Search Results (48)

Solid waste for incineration and wastewater from the country’s largest city, Mexico City (CDMX), is transported to the southern region of Valle del Mezquital (MV). This area also hosts an oil refinery, a thermoelectric plant (PEMEX-CFE), cement factories, industrial corridors, and mining operations, all of which harm environmental and public health. From a Political Ecology (PE) perspective, we examine the mechanisms of accumulation, emphasizing the allocation of property titles and the extraction of rent as an environmental reservoir. We also explore the power of socio-environmental movements to provide a comprehensive understanding of environmental conflict. Based on economic power structures, we identify a geopolitical configuration that deepens the spatial divisions between labor in the MV and consumption in CDMX, exacerbating health disparities. We conclude that an unequal geography has been built that has produced capitalist and rentier landowners who are exempt from the externalities that have produced a sacrifice zone. The Mexican State is a key stakeholder, collaborating with the industrial elite in both legal and illegal spheres. Within this sacrifice zone, the inhabitants of the MV have resisted pollution and industrial accidents for over 50 years. Despite publicizing their struggle internationally and collaborating with academics, members of the movement have been assassinated. Full article

This paper contributes to research on the geography of cultural sectors by exploring cultural consumption habits from a spatial perspective. The study introduces a novel method to the study of cultural consumption spatial patterns by using human mobility data (GPS) to overcome the lack of traditional data on cultural consumption. The results reveal the emergence of spatial inequalities both in the distribution of cultural amenities and in individual consumption behaviours. It shows that proximity to cultural amenities describes individual consumption patterns through a negative power law function, and that this relation is stronger for individuals averse to cultural consumption. Full article

This study demonstrates that small-scale liquefied natural gas (SS LNG) is a viable and cost-effective alternative to High-Speed Diesel (HSD) for power generation in remote areas of Indonesia. An integrated supply chain model is developed to optimize total costs based on LNG inventory levels. The model minimizes transportation costs from supply depots to demand points and handling costs at receiving terminals, which utilize Floating Storage Regasification Units (FSRUs). LNG distribution is optimized using a Multi-Depot Capacitated Vehicle Routing Problem (MDCVRP), formulated as a Mixed Integer Linear Programming (MILP) problem to reduce fuel consumption, CO₂ emissions, and vessel rental expenses. The novelty of this research lies in its integrated cost optimization, combining transportation and handling within a model specifically adapted to Indonesia’s complex geography and infrastructure. The simulation involves four LNG plant supply nodes and 50 demand locations, serving a total demand of 15,528 m³/day across four clusters. The analysis estimates a total investment of USD 685.3 million, with a plant-gate LNG price of 10.35 to 11.28 USD/MMBTU at a 10 percent discount rate, representing a 55 to 60 percent cost reduction compared to HSD. These findings support the strategic deployment of SS LNG to expand affordable electricity access in remote and underserved regions. Full article

Social media has rapidly intervened in the interaction between urban consumers and commercial space, further reshaping the structure of urban commercial space. This study employed the social, spatial, and subjective dimensions of geographies of consumption as the theoretical framework. Based on the data from five social media platforms, including Douyin, REDnote, Weibo, Dianping, and Baidu Index, we constructed a multi-level evaluation method of “attention level–activity degree–experience quality” and applied it to measure the dynamics of the shopping malls in Shanghai to investigate their mechanism of generating urban commercial space vitality. The findings indicate that the “core + core–periphery + multi-center + circle structure, agglomeration, and balance” is the primary pattern of urban commercial space in Shanghai. The differences in business formats, consumer positioning, and consumption culture revealed by the social media data are conducive to clarifying the scale of the regional consumption space and the logic of urban commercial evolution. The main contribution of this study is the demonstration that this evaluation method rooted in social media has the potential to generalize the measurement of urban commercial space in major cities in China. We also propose corresponding countermeasures and suggestions for developing urban commercial space in Shanghai. Full article

Firefighters across the world face higher risks of occupational hazards, such as exposure to chemicals, extreme heat, traumatic stressors, and intense physical demands, which can increase their vulnerability to a range of psychological and physiological difficulties. These challenges include the risk of developing chronic stress, depression, and post-traumatic stress disorder (PTSD), potentially leading to detrimental negative coping patterns such as alcohol abuse. The consequent health implications impact both short-term and long-term health and well-being. This study aimed to explore the relationship between mental health status, alcohol consumption patterns, and gut microbiome alterations in firefighters from two different regions—America and Korea. By investigating these relationships, we hope to gain insights into how repeated exposure to severe stressors impacts gut health. Healthy male firefighters (ages 21–50) and controls (matched sex, geography, and age) were recruited via flyers and snowball sampling in the United States and South Korea, resulting in 203 participants (102 firefighters and 101 controls). Firefighters reported significantly higher PTSD symptoms and depression and drank 2.3 times more alcohol than the control group. American firefighters reported more drinking than Koreans. There was a significant correlation between higher alcohol consumption and the likelihood of witnessing deaths by suicide. However, there were no correlations between alcohol consumption and PTSD symptom severity. There were associations between alcohol consumption patterns and aspects of the gut microbiome. This study highlights the mental health challenges faced by firefighters, including elevated rates of PTSD, depression, and alcohol consumption, with specific microbial imbalances linked to PTSD and alcohol use, emphasizing the role of the gut–brain axis. Full article

Cities host over 50% of the world’s population and account for nearly 75% of the world’s energy consumption and 80% of the global greenhouse gas emissions. Consequently, ensuring a smart way to organize cities is paramount for the quality of life and efficiency of resource use, with emphasis on the use and management of energy, under the context of the energy trilemma, where the objectives of sustainability, security, and affordability need to be balanced. Electrification associated with the use of renewable energy generation is increasingly seen as the most efficient way to reduce the impact of energy use on GHG emissions and natural resource depletion. Electrification poses significant challenges to the development and management of the electrical infrastructure, requiring the deployment of Smart Grids, which emerge as a key development of Smart Cities. Our review targets the intersection between Smart Cities and Smart Grids. Several key components of a Smart City in the context of Smart Grids are reviewed, including elements such as metering, IoT, renewable energy sources and other distributed energy resources, grid monitoring, artificial intelligence, electric vehicles, or buildings. Case studies and pilots are reviewed, and metrics concerning existing deployments are identified. A portfolio of 16 solutions that may contribute to bringing Smart Grid solutions to the level of the city or urban settings is identified, as well as 11 gaps existing for effective and efficient deployment. We place these solutions in the context of the energy trilemma and of the Smart Grid Architecture Model. We posit that depending on the characteristics of the urban setting, including size, location, geography, a mix of economic activities, or topology, the most appropriate set of solutions can be identified, and an indicative roadmap can be built. Full article

In China, with the increasing emphasis on the concept of green sustainable development, polluting industries characterized by pollution and high energy consumption are facing unprecedented challenges. The development of the intermediate demand-type characteristics of polluting industries should be more reasonably laid out and regulated. In this paper, environmental regulation and environmental quality are introduced into the new economic geography model. On the basis of theoretical analysis, the IV regression method was used to study the interaction between polluting industry agglomeration, environmental regulation, and their effects on urban air quality with key cities as research objects. The results show that an increase in the agglomeration of polluting industries leads to significant deterioration in urban air quality and that this effect is linear, whereas an increase in the intensity of environmental regulation significantly dampens this effect. Each 1% increase in the intensity of environmental regulation results in a 1.17% reduction in air pollution. Therefore, to effectively protect the environment, the development of polluting industries should be relatively decentralized. Additionally, city governments should fully consider their urban eco-geographical characteristics, directly reduce and indirectly inhibit the degree of agglomeration of polluting industries and simultaneously strengthen the intensity of environmental regulation. Full article

Cooperative and self-enforceable water allocation is a key instrument to manage geopolitical conflict induced by water scarcity, which necessitates the cooperative willingness of the agents and considers their heterogeneity in geography, climate, hydrology, environment and social economy. Based on a multi-indicator system that contains asymmetric information on water volume contribution, current water consumption, water economic efficiency and efforts for eco-environmental protection, this study proposed a water allocation framework by combining the asymmetric power index approach with bankruptcy theory for solving the transboundary water allocation problem under scarcity. The proposed method was applied to the Yellow River Basin in northern China, which is mainly shared by nine provincial districts and frequently suffers from severe water shortages, and its results were compared with six alternative methods. The results highlight the necessity of quantifying agents’ willingness to cooperate under the condition of asymmetric negotiation power when making decisions on transboundary water allocations. The proposed method allows for transboundary water allocations through simultaneous consideration of the agent’s willingness to cooperate and asymmetric negotiation power, as well as disagreement allocation points, which ensure the stability, fairness and self-enforceability of allocation results. Therefore, it can offer practical and valuable decision-making insights for transboundary water management under water scarcity. Full article

The pursuit of the Sustainable Development Goals has highlighted rural electricity consumption patterns, necessitating innovative analytical approaches. This paper introduces a novel method for predicting rural electricity consumption by leveraging deep convolutional features extracted from satellite imagery. The study employs a pretrained remote sensing interpretation model for feature extraction, streamlining the training process and enhancing the prediction efficiency. A random forest model is then used for electricity consumption prediction, while the SHapley Additive exPlanations (SHAP) model assesses the feature importance. To explain the human geography implications of feature maps, this research develops a feature visualization method grounded in expert knowledge. By selecting feature maps with higher interpretability, the “black-box” model based on remote sensing images is further analyzed and reveals the geographical features that affect electricity consumption. The methodology is applied to villages in Xinxing County, Guangdong Province, China, achieving high prediction accuracy with a correlation coefficient of 0.797. The study reveals a significant positive correlations between the characteristics and spatial distribution of houses and roads in the rural built environment and electricity demand. Conversely, natural landscape elements, such as farmland and forests, exhibit significant negative correlations with electricity demand predictions. These findings offer new insights into rural electricity consumption patterns and provide theoretical support for electricity planning and decision making in line with the Sustainable Development Goals. Full article

Accurately predicting industrial electricity consumption is of paramount importance for optimizing energy management and operational efficiency. Traditional forecasting approaches face significant challenges in capturing the complex factors influencing industrial electricity consumption, often due to the inadequate representation of correlations, thus limiting their predictive capabilities. To overcome these limitations, we propose a novel graph-based forecasting model termed Industry–Geography Time Series Forecasting Model (IG-TFM). Our approach leverages historical electricity consumption data and geographical information relevant to similar industries to construct an industry–geography relationship graph. This graph serves as the foundation of a comprehensive network that encompasses all industries of interest, allowing us to identify sectors closely associated with the target industry. The structured graph data are then processed within a graph convolutional neural network framework, which effectively captures the impact of geographical location, industry similarities, and inter-industry relationships on electricity consumption patterns. Utilizing this enriched representation, we develop our IG-TFM for accurate time series forecasting of industrial electricity consumption. Experiments conducted on real-world data, including 31 industries across 9 cities in a southern province of China, demonstrate the significant advantages of our proposed method across key performance indicators such as the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). These findings underscore the importance and efficacy of employing complex networks to encode sequence-related information, thereby substantially improving prediction accuracy in industrial electricity consumption forecasting. Full article

Load balancing to alleviate network congestion remains a critical challenge in Vehicular Ad Hoc Networks (VANETs). During route and response scheduling, road side units (RSUs) risk being overloaded beyond their calculated capacity. Despite recent advancements like RSU-based load transfer, NP-Hard hierarchical geography routing, RSU-based medium access control (MAC) schemes, simplified clustering, and network activity control, a significant gap persists in employing a load-balancing server for effective traffic management. We propose a server-based network congestion handling mechanism (SBNC) in VANETs to bridge this gap. Our approach clusters RSUs within specified ranges and incorporates dedicated load balancing and network scheduler RSUs to manage route selection and request–response scheduling, thereby balancing RSU loads. We introduce three key algorithms: optimal placement of dedicated RSUs, a scheduling policy for packets/data/requests/responses, and a congestion control algorithm for load balancing. Using the VanetMobiSim library of Network Simulator-2 (NS-2), we evaluate our approach based on residual energy consumption, end-to-end delay, packet delivery ratio (PDR), and control packet overhead. Results indicate substantial improvements in load balancing through our proposed server-based approach. Full article

Place branding is a discipline at the intersection of geography and communications, devoted to the process by which places become brands, understood as devices for managing a desired identity presented to the outside world, and also for internal consumption by the residents of the place. This paper intends to explain the conceptualization process of a place brand, and to present the methodological framework for building a brand that takes into account all audiences and stakeholders, thus strengthening the identity of the place. The case presented here is Masquefa, a municipality in the Barcelona province. The methodology has been structured in three phases: first, an initial diagnosis and data gathering; next, fieldwork and public participation (interviews, surveys, and discussion in focus groups); and third, construction of the story. The conclusions of this article show how a municipality without any significant tangible and intangible assets to truly identify it can build a brand story accepted by all agents, both public and private, which will help it grow sustainably in the future. Full article

Growing worldwide food demand with its environmental impacts requires a reshaping of food consumption. This study aims to evaluate the degree of Italian consumers’ awareness of sustainability and whether protein alternatives to meat could be accepted. A cross-sectional survey was carried out on a group of 815 respondents, representative of the Italian adult population for geography, gender, and age, using multivariate analysis together with cluster analysis. Lack of awareness of the consequences of food choices on the environment was found in 45% of respondents, and 51% reduced their consumption of meat. Typical foods of the Mediterranean diet (84% legumes 82% eggs, and 77% fish) were selected as the preferred sources of protein to replace meat, while insects and insect-based products were less accepted (67%). The importance of meat is the latent factor that explains more than 50% of the common variance observed in the factor analysis. The cluster analysis confirmed the importance of meat for Italian consumers, emphasizing other aspects of the sustainability of food choices. Cluster 1 (25.6%) considered meat very important. Two out of five clusters (clusters 2 and 3, 38%) considered meat replaceable in the diet, and cluster 4 (31.3%) included meat consumers that were willing to be sustainable. Cluster 5 identifies the “unsustainable consumers” (5.7%). In conclusion, besides the perceived importance of meat, there is room for recommendations for its reduction by proposing alternative foods already present in the Mediterranean diet. Full article

Cooling energy consumption is a major contributor to various sectors in hot climates with a significant number of warm days throughout the year. Buildings account for 40% of total energy consumption, with approximately ∼30–40% of that used for cooling in geographical areas such as Iran. Energy demand for cooling is an important factor in the overall energy efficiency of electric mobility. Electric vehicles (EVs) consume ∼30–50% of energy for the air conditioning (AC) system. Therefore, the efficient management of the cooling demand is essential in implementing energy-saving strategies. Passive radiative cooling is capable of providing subambient cooling without consuming any energy. This article reviews potential applications of passive radiative cooling in reducing cooling energy for buildings. It also provides a rough estimate of the amount of energy saved when applying a radiative cool roof to a model building. It is shown that by using radiative cool materials on roofs, the share of electricity usage for cooling can be reduced to 10%, leading to a reduction in cooling load by 90%. Additionally, the potential use of radiative cool coats of various types for different EV components, such as shell/body, windows, and fabrics, is introduced. Although the prospects of the design and engineering of radiative cooling products appear promising for both buildings and EVs, further investigations are necessary to evaluate scalability, durability, and performance based on factors such as geography and meteorology. Full article

In 2019, Indonesia’s electricity consumption exceeded 278 TWH, or about 1.08 MWh/capita. This value shows a considerable increase in electricity consumption which has doubled in just a decade. Previous studies have shown that the proportion of electricity consumption used for lighting needs is correlated to the country’s GDP. This is generally around 20 to 50% of electricity production but can go up to 86% in the case of Tanzania. Indonesia is the 4th country in the world in terms of population and its lighting market as well as its lighting-related energy consumption has a strong impact on several levels: societal, environmental but also economic and energy. Having a knowledge of the lamps used by the Indonesian people is therefore particularly interesting and important, in particular in the context which presents a great societal diversity but also in a context of energy saving. Indonesia is an archipelagic country made up of 5 large islands and over 17,000 small islands with widely varying levels of population density. This island geography leads Indonesia to face challenges in the distribution and production of electrical energy, which affects the use of lamps in various types of regions. The overview of this study was done by collecting data from various sources, especially BPS (Biro Pusat Statistik/Statistic Center Bureau of Indonesia), CLASP (an NGO for clean energy), the Ministry of Energy and Mineral Resources of Indonesia (ESDM), PLN (Indonesian Electrical Company), etc. The data obtained from these sources provides several descriptions of general lighting conditions in Indonesia viewed from several angles, such as growth of lamp market, use of lamp types, percentage of use of lamps with energy saving (ESL), etc. Considering that Indonesia has various regional characteristics, in this study, the survey of a total of 394 respondents was conducted on the use of lamps by creating regional categories based on electrical conditions, power consumption, and electricity per capita, among others. The categories of areas observed fall into 5 types based on their population and geography: large cities, small towns, rural/village areas, islands and remote areas. The results of compiling data from these various sources show that the types of lamps used by Indonesians follow the lighting trend in the world. The use of LED lamps has a utilization percentage of around 52%, much higher than other types of lamps such as CFL, fluorescent or incandescent. Based on the survey conducted, it is known that the widely used LED power is between 1 and 10 watts with a usage time of 8 to 12 h per day. In the next few years, it is estimated that the use of LEDs in Indonesia will increase as the government has prepared various regulations and policies related to energy saving, one of which relates to lighting. Full article