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Data Driven Approaches for Environmental Sustainability

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B: Energy and Environment".

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 16788

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Special Issue Editors

Prof. Dr. Gorm Bruun Andresen

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Guest Editor

Aarhus Univ, Dept Engn, Inge Lehmanns Gade 10, DK-8000 Aarhus C, Denmark
Interests: renewable energy; thermodynamics

Dr. Neeraj Bokde

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Guest Editor

Aarhus Univ, Dept Engn, Inge Lehmanns Gade 10, DK-8000 Aarhus C, Denmark
Interests: time series analysis; software package development; prediction applications in natural entities such as wind energy
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Special Issue Information

Dear Colleagues,

The “three pillars of sustainability” concept, which encompasses social, economic, and environmental sustainability, is well-known and very important in society. However, currently, greater importance is given to social and economic development at the cost of environmental sustainability. In recent decades, major topic discussed in this area have included the harvesting of renewable resources, the depletion of non-renewable resources, and the creation of pollution. Recent advancements in data analysis techniques and methodologies along with higher-level computational infrastructures have presented many new dimensions to observe patterns and provide more effective solutions. For this Special Issue of Energies on “Data-driven approaches for environmental sustainability”, we invite authors to submit articles on, but not limited to, the following topics: data-analysis-driven analysis, policies, and case studies of environmental parameters such as renewable energy, air and water pollution, and water leakage management; enhancement of data analysis techniques such as predictions, time series forecasting, data imputations, optimization methodologies, and their applications in environmental sustainability; data collection, data cleaning, and novel visualization techniques; data analysis tools, software, and packages for use in environmental sustainability.

Prof. Dr. Gorm Bruun Andresen
Dr. Neeraj Bokde
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

environment
energy
pollution
wind
solar
renewable energy generation
time series analysis
data mining
water resource management
environment sustainability

Published Papers (3 papers)

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Research

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24 pages, 1254 KiB

Open AccessArticle

ForecastTB—An R Package as a Test-Bench for Time Series Forecasting—Application of Wind Speed and Solar Radiation Modeling

by Neeraj Dhanraj Bokde, Zaher Mundher Yaseen and Gorm Bruun Andersen

Energies 2020, 13(10), 2578; https://doi.org/10.3390/en13102578 - 19 May 2020

Cited by 62 | Viewed by 4196

Abstract

This paper introduces an R package ForecastTB that can be used to compare the accuracy of different forecasting methods as related to the characteristics of a time series dataset. The ForecastTB is a plug-and-play structured module, and several forecasting methods can be included with simple instructions. The proposed test-bench is not limited to the default forecasting and error metric functions, and users are able to append, remove, or choose the desired methods as per requirements. Besides, several plotting functions and statistical performance metrics are provided to visualize the comparative performance and accuracy of different forecasting methods. Furthermore, this paper presents real application examples with natural time series datasets (i.e., wind speed and solar radiation) to exhibit the features of the ForecastTB package to evaluate forecasting comparison analysis as affected by the characteristics of a dataset. Modeling results indicated the applicability and robustness of the proposed R package ForecastTB for time series forecasting. Full article

(This article belongs to the Special Issue Data Driven Approaches for Environmental Sustainability)

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29 pages, 1549 KiB

Open AccessArticle

Environmental Sustainability in City Logistics Measures

by Jagienka Rześny-Cieplińska and Agnieszka Szmelter-Jarosz

Energies 2020, 13(6), 1303; https://doi.org/10.3390/en13061303 - 11 Mar 2020

Cited by 18 | Viewed by 3821

Abstract

Sustainable urban transport is fundamental not only for economic growth but also for the environmental protection, thus all logistics activities within the cities should be organized in a way to be environmentally friendly. The article aims at presenting the environmental sustainability of city logistics measures from different stakeholder perspectives. In the paper, a multi-method approach was implemented: literature review, text analysis, text mining, and statistical analysis. The paper presents how the stakeholders perceive urban logistics, if they see the need for coordination of its elements, who should be responsible for it, and what areas are the most important for them. The main task of this study is to recognize the priorities of different stakeholders. In consequence, the final effect of this article is an insight that is valuable not only for the local authorities but for many stakeholders, groups operating within the city that are and in many cases cooperating within the framework of creating sustainable urban mobility plans. Full article

(This article belongs to the Special Issue Data Driven Approaches for Environmental Sustainability)

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Review

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23 pages, 1551 KiB

Open AccessReview

Smart Water Technology for Efficient Water Resource Management: A Review

by Aditya Dinesh Gupta, Prerna Pandey, Andrés Feijóo, Zaher Mundher Yaseen and Neeraj Dhanraj Bokde

Energies 2020, 13(23), 6268; https://doi.org/10.3390/en13236268 - 27 Nov 2020

Cited by 44 | Viewed by 8060

Abstract

According to the United Nation’s World Water Development Report, by 2050 more than 50% of the world’s population will be under high water scarcity. To avoid water stress, water resources are needed to be managed more securely. Smart water technology (SWT) has evolved for proper management and saving of water resources. Smart water system (SWS) uses sensor, information, and communication technology (ICT) to provide real-time monitoring of data such as pressure, water ow, water quality, moisture, etc. with the capability to detect any abnormalities such as non-revenue water (NRW) losses, water contamination in the water distribution system (WDS). It makes water and energy utilization more efficient in the water treatment plant and agriculture. In addition, the standardization of data format i.e., use of Water Mark UP language 2.0 has made data exchange easier for between different water authorities. This review research exhibits the current state-of-the-art of the on-going SWT along with present challenges and future scope on the mentioned technologies. A conclusion is drawn that smart technologies can lead to better water resource management, which can lead to the reduction of water scarcity worldwide. High implementation cost may act as a barrier to the implementation of SWT in developing countries, whereas data security and its reliability along with system ability to give accurate results are some of the key challenges in its field implementation. Full article

(This article belongs to the Special Issue Data Driven Approaches for Environmental Sustainability)

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