The Endless Possibilities of Modelling of Toxic Chemical Warfare

Agents and Possible Impacts of Their Release in Water Sensitive Areas

NIKOLAOS STASINOPOULOS1, MICHAIL CHALARIS1, ANASTASIA TEZARI1,

KALLIOPI KRAVARI2

1Department of Chemistry,

International Hellenic University,

Kavala,

GREECE

2Department of Production Engineering and Management,

International Hellenic University,

Thessaloniki,

GREECE

Abstract: - Nerve agents are chemical compounds that constitute chemical weapons with many effects on

human health as well as the environment. In this work, an analysis of the properties of several nerve agents and

their dispersion in aquatic ecosystems is proposed, by exploring the possibilities of state-of-the-art

computational methods, such as molecular dynamic simulations, quantitative structure-activity relationship

models such and other simple computational models for the simulation of a water ecosystem.

Key-Words: - water terrorism, nerve agents, Molecular Dynamics simulations, risk assessment, aquatic

ecosystems, QSAR Models.

Received: May 9, 2023. Revised: July 24, 2023. Accepted: September 17, 2023. Published: October 10, 2023.

1 Introduction

The understanding of nerve agents may be quite

critical, as they constitute chemical weapons and

part of the weapons of mass destruction with

multiple effects on human health and the

environment. This work explores an original and

unique idea, by equally combining theoretical

aspects, molecular simulation techniques, and

concepts for the first time, with practical

applications for safety on a large scale, proposing a

complete analysis and study will be carried out for a

set of liquid nerve agents, identifying their structure

and properties, by using classical molecular

simulations in combination with machine learning.

Additionally, the well-known Quantitative and

qualitative structure–activity relationships (QSARs)

could be an excellent tool to understand the

chemical behavior of these substances.

As a final step, the modelling of the effects of

their release in water sensitive areas is proposed.

Simple models could be used to simulate the

ecosystems of water sensitive areas and demonstrate

the possible consequences of a release, [1].

The impact of molecular dynamics (MD)

simulations in molecular modeling, particularly in

the realm of substance research, has witnessed a

substantial expansion in recent years. Molecular

simulations serve as highly valuable tools for

gaining profound insights into the physicochemical

properties of nerve agents, ultimately facilitating the

development of innovative methods for their early

detection, protection, and decontamination.

These simulations meticulously capture the

behavior of nerve agents at the atomic level,

providing a remarkably detailed temporal resolution.

They have demonstrated their worth in unraveling

the functional mechanisms of nerve agents and

aiding in the resolution of complex chemical

challenges. These simulations leverage the

techniques of theoretical chemistry, integrated into

efficient computer programs, to calculate the

structures, interactions, and properties of molecules.

The potency of these simulations lies in several

aspects. Firstly, they meticulously record the

position and motion of every atom at each point in

time, a feat challenging to achieve through any

experimental technique. Secondly, the simulation

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conditions are precisely defined, allowing for

precise control over numerous structural and

dynamic properties. By comparing simulations

conducted under varying conditions, one can discern

the effects of a wide array of molecular

perturbations.

Quantitative and qualitative structure-activity

relationships, commonly known as QSARs,

represent a modeling approach which serves both as

a fundamental framework and a toolkit for over a

century. QSARs can be applied across various

domains within the natural sciences, as a means to

acquire insights and generate new knowledge by

establishing connections between molecular or

material structures and chemistry-related

phenomena. QSAR has its foundational origins

rooted in physical organic chemistry, contributing

significantly to our understanding of chemical

reactivity. The enduring relevance of QSAR is

further exemplified by its achievements in the

systematic examination of the adverse outcomes

caused by chemical substances. The multifaceted

roles of QSAR as a scientific methodology have

distinguished it as a unique approach for the

acquisition of novel insights.

Finally, anomalous relaxation, nonlinear

transport phenomena, and field-induced effects in

composite and biological materials, as well as in

materials undergoing internal physical and chemical

reactions and phase transitions, have garnered

significant attention from researchers and medical

professionals. These phenomena are ubiquitous in

nature and find active application in advanced

industrial and biomedical technologies, [2].

2 Nerve Agents

2.1 Effects of Nerve Agents

Chemical weapons usage dates back to antiquity,

however, they became weapons of mass destruction

during World War I. Modern chemical weapons

include lethal nerve agents. In general, chemical

weapons are categorized according to their physical

state when being delivered (i.e., solid, liquid, gas)

and their physical characteristics (such as their

persistence, their mode of action on the human

body, and their level of lethality), [3].

The level of lethality varies a lot, with chemical

agents, like tear gas, acting only as irritants or

incapacitants being unable to cause death unless

they are used in a very large quantity, while others

being highly lethal. Nerve agents are typical

examples. They are classified as highly poisonous

chemical agents that disrupt the normal function of

the human nervous system. These substances may

be absorbed in the human body through inhalation

or through the skin and they may be used in

chemical warfare. With only a few drops absorbed

through the skin, substances like Sarin, Soman,

Novichok, Tabun, and VX can paralyze almost

instantly and kill in a few minutes. They are usually

known by their chemical name and a two-letter

military designation, for example cyclosarin (GF),

tabun (GA), sarin (GB), dimethyl

methylphosphonate (DMMP), diisopropyl

methylphosphonate (DIMP), soman (GD), N, N-

diethyl 2(methyl-(2-

methylpropoxy)phosphoryl)sulfanylethanamide

(VR) and 22-(diisopropylamino)ethyl-O-ethyl

methylphosphonothioate (VX).

Nerve agents are responsible for severe damages

to the human central nervous system, as they disrupt

the normal function of the enzyme

acetylcholinesterase (AChE). Our body uses

acetylcholine for cell communication, by sending an

electrical impulse. AChE prevents the acetylcholine

molecules from building up on the receptors. For

this reason, it is crucial to know the precise

properties of these substances and how to tackle

them, [4].

Therefore, when AChE is inhibited,

acetylcholine accumulates on neural and

neuromuscular junctions, stimulating excessively,

causing a cholinergic syndrome, which involves

central, nicotinic, and muscarinic effects, such as

miosis, sweating, nausea, diarrhea, increased

salivation, and airway secretions, central respiratory

depression, respiratory failure, rhinorrhea,

bronchoconstriction, ataxia, altered mental status,

involuntary urination and defecation, bradycardia or

tachycardia, convulsion, fasciculations,

hyperthermia, lethargy, and coma. The recognition

of the toxidrome in its early stages is crucial for

administering an antidote, such as atropine,

diazepam, and pyridostigmine. In addition, besides

the acute effects caused by poisoning with nerve

agents, many studies have made clear that survivors

of intermediate or high-level exposure may

experience many neurological and

neuropsychological symptoms, [5].

2.2 Chronology of Nerve Agents’ Usage

Nerve agents were first invented in the 1930s by

accident, as German scientists were trying to find

alternative solutions to replace nicotine as

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insecticide. They discovered two organic

compounds, later known as tabun and sarin, that

contained phosphorus and were very efficient in

killing insect pests. However, they were found to be

very toxic for commercial use. Wehrmacht

characterized these two substances as chemical

weapons and tried to manufacture them on a big

scale. When the 3rd Reich collapsed, sarin was

acquired by the Soviet Union. Later on, in the

1950s, another substance, known as VX, was

manufactured in the UK. Again, it was very toxic to

be used in the agricultural sector, and it was

forwarded to the Porton Down Chemical Weapons

Research Centre of UK, and then to the US

government. Throughout the years, many other

nerve agents have been produced, but not many

things are known about them. Furthermore, till the

1980s, it is believed that nerve agents were not used

in warfare. Sarin was used by the forces of Saddam

Hussein during the Iran-Iraq war. Specifically in

1988, approximately 5000 Kurdish citizens were

killed in Halabja. On 5 March 2018, the former

Russian spy Sergei Skripal alongside his daughter,

was found unconscious in a park and they were

hospitalized in a critical condition in Salisbury, UK,

following exposure to an unknown nerve agent. The

most probable substance responsible for this event is

the nerve agent Novichok, [6].

Even three decades after signing the Chemical

Weapons Convention, chemical warfare agents

(CWAs) remain a threat. The development of novel

methods for the detection of CWAs, protection from

CWAs, and CWA decontamination motivates

research on their physicochemical properties.

Several attempts have been made to identify the

structure and the properties of nerve agents’

compounds, [7]. However, this is not an easy task,

and so far, only sarin has been adequately described,

which is due to several reasons. After the signing of

the Chemical Weapons Convention in 1997,

substances like nerve agents have been prohibited to

use and produce due to their extreme toxicity.

Specifically, on April 29, 1997, the Chemical

Weapons Convention (CWC) entered into force.

Initially, it was approved by the United Nations

Conference in 1992. The goal was, and still is, the

total disarmament of chemical weapons. According

to the treaty, the country that signed must destroy all

chemical weapons it may have on the ground but

also on the territory of other countries, as well as

their production facilities. For the specific

convention, as chemical weapons are considered

specific toxic chemicals and any chemical reagent

involved in any stage of their production as well as

ammunition and devices, specially designed to

cause death or other harm. As of 2013, the only

countries that had neither signed nor joined the

CWC were Angola, Egypt, North Korea, and South

Sudan, [8].

2.3 Necessity of Modelling Nerve Agents’

Properties

For this reason, there is not much data available, as

all experimental studies must use less toxic simulant

compounds, and only in silico experiments, such as

molecular simulations, since there is no way to

actually test these substances on human beings

and/or animals, due to bioethics. Therefore, the

modelling of the resting nerve agents is a necessity

in order to deepen our knowledge regarding their

properties and their effects on human health and the

ecosystems.

Multiscale simulation and homogenization

techniques, particularly for materials like the

substances we study, have emerged as the primary

computational technologies and engineering tools in

the field of material modeling and design.

Nevertheless, concurrent multiscale simulations

demand substantial computational resources due to

the exponential increase in CPU time as spatial and

temporal scales expand. With only a few exceptions,

both hierarchical and concurrent multiscale

modeling methods have not found widespread

adoption in the industrial sector, primarily due to

their computational expenses.

Recent advancements in artificial intelligence

technology, coupled with rapid growth in

computational resources and data availability, have

spurred the widespread integration of machine

learning-based methodologies. These methods aim

to enhance the computational efficiency and

accuracy of multiscale simulations and their various

applications. While the anticipation of a

revolutionary impact from artificial intelligence and

machine learning in computational materials and

mechanics is high, machine learning-based

multiscale modeling and simulation are still in their

early stages. This work presents several perspectives

on innovative techniques, such as machine learning-

based multiscale modeling and simulation of

materials, as well as their applications in defect

mechanics modeling and material design. These

approaches hold the potential to eventually replace

conventional multiscale modeling methods, [9].

Regulatory chemical risk assessment has

traditionally focused on typical hazardous chemicals

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rather than chemical weapons. Predictive models are

indispensable for estimating chemical toxicity, both

for scientific research and regulatory purposes.

However, conventional models face significant

challenges in the case of nerve agents, primarily due

to the lack of information about their specific modes

of toxic action. Therefore, alternative models that

rely on different types of information, rather than

modes of action, must be developed. The objective

of this study is to explore the current state-of-the-art

in predictive models based on quantitative

structure–activity relationship techniques for

assessing the toxicity of substances. Additionally, it

aims to identify future challenges that hinder more

reliable risk assessment in the context of

environmental risk assessment. These alternative

models are essential not only to overcome the

limitations of conventional models but also to

enhance their overall performance, [10].

3 Molecular Dynamics

3.1 Molecular Dynamics Simulations

Molecular dynamics (MD) is a method of computer

simulations for the analysis of the physical

properties and movements of atoms and / or

molecules, applied mostly in chemical physics,

material science and biophysics. The representation

of the model can be at various levels of details, with

the atomistic representation leading to the best

reproduction of the actual system.

Atoms and molecules interact for a specific time

period, providing an insight into the system’s

dynamics and dynamic evolution. The trajectories of

the selected atoms and molecules are calculated

numerically by solving the Newtonian motion

equations for a system of interacting particles. The

forces developed between the interacting particles,

as well as their potential energies, are usually

calculated by using either interatomic potentials

(mathematical functions used for the calculation of

the potential energy of a system of atoms with given

positions in space) or molecular mechanic force

fields (computational methods used for the estimate

of the forces between atoms within molecules and

also between molecules). Force field equations may

be complex, but the calculation remains quite

simple, allowing the determination of several

physical quantities, such as springs for bond length

and angles, periodic functions for bond rotations,

Lennard–Jones potentials, Coulomb's law for van

der Waals and electrostatic interactions. Then, the

classical Newton’s equations of motion are used to

calculate the position, the velocity, and the

acceleration of the atoms or molecules.

Since molecular systems are very complex,

involving typically a large number of particles

interacting with each other, the determination of

their properties analytically is almost impossible

(Figure 1). MD methods are very useful for the

determination of the properties of these complex

chemical compounds, especially chemical warfare

substances such as nerve agents, by circumventing

this problem and using numerical methods. Force

field equations can be parameterized in many

different ways, and each equation cannot necessarily

allow the representation of each molecule type.

With the proper selection of parameters and

algorithms, cumulative errors in numerical

integrations can be eliminated to a great extent.

The complex and time-consuming calculations

of MD simulations can be particularly suitable for

the application of Machine Learning (ML)

techniques, such as neural networks and deep

learning architectures. Many of the challenges faced

in MD simulations may be formulated as ML

problems, addressing the potential energy surface,

the free energy surface, the coarse graining, the

kinetics, the sampling and the thermodynamics.

Fig. 1: Steps of MD simulation

To conclude about proposed Force Field

(Potential Model) Development methods, structures

proposed in the literature for each nerve agent if

they are available may be used. At first all the

molecular structures of the study agents will be

created in a software along with the Steepest

Descent Algorithm in order to determine the most

stable molecular geometry in each case. Afterwards,

extended charge equilibration (eQeq) technique will

be employed on the rigid body structures to estimate

in increased precision the atomic partial charges for

each atom/atoms group (molecular sites).

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Finally, parameters from already published

literature will combine to obtain the full potential

model, for a fully flexible structure, using, Lennard-

Jones 12-6, Potential with long range Ewald

corrections, flexible harmonic bond potential,

flexible harmonic angle potential and flexible

harmonic dihedral potential. Alternative we will use

the ML techniques to produce the aforementioned

parameters. Data from several sources were

incorporated into the models.

In order to perform MD simulations, several

software packages may be used, such as LAMMPS,

BOSS and CHARMM, while to employ Machine

Learning methods to develop accurate atomic and

interatomic potentials for molecular simulations, the

ACEMD software package by Acellera could be

employed. Moreover, specific software packages

with proprietary license need to be included in order

to employ further complex calculations in this

project, such as Spartan 20 by Wavefun.com,

YASARA Structure, DESMOND by Schrodinger

Inc., and SCIGRESS and AMS by FUJITSU Ltd.

3.2 QSAR Models

Structure-activity relationship (SAR) and

quantitative structure-activity relationship (QSAR)

models, collectively known as (Q)SARs, are

mathematical models utilized for the prediction of

the physicochemical, biological, and environmental

fate properties of compounds based on their

chemical structure. These models can be found in

both free and commercial software applications. The

workflow of such models consists of the selection of

data sets and extraction of descriptors, the variable

selection, the construction of models and the

validation. As the scope of such models is the

delivery of reliable information, the last step, i.e.,

the scientific validation, is very important. It goes

without saying that there are limitations in the

substance that can be treated by each model, [11].

SAR refers to the assumption that similar molecules

have similar activities. The challenge that these

models have to face is the treatment of small

differences in molecular level, since each activity

(e.g., reaction ability etc) might be affected by

multiple differences. As a result, such activities

have to be modelled using multiple variables

(Figure 2).

Fig. 2: An outline of QSAR Models

Another challenge, which concerns stronger

trends too, is the fact that the hypotheses usually

rely on a finite number of input data. Thus, one must

be careful in order to avoid overfitting, i.e., to

describe accurately the training data, but purely any

new data, [12].

In a study like this, QSAR models could be used

for the determination of the physiochemical,

biological,

and toxic effects of several nerve agents.

An ecological model(s) will be developed,

specifically for use in practical applications.

Ecological modeling approaches are crucial for

understanding the potential impact of toxic chemical

warfare agents (CWAs) on water-sensitive areas for

several reasons:

Risk Assessment: Ecological models help in

assessing the risks associated with the release of

chemical warfare agents (CWAs) into water-

sensitive environments. They enable scientists and

policymakers to quantify the potential ecological

and human health impacts, helping in decision-

making and risk management.

Complex Interactions: Water-sensitive regions

frequently harbor diverse ecosystems characterized

by intricate interactions among various species and

environmental factors. Ecological models are

capable of simulating these complex relationships,

thereby offering insights into the potential

disruption of these ecosystems by chemical warfare

agents (CWAs).

Predictive Capability: These models possess the

ability to forecast the dispersion and behavior of

chemical warfare agents (CWAs) within aquatic

environments. This information plays a pivotal role

in response planning and the formulation of

effective countermeasures to mitigate the

contamination caused by CWAs.

Long-term Effects: Ecological models can

effectively replicate the enduring consequences of

exposure to chemical warfare agents (CWAs) on

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aquatic ecosystems. Such modeling proves crucial

in evaluating the persistence of contamination,

recovery rates, and the likelihood of chronic

ecological damage.

Protection of Biodiversity: Water-sensitive regions

often house abundant biodiversity. Ecological

models assist in assessing the potential harm that

may be inflicted upon endangered or sensitive

species and their habitats, thereby contributing to

the preservation of these ecosystems.

Resource Allocation: In scenarios where resources

for cleanup and remediation are limited, ecological

models play a pivotal role in prioritizing areas that

are most susceptible or critical for protection. This

ensures the efficient allocation of available

resources.

Regulatory Compliance: Many countries have

environmental regulations and international

agreements in place to protect water-sensitive areas.

Ecological models provide a scientific basis for

assessing compliance with these regulations.

Public Health: Toxic chemical warfare agents

(CWAs) can contaminate drinking water sources

and affect human health. Ecological models help in

understanding how pollutants may enter the food

chain and impact human populations, thereby

informing public health responses.

Environmental Management: These models are

valuable tools for designing and implementing

strategies for environmental management and

remediation after chemical warfare agent (CWA)

contamination events.

Various modeling approaches can be employed

to predict how ecosystems respond to anthropogenic

interventions. These approaches encompass

mechanistic models, statistical models, and machine

learning (ML) methods. Our first step will be

selecting the approach that best suits our problem.

Additionally, we will create an outline for aligning

the modeling process with decision-making and

identifying the essential requirements to enhance the

utility of ecological models in supporting

management decisions, particularly when the need

arises to justify these decisions to the public (Figure

3).

Fig. 3: An Ecological modeling approach

4 Proposed Analysis

In the frame of this proposed analysis, a brief

outline of the overall work plan with the required

steps is the following:

 The molecular modelling of several nerve agents

using molecular dynamic simulation in order to

define their molecular structure and to study the

thermodynamical, transport and other dynamical

properties. Flexible models for nerve agents

(GF, GP, GB, GA, VX, VM, Soman, A230,

A232 & A234) will be created for molecular

dynamics simulations. The new models will test

against experimental data for available

thermodynamic and other properties. An array

of thermodynamic and structural properties will

be presented and compared to experimental

studies if available. To achieve that, machine

learning techniques will be integrated in our

approach so that our simulation will take

advantage of this powerful tool.

 The modelling of the effects of these substances,

by applying a series of QSAR models toxicity,

skin permeation, pharmacokinetic aspects as

well as the environmental fate of a series of

nerve agents. The extraction of reliable

information about the toxic effects caused by

nerve agents will be performed by using a series

of freely available and validated QSAR models

that predict the physicochemical, biological, and

environmental effects of these substances. The

knowledge of the substances’ structure is

necessary and will be available through the

molecular dynamics modelling carried out first

hand.

 The modelling of the effects of the release of the

nerve agents in water sensitive areas. Simple

models will be used to simulate the ecosystems

of the water sensitive areas and demonstrate the

possible consequences of a release. Water-

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sensitive areas that exist in various regions of

Greece will be identified, with a special

emphasis on Northern Greece. The biodiversity

of these specific areas will be analyzed, and

their aquatic and mixed ecosystems will be

categorized accordingly. Marine and freshwater

ecosystems perform many vital functions such

as filtering, diluting, and storing water,

preventing flooding, maintaining local

microclimatic balance, and preserving

biodiversity. All types of ecosystems provide

natural resources and are available for a wide

range of products and services, such as trade,

transport routes and recreational opportunities.

The protection of these goods requires a broad

perspective. Having categorised the various

ecosystems, the visual programming language

STELLA will be used to model the possible

ways nerve agents could be released in a release

in water sensitive areas as well as the effects that

will be caused in these areas in the event of an

incident, [13]. STELLA software is a graphical,

icon-based modelling software package that can

be used to build relatively complex models. It is

constructed to describe and analyse communities

of organisms under the influence of random

variability in disturbance rates and episodic

disturbances. Nerve agents are highly toxic and

can rapidly affect exposed subjects. Therefore,

the modelling of the chemical warfare toxic

agents in water sensitive areas and the possible

effects of their release may lead to the creation

of an immediate warning mechanism, [14].

5 Discussion

The concept and methodology of the proposed

analysis have been set to specifically ensure

maximum impact on the scientific, societal,

economic, and environmental ecosystems involved

by developing, adapting, and integrating dedicated

scientific tools and methodologies in an effective

way that leads in pushing the current knowledge

state to new limits.

The strategic objectives of this study are the

following:

 Connecting our research with the solving of

challenges and the reinforcement of some of the

Sustainable Development Goals (SDGs),

adopted by the United Nations, and to the

framework of the European Green Deal for an

environment without toxic substances.

 In line with the strategy for EU international

cooperation in research and innovation,

multilateral international cooperation is

encouraged.

 Promote scientific and practical approaches to

the scientific community for the extreme

emergency situations related to chemical

warfare agents (CWAs).

 Eradication of chemical weapons and prevention

of their re-emergence in accordance with the

objectives of the Organization for the

Prohibition of Chemical Weapons (OPCW).

On the other hand, the operational objectives are the

following:

 Design an innovative approach that with the

combined use of classical molecular modelling

and machine learning techniques will produce

the force field used to describe each system.

 Investigate the state-of-the-art predictive models

based on quantitative structure-activity

relationship techniques for the assessment of

substance toxicity.

 Identify the future challenges that impede more

reliable risk assessment for environmental risk

assessment.

 Design and implementation of an effective and

efficient method utilising simple models to

simulate the ecosystems of water sensitive areas

and demonstrate the possible consequences of

nerve agents’ release.

 The outcome of this analysis may be useful for

the solving of challenges and the reinforcement

of some of the Sustainable Development Goals

(SDGs), adopted by the United Nations in 2015.

These SDGs have been adopted worldwide by

governments, industry, and many organisations,

with a horizon of realisation by 2030.

Specifically, the Sustainable Development Goals

(SDGs) of interest are the following:

SDG3 Good health and well-being: Exposure to

toxic chemical warfare agents (CWAs) through

contaminated water can have severe health

implications for communities living in affected

areas. Achieving good health and well-being is

compromised when populations are at risk of

exposure to these hazardous agents. The project may

be a key to achieving the 3rd Sustainable

Development Goal (SDG), as it will provide a

deeper understanding of hazardous chemicals, such

as nerve agents, in water, and will provide new

solutions for the reduction of hazardous chemical

pollution and the impacts on human health.

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SDG6 Clean water and sanitation: This goal

directly addresses issues related to water quality and

access. The presence of toxic chemical warfare

agents (CWAs) in water-sensitive areas can severely

compromise the availability of clean and safe

drinking water, making it difficult to achieve this

goal. This analysis may contribute to this

Sustainable Development Goal (SGD) by proposing

mitigation techniques regarding the pollution of

water sensitive areas with hazardous warfare

chemical substances (i.e., nerve agents) that may

pose a danger to public health.

SDG9 Industry, innovation, and infrastructure:

This Sustainable Development Goal (SDG) calls for

resilient infrastructure, including disaster risk

reduction strategies. Preparing for and responding to

chemical warfare agent (CWA) incidents in water-

sensitive areas involves innovation in disaster

management and infrastructure protection. One of

the important aspects of disaster management is the

creation of precise ecological models, like the one

discussed in this work. Therefore, the project’s

outcome may be useful for the future of industry

and infrastructure, as it will offer insights on how to

cope with dangerous situations regarding chemical

warfare substances and sustainability.

This project could also be indirectly related with

other Sustainable Development Goals (SDGs) as

well, such as:

SDG 11: Sustainable Cities and Communities:

Urban areas near water-sensitive regions may be

impacted by chemical warfare agent (CWA)

contamination. Ensuring sustainable, resilient cities

and communities requires addressing the potential

risks posed by toxic chemical warfare agents

(CWAs).

SDG 13: Climate Action: Chemical warfare agents

can have environmental impacts, including

contributions to climate change if they contaminate

soil and water. Addressing chemical warfare agent

(CWA) incidents is connected to broader efforts to

mitigate climate change and protect the

environment.

SDG 14: Life Below Water: Water-sensitive areas,

such as wetlands, rivers, and coastal regions, are

critical for marine life. Chemical contamination

from chemical warfare agent (CWA) can harm

aquatic ecosystems and marine biodiversity, making

it challenging to meet this goal's objectives.

SDG 15: Life on Land: Chemical contamination,

including chemical warfare agent (CWA), can have

adverse effects on terrestrial ecosystems,

biodiversity, and soil quality. Water-sensitive areas

often connect with land-based ecosystems, and the

contamination can spread, affecting life on land.

Moreover, seas, oceans, rivers and lakes are a

source of natural and economic wealth for Europe.

During the next few years extensive water-related

investments will take place. The priorities of the

European Green Deal include the protection of

biodiversity and ecosystems, by reducing air-,

water- and land- pollution, and moving towards a

circular economy. Working in these key areas, for a

toxic-free environment, the European Union will

improve the health status and the quality of citizens'

lives, as well as help protect the environment from

dangerous chemical substances. The toxic chemical

warfare agents (CWAs) under investigation in this

study are extremely harmful to living organisms. In

the framework of the European Green Deal for an

environment without toxic substances, modelling of

these chemical agents is essential, as well as their

effective identification and removal in a limited

period of time in order to protect the human health

and aquatic ecosystems.

6 Conclusions

In summary, ecological modeling approaches are

essential for assessing the potential consequences of

chemical warfare agent (CWA) incidents in water-

sensitive areas. They provide a systematic and

scientific way to understand the ecological and

human health risks, which is crucial for developing

effective strategies for prevention, response, and

recovery in the event of such incidents.

An integrated risk monitoring and forecasting

system enables individuals, communities,

governments, businesses, and other stakeholders to

take timely action in order to reduce disaster risks

before hazardous events occur, through several

systems and procedures of communication and

preparedness activities. One of the basics elements

of early warning systems is the knowledge from its

system risk of destruction. This is of course based

on systematic data collection and simultaneous

disaster risk assessments. An additional key element

is the ability to detect, monitor, analyse and predict

risks and possible consequences. The modelling of

toxic chemical warfare agents and the release of

such substances in water sensitive areas, may

provide useful insights about the structure and

possible effects, that could be used by an early

warning system, [15].

The results achieved by the proposed study will

be the cornerstone of the innovative technologies

WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT

DOI: 10.37394/232015.2023.19.94

Nikolaos Stasinopoulos, Michail Chalaris,

Anastasia Tezari, Kalliopi Kravari

E-ISSN: 2224-3496

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Volume 19, 2023

that will make the industrial sector prosper in the

specific mobility and transportation field. Due to the

involvement of multiple related entities, the actions,

results and impacts of this project can be further

exploited EU wide and globally. Therefore, it is of

high importance to create solid communication,

dissemination, and exploitation routes of the

developed outputs. The identified target groups may

involve the industry, the academia as well as the

public sector, while stakeholders that may be

engaged include professionals (firefighters,

emergency medical services, trainers for first and

second responders, civil protection administrative

and operational staff), members of the scientific

community, private sector and public bodies

(companies, ministries, EC), as well as the media

and the general public.

Acknowledgement:

This work is performed under the project

"GROWTH" in the framework of "ERASMUS-

EDU-2022-CB-VET" of European Education and

Culture Executive Agency (EACEA) within the

framework of the "Erasmus+" Program, Key Action

2 with the aim of "Strengthening resilience by

developing targeted national, local scientific and

practical training activities for capacity building and

risk awareness and the effects of man-made

disasters (Project Code 80884)".

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WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT

DOI: 10.37394/232015.2023.19.94

Nikolaos Stasinopoulos, Michail Chalaris,

Anastasia Tezari, Kalliopi Kravari

E-ISSN: 2224-3496

1006

Volume 19, 2023

National Perspective, Journal of Engineering

Science and Technology Review, vol14, 2021,

pp. 169-175.

Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

-Michail Chalaris was responsible for the

Supervision.

The authors equally contributed in the present

research, at all stages from the formulation of the

problem to the final findings and solution.

Sources of Funding for Research Presented in a

Scientific Article or Scientific Article Itself

This work was funded under the project

"GROWTH" in the framework of "ERASMUS-

EDU-2022-CB-VET" of the European Education

and Culture Executive Agency (EACEA) within the

framework of the "Erasmus+" Program, Key Action

Conflict of Interest

The authors have no conflict of interest to declare.

Creative Commons Attribution License 4.0

(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

https://creativecommons.org/licenses/by/4.0/deed.en

_US

WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT

DOI: 10.37394/232015.2023.19.94

Nikolaos Stasinopoulos, Michail Chalaris,

Anastasia Tezari, Kalliopi Kravari

E-ISSN: 2224-3496

1007

Volume 19, 2023