Estimation of Real Seasons in a Semi-Arid Region, Ghardaia, Case Study

Throughout The climate of our planet is based on seasons, which are classified into two major categories, namely; astronomical and real seasons. Generally, the astronomical seasons are known by their spring and autumn equinoxes’ seasons, whereas summer and winter are the solstice’s seasons. The first category practically keeps the same behavior on global scale [1]. However, the second category varies from one region to another, due to several parameters [2]. The determination of inter-season periods is thermally ideal and passively comfortable and based on different parameters [3]; among them:

• Start and end of the device operation; Such as heating and air conditioning [3].

• Heating Day (DJC) and Day Air Conditioning (DJF) degrees; are as small as possible (weak) [4].

• Internal hygro-thermal comfort; are generally insured within the comfort intervals by temperature ranges (18 <Tc <28, 25% <Hc <80%) [4].

• External temperatures are nexus the internal temperatures (The temperature ranges between the outside and inside of the building is low).

• Wind speeds.

• Atmospheric pressure, sunshine and precipitation.

So it can be said that the challenge in these periods is to avoid as possible the use of heating and air-conditioning systems. In other hand, the natural hygro-thermal comfort should be ensured (the inertia of the housing and the natural ventilation), based on the sensitive storage which is difficult. This is due to the influence of several indices related to human beings or to the buildings themselves [5], such as human metabolism (age, sex, fatigue, etc.), ambient temperature (Ta), the mean temperatures radiated from the walls (Tp) relative air humidity (Hr), air velocity, orientation of the building and other Different materials used, insulation, etc.). Additionally, the internal thermal imbalance and all the known problems can be partially solved by applying new techniques and approaches. Accordingly, it can be cited the intelligent materials called phase change materials (PCM) based on the latent storage principle, whose their melting temperatures are closer to the desired comfort temperature (between 18℃ and 27℃). The storage and discharge of these materials are based on the endothermic-exothermic phenomena whose shape variation is sinusoidal (above and below these melting temperatures).

Several researches adopted the selection and integration of this new material in summer. They focused on the integration based on the use of phase change materials in the building structure. Therefore, its choice is reduced to a single melting temperature in the comfort interval, between 17℃ and 30℃. Accordingly, a study has been carried out within this field in Ghardaïa region by Stojanovi et al. [6]. These essential thermal problems related to buildings, caused many of the social hazards and social problems such as: the carbon monoxide emission (CO₂) which causes environmental impacts: In Algeria; for example;

The number of people who died between 1 January and 09 February 2017, was 49 people, due to the carbon monoxide emitted by the different heating systems at the national scale [6], High heating and air conditioning bills, Greenhouse gas emissions (the increase in CO₂ in the planet), thermal imbalance in housing, etc.

The climate is variable over the world regions and in the same country due to the radical change, the geographical localization ... etc.). In the Algerian case, the climate varies from north to south and divided into seven main climatic zones (A, B, B, C, D1, D2, D3), zone has a different weather conditions. Thus, our current study is based on Ghardaïa region characteristics, which presents a hard climate, regarding its important situation in the southern part of Algeria, which belongs to the climatic zone D1. The known weather of this city is a cold winter within three months (December, January and February) and a dry very hot summer within a period of five months (May, June, July, August and September). In addition to the spring disturbances, caused by sandy storms between April and March, however, the fall season is generally the most stable weather within period (October and November). This medium weather influences the energy expenditure of the summer period within the months [May, June, July, August and September]. In other times, it constitutes the more rate with (3/2); including the months of winter period [December, January and February]. Reference to the work of [7], about 16893.4 KWH in summer 2014 and about 12738 KWH in winter of the years [2013-2014] have been recorded, respectively. This study yielded energy expenditure of 28% for the winter, 13% for the spring, 42% for the summer and 17% for the fall. In order to raise these problems mentioned above, our work based on a new idea, and on the integration of two phase change materials, at different melting temperatures (MCPTf1 and MCPTf2), within the comfort intervals [18℃, 27℃]. The used values are for the winter season between 18℃ and 22℃ and for the other for the summer season between 24℃ and 28℃.

The main objectives of this project are the radical elimination of active heating and cooling during the inter-season periods to will make the most of the equinoxes (autumn and spring) to ensure hygrothermal comfort.

Because the difference between the mean (amplitude) temperatures of the night and day (daytime and night) of the equinoxes is not great, they remain acceptable [between -5 and +5]. But the amplitudes of the solstices remain large over all the Saharan regions and over the high plateaus of Algeria (between 0 and 30) [8]. Unfortunately, we are faced with the thermal failure of the two solstices and all of them in the summer period. The technical aspect of this new idea will allow us to delay the re-entry of the thermally critical seasons (winter and summer) and accelerate it out of its periods. A time prolongation of the real intervals of the two equinoxes takes place by a precise selection and the specific integration of the two intelligent materials (MCPs). For the proper functioning of the storage and the discharge of the MCPs; the use of its MCPs will reduce the energy consumption related to heating, air conditioning and diminution of greenhouse gases. These materials will delay and dampen peak temperatures in the heat wave periods, in a dysphasic manner and the distance of time from the devices will affect the improvement of the social and economic Tangible reality with these integration techniques.

Our current work consists of a first kind study, which involves the actual use and study of the two MCPs in the building structure. First, it will consist of a site selection, a construction of a large meteorological database of two stations [ENERCO (Series 400 and 500), German] Thus, the obtained data were compared to the climatological data of the RET Screen engines of [1980-2006], as well as data acquired from the National Weather Office (ONM) of Ghardaïa. Accordingly, the heating day (DJC) and the day of air conditioning (DJF) have been calculated. In the goal to determine exactly the actual thermal seasons and to make simulated calculus, moreover, the intervals days between the seasons were selected and the real socio-economic impact of the MCPs integration in the multizone building tissue, in the region of Ghardaïa, is deduced.

The Wireless Weather Station with Touch WS2-550: is used to record, process and display real internal data for a 2016 year of accommodation studied at the level of our URAER city. It is a very reliable and efficient station, equipped with a combined weather sensor (thermo-hygrometer, rain gauge, and anemometer).

For the outside date collection an efficient specific metrological station has been used to, measure several parameters such as temperatures, humidity, wind speed, pressure, and solar radiation (Figure 2).

The station Operates with 10 min and an accuracy of 0.005 (℃).

2.png

Figure 2. URAER Ghardaïa weather station

The choice of the comfort range [19℃-30℃]:

1. Comfort temperature: Several researchers are working on the determination of thermal comfort limits on buildings; According to the diagnosis of [8].

$T_{n}=9.22+0.48 T_{\text {int }}+0.14 T_{\text {ext }}$     (1)

This is the new standard 55-200432, which he used by Khelifi et al. [9]. The choice of the building's comfort domain, linked to the impacts of several parameters, cited above, and others which are grouped in the following two tables (Table 1 and Table 2) [10].

Table 1. Contact temperature between the human body and some materials [10]

Table 2. Operational temperatures for summer and / or winter comfort [11]

For the calculation of the day Degrees; either for heating (DJC) or for air conditioning (DJF), we have several methods that do this, among the most used; the real method what I call " the professional energy method " (conforms to the regulatory Costic method for the heating and air conditioning operating markets to be used for monitoring) and the "Weather" method with simple calculation, to be used by the RET Screen motor [08].

The importance of calculating the degree-day is to allow estimating the expenditure of energy consumption linked to the thermal (heating and air conditioning) of the buildings. Therefore, it is the evaluation of the harshness of the climate from one year to another and from one region to another (to compare buildings located in different climatic zones and to compare years of heating between them, p .ex. following investments). The Degree Day for any chosen site is a value representative of the difference between the temperature of a given day and a preset temperature threshold.

The Degree Day for any chosen site is a value representative of the difference between the temperature of a given day and a preset temperature threshold [12-14].

Tmin: Minimum temperature for D-day measured at 2 meters from the ground under shelter and recorded between D-1 (the day before) at 6 p.m. and D at 6 p.m. UTC.

Tmax: Maximum temperature on day D measured at 2 meters from the ground under shelter and recorded between D at 6 a.m. and J+1 (the next day) à 06h UTC. $T_{\text {moy }}=\frac{T_{\min }+T_{\max }}{2}$, average temperature of the day.

Tcs: Set point temperature or selected reference temperature threshold.

For our study: Tcs1 = 18℃ and Tcs2 = 27℃.

In our calculation, applied the following two methods:

• Weather method:

If $\left(T_{c s 1}<T_{\text {moy }}\right), D J C=0 ; \quad$ If $\quad\left(T_{c s 1}>T_{\text {moy }}\right)$

$\ldots \ldots \ldots \ldots J=T_{c s 1}-T_{\text {moy }}$     (2)

•Professional energy method:

For the start and end of the heating period:

$DJC=\left( {{T}_{c}}-{{T}_{\min }} \right)*\left( \begin{align}  & \frac{0.08+0.42*\left( {{T}_{c}}-{{T}_{\min }} \right)}{\left( {{T}_{\max }}-{{T}_{\min }} \right)} \\ &  \\\end{align} \right)$     (3)

For the start and end of the air conditioning period:

$D J F=\left(T_{\max }-T_{c}\right) *\left(0.08+0.42 *\left(T_{\max }-T_{c}\right) /\left(T_{\max }-T_{\min }\right)\right)$      (4)

Table 3. Heating day degrees using the actual method, weather method compared with data from the average RET screen motor

Table 4. Air conditioning day degrees using the actual method, weather method compared with data from the 26-year-old RET screen motor

Note that the results in the two Tables 3 and 4 are comparable with each other and coincide with that of RETS screen, the differences either less or more because of the influence of global warming which has become a reality in Algeria [15-17].

In Figure 29, we note that the evolution of average temperatures at synoptic hours of Ghardaïa during the five years of our study (2012-2016) are increasing compared to NASA data from (1940-2006), due to global warming.

29.png

Figure 29. Evolution of average temperatures at synoptic (average temperature of the Ghardaïa region) hours of Ghardaïa (2012-2016) compared with the Ret screen (1940-2006)

In Table 7, we see that the average length of spring and autumn are shorter in comparison with summer and winter, represent respectively; 54 days, 52 days, 135 days and 124 days, during the five years study. In the two previous Tables 8 and 9, we note that the full south orientation is better compared to the studied East-South orientation 35° (real state of housing), because the duration of sunshine of hot periods of the latter and more significant than the first (due south). Therefore, there is more consumption linked to air conditioning (same comments for Figures 30, 31, 32 and 33).

Table 7. Average length of each Ghardaïa season [2012-2016]

Table 8. Sunrise and sunset at the start of each season; duration of sunshine of each face and the sunshine rate for each face in Ghardaïa, for a clear sky facing south

Table 9. Sunrise and sunset at the start of each season; duration of sunshine of each facade as well as the rate of sunshine for each facade in Ghardaïa, for a clear sky east_south orientation with 35 ° [the case study (accommodation location)]

30.png

Figure 30. The duration of the sunshine on the surface of each facade during the year (hour) of Full south orientation in Ghardaïa

31.png

Figure 31. The duration of the sunshine on the surface of each facade during the year (hour) of East-South Orientation with 35 ° in Ghardaïa [The study case]

32.png

Figure 32. The duration of the sunshine on the surface of each facade during the year (%) of Full south orientation in Ghardaïa

33.png

Figure 33. The duration of the sunshine on the surface of each facade during the year (%) of East_South Orientation with 35 ° in Ghardaïa [The study case]

34.png

Figure 34. The sunshine rate of each façade on December 21

35.png

Figure 35. The rate of sunshine of each Facade on March 21

36.png

Figure 36. The rate of sunshine of each Facade on June 21

37.png

Figure 37. The rate of sunshine of each Facade on September 21

38.png

Figure 38. Comfort temperatures as a function of average monthly temperatures 2012, compared with stool [19]

39.png

Figure 39. Comfort temperatures as a function of average monthly temperatures for 2013, compared with stool [19]

40.png

Figure 40. Comfort temperatures as a function of average monthly temperatures for 2014, compared with stool [19]

41.png

Figure 41. Comfort temperatures as a function of average monthly temperatures for 2015, compared with stool [19]

Table 10. The days of average energy expenditure in all seasons for the five selected years [2012-2016]

Table 11. Comfort real temperature in the Ghardaïa region

Figures 34, 35, 36 and 37 show the rate of sunshine of each Facade on March 21st, June 21st, September 21st and December 21st, however the Comfort temperatures as a function of average monthly temperatures 2012, 2013, 2014 and 2015 compared with stool [19] are presented in the Figures 38, 39, 40 and 41. The days of average energy expenditure in all seasons for the five selected years [2012-2016] are mentioned in the Table 10, where the recapitulation Table 11 presents the comfort real temperature in the Ghardaïa region. All the last figures and tables are presented to enrich and detail the previous explanations.