A Review of Studies Involving the Effects of Climate Change on the Energy Consumption for Building Heating and Cooling
Abstract
:1. Introduction
2. Specific Amounts Estimation of Climate Change Influences on Building Heating and Cooling Energy Consumption
2.1. Statistical Method
2.2. Model Method
2.2.1. Physical Model Method
2.2.2. Comprehensive Assessment Model Method
2.3. Combination Method of the Statistical and Model Methods
3. Influences of Climate Change on the Energy Consumption of Building Heating and Cooling Based on the Degree Days Method
3.1. Indices Related with Degree Days
3.2. Spatial-Temporal Changes in Indices Related to Degree-Days
3.3. Influece Factors of the Spatial Distribution of Degree Days
3.4. Impacts of Urbanization on Degree Days
4. Future Directions
4.1. Estimating the Amounts of Impacts of Climate Change on Building Heating and Cooling Energy Consumption
4.2. Spatial-Temporal Changes in Heating and Cooling Degree Days and Their Influencing Factors
4.3. Impacts of Urbanization on Heating and Cooling Degree Days
4.4. Production and Share of Related Datasets
4.5. Subsequent Effects Induced by the Climate Change on the Energy Consumption of Building Heating and Cooling
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Method Name | Basic Operations | Advantages | Disadvantages | Representative Studies |
---|---|---|---|---|
Statistical method | Establish the relationship between energy consumption and its influencing factors. | Estimate the specific amounts of influences of climate change on building heating and cooling energy consumption at a single building, city, or region scale. |
| [6,14,22,24,26] |
Physical model method | Use software to simulate the heating and cooling energy consumption of representative manual set or actual existing buildings under past, present, and future climate and building parameters. | Estimate the specific amounts of influences of climate change on building heating and cooling energy consumption of a single building in high temporal resolution under various scenarios. |
| [29,30,31,32,33] |
Comprehensive assessment method | Only choose some key parameters to roughly simulate or calculate the effects of climate change on building heating and cooling energy consumption. | Estimate the specific amounts of influences of climate change on building heating and cooling energy consumption at the year or month scale in regional or global scale. |
| [7,34,35,36,37] |
Combination method of the statistical and physical model methods | Establish the relationship between simulated energy consumption by physical model rather than actual consumption and the influencing factors. | Estimate the specific amounts of influences of climate change on building heating and cooling energy consumption in a single building without using actual energy consumption data. |
| [29,38,39,40] |
Degree days method | Analyze the spatial-temporal evolution of degree days and their differences between at the urban and suburban or rural stations. | Simple, efficient and reliable to represent the impacts of climate change on the energy consumption of building heating and cooling. |
| [41,42,43,44,45] |
Variable | Source |
---|---|
Building size (sqft) | Assessor DB 1 |
Building age | Assessor DB/RASS 2 |
Number of stories | RASS |
Number of bedrooms | RASS |
Presence of garage | RASS |
Cooling technology and age | RASS |
Heating technology and age | RASS |
Window quality | RASS |
Framing and foundation | Assessor handbook |
Exterior finishes | Assessor handbook |
Interior finishes | Assessor handbook |
Ceiling fans | RASS |
Temperature set point | RASS |
Water heater technology and age | RASS |
Study Area | Degree Days Indices | Influencing Factors | Analysis Methods | References |
---|---|---|---|---|
Madison, Wisconsin USA | HDDs 1 and CDDs 2 | Percent impervious surface coverage, lake effects, topographic relief | Linear and spatial regression | [41] |
Bangladesh | HDDs and CDDs | Latitude, longitude, altitude, annual mean daily temperature, 10 large scale atmospheric circulation indices | Linear regression method, Pearson correlation, random forest (RF) model | [53] |
Florence, Italy | CDDs | Impervious surfaces | Linear regression | [68] |
Andalusia Autonomous Region, Spain | HDDs and CDDs | Elevation, distance to the sea | Semi-partial correlation | [79] |
Xinjiang Province, China | HDDs and CDDs | Latitude, longitude, and altitude | Linear regression method | [80] |
Parameter | Var. Explained (%) | ||
---|---|---|---|
Percent Impervious | Lake Proximity | Topographic Relief | |
HDDs 1 | 67 | 6 | 2 |
CDDs 2 | 75 | 3 | 2 |
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Li, Y.; Wang, W.; Wang, Y.; Xin, Y.; He, T.; Zhao, G. A Review of Studies Involving the Effects of Climate Change on the Energy Consumption for Building Heating and Cooling. Int. J. Environ. Res. Public Health 2021, 18, 40. https://doi.org/10.3390/ijerph18010040
Li Y, Wang W, Wang Y, Xin Y, He T, Zhao G. A Review of Studies Involving the Effects of Climate Change on the Energy Consumption for Building Heating and Cooling. International Journal of Environmental Research and Public Health. 2021; 18(1):40. https://doi.org/10.3390/ijerph18010040
Chicago/Turabian StyleLi, Yuanzheng, Wenjing Wang, Yating Wang, Yashu Xin, Tian He, and Guosong Zhao. 2021. "A Review of Studies Involving the Effects of Climate Change on the Energy Consumption for Building Heating and Cooling" International Journal of Environmental Research and Public Health 18, no. 1: 40. https://doi.org/10.3390/ijerph18010040