CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 61, 2017 

A publication of 

 

The Italian Association 
of Chemical Engineering 
Online at www.aidic.it/cet 

Guest Editors: Petar S Varbanov, Rongxin Su, Hon Loong Lam, Xia Liu, Jiří J Klemeš 
Copyright © 2017, AIDIC Servizi S.r.l. 

ISBN 978-88-95608-51-8; ISSN 2283-9216 

Simulation of Power Plant Environmental Impacts within the 

Extended Marine Framework 

Agostino G. Bruzzonea,*, Marina Masseia, Andrea Reverberib, Marina Cardellic, 

Riccardo di Matteoc, Giovanni Luca Maglionec 

aDIME, University of Genova, via Opera Pia 15, 16145 Genova, Italy 
bDCCI, University of Genova, via Dodecaneso 31, 16146 Genova, Italy  
cSimulation Team, via Molinero 1, 17100 Savona, Italy 

 agostino@itim.unige.it 

This paper proposes the use of Modelling and Simulation to analyse the different Environmental Impacts of 

Industrial Facilities with special attention to Power Plant located within the Extended Maritime Framework. The 

approach proposed is based on combining different simulation approaches to be able to reproduce the 

phenomena affecting this context in a comprehensive way. The simulation experimental results are dynamically 

presented and updated within a Synthetic Environment, based on a Serious Game, in order to be able to 

augment the virtual representation with additional information. It is proposed a case study related to a Power 

Plant including different Gas Turbines located in front the coast and the scenario include the evaluation of the 

emissions on the Atmosphere, Sea Water and Ground, the inclusions on these domains as well as their impact 

on the flora, fauna and social layers. 

1. Introduction 

The concept of sustainability is evolving along years therefore the related basic foundations are probably still 

valid: “the sustainability of ecosystems on which the global economy depends must be guaranteed and the 

economic partners must be satisfied that the basis of exchange is equitable” (Brundtland, 1987).   

So to address this point it is fundamental to evaluate in comprehensive way the whole ecosystems including 

human installations (Liu et al., 2008). The complexity due to the explosive nature of the context, the long term 

effects of the decisions overpassing human horizons and the presence of multiple interactions and stochastic 

factors make it evident the necessity to move out of qualitative approaches and to adopt quantitative methods 

(Belcher et al., 2004). Obviously from this point of view Modelling and Simulation (M&S) result a strategic 

science to study these problems (Swart et al., 2004). Indeed, environmental impacts (EIs) of industrial 

processes, considering both pollution and acute major hazards, are very complex due to the fact that involve a 

myriad of factors and elements related to intrinsic chemical properties (Reverberi et al., 2016) and physical 

aspects (Fabiano et al., 2015) whose mutual interactions are still not very well known. Despite these facts, the 

possibility of model relationships between environmental impacts, industrial plant characteristics and operational 

modes could strongly improve the understanding of these phenomena; indeed, dependency and combined 

effects could be estimated by designing a hierarchical relationship model (Bruzzone et al., 2010). By utilizing a 

risk matrix and defining a target line of consequence-frequency combinations, it is possible to perform a cost-

benefit assessment and answer the question how safe is safe enough, considering both acute risk and chronic 

environmental risk as well as environmental sustainability (Vairo et al., 2017). In the past, the authors developed 

these models focusing on Logistics as well as on Port Operations supporting the development of Green 

Solutions for these frameworks (Bruzzone et al., 2009). Recently, the evolution of policies on Greenhouse 

Gases had big impacts on industrial plants configuration, considering that several energy saving systems and 

policies, that are consolidated and already operational, have to be dismissed due to the change in tax policies 

(Zhang, 2016); this situation leads sometimes to strange solutions that are not really “energy saving”, but result 

effective in reducing taxes and fees (Burtraw et al., 2014). 

                               
 
 

 

 
   

                                                  
DOI: 10.3303/CET1761208

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Please cite this article as: Bruzzone A.G., Massei M., Reverberi A., Cardelli M., di Matteo R., Maglione G.L., 2017, Simulation of power plant 
environmental impacts within the extended marine framework, Chemical Engineering Transactions, 61, 1261-1266  DOI:10.3303/CET1761208  

1261



 

Figure 1: Models of the Power Plant EIs on the EMF 

2. Simulation background 

Due to these reasons, the authors are active in developing models to simulate the whole process and to address, 

in comprehensive way, the EIs over a complex framework; in this case it is proposed to study the Extended 

Maritime Framework (EMF) including air, underwater, sea surface, land and coast, etc (Bruzzone, 2014). In the 

past, the authors addressed this context in relation to operations with UxV (Unmanned multidomain Vehicles) 

that were integrated over a heterogeneous network (Bruzzone et al., 2016a); by the way these studies could be 

useful also in this case in order to develop future sensor networks with autonomous capabilities to investigate 

on symptoms and alerts: e.g. sending an Autonomous Underwater Vehicle, AUV, to check diffusion of emission 

at different depth in the sea. However, this paper proposes a case study related to a power plant to be simulated 

to estimate its EIs by adopting a combined and innovative modelling approach. The motivation to conduct this 

scientific study is to develop a comprehensive model of Environmental Impacts such as emissions in marine 

environment of a specific Power Plant with multiple Gas Turbine, therefore it is evident the possibility to adapt 

approach to many different cases of Industrial plants. Among the viable alternative systems to be evaluated, the 

model should allow to support a feasibility analysis related to an innovative process that redirects CO2 emissions 

in Marine Environment. These simulators are addressing a wide spectrum of applications such as industrial 

plant engineering, emergency management, industrial processes, joint operations, homeland security and 

defence, logistics, innovative technologies, autonomous systems and decision support solutions. Indeed, 

Simulation Team is a non-profit organization involving individuals and organizations where different modules 

such as Green Log, MOSES and IDRASS (Bruzzone et al., 2013) have been implemented. The authors propose 

here to adopt the MS2G paradigm (Modeling, Interoperable Simulation and Serious Game) that allows to 

combine different models by adopting simulation interoperability standards and to guarantee the MMI (Main 

Machine Interface) through the Serious Game approach. Indeed, Serious Game, by immersive technologies 

and properly design representations, is able to improve usability and understanding for simulation users through 

a physical and emotional engagement. 

In a different case study, the authors analysed a Power Plant Emission within a special CAVE (Cave Automatic 

Virtual Environment) developed ad hoc by Simulation Team in the frame of above mentioned MS2G solutions. 

This CAVE is named SPIDER (Simulation Practical Immersive Dynamic Environment for Reengineering) and is 

able to support distributed interactive simulation by combining continuous modelling of hazardous material spills 

and contaminations of air and soil with discrete event simulation about plant and autonomous asset behaviours 

(Bruzzone et al., 2016b).  

3. Simulation models 

The simulation to be developed in this research track adopts the HLA standards for interoperability (Kuhl et al., 

1999); this approach enables the possibility to create a Federation of simulator that interoperate. In this way, it 

could be possible to federate different kind of models within the same context such as continuous simulation, 

discrete event simulation, combined simulation and system dynamics (Zacharewicz et al., 2005). Currently the 

authors are planning to combine different models addressing the different elements to be simulated as proposed 

in Figure 1. The proposed simulation uses different simulation techniques for reproducing plant operations, 

emissions, diffusions, EIs impact estimation and costs and regulation respect analysis; indeed, continuous 

simulation of emissions and diffusions in the marine environment are combined, for instance, with discrete event 

simulation of plant processes and system dynamics related. In order to complete successfully the Validation, 

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Verification and Accreditation (VV&A) of the Simulator it is necessary to address different aspects and to develop 

the corresponding models as summarized in the following: 

Plant Simulation: 

The model of the plant and its operations is a crucial part of the simulation and should be based on a technical 

process (Ylén et al., 2005); by adopting MS2G paradigm it is possible to include a simplified plant meta-model 

during preliminary tests and experimentations. 

This approach could allow to speed up the development and VV&A as well as to reduce the computational 

efforts for applying DOE (Design of Experiments) for optimization (Montgomery, 2008). On the opposite, further 

investigation on optimized configurations could be carried out substituting the meta-models with detailed plant 

simulator within the High-Level Architecture (HLA) Federation.  

Modeling Different Power Plant Emissions : 

The plant emissions should be identified and specific models should be developed to estimate their nature and 

flow rates (Bottenheim, 1982) and several year later (Lefebvre, 1998); for instance it should be possible to 

estimate the quantities of CO2 and other components dispersed in regular configuration within the environment, 

modelling the relationships among emissions and different plant configurations; these models should consider 

the emission nature as well as the related characteristics under the different operational modes of the plant and 

along the years. 

Modelling the EIs and their Diffusion in the EMF: 

It is necessary to create diffusion models that should consider boundary conditions (e.g. temperature, wind, 

current, etc.) as well as release methods to estimate the diffusion of the emission in the Extended Maritime 

Framework (Moussiopoulos, 1990); these components should also take care of modelling the interaction of the 

EI within the sea water, terrain and Air in EMF, the model should estimate how much part of them dissolves in 

water and how much part still remains in it. An appropriate model should take into account the diffusivity 

phenomena, the interactions with the electrolytes contained in the environment (e.g. seawater) as well as the 

relevant equilibria of dissolved chemical elements. 

The boundary conditions from this point of view represent crucial factors: for instance the effect of tides and 

currents affect the concentration profiles along the coast and in the deep sea and should be estimated by proper 

models. In similar way it is necessary to consider the medium and long terms of EI that will be dispersed in the 

different EMF domains according to thermodynamics of vapor-liquid equilibria. 

Models of the EI impacts on EMF Flora 

These models should cover the impacts of different EIs and emissions on the flora in terms of health status 

within the Extended Maritime Framework (Aleem, 1972) later (Suresh et al., 1993) and the most recently (Ou et 

al., 2016). For instance it should be necessary to develop models able to foresee the CO2 concentration in water 

and its effects on algae population evolution, growth, reproduction as well as on the potential changes in their 

biological processes. 

Models of the EI impacts on Marine Fauna 

The adaptability of the EMF fauna to EI is another crucial component to be model and one of the most 

challenging in terms of environmental sustainability and eco-compatibility (Aleem, 1972) later (Suresh et al., 

1993) and recently (Ou et al., 2016). For instance, a concentration map of emissions in water will be related to 

their biological effects on different living species to ensure the respect of the marine ecosystem. As for Marine 

Flora, these models should estimate the changes on growth, reproduction and biological processes concerning 

vertebrates and invertebrates and the impacts that these changes might have on other symbiotic species, 

humans included. 

Economic Models 

The economic models should deal with estimation of profits and costs related to different plant solutions and 

operational models, reproducing dynamically the market evolution and potential trends (Benz et al., 2009). Risk 

reduction strategies aiming at reducing frequency or mitigating the magnitude of the impact on the environment 

can be categorized as engineered active and passive; managerial/procedural; inherent (Palazzi et al., 2015). 

The estimation of fixed costs related to different plant configurations and/or systems and subsystems will be 

required to analyse the different solutions, therefore it is also possible to adopt a reverse engineering approach 

to estimate the threshold levels for feasibility of different solutions. 

Modelling Policies, Taxations, Rules and Regulations 

The Rules, Taxations and Regulations should be included in the model in order to estimate the taxes and fees 

related to different plant configurations and operational modes (Rafieisakhaei et al., 2016); in addition, this allow 

also to estimate the dynamical respect of threshold levels and policies along the plant life cycle; it is important 

to outline that these aspects deal with International and National regulations and the related models should be 

tailored for the different areas. The structure of the models should allow to change these conditions and 

parameters in order to reproduce different scenarios. These elements are today very important in order to 

understand the feasibility of plant refurbishments and changes according to economic advantages and 

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compliances with existing laws and best practices. It is even fundamental to evaluate the effective advantage in 

terms of emission calculation in the environment and the regulations to be considered for the project feasibility. 

4. Outline of the architecture model 

The general architecture of the model includes different simulators to be federated together each one including 

some of the mentioned models; the relevant simulators are shortly introduced in the following: 

VAED (Virtual Aided Engineering & Design) is a combined simulation (continuous and discrete event simulation) 

that reproduce the power plant principal and secondary systems as well as auxiliary plants and related 

processes, including thermodynamics and chemical reactions (Bruzzone et al., 1997). IDRASS (Immersive 

Disaster Relief and Autonomous System Simulation) is a MS2G (Modelling, Interoperable Simulation & Serious 

Game) environment combining discrete events and continuous simulation originally devoted to reproducing fall-

out and spin off of hazardous material in industrial plants; this system could be tailored to reproduce dynamics 

of emissions and diffusion into the EMF during regular operations (Bruzzone et al., 2016b). GREENLOG PORT 

(Green Logistics for Ports) is a hybrid simulator allowing to consider the different EIs and to combine them based 

on a hierarchical structure (Bruzzone et al., 2010); the model has been developed for analysing Port Logistics 

and Processes, including ship emissions in air and sea and could be adapted to address this specific case 

study. MOSES (Modelling Sustainable Environments through Simulation) is a model based on system dynamics 

able to reproduce the impact of actions over an urban environment. This model could consider the EIs of different 

Power Plant configurations according to human, economic, environmental and social sustainability (Bruzzone 

et al., 2013). JESSI (Joint Environment for Serious Games, Simulation and Interoperability) is an interoperable 

simulation environment applied several time to the EMF (Bruzzone et al., 2016a); currently some kinds of marine 

fauna have been already successfully introduced (e.g. birds and sea mammals); due to these reason the models 

of marine flora and fauna could be introduced in this simulation; in addition it could be possible to reproduce 

and to estimate capabilities, costs and effectiveness on the use of AUV (Autonomous Underwater Vehicles) and 

UAV (Unmanned Aerial Vehicles) as solution to monitor and investigate the environmental impacts.  

These simulators can interoperate and are integrated also with other solutions devoted to improving usability 

and VV&A through innovative MMI such as: 

SPIDER (Simulation Practical Immersive Dynamic Environment for Reengineering) is an innovative Interactive 

CAVE (Cave Automatic Virtual Environment) developed by Simulation Team able to immerse multiple decision 

makers and/or scientists into a complex interoperable simulation. The basic configuration is compact (just 2m x 

2m x 2.6m) and could be installed within a standard High Cube Container; SPIDER is fully compatible with any 

interoperable simulator and it has been already used to carried out experimentations with IDRASS and JESSI. 

Indeed, the SPIDER is interactive also through touch screen technology and it is fully immersive including sound 

and motion. ARTEM (Augmented Reality TErrain interoperable Module) is an interoperable HLA module 

designed to be integrated in a MS2G (Modelling, interoperable Simulation & Serious Game) systems. The 

results of the simulation are dynamically presented over smartphone and mobile devices providing them to the 

user in real-time and geo-referenced framework (Bruzzone et al., 2016b). 

5. Applicative case-study 

Preliminary results on experimental error estimations due to the stochastic factors related to CO2 emissions are 

reported in Figure 2.  

 

Figure 2: ANOVA on CO2 emission for this case study. 

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The time evolution of the MSpE (Mean Square pure Error) is proposed as ANOVA (Analysis of Variance) in 

order to conduct the dynamic VV&A on the simulator (Bruzzone et al, 2016a); this approach allows to estimate 

its confidence bands expressed by the following relationship: 

𝑀𝑆𝑝𝐸(𝑡,𝑟, 𝑗) =
∑ [𝑌𝑗,𝑖(𝑡)−�̅�𝑗(𝑡)]

2𝑟
𝑖=1

𝑟 − 1
 (1) 

where MSpE(t,r,j) is the mean square pure error of j-th target function at t time with r replications, r is the number 

of replications obtained by running the simulation on same boundary conditions by changing only the random 

seeds, j is the j-th target function (in the proposed case emissions of CO2) and Yj,i (t) is the value of the j-th 

target function on the i-th replication carried out by the simulator at t time. 

Moreover, �̅�𝑗(𝑡) =
∑ [𝑌𝑗,𝑖(𝑡)]
𝑟
𝑖=1

𝑟
   and  �̿�𝑗 =

∫
∑ [𝑌𝑗,𝑖(𝑡)]
𝑟
𝑖=1

𝑟
𝑑𝑡

𝑡𝑒
𝑡𝑠

𝑡𝑒−𝑡𝑠
 , where �̅�𝑗(𝑡) is the average value of the j-th target 

function over r replications carried out by the simulator at t time, �̿�𝑗 is the average value of the j-th target 

function over r  replications carried out by the simulator along the whole simulation and te,ts are the ending and 

starting time of the simulation. 

𝐶𝐵(𝑡,𝑗) = +2𝑡,𝑟−1√𝑀𝑆𝑝𝐸(𝑡,𝑟, 𝑗)                                    (2) 

𝐶𝐵𝑝(𝑡,𝑗) =

{
 
 

 
 �̅�𝑗(𝑡) <> 0

𝐶𝐵(𝑡,𝑗)

�̅�𝑗(𝑡)

�̅�𝑗(𝑡) = 0
�̿�𝑗(𝑡) <> 0

𝐶𝐵(𝑡,𝑗)

�̿�𝑗(𝑡)

�̿�𝑗(𝑡) = 0 0

 (3) 

CB(t,j) is the confidence band amplitude at t time for j-th target function and CBp(t,j) is the confidence band 

amplitude expressed in percentage respect average value of the j-th target function at t time. 

The analysis has been conducted by using a simplified meta-model in VAED and confirms good level of 

experimental error and confidence band even after few simulated months of operations; obviously these results 

cannot be generalized depending on the scenario adopted for the operational use of the Power Plant, but the 

set of tests could be easily repeated to update the analysis. The authors are currently extending the experimental 

analysis to cover all different target functions related to the EI on different layers. 

6. Conclusions 

The proposed approach guarantees the possibility to investigate the impact of different aspects related to plant 

engineering solutions as well as to operational models; by this approach it becomes possible to understand 

clearly the effects of these elements on the multiple layers (e.g. air, water, flora, fauna, social, economic) of the 

Extended Maritime Framework. This research represents a first step towards the development of an 

experimentation on a more extended case study; until now the authors completed the identification of models 

and simulators to be used as well as the overall architecture. In the future, this modelling approach will be used 

to conduct experimentations for investigating the most effective solutions for CO2 storage taking into account 

their environmental impacts on ground, sea and air factors and also considering their sustainability in terms of 

economic aspects and technical reliability. 

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