**1. Introduction**

Glass is one of the world's most diverse substances because of its substantial properties, such as chemical inertness, optical clarity, low permeability, and high authentic strength [1–3]. The usage of glass items has greatly increased, leading to enormous quantities of WG. Globally, it is estimated that 209 million tons of glass are produced annually [4–6]. In the U.S., according to the Environmental Protection Agency (EPA) [7–9], 12.27 million tons of glass were created in 2018 in municipal solid waste (MSW), as shown in Figure 1, most of which were containers for drinking and food. Furthermore, in 2018, the EU generated 14.5 million tons of glass package wastes [10–12]. The quantity of generated WG will increase due to the increasing demand for glass components [13–16].

Recycling and reducing waste are key parts of a waste-management system since they contribute to conserving natural resources, reducing requests for waste landfill space, and reducing pollution of water and air [17,18]. According to Meyer [19], by 2030, the EU zero-waste initiative estimates that improvements in resource efficiency throughout the

**Citation:** Qaidi, S.; Najm, H.M.; Abed, S.M.; Özkılıç, Y.O.; Al Dughaishi, H.; Alosta, M.; Sabri, M.M.S.; Alkhatib, F.; Milad, A. Concrete Containing Waste Glass as an Environmentally Friendly Aggregate: A Review on Fresh and Mechanical Characteristics. *Materials* **2022**, *15*, 6222. https://doi.org/ 10.3390/ma15186222

Academic Editor: Krzysztof Schabowicz

Received: 1 August 2022 Accepted: 2 September 2022 Published: 7 September 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

chain could decrease material input requirements by 17% to 24%, satisfying the demand for raw materials between 10% to 40%, and could contribute to reducing emissions by 40% [20–22].

**Figure 1.** Distribution of MSW stream produced in the U.S in 2018. Adapted from [7].

In fact, innovative options for recycling WG must be developed. One significant option is to use WG for construction materials [23]. The recycling of WG not only decreases the demand for landfill sites in the building sector but also significantly helps in decreasing the carbon footprint and saving resources [24–26]. In 1963, Schmidt and Saia [27] performed the first research on the use of WG for building materials. The authors recycled WG into useful glass particles for wall-panel production. Subsequently, a significant study was conducted in order to use recycled glass for fine or coarse aggregate in mortar and concrete, because of the good hardness of the glass [14,28,29]. This study aims at reviewing the possibilities of utilizing WG in concrete as a partial or full replacement for fine or coarse aggregates in order to give practical and brief guidance on recycling and using WG [30–33].

#### **2. Research Significance**

Besides the above-mentioned dangers of WG and the need to recycle it economically and environmentally, this research explores the source of WG as well as its physical and chemical characteristics. In addition, this study aims to review the literature that discusses the use of recycled WG in concrete as a partial or complete alternative to aggregates by focusing on the effect of this waste on the fresh and mechanical properties of concrete in order to demonstrate the possibilities of using recycled WG in concrete and to provide practical and brief guidance. Furthermore, we are establishing a foundation for future study on this material and describing research insights, existing gaps, and future research goals.


**2.5.4 Immunohistochemistry**

3-5 µm thick sections obtained from formaldehyde fixed, paraffin-embedded tissue were dehydrated in graded ethanol. After antigen retrieval, slides were blocked using 3% BSA in PBS and incubated with mouse anti-human αvβ3 integrin (R&D Systems, Minneapolis, MN, USA), Muc-1 (Abcam, Cambridge, UK), LIF and rat anti-human MECA-79 monoclonal antibody (Santa Cruz biotechnology, INC., Santa Cruz, California, USA). Excess primary antibody was washed with PBS and the sections were again incubated with anti-mouse and anti-rat biotinylated secondary antibody (Santa Cruz biotechnology, INC., Santa Cruz, California, USA) according to the manufacturer's protocol, before incubation with avidin biotinylated horseradish peroxidase (Santa Cruz biotechnology, INC., Santa Cruz, California, USA). Labeled cells were visualized with Diaminobenzidine (DAB) and sections counterstained with hematoxylin. Next, the slides were dehydrated using series of alcohol gradient and mounted using distrene, tricresyl phosphate (DPX) and xylene. The slides were then examined under bright field microscope (Carl Zeiss, Jena, Germany).

#### **2.5.5 Scanning electron microscopy**

Formaldehyde-fixed tissues were washed in PBS and dehydrated in a series of alcohol gradient (50%, 70%, 90%, 95%, 100%), each for 10 mins, dipped in HMDS (1,1,1,3,3,3 hexamethyl disilazane; SRL, Bombay, India) and air dried. Dried tissues were then mounted and coated with gold and the luminal endometrial surface thoroughly examined under SEM (Jeol JSM-5800 Scanning Microscope, Tokyo, Japan). Pinopode formation was also evaluated semi-quantitatively depending on their stage of development on the surface of the endometrium, and scored as (i) well-developed (ii) poorly developed and (iii) absent and on their abundance and scored as (i) abundant (ii) moderate (iii) few.

#### **2.5.6 Real-time PCR**

Levels of COX-2, MMP-2, -9, TIMP-1 and -2 gene expression were analyzed by real time PCR (RT-PCR), which was performed with ABI Prism 7000 Sequence Detection System (Applied Biosystems Inc., Carlsbad, California, USA) using syber green master mix (Applied Biosystems Inc., Carlsbad, California, USA). RT-PCR primers were designed using sequence data. Total RNA was isolated from tissue by RNA isolation kit (Trizol Reagent, Invitrogen, Carlsbad, California, USA) and 10 μl of total RNA isolated was subjected to reverse transcription for cDNA synthesis with High-Capacity cDNA Reverse Transcription Kits (Applied Biosystems, Carlsbad, California, USA), according to the manufacturer's instructions. After synthesis, 5 μl of cDNA was used for the RT-PCR mixed with syber green. At the end of each reaction, Cycle threshold (Ct) was manually set at the level that reflected the best kinetic PCR parameters, and melting curves were acquired and analyzed. Relative quantification was used to measure gene expression by relating the PCR signal.


*4.1. Model Validation*

For validation, the comparison between the present models and Reference [8] is considered in this section (Table 4). There might be some errors due to the basic equations that EES uses to derive the characteristics of fluids. As results show, the deviation is low, and the models can be used for this analysis.

**Table 4.** Model validation of simulations by R11 with Reference [8].

As shown in Table 4, DRORC has a maximum exergy efficiency with 65.2% among the present systems. BORC produced more power compared with two other cycles, but as it is seen, this system has the lowest exergy efficiency because of its high exergy destruction rate in its components.

#### *4.2. Conventional and Advanced Exergy Analysis*

Considering conventional exergy analysis and by using the equations for each component of the cycles presented in Table 1, the exergy destruction rates are obtained. In the three cycles, the total exergy fuel rate is obtained from subtracting the exergy rate of the working fluid that leaves the evaporator from exhaust gases that enter the evaporator, and the total product exergy is the turbine power output. The main results of the conventional exergy analysis for BORC, SRORC and DRORC are presented in Tables 5–7, respectively. *EF*, *EP*, *EP*, *ED*, *YK*,*Y*∗ *K* in this tables are exergy of fuel, exergy of product, exergy destruction, exergy loss ratio and exergy of fuel with the total exergy destruction. It can be said that the components with higher exergy destruction rates have more e ffects on the e fficiency of systems from an exergy point of view compared with other components. Referring to Table 5, in BORC, the maximum exergy destruction rate happens in the evaporator, followed by the turbine, the condenser and the pump. Table 6 shows the exergy destruction rates for the SRORC components. As it is seen, in single-regenerative systems, turbines show the highest exergy destruction rates among cycles components due to their design, and evaporators, condensers, feed-water heaters and pumps are in the next ranks, respectively. For DRORC, the exergy destructive rates are shown in Table 7. In these systems, as in single-regenerative cycles, turbines have the maximum exergy destructive rate, and they are followed by evaporators. However, unlike SRORC, pump1 and feed-water heater 2 are placed in the next ranks because of the second flow that extracts from the turbine. As a summary, it can be concluded that evaporators, turbines and feed-waters have more potential to reduce their destructive rates and to increase system e fficiency. As it is seen, a conventional exergy analysis just focuses on components with high rates of exergy destruction, and it is not possible to specify whether these destructions occur in other components or in the component itself. These irreversibilities may only be specified by advanced exergy tools. As discussed above, an advanced exergy analysis evaluates the effects of component interactions and the real possibility of components to improve system e fficiency.

**Table 5.** Results from exergy calculations for BORC.

**Table 6.** Results from exergy calculations for SRORC.

**Table 7.** Results from exergy calculations for DRORC.

By advanced exergy analysis, the exergy destructions of each component calculated in the previous section can be discussed in detail to find the sources of these destructions and real potentials of each component to amend the e fficiency of the whole system. As mentioned above, these irreversibilities

can be divided into exogenous, endogenous, unavoidable and avoidable parts to help researchers observe the effects of technological limitations and component interactions on the exergetic efficiency of a system for improvements [33]. In the advanced exergy analysis, the endogenous part of exergy loss for the kth component is calculated by defining real and ideal conditions for the cycles first. Then, the exogenous destruction rate is obtained by the difference of the total exergy and endogenous part (Equation (22)). To calculate the unavoidable exergy rate of loss in the kth part, instead of real conditions in cycles, unavoidable conditions are considered, and avoidable exergy is obtained from Equation (23). Furthermore, the values of exogenous/avoidable, endogenous/avoidable, exogenous/unavoidable and endogenous/unavoidable are determined using Equations (25) to (28). Advanced exergy analysis results for each part in three different cycles (BORC, SRORC and DRORC) are presented in Tables 8–10.

**Table 8.** Advanced exergy analysis results (kW) for BORC.

**Table 9.** Advanced exergy analysis results (kW) for SRORC.

**Table 10.** The results of the advanced exergy analysis (per kW) for DRORC.

As indicated in Table 9, for BORC, the exogenous exergy rate is greater than the endogenous exergy rate in system components, except the evaporator. So, system performance and modification of other components are necessary for turbines and condensers to decrease their exogenous destruction rates. The greater share of exergy destruction in the evaporator is caused by irreversibility of the component itself because of its high exergy loss rate in the endogenous part. As it was discussed before, the avoidable destruction rate in exergy can be controlled and reduced in practice. Table 8 shows that a turbine consists of a high value of avoidable destruction rates (7.4 kW) among the components of a system. Thus, the efficiency of this component can be improved using some technical modifications and new technologies or by replacing the component with the ones with higher efficiencies. It is important to note that, unlike the conventional analysis, a turbine is the most effective component due to its avoidable destruction rate to reduce irreversibilities. So, the main focus will be on the avoidable/endogenous parts of the exergy destruction, which can be decreased by improving the efficiency of the kth component. It follows by an investigation on the exogenous/avoidable exergy rates of loss, which can be reduced by improving the efficiency of other parts [34]. As it is stated

in [17], Table 8 shows that the avoidable/endogenous exergy destruction rates in the turbine are greater than the unavoidable/endogenous destruction rates for BORC. This shows that the efficiency can be improved by technical modifications of this component. Table 8 also indicates that, except the condenser, the exogenous/avoidable exergy destruction rates are higher than the exogenous/unavoidable exergy rates of loss for the components. Results of the advanced exergy analysis for the division of the exergy rate of loss in the main parts in BORC are shown in Figure 4. As Figure 4 indicates, for the turbine, 79% of the total exergy rate of loss is avoidable, and from this rate, 53% can be reduced by amending other components efficiencies, and 26% of this rate depends on the performance of the component itself.

**Figure 4.** Splitting exergy destruction rates of components: (**a**) the evaporator, (**b**) turbine and (**c**) condenser in the BORC system.

In Table 9, for SRORC, except the condenser, the endogenous exergy destruction rate is higher than the exogenous exergy destruction rate in the system's components, which shows that, unlike BORC, the greater share of the destruction rate is because of the internal irreversibilities in the component itself. So, among all components in SRORC, the turbine consists of the highest destruction rate in the exogenous part (1.77 kW), and the evaporator has the maximum endogenous destruction rate (2.56 kW) among the system's components due to its irreversibilities. As it is seen in Table 9, the avoidable part of the exergy destruction rate is higher than the unavoidable part in all components of SRORC. This indicates that there is a great potential in a system to reduce its irreversibilities by using some efficient and new components. Splitting the exergy destruction rates into endogenous/avoidable and exogenous/avoidable parts provides some important information that helps researchers to optimize systems. As it is seen in Table 9, the avoidable/endogenous exergy destruction rates in all equipment are higher than the exogenous/avoidable rates, except for the condenser. Priority in the improvement process of a component should be given to the turbine and the evaporator because of their higher values in the endogenous/avoidable destruction rates. For a better analysis, results for splitting the exergy destruction rate for the components in SRORC are shown in Figure 5. The highest unavoidable/endogenous exergy destruction rates belong to the evaporator in the system, with about a 54% of the total exergy destruction rate, which shows low potential in reducing the irreversibility for this component.

**Figure 5.** Splitting exergy destruction rates of components: (**a**) the evaporator, (**b**) turbine, (**c**) pump1, (**d**) pump2, (**e**) feed-water heater and (**f**) condenser in the SRORC system.

By referring to Table 10, it can be seen that, for DRORC, the endogenous exergy rate of loss is higher than the exogenous part for the evaporator and the turbine. This means that, in order to reduce the destruction rate, designers should focus on improving the efficiency of these components. Additionally, from these results, it is observed that there is a considerable contribution of the exergy rate of loss in pumps, feed-water heaters and condensers because of other components' performances in the systems. As it is mentioned above, the avoidable exergy destruction rate is an important part in reducing destruction. Table 10 shows that the avoidable exergy destruction rate is higher than the

unavoidable part for all components in DRORC, which indicates that a system has a great potential for reducing its total exergy destruction by using modern technologies or replacing components with new, efficient ones. Among components, turbines with 6.587 kW consist of the highest avoidable exergy destruction rate, which should be paid more attention to in designing. As it is shown in Table 10, the endogenous/avoidable exergy destruction rates for the evaporator, turbine and pump1 is higher than the endogenous/unavoidable destruction rates in DRORC. Modifications in these components and improving working conditions should be noticed by designers to reduce this part of the exergy destruction. Priority in improving the performance of components in DRORC should be given to the turbine, the evaporator, pump 1 and feed-water heater 2. As for the previous cycles, the results of the advanced exergy analysis for DRORC components are shown in Figure 6.

**Figure 6.** *Cont.*

**Figure 6.** Splitting exergy destruction rates of components: (**a**) the evaporator, (**b**) turbine, (**c**) pump1, (**d**) pump2, (**e**) pump3, (**f**) feed-water heater1, (**g**) feed-water heater 2 and (**h**) condenser in the DRORC system.

In addition, the total exergy destruction rate for different parts obtained from an advanced exergy analysis for the three cycles are shown in Figures 7–9. As indicated, the total avoidable exergy rate of loss in these three systems is higher than unavoidable part, which shows a good potential to reduce irreversibilities. Avoidable exergy rate of loss with about 78% of the total rate of loss in DRORC is the first to be noticed by designers. SRORC and BORC with 74% and 55%, respectively, are given the next priorities. Additionally, in SRORC and DRORC, the total endogenous/avoidable exergy destruction rates are about 47% and 45% of the total exergy destruction rate, respectively, which are higher than other three combination parts.

**Figure 7.** Total exergy destruction rate for the different parts in BORC.

**Figure 8.** Total exergy destruction rate for the different parts in single-regeneration ORC (SRORC).

**Figure 9.** Total exergy destruction rate for the different parts in DRORC.


*3.1. Quantification and Destination of Horticultural Postharvest Loss*

#### 3.1.1. Quantification of Loss

Supply chain one involved a total 137.41 t of harvestable product. Between the point-of-harvest and the retail point-of-sale, 55.34 t or 40.3% of harvestable product was removed from the commercial supply chain (Table 3). A total of 28.7% (39.4 t) of harvestable product was discarded in-field. Packing shed losses were 10.8% (10.56 t), based on the total volume of product entering the shed of 98.01 t (Table 3). Following grading, sorting and packing, a consignment of 4128 cartons was transported 392 km from the farm to the Rocklea Market, Brisbane. On arrival at the market, 7 h 20 min after leaving the farm, the consignment was moved into refrigerated storage, with no observed postharvest losses on arrival (Table 3). At 28 h, product was moved to the market floor where it was held at an ambient temperature for 3 h before being transported to the Morningside retail outlet, 14.2 km from the Rocklea Market. At 5 days of retail storage and display, 5.4% (5.38 t) of the product was deemed unsaleable by the retailer, with 100% of the loss going to landfill (Table 4).

Supply chain two involved a total 52.96 t of harvestable product. Between the point-of-production and the retail point-of-sale, 29.61 t or 55.9% of harvestable product was removed from the commercial supply chain (Table 3). A total of 47% (24.9 t) of harvestable product was discarded in-field. Packing shed losses were 14.1% (3.96 t), based on the total volume of product entering the shed of 28.05 t (Table 3). When averaged with two consecutive days', mean packing shed losses were 14.6%, based on the total volume of product entering the shed. A consignment of 300 cartons was transported 19.1 km from farm to a local wholesale/retail market in Bundaberg. On arrival at the market, 1.5 h after leaving the farm, the consignment was moved into refrigerated storage, with no observed postharvest losses on arrival (Table 3). At 17 h product was moved to a refrigerated display where it remained until it was sold, 12 h later. At 2.5 days of retail storage and display, the retailer deemed 2.4% (0.74 t) of the product unsaleable, with 100% of the loss going to landfill (Table 4).

Despite a lower total at-harvest yield, SC2 had proportionally higher postharvest losses in the field and packing shed when compared to SC1 (Table 3). The reason for this variability is thought to be due to differences in out-grading. Supply chain two did not include a third-grade product and harvesting cycles were more frequent, every one to two days, with less fruit on the vine. Supply chain one involved picking and packing all sizes and colours, with less frequent harvesting cycles, every third day, with more fruit on the vine. Differences in transport distance between SC1 (392 km) and SC2 (19 km) had no tangible impact, with no determined wholesale loss in either chain.

**Table 3.** Percent of actual and cumulative losses by location within the supply chain where postharvest loss was determined, and calculation of the percentageharvested product made available to the consumer.

 of

the total potential harvest (i.e., to include

point-of-harvest

 field loss). c Percent loss at each point along the supply chain relative to overall loss.

a Product (tomato) not harvested and left in the field or tilled back into the soil; b Product that was used as organic material on or below the surface of the land to enhance soil quality; c Product removed from the farm to an area of land or an excavated site specifically designed and built to receive wastes; d Diverting material from the food supply chain (directly or after processing) to animals.

#### 3.1.2. Destination of Losses

In SC1, of the total loss, 71.2% (39.4 t) of harvestable product was left in the field and not harvested, 17.2% (9.5 t) was disposed of via land application, 9.7% (5.39 t) became landfill, and 1.9% (1.05 t) was used as animal feed on an adjacent property (Table 4). For SC2, 84.1% (24.9 t) of harvestable product was left in the field, 12% (3.56 t) was disposed of via land application, 2.5% (0.75 t) became landfill, and 1.3% (0.4 t) was used as animal feed (Table 4). Based on the cumulative destination of loss for SC1 and SC2, the volume of product available for consumption was 59.7% and 44.1% respectively (Table 3).

#### *3.2. Drivers of Loss*