• Energy Research
• 13. Climate action close
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A key determinant and outcome of successful environmental education is ‘pro-environmental behavior’, i.e., behavior that involves conscious action to mitigate adverse environmental impacts at personal or community level, e.g., reducing resource consumption and waste generation, avoiding toxic substances, and organizing community awareness initiatives. However, some theorists have sought to move away from rationalist models of behavioral modification, towards holistic pedagogical initiatives that seek to develop action competence. In light of the global push towards achievement of the Sustainable Development Goals (SDGs), emerging evidence suggests that education initiatives should foster action competence so students may be equipped to contribute to sustainable development as part of their education. The UNESCO Education for Sustainable Development (ESD) Roadmap 2030 has also identified key priority areas to strengthen ESD in formal curricula. This article reports two informal environmental education initiatives for promoting action competence and pro-environmental behaviors in school-aged children. The authors recommend that formal education settings (e.g., schools) should incorporate self-directed, free-choice project-based learning to augment environmental education programs and promote students’ action competence for contribution to attainment of SDGs. To this end, we propose a Free-Choice Project-based Learning for Action Competence in Sustainable Development (ACiSD) Curriculum, comprising six implementation dimensions, namely: (1) project duration and teaming arrangements, (2) topic selection, (3) student support, (4) teacher support, (5) learning environments, and (6) digital access and equity. For each implementation dimension, we recommend action steps to help educators implement this curriculum in their own educational settings, with the aid of an illustrative worked example.

Room occupancy prediction based on indoor environmental quality may be the breakthrough to ensure energy efficiency and establish an interior ambience tailored to each user. Identifying whether temperature, humidity, lighting, and CO2 levels may be used as efficient predictors of room occupancy accuracy is needed to help designers better utilize the readings and data collected in order to improve interior design, in an effort to better suit users. It also aims to help in energy efficiency and saving in an ever-increasing energy crisis and dangerous levels of climate change. This paper evaluated the accuracy of room occupancy recognition using a dataset with diverse amounts of light, CO2, and humidity. As classification algorithms, K-nearest neighbors (KNN), hybrid Adam optimizer–artificial neural network–back-propagation network (AO–ANN (BP)), and decision trees (DT) were used. Furthermore, this research is based on machine learning interpretability methodologies. Shapley additive explanations (SHAP) improve interpretability by estimating the significance values for each feature for classifiers applied. The results indicate that the KNN performs better than the DT and AO-ANN (BP) classification models have 99.5%. Though the two classifiers are designed to evaluate variations in interpretations, we must ensure that they have accurate detection. The results show that SHAP provides successful implementation following these metrics, with differences detected amongst classifier models that support the assumption that model complexity plays a significant role when predictability is taken into account.

Entrepreneurship may be regarded as the mechanism of change towards sustainability. Any entrepreneur that seeks to start a new venture in an emerging industry will face resource and time constraints. The question we raise here is how the entrepreneur should prioritize use of time and resources to increase likeliness of success. To address this question we depart from a theoretical perspective of entrepreneurship seen as judgment, and bridges it over to entrepreneurship seen as co-creation. In other words, we combine the subjective with the intersubjective, and explore the effects of the actions successful green technology entrepreneurs in the emerging offshore renewable energy industry make in building their new ventures in nascent markets. Inspired by earlier studies on market entry, combined with new ways to understand new venture emergence, we find that independent entrepreneurs benefit from leapfrogging typical stages in the technology development process and rather devote time and efforts on resource acquisition. We also find that the most important value-capturing, decision-making heuristics are those related to “hybrid governance”. We discuss implications for theory, practice, and policy.

A reverse osmosis system driven by photovoltaic energy is an eco-friendly and sustainable way to produce freshwater in rural areas without connection to a power grid and with available brackish water sources. This paper describes a project where a photovoltaic-driven low-pressure reverse osmosis system (LPRO-PV) was designed, tested under laboratory conditions, and installed in Samalayuca, Chihuahua, Mexico, to evaluate the technical feasibility and social impact of this technology. The LPRO-PV system was tested with synthetic water with a salinity of 2921 ± 62.3 mg/L; the maximum freshwater volume produced was 1.8 ± 0.06 m3/day with a salinity value of 91 ± 1.9 mg/L. The LPRO-PV system satisfied the basic freshwater requirements for a local family of three members for one year, including the mobility-restriction period due to the COVID-19 pandemic. The social evaluation analysis reflects the importance of considering the technical aspects derived from the experimental tests, as well as the users’ perception of the performance and operation of the system. As a result of the implementation of this technology and the benefits described by the users, they committed to the maintenance activities required for the LPRO-PV system’s operation. This technology has great potential to produce fresh water in arid and isolated regions with high-salinity groundwater sources, thus fulfilling the human right to safe and clean drinking water.

This paper discusses the effect of various climatic conditions that pertain to passive design measurements and their relationships with building configurations to improve indoor thermal comfort based on the different climate zones in Egypt to support Egypt’s sustainability agenda 2030. We find the most appropriate design settings that can increase the indoor thermal comfort, such as building orientation and shape. These settings can be modeled using DesignBuilder software combined with Egyptian meteorological data. This software is used accompanied by computational fluid dynamics to numerically assess the outcomes of different changes, by simulating indoor climate condition factors such as wind speed and temperature. Natural ventilation simulations were performed for four different shapes to create comprehensive dataset scenarios covering a general range of shapes and orientations. Seven scenarios were optimized to put forward a series of building bioclimatic design approaches for the different characteristic regions. The results indicated that the temperature decreased by about 3.2%, and the air velocity increased within the study domain by 200% in the best and the worst cases, respectively, of the four different shapes. The results of the study gave evidence that the configuration of buildings, direction, and wind speed are very important factors for defining the natural ventilation within these domains to support the green building concept and the sustainable design for a better lifestyle.

The environmental control and management of municipal solid waste (MSW) dumping sites is considered one of the sensitive challenges faced by executive municipalities. This is especially true in Makkah due to the gradual increase in urban population and visitors, with an overall MSW generation of about one million tons per year. Consequently, the geo-environmental evaluation of the Kaakia dumping site shed light on the potential environmental threats, in terms of ambient air quality levels and meteorological parameters, in addition to geophysical inspection. An air quality survey discussed the major trends of ambient air pollutants (SO2, NO2, CO, O3, CH4, and PM10) downwind from the Kaakia dumping site. It indicated the presence of a significant increase in sporadic plumes of Methane concentration. The maximum hourly averages ranged between 22.9–26.6 µg/m3 for SO2, 44.4–64.0 µg/m3 for NO2, 0.86–1.38 mg/m3 for CO, 150.2–158.8 µg/m3 for O3, 5.09–5.9 ppm for CH4, and 955–994 µg/m3 for PM10. The ground penetrating radar (GPR) geophysical survey indicated the subsurface sequence of three geological layers, as confirmed by nearby bores of the investigated site: (1) a surface layer formed of alluvial sediments of sand, which were 2.5–3.1 m thick; (2) a second layer represented by sand and gravel, with a thickness of 4.6–6.5 m; and (3) a third layer equivalent to saturated alluvial sediments mixed with rock fragments that extended to a depth of 13 m. The signals of the GPR were attenuated at the base of the conducted profiles due to the percolation of generated leachate to the subsurface sequence and contaminated groundwater aquifer.

The university is an essential participant in education, a key place where societal change processes are developed. So, it must be a place to bring up current challenges and social requirements. That is the reason why it holds the responsibility to assure the creation of knowledge, skills, attitudes, and values in the students to achieve an effective solution to environmental issues. The objective of this research was the assessment of the attitudes, knowledge, and pro-environmental behavior in university students from different faculties, studies, and degrees, as well as their influence in this group. The results show that most of the students have previous concepts of environment, and they consider that a good environmental education is necessary to solve the environmental issues that they have around. This proves that key factors in attitudes become essential elements for changing them. The differences made by gender and studies in several fields in attitudes (cognitive and emotional levels) are also confirmed.

On 25 September 2015, the member states of the United Nations approved an initiative in New York called “Transforming our world: the 2030 Agenda for Sustainable Development” [...]

Accurate health prognostics of lithium-ion battery packs play a crucial role in timely maintenance and avoiding potential safety accidents in energy storage. To rapidly evaluate the health of newly developed battery packs, a method for predicting the future health of the battery pack using the aging data of the battery cells for their entire lifecycles and with the early cycling data of the battery pack is proposed. Firstly, health indicators (HIs) are extracted from the experimental data, and high correlations between the extracted HIs and the capacity are verified by the Pearson correlation analysis method. To predict the future health of the battery pack based on the HIs, degradation models of HIs are constructed by using an exponential function, long short-term memory network, and their weighted fusion. The future HIs of the battery pack are predicted according to the fusion degradation model. Then, based on the Gaussian process regression algorithm and battery pack data, a data-driven model is constructed to predict the health of the battery pack. Finally, the proposed method is validated with a series-connected battery pack with fifteen 100 Ah lithium iron phosphate battery cells. The mean absolute error and root mean square error of the health prediction of the battery pack are 7.17% and 7.81%, respectively, indicating that the proposed method has satisfactory accuracy.

In this work, the impact of exogenous aerobic bacteria mixture (EABM) on municipal solid waste (MSW) is well evaluated in the following aspects: biogas production, leachate analysis, organic waste degradation, EABM population, and the composition of microbial communities. The study was designed and performed as follows: the control bioreactor (R1) was filled up with MSW and the culture medium of EABM and the experimental bioreactor (R2) was filled up with MSW and EABM. The data suggests that the composition of microbial communities (bacterial and methanogenic) in R1 and R2 were similar at day 0, while the addition of EABM in R2 led to a differential abundance of Bacillus cereus, Bacillus subtilis, Staphylococcus saprophyticus, Staphlyoccus xylosus, and Pantoea agglomerans in two bioreactors. The population of exogenous aerobic bacteria in R2 greatly increased during hydrolysis and acidogenesis stages, and subsequently increased the degradation of volatile solid (VS), protein, lipid, and lignin by 59.25%, 25.68%, 60.47%, and 197.62%, respectively, compared to R1. The duration of hydrolysis and acidogenesis in R2 was 33.33% shorter than that in R1. At the end of the study, the accumulative methane yield in R2 (494.4 L) was almost three times more than that in R1 (187.4 L). In addition, the abundance of acetoclasic methanogens increased at acetogenesis and methanogenesis stages in both bioreactors, which indicates that acetoclasic methanogens (especially Methanoseata) could contribute to methane production. This study demonstrates that EABM can accelerate organic waste degradation to promote MSW biodegradation and methane production. Moreover, the operational parameters helped EABM to generate 20.85% more in accumulative methane yield. With a better understanding of how EABM affects MSW and the composition of bacterial community, this study offers a potential practical approach to MSW disposal and cleaner energy generation worldwide.