. Building designs need to account for future climate scenarios and effective adaptation and mitigation measures are needed. However, the future is unknown, and climate models only present a snapshot of what the future climate may look like and have many uncertainties. Building energy operations can also be influenced by users and building thermophysical factors which are dynamic and can change through time. Climate uncertainty adds to this uncertainty and complicates evaluating building energy performance and makes classical deterministic approaches in assessing building energy unreliable. Therefore, there is an urgent need for analytical methods in building design to account for climate change while considering uncertainties. This work investigated a critical gap in our understanding of how to address uncertainties associated with building energy use under competing climate change scenarios over their lifetime. The scientific innovation of this work is the integration of climate change-driven building energy modeling with uncertainty analysis. First, the impact of climate change on building energy use and potential response measures are given. Next, methods to generate future weather files which can be directly incorporated into building energy use are examined. Then, a hybrid method to quantify the share of uncertainties from building factors, users and climate is presented by combining ANOVA and Monte Carlo analysis. Finally, a new method is proposed to propagate climate change uncertainties into building energy use by combining regression analysis and Monte Carlo. It was found that downscaling climate models using weather generators can add to existing uncertainties. Buildings should be designed through a framework of possibilities and vulnerabilities to reflect a range of solutions that best suits the intended design. The uncertainty partitioning method has the potential to show the share of uncertainties from climate, user and building factors for any energy use indicator up to the end century. The method was found to be sensitive to input distributions of uncertainty factors. The uncertainty propagation method can be used to provide valuable insight on interpreting the impact of climate uncertainties on building energy use. It can be used where limited future weather files can be generated and reduces computational needs. Results of this work can be leveraged towards enhancing analytical methods in building designs and simulation tools under climate change and towards overcoming limitations of classical approach.

S team systems are a ubiquitous element in nearly every type of manufacturing plant. In the United States, steam systems are the single largest consumer of energy in the industrial sector, where they account for 37% of annual onsite energy use. Steam use is particularly prominent in the chemicals, paper, petroleum refining, and food and beverage industries, where it is used in a wide range of processes, including reforming, distillation, concentration, cooking, and drying. Together, these four industries comprise nearly 90% of U.S. industrial steam demand, with chemicals manufacturing (30%) and paper manufacturing (30%) holding the largest shares. At the national level, industrial steam systems account for around 6% of U.S. total primary energy use, or 5,900 trillion British thermal units (TBtu). As such, much attention has been paid to steam system energy efficiency improvements as part of corporate, utility, and government energy and air pollution initiatives. Key incentives include local utility rebates, tax incentives, and lowor no-cost steam system energy efficiency audits. Steam system energy efficiency not only makes sense from an environmental perspective, but also from an economic perspective. As of 2006, U.S. manufacturers spent $21 billion on externally purchased boiler fuels. The actual price tag of industrial steam is likely much higher; nearly one-half of U.S. boiler fuels are self-generated within plants in the form of waste gas, black liquor, wood wastes, and other byproducts. These byproduct fuels are not free, as they are generated from purchased materials and typically require further processing for efficient combustion. Reducing demand for boiler fuels can, therefore, help reduce operating costs and improve profit margins. While clearly justified, the historical focus on reducing energy use has overlooked an increasingly compelling benefit of steam system efficiency: namely, reduced water use. Compared to the many public and private incentives for industrial energy efficiency, there are surprisingly few external incentives for industrial water efficiency. One key barrier to such incentives is the lack of credible data on industrial water use, which, unlike data on energy use, are not compiled at the manufacturing industry or process level in regular national surveys. This dearth of data contributes to a general lack of awareness of the sources and scale of industrial water use within the engineering and policy communities, which limits broader attention to water efficiency beyond the plant floor. Another barrier to steam system water efficiency is that the cost of boiler water—and the associated chemicals required for its treatment—typically only represents a small fraction of boiler operating costs, which are dominated by the costs of fuel. However, as we discuss in this Perspective, U.S. industrial steam systems consume copious amount of water. It follows that steam systems are worth a closer look as a manufacturing water efficiency target. Several current trends suggest that water efficiency will play an increasingly prominent role in the financial and sustainability plans of U.S. manufacturers. Recent water stress due to droughts and rising water infrastructure costs have led to increased public water rates around the country. These conditions may worsen with a changing climate. An increasing number of manufacturers are reporting water use as an important environmental indicator in annual corporate sustainability reports, which raises both public awareness of and accountability for water efficiency. Many manufacturers are also being asked by their corporate customers for environmental “footprint” data as part of large-scale sustainable Correspondence concerning this article should be addressed to E. Masanet at eric.masanet@northwestern.edu; M.E. Walker at mwalker9@hawk.iit.edu.

A century ago, the world had many cities of which the greatest were magnificent centers of culture and commerce. However, even in the most industrialized countries at the time, only a tiny fraction of the people lived in these cities. Most people lived in rural areas, in small towns, in villages, and on farms. Visits to a great city were, for most of the population, uncommon events often of great fascination. The world has changed dramatically in the intervening years. Now most of the industrial world lives in urban areas in close proximity to large cities. Industry is often located in these vast urban areas. As the urbanized zones grow in extent, they begin to approach one another, as on the East Coast of the United States. The phenomenon of urbanization has moved to developing countries as well. There has been a flood of migrants who have left impoverished rural areas to seek economic opportunities in urban areas throughout the developing world. This movement from the countryside to cities has changed the entire landscape and economies of developing nations. Importantly, the growth of cities places very great demands on infrastructure. Transportation systems are needed to assure that a concentrated population can receive food from the countryside without fail. They are needed to assure personal and work-related travel. Water supplies must be created, water must be purified and maintained pure, and this water must be made available to a large population. Medical services--and a host of other vital services--must be provided to the population. Energy is a vital underpinning of all these activities, and must be supplied to the city in large quantities. Energy is, in many ways, the enabler of all the other services on which the maintenance of urban life depends. In this paper, we will discuss the evolution of energy use in residential and commercial buildings. This topic goes beyond urban energy use, as buildings exist in both urban and non-urban areas. The topic does not address all energy use in cities--urban transportation is clearly important. However, buildings are the largest energy consumer in cities by a wide margin. (A typical Western home will consume at least five times as much energy as the typical car that services it.) As we note later, buildings consume more than one-third of total commercial energy globally. In developing countries, a large portion of energy use in buildings is in urban areas even though there are still large populations in rural areas. This is because vast quantities of non-commercial energy--residue from plants, farm products, forests and dung from animals--are used to provide the services needed in households (primarily cooking and water heating) in many rural areas. Most of industrial energy use (which accounts for slightly more than 40 percent of global energy use) is outside of urban areas. Thus, any effort to address energy use in urban areas needs necessarily to deal with the energy use in buildings.

Anthropogenic heat generated by building energy use contributes to the urban island and climate change. Quantifying high spatiotemporal resolution city scale building energy use (BEU) and anthropogenic heat emission (AHE) is necessary for understanding urban microclimate and sustainable development. However, the current shortage of such data is insufficient to support urban energy management and climate decision-making. We estimated BEU and AHE from buildings in Hong Kong using a GIS-based city-scale building energy model (GIS-CBEM) and investigated their spatiotemporal variations. First, all buildings were categorized into 11 types, and a prototype was developed for each type. These prototypes were then calibrated using annual building energy consumption data from surveys. We studied the energy use profile for each building prototypes under the Typical Meteorological Year (TMY) weather data. Then, we estimated hourly BEU and AHE for all buildings in Hong Kong at the individual building level. The study results unveiled the spatiotemporal variation of buildings in Hong Kong at high resolution and detected divergent structure of building end-use and fuel use for different building prototypes. We found that the total BEU of all buildings in Hong Kong peaked at 5.1 × 109 kWh in August, with 36.7% from HAVC system, while the lowest BEU was found in February at 3.5 ×109kWh, with 14.1% from HAVC system. Total AHE from all buildings reached a maximum of 8.1 × 109 kWh in July and minimum of 4.1 × 109 kWh in February. Our findings have critical significance in enhancing energy efficiency, reducing environmental impact, and promoting sustainable development.

Assessment of climate change impact on building energy use and mitigation measures in subtropical climates

Setyawan AD, Supriatna J, Nisyawati, Sutarno, Sugiyarto, Nursamsi I. 2018. Predicting impacts of future climate change on the distribution of the widespread selaginellas (Selaginella ciliaris and S. plana) in Southeast Asia. Biodiversitas 19: 1960-1977. The current global climate is moving towards dangerous and unprecedented conditions that have been seen as a potentially devastating threat to the environment and all living things. Selaginella is a fern-allies that needs water as a medium for fertilization, hence its distribution is presumed to be affected by climate change. In Southeast Asia (SEA), there are two widely distributed selaginellas, namely Selaginella ciliaris and S. plana. S. ciliaris is a small herb (up to 4 cm), annual, abundant during the rainy season, and found in the middle-high plains, whereas S. plana is a stout large herb (up to 80 cm), perennial, and mainly found in the lowlands. The purpose of this study was to determine the potential niche distribution of S. ciliaris and S. plana under current climatic conditions, and to predict its future distribution under the impacts of climate change. We used Maxent software along with bioclimatic, edaphic, and UV radiation variables to model the potential niche distribution of those two selaginellas under current and future predictions climate conditions. We generated future predictions under four detailed bioclimatic scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) over three times intervals (2030, 2050, 2080). The results showed that future climatic conditions in the SEA had been predicted to significantly disrupt the distribution of suitable habitat of S. ciliaris and S. plana, and alter their geographic distribution patterns. Although some areas were predicted to become suitable habitat in the early period of future climate change, the overall projections show adverse effects of future climate conditions on the suitable habitat distribution of S. ciliaris and S. plana, as estimated losses of suitable habitat will be higher than the gains.