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Electronics
Special Issues
Modeling and Control of Environmental Systems: Theory and Application
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Modeling and Control of Environmental Systems: Theory and Application

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 4753

Special Issue Editors

Dr. Claudio Carnevale

E-Mail Website
Guest Editor
DIMI-Sede Branze, Via Branze, University of Brescia, 3825121 Brescia, Italy
Interests: control systems; air quality management; air quality planning; nonlinear modelling; uncertainty analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Enrico Turrini

E-Mail Website
Guest Editor
DIMI-sede Branze via Branze, University of Brescia, 3825121 Brescia, Italy
Interests: nonlinear modeling; environmental modeling; control systems; decision models for planning and control of complex systems

Special Issue Information

Dear Colleagues,

In recent years, research in environmental systems has become increasingly important, involving a number of disciplines such as engineering, information science, physics, mathematics, economy, biology, and social sciences.

The complexity of the involved phenomena usually forces researchers to split the problem at hand into two strongly related phases: modeling and control.

In terms of modeling, the complexity is due to the fact that environmental systems are often nonlinear, distributed, and affected by (high) uncertainties in both input and knowledge of the involved phenomena.
From the control design point of view, several challenges arise from (1) the complexity of the model, which often pushes to introduce approximations (i.e., linearity), heavily affecting the performances, and (2) the pointwise nature of the available measurements for the variable to be controlled.

This Special Issue is going to include papers addressing all the scientific challenges related to environmental systems modeling and control. Papers related to air quality, water management, and climate change, focusing on theoretical results and/or applications, are welcome.

The Special Issue will investigate the following topics, but contributions in related fields will also be considered:

  • Environmental systems modelling, analysis and control
  • Data-driven environmental/climate change modeling
  • Climate change analysis
  • Air quality modelling, control and planning
  • Water management

Prof. Dr. Claudio Carnevale
Dr. Enrico Turrini
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. Electronics 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 2400 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

  • Environmental systems
  • System modeling
  • Data-driven modeling
  • System control
  • Air quality
  • Water management

Published Papers (2 papers)

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Research

17 pages, 3122 KiB  
Article
A Short-Term Air Quality Control for PM10 Levels
by Claudio Carnevale, Elena De Angelis, Franco Luis Tagliani, Enrico Turrini and Marialuisa Volta
Electronics 2020, 9(9), 1409; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9091409 - 01 Sep 2020
Cited by 6 | Viewed by 1902
Abstract
In this work, the implementation and test of an integrated assessment model (IAM) to aid governments to define their short term plans (STP) is presented. The methodology is based on a receding horizon approach where the forecasting model gives information about a selected [...] Read more.
In this work, the implementation and test of an integrated assessment model (IAM) to aid governments to define their short term plans (STP) is presented. The methodology is based on a receding horizon approach where the forecasting model gives information about a selected air quality index up to 3 days in advance once the emission of the involved pollutants (control variable) are known. The methodology is fully general with respect to the model used for the forecast and the air quality index; nevertheless, the selection of these models must take into account the peculiarities of the pollutants to be controlled. This system has been tested for particulate matter (PM10) control over a domain located in Northern Italy including the highly polluted area of Brescia. The results show that the control system can be a valuable asset to aid local authorities in the selection of suitable air quality plans. Full article
(This article belongs to the Special Issue Modeling and Control of Environmental Systems: Theory and Application)
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16 pages, 3467 KiB  
Article
Source Apportionment and Integrated Assessment Modelling for Air Quality Planning
by Elena De Angelis, Claudio Carnevale, Enrico Turrini and Marialuisa Volta
Electronics 2020, 9(7), 1098; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9071098 - 05 Jul 2020
Cited by 2 | Viewed by 2325
Abstract
In Northern Italy a large fraction of the population is exposed to PM10 and PM2.5 concentrations that exceed the European limit values and the stricter WHO air quality guidelines. For this reason, in 2017 four Regions (Piemonte, Lombardia, Veneto, and Emilia Romagna) and [...] Read more.
In Northern Italy a large fraction of the population is exposed to PM10 and PM2.5 concentrations that exceed the European limit values and the stricter WHO air quality guidelines. For this reason, in 2017 four Regions (Piemonte, Lombardia, Veneto, and Emilia Romagna) and the national Ministry of the Environment adopted a set of joint measures, namely the “Po Basin air quality plan”. The plan mainly tackles emission from road transport, residential heating, and agriculture. Air quality plans at regional and local scale are usually implemented defining a set of emission abatement measures, starting from experts’ knowledge. The aim of this work is to define a methodology that helps decision makers in air quality planning, combining two different approaches: Source-Apportionment techniques (SA) and Integrated Assessment Modelling (IAM). These techniques have been applied over a domain in Northern Italy to analyze the contribution of emission sources on PM10 concentration and to compute an optimal policy, obtained through a multi-objective optimization approach that minimizes both the PM10 yearly average concentration and the policy implementation costs. The results are compared to the Po Basin air quality plan impacts. The source-apportionment technique and the IAM optimization approach show intervention priorities in three main sectors: residential heating, agriculture, and road transport. The Po Basin air quality plan is effective in reducing PM10 concentrations, but not efficient, as a matter of fact the cost-effective policy at the same cost has a higher impact on air quality and on greenhouse gases emissions reduction. Full article
(This article belongs to the Special Issue Modeling and Control of Environmental Systems: Theory and Application)
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