Landscape Variables Research Articles

On the genesis and unique functions of zinc neuromodulation.

In addition to the essential structural and catalytic functions of zinc, evolution has adopted synaptic zinc as a neuromodulator. In the brain, synaptic zinc is released primarily from glutamatergic neurons, notably in the neocortex, hippocampus, amygdala, and auditory brainstem. In these brain areas, synaptic zinc is essential for neuronal and sensory processing fine-tuning. But what niche does zinc fill in neural signaling that other neuromodulators do not? Here, we discuss the evolutionary history of zinc as a signaling agent and its eventual adoption as an essential neuromodulator in the mammalian brain. We then attempt to describe the unique roles that zinc has carved out of the vast and diverse landscape of neuromodulators.

Spatial and temporal variability of movements among sympatric salmonids in an unfragmented inland watershed

AbstractObjectiveOur aim was to determine the movement patterns of three abundant salmonids—Brown Trout Salmo trutta, Mountain Whitefish Prosopium williamsoni, and Rainbow Trout Oncorhynchus mykiss—in the Smith River watershed of Montana.MethodsWe tagged 7172 fish with passive integrated transponder (PIT) tags, monitored their movements past 15 stationary PIT arrays over 4 years, and located tagged fish between arrays by conducting mobile surveys.ResultMovement patterns varied seasonally, among species, and among locations. Movement was greatest in the middle portion of the watershed, which included a pristine main‐stem canyon and lower reaches of major tributaries. Fish rarely left the canyon, but movement into the canyon from other regions was common. Mountain Whitefish were most likely to move, and Brown Trout were least likely to move. Most fish travelled less than 10 km, but some fish travelled over 100 km. Distinct movement patterns were not evident; rather, a continuous spectrum of movement behaviors was apparent. Movements by Mountain Whitefish and Rainbow Trout increased during their spawning periods. Movements peaked when mean daily water temperatures were between 11.3 and 17.1°C.ConclusionMovements were diverse and probably contributed to metapopulation dynamics, population resiliency, and species diversity. Fish movements along stream networks connect populations across diverse landscapes, and therefore, protecting and restoring stream connectivity along inland streams such as the Smith River is critical to maintaining productive fish assemblages.

Estimating erosion vulnerability within agricultural fields by downscaling the Daily Erosion Project (DEP): the OFEtool

AbstractAgriculture continues to be one of the most important sources of nonpoint source pollution to surface water bodies. Consequently, it is critical to identify and prioritize high‐contributing agricultural fields and sub‐field areas for reducing soil erosion and sediment delivery by implementing best management practices (BMPs). Current erosion risk assessment tools are either complex modelling approaches or rely on a simplified reality and generalized assumption. The Daily Erosion Project (DEP) is a daily estimator of precipitation, hillslope runoff, detachment and soil loss covering ~630 000 km2 across the Midwest United States. These estimations are reported daily and publicly at the hydrologic unit code 12 watershed resolution (approximately 100 km2). The main objective of this study was to develop a new tool (named Overland Flow Element tool [OFEtool]) that downscales the watershed scale of DEP to estimate average runoff and soil displacement within a field, helping to locate erosive hotspots at multiple scales. We also demonstrated the applicability of OFEtool in Bennet Creek‐Sugar Creek in East Central Iowa (the United States) and compared its results with other erosion vulnerability tools such as the Soil Vulnerability Index for Cultivated Cropland (SVI‐cc) and a GIS‐based Revised Universal Soil Loss Equation (RUSLE). The same erosion risk classes and ranges (low, moderate, moderately high and high) were implemented for all indexes. The advantages of the OFEtool compared to the SVI‐cc and RUSLE models are related to the use of an event‐based modelling approach, such as DEP, with updated soil loss estimates based on temporal changes in climate inputs and land use and management. The OFEtool uses a 6‐year time frame and a more up‐to‐date field inputs, while RUSLE provides a long‐term average and SVI‐cc only considers soil and topographical factors for risk assessment. Results indicated that the spatial distribution of vulnerable fields (and parts of the fields) followed a similar trend as other tested indices. However, the risk level associated with each tool differed (SVI‐cc > RUSLE > OFEtool). These differences could arise from intrinsic disparities within the tools (inputs, timing, processes considered, assumptions). While currently limited to the DEP domain and relying on the DEP random sampling scheme, further research is warranted to validate the tool at other Midwest locations and ensure it captures the watershed's landscape variability (combination of terrain, soil, land use and management) required to identifying critical erosion hotspots.

Technology Selection of High-Voltage Offshore Substations Based on Artificial Intelligence

This paper proposes an automated approach to the technology selection of High-Voltage Alternating Current (HVAC) Offshore Substations (OHVS) for the integration of Oil & Gas (O&G) production and Offshore Wind Farms (OWF) based on Artificial Intelligence (AI) techniques. Due to the complex regulatory landscape and project diversity, this is enacted via a cost decision-model which was developed based on Knowledge-Based Systems (KBS) and incorporated into an optioneering software named Transmission Optioneering Model (TOM). Equipped with an interactive dashboard, it uses detailed transmission and cost models, as well as a technological and commercial benchmarking of offshore projects to provide a standardized selection approach to OHVS design. By automating this process, the deployment of a technically sound and cost-effective connection in an interactive sandbox environment is streamlined. The decision-model takes as primary inputs the power rating requirements and the distance of the offshore target site and tests multiple voltage/rating configurations and associated costs. The output is then the most technically and economically efficient interconnection setup. Since the TOM process relies on equivalent models and on a broad range of different projects, it is manufacturer-agnostic and can be used for virtually any site as a method that ensures both energy transmission and economic efficiency.

Digital technologies and the future of health: aspirations, care and data

As projects seeking to provide digitized tools in health care and medicine are gaining ground at an accelerating pace, imaginations and incipient formations of digital health have acquired a new political urgency. These projects promise to revolutionize health care and medicine. However, efforts to institutionalize digital technologies in health are often fraught with difficulties that cause them to stall during implementation. We explore digital health technologies with respect to how they are aspired to, designed, used, and resisted. Our central argument is that the spread of digital health technologies has set in motion complex processes around the production, extraction, circulation, and economic valorization of data. These processes reconfigure multiple sets of relationships between people, between human bodies, and machines, and between actors in health care and the diverse institutional landscapes they inhabit. We explore these processes in three interrelated and geographically dispersed fields: (a) imaginaries of health and well-being; (b) new geographies of care; and (c) the datafication and (dis-)embodiment of health. This special issue brings into creative tension case studies from across geographical locations and thematic areas. Taken together, they draw attention to the question of how digital health technologies are situated in making and shaping the future of health care. By foregrounding anthropological perspectives, this Special Issue pushes the epistemological boundaries of the emerging scholarship on digital health technologies and global health. At the same time, it argues for a closer engagement of medical anthropologists and sociologists with processes of digitization in health.

Alternative Pathways in Astrobiology: Reviewing and Synthesizing Contingency and Non-Biomolecular Origins of Terrestrial and Extraterrestrial Life.

The pursuit of understanding the origins of life (OoL) on and off Earth and the search for extraterrestrial life (ET) are central aspects of astrobiology. Despite the considerable efforts in both areas, more novel and multifaceted approaches are needed to address these profound questions with greater detail and with certainty. The complexity of the chemical milieu within ancient geological environments presents a diverse landscape where biomolecules and non-biomolecules interact. This interaction could lead to life as we know it, dominated by biomolecules, or to alternative forms of life where non-biomolecules could play a pivotal role. Such alternative forms of life could be found beyond Earth, i.e., on exoplanets and the moons of Jupiter and Saturn. Challenging the notion that all life, including ET life, must use the same building blocks as life on Earth, the concept of contingency-when expanded beyond its macroevolution interpretation-suggests that non-biomolecules may have played essential roles at the OoL. Here, we review the possible role of contingency and non-biomolecules at the OoL and synthesize a conceptual model formally linking contingency with non-biomolecular OoL theories. This model emphasizes the significance of considering the role of non-biomolecules both at the OoL on Earth or beyond, as well as their potential as agnostic biosignatures indicative of ET Life.

Paragliding Events & Festivals: Catalyzing Aero-Sports Tourism Development in India

India’s diverse geographical landscape and rich cultural history make it an ideal destination for paragliding events and festivals, highlighting its potential for aero sports tourism in the world. India has been the host of the Paragliding World Cup, and Paragliding Accuracy Pre-World Cup integrating with various cultural events and festivals. Paragliding destinations of Himachal Pradesh, Uttarakhand, Maharashtra, and Kerala have gained popularity among the paragliding community worldwide by hosting paragliding “events & festivals”. This study has evaluated the potential of the paragliding destination of various states in India and the role of paragliding “events and festivals” in aero-sports tourism development in India. After analyzing the data from the secondary sources found the various challenges for aero sports tourism in India. Managerial implication has underlined the importance of strategic planning required by state tourism departments, paragliding associations, and local communities to incorporate music and dance festivals with paragliding events. Skill development and training programs for local youth, development of the infrastructure, sustainable environmental practices, and effective marketing and promotion will all contribute to the growth of paragliding tourism in India. Findings highlight the incorporation of local culture (dance music & food) into paragliding festivals, which promotes India’s rich heritage. Organizing events and festivals at Aero sports destinations attract tourists as well as benefits the local economy, resulting in job growth. Sustainable environment-friendly practices and community participation can reduce environmental damage and it will promote a sense of ownership among locals. The results underline the importance of empowering local communities to benefit from paragliding tourism development. Paragliding festivals not only paragliding pilots and tourists, but they also serve as an effective destination marketing tool, promoting lesser-known destinations and contributing to India's long-term Aero-sports tourism development goals.

Response of Surface Runoff Evolution to Landscape Patterns in Karst Areas: A Case Study of Yun–Gui Plateau

To control and improve the phenomena of rocky desertification and soil erosion in karst landform areas, which are caused by a series of human factors that include social and economic development and human activities, China has successively introduced many policies, resulting in spatial and temporal changes in the landscape pattern of the southern karst area. In this study, land use transfer intensity maps, the grid method, the sample line method, the semivariogram method, and the Spearman analysis method are used to explore the spatial and temporal evolutions in surface runoff as responses to landscape pattern and policy factors in karst landform area. Therefore, this study provides theoretical and policy support for improving the regional landscape structure, optimizing the landscape layout, introducing regional policies, reducing surface runoff, and alleviating soil erosion. The results show that the best scale for the study of landscape patterns in the southern karst area is 3000 m. Forests are the land type that make up the highest proportion in the southern karst area, and they have the strongest interception capacity for surface runoff. The spatial and temporal distributions of the surface runoff are significantly different, and urban expansion has led to an increase in impervious runoff year over year. Runoff is positively correlated with the Shannon diversity index (SHDI), patch density (PD), and landscape shape index (LSI). The stronger the landscape heterogeneity, the more runoff. DIVISION is positively correlated with forest runoff and negatively correlated with other land types. The higher is the degree of aggregation of impervious patches, the higher the regional runoff rate. The more dispersed the forest patches are, the smaller the area proportion, and the greater the runoff. In addition, policy factors have a significant impact on surface runoff.

Bibliometric analysis of global research in palliative care for cervical cancer.

The present study aims to conduct a comprehensive bibliometric analysis of global research in palliative care for cervical cancer, providing insights into publication trends, authorship patterns, influential journals, and thematic concentrations. A bibliometric analysis approach was employed using metadata extracted from Scopus spanning 2000-2023. The search utilized main terms related to cervical cancer and palliative care. Data analysis and visualization were performed using the Bibliometrix R Package's web app Biblioshiny and VOSviewer software. The study identified 2,492 publications on palliative care for cervical cancer, with a notable peak in 2021. The analysis revealed a diverse publication landscape, encompassing primarily articles. Citation analysis showed a staggering 63,994 citations. The most relevant journals were The Lancet Oncology, Gynecologic Oncology, and International Journal of Gynecological Cancer. The study also highlighted influential authors, institutions, and countries, with Harvard University, the University of Toronto, and the University of Texas MD Anderson Cancer Center leading in publications. The findings reflected a growing interest in palliative care for cervical cancer, marked by increasing publications over the years. However, the analysis indicated limited international collaborations, with research efforts concentrated in high-income countries. Thematic areas include surgery, palliative care, chemotherapy, radiotherapy, and quality of life. Thus, further collaborations and research in developing countries are needed. This bibliometric analysis showcased a comprehensive overview of the global research landscape on palliative care for cervical cancer. The study identified trends, key contributors, and thematic concentrations, offering valuable insights for future research directions and enhancing palliative care services. Addressing the identified gaps, fostering international collaborations, and directing research efforts toward developing countries can contribute to the advancement of palliative care for cervical cancer globally.

Batteries for electric vehicles: Technical advancements, environmental challenges, and market perspectives

AbstractThe rapid evolution of electric vehicles (EVs) highlights the critical role of battery technology in promoting sustainable transportation. This review offers a comprehensive introduction to the diverse landscape of batteries for EVs. In particular, it examines the impressive array of available battery technologies, focusing on the predominance of lithium‐based batteries, such as lithium‐ion and lithium‐metal variants. Additionally, it explores battery technologies beyond lithium (“post‐lithium”), including aluminum, sodium, and magnesium batteries. The potential of solid‐state batteries is also discussed, along with the current status of various battery types in EV applications. The review further addresses end‐of‐life treatment strategies for EV batteries, including reuse, remanufacturing, and recycling, which are essential for mitigating the environmental impact of batteries and ensuring sustainable lifecycle management. Finally, market perspectives and potential future research directions for battery technologies in EVs are also discussed.

Perceptions of Diversity, Equity, Inclusion, and Anti-Racism Among Pharmacy Faculty by Racial and Ethnic Identity

ObjectiveTo compare perceptions of underrepresented minorities (URM), non-URM people of color (POC), and nonminoritized pharmacy faculty in academia in relation to workplace diversity, equity, inclusion, and anti-racism (DEIA) landscape in the United States. MethodsThis study utilized the DEIA Faculty Perceptions of College Climate (FPCC) scale, which was developed and validated by the authors. The FPCC scale was used to investigate perceptions of pharmacy faculty from the American Association of Colleges of Pharmacy membership directory regarding DEIA within their respective academic pharmacy institutions. Demographic differences were examined using a Pearson chi-square test, while response disparities in FPCC questions were analyzed with a one-way ANOVA. ResultsA total of 846 respondents met the inclusion criteria for the study and were included in the analysis. Results indicate disparities in perceptions within all 4 DEIA domains of the FPCC survey among the 3 demographic groups. ConclusionThis study uncovers significant differences in how pharmacy faculty perceive DEIA within pharmacy education, with nonminoritized faculty expressing more positive views compared to their URM and non-URM counterparts. These results emphasize the need for focused interventions and institutional support to bridge DEIA disparities, emphasizing the importance of fostering an inclusive academic environment to enhance faculty well-being and empower the pharmacy profession to meet diverse needs more effectively.

Performance enhancement of deep learning based solutions for pharyngeal airway space segmentation on MRI scans

The automatic segmentation of the pharyngeal airway space has many potential medical use, one of which is to help facilitate the creation of the Tubingen Palatal Plate. Therefore, it is of great importance to understand which methods are suitable for this task. Here, neural network based solutions available in the literature are compared to find the best methods. Neural network models were chosen to encompass a diverse landscape. Some models were taken from the general semantic segmentation literature, while others were taken from the medical or pharyngeal airway space segmentation literature. Some models are convolutional neural networks, while others are transformer-based model or a mix of both convolutional and transformer-based model. These models include 2d/3d U-Net, Deeplabv3, YOLOv8, Swinv2 UNETR, SegFormer, and 3D MRU-Net. Furthermore, additional strategies to enhance performance were also considered. These strategies consisted of training two separate networks in multiple stages as well leveraging unlabeled data to pretrain the neural networks before fine-tuning them on the labeled data. It was found that out of all the models considered here, the 2d U-Net performed the best achieving an average dice score of 0.9180 ± 0.0111. Out of all the strategies to enhance performance, only two strategies improve the actual results but only by a small margin. Therefore, these strategies can be consider if a small increase in performance is desired from the 2d U-Net at the expense of computational resource.

Complex stands in forested tropical landscapes harbor more endemic biodiversity and ecosystem functions

Transformation of forests into agricultural lands threatens biodiversity and ecosystem functions globally. In the biodiversity hotspot Madagascar, key ecosystem functions along with highly endemic flora and fauna are under threat. Comprehensive studies identifying determinants of biodiversity and ecosystem function losses are lacking, with no studies accounting for endemic species richness across multiple taxa. We assess how plot-scale stand structural attributes (basal area, leaf area index, diameter diversity, and tree species richness) and landscape-scale forest cover influence biodiversity (species richness of butterflies, ants, birds, reptiles, amphibians, herbaceous plants, and multidiversity) and ecosystem functions (soil organic carbon, predation rate, acoustic diversity, and multifunctionality) in the tropical mosaic landscape of northeastern Madagascar. Complexly structured stands with a larger basal area and/or a higher tree species richness promoted greater endemic multidiversity (R² = 0.70), soil organic carbon, and acoustic diversity. However, our models did not indicate significant explanatory variables for multidiversity (R² = 0.25) and multifunctionality (R² = 0.43). Landscape-scale forest cover significantly favored endemic bird species richness. Our findings highlight that a simplified stand structure, resulting from land-use change, substantially reduces endemic biodiversity and ecosystem functions in this historically forested region. Conservation actions should aim at maintaining complex stand structure in forests and agroforests, while restoration interventions should focus on re-building such structures.

From Near-Sensor to In-Sensor: A State-of-the-Art Review of Embedded AI Vision Systems.

In modern cyber-physical systems, the integration of AI into vision pipelines is now a standard practice for applications ranging from autonomous vehicles to mobile devices. Traditional AI integration often relies on cloud-based processing, which faces challenges such as data access bottlenecks, increased latency, and high power consumption. This article reviews embedded AI vision systems, examining the diverse landscape of near-sensor and in-sensor processing architectures that incorporate convolutional neural networks. We begin with a comprehensive analysis of the critical characteristics and metrics that define the performance of AI-integrated vision systems. These include sensor resolution, frame rate, data bandwidth, computational throughput, latency, power efficiency, and overall system scalability. Understanding these metrics provides a foundation for evaluating how different embedded processing architectures impact the entire vision pipeline, from image capture to AI inference. Our analysis delves into near-sensor systems that leverage dedicated hardware accelerators and commercially available components to efficiently process data close to their source, minimizing data transfer overhead and latency. These systems offer a balance between flexibility and performance, allowing for real-time processing in constrained environments. In addition, we explore in-sensor processing solutions that integrate computational capabilities directly into the sensor. This approach addresses the rigorous demand constraints of embedded applications by significantly reducing data movement and power consumption while also enabling in-sensor feature extraction, pre-processing, and CNN inference. By comparing these approaches, we identify trade-offs related to flexibility, power consumption, and computational performance. Ultimately, this article provides insights into the evolving landscape of embedded AI vision systems and suggests new research directions for the development of next-generation machine vision systems.

Nutrition and Physical Activity Education in Medical School: A Narrative Review.

This review explores the diverse landscape of integrating nutrition and physical activity education into medical school curricula, focusing on the imperative role of physicians in promoting health through lifestyle changes. By examining global medical education structures, we uncovered disparities in nutrition and physical activity training, and highlighted the need for a shared framework to address international and regional challenges. Despite acknowledging the importance of both nutrition and physical activity, studies have consistently uncovered deficiencies in medical school curricula, especially in skills related to providing lifestyle advice and behavioral counseling. Survey studies among medical students have illuminated various perceptions and knowledge gaps, emphasizing the need for more comprehensive and mandatory nutrition and physical activity training. While acknowledging progress, challenges, such as time constraints, resource availability, and faculty expertise, persist. Integrating lifestyle education results in resistance, a demand for strategic communication, and faculty buy-ins. These findings underscore the importance of a holistic approach that balances theoretical knowledge, practical skills, and confidence that medical students need to promote effective nutrition and physical activity in healthcare.

Linguistic Diversity in Southeast Asia and Its Impact on Multilingual Education

The Southeast Asian region exhibits a rich and diverse linguistic landscape due to its diversity. This paper aims to explore the linguistic diversity of Southeast Asia and its impact on multilingual education. By providing an overview of the main languages in Southeast Asian countries, this paper analyzes the challenges language differences pose to society, culture, and education systems. In terms of multilingual education, the paper studies various strategies adopted by Southeast Asian countries and evaluates the effectiveness of these strategies in preserving and promoting linguistic diversity. Finally, the paper presents several suggestions aimed at strengthening the multilingual education system in Southeast Asia to better address the challenges posed by linguistic diversity.

Managing the Historic Burden of Kernicterus Mortality in India.

Prevention of neonatal bilirubin injury exemplifies success of systems approach to avert adverse neonatal and childhood outcomes that rely on strategies including prenatal identification of Rhesus sensitization, universal maternal blood typing, risk assessment for neonatal extreme hyperbilirubinemia (EHB), unfettered access to safe, effective phototherapy, and application of patient safety principles. India's diverse landscape suggests varied real-time experiences of neonatal hyperbilirubinemia and consequent infant mortality rates (IMR). Utilizing Global Burden of Disease (GBD) database, the authors examined national and subnational trends, infant mortality timing, and the disease burden from hemolytic and perinatal jaundice over 30 y (1999 to 2019). They also assessed the correlation of EHB-IMR with socio-demographic index and health expenditure per capita, estimating economic losses from EHB-related infant mortality to guide policy decisions at national and state domains. From 1990 to 2019, India delivered 811,078,415 livebirths of which, 1,189,856 infant deaths were due to EHB. EHB-related deaths decreased from 57,773 in 1990 to 19,664 in 2019, a 60% reduction vs. 40% in overall IMR. Early (0-6 d), late (7-27 d), and post-neonatal (28-364 d) deaths accounted for 61%, 34%, and 5% of mortality, respectively. Uttar Pradesh and Bihar contributed to 38% of all EHB deaths. Economic analysis estimate losses between US $7.2 and 11.7 billion for the year 2019 secondary to EHB-related mortality. The present analysis reveals consistent declines across all states to reach current EHB-IMR of 0.8 per 1,000 live-births in India by 2019. Significant economic impact of lost human productivity highlight ongoing need for targeted life-saving public health strategies.

The Hidden Threat: Analysis of Linux Rootkit Techniques and Limitations of Current Detection Tools

This paper addresses the significant threat posed by rootkits as part of the diverse malware landscape of today. Rootkits enable an attacker to regain access to an already comprised system at root-level making their prompt identification and removal crucial. However, rootkits implement advanced stealth features, enabling them to evade detection by conventional measures during analysis. Consequently, analysts generally rely on customized tools to detect the presence of a rootkit. However, our research highlights significant deficits in the tools available for the detection of rootkits on the Linux operating system, which is frequently encountered in investigations of server environments. Recognizing the need for improved awareness and capabilities among investigators, we conducted an in-depth analysis of 21 distinct Linux rootkits allowing us to dive into their techniques and features. Furthermore, we critically assessed the effectiveness of standard detection tools, revealing their limitations. Based on these insights, we propose best practices for investigators to effectively identify and detect signs of rootkit infections. Additionally, we provide a repository of indicators of compromise we extracted during our analyses to facilitate the detection of the analyzed rootkits on compromised systems along with a utility to detect rootkits via hidden files on a live system.

Wildland Firefighter Estimated Ground Evacuation Time Modeling to Support Risk-Informed Decision-Making

Wildland firefighters often work in remote settings with multiple hazards that can cause life-threatening injuries. Prompt access to medical care is key to reducing injury consequences. For the last decade, a spatial model of wildland firefighter estimated ground evacuation time (GET) has been used when developing operational response strategies in the contiguous United States (CONUS). This paper describes our updated and improved GET model and the resulting decision support spatial data representing the estimated time to evacuate to a hospital from anywhere within the CONUS using ground transportation only. The new GET model leverages updated input datasets and has improved off-road travel time estimation methods that incorporate the latest science on how terrain slope influences pedestrian travel rates. It also accounts for a novel set of landscape variables not previously considered, including minor roads and trails, streams, woody debris, cliffs, and an improved handling of shrub cover. When compared to a set of recent safety incidents, the reported evacuation times were correlated with the model predictions. The spatial patterns of GET from the new model are similar to the old product; however, we found that, on average, the new version of GET yields slightly faster evacuation times, but with regional variation in this trend.

Sectoral carbon emission prediction and spatial modeling framework: A local climate zone-based case study of the Guangdong-Hong Kong-Macao Greater Bay Area

Understanding the spatio-temporal pattern of carbon emission (CE) is prerequisite for formulating carbon reduction policies. Previous studies emphasized quantitative analysis of CE inventory while ignoring sectoral spatial distribution. This study fills this gap by developing a framework for coupling the CE quantitative prediction model with the sectoral CE spatial model based on the Long-range Energy Alternatives Planning (LEAP) model, spatial proxy data and local climate zone (LCZ). The framework's sectoral CE results reveal a great varied landscape within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), one of the leading bay areas in the world with rapid urbanization and emphasis on low-carbon development, under four carbon reduction scenarios. By 2060, the CN3 scenario that considers both energy-supply and consumption sides, predicts a drastic emission cut to 35.76 million tons, just 10 % of the business as usual (BAU) scenario's forecast, mainly from transportation (29.45 million tons) and industry (9.34 million tons) sectors. Besides, compared with the common CE spatial products, the spatial simulation results of sectoral CE in our framework present detailed spatial differences at the jurisdictional level. The findings are conducive for governments to formulate accurate CE reduction and optimization strategies of the cities towards to the 2060 carbon neutrality.