Ecodesign Strategies for Reducing Environmental Impact on Solar HVAC Systems †

. Abstract: Approximately 40% and 36% of total energy consumption and CO 2 emissions, respectively, in the EU are due to buildings. A large percentage of this energy consumption and its associated CO 2 emissions are due to conventional heating, ventilation, and air conditioning (HVAC) systems. Solar desiccant cooling (SDEC) systems present a high energy saving potential to replace conventional HVAC systems. However, SDEC systems could generate a high environmental impact during their manufacturing stage, which may even exceed the beneﬁt in the use phase. Therefore, the aim of this work is to focus on studying feasible ecodesign strategies for a SDEC system composed mainly of an indirect evaporative cooler, a desiccant wheel and a solar thermal system. More speciﬁcally, the strategies considered were: (a) selection of environmentally friendly materials, such as biocomposites based on natural ﬁbers; (b) weight optimization; and (c) reuse of components at the end of the life phase. The results showed that the proposed strategies to the SDEC system could signiﬁcantly improve the environmental impact throughout its entire life cycle. Combining all the proposed improvements, the environmental impact was reduced between 45% and 60% for all the indicators.


Introduction
The global energy consumption of buildings has increased sharply in recent years, which has generated problems owing to its associated environmental impacts [1]. Solar desiccant cooling (SDEC) systems could help to reduce energy consumption in buildings, due to the use of renewable energies and its high energy efficiency [2]. However, during the manufacturing and end-of-life stages, these system also consume raw materials and energy from non-renewable sources, hence generating high environmental impacts [3]. Therefore, to properly assess the real benefits of the SDEC system, it is necessary to determine its environmental impact throughout its entire life cycle [4]. Life cycle assessment (LCA) is an appropriate methodology to scientifically evaluate any type of system or process in terms of environmental impact [5].
Considering that the environmental impact generated by SDEC systems is mainly owing to their manufacturing and end-of-life phases [6], reuse or recyclability can be especially advantageous in terms of circular economy and sustainability. Thereby, the aim of this work was to analyze some improvements of the SDEC systems in term of environmental impact. Specifically, some eco-design strategies were evaluated, material changes and reuse of materials at the end-of-life of the system.

Material and Methods
The experimental SDEC system studied was located in Andaltec (Martos, southern Spain) and was designed to supply air conditioned to a research laboratory. LCA was applied to analyse the influence on the environmental impact of the ecodesign strategies considered. Different case studies were analysed: (a) the base system (DW1), (b) the base system with improvements in the manufacturing phase (DW2), (c) the base system with improvements in the end-of-life phase (DW3); and, finally, (d) the two types of previous improvements (DW2 and DW3) applied together (DW4). Concerning DW2, the specific modifications in terms of ecodesign were the replacement of the aluminum in the structure of the solar collector with steel; and the replacement of the steel in the structure of the desiccant cooling systems with natural fiber-based biocomposites (NFB), achieving a reduction of 50% in weight. Regarding DW3, an improvement of the end-of-life phase was studied in which 50% of total mass of the components were reuse.
For this work, Eco-Indicador99 method [7] was selected because it allows easy comparison of the results. This method assesses the life cycle based on the three impact categories: All of the impact categories described above can be summed up in a single parameter, called the "single score parameter" (SCP).

SCP on Manufacturing Phase
The contribution of the manufacture phase to the SCP in DW1 and DW2, respectively, is shown in Figure 1. It can be observed that the maximum SCP value for DW2 was for steel, this result being half of the maximum value of DW1, for aluminium. This was due to the amount of aluminum involved in DW2 was less than half that of DW1 as a consequence of replacing some aluminum with NFB and weight optimization. of this work was to analyze some improvements of the SDEC systems in term of envi mental impact. Specifically, some eco-design strategies were evaluated, material chan and reuse of materials at the end-of-life of the system.

Material and Methods
The experimental SDEC system studied was located in Andaltec (Martos, south Spain) and was designed to supply air conditioned to a research laboratory. LCA applied to analyse the influence on the environmental impact of the ecodesign strate considered. Different case studies were analysed: (a) the base system (DW1), (b) the system with improvements in the manufacturing phase (DW2), (c) the base system w improvements in the end-of-life phase (DW3); and, finally, (d) the two types of prev improvements (DW2 and DW3) applied together (DW4). Concerning DW2, the spe modifications in terms of ecodesign were the replacement of the aluminum in the st ture of the solar collector with steel; and the replacement of the steel in the structure o desiccant cooling systems with natural fiber-based biocomposites (NFB), achieving duction of 50% in weight. Regarding DW3, an improvement of the end-of-life phase studied in which 50% of total mass of the components were reuse.
For this work, Eco-Indicador99 method [7] was selected because it allows easy c parison of the results. This method assesses the life cycle based on the three impact c gories: • Impacts on natural resources: this category is represented by the Land Used Pote (LUP) indicator. All of the impact categories described above can be summed up in a single param called the "single score parameter" (SCP).

SCP on Manufacturing Phase
The contribution of the manufacture phase to the SCP in DW1 and DW2, respectiv is shown in Figure 1. It can be observed that the maximum SCP value for DW2 was steel, this result being half of the maximum value of DW1, for aluminium. This was to the amount of aluminum involved in DW2 was less than half that of DW1 as a co quence of replacing some aluminum with NFB and weight optimization.

Impact Indicators
The percentage change in environmental performance (PC EP ) for all impact indicators in DW4 and DW1 is shown in Figure 2. The lowest PC EP values are presented in DW4 owing to the reduction in material consumption during the manufacturing phase and due to the material reuse at the end-of-life phase. The lowest indicators in DW4 were CEP, REP, Environ. Sci. Proc. 2022, 18, 17 3 of 4 CHP, RDEP, OLD, ETP, AP and FFD. However, LUP and MND were barely modified due to their low influence on electricity consumption. The main differences of PC EP between DW4 and DW1 came from the great reduction of the electricity consumption from the grid necessary for the manufacture of the aluminum. The CHP result is noteworthy, since it is an indicator highly regarded nowadays and a reduction of 60% was achieved with DW4.

Impact Indicators
The percentage change in environmental performance (PCEP) for all impact indicators in DW4 and DW1 is shown in Figure 2. The lowest PCEP values are presented in DW4 owing to the reduction in material consumption during the manufacturing phase and due to the material reuse at the end-of-life phase. The lowest indicators in DW4 were CEP, REP, CHP, RDEP, OLD, ETP, AP and FFD. However, LUP and MND were barely modified due to their low influence on electricity consumption. The main differences of PCEP between DW4 and DW1 came from the great reduction of the electricity consumption from the grid necessary for the manufacture of the aluminum. The CHP result is noteworthy, since it is an indicator highly regarded nowadays and a reduction of 60% was achieved with DW4.

Results for the Different Impact Categories
The results of the impact categories for all the case studies analysed are shown in Figure 3. The weight optimization strategy and the use of more environmentally friendly materials (DW2) led to a reduction of 50%, 18% and 22% in the impact categories of human health, ecosystem quality and resource consumption, respectively. In addition, DW3 results show that the reuse of materials used for manufacturing led to a reduction between 20% and 25% in the three impact categories studied. Finally, combining both strategies, DW2 and DW3, weight optimization and material reuse, a synergistic effect was perceived which led to a significant reduction in the impact associated with the different categories: up to 60% in human health, 25% in ecosystem quality and 45% in resource consumption.

Results for the Different Impact Categories
The results of the impact categories for all the case studies analysed are shown in Figure 3. The weight optimization strategy and the use of more environmentally friendly materials (DW2) led to a reduction of 50%, 18% and 22% in the impact categories of human health, ecosystem quality and resource consumption, respectively. In addition, DW3 results show that the reuse of materials used for manufacturing led to a reduction between 20% and 25% in the three impact categories studied. Finally, combining both strategies, DW2 and DW3, weight optimization and material reuse, a synergistic effect was perceived which led to a significant reduction in the impact associated with the different categories: up to 60% in human health, 25% in ecosystem quality and 45% in resource consumption.
The percentage change in environmental performance (PCEP) for all impact in in DW4 and DW1 is shown in Figure 2. The lowest PCEP values are presented owing to the reduction in material consumption during the manufacturing phase to the material reuse at the end-of-life phase. The lowest indicators in DW4 w REP, CHP, RDEP, OLD, ETP, AP and FFD. However, LUP and MND were bare fied due to their low influence on electricity consumption. The main difference between DW4 and DW1 came from the great reduction of the electricity cons from the grid necessary for the manufacture of the aluminum. The CHP result is thy, since it is an indicator highly regarded nowadays and a reduction of achieved with DW4.

Results for the Different Impact Categories
The results of the impact categories for all the case studies analysed are s Figure 3. The weight optimization strategy and the use of more environmentally materials (DW2) led to a reduction of 50%, 18% and 22% in the impact categories o health, ecosystem quality and resource consumption, respectively. In addition, sults show that the reuse of materials used for manufacturing led to a reduction 20% and 25% in the three impact categories studied. Finally, combining both s DW2 and DW3, weight optimization and material reuse, a synergistic effect was p which led to a significant reduction in the impact associated with the different ca up to 60% in human health, 25% in ecosystem quality and 45% in resource consu

Conclusions
A Life cycle Assessment (LCA) for a solar desiccant cooling (SDEC) system was carried out. In this work, environmentally friendly and light materials, such as natural fiber-based biocomposites (NFB), were selected with the aim of reducing the environmental impact of the SDEC system. The results showed significant impact reductions, between 25% and 60%, for all impact categories analyzed. This improvement was due to the manufacturing