Impact of Climate Change on the Heating Demand of Buildings. A District Level Approach

In the 21st century, the importance of energy generation and carbon emissions in developing countries is indisputable. In the whole wide world, the building stock is responsible for the two fifths of the total world annual energy consumption. Considering the predictions regarding future climate due to climate change, a good understanding on the energy use due to future climate is required. The aim of this study was to evaluate the impact of future weather in the heating demand and carbon emissions for a group of buildings at district level, focusing on an area of London in the United Kingdom. The methodological approach involved the use of geospatial data for the case study area, processed with Python and Anaconda through Jupyter notebook, generation of an archetype dataset with energy performance data and TABULA typology and the use of python embedded in QGIS to calculate the heating demand in the reference weather data, 2050 and 2100 in accordance to RCP4.5 and RCP 8.5 scenarios. A validated model was used for the district level heating demand calculation. On the one hand, the results suggest that a mitigation of carbon emissions under the RCP4.5 scenario will generate a small decrease on the heating demand at district level, so slightly similar levels of heating generation must continue to be provided using sustainable alternatives. On the other hand, following the RCP 8.5 scenario of carbon emission carrying on business as usual will create a significant reduction of heating demand due to the rise on temperature but with the consequent overheating in summer, which will shift the energy generation problem. The results suggest that adaptation of the energy generation must start shifting to cope with higher temperatures and a different requirement of delivered energy from heating to cooling due to the effect of climate change

Parametric Study of different Levels of Detail in buildings for the estimation of Annual Heating Demand: A case study in London, UK

In the 21st century, the importance of energy in developing countries is indisputable. In the whole wide world, the building stock is responsible for the two fifths of the total world annual energy consumption. Over recent years, the refurbishment of the existing building stock, with the purpose of being transmuted into energy efficient, and the construction of sustainable and low energy buildings, has interested the broader construction sector. Taking into account the predictions about the future climate, the need for the expeditious refurbishment of entire building blocks is essential. The Level of Detail (LoD), that it is the method used to display a project's construction details, is an important factor to consider while modelling energy at the urban scale. A parametric study regarding the data requirements for the estimation of the annual residential heat demand in city of London has been conducted for this research project. More particularly, the requirement of the observation of the actual roof type (LoD2) and the window to wall ratio (LoD3) has been examined in two different areas. The results have shown that there is a minor difference from the upgrade of lower to higher LoD, regarding these parameters. This means that the time and money – consuming procedure of observation for the roof types and calculation of windows to wall ratio of buildings at an area is not necessary, and energy performance of buildings could be estimated with an assumption from archetypes and building ages. Finally, in future work, from the energy aspect, the refurbishment date, as well as different air change rate of buildings or indoor temperatures, could be taken into consideration for more representative results, at mixed age areas, but also, from the data requirement and modelling point of view, studies could be conducted regarding the simplest way to link the required data from different surveying companies into a single dataset that could be used with ease from analyzers and by this way help policy makers, regarding the reduction of the residential energy demand and carbon dioxide emissions

Parametric Study of different Levels of Detail in buildings for the estimation of Annual Heating Demand: A case study in London, UK

In the 21st century, the importance of energy in developing countries is indisputable. In the whole wide world, the building stock is responsible for the two fifths of the total world annual energy consumption. Over recent years, the refurbishment of the existing building stock, with the purpose of being transmuted into energy efficient, and the construction of sustainable and low energy buildings, has interested the broader construction sector. Taking into account the predictions about the future climate, the need for the expeditious refurbishment of entire building blocks is essential. The Level of Detail (LoD), that it is the method used to display a project's construction details, is an important factor to consider while modelling energy at the urban scale. A parametric study regarding the data requirements for the estimation of the annual residential heat demand in city of London has been conducted for this research project. More particularly, the requirement of the observation of the actual roof type (LoD2) and the window to wall ratio (LoD3) has been examined in two different areas. The results have shown that there is a minor difference from the upgrade of lower to higher LoD, regarding these parameters. This means that the time and money – consuming procedure of observation for the roof types and calculation of windows to wall ratio of buildings at an area is not necessary, and energy performance of buildings could be estimated with an assumption from archetypes and building ages. Finally, in future work, from the energy aspect, the refurbishment date, as well as different air change rate of buildings or indoor temperatures, could be taken into consideration for more representative results, at mixed age areas, but also, from the data requirement and modelling point of view, studies could be conducted regarding the simplest way to link the required data from different surveying companies into a single dataset that could be used with ease from analyzers and by this way help policy makers, regarding the reduction of the residential energy demand and carbon dioxide emissions

Parametric assessment of building heating demand for different levels of details and user comfort levels: a case study in London, UK

The Level of Detail (LoD), a parameter used to define the information contained in building models, is an important factor to consider in modeling building energy at the urban scale. In this research, we conducted a parametric study regarding the data requirements for the estimation of the annual residential heat demand in London. More particularly, the requirement of the observation of the actual roof type (LoD2) and the window-to-wall ratio (LoD3) was examined in two different case study areas. Meanwhile, an adaptive comfort level study was implemented using LoD5 models, and its results were assessed holistically with the heat demand to reveal the energy performance of the buildings. The results showed that there was a minor difference in the upgrade of a lower to higher LoD regarding these parameters. At an urban scale, the energy demand of buildings could be estimated using an assumption of archetypes and building ages. However, with a scalable parametric script developed in places, models with a high LoD could provide more detailed insights in the energy performance assessment without generating excessive workload

Towards a Combined Physical and Social Evaluation of Climate Vulnerability in Coastal Urban Megacities

Coastal urban megacities across Asia face significant risks from climate change, including coastal flooding, high temperatures, urban heat island impacts and air pollution. These hazards are associated with negative impacts on infrastructure, communities and the environment. To identify the current intensity of climate change impacts in coastal urban megacities, an integrated evaluation method is needed. Firstly, the present study assesses the climate change impacts of Guangzhou, a Chinese coastal urban megacity, for both physical and social aspects. This study includes 60 years of time-series data for 1960–2020 to examine temperatures, precipitation, humidity and air pollution in Guangzhou city. At the same time, a survey was conducted between April and July 2022 in this megacity and collected the views of 336 people on climate change and its associated environmental impacts. Secondly, the Ganzhou city results are compared with existing data from similar nearby cities to evaluate the diverse climate change trends. Results show that during 1961-1990, the city received the most rainfall in May, reaching 283.6 mm. From 1990 to 2020, June recorded the highest rainfall of 356.6 mm and shows an increase of 73 mm during that period. The very severe monsoon season brought an increased risk of flooding. Results also revealed that the warmest month is July, and the coldest month is January, and both months showed increased temperatures of 0.60 ℃. Comparison results revealed that Guangzhou is not the only city which scored increased highest temperatures; other nearby cities including Heyuan, Shantou and Shaoguan also scored increased highest temperatures. The survey reveals that the majority of respondents (75%) perceived the increased frequency of extreme weather, including typhoons, heavy rainfall and multiple days of hot weather, such as higher temperatures and an increased number of hot days. In the responses to the questions related to the heat island effect, more than 80% of residents are aware of the existence of the heat island and its impacts. People believe that the primary causes of the urban heat island problem are industrial production and anthropogenic heat generated by the city. These results will be helpful to local and national policy and decision makers to revise and/or develop new strategies to improve the environment and quality of life in coastal megacities, particularly Ganzhou

Prevalence of HPV infection among Greek women attending a gynecological outpatient clinic

Background: Human papillomavirus (HPV) infection is a causative factor for cervical cancer. Early detection of high risk HPV types might help to identify women at high risk of cervical cancer. The aim of the present study was to examine the HPV prevalence and distribution in cervical smears in a sample of Greek women attending a gynecological outpatient clinic and to explore the determinants of the infection.Methods: A total of 225 women were studied. All women underwent a regular gynecological control. 35 HPV types were studied; 6, 11, 16, 18, 26, 31, 33, 35, 39, 40, 42, 43, 44, 45, 51, 52, 53, 54, 56, 58, 59, 61, 62, 66, 68, 70, 71, 72, 73, 81, 82, 83, 84, 85 and 89. Also, basic demographic information, sociodemographic characteristics and sexual behavior were recorded.Results: HPV was detected in 22.7% of the study population. The percentage of the newly diagnosed women with HPV infection was 17.3%. HPV-16 was the most common type detected (5.3%) followed by HPV-53 (4.9%). 66.2% of the study participants had a Pap test during the last year without any abnormalities. HPV infection was related positively with alcohol consumption (OR: 2.19, 95% CI: 1.04-4.63, P = 0.04) and number of sexual partners (OR: 2.16, 95% CI: 1.44-3.25, P < 0.001), and negatively with age (OR: 0.93, 95% CI: 0.87-0.99, P = 0.03), and monthly income (OR: 0.63, 95% CI: 0.44-0.89, P = 0.01).Conclusion: The prevalence of HPV in women attending an outpatient clinic is high. Number of sexual partners and alcohol consumption were the most significant risk factors for HPV infection, followed by young age and lower income

Evaluating the performance of an EnerPHit building under different climates in Greece – A Digital Twin approach

This paper presents a critical evaluation of the performance of the first awarded EnerPHit building under the different climate zones of Greece following a digital twin approach. The thermal behavior and the relative humidity of the original building without active strategies have been numerically investigated for the four different climates. The results show that the Passive House design could be applied in all four climate zones in Greece with minimum updates in terms of insulation thickness, providing an avenue for mass prefabrication and application of the Passivhaus concept in Greece

Impact of Climate Change on the Heating Demand of Buildings. A District Level Approach

There is no doubt that during recent years, the developing countries are in urgent demand of energy, which means the energy generation and the carbon emissions increase accumulatively. The 40 % of the global energy consumption per year comes from the building stock. Considering the predictions regarding future climate due to climate change, a good understanding on the energy use due to future climate is required. The aim of this study was to evaluate the impact of future weather in the heating demand and carbon emissions for a group of buildings at district level, focusing on two areas of London in the United Kingdom. The methodological approach involved the use of geospatial data for the case study areas, processed with Python programming language through Anaconda and Jupyter notebook, generation of an archetype dataset with energy performance data from TABULA typology and the use of Python console in QGIS to calculate the heating demand in the reference weather data, 2050 and 2100 in accordance with RCP 4.5 and RCP 8.5 scenarios. A validated model was used for the district level heating demand calculation. On the one hand, the results suggest that a mitigation of carbon emissions under the RCP4.5 scenario will generate a small decrease on the heating demand at district level, so slightly similar levels of heating generation must continue to be provided using sustainable alternatives. On the other hand, following the RCP 8.5 scenario of carbon emission carrying on business as usual will create a significant reduction of heating demand due to the rise on temperature but with the consequent overheating in summer, which will shift the energy generation problem. The results suggest that adaptation of the energy generation must start shifting to cope with higher temperatures and a different requirement of delivered energy from heating to cooling due to the effect of climate change

Prevalence of HPV infection among Greek women attending a gynecological outpatient clinic

Background: Human papillomavirus (HPV) infection is a causative factor for cervical cancer. Early detection of high risk HPV types might help to identify women at high risk of cervical cancer. The aim of the present study was to examine the HPV prevalence and distribution in cervical smears in a sample of Greek women attending a gynecological outpatient clinic and to explore the determinants of the infection.Methods: A total of 225 women were studied. All women underwent a regular gynecological control. 35 HPV types were studied; 6, 11, 16, 18, 26, 31, 33, 35, 39, 40, 42, 43, 44, 45, 51, 52, 53, 54, 56, 58, 59, 61, 62, 66, 68, 70, 71, 72, 73, 81, 82, 83, 84, 85 and 89. Also, basic demographic information, sociodemographic characteristics and sexual behavior were recorded.Results: HPV was detected in 22.7% of the study population. The percentage of the newly diagnosed women with HPV infection was 17.3%. HPV-16 was the most common type detected (5.3%) followed by HPV-53 (4.9%). 66.2% of the study participants had a Pap test during the last year without any abnormalities. HPV infection was related positively with alcohol consumption (OR: 2.19, 95% CI: 1.04-4.63, P = 0.04) and number of sexual partners (OR: 2.16, 95% CI: 1.44-3.25, P < 0.001), and negatively with age (OR: 0.93, 95% CI: 0.87-0.99, P = 0.03), and monthly income (OR: 0.63, 95% CI: 0.44-0.89, P = 0.01).Conclusion: The prevalence of HPV in women attending an outpatient clinic is high. Number of sexual partners and alcohol consumption were the most significant risk factors for HPV infection, followed by young age and lower income

Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

A methodology aiming to predict the vulnerability of masonry structures under seismic action is presented herein. Masonry structures, among which many are cultural heritage assets, present high vulnerability under earthquake. Reliable simulations of their response to seismic stresses are exceedingly difficult because of the complexity of the structural system and the anisotropic and brittle behavior of the masonry materials. Furthermore, the majority of the parameters involved in the problem such as the masonry material mechanical characteristics and earthquake loading characteristics have a stochastic-probabilistic nature. Within this framework, a detailed analytical methodological approach for assessing the seismic vulnerability of masonry historical and monumental structures is presented, taking into account the probabilistic nature of the input parameters by means of analytically determining fragility curves. The emerged methodology is presented in detail through application on theoretical and built cultural heritage real masonry structures.info:eu-repo/semantics/publishedVersio