Cooling Degree Hours Research Articles

Assessing the impact of heat mitigation measures on thermal performance and energy demand at the community level: A pathway toward designing net-zero energy communities

In the context of escalating global energy demands, urban areas, specifically the building sector, contribute to the largest energy consumption, with urban overheating exacerbating this issue. Utilizing urban modelling for heat-mitigation and reduction of energy demand is crucial steps towards a sustainable built-environment, complementing onsite energy generation in the design and development of Net-zero Energy (NZE) Settlement, especially in the context of Australian weather conditions. Addressing a significant gap in existing literature, this study offers empirical analysis on the climate and energy efficacy of integrated heat mitigation strategies applied in 14 neighbourhood typologies located in Sydney, Australia. Examining the application of cool materials on roads, pavements, and rooftops, alongside urban vegetation enhancement, the analysis demonstrates scenario effectiveness on heat mitigation that leads to reduce ambient temperature and energy demands along with CO2 emissions within the neighbourhoods. Considering building arrangement, built-area ratio, building height, and locations, ENVI-met and CitySim are utilized to assess the heat-mitigation and the energy demand of neighbourhoods, respectively. Results indicate that mitigation measures can lead up to a 2.71 °C reduction in ambient temperature and over 25% reduction in Cooling Degree Hours, with a 34.34% reduction in cooling energy demand and overall energy savings of up to 12.49%. In addition, the annual energy-saving yields a CO2 reduction of approximately 141.12 tonnes, where additional vegetation further amplifies these reductions by enhancing CO2 absorption. This study showcases the pathway towards achieving NZE goals in climates similar to that of Australia, highlighting significant benefits in heat-mitigation, environmental impact, and energy-savings.

Adaptive Comfort Potential in Different Climate Zones of Ecuador Considering Global Warming

Ecuador is a country with several climate zones. However, their behaviour is similar throughout the year, with no peaks of extreme temperatures in the various seasons. This paper is a first approach to study the adaptive comfort behaviour in several areas and populations of the country. Considering the ASHRAE 55-2020 model, energy simulation programmes are applied not just to the current climate scenario but also to the climate change scenarios of 2050 and 2100. The results of locations are analysed and compared to determine their performance. Thanks to their climate characteristics, adaptive comfort models could be applied as a passive strategy, using natural ventilation for building indoor comfort improvement, particularly social dwellings. According to previous studies, some prototypes have not considered the climate determinants in each region. Given the geographic situation of the study areas, the adaptive comfort model could be applied in all cases. Percentages of application of natural ventilation and heating and cooling degree hours have similar behaviours according to the climatic region, with a variation greater than 30% among them.

Multiple regional climate model projections to assess building thermal performance in Brazil: Understanding the uncertainty

Understanding the trends and uncertainties in Building Energy Simulation (BES) performance indicators under future climate conditions is crucial for mitigating issues such as overheating and power outages. To address this, we generated a set of weather files for all 27 state capitals in Brazil, considering six climate model projections (three General Circulation Models as driving models and two nested Regional Climate Models) and two distinct emission scenarios from the CORDEX project. We analyzed the variability in climatic variables and subsequently performed BES on a representative Brazilian social housing unit to evaluate its impact on the performance indicators outcomes. Consistent with previous studies, a substantial increase in cooling-related demands was observed in the more pessimistic scenario (RCP8.5) and mild increases in the more optimistic scenario (RCP2.6), with a trend toward stabilization after 2050. Regarding uncertainties, we found higher Relative Standard Deviation (RSD) values for the cooling degree hours indicator. The capitals in the Central-West, Southeast, and South regions exhibited greater uncertainty regarding temperature indicators, whereas the irradiation parameters displayed higher uncertainties in the Northeast region. For the BES outcomes, RSD values as high as 19.9% were found for cooling load values. It was also demonstrated that locations, periods, and scenarios exhibit different extreme climate model projections. Ideally, employing an ensemble of weather files developed from other models would help assess associated uncertainties in the building performance indicators.

Improved mesoscopic meteorological modelling of the urban climate for building physics applications

A meteorological mesoscale model is used to predict the local urban climate at 250 m resolution. The authors propose a hybrid machine learning approach to improve the prediction accuracy and remove simulation bias. Two case studies are presented to show the improvements of the simulation accuracy. Based on the hybrid model results, using cooling degree hours is proposed as an insightful time-dependent index to map local hotspots and assess the difference of cooling loads between rural and urban environments.

Relating three-decade surge in space cooling demand to urban warming

Rising demand for space cooling has been placing enormous strain on various technological, environmental, and societal dimensions, resulting in issues related to energy consumption, environmental sustainability, health and well-being, affordability, and equity. Holistic approaches that combine energy efficiency optimization, policy-making, and societal adaptation must be rapidly promoted as viable and timely solutions. We interpret the 30 year climatic-induced upward trend and spikes in urban space cooling demand from the perspective of climate change, urbanization, and background climates, through the lens of five major populated cities: Hong Kong, Sydney, Montreal, Zurich, and London. An unequivocal, worrying upward trend in cooling demand is observed in meteorological data, using cooling degree hours (CDHs) as a city-scale climatic-induced metric. The surge in cooling energy demand can be largely attributed to climate warming and urban heat islands, with the most abrupt spikes associated with intensified extreme heat events. Further, our quantification of the impact of the base temperature, in relation to the historical CDH, reveals that a 20% energy saving could be achieved instantly within a rather broad range of air temperature and relative humidity by increasing the setpoint temperature by one degree. With the rise in background temperatures due to climate change, the potential for energy saving diminishes for the same level of increase in setpoint temperature. For instance, an increase from 26 °C to 27 °C results in about 10% energy savings, while an increase from 22 °C to 23 °C could yield over 20% in energy savings. To reduce cooling energy demand rapidly in a warming climate, we highlight the necessity of promoting hard and soft behavioral adaptation along with regulatory intervention for the operation of space cooling systems.

Predictive modelling of heating and cooling degree hour indexes for residential buildings based on outdoor air temperature variability

Heating and cooling degree hours (HDH and CDH) are weather-based technical indexes designed to describe the need for energy requirements of buildings. Their calculation is the simplest method to estimate energy demand, providing the pattern of internal temperature variations in a building in response to weather conditions. The aim of the study is HDH and CDH prediction for Wrocław, Poland, based on outdoor air temperature using machine learning methods: artificial neural networks and support vector regression (ANN and SVR). The key issues raise in the study are: a detailed analysis of the most significant temperature lags (from 1 to 24 past hours) serving as predictors for modelling and an assessment of the impact of the database clustering on its accuracy. The best results are obtained with the clustering approach. The best predictor is the outdoor temperature observed 1 and 24 h before forecast demand (R2 = 0.981 and 0.904 for heating degree and cooling degree hours indices, respectively). Models with the highest quality are created using ANN, and the lowest with SVR. Prediction of heating/cooling degree hour indices provides building demand in advance, does not require knowledge about its characteristics, and expresses the possible impact of regional climate modifications.

Development and performance evaluation of a minimum input model calibration methodology for residential buildings

Energy simulations of existing dwellings are often impeded by the complexity of assigning appropriate model inputs. While data-driven calibration is an effective method to reduce variance between measured and simulated datasets, significant effort is required for monitoring and auditing. A new minimum input calibration method is proposed, where the number of inputs is greatly reduced through a three-step sensitivity analysis creating an input set with the most influential parameters on internal temperatures. The reduction in input parameters simplifies calibration and reduces the likelihood of unrealistic solutions. The proposed method is verified on two dwellings where conventional calibration techniques were compared to the minimum input calibration method using sub-hourly internal temperatures. Compared to baseline models, the variance of minimum input models reduced from 9.9% and 9.7% to 3.3% and 3.8% (CVRMSE (%)). Results indicate that minimum input model calibration can sufficiently predict thermal performance and could be applied to retrofit optimization. Acronyms: BoM: Bureau of Meteorology; BPS: building performance simulation; CD: cooling dominant; CDH: cooling-degree hours; CVRMSE: coefficient of variation of the root mean square error; D: discrete; ECM: energy conservation measure; HD: heating dominant; HDH: heating-degree hours; MAE: mean absolute error; MBE: mean bias error; MIM: minimum input model; MIS: minimum input set; MOAT: manual one at a time; N: normal distribution; NRMSE: normalized root mean square error; RMSE: root mean square error; RMY: reference meteorological year; SHGC: solar heat gain coefficient; U: uniform distribution

The Impact of Urban Heat Island on Cooling Needs in Urban and Suburban Areas of Hyderabad Sindh Pakistan

The urban heat island phenomenon is causing numerous problems, and studying its effects in rapidly developing cities is crucial to meet the Sustainable Development Goal 14 for sustainable building and cities. This research focuses on investigating the characteristics of the Urban Heat Island in Hyderabad Sindh, specifically in a densely populated commercial area and a rural suburb known as TandoJam. The study utilized weather station data from the Pakistan Meteorological Department and temperature sensors from Qasimabad to compare air temperature differences between the urban and reference rural areas. The UHI intensity was determined by calculating the air temperature difference between urban and rural areas. Results showed that the UHI effect was more prominent during winter and nighttime than during summer and daytime, with only a few months, like June, showing some UHI effects during daytime. The study also used cooling degree days and cooling degree hours as a measure of energy required for cooling, and all areas observed higher numbers of CDDs and CDHs. However, urban areas had more CDDs than rural areas, indicating that the maximum cooling degree days in urban areas are a direct consequence of the UHI. The 7-year average data revealed that TandoJam experienced the least number of CDDs compared to its urban area, suggesting better thermal comfort in the rural area. The study’s findings were further validated through a day UHI analysis in the town of Qasimabad Hyderabad, which showed high CDHs and higher UHI intensity in Qasimabad than in other rural towns in Hyderabad.

On the cooling energy penalty of urban photovoltaics: a case study in Sydney, Australia

While application of photovoltaic (PV) solar panels as an energy harvesting system becomes more popular, there are significant urban microclimate and energy penalties associated with their large-scale applications. This study evaluated the impact of PV solar panels on urban temperature and corresponding cooling load penalties in 17 representative building types during the two-summer months of January and February in Sydney. We calculated that when 25–100% areas of roofs are covered by PV solar panels, the ambient air temperature may increase by 0.6–2.3 °C. As estimated, the application of PV solar panels on 25%, 50%, 75%, and 100% area of roofs can increase the cooling degree hour (CDH) base 25 °C by 10.2%-31.7% and 6.2%-19.1% in the coldest and hottest weather stations in Sydney (i.e. Observatory and Penrith), respectively. We computed that this is equivalent to cooling load penalties of around 1.7 and 6.8 kWh/m2 (8–25%) in 17 different types of buildings during the two summer months period. It is estimated that the total cooling penalty by covering 25%, 50%, 75%, and 100% area of roofs for all building types, including residential and commercial buildings per local government area (LGA) in Greater Sydney can range between 0.5–29.6 GW (3.1–3.9%), 1.2–52 GW (4.8–8.0%), 1.3–61.8 (7.5–9.0%), and 1.8–82.8 GW (8.8–12.1%), respectively. It is advised that future advancements in PV technologies focus on both greater efficiency and the demand to increase reflection of wavelengths of light that are not converted into electricity by the PV solar panels.

Assessment of climate change's impact on energy demand in Mexican buildings: Projection in single-family houses based on Representative Concentration Pathways

In Mexico, buildings' deficient thermal performance is one of the leading causes of the intensive use of energy. This research analyzes the perspective of energy demand required to meet the cooling needs in the country through the Weather-based technical indexes: Cooling Degree Hour (CDH) and Operation Hours (OH). The study considered the 2440 municipalities that make up the 32 states of the Mexican Republic and three chronological progressions throughout the 21st century (2020, 2050, and 2100). Meteorological data was collected through the Meteonorm software considering climate change projections, precisely two Representative Concentration Pathway scenarios (RCP 4.5 - Intermediate) and (RCP 8.5 - High). Based on the calculations, spatial and temporal panoramas of the behavior of air conditioning hours under various target temperatures (20 °C, 23 °C, and 26 °C) were established. Taking the most important type of housing in Mexico (Social Interest Housing) as a case study, a database of air conditioning energy demand was performed and subsequently grouped the states according to cluster similarities. The results show that >50 % of the Mexican Republic requires high air conditioning levels. The maximum CDH for 2100-RCP 8.5 will be 70 % higher than currently needed. Even for the year 2050-RCP8.5, an increase of >40 % of CDH was obtained. Regarding the OH, the results show an increase of >50 % concerning the current behavior of the country. Regardless of the scenario, the range of operating hours with the highest operating requirements is between 11 am and 4 pm, peaking in the summer season. The simulations showed that some Mexican regions exceed 12,000 kWh in air conditioning. An increase of 20 % and 35 % is expected for the years 2050 and 2100. The simulations showed that a considerable percentage of Mexico exceeds 12,000 kWh in air conditioning, while by 2050 and 2100, this consumption will increase by 20 % and 35 %, respectively. Based on these results, the first classification of groups in energy demand was generated, allowing a focus on energy efficiency strategies to obtain net zero Buildings. The data obtained shows that relative humidity is a variable that affects the increase in energy consumption in refrigeration and simplifies the process of classifying regions with similar patterns in air conditioning.

Cooling Potential of Ship Engine Intake Air Cooling and Its Realization on the Route Line

A fuel efficiency of a ship engine increases with cooling inlet air. This might be performed by the chillers, which transform the heat of engine exhaust gas and scavenge air for refrigeration. The effect gained due to cooling depends on the intake air temperature drop and the time of engine operation at decreased intake air temperature. Thus, the cooling degree hour (CDH) number, calculated as air temperature depression multiplied by the duration of engine operation at reduced intake air temperature, is used as a primary criterion to estimate the engine fuel efficiency enhancement due to intake air cooling over the ship routes. The engine intake air cooling potential is limited by its value, available according to engine exhaust heat and the efficiency of heat conversion to refrigeration in the chiller, evaluated by the coefficient of performance (COP). Therefore, it should be determined by comparing both the needed and available values of CDH. The ejector chiller (ECh) was chosen for engine exhaust gas heat recovery to refrigeration as the simplest and cheapest, although it has a relatively low COP of about 0.3 to 0.35. However, the ECh generally consists of heat exchanges which are mostly adapted to be placed in free spaces and can be mounted on the transverse and board side bulkheads in the ship engine room. The values of sucked air temperature depression and engine fuel consumption reduction at varying temperatures and humidity of ambient air on the route were evaluated.

Assessment of Outdoor Design Conditions on the Energy Performance of Cooling Systems in Future Climate Scenarios—A Case Study over Three Cities of Texas, Unites States

The excessive use of energy in buildings due to increased populations and economic development leads to more greenhouse gas emissions, which affect climate change and global warming. Changes in prevailing outdoor weather conditions significantly affect the energy systems of buildings through increased cooling and decreased heating. In this paper, 30 years of data of dry and wet bulb temperatures (1990–2020) with a time interval of 3 h were considered in order to estimate the climatic outdoor design conditions in the cities of Dallas–Fort Worth, Houston, and San Antonio in the state of Texas. The results suggest that the dry bulb temperature (DBT) had significantly higher increases in Dallas–Fort Worth (2.37 °C) than the wet bulb temperature (WBT) in Houston (4.1 °C) during the study period. Furthermore, this study analyzed the effects of climate change on cooling degree hours (CDH) and heating degree hours (HDH) and the results suggest the most significant drop in HDH in Dallas–Fort Worth with a maximum CDH fluctuation as compared to other two cities. The effect of climate change on the performance of cooling systems is also investigated in this study via direct evaporative coolers (DECs) and direct-indirect evaporative coolers (IDEC), which do not perform well in the selected cities. In contrast, absorption system (Abs) and vapor compression (VC) systems show an increase in the number of additional loads. The second part of this study is related to the future projection using the ARIMA model, which suggests that DBT would rise significantly in Houston (from 37.18 °C to 37.56 °C) and Dallas–Fort Worth (39.1 °C to 39.57 °C) while diminishing in San Antonio (from 34.81 °C to 33.95 °C) from 2020 to 2030. In contrast, WBT will experience an upward trend in Houston (from 36.06 °C to 37.71 °C) and Dallas–Fort Worth (from 31.32 °C to 31.38 °C) and a downward trend in San Antonio (from 32.43 °C to 31.97 °C) during 2020–2030. Additionally, the future performance prediction of Abs and VC systems is also performed, which reveals that the amount of additional load required is significantly higher in 2030 compared to 2020 and is more prominent in Houston. Conversely, amount of additional load required for cooling systems in San Antonio shows a decreasing trend in 2030.

A novel degree-hour method for rational design loading

Cooling degree-hours (CDH) received the broadest application in evaluation of the ambient air cooling efficiency in power engineering (engine intake air cooling systems) and air conditioning. The current CDH numbers are defined as a drop in air temperature multiplied by associated time duration of performance and their summarized annual number is used to estimate the annual effect achieved due to sucked air cooling in power plants based on combustion engines (fuel saving, power output increment) and in air conditioning (refrigeration energy generation according to needs). A majority of approaches to designing ambient air cooling systems is proceeding from the cooling capacity of the chillers selected to provide a maximum current or annual CDH number with corresponding maximum current or annual effect (additional energy produced or fuel consumption reduction) in site climate location. But such approaches lead to inevitable oversizing the chillers and cooling systems in the whole. The analysis of intake air cooling efficiency in site varying climatic conditions, accompanied by quite a simple numerical simulation, enabled to reveal the potential of its enhancement and evaluate numerically the results of each step of designing in logical sequence. The new approaches to cooling system rational designing were introduced, that enables to synthesize and substantiate innovative principal decisions to exclude unproductive waste of installed (design) cooling capacity in actual operation. The innovative findings of methodological approaches include the use of the rate of annual CDH number increment as an indicator for selecting the optimum and rational values of design cooling capacity. The optimum cooling capacity corresponds to maximum rate of summarized annual CDH increment and maximum level of thermal loading accordingly, which provides minimum sizes of the chiller. In reality, it is a minimum permissible value of cooling capacity of the chiller installed and the overall ambient air cooling system. The rational cooling capacity, that enables to achieve practically maximum value of annual CDH and avoid chiller oversizing, is determined as the second, local, maximum of the rate in the summarized annual CDH over the range above the first one, global, maximum. A rational design cooling capacity determined by applying the novel methodology allows to decrease the ambient air cooling system sizes by 15 to 20% compared with traditional designing issuing from the peaked thermal load during a year. With this practically a maximum annual effect in fuel saving (energy generation or others) can be achieved too.

Impact of urban heat island on cooling energy demand for residential building in Montreal using meteorological simulations and weather station observations

Urban heat island (UHI) and the increased frequency of heatwaves due to climate change reduce thermal comfort inside buildings leading to increased use of air conditioning systems. In this research, the impact of the actual local climate on the cooling energy demand of residential buildings in Montreal is studied. Building energy simulations (BES) are conducted for microclimates at eight locations in the Montreal area and compared with a reference weather data. The climate data for four locations are provided by weather stations. The other climate data are simulated with a detailed weather research and forecasting (WRF) model at 250 m resolution with detailed land-use data over a period of four months during the summer of 2020. The air temperatures from meteorological mesoscale simulations are validated with available weather station observations. The BES results show an increase in the cooling energy demand due to higher air temperatures at urban locations compared to the rural periphery. The cooling energy demand varies significantly over the eight locations although being within a radius of 20 km. The mean variation in cooling energy demand between the locations amounts to 14 % compared to the average cooling demand. Using the reference climate data provided in BES, the cooling energy demand is significantly underestimated by 25 % to 34 % on average. Increasing the thermostat cooling setpoint with 1 °C results in a reduction in mean cooling energy demand of 4.5 kWh/m2, or 11.7 %. A linear trend is found between the cooling energy demand from BES and cooling degree hours (CDH) indicating CDH can be used as a first indication for building energy demand.

Farklı Denge Sıcaklıkları İçin Isıtma ve Soğutma Derece-Saatlerinin Değişimi: Bandırma Örneği

Data on exterior temperature constitute one of the most important parameters in the calculation of energy needs in buildings. This study obtained the temperature distribution curves by analyzing the outdoor air temperature in Bandırma. Heating Degree Hour (HDH) and Cooling Degree Hour (CDH) for three different base temperatures were calculated. A 21-year data set between 2000-2020 obtained from the General Directorate of Meteorology was used. The incidence (%) of outdoor air temperature according to months was determined. In the calculation of the HDH and CDH values, base temperatures of (15, 18 and 20 °C) and (20, 22 and 24 °C) were considered respectively. The results of the analysis showed that the number of HDH changed between 31357 and 53037, while CDH numbers ranged between 10433 and 2669. The increase in the average outdoor air temperature with the effects of global warming was determined for heating and cooling season in a 21-year period according to year. It was determined that there was an increase of 1.68 °C in the heating season in the 21-year period and 1.80 °C in the cooling season in the 21-year period. In this study, the necessity of determining energy needs for heating and cooling purposes in a clear and up-to-date manner was emphasized once again. This is highly important to not only achieve energy savings but also reduce the air pollution effects of energy consumption. It is believed that this study will make a contribution to the literature in this sense.

Estimating building cooling energy demand through the Cooling Degree Hours in a changing climate: A modeling study

The increasingly hot and long summers due to the climate change will cause a significant increase in energy demand for cooling systems, especially in highly-densely populated regions. The cooling energy needs of buildings are proportional to the Cooling Degree Hours, which consist in the cumulative sum of the positive differences between the hourly outdoor temperature and the indoor comfort temperature. In this work, this quantity is computed using gridded temperatures predicted by the Weather Research and Forecasting model for the years 2000, 2019, 2050 and 2080 across Italy. This allows investigating the evolution of the cooling energy needs on a national scale, following the climate-change related trend of the ambient temperature. For climate projections, an intermediate (RCP4.5) and a high emissions (RCP8.5) scenario defined by the Intergovernmental Panel for Climate Change have been considered. Findings show that results of 2050-RCP8.5 and 2080-RCP4.5 are very close, both in terms of amount of operational hours and cooling degree hours. The maximum level of cooling degree hours has increased more in the recent past than it will grow in the future, even according to RCP8.5. Yet in 2080 about 70% of Italy will reach levels of cooling degree hours not touched in 2000.

Influence of Façade Configuration on Thermal Performance of Residential Unit of Typical Walk-up Flats in Surabaya

Flat design has evolved and taken many shapes and forms. Most of the arrangements are arranged in a double-load layout where the units are positioned face to face along the corridor. Another type is two single-loaded flats that are configured to face the courtyard. Building façade also varies from those with shaded surfaces to those with minimum sun protection. Modification in design clearly has an impact on the thermal performance of the buildings. The aim of the study is to investigate the facade configuration on the thermal performance of the building. This study uses simulation software, namely, Design Builder, to predict the thermal performance of the buildings. Several variants of window areas, sun shading, balconies are arranged to explore their effects on thermal performance. Flat with yard selected as a reference model. The results showed that the smaller the window area and the greater coverage given to the window with a shading device, combined with the balcony, can provide a decrease in air temperature up to 0.57 ⁰C, with a reduction in cooling degree hours percentage of 36.97% comparing to the reference model.

Climate change resilience of school premises in Cyprus: An examination of retrofit approaches and their implications on thermal and energy performance

Educational buildings form a significant part of non-residential buildings that are of public use, and, in the case of Cyprus, this building stock tends to be less energy-efficient compared to a number of other public building typologies. Moreover, it is the purpose, frequency of use and user density of these buildings that make them a special case for study. These buildings are no longer fit for their assigned purpose as they require significant energy for heating in the winter and cooling in the summer, to avoid overheating. These conditions cause significant concerns in school buildings in Cyprus and the effects of climate change exacerbates these parameters. This research aims to evaluate the effectiveness of different retrofitting measures and their impact on the thermal comfort and the energy performance of educational premises under different climatic scenarios. For the purposes of this study, a secondary school building was selected as a representative case study of educational buildings in Cyprus and was modelled using IES-VE. Retrofit measures optimizing geometry, construction and operation were examined using a calibrated dynamic thermal simulation model in current and future climatic scenarios, to determine both their effectiveness in minimizing heating demand in the winter and overheating conditions in the summer period. Comfort conditions were assessed with reference to international standards based on adaptive thermal comfort. The study demonstrates that most educational buildings in Cyprus cannot ensure thermal comfort conditions, without the support of technical systems, neither in the present nor in anticipated future climatic conditions, thereby indicating the urgent need to take action. According to the research results, natural ventilation and insulation of the roof are considered very important in achieving this goal, as they have the potential to minimize the cooling degree hours by 96.8% and the heating degree hours by 4.3%. A combination of all passive measures and heat recovery ventilation can reduce degree hours for both heating and cooling by 51% in the current climatic conditions, and by 60% and 66.4% according to climatic projections for 2050 and 2090, respectively. The methodology for the evaluation of the thermal and energy behaviour of the educational building stock applied in this study could be a trustworthy tool for decision-making in energy retrofitting projects in Cyprus, as well as in other areas with similar climatic conditions.

Degree-hours and Degree-days in Coastal Mediterranean Cities, Patras and Kalamata, Greece

The hourly ambient air temperature information was analyzed for two Greek coastal Mediterranean cities: Patras (for the entire 2018 year) with ten urban and one rural stations, and Kalamata (for the entire 2019 and 2020 years) with eight urban and two rural stations. The heating and cooling Degree Hours (DH) and Degree Days (DD) were calculated, for base temperatures of 18 °C and 26 °C, respectively. The urban heating degree hours for the cities of Patras and Kalamata were observed to be 19.2% and 24%, respectively, lower than that of the rural areas. Similarly, the urban cooling degree hours for the two cities were 9% and 22% higher than that of rural areas. These findings indicate a distinct urban heat island effect in both the cities, with greater effects in Kalamata than in Patras. Following comparisons with historical data from reliable sources, it could be observed that summers are trending warmer and winters are trending milder.

Crowdsourcing Urban Air Temperature Data for Estimating Urban Heat Island and Building Heating/Cooling Load in London

Urban heat island (UHI) effects significantly impact building energy. Traditional UHI investigation methods are often incapable of providing the high spatial density of observations required to distinguish small-scale temperature differences in the UHI. Crowdsourcing offers a solution. Building cooling/heating load in 2018 has been estimated in London, UK, using crowdsourced data from over 1300 Netatmo personal weather stations. The local climate zone (LCZ) scheme was used to classify the different urban environments of London (UK). Inter-LCZ temperature differences are found to be generally consistent with LCZ temperature definitions. Analysis of cooling degree hours in July shows LCZ 2 (the densest urban LCZ in London) had the highest cooling demand, with a total of 1550 cooling degree hours. The suburban related LCZs 5 and 6 and rural LCZs B and D all had about 80% of the demand of LCZ 2. In December, the rural LCZs A, B and D had the greatest heating demand, with all recording around 5750 heating degree hours. Urban LCZs 2, 5 and 6 had 91%, 86% and 95% of the heating demand of LCZ D, respectively. This study has highlighted both advantages and issues with using crowdsourced data for urban climate and building energy research.