Cooling Degree Days Research Articles

The Goldilocks Zone in Cooling Demand: What Can We Do Better?

AbstractThe higher frequency and intensity of sustained heat events have increased the demand for cooling energy across the globe. Current estimates of summer‐time energy demand are primarily based on Cooling Degree Days (CDD), representing the number of degrees a day's average temperature exceeds a predetermined comfort zone temperature. Through a comprehensive analysis of the historical energy demand data across the USA, we show that the commonly used CDD estimates fall significantly short (±25%) of capturing regional thermal comfort levels. Moreover, given the increasingly compelling evidence that air temperature alone is not sufficient for characterizing human thermal comfort, we extend the widely used CDD calculation to heat index, which accounts for both air temperature and humidity. Our results indicate significant mis‐estimation of regional thermal comfort when humidity is ignored. Our findings have significant implications for the security, sustainability, and resilience of the grid under climate change.

Effect of base temperature and cooling degree day on optimum insulation thickness in building walls

In the present work, degree day's method is used to get the optimum insulation thickness for different insulation materials. Some of the commonly used insulation materials available in the market are considered in the study. The study analyses the effect of CDD and base temperature on insulation thickness. The CDD was calculated from the base temperature that varies from 18°C to 26°C for the four cities of India. Based on the result, it is found that optimum insulation thickness is affected by the thermal conductivity of the material, base temperature, CDD, material cost, and fuel cost. The optimum insulation thicknesses vary between 1 and 12 centimetres for the different base temperatures. Annual cooling cost per m2 is found minimum at 24°C base temperature, and energy-saving varies with the thickness of the insulating materials apply on the wall.

Effect of base temperature and cooling degree day on optimum insulation thickness in building walls

Effect of base temperature and cooling degree day on optimum insulation thickness in building walls

Temporal characteristics of urban heat island and its response to heat waves and energy consumption in the mountainous Chongqing, China

In this study, the time series of temperature in Chongqing, China, from 1979 to 2018 was statistically analyzed, and both the interdecadal and seasonal variation characteristics of urban heat island intensity (UHII) were studied. The results show that the temperature in Chongqing has risen significantly in the past 40 years and that the temperature of the Chongqing urban area is approximately 1.6 times higher than the global warming trend. During the study period, the annual average UHII at urban and rural stations increased significantly at a rate of +1.3 °C/century. The seasonal variation in the nighttime UHII was higher in summer, while the seasonal variation in the daytime UHII was higher in winter. In addition, the annual average UHII was found to be related to the heat wave (HW) days, cooling degree days (CDD), and heating degree days (HDD). With an increase of 1 °C in the UHII, the HW days in urban area increased by approximately 10 d, the average difference of the CDD increased by approximately 72 °C•d, and the average difference of the HDD decreased by approximately 86 °C•d.

Downscaling Building Energy Consumption Carbon Emissions by Machine Learning

The rapid rate of urbanization is causing increasing annual urban energy usage, drastic energy shortages, and pollution. Building operational energy consumption carbon emissions (BECCE) account for a substantial proportion of greenhouse gas emissions, crucially influencing global warming and the sustainability of urban socioeconomic development. As a foundation of building energy conservation, determination of refined statistics of BECCE is attracting increasing attention. However, reliable and accurate representation of BECCE remains lacking. This study proposed an innovative downscaling method to generate a gridded BECCE intensity benchmark dataset with 1 km2 spatial resolution. First, we calculated BECCE at the provincial level by energy balance table application. Second, on the basis of building climate demarcation, partial least squares regression models were used to establish the BECCE behavior equations for three climate regions. Third, Cubist regression models were built, retrieving down scale at the prefecture level to 1 km2 BECCE, which well-captured the complex relationships between BECCE and multisource covariates (i.e., gross domestic product, population, ground surface temperature, heating degree days, and cooling degree days). The downscaled product was verified using anthropogenic heat flux mapping at the same resolution. In comparison with other published pixel-based datasets of building energy usage, the gridded BECCE intensity map produced in this study showed good agreement and high spatial heterogeneity. This new BECCE intensity dataset could serve as a fundamental database for studies on building energy conservation and forecast carbon emissions, and could support decision makers in developing strategies for realizing the CO2 emission peak and carbon neutralization.

Benchmarking urban local weather with long-term monitoring compared with weather datasets from climate station and EnergyPlus weather (EPW) data

Weather is essential for building energy simulation and energy efficient retrofitting since building energy use is highly weather-dependent. Weather data provided by EnergyPlus weather (EPW) data or generated by urban climate stations are used in most simulation tools. However, weather varies temporally and spatially, and the gaps may exist in the typical-year weather, weather from peri-urban areas, and local actual weather. This paper compares three types of weather datasets, from EPW data, from an urban climate station (STATION), and from long-term measurement with a local micro-climate station at Southeast University (SEU) campus. Results show there are significant gaps between the three weather datasets and compared with the STATION and EPW data, the average temperature in the micro-climate (SEU) is higher by 1.2 °C and 2.2 °C, respectively. The cooling degree day in SEU weather data is 20.4% and 40.8% higher, with heating degree day 15.7% and 26.3% lower. Comparing average relative humidity shows a big difference of 18.3% and 22.1% between SEU, STATION and EPW, and the former is comparatively lower than the latter two and no clear correlated trend. The SEU weather data has 23.1% more solar radiation hours than STATION weather data. As for wind speed, the average wind speed in the SEU weather data is lower by 1.14m/s and 1.29m/s, respectively, when compared with the STATION and EPW data. This study could be the reference for different trials for energy performance dynamic simulation for building energy analysis.

Estimation, analysis and mapping of electricity consumption of a regional building stock in a temperate climate in Europe

This study financed by ERDF and the Wallonia Region estimates the annual electricity consumption (EC) of building stock, including the 3 building sectors namely residential, tertiary and industrial building. The estimation takes into account appliances, electrical heating, cooling, lighting, cooking and EC by m2 on a building level. The results are spatialized on different territorial scales. Using cadastral data of more than 1,700,000 Walloon buildings and annual EC data from a sample collected in 2012 from the energy reports, the paper assesses the EC of the whole building stock and tests to what extent different types of variables (building factors and socio-demographics) explain annual EC. It then shows which individual variables have the highest explanatory power. In contrast to many other studies, the research recognizes the problem of multicollinearity between predictors in regression analysis and uses Lasso regression to address this issue. Three separate regression models were used to study the predictors of annual EC of residential, tertiary and industrial buildings. EC building factors (appliances, auxiliary and main heating, domestic hot water and cooking) explained the largest share which is 66.46% of the variability in EC for residential buildings whereas the EC usages share for tertiary buildings (lighting, heating and domestic hot water, air conditioning, cooling, etc.) is about 50.53% and 38.55% for industrial buildings. Socio-demographic variables on their own explained about 61.59%, 26.34% and 3.41% of the annual EC, respectively for residential, tertiary and industrial buildings. Hence, the building variables present the highest explanatory power for EC, presumably because heating and cooling EC are included in this study. The study highlights that when attempting to explain EC related to Walloon households, including heating and cooling EC, appliances usage has the strongest predictive power in residential buildings. On the other hand, the projected decrease in EC use for heating in existing residential buildings is −8.82% and −10% for existing tertiary buildings while the projected increase in EC use for cooling in existing tertiary buildings is + 11.94% from 2012 to 2050 on a regional scale. These trends follow the predicted regional heating degree-days (HDD) of −11.76% and cooling degree-days (CDD) of 14.04% for the same period based on the gated recurrent unit (GRU) an implemented deep learning (DL) model. In addition, the produced EC maps on different territorial scales show that the highest EC is seen in large and main cities in general.

Modeling seasonal emergence of Poa annua in urban greenspace

Turfgrasses are perennial components of urban greenspaces found in parks, recreational areas, golf courses, sports fields, and lawns that confer many ecosystem services. A copious seed producer, Poa annua is the most troublesome weed of turfgrass and continually threatens the ecosystem services provided by urban greenspaces. Field research was conducted in Knoxville, TN to better understand environmental conditions triggering P. annua seedling emergence patterns to assist managers with optimally timing interventions—both chemical and non-chemical—for control. Fluctuations in cooling degree day (CDD21C) accumulation accounted for 82% of the variance in yearly cumulative P. annua emergence data collected in a single irrigated sward of hybrid bermudagrass [C. dactylon (L.) Pers. x. C. transvaalensis Burtt-Davy]. However, non-linear models using CDD21C data developed ex post were not able to accurately predict P. annua emergence patterns ex ante. In both years, P. annua emergence changed most rapidly between the 40th and 43rd week of the year when seven-day mean soil temperature and rainfall were 18.9 °C and 12.7 mm, respectively. Future research should explore the efficacy of herbicide mixtures applied when P. annua emergence is most rapidly changing in lieu of developing models to predict when specific emergence thresholds occur.

Sectoral and temporal changes in natural gas demand in the United States

This research explores the temporal and spatial variation of sectoral natural gas demand in the United States. Fixed-effects econometric methods with robust identification approaches are the empirical techniques configured in the study using monthly data between 2001 and 2015. The results reveal the inelastic price responses at state, regional, and national levels across natural gas consumption sectors. The implication is that the efficacy of price based policies can differ in the natural gas consumption sectors across spatial scales. The statistically significant weather impacts in terms of heating degree days (HDD) and cooling degree days (CDD) revealed in this analysis are consistent with the extant energy demand literature, where higher HDD stimulates greater consumption of natural gas in the residential sector while CDD appears to increase natural gas consumption for electricity generation.

Integrated modeling of human-earth system interactions: An application of GCAM-fusion

Typically in human-earth system modeling studies, feedbacks between the earth and human systems are analyzed by passing information between independent models. The reliance on existing Earth System Model outputs limits the ability to explore feedbacks under arbitrary scenarios and equally important limits the ability to explore large-scale uncertainty in these interactions. In this study we explore a wide range of climate uncertainties and incorporate the implications of increased cooling hydrofluorocarbons emissions. We implement a statistical relationship between global mean temperature change and heating and cooling degree days that allows us to produce changes in building energy demands within GCAM at every time step and every region. While there is a general agreement in the literature that increasing temperatures will increase cooling energy demands and decrease heating energy demands, there has been no fully-coupled analysis of this dynamic that would, for example, account for the feedbacks on hydrofluorocarbons from increased cooling demands. The variation in the spatial distribution of temperatures leads to substantial variation in the change in cooling and heating energy across regions, with regions like USA, India and Sub-Saharan Africa experiencing a factor of two difference in cooling demands. While the feedbacks between building energy demand and global mean temperature are modest by themselves, this study prompts future research on coupled human-earth system feedbacks, in particular in regards to land, water, and other energy infrastructure.

Potential impact of 1.5, 2 and 3 °C global warming levels on heat and discomfort indices changes over Central Africa

Investigating the effects of the increased global warming through the lens of the Paris agreements would be of particular importance for Central African countries, which are already experiencing multiple socio-political and socio-economic constraints, but are also subject to severe natural hazards that interact to limit their adaptive capacity and thus increase their vulnerability to the adverse effects of climate change. This study explores changes in heat stress and the proportion of population at risk of discomfort over Central Africa, based on an ensemble-mean of high-resolution regional climate model simulations that cover a 30-year period, under 1.5, 2 and 3 °C Global Warming Levels (GWLs). The heat index was computed according to Rothfusz's equation, while the discomfort index was obtained from Thom's formula. The results show that throughout the year but with a predominance from March to August, the spatial extent of both heat and discomfort categories is projected to gradually increase according to the considered GWLs (nearly threefold for an increasing warming thresholds from 1.5 to 3 °C). As these heat conditions become more frequent, they lead to the emergence of days with potentially dangerous heat-related risks, where almost everyone feels discomfort due to heat stress. It thus appears that the majority of populations living in countries located along the Atlantic coast and in the northern and central part of the study area are likely to be more vulnerable to certain health problems, which could have repercussions on the socio-economic development of the sub-region through decreased workers’ productivity and increased cooling degree days. Overall, these heat-related risks are more extended and more frequent when the GWL reaches 2 °C and above.

Analysis of Cooling and Heating Degree Days over Mexico in Present and Future Climate

One simple way to estimate the relationship between air temperature and the energy needed for heating and cooling is to use the concept of degree day. Cooling degree days (CDD) and heating degree days (HDD) are indicators of the energy required to reach comfort levels and are related directly to energy demands. Therefore, using a novel approach, we examine the current conditions and future projections in degree days over Mexico using observations (Livneh and CPC), ERA5 reanalysis, and simulations from the Regional Climate Model (RegCM4). The RegCM4 experiments were driven by different General Circulation Models for two Representative Concentration Pathways scenarios. We consider three 20-year periods as “present conditions” (1995–2014), “near-future conditions” (2041–2060), and “far-future conditions” (2080–2099). The results suggest that in the future, under the lowest radiative forcing scenario there will be a smaller increase (decrease) in CDD (HDD) for the far-future, as compared to the near-future. This could represent the model’s response to the peak of radiative forcing at mid-century and its subsequent decline. For the highest radiative forcing scenario, we found a greater increase (decrease) in CDD (HDD) for the far-future, which could be explained by the response of the RegCM4 to the warming increase projected for 2100.

Thermal perception in outdoor urban spaces under the Mediterranean climate of Annaba, Algeria

Many studies were investigated to grade outdoor thermal comfort and related thermal sensation during the past years. This study aims to explore thermal comfort conditions and thermal sensation in the hot Mediterranean climate (Csa), which annually includes 1100–1700 cooling degree days and 1200–1800 heating degree days (CDD = 1100–1700, HDD = 1200–1800). This research tested the human thermal sensation by applying the Physiological Equivalent Temperature (PET) index. A field survey of 1230 interviewees was conducted in Annaba, Algeria, in four outdoor environments having the same morphology and different green cover. The scientific method involved combining two software. Envi-met was used to calibrate microclimatic data (air temperature, wind velocity, relative humidity and mean radiant temperature); in comparison, RayMan used to calculate PET. The results showed the neutral sensation range for this Mediterranean climate varies between 20 °C and 26 °C. The highest scores of neutral thermal sensation were recorded in spaces with vegetation cover, which involves the trees cooling effect in enhancing thermal comfort, especially during the hot hours of the day. The air temperature divergence reached 4 °C and 3 °C for Tmrt at noon, considered the day's hottest hour. The findings also highlight the existence of a thermal adaptation in outdoor spaces having a green cover.

Indicators of climate risk in the UK at different levels of warming

Assessments of the impacts of climate change are typically made using climate scenarios based on assumptions about future emissions of greenhouse gases, but policymakers and climate risk communicators are increasingly asking for information on impacts at different levels of warming. This paper provides this information for a set of indicators of climate risks in the UK for levels of warming up to 4 °C above pre-industrial levels. The results show substantial increases in climate risks at 2 °C, which is often inferred in the media to be a ‘safe’ level of climate change. In a 2 °C world, the chance of a heatwave is doubled, and the frequency of heat stress affecting people, crops and animals can be increased by a factor of five. Cooling degree days more than double, wildfire danger can increase by 40%–70%, the frequency of agricultural and water resources droughts doubles in England, and flood frequency in Wales increases by 50%. At 4 °C the increases in risk are considerably greater: heatwaves occur in virtually every year. The frequency of cold weather extremes reduces, but is not eliminated, with increasing warming. The rate of change in an indicator with warming varies across the UK. For temperature-based indicators this reflects variability in current climate, but for rainfall-based indicators reflects variations in the change in climate. Most indicators show a generally linear increase in risk with level of warming (although the change in risk from now is around 2.4 times higher in a 4 °C world than a 2 °C world because of warming experienced so far). However, some indicators—particularly relating to heat extremes—show a highly non-linear increase with level of warming. The range in change in indicator at a given level of warming is primarily caused by uncertainty in the estimated regional response of to increasing forcing.

Phosphorus application affects lowland rice yields by changing phenological development and cold stress degrees in the central highlands of Madagascar

• P-deficiency delayed heading of rice by 6–24 days in Madagascar highlands. • Delayed heading in P deficiency had a positive effect on yield under no cold stress. • Phenological delay increased risk of cold stress at reproductive to ripening stages. • P effect was greater when avoiding cold stress by shortening days to heading. • P deficiency management should take into account the effect of P on rice phenology. Despite a general perception that phosphorus (P) deficiency delays phenological development in annual crops, the impacts of interaction between this phenological delay and climatic conditions on crop productivity remain poorly understood. On-farm experiments were conducted in the central highlands of Madagascar, where P deficiency and late-season low temperature stress frequently restrict rice yields. Rice X265 was grown under four different fertilizer treatments with different combinations of N and P during early, intermediate, and late transplanting dates (ETP, ITP, and LTP, respectively). Plants subject to no fertilizer or single N treatments showed delayed heading by 6–24 days. This notable delay in the phenological development favored biomass accumulation and resulted in greater yield in ETP when low temperature stress was negligible. In contrast, delay in phenological development without P application increased cooling degree days and spikelet sterility in ITP. Consequently, the effect of a single N application had a positive effect only in ETP. The effect of P was much greater in ITP than in ETP because P application alleviated not only P deficiency but low temperature stress as well by shortening day to heading. In LTP plots, yield was severely suppressed to less than 1 t ha −1 , with sterility rate above 75 %, irrespective of fertilizer treatment. This study provides field evidence that phenological delay under P deficiency has dual effects on grain yield and that optimal N and P management practice differs with climatic growing conditions. Changes in phenological development due to plant nutrient status and its interaction with climate-induced stress needs further attention for improving fertilizer management practice.

Impact of weather data and climate change projections in the refurbishment design of residential buildings in cooling dominated climate

The methodology, the site and the dataset as well as the emissions scenario considered in the weather file definition influence the numerical evaluation of efficiency measures resilience. With a complete statistical and critical approach, the paper analyzes the importance of these aspects by means of a residential case study simulated in Benevento, a city of south Italy.Using data monitored from 2015 to 2020, a current weather file is built with different methodologies. The comparison indicates that there is not repeatability of the year chosen as a reference for the various months and thus the resolution of the building energy balance could bring different results. Some future climate projections are also generated on medium (2050 s) and long (2080 s) term considering different emission scenarios. With long term projection, the heating degree days are reduced also of − 21% meanwhile the cooling degree days are more than double compared with the current condition. This suggests a remarked transition towards a dominant cooling climate for Benevento.Moreover, when the climate change is considered, the insulation intervention and the installation of double glazed low emissive window is not resilient because the heating energy need decreases also of −56%, but the cooling energy need increases of + 62% (2080 s). If the efficiency measures include also the cool roof and the external shadings, the cooling demand could be reduced until –33% in some scenarios (e.g. RCP 4.5-50th percentile) and increased (+31%) in some others (e.g. 2080 s).

Effects of chilling at the booting and flowering stages on rice phenology and yield: A case study in Northeast China

AbstractClimate change has resulted in a continuous increase in the frequency and intensity of chilling events in cold regions. In Northeast China, chilling at the booting and flowering stages negatively affects japonica rice grain yield. In this field experiment study, we conducted a 2‐year temperature‐controlled experiment to investigate the effects of chilling temperature and duration applied at the booting and flowering stages on japonica rice. The results showed that chilling at the two study stages delayed the rice phenology and decreased the grain yield. In particular, japonica rice was more sensitive to chilling at the booting stage than at the flowering stage. The rice grain yield was reduced by more as the chilling temperature decreased and the chilling duration increased. As for the yield components, the spikelet fertility and grain number per spike were more sensitive to chilling at the booting stage than at the flowering stage. Variations in the grain yield per plant were primarily contributed by the differences in spikelet fertility and grain number per spike, especially the spikelet fertility. In addition, cooling degree days showed statistically significant negative correlations with grain yield per plant, grain number per spike and spikelet fertility. For every 10°C·day increase in CDD at the booting (flowering) stage, the grain yield per plant, spikelet fertility and grain number per spike decreased by 7.1%, 6.2% and 3.4% (3.9%, 5.0% and 1.2%) respectively. As the spikelet fertility and grain number per spike decreased, the sink capacity decreased as well with the increasing of allocated assimilation to the stem and leaf while decreasing the assimilation allocated to the panicle. Increasing cooling degree days at the booting and flowering stages increased the allocations of assimilation to the stem and leaf. As a result, less assimilation was allocated to the panicle. This study suggests that breeding cultivars to improve the spikelet fertility and grain number per spike could help to minimize the potential rice grain yield loss due to the increase in chilling events occurring at the booting and flowering stages.

Factors affecting the abundance of age‐0 sport fish in four mainstem Missouri River reservoirs

AbstractThe age‐0 abundance of eight sport fish species in the four mainstem Missouri River reservoirs in South Dakota was evaluated to estimate the influence of environmental and biological factors on age‐0 species abundance. Datasets (at least ten consecutive years) from each reservoir were analysed to evaluate the effects of both monthly (i.e. gauge height, temperature and precipitation) and annual (i.e. cooling degree days and heating degree days, minimum, average, and maximum temperature, and average precipitation) environmental and biological factors. Biological factors including age‐0 prey fish abundance (i.e. gizzard shad Dorosoma cepedianum [Leseuer] abundance), age‐0 sport fish abundance and adult sport fish abundance were examined. Factors were included that are known to have impacts on abundance of age‐0 sport fish in other systems. The abundance of all sport fish species was stable or increasing in all reservoirs, except for walleye Sander vitreus (Mitchell) and white bass Morone chrysops (Rafinesque) in Lewis and Clark Lake. Age‐0 white crappie was the most supported model for explaining age‐0 walleye abundance in Lewis and Clark Lake, and adult white crappie abundance was the most supported model parameter for explaining age‐0 white bass abundance in the reservoir. Findings of the current study highlight the need for species‐specific management of both environmental (i.e. flow manipulation) and biological factors (i.e. harvest limits for sport fish) to increase the abundance of age‐0 sport fish. Due to the dynamic nature of aquatic systems, resulting requirements for management agencies are system‐specific evaluations and management approaches.

Environmental and Social Dynamics of Urban Rooftop Agriculture (URTA) and Their Impacts on Microclimate Change

Urban cities are facing the challenges of microclimatic changes with substantially warmer environments and much less access to fresh vegetables for a healthier food supply than in adjacent rural areas. In this respect, urban rooftop agriculture is considered as a green technology for city dwellers and the community to attain environmental and socioeconomic benefits in a city. For this purpose, a roof top of 216 square meters was selected as an experimental plot where 70% of the area was covered with the selected crops (Tomato, Brinjal, Chili, Bottle Gourd and Leafy vegetables such as Spinach, Red Spinach and Water Spinach; they were cultivated under fencing panels of Bottle Gourd). The microclimatic parameters such as air temperature, near roof surface temperature, indoor temperature and relative humidity and carbon dioxide concentration from different locations of the agricultural roof and from nearby bare roofs were observed during the whole experimental period (November 2018–May 2019). Five existing rooftop gardens with green area coverages of 40, 50, 60, 80, and 85% were selected, and 5 bare nearby roofs were also selected through field visits and questionnaire surveys of 200 existing rooftop gardens. The air and ambient temperature, cooling degree day and energy saving trends were assessed for the selected roofs. The economic assessment was carried out through the net present value and internal rate of return approach of urban rooftop agriculutre. The results showed that the temperature was reduced from 1.2 to 5.5% in different area coverages of agricultural roofs with plants compared to the nearest bare roofs. For the time being, the cooling load was decreased from 3.62 to 23.73%, and energy saving was increased significantly from 5.87 to 55.63% for agricultural roofs compared to bare roofs. The study suggested that the value of urban rooftop agriculture was high environmentally and economically compared to the traditional bare roof, which would be an added amenity by the city dweller’s individual motivations and state interests, and it could be aligned to achieve a more sustainable city.

Nonlinear temperature response of electricity loads and implications for power development policies in Vietnam

Understanding how electricity demand responds to the ambient temperature is critical for the safe and efficient operation of the power system. Examining an extended series of daily electricity records from 2011 to 2020, we find that there is a significant nonlinear temperature-electricity load response approximating a cubic function of the temperature or the cooling degree days in the two major power subsystems in northern and southern Vietnam. Such a nonlinearity indicates a major concern for power supply infrastructure to meet increasingly more severe weather-induced load variations. We conclude the paper with several critical recommendations for future power development policies in Vietnam.