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Saudi Arabia's path to carbon neutrality: Analysis of the role of Hajj pilgrimage, energy consumption, and economic growth
Get PDFSaudi Arabia's religious sites stimulate economic growth and create green jobs through sustainable tourism. Tourism expansion may raise carbon dioxide (CO2) emissions due to energy use. Thus, this article examines 1970–2019 time series data to assess how Hajj pilgrims, energy consumption, and economic growth affect Saudi Arabia's CO2 emissions. Unit root tests analyzed data stationarity, while the autoregressive distributed lag (ARDL) method investigated the variable nexus in the near and distant futures. A 1% boost in Hajj pilgrims and energy usage would raise CO2 emissions by 0.02% and 0.91% in the near term and 0.03% and 1.02% in the long term. By redeploying money into big carbon abatement projects, a 1% economic expansion reduces CO2 emissions by 0.04% in the near term and 0.05% in the long term. Multiple estimators, including the fully modified least squares (FMOLS), dynamic ordinary least squares (DOLS), and canonical cointegrating regression (CCR), were utilized to test the robustness of ARDL results. Pairwise Granger causality study analyzed the components' causal relationship. This article proposes Saudi Arabian carbon neutrality and green pilgrimage policies
Growing Glacial Lake Outburst Flood Risks in Ghizer District: A Karakoram Anomaly Region
Get PDFDue to climate change, the Northwesterner Gilgit Baltistan's, Ghizer district is highly susceptible to glacial lake outburst floods (GLOFs). Nearly 24 GLOFs have occurred in this area in the last ∼200 years, demonstrating the growing recurrent nature of these incidents. Taking this into account, the assessment of risks associated with GLOFs was investigated in this study. All regional glacial lakes were identified in the first phase, and changes between 2000 and 2023 were mapped using moderate-resolution satellite images (Landsat). To map built-up and agriculture areas, Landsat's lower resolution limited its use in such complex topography. Therefore Sentinel-2 data was used, and images from 2016 to 2023 were classified using a random forest (RF) classifier. A total of 617 glacial lakes covering ∼31.67 km2 of the area were mapped in 2023. Since 2000, ∼88 glacial lakes have appeared, showing an increasing trend in the number of lakes. In the second phase, categorization and susceptibility to GLOFs were assessed using multi-criteria decision analysis (MCDA). The grass GIS tool, r.avaflow, was used to generate GLOFs simulations based on friction, density, release area, travel time, and two travel time scenarios, i.e., 1800 and 3600 seconds, for four high-weighted glacial lakes. Results showed that the glacial lake near Darkut village, Yaseen Valley, poses a significant threat to downstream communities. In contrast, two other lakes in Gupis valley will have a moderate effect on the infrastructure and agriculture. The glacial lake of Punyal Valley poses no significant threat
Improving On-farm Energy Use Efficiency by Optimizing Machinery Operations and Management: A Review
Get PDFThe energy use and emissions from direct fossil fuel combustion on-farms to power farm machinery was critically reviewed. Approximately, 15% of agricultural production costs on-farm are energy-related. A potential solution to more sustainable energy use is a shift toward biofuels from renewable resources. The reduction of greenhouse gas emissions through the substitution of diesel oil with biodiesel depends on the feedstock, the inter-esterification process, the storage period, and ambient conditions. In modern tractors, increased fuel use efficiency (or reduced fuel consumption) has been achieved by power/load matching and the use of variable transmission. Engine management systems that are capable of continuously communicating with the engine and transmission to make appropriate adjustments based on inputs received from the tractor allow for quick and precise responses to changing conditions. As a result, maximum efficiency and productivity can be obtained from the tractor operating similarly to the traditional ‘gear-up and throttle-back’ methods of a proficient operator. The future for autonomous tractors is promising, though not new. Electric-powered tractors are near to commercialization or are already commercially available. Hybrid electric driven tractors present some advantages in terms of increased energy use efficiency and functionalities. Increased efficiency can lead to a reduction in diesel fuel consumption and hence, a concurrent decrease in CO2 emission. Where the local electricity supply has a low-carbon emission factor, this can also result in significant emission reductions. Small light-weight robotic equipment can potentially perform functions currently undertaken by tractor-drawn and other heavy equipment with high-fuel consumption, provided field operating capacity was not compromised. However, the size and weight limitations inherent in current harvesting and transport technology mean that soil compaction will still be a problem with robotic units. The robotic operation of medium-scale equipment within a precision-controlled traffic farming environment should offer more feasible and energy-efficient alternatives
Personal Values and Sustainable Consumerism: Performance Trends, Intellectual Structure, and Future Research Fronts
No full textExtant literature suggests that personal values influence consumers' choice, intention, and preference for sustainable and environment-friendly products. By adopting a replicative and systematic-cum-quantitative approach, this bibliometric review attempts to map the existing literature, which jointly studies personal values and sustainable consumption. Choosing from the bibliometric toolbox, we employed a diverse set of analyses such as performance analysis, co-authorship analysis, cartographic analysis, thematic mapping, and thematic evolution on a refined dataset comprising 419 peer-reviewed journal articles from 187 journals. The findings of this synthesis point to six distinct topical clusters to orchestrate and present the intellectual structure, along with identifying top contributors and constituents in the domain. We also map the themes and chart the evolution using the Sankey diagram on Bibliometrix-R. In addition, a three-dimensional TMC framework is adopted to outline avenues for future research. Furthermore, we suggest implications for theory and practice and elucidate the limitations
Graphene oxide-based nanofluidic membranes for reverse electrodialysis that generate electricity from salinity gradients
No full textA widely employed energy technology, known as reverse electrodialysis (RED), holds the promise of delivering clean and renewable electricity from water. This technology involves the interaction of two or more bodies of water with varying concentrations of salt ions. The movement of these ions across a membrane generates electricity. However, the efficiency of these systems faces a challenge due to membrane performance degradation over time, often caused by channel blockages. One potential solution to enhance system efficiency is the use of nanofluidic membranes. These specialized membranes offer high ion exchange capacity, abundant ion sources, and customizable channels with varying sizes and properties. Graphene oxide (GO)-based membranes have emerged as particularly promising candidates in this regard, garnering significant attention in recent literature. This work provides a comprehensive overview of the literature surrounding GO membranes and their applications in RED systems. It also highlights recent advancements in the utilization of GO membranes within these systems. Finally, it explores the potential of these membranes to play a pivotal role in electricity generation within RED systems
Assessing the Spatio-temporal Activity Pattern and Habitat Use of Bengal Tiger (Panthera tigris tigris) Across Three Forest Management Regimes in Nepal
No full textTigers (Panthera tigris) are an endangered species facing severe threats of population decline worldwide, and understanding their spatio-temporal activity patterns and habitat use in different forest management regimes is crucial for their conservation and management. We analyzed systematically collected camera trap data using occupancy modelling and kernel density functions to assess the spatio-temporal activity patterns of tigers across three forest management regimes in Nepal: Parsa National Park (PNP), its buffer zone, and adjoining national forests. Each of these three forest management regimes are differentially influenced by prey availability, habitat condition, and anthropogenic disturbances. We found that highest spatio-temporal overlap of tigers occurred with gaur (Bos gaurus) and spotted deer (Axis axis) in PNP. On the other hand, tigers highly overlap with wild boar (Sus scrofa), spotted deer (Axis axis) and barking deer (Muntiacus muntjac) in buffer zone and national forests. Mixed forest, grassland and riverine forest were the highly used habitat by the tigers, and domestic animals had a greater adverse impact on tigers than humans. Our findings showed that prey availability, habitat class and domestic animals significantly influence tiger presence, while, forests of every management regime are important for tiger conservation. Tiger conservation could be improved with greater collaboration and coordination between and across different forest management regimes
Causal determinism by plant host identity in arbuscular mycorrhizal fungal community assembly
No full text1. An assumption in ecology is that plant identity plays a central role in the assembly of root-colonising arbuscular mycorrhizal (AM) fungal communities. While numerous correlational studies support this notion, with evidence of host selectivity among fungal taxa and host-specific responses to different AM fungi, empirical demonstrations of host-driven AM fungal community assembly remain surprisingly limited.
2. We conducted a factorial experiment growing two globally significant crop species, wheat (Triticum aestivum) and sorghum (Sorghum bicolor), with a common pool of AM fungal species, or without AM fungi. We hypothesised strong differences in AM fungal community structure between the two species driven by strong habitat filtering. Plants were harvested at two time points in which we analysed the community structure of AM fungi in the roots, the phylogenetic diversity, and interactions with plant physiological responses.
3. As we expected, there were distinct trajectories in both the composition and phylogenetic diversity of AM fungal communities between the two host plants through time. However, the effect of habitat filtering during community assembly differed between the two species. In sorghum roots, AM fungal communities exhibited increased richness and became more phylogenetically clustered over time. This shift suggests that community assembly was primarily driven by habitat filtering, or selectivity, imposed by the host which was accompanied by significant increases in plant mycorrhizal growth (from 11.83% to 43.67%) and phosphorus responses (from −0.6% to 43.3%). In contrast, AM fungal communities in wheat displayed little change in diversity, remained phylogenetically unstructured, and provided minimal benefits to the host, indicating a more stochastic assembly process with a stronger influence of competitive interactions.
4. As the field looks to understand what determines the distribution of AM fungi and their community composition while simultaneously seeking to utilise AM fungi for ecosystem benefits, it is important to know the extent to which host identity can influence fungal assembly within plant roots. Our results provide empirical support of host-determinism in AM fungal community assembly and suggest that this determinism is associated with the growth and nutrient benefits provided by the symbiosis to plants
A qualitative analysis of the role of the Hospital in the Home registered nurse in Australia
No full textBackground
Healthcare and societal expectations change over time, with Hospital in the Home (HITH) registered nurses (RNs) increasing in community profile in Australian nursing domains. With increases in service demand and bed pressure creating an increased need for services outside the hospital environment, understanding of the role of the registered nurse working in HITH is needed.
Aim
This research aims to identify the role and function of the RNs’ experience in their day-to-day work in the HITH setting. Additionally, the research shares a content analysis of the position descriptions of participating HITH RNs to analyse key performance indicator inclusions and barriers in scope of practice for the registered nurse.
Method
Using an interpretive phenomenological approach and Gadamer’s method, 12 HITH RN participants from across Australia were engaged in in-depth interviews. Interviews provided HITH RNs the opportunity to share their experience of the role, and a contributing content analysis of position descriptions followed, providing a synopsis of key areas of commonality and difference.
Findings
Three key areas emerged: professionalism, knowledge, and responsiveness, with an identified mismatch between generalisations in scope of practice in the position descriptions and the shared experience of the HITH RN participants.
Discussion
The research identified shared challenges that exist in the day-to-day role and function of the HITH RN, determining that HITH RNs undertake complex roles, working with generic position descriptions, often absent of core components of autonomous practice, experience, and knowledge. Limitations exist in the scope of practice of the HITH RN resulting in delays in care where advanced practice could be applied
Refraining from exploiting disaster-hit communities, as an emerging principle of corporate social responsibility
No full textDisasters are more destructive and frequent in the age of
climate change, overpopulation, and neoliberal globalisation.
While the literature on disaster prevention and management proliferates, the role of for-profit corporations has
only recently started to be examined, usually through the
lens of corporate social responsibility (CSR)—the expectation that business will consider social and environmental
interests in its operations, in addition to profit. There is
lately much academic creativity in the CSR space pertaining
to why and how large corporations should contribute to
disaster recovery, but a conceptual red thread is missing.
This paper proposes that the unifying concept is the CSR
principle of refraining from exploiting disaster-hit communities. Indeed, CSR principles evolve in time, reflecting contemporary societal priorities. In a contractarian perspective on CSR, a rational community would nowadays have solid reasons to expect, in its social contract with business, the latter's commitment to decency when the former is devastated by earthquakes, pandemics, wars, and the like
Artificial Intelligence-Based Suicide Prevention and Prediction: A Systematic Review (2019-2023)
No full textSuicide is a major global public health concern, and the application of artificial intelligence (AI) methods, such as natural language processing (NLP), machine learning (ML), and deep learning (DL), has shown promise in advancing suicide prediction and prevention efforts. Recent advancements in AI – particularly NLP and DL have opened up new avenues of research in suicide prediction and prevention. While several papers have reviewed specific detection techniques like NLP or DL, there has been no recent study that acts as a one-stop-shop, providing a comprehensive overview of all AI-based studies in this field. In this work, we conduct a systematic literature review to identify relevant studies published between 2019 and 2023, resulting in the inclusion of 156 studies. We provide a comprehensive overview of the current state of research conducted on AI-driven suicide prevention and prediction, focusing on different data types and AI techniques employed. We discuss the benefits and challenges of these approaches and propose future research directions to improve the practical application of AI in suicide research. AI is highly capable of improving the accuracy and efficiency of risk assessment, enabling personalized interventions, and enhancing our understanding of risk and protective factors. Multidisciplinary approaches combining diverse data sources and AI methods can help identify individuals at risk by analyzing social media content, patient histories, and data from mobile devices, enabling timely intervention. However, challenges related to data privacy, algorithmic bias, model interpretability, and real-world implementation must be addressed to realize the full potential of these technologies. Future research should focus on integrating prediction and prevention strategies, harnessing multimodal data, and expanding the scope to include diverse populations. Collaboration across disciplines and stakeholders is essential to ensure that AI-driven suicide prevention and prediction efforts are ethical, culturally sensitive, and person-centered