Search results

Occupant behavior can lead to considerable uncertainties in thermal comfort and air quality within buildings. To tackle this challenge, the use of probabilistic controls to simulate occupant behavior has emerged as a potential solution. This study seeks to analyze the performance of free-running households by examining adaptive thermal comfort and CO2 concentration, both crucial variables in indoor air quality. The investigation of indoor environment dynamics caused by the occupants' behavior, especially after the COVID-19 pandemic, became increasingly important. Specifically, it investigates 13 distinct window and shading control strategies in courtyard houses to identify the factors that prompt occupants to interact with shading and windows and determine which control approach effectively minimizes the performance gap.

This paper compares commonly used deterministic and probabilistic control functions and their effects on occupant comfort and indoor air quality in four zones surrounding a courtyard. The zones are differentiated by windows facing the courtyard. The study utilizes the energy management system (EMS) functionality of EnergyPlus within an algorithmic interface called Ladybug Tools. By modifying geometrical dimensions, orientation, window-to-wall ratio (WWR) and window operable fraction, a total of 465 cases are analyzed to identify effective control scenarios. According to the literature, these factors were selected because of their potential significant impact on occupants’ thermal comfort and indoor air quality, in addition to the natural ventilation flow rate. Additionally, the Random Forest algorithm is employed to estimate the individual impact of each control scenario on indoor thermal comfort and air quality metrics, including operative temperature and CO2 concentration.

The findings of the study confirmed that both deterministic and probabilistic window control algorithms were effective in reducing thermal discomfort hours, with reductions of 56.7 and 41.1%, respectively. Deterministic shading controls resulted in a reduction of 18.5%. Implementing the window control strategies led to a significant decrease of 87.8% in indoor CO2 concentration. The sensitivity analysis revealed that outdoor temperature exhibited the strongest positive correlation with indoor operative temperature while showing a negative correlation with indoor CO2 concentration. Furthermore, zone orientation and length were identified as the most influential design variables in achieving the desired performance outcomes.

It’s important to acknowledge the limitations of this study. Firstly, the potential impact of air circulation through the central zone was not considered. Secondly, the investigated control scenarios may have different impacts on air-conditioned buildings, especially when considering energy consumption. Thirdly, the study heavily relied on simulation tools and algorithms, which may limit its real-world applicability. The accuracy of the simulations depends on the quality of the input data and the assumptions made in the models. Fourthly, the case study is hypothetical in nature to be able to compare different control scenarios and their implications. Lastly, the comparative analysis was limited to a specific climate, which may restrict the generalizability of the findings in different climates.

Occupant behavior represents a significant source of uncertainty, particularly during the early stages of design. This study aims to offer a comparative analysis of various deterministic and probabilistic control scenarios that are based on occupant behavior. The study evaluates the effectiveness and validity of these proposed control scenarios, providing valuable insights for design decision-making.

Despite the importance of tax policy in reducing energy consumption and carbon emissions, there is a dearth of research on the environmental impact of indirect taxes. This paper examines the impact of indirect taxes on carbon dioxide (CO₂) emissions, with an emphasis on institutional quality.

The study uses the Government Revenue Dataset (2021), comprising 143 countries, dividing into 114 developing and 29 developed countries, during the period between 1996 and 2019. The author adopts panel data techniques, with Driscoll–Kraay standard errors to account for the issue of cross-sectional dependence (CSD).

The results indicate that indirect tax revenues have a negative and significant impact on CO₂ emissions for the total sample. The subsample analysis revealed that while indirect taxes reduce carbon emissions in developing countries, opposed results are reported for developed countries. This finding implies that most of the advanced countries have already reached a high level of taxes, at which carbon emissions increase as indirect tax increases further. Interestingly, the results revealed that institutional quality enhances the role of indirect taxes in mitigating carbon emissions for both developing and developed countries.

To the best of the authors' knowledge, this is the sole study using the newly developed tax data by the United Nations University, World Institute for Development Research (UNU-WIDER) to investigate the impact of indirect taxes on carbon emissions, with an emphasis on institutional quality. The existing literature focuses on specific taxes, like carbon taxes, with no comprehensive research on the link between indirect taxes and carbon emissions.

Social development is the ultimate goal of every nation, and climate change is a major stumbling block. Climate Risk Index has documented several climate change events with their devastations in terms of lives lost and economic cost. This study aims to link the climate change and renewable energy with the social progress of extreme climate affected countries.

This research used the top 50 most climate-affected countries of the decade and estimated the impact of climate risk on social progress with moderation effects of renewable energy and technology. Several competing panel data models such as quantile regression, bootstrap quantile regression and feasible generalized least square are used to generate robust estimates.

The results confirm that climate hazards obstruct socioeconomic progress, but renewable energy and technology can help to mitigate the repercussion. Moreover, improved institutions enhance the social progress of nations.

Government should improve the institutional quality that enhances their performance in terms of Voice and Accountability, Political Stability and Absence of Violence, Government Effectiveness, Regulatory Quality, Rule of Law and Control of Corruption to increase social progress. In addition, society should use renewable energy instead of fossil fuels to avoid environmental degradation and health hazards. Innovation and technology also play an important role in social progress and living standards, so there should be free hand to private business research and development, encouraging research institutes and universities to come forward for innovation and research.

The ultimate goal of all human struggle is to have progress that facilitates human beings to uplift their living standard. One of the best measures that can tell us about a nation’s progress is Social Progress Index (SPI), and one of many factors that can abruptly change it is the climate; so this study is an attempt to link the relationship among these variables and also discuss the situation where the impact of climate can be reduced.

Although social progress is an important concept of today’s economics discussion, relatively few studies are using the SPI to measure social well-being. Similarly, there is consensus about the impact of climate on people, government and crops but relatively less study about its overall impact on social progress, so this study attempts to fill the gap about the relationship between social progress and climate change.

The main contribution of this study is the solution for the impact of climate risk. Climate risk is not in human control, and we cannot eliminate it, but we can reduce the negative impacts of climate change. Moderator impact of renewable energy decreases the negative impact of climate change, so there is a need to use more renewable energy to mitigate the bad consequences of climate on social progress. Another moderator is technology; using technology will also mitigate the negative consequences of the climate, so there is a need to facilitate technological advancement.

This study aims to investigate the relationship between business group affiliation and CO2 emissions in Chile, providing insights into the pollution externalities associated with business group structures and their implications for environmental performance.

A hand-matched sample of industrial facilities and subsidiaries of listed firms in Chile was utilized to analyze the CO2 emissions of business group-affiliated firms compared to stand-alone firms. Fixed-effect regression analysis and propensity score matching were employed to examine the differences in emissions levels.

The results suggest that firms affiliated with business groups have higher CO2 emissions in comparison to similar stand-alone firms. This suggests that business group structures may weaken the pressures for emission reduction and maintenance of public legitimacy among affiliated firms.

The findings of this study are subject to certain limitations, such as the use of a specific dataset from Chile and the inability to explore certain factors due to data constraints. For instance, we were unable to examine the separation between control and cash-flow rights as well as the influence of manager characteristics on pollution levels. Future research should address these limitations and expand the analysis to other emerging market countries to further investigate the impact of lax or ineffective environmental regulations on pollution outcomes.

The research findings have practical implications for investors and policymakers. Investors interested in environmentally sustainable investments should consider the higher pollution levels associated with business group-affiliated firms. Policymakers can use these findings to design more effective regulations and incentives to encourage emission reduction efforts within business group structures.

The study’s results emphasize the need for a comprehensive understanding of the environmental implications of business group affiliation. By recognizing the potential for higher emissions in business group structures, stakeholders can advocate for sustainable practices, encourage transparency and promote responsible environmental management within corporate entities.

This study contributes to the literature on corporate governance, climate risks and pollution externalities by providing an empirical evidence on the relationship between business group affiliation and CO2 emissions. It highlights the importance of considering the influence of corporate structures on environmental performance, particularly in the context of emerging market economies.

Este estudio tiene como objetivo investigar la relación entre la afiliación a grupos empresariales y las emisiones de CO2 en Chile, proporcionando información sobre las externalidades de contaminación asociadas con las estructuras de grupos empresariales y sus implicaciones para el desempeño ambiental de las empresas.

Se utilizó una muestra recolectada de manera manual de instalaciones industriales y subsidiarias de empresas listadas en Chile para analizar las emisiones de CO2 de empresas afiliadas a grupos empresariales en comparación con empresas independientes. Se emplearon análisis de regresión de efectos fijos y modelos de emparejamiento por puntaje de propensión para examinar las diferencias en los niveles de emisiones.

Los resultados sugieren que las empresas afiliadas a grupos empresariales tienen mayores emisiones de CO2 en comparación con empresas independientes similares. Esto sugiere que las estructuras de grupos empresariales pueden debilitar las presiones para la reducción de emisiones y el mantenimiento de la legitimidad pública entre las empresas afiliadas.

Este estudio contribuye a la literatura sobre gobierno corporativo, riesgos climáticos y externalidades de contaminación al proporcionar evidencia empírica sobre la relación entre la afiliación a grupos empresariales y las emisiones de CO2. Destaca la importancia de considerar la influencia de las estructuras corporativas en el rendimiento ambiental, especialmente en el contexto de las economías de mercados emergentes.

Los hallazgos de este estudio están sujetos a ciertas limitaciones, como el uso de un conjunto de datos específico de Chile y la incapacidad para explorar ciertos factores debido a restricciones de datos. Por ejemplo, no pudimos examinar la influencia de las características de los ejecutivos de las empresas en los niveles de contaminación. Investigaciones futuras deberían abordar estas limitaciones y ampliar el análisis a otros países de mercados emergentes para investigar más a fondo el impacto de regulaciones ambientales laxas o ineficaces en los resultados de contaminación.

Los hallazgos de la investigación tienen implicaciones prácticas para inversores y responsables políticos. Los inversores interesados en inversiones ambientalmente sostenibles deben tener en cuenta los niveles más altos de contaminación asociados con empresas afiliadas a grupos empresariales. Los responsables políticos pueden utilizar estos hallazgos para diseñar regulaciones más efectivas e incentivos para fomentar los esfuerzos de reducción de emisiones dentro de las estructuras de grupos empresariales.

Los resultados del estudio enfatizan la necesidad de comprender de manera integral las implicaciones ambientales de la afiliación a grupos empresariales. Al reconocer el potencial de mayores emisiones en las estructuras de grupos empresariales, los interesados pueden abogar por prácticas sostenibles, fomentar la transparencia y promover una gestión ambiental responsable dentro de las entidades corporativas.

Growing food insecurity is a leading cause of fatalities, particularly in developing nations like Sub-Saharan Africa and Southeast Asia. However, the rising energy consumption and carbon dioxide (CO2) emissions are mostly associated with food production. Balancing the trade-offs between energy intensity and food security remains a top priority for environmentalists. Despite the critical role of the environment in food security, there is a scarcity of substantial studies that explore the statistical connections among food security, CO2 emissions, energy intensity, foreign direct investment (FDI) and per capita income. Therefore, this study aims to provide more precise and consistent estimates of per capita CO2 emissions by considering the interplay of food security and energy intensity within the context of emerging economies.

To examine the long-term relationships between CO2 emissions, food security, energy efficiency, FDI and economic development in emerging economies, this study employs correlated panel-corrected standard error, regression with Newey–West standard error and regression with Driscoll–Kraay standard error models (XTSCC). The analysis utilizes data spanning from 1980 to 2018 and encompasses 32 emerging economies.

The study reveals that increasing food security in a developing economy has a substantial positive impact on both CO2 emissions and energy intensity. Each model, on average, demonstrates that a 1 percent improvement in food security results in a 32% increase in CO2 levels. Moreover, the data align with the Environmental Kuznets Curve (EKC) theory, as it indicates a positive correlation between gross domestic product (GDP) in developing nations and CO2 emissions. Finally, all experiments consistently demonstrate a robust correlation between the Food Security Index (FSI), energy intensity level (EIL) and exchange rate (EXR) in developing markets and CO2 emissions. This suggests that these factors significantly contribute to environmental performance in these countries.

This study introduces novelty by employing diverse techniques to uncover the mixed findings regarding the relationship between CO2 emissions and economic expansion. Additionally, it integrates energy intensity and food security into a new model. Moreover, the study contributes to the literature by advocating for a sustainable development goal (SDG)-oriented policy framework that considers all variables influencing economic growth.

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

This study aims to explore the relationship between the degree of state-owned enterprises’ (SOEs) mixed reform and the environmental response of enterprises, against the background of actively promoting the reform of mixed ownership in China.

The study is conducted on a sample of A-share listed manufacturing companies in Shanghai and Shenzhen of China, investigated for the period 2015 to 2020. The baseline regression results are robust to a series of robustness and endogeneity tests. To deal with the issue of endogeneity, the technique of instrumental variable method has been applied.

The study confirms the U-shaped effect of the depth and restriction of mixed ownership on SOEs’ environmentally responsive behaviour in the manufacturing industry, especially for lower environmental regulation and higher level of risk-taking firms. The findings indicate that the government, shareholders and other stakeholders of enterprises should not simply consider that the mixed reform is directly promoting or reducing the environmental response behaviour of enterprises.

SOEs should improve their shareholding structures to undermine performance enhancement at the expense of the environment and increase environmentally beneficial behaviours. Regulators and governments should improve the institutional mechanism of environmental regulation and make efforts to promote corporate awareness of the environment.

Although the adoption and implementation of environmentally friendly policies are costly, improved environmental response and other social responsibilities are helpful to corporate long-term growth and reputation and obtain more capital market attention. Therefore, firms would benefit from improving their environmental response to protect nature, as well as to enjoy the economic and social benefits of a better environmental response.

To the best of the authors’ knowledge, there is a lack of studies focussing on the environmental behaviour of SOEs of mixed reform. As the mixed reform in China has come to a climax phase in recent several years, SOEs of mixed reform is an ideal environment for research. The study focusses on manufacturing firms as these firms are more susceptible to contribute to environmental pollution, exploitation of natural resources and labour concerns.

The coal-fired power plants have been confronted with new operation challenge since the unified carbon trading market was launched in China. To make the optimal decision for the carbon emissions and power production has already been an important subject for the plants. Most of the previous studies only considered the market prices of electricity and coal to optimize the generation plan. However, with the opening of the carbon trading market, carbon emission has become a restrictive factor for power generation. By introducing the carbon-reduction target in the production decision, this study aims to achieve both the environmental and economic benefits for the coal-fired power plants to positively deal with the operational pressure.

A dynamic optimization approach with both long- and short-term decisions was proposed in this study to control the carbon emissions and power production. First, the operation rules of carbon, electricity and coal markets are analyzed, and a two-step decision-making algorithm for annual and weekly production is presented. Second, a production profit model based on engineering constraints is established, and a greedy heuristics algorithm is applied in the Gurobi solver to obtain the amounts of weekly carbon emission, power generation and coal purchasing. Finally, an example analysis is carried out with five generators of a coal-fired power plant for illustration.

The results show that the joint information of the multiple markets of carbon, electricity and coal determines the real profitability of power production, which can assist the plants to optimize their production and increase the profits. The case analyses demonstrate that the carbon emission is reduced by 2.89% according to the authors’ method, while the annual profit is improved by 1.55%.

As an important power producer and high carbon emitter, coal-fired power plants should actively participate in the carbon market. Rather than trade blindly at the end of the agreement period, they should deeply associate the prices of carbon, electricity and coal together and realize optimal management of carbon emission and production decision efficiently.

This paper offers an effective method for the coal-fired power plant, which is struggling to survive, to manage its carbon emission and power production optimally.

The aim of this study is to assess the opportunity for the development of hydrocarbon transportation using high-strength steel (HSS) in pipeline construction in terms of cost savings and reliability.

Several optimizations of pipeline design and operations were performed to estimate the total life-cycle cost variation associated with different grades of high-strength steel. The generalized reduced gradient (GRG) method was used in an Excel table to determine optimal total life cycle each pipeline. Variables used in this optimization with respect to each steel grade were as follows: pipeline external diameter, wall thickness, number of compression stations and installed power in each compression station. The reliability of a pipeline with optimal cost was assessed to highlight the impact of steel grade on pipeline reliability.

The study showed that the cost reduction is strongly dependent on the adopted gas pipeline configuration. The number of compression stations and external diameter are the main factors influencing the pipeline total life cycle cost, while the steel price seems to have a minor effect, the reduction of the gas pipeline total life cycle does not exceed 5% even with a 50% difference in pipe steel prices between X70 and X100 steels. On the other side, for the same external diameter, X100 steel presents better pipeline reliability against carbonic corrosion compared to X70 steel.

The main contribution of this study is to provide a decision-support tool to help pipeline constructors enhance the profitability of natural gas transmission pipelines. The optimization method used is simple to use for design engineers during a feasibility study.

The present study presents one step to fill the gap concerning the question of balancing the trade-off between cost savings and structural reliability in high-strength steel pipelines during the early stages of feasibility studies. The optimal design and operations parameters ensuring cost savings on total life cycle costs are identified via an optimization method. The impact of selected optimal parameters on the long-term pipeline service life was estimated via a structural reliability analysis.

This study is intended to analyze the impact of information and communication technology (ICT) infrastructure, technological innovation, renewable energy consumption and financial development on carbon dioxide emissions in emerging economies.

The present study adopts the autoregressive distributed lag (ARDL) cointegration technique for the annual data collection of Vietnam from 1990 to 2020.

The results of the study unveil that renewable energy consumption, the interaction between renewable energy consumption and ICT infrastructure and financial development have significant predictive power for carbon dioxide emissions. In the long term, renewable energy consumption, export and population growth reduce CO2 emissions, whereas the interaction between renewable energy consumption and ICT infrastructure and financial development increases CO2 emissions, while ICT infrastructure does not affect emissions. In the short run, changes in ICT infrastructure contribute to carbon dioxide emissions in Vietnam. In addition, changes in renewable energy consumption, financial development, the interaction between ICT infrastructure and renewable energy consumption and population growth have a significant effect on CO2 emissions. Notably, technological innovation has no impact on CO2 emissions in both the short and long run.

The current study provides new insights into the environmental effects of ICT infrastructure, technological innovation, renewable energy consumption and financial development. The interaction between renewable energy consumption and ICT infrastructure has a significant effect on carbon dioxide emissions. The paper suggests important implications for setting long-run policies to boost the effects of financial development, renewable energy consumption and ICT infrastructure on environmental quality in emerging countries like Vietnam in the coming time.