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Both electrical and thermal efficiencies combine in determining and evaluating the performance of a PV/T collector. In this study, two PV/T systems consisting of poly and monocrystalline PV panels were used, which are connected from the bottom by a heat exchanger consisting of a spiral tube through which a nanofluid circulates. In this study, a base fluid, water, and ethylene glycol were used, and iron oxide nanoparticles (nano-Fe2O3) were used as an additive. The mixing was carried out according to the highest specifications adopted by the researchers, and the thermophysical properties of the fluid were carefully examined. The prepared nanofluid properties showed a limited effect of the nanoparticles on the density and viscosity of the resulting fluid. As for the thermal conductivity, it increased by increasing the mass fraction added to reach 140% for the case of adding 2% of nano-Fe2O3. The results of the zeta voltage test showed that the supplied suspensions had high stability. When a mass fraction of 0.5% nano-Fe2O3 was added the zeta potential was 68 mV, while for the case of 2%, it reached 49 mV. Performance tests showed a significant increase in the efficiencies with increased mass flow rate. It was found when analyzing the performance of the two systems for nanofluid flow rates from 0.08 to 0.17 kg/s that there are slight differences between the monocrystalline, and polycrystalline systems operating in the spiral type of exchanger. As for the case of using monocrystalline PV the electrical, thermal, and total PV/T efficiencies with 2% added Fe2O3 ranged between 10% to 13.3%, 43–59%, and 59 to 72%, respectively, compared to a standalone PV system. In the case of using polycrystalline PV, the electrical, thermal, and total PV/T efficiencies ranged from 11% to 13.75%, 40.3% to 63%, and 55.5% to 77.65%, respectively, compared to the standalone PV system. It was found that the PV/T electrical exergy was between 45, and 64 W with thermal exergy ranged from 40 to 166 W, and total exergy from 85 to 280 W, in the case of using a monocrystalline panel. In the case of using polycrystalline, the PV/T electrical, thermal, and total exergy were between 45 and 66 W, 42–172 W, and 85–238 W, respectively. The results showed that both types of PV panels can be used in the harsh weather conditions of the city of Baghdad with acceptable, and efficient productivity.

AbstractNowadays, researchers are focusing on the methods of using recycled industrial/agricultural wastes as raw materials, which are not only economically but also environmentally useful. In the recent years, many scholars have conducted research on the rational use of rice husks (RHs) and found that RHs are rich in inorganic/organic components and used in combination with the certain building materials to produce new green composite building materials. This paper studies the method of using RH processed products and the sodium silicate solution (liquid glass) made from RH ash to produce cheap wood substitute composite materials, which can be improved the insulation performance of the wall greatly. Obtained results are determined by comparing with the properties of standard polymer composite materials such as particleboards, chipboards, and medium‐density fiberboards (MDF). The significance of the work is pointing out by solving the problem of recycling large‐tonnage agricultural waste and reproduce products with the consumer's value.

Abstract This study presents and evaluates the feasibility of a novel hybridization of modified Kalina cycle, reverse osmosis desalination, and low-temperature water electrolysis utilizing geothermal energy to yield power, distilled water, and hydrogen, respectively. The scientific impact of the current work has been improved considering the features of Sabalan flash-binary geothermal wells in Iran as a real model through a case study. In addition to designing a novel setup, the smart use of multi-heat recovery technique, modifying the base cycle, and utilizing a part of generated distilled water to produce hydrogen by the electrolyzer are the other structural originalities, distinguishing the current work from the previous studies. The suggested system is scrutinized via a parametric study and optimized based on a genetic algorithm. The parametric study demonstrated that the highest sensitivity of varying the performance criteria of the whole system is attributed to the change in flash tank pressure. Moreover, the multi-objective optimization led to achieving the exergy efficiency and trigeneration gain output ratio as 51.3% and 1.7 for the system, respectively. Furthermore, the system was able to produce 4795 kW of power, 5.3 kg/h of hydrogen, and 19.9 kg/s of distilled water.

Closed-loop supply chain networks are gaining research popularity due to environmental, economic and social concerns. Such networks are primarily designed to overcome carbon footprints and to retrieve end of life products from customers. This study considers a multi echelon closed-loop supply chain in the presence of machine disruption. A multi-objective model is presented to optimize the total cost, the total time and emissions in a closed-loop supply chain network. The aim is to analyze the trade-off between the objectives of cost, time, and emissions and how these decisions are impacted by the selection of different available machines. A number of solution approaches are tested on a case study from the tire industry. The results suggest the improved performance of the hybrid heuristic and the importance of controlling disruption in a closed-loop supply chain network. Furthermore, there is a trade-off between the different objective functions which can help the decision maker to choose a particular solution according to the preference of an organization. Finally, conclusion and future research avenues are provided.

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.

This research deals with the process of reviving urban heritage, especially in old cities after the war, due to their symbolic and moral values in society. By studying the reality of the city and its destructed heritage features, there was a local need to study the integrated strategies of the urban heritage revival process to reach indicators that are drawn from international experiences and the curricula and studies of international organizations (ICOMOS, World Bank, UN-Habitat, IOM) that interested in cultural heritage and to use these indicators in evaluating local projects in the center of the old city of Mosul which was chosen as a case study for this research, due to its historical and civilizational importance, which has contributed greatly to the formation of the city of Mosul through the ages, and as this city has witnessed deliberate sabotage of its urban heritage due to the terrorist acts witnessed before its liberation.

Abstract Mitigating the effects of environmental deterioration requires a focus on not just CO2 emissions from energy consumption, but also environmental pollution from industry sectors. To reach this goal, recent studies have extended ecological footprint (EF) analysis to identify the ecological drivers of various key industry sectors. The role of the phosphorus (P) industry on the EF within the environmental Kuznets curve (EKC) framework for China is the emphasis of this study. Autoregressive distributive lag (ARDL) as well as the impulse response function and robustness analysis were used to consider a time from 1985 to 2018. The study verifies the EKC hypothesis for China in both the long and the short run, and indispensable determinants are proposed to be included to assure the model’s fitness and robustness when conducting EF analysis of industry sectors. Energy consumption–based carbon emissions have been verified as the dominant contributor to EF, but P use and urbanization have a significant lagged positive influence on EF in the short run. P exports, in particular, have been highlighted as a critical driver of the EF of China’s P industry. The conducted frequency domain causality test reinforced the above findings and demonstrated bidirectional causality at different frequencies. This work suggests that formulating plausible P export policies to alleviate the conflict between the output of China’s P industry and the environmental sustainability of this industry are necessary. In this context, “multidisciplinary, multidimensional, and practical solutions” are most desirable for sustainable P management.

Confocal microscope imaging has become popular in biotechnology labs. Confocal imaging technology utilizes fluorescence optics, where laser light is focused onto a specific spot at a defined depth in the sample. A considerable number of images are produced regularly during the process of research. These images require methods of unbiased quantification to have meaningful analyses. Increasing efforts to tie reimbursement to outcomes will likely increase the need for objective data in analyzing confocal microscope images in the coming years. Utilizing visual quantification methods to quantify confocal images with naked human eyes is an essential but often underreported outcome measure due to the time required for manual counting and estimation. The current method (visual quantification methods) of image quantification is time-consuming and cumbersome, and manual measurement is imprecise because of the natural differences among human eyes’ abilities. Subsequently, objective outcome evaluation can obviate the drawbacks of the current methods and facilitate recording for documenting function and research purposes. To achieve a fast and valuable objective estimation of fluorescence in each image, an algorithm was designed based on machine vision techniques to extract the targeted objects in images that resulted from confocal images and then estimate the covered area to produce a percentage value similar to the outcome of the current method and is predicted to contribute to sustainable biotechnology image analyses by reducing time and labor consumption. The results show strong evidence that t-designed objective algorithm evaluations can replace the current method of manual and visual quantification methods to the extent that the Intraclass Correlation Coefficient (ICC) is 0.9.