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Article
Publication date: 26 July 2023

Aarzoo Sharma, Aviral Kumar Tiwari, Emmanuel Joel Aikins Abakah and Freeman Brobbey Owusu

This paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be…

Abstract

Purpose

This paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be specific, the authors aim to address the following questions: Is there any distributional predictability among green bonds and energy commodities during COVID-19? Is there exist any directional predictability between green investments and energy commodities during the global pandemic? Can green bonds hedge the risk of energy commodities during a period of the financial crisis.

Design/methodology/approach

The authors use the nonparametric causality in quantile and cross-quantilogram (CQ) correlation approaches as the estimation techniques to investigate the distributional and directional predictability between green investments and energy commodities respectively using daily spot prices from January 1, 2020, to March 26, 2021. The study uses daily closing price indices S&P Green Bond Index as a representative of the green bond market. In the case of energy commodities, the authors use S&P GSCI Natural Gas Spot, S&P GSCI Biofuel Spot, S&P GSCI Unleaded Gasoline Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI, OPEC Oil Basket Price, Crude Oil Oman, Crude Oil Dubai Cash, S&P GSCI Heating Oil Spot, S&P Global Clean Energy, US Gulf Coast Kerosene and Los Angeles Low Sulfur CARB Diesel Spot.

Findings

From the CQ correlation results, there exists an overall negative directional predictability between green bonds and natural gas. The authors find that the directional predictability between green bonds and S&P GSCI Biofuel Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI Spot, OPEC Oil Basket Spot, Crude Oil Oman Spot, Crude Oil Dubai Cash Spot, S&P GSCI Heating Oil Spot, US Gulf Coast Kerosene-Type Jet Fuel Spot Price and Los Angeles Low Sulfur CARB Diesel Spot Price is negative during normal market conditions and positive during extreme market conditions. Results from the non-parametric causality in the quantile approach show strong evidence of asymmetry in causality across quantiles and strong variations across markets.

Practical implications

The quantile time-varying dependence and predictability results documented in this paper can help market participants with different investment targets and horizons adopt better hedging strategies and portfolio diversification to aid optimal policy measures during volatile market conditions.

Social implications

The outcome of this study will promote awareness regarding the environment and also increase investor’s participation in the green bond market. Further, it allows corporate institutions to fulfill their social commitment through the issuance of green bonds.

Originality/value

This paper differs from these previous studies in several aspects. First, the authors have included a wide range of energy commodities, comprising three green bond indices and 14 energy commodity indices. Second, the authors have explored the dependency between the two markets, particularly during COVID-19 pandemic. Third, the authors have applied CQ and causality-in-quantile methods on the given data set. Since the market of green and sustainable finance is growing drastically and the world is transmitting toward environment-friendly practices, it is essential and vital to understand the impact of green bonds on other financial markets. In this regard, the study contributes to the literature by documenting an in-depth connectedness between green bonds and crude oil, natural gas, petrol, kerosene, diesel, crude, heating oil, biofuels and other energy commodities.

Details

Studies in Economics and Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1086-7376

Keywords

Content available
Article
Publication date: 5 December 2023

Thalis P.V. Zis

This paper focusses on the aftermath of disruptions and the importance of the two largest canals (Suez and Panama), commenting on how during the pandemic the canal fees were…

Abstract

Purpose

This paper focusses on the aftermath of disruptions and the importance of the two largest canals (Suez and Panama), commenting on how during the pandemic the canal fees were lowered. Considering the ongoing efforts to decarbonize shipping, some of the ongoing disruptions will help reach these objectives faster.

Design/methodology/approach

Following a literature review of route choice in shipping, and a presentation of significant disruptions in recent years, the author deploys a simplified fuel consumption model and conduct case study analyses to compare different routes environmentally and economically.

Findings

The results explain why at times of low fuel prices as in 2020, canals provided discounts to entice ship operators to keep transiting these, instead of opting for longer routes. Considering the ongoing repercussions of the pandemic in supply chains, as well as the potential introduction of market-based measures in shipping, the value of transiting canals will be much higher in the coming years.

Research limitations/implications

The main limitation in this work is that the author used the publicly available information on canal tolls, for the different ship types examined.

Practical implications

The envisioned model is simple, and it can be readily used for any ship and route (port to port) combination available, if ship data are available to researchers.

Social implications

It is possible that canal tolls will increase, to account for the additional environmental benefits brought to ship operators.

Originality/value

The methodology is simple and transferable, and the author proposes several interesting research questions for follow-up work.

Details

Maritime Business Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2397-3757

Keywords

Article
Publication date: 13 April 2023

Priyanka Sakare and Saroj Kumar Giri

The purpose of this paper was to study the color change kinetics of lac dye in response to aldehydes, carbon dioxide and other food spoilage metabolites for its potential…

Abstract

Purpose

The purpose of this paper was to study the color change kinetics of lac dye in response to aldehydes, carbon dioxide and other food spoilage metabolites for its potential application in intelligent food packaging.

Design/methodology/approach

UV–Vis spectroscopy was used to study the color change of dye solution. Ratio of absorbance of dye solution at 528 nm (peak of ionized form) to absorbance at 488 nm (peak of unionized form) was used to study the color change. Color change kinetics was studied in terms of change in absorbance ratio (A528/A488) with time using zero and first-order reaction kinetics. Lac dye-based indicator was prepared to validate the result of study for monitoring quality of strawberries.

Findings

Lac dye was orange-red in acidic medium and purple in alkaline medium. Color change of dye in response to benzaldehyde followed zero-order reaction kinetics, whereas for carbon dioxide first-order model was found best. No color change of dye solution was observed for alcohols, ketones and sulfur compounds. In the validation part, the color of the indicator label changed from purple to orange when the strawberries spoiled.

Originality/value

The study expands application area for lac dye as sensing reagent in intelligent food packaging for spoilage or ripeness detection of fruits and vegetables.

Details

Pigment & Resin Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0369-9420

Keywords

Article
Publication date: 11 July 2023

Nehal Elshaboury, Eslam Mohammed Abdelkader and Abobakr Al-Sakkaf

Modern human society has continuous advancements that have a negative impact on the quality of the air. Daily transportation, industrial and residential operations churn up…

Abstract

Purpose

Modern human society has continuous advancements that have a negative impact on the quality of the air. Daily transportation, industrial and residential operations churn up dangerous contaminants in our surroundings. Addressing air pollution issues is critical for human health and ecosystems, particularly in developing countries such as Egypt. Excessive levels of pollutants have been linked to a variety of circulatory, respiratory and nervous illnesses. To this end, the purpose of this research paper is to forecast air pollution concentrations in Egypt based on time series analysis.

Design/methodology/approach

Deep learning models are leveraged to analyze air quality time series in the 6th of October City, Egypt. In this regard, convolutional neural network (CNN), long short-term memory network and multilayer perceptron neural network models are used to forecast the overall concentrations of sulfur dioxide (SO2) and particulate matter 10 µm in diameter (PM10). The models are trained and validated by using monthly data available from the Egyptian Environmental Affairs Agency between December 2014 and July 2020. The performance measures such as determination coefficient, root mean square error and mean absolute error are used to evaluate the outcomes of models.

Findings

The CNN model exhibits the best performance in terms of forecasting pollutant concentrations 3, 6, 9 and 12 months ahead. Finally, using data from December 2014 to July 2021, the CNN model is used to anticipate the pollutant concentrations 12 months ahead. In July 2022, the overall concentrations of SO2 and PM10 are expected to reach 10 and 127 µg/m3, respectively. The developed model could aid decision-makers, practitioners and local authorities in planning and implementing various interventions to mitigate their negative influences on the population and environment.

Originality/value

This research introduces the development of an efficient time-series model that can project the future concentrations of particulate and gaseous air pollutants in Egypt. This research study offers the first time application of deep learning models to forecast the air quality in Egypt. This research study examines the performance of machine learning approaches and deep learning techniques to forecast sulfur dioxide and particular matter concentrations using standard performance metrics.

Details

Construction Innovation , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 24 May 2023

Tuna Uysaler, Pelin Altay and Gülay Özcan

In the denim industry, enzyme washing and its combination with stone washing are generally used to get the desired worn-out look. However, these conventional methods include high…

Abstract

Purpose

In the denim industry, enzyme washing and its combination with stone washing are generally used to get the desired worn-out look. However, these conventional methods include high water, energy and time consumption. Nowadays, laser fading, which is a computer-controlled, dry, ecological finishing method, is preferred in the denim fading process. The purpose of this study is to observe the effects of chemical pretreatment applications on laser-faded denim fabric in terms of color and mechanical properties. To eliminate the enzyme washing process in denim fading and to minimize the disadvantages of laser fading, such as decreased mechanical properties and increased fabric yellowness, various chemical pretreatment applications were applied to the denim fabric before laser fading, followed by simple rinsing instead of enzyme washing.

Design/methodology/approach

Two different indigo-dyed, organic cotton denim fabrics with different unit weights were exposed to pretreatment processes and then laser treatment, followed by simple rinsing. Polysilicic acid, boric acid, borax and bicarbonate were used for pretreatment processes, and laser treatment was carried out under optimized laser parameters (40 dpi resolution and 300 µs pixel time). Tensile strength was tested, and color values (CIE L*, a*, b*, ΔE*, C* and h), color yield (K/S), yellowness and whiteness indexes were measured to identify the color differences.

Findings

Before laser fading, 30 g/L and 40 g/L polysilicic acid pretreatments for sulfur-indigo-dyed fabric and a mixture of 10 g/L boric acid and 10 g/L borax pretreatments for the fabric only indigo-dyed were recommended for the laser fading with sufficient mechanical properties and good color values.

Originality/value

With the chemical pretreatments defined in this study, it was possible to reduce yellowness and maintain the mechanical properties after laser fading, thus minimizing the disadvantages of laser treatment and also eliminating enzyme washing.

Details

Research Journal of Textile and Apparel, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1560-6074

Keywords

Article
Publication date: 11 March 2024

Hendrik Hensel and Markus Clemens

Gas insulated systems, such as gas insulated lines (GIL), use insulating gas, mostly sulfur hexalfluoride (SF6), to enable a higher dielectric strength compared to e.g. air…

Abstract

Purpose

Gas insulated systems, such as gas insulated lines (GIL), use insulating gas, mostly sulfur hexalfluoride (SF6), to enable a higher dielectric strength compared to e.g. air. However, under high voltage direct current conditions, charge accumulation and electric field stress may occur, which may lead to partial discharge or system failure. Therefore, numerical simulations are used to design the system and determine the electric field and charge distribution. Although the gas conduction shows a more complex current–voltage characteristic compared to solid insulation, the electric conductivity of the SF6 gas is set as constant in most works. The purpose of this study is to investigate different approaches to address the conduction in the gas properly for numerical simulations.

Design/methodology/approach

In this work, two approaches are investigated to address the conduction in the insulating gas and are compared to each other. One method is an ion-drift-diffusion model, where the conduction in the gas is described by the ion motion in the SF6 gas. However, this method is computationally expensive. Alternatively, a less complex approach is an electro-thermal model with the application of an electric conductivity model for the SF6 gas. Measurements show that the electric conductivity in the SF6 gas has a nonlinear dependency on temperature, electric field and gas pressure. From these measurements, an electric conductivity model was developed. Both methods are compared by simulation results, where different parameters and conditions are considered, to investigate the potential of the electric conductivity model as a computationally less expensive alternative.

Findings

The simulation results of both simulation approaches show similar results, proving the electric conductivity for the SF6 gas as a valid alternative. Using the electro-thermal model approach with the application of the electric conductivity model enables a solution time up to six times faster compared to the ion-drift-diffusion model. The application of the model allows to examine the influence of different parameters such as temperature and gas pressure on the electric field distribution in the GIL, whereas the ion-drift-diffusion model enables to investigate the distribution of homo- and heteropolar charges in the insulation gas.

Originality/value

This work presents numerical simulation models for high voltage direct current GIL, where the conduction in the SF6 gas is described more precisely compared to a definition of a constant electric conductivity value for the insulation gas. The electric conductivity model for the SF6 gas allows for consideration of the current–voltage characteristics of the gas, is computationally less expensive compared to an ion-drift diffusion model and needs considerably less solution time.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0332-1649

Keywords

Content available
Article
Publication date: 29 September 2023

Maneerat Kanrak, Yui-yip Lau, Xavier Ling and Saksuriya Traiyarach

The rapid growth in cruise shipping coupled with increasing public awareness of climate change has led to increasing concerns about the impact cruise shipping poses on the…

Abstract

Purpose

The rapid growth in cruise shipping coupled with increasing public awareness of climate change has led to increasing concerns about the impact cruise shipping poses on the environment, especially regarding air emissions. This study analyses the cruise shipping network of ports in and around the emission control areas (ECAs) to understand the structural properties of the network and ports.

Design/methodology/approach

A complex network approach was used to analyse the network data of 239 voyages serviced by 14 international cruise lines, visiting 127 ports across 44 countries in the Caribbean Sea.

Findings

It is found that the network has a small-world property with a short average path length and a high clustering coefficient. The regulations affect connections among ports, in which most ports in ECAs have lower connections than ports outside ECAs. A few ports in ECAs play important key roles, but many ports outside ECAs play a more important role in the network because the regulations are barriers for cruise ships entering the ports.

Originality/value

The findings of this study have drawn useful guidelines for cruise lines and port authorities to improve their operations. Constrictive recommendations are suggested to policymakers for designing reasonable regulations to attract more cruise shipping to travel in ECAs.

Details

Maritime Business Review, vol. 8 no. 4
Type: Research Article
ISSN: 2397-3757

Keywords

Article
Publication date: 29 September 2023

Li Wang, Yanhong Lv, Tao Wang, Shuting Wan and Yanling Ye

The purpose of this research is to address the existing gap in the study of construction and demolition waste (C&DW) by focusing on its impact on human health throughout the…

Abstract

Purpose

The purpose of this research is to address the existing gap in the study of construction and demolition waste (C&DW) by focusing on its impact on human health throughout the entire life cycle. And this research provides a comprehensive assessment model that incorporates the release of gaseous pollutants and particulate matter during the whole life cycle of C&DW, thereby contributing to a more holistic understanding of its impact on human health.

Design/methodology/approach

The research was conducted in two stages. Firstly, the quantitative model framework of pollutants emitted by C&DW was established. Three types of pollutants were considered, namely nitrogen dioxide (NO2), sulfur dioxide (SO2) and inhalable particulate matter (PM10). Second, disability-adjusted life year (DALY) and willingness to pay (WTP) assessments were used to provide a monetary quantified health impact for pollutants released by C&DW.

Findings

The results show that the WTP value of PM10 is the highest among all pollutants and 8.68E+07 dollars/a, while the WTP value in the disposal stage accounts for the largest proportion compared to the generation and transportation stage. These findings emphasize the importance of PM10 and C&DW treatment stage for pollutant treatment.

Originality/value

The results of this study are of great significance for the management department to optimize the construction management scheme to reduce the total amount of pollutants produced by C&DW and its harm to human health. Meanwhile, this study fills the gap in existing research on the impact assessment of C&DW on human health throughout the whole life cycle, and provides reference and basis for future research and policy formulation.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Book part
Publication date: 28 September 2023

Medha Gupta, Anmol Sharma, Kiran Sood and Simon Grima

Air pollution is the combination of fine particles and gases in the atmosphere that harm humans and animals. Our objective is to find the various air pollution contaminants and…

Abstract

Air pollution is the combination of fine particles and gases in the atmosphere that harm humans and animals. Our objective is to find the various air pollution contaminants and its repercussion on Homo sapiens’ health. We discuss how air quality is measured with the air quality index and measures that help us cope with the consequences of air pollution. To carry out this study, we carried out a systematic literature review to uncover the different dimensions of air pollution and mitigation strategies. From the existing literature and observations of the different data sets, we can conclude that air pollutants have a severe impact on the life of Homo sapiens, causing various diseases such as respiratory issues, skin diseases, etc. Today, we have ample laws, but the need of the hour is to initiate new policies to change the behavioural of Homo sapiens. Our findings will help in decision-making by stakeholders such as policy-makers, manufacturing industries, households, etc. This article will also help in highlighting the need for Homo sapiens behavioural change.

Details

Digital Transformation, Strategic Resilience, Cyber Security and Risk Management
Type: Book
ISBN: 978-1-80455-262-9

Keywords

Open Access
Article
Publication date: 12 September 2023

Zhiping Hou, Jun Wan, Zhenyu Wang and Changgui Li

In confronting the challenge of climate change and progressing towards dual carbon goals, China is actively implementing low-carbon city pilot policy. This paper aims to focus on…

Abstract

Purpose

In confronting the challenge of climate change and progressing towards dual carbon goals, China is actively implementing low-carbon city pilot policy. This paper aims to focus on the potential impact of this policy on enterprise green governance, aiming to promote the reduction and balance of carbon emissions.

Design/methodology/approach

Based on the panel data of China's large-scale industrial enterprises from 2007 to 2013, this paper uses the Difference-in-differences (DID) method to study the impact and path mechanism of the implementation of low-carbon city pilot policy on enterprise green governance. Heterogeneity analysis is used to compare the effects of low-carbon city pilot policy in different regions, different enterprises and different industries.

Findings

The low-carbon pilot can indeed effectively enhance corporate green governance, a conclusion that still holds after a series of robustness tests. The low-carbon city pilot policy mainly enhances enterprise green governance through two paths: an industrial structure upgrade and enterprise energy consumption, and it improves green governance by reducing enterprise energy consumption through industrial structure upgrade. The impact of low-carbon city pilot policy on enterprise green governance shows significant differences across different regions, different enterprises and different industries.

Research limitations/implications

This paper examines the impact of low-carbon city pilot policy on enterprise green governance. However, due to availability of data, there are still some limitations to be further tackled. The parallel trend test in this paper shows that the pilot policy has a significant positive effect on the green governance of enterprises. However, due to serious lack of data in some years, the authors only selected the enterprise data of a shorter period as our experimental data, which leads the results to still have certain deficiencies. For the verification of the impact mechanism, the conclusions obtained in this paper are relatively limited. Although all the mechanism tests are passed, the reliability of the results still needs to be further tested through future data samples. In addition, as the pilot policy of low-carbon cities is still in progress, the policy can be tracked and analysed in the future as more data are disclosed, and further research can be carried out through dimensional expansion.

Practical implications

Low-carbon city pilot policy plays an important role in inducing the green governance of enterprises. Therefore, policy makers can continue to strengthen the construction of low-carbon city pilots by refining pilot experience, building typical cases, actively promoting pilot policy experience, expanding pilot scope and enhancing the implementation efficiency of pilot policy nationwide, which will contribute to the optimization and upgrading of the regional industrial structure at the urban level and will provide experience and reference for the synergistic implementation plan of pollution reduction and carbon reduction.

Social implications

The impact of the low-carbon city pilot policy on enterprise green governance not only exists in two separate paths of urban industrial upgrading and enterprise energy consumption but also exists in a chain transmission path from macro to micro. The authors find that the effect value of each influence path is different, and there is an obvious leading influence path for the role of enterprise green governance. Therefore, in the process of implementing a low-carbon city pilot policy, policies should be designed specifically for different mechanisms. Moreover, complementing and coordinating several paths should be advocated to give full play to the green governance effect of enterprises brought by different paths and to further expand the scope of industries and enterprises where policies play a role.

Originality/value

To the best of the authors’ knowledge, for the first time, this paper connects macro mechanisms with micro mechanisms, discovering a macro-to-micro transmission mechanism in the process of low-carbon city pilot policy affecting enterprise green governance. That is, the low-carbon city pilot policy can facilitate industrial structure upgrading, resulting in reduced enterprise energy consumption, ultimately enhancing enterprise green governance.

Details

International Journal of Climate Change Strategies and Management, vol. 15 no. 5
Type: Research Article
ISSN: 1756-8692

Keywords

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