scholarly journals The Impact of Economic, Energy, and Environmental Factors on the Development of the Hydrogen Economy

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4811
Author(s):  
Justyna Cader ◽  
Renata Koneczna ◽  
Piotr Olczak
Keyword(s):  
Environmental Factors ◽  
Co2 Emission ◽  
Energy Technology ◽  
Development Programs ◽  
Technology Research ◽  
Hydrogen Economy ◽  
Final Energy Consumption ◽  
Different Characteristics ◽  
The Impact ◽  
Spearman’S Correlation

This article attempts to model interdependencies between socio-economic, energy, and environmental factors with selected data characterizing the development of the hydrogen economy. The study applies Spearman’s correlation and a linear regression model to estimate the influence of gross domestic product, population, final energy consumption, renewable energy, and CO2 emission on chosen hydrogen indicators—production, patents, energy technology research, development, and demonstration budgets. The study was conducted in nine countries selected for their actions towards a hydrogen economy based on analyses of national strategies, policies, research and development programs, and roadmaps. The results confirm the statistically significant impact of the chosen indicators, which are the drivers for the development of the hydrogen economy from 2008 to 2018. Moreover, the empirical results show that different characteristics in each country contribute to the development of the hydrogen economy vision.

Assessing the sustainability of the Siberian Federal District regions

2020 ◽  
Vol 18 (5) ◽  
pp. 891-908
Author(s):  
T.A. Smirnova
Keyword(s):  
Sustainable Development ◽  
Environmental Factors ◽  
Regional Development ◽  
Federal District ◽  
Integrated Approach ◽  
Siberian Federal District ◽  
The Sustainable Development ◽  
The Impact ◽  
Empirical Analyses

Subject. This article deals with the issues of functioning of the region as a system. Objectives. The article aims to identify the problems of the region's functioning as a system, develop methodological tools to monitor the sustainable development of the Siberian Federal District territories, and determine the the impact of socio-economic and environmental factors on the sustainable development of the region as a whole. Methods. For the study, I used the methods of theoretical, statistical, and empirical analyses taking into account an integrated approach. Results. The article reveals the impact of some individual components of regional development on the sustainability of the territorial system as a whole. Relevance. The results of the study can be used to analyze the sustainability of regions' development.

Directions of Accounting Environmental Factors for Forecasting Formation of Agroecosystems

2020 ◽  
pp. 31-35
Author(s):  
L.Z. Khalishkhova ◽  
◽  
A. Kh. Temrokova ◽  
I.R. Guchapsheva ◽  
K.A. Bogаtyreva ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Comparative Analysis ◽  
Environmental Factors ◽  
Environmental Safety ◽  
Logical Analysis ◽  
Management Decisions ◽  
The Sustainable Development ◽  
The Impact

Ensuring the sustainable development of agroecosystems requires research into the justification of the impact of environmental factors on the formation of territorial agroecosystems and identifies ways to take them into account in order to justify management decisions and ensure environmental safety. The main goal of the research within the article is to identify the most significant environmental factors in predicting the formation of agroecosystems. Provisions are devoted to the study of the laws governing the functioning of agroecosystems in order to increase their stability. The methods of comparative analysis, generalization, abstraction, logical analysis are applied. A number of provisions are formulated regarding ways to account for the influence of factors on the formation of key elements of agroecosystems.

Examining the Impact and Influencing Channels of Emission Trading Pilot Markets in China

2020 ◽  
Vol 11 (1) ◽  
pp. 136-136
Author(s):  
Qiong Wu ◽  
Kanittha Tambunlertchai ◽  
Pongsa Pornchaiwiseskul
Keyword(s):  
Total Factor Productivity ◽  
Co2 Emission ◽  
Carbon Emission ◽  
Emission Trading ◽  
Chinese Government ◽  
Synergy Effect ◽  
Factor Productivity ◽  
Plan Period ◽  
Carbon Emission Trading ◽  
The Impact

The global warming has become a serious issue in the world since the 1980s. The targets for the first commitment period of the Kyoto Protocol cover emissions of the six main greenhouse gasses (GHGs). China is the world's largest CO2 emitter and coal consumer and was responsible for 27.3 percent of the global total CO2 emission and 50.6 percent of the global total coal consumption in 2016 (BP, 2017). As China plays an important role in the global climate change, China has set goals to improve its environmental efficiency and performance. In 2011, the Chinese government for the first time announced an intent to establish carbon emission trading market in China. Eight regional emission trading schemes have been operating since 2013 (seven pilot markets during the 12th Five Year Plan period and one pilot market during the 13th Five Year Plan period) including provinces of Guangdong, Hubei, and Fujian, and cities of Beijing, Tianjin, Shanghai, Shenzhen, and Chongqing. The goal of these regional emission trading pilot markets is to help the government establish an efficient carbon emission trading scheme at national level. Some researchers have been focused on examining the impact of emission trading schemes in China using CGE model by constructing different scenarios and ex-ante analysis using data prior to emission trading pilot markets implementation. While this paper tries to conduct an ex-post analysis with data of 2005-2017 to evaluate the impact of emission trading pilot markets in China at provincial level using difference-in-difference (DID) model. By including both CO2 and SO2 as undesirable outputs to calculate Malmquist-Luenberger (ML) Index to measure green total factor productivity, this paper plans to evaluate the impact of carbon emission trading pilot markets in China via emission reduction, regional green development, synergy effect and influencing channels. This paper tries to answer the following research questions: (1) Do emission trading pilot markets reduce CO2 emission and increase regional green total factor productivity? (2) Is there any synergy effect from emission trading pilot markets? (3) What are the influencing channels of emission trading pilot markets? Keywords: Emission trading, CO2 emissions, Different-in-difference

Impact of Chatbot in Transforming the Face of Retailing- An Empirical Model of Antecedents and Outcomes

2019 ◽  
Vol 12 ◽  
Author(s):  
Kumari Anshu ◽  
Loveleen Gaur ◽  
Arun Solanki
Keyword(s):  
Research Work ◽  
Shopping Behavior ◽  
Model Framework ◽  
Shopping Experience ◽  
The Face ◽  
Strongly Agree ◽  
Different Characteristics ◽  
Work Done ◽  
The Impact ◽  
Self Administered Questionnaire

Chatbot has emerged as a significant resolution to the swiftly growing customer caredemands in recent times. Chatbot has emerged as one of the biggest technological disruption. Simply speaking, it is a software agent facilitating interaction between computers and humans in natural language. So basically, it is a simulated, intellectual dialogue agent functional in a range of consumer engagement circumstances. It is the easiest and simplest means enable interaction between the retailers and the customers. </p><p> • Purpose- Most of the research work done in this field is concerned with their technical aspects. The recent research on chatbot pay little attention to the impact it is creating on users’ experience. Through this work, author is making an effort to know the customer-oriented impact that the chatbot bear on the shoppers. The purpose of this study is to develop and empirically test a framework that identify the customer oriented attributes of chatbot and impact of these attributes on customers. </p><p> • Objectives- The study intends to bridge the gap between concepts and actual attributes and applications on the subject of Chatbot. The following research objectives can address the various aspects of Chatbot affecting the different characteristics of consumers shopping behaviors: a) Identify the various attributes of chatbot that bears an impression on consumer shopping behavior. b) Evaluate the impact of chatbot on consumer shopping behavior that leads to the development of chatbot usage and adoption among the customer. </p><p> • Design/Methodology/Approach – For the purpose of analysis, author has administered Factor analysis and Multiple regression using SPSS version 23 for identification of various attributes of Chatbot and knowing their impact on shoppers. A self-administered questionnaire from the review of literature is developed. Industry experts in the field of retailing and academician evaluate the questionnaire. Primary information from the respondents is gathered using this questionnaire. The questionnaire comprises of Likert scale on a scale of 1 to 5 where 1 stands for strongly disagree and 5 stands for strongly agree. Data is collected from 126 respondents, out of which 111 respondents were finally considered for study and analysis purpose. </p><p> • Findings – The empirical results show that the study identifies various attributes of chatbot like Trust, Usefulness, Satisfaction, Readiness to Use and Accessibility. It is also found that chatbot is really influencing the customers in providing them with shopping experience, which can be very helpful to the businesses for increasing the sales and creating repurchase intention among the customers. </p><p> • Originality/value – The recent research on chatbot pay little attention to the impact it is creating on customers who are actually interacting with it on regular basis. The research paper extends information for understanding and appreciating the customer oriented attributes of artificially intelligent Chatbot. In this regard, the author has developed a model framework and proposed the attributes identified. Through the work, author is also making an effort to test empirically the impact of the identified attributes on the shoppers.

scholarly journals Time Granularity Impact on Propagation of Disruptions in a System-of-Systems Simulation of Infrastructure and Business Networks

2021 ◽  
Vol 18 (8) ◽  
pp. 3922
Author(s):  
Mateusz Iwo Dubaniowski ◽  
Hans Rudolf Heinimann
Keyword(s):  
Recovery Time ◽  
System Of Systems ◽  
Future Research ◽  
Business Networks ◽  
Simulation Experiments ◽  
Huge Impact ◽  
High Level ◽  
Systems Simulation ◽  
Different Characteristics ◽  
The Impact

A system-of-systems (SoS) approach is often used for simulating disruptions to business and infrastructure system networks allowing for integration of several models into one simulation. However, the integration is frequently challenging as each system is designed individually with different characteristics, such as time granularity. Understanding the impact of time granularity on propagation of disruptions between businesses and infrastructure systems and finding the appropriate granularity for the SoS simulation remain as major challenges. To tackle these, we explore how time granularity, recovery time, and disruption size affect the propagation of disruptions between constituent systems of an SoS simulation. To address this issue, we developed a high level architecture (HLA) simulation of three networks and performed a series of simulation experiments. Our results revealed that time granularity and especially recovery time have huge impact on propagation of disruptions. Consequently, we developed a model for selecting an appropriate time granularity for an SoS simulation based on expected recovery time. Our simulation experiments show that time granularity should be less than 1.13 of expected recovery time. We identified some areas for future research centered around extending the experimental factors space.

scholarly journals Simulation of Energy Absorption Performance of the Couplers in Urban Railway Vehicles during a Heavy Collision

Machines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 91
Author(s):  
Sunghyun Lim ◽  
Yong-hyeon Ji ◽  
Yeong-il Park
Keyword(s):  
Reaction Force ◽  
Crash Test ◽  
Railway Vehicle ◽  
Buffer System ◽  
Railway Vehicles ◽  
Hydraulic Shock Absorber ◽  
Coupling Buffer ◽  
Absorption Performance ◽  
Different Characteristics ◽  
The Impact

Railway vehicles are generally operated by connecting several vehicles in a row. Mechanisms connecting railway vehicles must also absorb front and rear shock loads that occur during a train’s operation. To minimize damage, rail car couplers are equipped with a buffer system that absorbs the impact of energy. It is difficult to perform a crash test and evaluate performance by applying a buffer to an actual railway vehicle. In this study, a simulation technique using a mathematical buffer model was introduced to overcome these difficulties. For this, a model of each element of the buffer was built based on the experimental data for each element of the coupling buffer system and a collision simulation program was developed. The buffering characteristics of a 10-car train colliding at 25 km/h were analyzed using a developed simulator. The results of the heavy collision simulation showed that the rubber buffer was directly connected to the hydraulic shock absorber in a solid contact state, and displacement of the hydraulic buffer hardly occurred despite the increase in reaction force due to the high impact speed. Since the impact force is concentrated on the vehicle to which the collision is applied, it may be appropriate to apply a deformation tube with different characteristics depending on the vehicle location.

scholarly journals GPS Coordinates for Modelling Correlated Herd Effects in Genomic Prediction Models Applied to Hanwoo Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 2050
Author(s):  
Beatriz Castro Dias Cuyabano ◽  
Gabriel Rovere ◽  
Dajeong Lim ◽  
Tae Hun Kim ◽  
Hak Kyo Lee ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Genomic Prediction ◽  
Prediction Models ◽  
Phenotypic Expression ◽  
Genetic Evaluation ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Korean Cattle ◽  
Evaluation Programs ◽  
The Impact

It is widely known that the environment influences phenotypic expression and that its effects must be accounted for in genetic evaluation programs. The most used method to account for environmental effects is to add herd and contemporary group to the model. Although generally informative, the herd effect treats different farms as independent units. However, if two farms are located physically close to each other, they potentially share correlated environmental factors. We introduce a method to model herd effects that uses the physical distances between farms based on the Global Positioning System (GPS) coordinates as a proxy for the correlation matrix of these effects that aims to account for similarities and differences between farms due to environmental factors. A population of Hanwoo Korean cattle was used to evaluate the impact of modelling herd effects as correlated, in comparison to assuming the farms as completely independent units, on the variance components and genomic prediction. The main result was an increase in the reliabilities of the predicted genomic breeding values compared to reliabilities obtained with traditional models (across four traits evaluated, reliabilities of prediction presented increases that ranged from 0.05 ± 0.01 to 0.33 ± 0.03), suggesting that these models may overestimate heritabilities. Although little to no significant gain was obtained in phenotypic prediction, the increased reliability of the predicted genomic breeding values is of practical relevance for genetic evaluation programs.

scholarly journals Are Bacterio- and Phytoplankton Community Compositions Related in Lakes Differing in Their Cyanobacteria Contribution and Physico-Chemical Properties?

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 855
Author(s):  
Mikołaj Kokociński ◽  
Dariusz Dziga ◽  
Adam Antosiak ◽  
Janne Soininen
Keyword(s):  
Environmental Factors ◽  
Community Composition ◽  
Phytoplankton Community ◽  
Heterotrophic Bacteria ◽  
Bacterial Community Composition ◽  
Physical Factors ◽  
Research Attention ◽  
Phytoplankton Community Composition ◽  
The Impact ◽  
Bacteria Communities

Bacterioplankton community composition has become the center of research attention in recent years. Bacteria associated with toxic cyanobacteria blooms have attracted considerable interest. However, little is known about the environmental factors driving the bacteria community, including the impact of invasive cyanobacteria. Therefore, our aim has been to determine the relationships between heterotrophic bacteria and phytoplankton community composition across 24 Polish lakes with different contributions of cyanobacteria including the invasive species Raphidiopsis raciborskii. This analysis revealed that cyanobacteria were present in 16 lakes, while R. raciborskii occurred in 14 lakes. Our results show that bacteria communities differed between lakes dominated by cyanobacteria and lakes with minor contributions of cyanobacteria but did not differ between lakes with R. raciborskii and other lakes. Physical factors, including water and Secchi depth, were the major drivers of bacteria and phytoplankton community composition. However, in lakes dominated by cyanobacteria, bacterial community composition was also influenced by biotic factors such as the amount of R. raciborskii, chlorophyll-a and total phytoplankton biomass. Thus, our study provides novel evidence on the influence of environmental factors and R. raciborskii on lake bacteria communities.

scholarly journals Enhanced Viral Activity in the Surface Microlayer of the Arctic and Antarctic Oceans

2021 ◽  
Vol 9 (2) ◽  
pp. 317
Author(s):  
Dolors Vaqué ◽  
Julia A. Boras ◽  
Jesús Maria Arrieta ◽  
Susana Agustí ◽  
Carlos M. Duarte ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Food Web ◽  
Physicochemical Characteristics ◽  
The Arctic ◽  
Microbial Food Web ◽  
Surface Microlayer ◽  
Polar Regions ◽  
Nutrient Inputs ◽  
Viral Activity ◽  
The Impact

The ocean surface microlayer (SML), with physicochemical characteristics different from those of subsurface waters (SSW), results in dense and active viral and microbial communities that may favor virus–host interactions. Conversely, wind speed and/or UV radiation could adversely affect virus infection. Furthermore, in polar regions, organic and inorganic nutrient inputs from melting ice may increase microbial activity in the SML. Since the role of viruses in the microbial food web of the SML is poorly understood in polar oceans, we aimed to study the impact of viruses on prokaryotic communities in the SML and in the SSW in Arctic and Antarctic waters. We hypothesized that a higher viral activity in the SML than in the SSW in both polar systems would be observed. We measured viral and prokaryote abundances, virus-mediated mortality on prokaryotes, heterotrophic and phototrophic nanoflagellate abundance, and environmental factors. In both polar zones, we found small differences in environmental factors between the SML and the SSW. In contrast, despite the adverse effect of wind, viral and prokaryote abundances and virus-mediated mortality on prokaryotes were higher in the SML than in the SSW. As a consequence, the higher carbon flux released by lysed cells in the SML than in the SSW would increase the pool of dissolved organic carbon (DOC) and be rapidly used by other prokaryotes to grow (the viral shunt). Thus, our results suggest that viral activity greatly contributes to the functioning of the microbial food web in the SML, which could influence the biogeochemical cycles of the water column.

scholarly journals The impact of environmental variables on the spread of COVID-19 in the Republic of Korea

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yong Kwan Lim ◽  
Oh Joo Kweon ◽  
Hye Ryoun Kim ◽  
Tae-Hyoung Kim ◽  
Mi-Kyung Lee
Keyword(s):  
Environmental Factors ◽  
Virus Disease ◽  
Environmental Parameters ◽  
Environmental Data ◽  
Republic Of Korea ◽  
Metropolitan Region ◽  
Health Concern ◽  
Ozone Level ◽  
The Republic ◽  
The Impact

AbstractCorona virus disease 2019 (COVID-19) has been declared a global pandemic and is a major public health concern worldwide. In this study, we aimed to determine the role of environmental factors, such as climate and air pollutants, in the transmission of COVID-19 in the Republic of Korea. We collected epidemiological and environmental data from two regions of the Republic of Korea, namely Seoul metropolitan region (SMR) and Daegu-Gyeongbuk region (DGR) from February 2020 to July 2020. The data was then analyzed to identify correlations between each environmental factor with confirmed daily COVID-19 cases. Among the various environmental parameters, the duration of sunshine and ozone level were found to positively correlate with COVID-19 cases in both regions. However, the association of temperature variables with COVID-19 transmission revealed contradictory results when comparing the data from SMR and DGR. Moreover, statistical bias may have arisen due to an extensive epidemiological investigation and altered socio-behaviors that occurred in response to a COVID-19 outbreak. Nevertheless, our results suggest that various environmental factors may play a role in COVID-19 transmission.

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