Increasing emissions of greenhouse gases after the Industrial Revolution caused warming of Earth’s climate system (IPCC 2014). British Petroleum (2019) reported that world population may grow up to 50% in the next forty years and thereby energy demand may increase by 80%. About 40% of the world’s energy consumption is allocated to the residential sector (United Nations 2016), leading to 36% of the world’s CO2 emissions (Delgarm et al. 2016; Naderi et al. 2020). By continuation of the current CO2 emissions rate, global temperature increase by 3.2-4 ºC in comparison to pre-industrial level until 2050 is not unexpected (IPCC 2014). Some studies in the United States showed that 1 ºC increase in air temperature leads to 3–15% decrease in heating demand and 5–20% increase in cooling demand (EPA 2016; Obringer et al. 2020). To stop global warming’s increasing trend and control climate changes, we need to significantly and sustainably reduce greenhouse gas emissions. One effective method for controlling greenhouse gas emissions is to enhance buildings’ energy performance (Ferrara et al. 2014). An undeniable fact regarding greenhouse gas emissions is that this important task can only be done by cooperation of all countries.
Weather directly impacts buildings’ heating and cooling energy demand (Atalla et al. 2018). Energy consumed for buildings’ heating and cooling is influenced by climate change. Nowadays, heating and cooling energy supply has become a critical problem in many countries. Also global warming and climate change are considered as a threat for human population by many scientists and they have been analysed via different viewpoints. Degree-day method is considered a very important index in evaluating climate changes (You et al. 2014) and one of the simplest yet useful methods for calculating the energy consumption of a building. This simple method is also utilized in other scientific fields such as agriculture, architecture, entomology, etc. The degree-day method has been used for calculating energy consumption specifically for building’s heating and cooling since 1932 (Dufton 1934) and it is generally considered a trusted method for this purpose (Atalla et al. 2018). Adjusting living environment’s temperature status with a reasonable consumption of energy along with effective environmental management can reduce expenses and maximize benefits from resources for the sake of society (Christenson et al. 2006).
HDD and CDD can be studied using different temperature thresholds. The temperature threshold is defined as the comfortable temperature for human so that there is no heating or cooling demand. The thresholds may differ depending on economic status, energy supply and human physiological needs. For example, heating and cooling temperature thresholds are respectively 18 ºC to 22 ºC for Europe (Eskeland and Mideksa 2010), 17 ºC and 22 ºC for Florence, Italy (Petralli et al. 2011), 18 ºC and 26 ºC for Hong Kong (Chan et al. 2012), 14 ºC and 21 ºC for Andalusia, Spain (Limones-Rodríguez et al. 2018), 20 ºC and 23.8 ºC for Indiana state, USA (Hamlet et al. 2019), 18 ºC for HDD for China (Shi et al. 2018), and 22 ºC for CDD in India (Mazdiyasni et al. 2017). In this study, as recommended by Iran Meteorological Organization (IRIMO), we determined 18 ºC temperature threshold for heating and 21 ºC temperature threshold for cooling.
Owing to the importance of energy demand, numerous studies have analysed HDD and CDD, it can be referred to the works of (Petri and Caldeira 2015; Quayle and Diaz 1980) in USA, (Dombaycı 2009) in Turkey, (Semmler et al. 2010) in Ireland, (Taseska et al. 2012) in Macedonia, (Castañeda and Claus 2013) in Argentina, (Al-Hadhrami 2013) in Saudi Arabia, (Shen and Liu 2016) in China, (Choi and Kim 2019) in East Asia and (Arnell et al. 2019) at the global scale. Roshan et al. (2017b) investigated thermal comfort boundaries for 12 cities in Iran. In another study, Roshan et al. (2017a) reported that only 18% of studied stations in Iran had thermal comfort bioclimatic conditions. Wachs and Singh (2020) projected that due to climate changes, residential cooling energy demand in northern cities of the state will increasingly grow by 2080.
The trend analysis and change point detection of climate parameters provide precious information for a physical understanding of climate change and its impact on our living environment. One of the most important challenges caused by global warming and climatic change is an energy consumption shift. Iran is a major energy supplier: the second oil and gas supplier and exporter in the world (before the USA sanctions against Iran in 2019). Yet, having more than 80 million population along with its old infrastructure made Iran also one of the major energy consumers. Energy consumption in the country is 4.4 times above the global average, making it one of the top ten greenhouse gas emitting countries (Gorjian et al. 2019). Achieving a sustainable development without considering energy sector is impossible. One of the most important potential factors of energy consumption increases in any region is temperature changes. Measuring cooling and heating degree-days can present a clear and exact image of building, city and region’s thermal demands. It can also play an important role in reforming energy consumption patterns. In this study, monotonic analysis was performed on HDD, CDD and HDD + CDD time series for the first time. Previous studies (Kadioğlu et al. 2001; OrtizBeviá et al. 2012; Shi et al. 2018; Spinoni et al. 2015) have investigated the long-term changes in HDD and CDD time series, but not abrupt changes. For an accurate fluctuation analysis of these time series, pre- and post-breakpoint series trends were obtained and analysed. Return periods were also calculated using the best statistical distribution for the studied time series. Spatial analysis of the studied indices was carried out with Cokriging interpolation method. It should also be noted that in this study, the Pettitt test was used for the first time in detecting multiple breakpoints in the time series. Our findings can reveal climate change impacts on buildings’ cooling and heating demand, thus contributing to decision-making and planning process for energy management.