Energy Intensity Research Articles

Impact of artificial intelligence technology applications on corporate energy consumption intensity

Artificial intelligence (AI), as a new technology, not only revolutionizes economic development, but also provides an opportunity for environment governance. Extant studies primarily explore the environmental performance of AI from a macro perspective, while evidence on how AI technology applications affect firms’ energy-saving behavior is scarce. Employing Python technology to recognize AI-related keywords in the annual reports of listed enterprises and adopting data on corporate energy consumption from 2011 to 2020, we explore the impact of AI on corporate energy consumption intensity (CECI) and its mechanisms. We observe that AI technology applications reduce CECI. After a range of robustness tests, the conclusions are still solid. The mechanism analysis reveals that AI cuts CECI through spurring firm green innovation, stimulating firms to introduce new equipment, and reducing firms’ internal management costs. Heterogeneity analysis reveals that this negative impact is more prominent for SOEs and private enterprises’ energy intensity; we also find that this effect is more pronounced for high-tech industry enterprises and high-polluting enterprises. Our findings provide micro evidence for policymakers to reduce corporate energy intensity and realize energy conservation and emission abatement targets.

Geo-political risks, uncertainty, financial development, renewable energy, and carbon intensity: Empirical evidence from countries at high geo-political risks

Geopolitical risks and uncertainty negatively affect the economy and environmental quality. High geopolitical risks and high uncertainty increase carbon emission intensity by increasing dependence on fossil fuels. However, research in this area is still in its infancy and more empirical evidence is needed to justify the causal link. This research examines the causal mechanism linking geopolitical risk, uncertainty, financial development, renewable energy, and carbon intensity in a sample of eighteen countries with high geopolitical risk between 1985 and 2021. The selected countries have a high intensity of geopolitical risks due to internal and external conflicts that have worsened in recent years. We employ cointegration techniques from Hatemi-J [1] and Maki [2] in the presence of structural breaks, fully modified ordinary least squares (FMOLS), canonical cointegration regression (CCR) models, and static time-variant Granger causality (1969) test. We find robust empirical evidence that geopolitical risk, financial development, renewable energy, uncertainty, and carbon intensity have a cointegrating relationship in the presence of structural breaks. Results from FMOLS and CCR models indicate that carbon intensity responds differently to changes in geopolitical risk, renewable energy, uncertainty, and financial development. Environmental and energy policymakers should mitigate carbon intensity through long-run rather than short-run mechanisms to achieve SDG12 and SDG13.

Effectiveness of Xanthan Gum-based composite in repairing cracks in reinforced concrete structures

Abstract This study investigates the enhancement of concrete slabs using a biopolymer-modified cementitious repair material (CXT) composed of Ordinary Portland Cement, Xanthan Gum, and Tartaric Acid Powder. The innovative formulation of CXT aims to improve the mechanical properties of repaired concrete structures. Experimental results demonstrate that CXT significantly enhances mechanical properties such as the load-bearing capacity of concrete slabs. Non-destructive testing methods, including the Rebound Hammer test and Ultrasonic Pulse Velocity (UPV), as well as destructive testing methods, were employed to evaluate the performance of CXT in repairing cracks. The study highlights the improved load-bearing capacity and structural integrity of CXT-repaired slabs, contributing to increased longevity and reduced maintenance costs of concrete structures. Furthermore, the sustainability metrics of CXT, including Process Mass Intensity (PMI), Energy Intensity (EI), Environmental Factor (E-Factor), and Reaction Mass Efficiency (RME), are evaluated, illustrating its cost-effectiveness and environmental benefits. This comprehensive approach underscores the potential of CXT as a durable and sustainable repair material for concrete infrastructure.

Green siphon or green spillover: Analyzing the spatial implications of industrial relocation on green development

Industry relocation has a profound impact on the green development of recipient cities and their neighboring areas, driven by various factors such as investment and technological progress. This study investigates the impact of industrial relocation on the green development efficiency (GDE) of recipient cities and its spatial spillover effect using national city-level data and the establishment of national-level Industrial Relocation Demonstration Zones (IRDZ) as a policy shock, employing spatial difference-in-differences models. Both theoretical analysis and empirical tests show that industrial outflow increases the GDE of recipient cities, but reducing the GDE of neighboring cities. This effect decays with spatial distance and only affects non-resource cities. In addition, regional integration and the influence of large cities can significantly mitigate the adverse effects of industrial relocation. Industrial agglomeration, environmental regulation, green innovation, and energy intensity are the main direct and indirect pathways through which industrial relocation affects GDE in recipient and neighboring cities. The findings of this study are significant for promoting industrial relocation, energy conservation, and emission reduction in developing regions, as well as enhancing green cooperation among governments.

Effects of Rainfall Intensity, Kinetic Energy and Slope Angle to the Upslope, Downslope, and Lateral Slope Components of Splash Erosion in Hillslope Agriculture: A Case in Badiangan, Ajuy, Iloilo

This study was conducted in Barangay Badiangan, Ajuy, Iloilo City, Philippines (11°10’N, 122°58’E) to determine the effects of rainfall intensity and other rainfall-derived parameters on the directional components of splash erosion in hillslopes. There are five experimental set-ups with slope angles ranging from 0% to 48% were tested under natural rainfall conditions using a modified splash collector. The data collected shows that kinetic energy, slope, and rainfall intensity have shown significant effects on splash erosion. The models obtained using regression analysis are 𝑄𝑄𝑑𝑑𝑑𝑑𝑑𝑑=0.0093(𝐾𝐾𝐾𝐾0.80) and 𝑄𝑄𝑡 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡=0.060(𝐾𝐾𝐾𝐾0.107)(𝑆𝑆0.700)(𝐼𝐼200.700) . The model equation performance has been validated using the Standard Error of Estimates with values of 12 and 9.4 for splash detachment and splash transport, respectively. The constants used for kinetic energy in detachment and slope in transport align with the research by Quansah (1981) for sandy soil, which is similar (the characteristics) to the soil at our research site. Additionally, rainfall intensity, especially with a 20-min duration, generated the best model as it yielded the lowest SEE value for all cases.

Research of electrode materials for the creation of multifunctional current sources with increased capacity as a components of the energy sector of an efficient urban environment

As part of creating a comfortable and safe environment, constructing energy-efficient residential and industrial buildings and structures that meet modern requirements and standards, the development of the production of environmentally friendly renewable and new individual energy sources is becoming especially relevant. In this regard, there is a need to increase the energy capacity of electrochemical cells. Research has been carried out on the metallized conductive materials creation based on rolled carbon non-woven material “Busofit” with the sequential application of metal coatings of titanium and silver using ion-plasma sputtering and electric pulse dispersion methods. It has been shown that surface layer metallization of the electrode material with titanium can improve the electrochemical cell characteristics. Additional silver film deposition leads to further cell performance improvement. It has been confirmed that the multilayer structure interfacial resistance between the carbon and the current collector has a significant effect on the conductivity of the electrochemical cell and the stability of its operation. The contact area increase of the electrode with the electrolyte leads to an increase in the rate processes occurring on the electrode surface and in the near-electrode space, which opens up prospects for increasing the energy intensity of the electrochemical system. A significant capacity increase of a water-based capacitor structure is achieved by the formation of a nanostructured dielectric layer of potassium titanate in the interelectrode space. It has been confirmed that the cell voltage cycling helps to stabilize the processes occurring in the surface layer of the electrode material at the interface and determining the range of mechanisms for transmitting electrical energy, which makes it possible to achieve higher energy intensity of the samples. Improvement of technological solutions in the field of ion-plasma technologies and the use of new perspective nanostructured materials creates the prerequisites for the creation of advanced automation and energy supply systems with a higher resource, which expands the possibilities of their use in various construction projects.

Life cycle perspective in design and product development

Abstract Eco-design is one of the cornerstones of the modern economy, as reflected in the policies aimed at implementing the principles of design for the environment in the European Union legislation. A life cycle perspective is a feature of eco-design. The study aimed to determine whether and to what extent the selected companies operating in manufacturing sectors consider life cycle perspectives when designing and developing the products they offer. The main research area discussed in the following article focused on the question: What kind of activities related to the idea of life cycle thinking in product policy can be identified in the analysed enterprises? Qualitative research was conducted using the individual in-depth interview method with representatives of selected industries located in Poland. Eight manufacturer groups were invited to participate in the study. Based on the recruitment process, 24 companies were chosen for the interview. Individual in-depth interviews were conducted using Microsoft Teams, following the ICC/ESOMAR Code 2016 standards. Based on the results, most companies that participated in the study considered the life cycle perspective when designing or further developing products. However, their activities varied in scope. The activities of the ten interviewed companies could be regarded as advanced. For six companies, the advanced activities targeted the product’s use phase. Two companies undertook such activities at more than one life cycle stage. The study provides evidence that the surveyed companies are beginning to think beyond operational boundaries and changing their pro-environmental orientation, albeit unimpressively. The paper provides evidence that eco-design requirements are an unquestionable driver for activities from a life cycle perspective. All surveyed manufacturers of energy-powered products are taking measures to reduce energy intensity with less activity, for example, ensuring the durability/reliability of products and finding solutions to facilitate disassembly and recycling.

The dark side of climate policy uncertainty: Hindering energy transition by shaping environmental taxes effectiveness

Climate policy uncertainty (CPU) may have an adverse impact on the environment by interfering with the effectiveness of environmental policies, but there is currently little evidence to support this indirect effect. By incorporating CPU into the transition function, this paper utilizes the panel smooth transition regression (PSTR) to dynamically analyze how CPU affects the relationship between environmental taxes (ETR) and energy transition. When CPU exceeds the threshold, the promoting effect of ETR on energy transition weakens or reverses. The robustness of the main conclusions is demonstrated by establishing a PSTR estimator with the instrumental variable. This paper also constructs a counterfactual scenario, showing that CPU reduces the positive impact of ETR on renewable energy consumption and generation by 7.6% and 3.5%, respectively. Further analysis indicates that this negative effect arises because CPU likely increases investment risk, particularly for long-term green projects, thereby inhibiting the clean energy market and energy-related green technological innovation. Heterogeneity analysis find that the weakening effect of CPU on the effectiveness of ETR is stronger in countries with low energy resource endowment, high energy intensity, and lower economic development levels, underscoring the need for tailored policy approaches. This research emphasizes that for countries with ambitious energy transition goals, climate policy stability is crucial for ensuring the healthy development of environmental taxes policy and renewable energy markets.

Analysis of Synergistic Drivers of CO2 and NOX Emissions from Thermal Power Generating Units in Beijing–Tianjin–Hebei Region, 2010–2020

Synergistic control of the emissions of air pollutants and CO2 is critical to the dual challenges of air quality improvement and climate change in China. Based on the emission inventories of thermal power units in Beijing, Tianjin, and Hebei, this study analyzes the CO2 and NOX emission characteristics of these units, and identifies and quantifies the synergistic drivers affecting these emission trends. The inventory data show that, between 2010 and 2020, NOX emissions were reduced by 86.1%, while CO2 emissions were reduced by only 29.8%. Although significant progress has been made in reducing NOX emissions through measures such as end-of-pipe treatment, controlling CO2 emissions remains a difficult task. The index decomposition analysis reveals that economic growth is the main driver of CO2 and NOX emission growth, energy intensity reduction is the main driver of CO2 emission reduction, and end-of-pipe treatment is the main driver of NOX emission reduction. Currently, coal occupies about 87% of the energy consumption of thermal power units in the Beijing–Tianjin–Hebei region, and remains the main type of energy for synergistic emissions, and the potential for emission reduction in the energy structure remains huge. For NOX emissions, it is expected that 90% of the reduction potential can be achieved through energy restructuring and end-of-pipe treatment. In conclusion, this high-precision unit-by-unit emission study confirms the effectiveness of the control policy for thermal power units in the region and provides some scientific reference for future policy formulation.

Enhancing energy efficiency: Design and simulation of air fractionation unit integrated through LNG cold energy and two‐stage organic Rankine cycles

AbstractThe study explores air separation processes, proposing an innovative design incorporating liquid natural gas (LNG)'s two‐stage Rankine cycles to address traditional approaches' complexity and energy intensity. Significant wastage of energy during air compression in standard units is recuperated for liquefied natural gas regasification, with a focus on enhancing cold energy recovery, emphasizing cryogenic LNG advantages. Aspen HYSYS (12.1) is used for process modelling and simulation evaluating a combined two‐stage Rankine cycle integrated into air separation. Specific energy requirements for high‐purity oxygen and nitrogen production are reduced to 0.38 and 0.12 kWh/kg, respectively. The integrated Rankine cycle generates 4456.32 kW, which is sufficient for air separation process. Exergy destruction and component efficiency are explored and parametric optimization, revealing LNG variables' significant impact. Economic analysis indicates a fair 5.25‐year payback period. This approach aligns with sustainability goals, providing a compelling efficiency‐enhancing option for the LNG sector.

Crude oil-water emulsions formed by nozzle type inflow control device

Conventional water-in-oil emulsion studies where shear energy intensity and duration are applied to achieve ‘equilibrium’ emulsion droplet properties may not represent partial emulsion conditions observed in single pass flow through Inflow Control Device (ICD) orifices. Our experiments provide data expected to improve emulsion transport models for partial emulsification processes expected in well completion and production tubulars. Development of a novel flow adaptor apparatus is described together with a laboratory homogeniser enables independent control of shear intensity and duration together with input water volume fraction. The emulsions formed are characterised with a benchtop Nuclear Magnetic Resonance spectrometer for water content and droplet size, viscosity by a rotating bob viscometer and free water/emulsion proportion by optical photography. Experimental results confirmed partial emulsification above 30% V/V, as observed in both previous ICD flow experiments and field observations. Electrical conductivity measurements of the emulsions produced indicated that partial emulsification comprising an oil external emulsion phase together with free water, rather than emulsion inversion, occurs in this system.

Sustainability and circularity assessment of the potential of a biofuel produced from black liquor as a substitute for conventional fuels

The European Bioeconomy Strategy aims to accelerate the deployment of a sustainable European bioeconomy to maximize its contribution to the 2030 Agenda and its Sustainable Development Goals (SDGs), as well as to the Paris Agreement on climate change. In this context, transport is considered as a key sector, with aviation and shipping playing an important role due to the need to meet its huge demand. In order to reduce potential emissions from the transport sector, the use of biofuels could be considered as a solution. However, with the aim of using biofuels to replace conventional fuels, it is important to assess their cost-effectiveness and feasibility, and in this aspect the valorization of waste streams for their production could help to meet this challenge. This is the framework of this research report, which is based on the use of black liquor (BL) from pulp and paper production to produce biofuel through a hydrothermal liquefaction (HTL) unit. Three technological designs and production capacities were considered: full extraction of the oil phase and its upgrading by catalytic hydrothermal deoxygenation (Scenario 1, S1), partial extraction of the oil phase (Scenario 2, S2) and full extraction but without upgrading (Scenario 3, S3). Low (100 t/d), medium (300 t/d) and high (600 t/d) production capacities were regarded.From the modelling data, a life cycle perspective was adopted, taking into account both the environmental analysis (LCA) and the life cycle costs (LCC), as well as the circular potential using different performance, resource-flow circularity and economic indicators. In addition, a composite indicator, CILCA-LCC-CA, has been proposed to obtain a single score taking into account the three assessments: environmental, cost and circularity. The results obtained show that S3, with a production of 300 t/d, has the lowest environmental impact and the highest profitability corresponds to a capacity of 600 t/d. In terms of circularity, S3 also shows the best performance, mainly due to its higher resource productivity and lower energy intensity. These results are in line with those obtained for the composite indicator, and also show that higher production capacities and a simple but efficient process technology, such as S3, is the alternative with the highest potential for both sustainability and circularity.

Uncovering socio-economic driving forces of volatile organic compounds emissions in the Beijing-Tianjin-Hebei region of China

The Beijing-Tianjin-Hebei (BTH) region is an important urban agglomeration in northern China, which has experienced rapid economic growth and heavy air pollution such as volatile organic compounds (VOCs) emissions. It is therefore urgent to uncover the socio-economic driving forces of VOCs emissions so that the BTH region can move toward sustainable development. This study aims to fill this research gap by measuring the contributions of different socio-economic factors to VOCs emissions in the BTH region during 2008–2017 by using the generalized Divisia index method (GDIM). Our results show that energy consumption scale and economic scale are the two largest contributors to the increase of VOCs emissions, while emission intensity of output and emission intensity of energy are the two dominant drivers for preventing the increase of VOCs emissions in the BTH region. Other factors, such as population scale, per capita emission, per capita GDP, and energy intensity, have marginal effects on VOCs emissions. These findings provide valuable insights to those policy makers in the BTH region to prepare effective measures to mitigate their VOCs pollution by considering regional disparity.

Spatio-temporal distribution and peak prediction of energy consumption and carbon emissions of residential buildings in China

With the acceleration of urbanization and the improvement of people's living standards, the carbon emissions of residential buildings (BCE) in China have been increasing, hindering the achievement of carbon peaking and carbon neutrality goals. It has become increasingly urgent and important to analyze and grasp the dynamic trends of BCE. Given the notable regional variations in carbon emissions, it is necessary to delve into the distribution characteristics of BCE and the underlying factors influencing them. First, based on the emission factor method, the energy consumption and carbon emissions calculation models are established. Next, the main influencing factors are obtained by improving Kaya's constant equation. Meanwhile, the GA-PPC-Kmeans model is established to divide BCE into different regions. Then, the STIRPAT-Ridge model is built to predict the peak carbon emissions. Finally, a combination of static and dynamic methods is used to forecast peaks under three scenarios, which are low-carbon (LC) scenario, baseline (BA) scenario, and high-carbon (HC) scenario. The results show that five pivotal factors significantly impact BCE in China, which are energy carbon emission intensity (ECEI), energy intensity (EI), economic density (ED), residential housing level (RHL) and population size(P). Furthermore, BCE is categorized into five distinct regions: low-carbon demonstration area, energy efficiency improvement area, carbon concentration and innovation area, high-carbon optimization area, and carbon poverty development area. Under BA scenario, the peaks for BCE in these regions converge primarily around 2040 and 2045. This study provides a regional research perspective for China's residential buildings to reach the peak of carbon emissions, and serves as a reference for formulating carbon emission reduction plans in different regions.

Sustainability Indicators to MSW Treatment Assessment: The Rio de Janeiro Case Study

The Brazilian Policy foresees the waste management hierarchy, according to which energy reuse from waste is preferred to final disposal. However, less than 0.2% of the country’s waste goes to energy production. This paper proposes sustainability indicators to support the decision to choose the best process to treat municipal solid waste (MSW) through bioenergy generation technologies. Then, we conduct a case study for Rio de Janeiro. Incineration and gasification were not economically feasible—despite TRL 9 and 8. However, the projects presented a null net present value by increasing the gate fee to 94.69 and 255.39 USD/ton of MSW, respectively. The social indicators (job creation, salary increase with the absorption of waste pickers, population served, reduction in MSW sent to landfill) did not indicate the best technology. The results of the environmental indicators for incineration and gasification were, respectively, 0.45 and 0.37 t CO2eq/tMSW for GWP, 1.49 and 1.23 MWh/tMSW for energy intensity, 1.24 and 6.14 m3/tMSW for water intensity, 39.3 and 27.9 m2/tMSW for land use and 0.135 and 0.088 t SO2eq/tMSW for acidification. Gasification presented better results on 60% of the environmental indicators. However, incineration scored better in the important ones, water and energy intensities, in addition to the technical–economic aspect.

Advanced Decision- Making Framework for Sustainable Energy Retrofit of Existing Commercial Office Buildings

In the background of rising global initiatives to combat climate change and promote better energy management, retrofitting of current structures has become a major strategy. This abstract and literature review aims at presenting a full review of a decision-making approach that can be used in choosing sustainable options for energy retrofitting. This particular framework is designed to help guide retrofit decision-making due to the many issues that surround the process by providing an economic as well as an environmental and social context. Energy retrofitting means improving the existing structure or complex to decrease its energy intensity and have a negative impact on the environment. As stated earlier, it is a critical process for attaining sustainability goals and advancing the performance of buildings. But the decision on which retrofit measures should be implemented can be rather difficult because of the availability of a vast number of technologies and because more factors must be considered, such as cost and energy savings. The decision-making framework provided in this article aims at categorizing retrofit selection into this list of features and views the current article as a way of making the process more efficient. It encompasses the life-cycle cost analysis (LCCA), the economic valuation, and the multi-criteria decision analysis tools and criteria. These tools facilitate the evaluation of financial viability, the advantages of climatically retrofitting, and the environmental effects of distinct retrofitting choices. The above-mentioned framework is exemplified with a case study of an office building retrofit project. The following case includes an example of the application of the mentioned framework and illustrates the explanation of how it helps to make decisions. Due to the consideration of costs, energy, and environmental performance, the framework enables the stakeholders to choose appropriate retrofit measures. Other than the case study, the framework also focuses on the need to establish a sustainable energy retrofit DSS. Thus, the DSS supplements collected data on building performance, retrofit technologies, and economic aspects, which can be accessed by the stakeholders in real-time and with built-in facilities for scenario analysis. This system improves decision-making since retrofit results can be monitored and evaluated frequently. Both tools and strategies for the decision-making of sustainable energy retrofits bring a logical and systematic approach aimed at neutralizing the decision-making challenges related to retrofit selection. By applying economic, environmental, and social factors in the decision-making process, the framework assists the stakeholders in reaching energy efficiency and sustainability goals. The development of another strong decision-support system also improves the working of the framework and checks that retrofit projects are done efficiently and are strategic to the general goal of sustainable development.

Development of national specialization in 5G technologies within the European Union

Nowadays the efforts of not only companies, but also governments in different countries are aimed at the development of 5G technologies. On the one hand, the introduction of 5G is an expensive process that requires investments in the development, deployment and maintenance of infrastructure, the involvement of a large number of market participants and service providers, the creation of a stimulating and regulatory legislative framework, the provision of radio frequencies of a more efficient spectrum, the solution of patenting issues. On the other hand, the introduction of 5G technologies will be aimed at developing the economy of many industries, creating social benefits, reducing energy intensity, and will create new opportunities for companies. Currently, the benefits of the digital economy can be most used by the United States, the Republic of Korea and China, which have the highest rates of 5G adoption in the world. The countries of the European Union are also interested in the development of 5G technologies. We analysed key 5G technologies for 74,940 related patents for 23 EU countries for the period 2012–2021. It is shown that the leaders in the number of 5G patents were Sweden, Germany, Finland, France, the Netherlands and Ireland. It is noteworthy that countries can either focus on developing a small number of technologies, or develop a wide range of them. Since 2018, France, Estonia and Germany demonstrate the greatest number of technological specializations primarily creating inventions related to 5G data processing. At the same time, the USA, the Republic of Korea and China still retain their competitive advantages in fields of basic electric elements and electric communication technique for fifth generation networks. To improve positions in the global technology market the EU countries need to specialize in rarer and more complex technologies and develop national policies in this area.

Impact of energy price reform on energy intensity in Iranian manufacturing industries

Impact of energy price reform on energy intensity in Iranian manufacturing industries

Deep Learning-Based Flood Detection for Bridge Monitoring Using Accelerometer Data

Flooding and consequential scouring are the primary causes of bridge failures, making the detection of such events crucial for structural safety. This study investigates the characteristics of accelerometer data from bridge pier vibrations and proposes a flood detection method with deep learning-based models based on ResNet18 and 1D Convolution architectures. These models were comprehensively evaluated for (1) detecting vehicles passing on bridges and (2) detecting flood events based on axis-specific accelerometer data under various traffic conditions. Continuous Wavelet Transform (CWT) was employed to convert the accelerometer data into richer time-frequency representations, enhancing the detection of passing vehicles. Notably, when vehicles are passing over bridges, the vertical direction exhibits a magnified and more sustained energy distribution across a wider frequency range. Additionally, under flooding conditions, time-frequency representations from the bridge direction reveal a significant increase in energy intensity and continuity compared with non-flooding conditions. For detection of vehicles passing, ResNet18 outperformed the 1D Convolution model, achieving an accuracy of 97.2% compared with 91.4%. For flood detection without vehicles passing, the two models performed similarly well, with accuracies of 97.3% and 98.3%, respectively. However, in scenarios with vehicles passing, the 1D Convolution model excelled, achieving an accuracy of 98.6%, significantly higher than that of ResNet18 (81.6%). This suggests that high-frequency signals, such as vertical vibrations induced by passing vehicles, are better captured by more complex representations (CWT) and models (e.g., ResNet18), while relatively low-frequency signals, such as longitudinal vibrations caused by flooding, can be effectively captured by simpler 1D Convolution over the original signals. Consequentially, the two model types are deployed in a pipeline where the ResNet18 model is used for classifying whether vehicles are passing the bridge, followed by two 1D Convolution models: one trained for detecting flood events under vehicles-passing conditions and the other trained for detecting flood events under no-vehicles-passing conditions. This hierarchical approach provides a robust framework for real-time monitoring of bridge response to vehicle passing and timely warning of flood events, enhancing the potential to reduce bridge collapses and improve public safety.

Impact of economic growth, renewable energy consumption and energy intensity on CO2 emissions in BRIC countries: An application of CS-ARDL

Impact of economic growth, renewable energy consumption and energy intensity on CO2 emissions in BRIC countries: An application of CS-ARDL