scholarly journals Resilience of a Building to Future Climate Conditions in Three European Cities

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4506 ◽  
Author(s):  
Virgilio Ciancio ◽  
Serena Falasca ◽  
Iacopo Golasi ◽  
Pieter de Wilde ◽  
Massimo Coppi ◽  
...  

Building energy need simulations are usually performed using input files that contain information about the averaged weather data based on historical patterns. Therefore, the simulations performed are not able to provide information about possible future scenarios due to climate change. In this work, future trends of building energy demands due to the climate change across Europe were studied by comparing three time steps (present, 2050, and -2080) in three different European cities, characterized by different Köppen-Geiger climatic classes. A residential building with modern architectural features was taken into consideration for the simulations. Future climate conditions were reached by applying the effects of climate changes to current hourly meteorological data though the climate change tool world weather file generator (CCWorldWeatherGen) tool, according to the guidelines established by the Intergovernmental Panel on Climate Change. In order to examine the resilience of the building, the simulations carried out were compared with respect to: peak power, median values of the power, and energy consumed by heating and cooling system. The observed trend shows a general reduction in the energy needs for heating (–46% for Aberdeen, –80% for Palermo, –36% for Prague in 2080 compared to the present) and increase (occurrence for Aberdeen) in cooling requirements. These results imply a revaluation of system size.

2021 ◽  
Vol 43 ◽  
pp. e56026
Author(s):  
Gabriela Leite Neves ◽  
Jorim Sousa das Virgens Filho ◽  
Maysa de Lima Leite ◽  
Frederico Fabio Mauad

Water is an essential natural resource that is being impacted by climate change. Thus, knowledge of future water availability conditions around the globe becomes necessary. Based on that, this study aimed to simulate future climate scenarios and evaluate the impact on water balance in southern Brazil. Daily data of rainfall and air temperature (maximum and minimum) were used. The meteorological data were collected in 28 locations over 30 years (1980-2009). For the data simulation, we used the climate data stochastic generator PGECLIMA_R. It was considered two scenarios of the fifth report of the Intergovernmental Panel on Climate Change (IPCC) and a scenario with the historical data trend. The water balance estimates were performed for the current data and the simulated data, through the methodology of Thornthwaite and Mather (1955). The moisture indexes were spatialized by the kriging method. These indexes were chosen as the parameters to represent the water conditions in different situations. The region assessed presented a high variability in water availability among locations; however, it did not present high water deficiency values, even with climate change. Overall, it was observed a reduction of moisture index in most sites and in all scenarios assessed, especially in the northern region when compared to the other regions. The second scenario of the IPCC (the worst situation) promoting higher reductions and dry conditions for the 2099 year. The impacts of climate change on water availability, identified in this study, can affect the general society, therefore, they must be considered in the planning and management of water resources, especially in the regional context


2016 ◽  
Vol 48 (5) ◽  
pp. 1327-1342 ◽  
Author(s):  
Spyridon Paparrizos ◽  
Andreas Matzarakis

Assessment of future variations of streamflow is essential for research regarding climate and climate change. This study is focused on three agricultural areas widespread in Greece and aims to assess the future response of annual and seasonal streamflow and its impacts on the hydrological regime, in combination with other fundamental aspects of the hydrological cycle in areas with different climate classification. ArcSWAT ArcGIS extension was used to simulate the future responses of streamflow. Future meteorological data were obtained from various regional climate models, and analysed for the periods 2021–2050 and 2071–2100. In all the examined areas, streamflow is expected to be reduced. Areas characterized by continental climate will face minor reductions by the mid-century that will become very intense by the end and thus these areas will become more resistant to future changes. Autumn season will face the strongest reductions. Areas characterized by Mediterranean conditions will be very vulnerable in terms of future climate change and winter runoff will face the most significant decreases. Reduced precipitation is the main reason for decreased streamflow. High values of actual evapotranspiration by the end of the century will act as an inhibitor towards reduced runoff and partly counterbalance the water losses.


2021 ◽  
pp. 1420326X2199391
Author(s):  
Naveen Kishore

This paper aims to investigate the implication of present and future bioclimatic potential of passive heating and cooling design strategies for climate change scenarios of five locations covering all climate zones of India. Weather data for future climate change were developed for A2 (medium-high) scenario of the Intergovernmental Panel on Climate Change (IPCC) for four time slices, namely TMY (Typical Meteorological Year), 2020, 2050 and 2080. A case study residential building was used for calibration and validation of the bioclimatic potential using EnergyPlus simulation. Results show a strong correlation between the annual bioclimatic summer and winter discomfort hours and the corresponding annual cooling and heating energy load for the changing climate scenarios. Results also show an overall increase in annual cooling energy load, over and above the base case, ranging from 18% to 89% among the five cities in 2020; 32% to 132% in 2050 and 58% to 184% in 2080 if residential buildings continue to be operated in the same manner as it is done today without passive strategies. The use of passive strategies may reduce the annual cooling load by about 50%– 60% in residential buildings in future.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 802
Author(s):  
Kristian Skeie ◽  
Arild Gustavsen

In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings.


2021 ◽  
Author(s):  
Erik Engström ◽  
Cesar Azorin-Molina ◽  
Lennart Wern ◽  
Sverker Hellström ◽  
Christophe Sturm ◽  
...  

<p>Here we present the progress of the first work package (WP1) of the project “Assessing centennial wind speed variability from a historical weather data rescue project in Sweden” (WINDGUST), funded by FORMAS – A Swedish Research Council for Sustainable Development (ref. 2019-00509); previously introduced in EGU2019-17792-1 and EGU2020-3491. In a global climate change, one of the major uncertainties on the causes driving the climate variability of winds (i.e., the “stilling” phenomenon and the recent “recovery” since the 2010s) is mainly due to short availability (i.e., since the 1960s) and low quality of observed wind records as stated by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC).</p><p>The WINDGUST is a joint initiative between the Swedish Meteorological and Hydrological Institute (SMHI) and the University of Gothenburg aimed at filling the key gap of short availability and low quality of wind datasets, and improve the limited knowledge on the causes driving wind speed variability in a changing climate across Sweden.</p><p>During 2020, we worked in WP1 to rescue historical wind speed series available in the old weather archives at SMHI for the 1920s-1930s. In the process we followed the “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization. Our protocol consisted on: (i) designing a template for digitization; (ii) digitizing papers by an imaging process based on scanning and photographs; and (iii) typing numbers of wind speed data into the template. We will report the advances and current status, challenges and experiences learned during the development of WP1. Until new year 2020/2021 eight out of thirteen selected stations spanning over the years 1925 to 1948 have been scanned and digitized by three staff members of SMHI during 1,660 manhours.</p>


2021 ◽  
Author(s):  
luis Augusto sanabria ◽  
Xuerong Qin ◽  
Jin Li ◽  
Robert Peter Cechet

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.


2019 ◽  
Vol 111 ◽  
pp. 06056
Author(s):  
Kuo-Tsang Huang ◽  
Yu-Teng Weng ◽  
Ruey-Lung Hwang

These future building energy studies mainly stem from hourly based dynamic building simulation results with the future weather data. The reliability of the future building energy forecast heavily relies on the accuracy of these future weather data. The global circulation models (GCMs) provided by IPCC are the major sources for constructing future weather data. However, there are uncertainties existed among them even with the same climate change scenarios. There is a need to develop a method on how to select the suitable GCM for local application. This research firstly adopted principal component analysis (PCA) method in choosing the suitable GCM for application in Taiwan, and secondly the Taiwanese hourly future meteorological data sets were constructed based on the selected GCM by morphing method. Thirdly, the future cooling energy consumption of an actual office building in the near (2011-2040), the mid (2041-2070), and the far future (2071-2100), were analysed. The results show that NorESM1-M GCM has the lowest root mean square error (RMSE) as opposed to the other GCMs, and was identified as the suitable GCM for further future climate generation processing. The building simulation against the future weather datasets revealed that the average cooling energy use intensity (EUIc) in Taipei will be increased by 12%, 17%, and 34% in the 2020s, 2050s, and 2080s, respectively, as compared to the current climate.


Author(s):  
Guillaume Rohat ◽  
Stéphane Goyette ◽  
Johannes Flacke

Purpose Climate analogues have been extensively used in ecological studies to assess the shift of ecoregions due to climate change and the associated impacts on species survival and displacement, but they have hardly been applied to urban areas and their climate shift. This paper aims to use climate analogues to characterize the climate shift of cities and to explore its implications as well as potential applications of this approach. Design/methodology/approach The authors propose a methodology to match the current climate of cities with the future climate of other locations and to characterize cities’ climate shift velocity. Employing a sample of 90 European cities, the authors demonstrate the applicability of this method and characterize their climate shift from 1951 to 2100. Findings Results show that cities’ climate shift follows rather strictly north-to-south transects over the European continent and that the average southward velocity is expected to double throughout the twenty-first century. These rapid shifts will have direct implications for urban infrastructure, risk management and public health services. Originality/value These findings appear to be potentially useful for raising awareness of stakeholders and urban dwellers about the pace, magnitude and dynamics of climate change, supporting identification of the future climate impacts and vulnerabilities and implementation of readily available adaptation options, and strengthening cities’ cooperation within climate-related networks.


2020 ◽  
Vol 4 (1) ◽  
pp. 15-22
Author(s):  
Muhammad Taqui ◽  
Jabir Hussain Syed ◽  
Ghulam Hassan Askari

Pakistan’s largest city, Karachi, which is industrial centre and economic hub needs focus in research and development of every field of Engineering, Science and Technology. Urbanization and industrialization is resulting bad weather conditions which prolongs until a climate change. Since, Meteorology serves as interdisciplinary field of study, an analytical study of real and region-specific meteorological data is conducted which focuses on routine, extreme and engineering meteorology of metropolitan city Karachi. Results of study endorse the meteorological parameters relationship and establish the variability of those parameters for Karachi Coastal Area. The rise of temperature, decreasing trend of atmospheric pressure, increment in precipitation and fall in relative humidity depict the effects of urbanization and industrialization. The recorded extreme maximum temperature of 45.50C (on June 11, 1988) and the extreme minimum temperature of 4.5 0C(on January 1, 2007) is observed at Karachi south meteorological station. The estimated temperature rise in 32 years is 0.9 0C, which is crossing the Intergovernmental Panel on Climate Change (IPCC) predicted/estimated limit of 2oC rise per century. The maximum annual precipitation of 487.0mm appearing in 1994 and the minimum annual precipitation of 2.5mm appearing in 1987 is observed at same station which is representative meteorological station for Karachi Coast. Further Engineering meteorological parameters for heating ventilation air condition (HVAC) system design for industrial purpose are deduced as supporting data for coastal area site study for industrial as well as any follow-up engineering work in the specified region.


Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4805
Author(s):  
Shu Chen ◽  
Zhengen Ren ◽  
Zhi Tang ◽  
Xianrong Zhuo

Globally, buildings account for nearly 40% of the total primary energy consumption and are responsible for 20% of the total greenhouse gas emissions. Energy consumption in buildings is increasing with the increasing world population and improving standards of living. Current global warming conditions will inevitably impact building energy consumption. To address this issue, this report conducted a comprehensive study of the impact of climate change on residential building energy consumption. Using the methodology of morphing, the weather files were constructed based on the typical meteorological year (TMY) data and predicted data generated from eight typical global climate models (GCMs) for three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5) from 2020 to 2100. It was found that the most severe situation would occur in scenario RCP8.5, where the increase in temperature will reach 4.5 °C in eastern Australia from 2080–2099, which is 1 °C higher than that in other climate zones. With the construction of predicted weather files in 83 climate zones all across Australia, ten climate zones (cities)—ranging from heating-dominated to cooling-dominated regions—were selected as representative climate zones to illustrate the impact of climate change on heating and cooling energy consumption. The quantitative change in the energy requirements for space heating and cooling, along with the star rating, was simulated for two representative detached houses using the AccuRate software. It could be concluded that the RCP scenarios significantly affect the energy loads, which is consistent with changes in the ambient temperature. The heating load decreases for all climate zones, while the cooling load increases. Most regions in Australia will increase their energy consumption due to rising temperatures; however, the energy requirements of Adelaide and Perth would not change significantly, where the space heating and cooling loads are balanced due to decreasing heating and increasing cooling costs in most scenarios. The energy load in bigger houses will change more than that in smaller houses. Furthermore, Brisbane is the most sensitive region in terms of relative space energy changes, and Townsville appears to be the most sensitive area in terms of star rating change in this study. The impact of climate change on space building energy consumption in different climate zones should be considered in future design strategies due to the decades-long lifespans of Australian residential houses.


Sign in / Sign up

Export Citation Format

Share Document