Analysis of territorial compatibility for Seveso-type sites using different risk assessment methods and GIS technique

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Analysis of territorial compatibility for Seveso-type sites using different risk assessment methods and GIS technique Zoltán Töröka, Ruxandra-Mălina Petrescu-Maga, Alexandru Mereuțăa, Cristian Valeriu Maloșa, ⁎ Viorel-Ilie Arghiușa, Alexandru Ozunua,b, a

Research Institute for Sustainability and Disaster Management based on High Performance Computing, Faculty of Environmental Science and Engineering, Babeș-Bolyai University, Cluj-Napoca, 30 Fantanele St., Romania b Disaster Management Training and Education Centre for Africa (DiMTEC), University of the Free State, Bloemfontein, South Africa

ARTICLE INFO

ABSTRACT

Keywords: Land-use planning Risk assessment GIS, Seveso Territorial compatibility

The increasing size of chemical plants and rapid growth in residential areas has led to many incompatible landuse scenarios in the last 100 years. In this context, the authors assume that assessment and planning have their significant role in preventing the juxtaposition of hazards and population, and that, in this field, there is a broad recognition of the need for legislative and policy consistency across the European Union. The paper presents a comparative case study in which the Romanian land-use planning (LUP) criteria and the risk-based quantitative approach for a chemical plant are applied. Accident scenarios involving chlorine and propylene arecomprehensively analyzed using consequence and risk modelling software and GIS technique for the territorial compatibility assessment. The objective of the paper is threefold. Firstly, it presents an overview about current risk analysis methods; secondly, the authors advance an understanding of risk assessment practices used in several countries for the prevention and control of major industrial accidents involving dangerous substances and, also, for LUP. Thirdly, a method targeting an improved risk assessment framework for LUP, encompassing Romania’s determinants is outlined. The results obtained using the two different approaches indicate significant differences regarding the possibly affected areas and territorial compatibility. Furthermore, based on the findings, the paper ends with a set of recommendations that can be transformed into the foundation for future enactments of new safety standards that cover risk assessment for LUP. Consequently, the present study aims to become a frame of reference for decision-makers towards more sustainable and updated risk assessment practices in the field of industrial activities.

1. Introduction One of the major consequences of the postindustrial modernization is the upward trend of technological and environmental risks that, most of the time, provoke tremendous humanitarian crises. The complexities and inevitable errors of technological systems caused failures in preventing accidents and in the escalation of industrial risks (Zhang and Chen, 2013). Numerous disciplines focus on risk study and they strive to find the most appropriate way of classifying it. Broadly, “risk” is seen as the uncertainty about economic gains and losses (Kaplan and Garrick, 1981; Petrescu and Petrescu-Mag, 2017), and it is shown that risks exist only in terms of the knowledge about them (Shrivastava, 1995). Moreover, Paul Shrivastava (1995) argued that risks can be changed, magnified and dramatized by knowledge. Thus, in terms of

managing the risks, knowledge is proved to be vital. Just as important as knowledge is the ability to use resources efficiently. In this sense, the design and development of a methodology for an integrated risk assessment targeting the prevention of major accidents will facilitate the achievement of a more realistic spatial analysis (Băbuţ, 2011) destined for both the landscaping plans and for the judicious allocation of the means of intervention in a crisis situation caused by a major accident. In general, assessments are organized as a way to inform decisionmakers about issues that are controversial (Farrell and Jäger, 2006), as land-use planning (LUP) in case of a plant location can be. Assessment and planning, in general, have their important role in preventing the juxtaposition of hazards and population and there is a broad recognition of the need for greater consistency across the European Union (EU) (Walker, 1991). In this context, the risk assessment procedure should be

⁎ Corresponding author at: Research Institute for Sustainability and Disaster Management based on High Performance Computing (ISUMADECIP), Faculty of Environmental Science and Engineering, Babeș-Bolyai University, Cluj-Napoca, 30 Fantanele St., Romania. E-mail address: [email protected] (A. Ozunu).

https://doi.org/10.1016/j.landusepol.2019.02.037 Received 8 October 2018; Received in revised form 21 February 2019; Accepted 21 February 2019 0264-8377/ © 2019 Elsevier Ltd. All rights reserved.

Please cite this article as: Zoltán Török, et al., Land Use Policy, https://doi.org/10.1016/j.landusepol.2019.02.037

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valued as one of the most crucial endeavors towards harnessing scientifically grounded information for prevention and control of industrial accidents caused by dangerous substances. The shift towards prevention is a topical issue of environmental and technology policies in the EU and worldwide, and, in this context, risk assessment is one of the equation terms of industrial accidents prevention. Going back in time, in the 1900s policymakers and planning authorities have been struggling with industrial plant location in the context of LUP (Lees, 2012). A mixture of increasing plant sizes and rapid growth in residential areas has led to many incompatible land-use scenarios. Although the Romanian Ministerial Order no. 3710/1212/99/2017 (Ministry of Internal Affairs, 2017a) (referred to as MO 3710 hereinafter) is entitled “Methodology for establishing the adequate distances against potential risk sources (…)” and it aims to provide the methodology for LUP in case of Seveso sites, the authors emphasize the fact that MO 3710 does not include the methods which should be applied for the risk assessment itself, it just points to the use of accident scenarios already analysed in the Safety Report (SR) or Major-Accident Prevention Policy (MAPP). One of the main problems identified by the authors is the absence in the Romanian legislation of the risk assessment methodology itself. The legislation should define the framework of the risk assessment procedure: algorithms of the process, methods and techniques to be used, data sources to be considered, representation of results for the SR or MAPP. Starting from the worrying reality above, and also referring to a national context, where more than 300 Seveso units are operating (General Inspectorate for Emergency Situations, 2016), the objective of the paper is threefold:

LUP methodology are presented in the Conclusions (section 7). The study contends that often planning authorities can face difficulties in the case of the authorizing procedure for chemical establishments. As decision-making should rely on a well-established risk assessment procedure, the herein proposed risk assessment method for LUP can help to fuel future policy decisions that target an improved risk assessment procedure. Thus, an undeniable reality remains: policies are grounded in science. 2. Historical context of chemical disasters and LUP Pittman et al. (2014) wisely say that a continuous and under scrutiny review of past incidents and disasters in order to identify common causes and learn lessons is an indispensable component to any process safety, and Abdolhamidzadeh et al. (2011) consider that they can provide useful inputs for the development of future prevention strategies. Thus, to set the stage for the relevance of LUP policies in the case of process industries and the consequences of bad or missing LUP, several records on historical accidents are presented in this section. The Oppau explosion (Germany), in 1921 reveals one of the earliest examples for the lack of basic LUP practices. At the core of the event, two major errors were identified: a change in the manufacturing process of the nitrogenous fertilizers, coupled with the use of explosives (a standard practice at the time) to loosen large masses of solidified salts. The increase in plant size resulted in larger storage areas. As a result, 4500 tons of nitrogenous fertilizers were involved in the explosion. In the aftermath of the explosion, over 500 deaths were reported, and 80% of the structures in Oppau were destroyed. Thus, these outdated storage practices were in part responsible for the severe consequences, whose outcomes were encountered up to 30 km from the site (French Ministry of Environment, 2008a; Pittman et al., 2014; Ulrich, 2016; Willey, 2017). In 1944, a LNG (Liquefied Natural Gas) storage plant in Cleveland (Ohio, USA) suffered multiple fires after a storage tank rupture. The vaporous discharge reached over the plant’s perimeter, flowing into the nearby urban area. Fires and explosions in the area caused 128 deaths and 200–400 injuries. In the accident report, investigators gave one of the first documented safety distance measurement. It was concluded that for a plant of this type, a margin of at least half of mile should be considered in respect to the nearest residential buildings (National Association of State Fire Marshals, 2005; Yang et al., 2011; Lees, 2012). In 1966 in Feyzin (France), several BLEVEs (Boiling Liquid Expanding Vapour Explosion) and fires engulfed a LPG (Liquefied Petroleum Gas) storage site. The accident took place after operators had undergone a chain of faulty procedures that lead to a major propane release. The vapour cloud spread to a nearby motorway, encountering an ignition source in the form of a hot car engine. The subsequent flash fire and BLEVEs accounted for 18 deaths, 84 serious injuries and major property loss. After the accident, The Ministerial Order of September 1967 and later amendments in’ 73 and’ 75 changed the technical regulations applicable to the LPG production and storage industry. Among the new provisions, with regard to LUP, the definition of danger zones was introduced together with specific distances separating process installations from residential areas (French Ministry of Environment, 2008b; Kletz, 2009; Török and Ozunu, 2010). The explosions at the cyclohexane plant in Flixborough (UK) in 1974 brought some of the most important revisions in safety culture and regulations to date. The explosion caused 28 deaths (Sadee et al., 1977), 36 injured and all buildings destroyed within a radius of 600 m from the explosion epicentre. It was estimated that around 30 tons of cyclohexane, which is equivalent to the contents of two of the oxidation vessels, formed an explosive cloud with an explosive effect of some 280 tons of TNT (Sadee et al., 1977; Venart, 2004). Over 1800 building units were damaged by debris being spotted as far as 32 km away. The

i) To provide an overview about current risk analysis methods; ii) To advance understanding of risk assessment practices used in several countries for the prevention and control of major industrial accidents involving dangerous substances and, also, for LUP purposes, and iii) To outline a method targeting an improved risk assessment framework for LUP, that considers Romania’s legislative, administrative and territorial determinants. For this, the authors resort to the comparison of two practices, the risk-based quantitative approach versus the Romanian LUP criteria included in MO 3710. To the authors’ best knowledge, this is the first study that, besides comparing the two methods of risk analysis for territorial planning, resorts to GIS technique in determining territorial compatibility by using data from the Urban Atlas and the Copernicus land-cover. Thus, we aim to compensate for a gap in the studies literature by providing practical support for risk assessment practices and creating the scene for future policy recommendations in the field of the risk assessment procedure for LUP. After the Introduction chapter, section 2 offers an overview of historical accidents caused by a poor LUP. Then, assuming that risk analysis is the foundation and scientific basis of safety planning for urban land-use (Zhou et al., 2014), in section 3 of the study a general description of the main risk analysis methods is made, and different LUP criteria applied in several European countries and Canada are described. Methods (section 4) are presented on two levels: Hazard and risk assessment (4.1) and Territorial compatibility analysis using GIS (4.2). The fifth part advances with a case study (section 5) that focuses on the use of the Romanian LUP criteria compared to a risk-based approach where Individual Risk (IR) levels are determined for an existing Romanian Seveso-type site. For this, two storage vessels, one of liquefied chlorine and one of propylene are used. The differences between the two approaches, the new Romanian LUP criteria and the risk-based criteria, are highlighted in Results and Discussions chapter (section 6). Finally, a set of recommendations for the development of a Romanian

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accident reports contained some of the most extensive inquiry into major accident scenarios known today. It also brought major industrial accidents into public attention, increasing awareness on this topic. As a result, the Advisory Committee on Major Hazards (ACMH) was formed with the task of advising on the control of such installations. From the three reports drafted by the ACMH it was clear that LUP became of principal concern within the industry regulations. The reports from Flixborough became the starting point on the first iteration of the European Council’s Major Accident Hazards Directive (Venart, 2006; French Ministry of Environment, 2008c; Hendershot, 2009; Kletz, 2009; Lees, 2012). Only two years after Flixborough, the Seveso accident forever changed the public perception on risks associated with the process industries. In 1976 in Seveso, Italy, a highly toxic discharge of 2,3,7,8Tetrachlorodibenzo-p-dioxin (TCDD) resulted in the evacuation of over 5000 people, after local intervention units defined three zones based on TCDD concentration levels. No direct deaths were reported to TCDD exposure after the Seveso accident (Nerín et al., 2014), nevertheless, a number of pregnant women exposed reported abortions, while hundreds of animals were sacrificed after being exposed. In a paper of Consonni et al. (2008) that reports the results of the mortality follow-up extension for 1997–2001, applied on a cohort of 278.108 residents at the time of the accident, it was concluded that the affected zones showed increased mortality from circulatory diseases in the first years after the accident. Moreover, carcinogenicity by TCDD in the case of Seveso in scientific literature has been extensively investigated (Eskenazi et al., 2018). The Italian Commission report that followed, together with the Flixborough report were at the forefront in the development of the EC Major Accident Hazards Directive in 1982 or, most commonly known as the “Seveso Directive”. Segregation between hazardous installations and residential areas was again brought into discussion, as in this case, over time, housing units gradually advanced closer to the plant area (Lees, 2012; Nerín et al., 2014; Eskenazi et al., 2018). The 1970s’ events brought major technological accidents into the public eye. As a result, the process industries were forced to reassess their approaches to risk assessments. The “Canvey reports”, in 1978 and 1981, and the “Rijnmond report”, in 1982, brought great improvements to the standard practices at that time. Both cases focused on installation clusters and the associated IR and SR to the said clusters. The reports produced valuable fault and event data that are still used to this day in risk-based LUP methods (described below) (Lees, 2012). Another large-scale event took place in Mexico City (Mexico), in 1984, at a LPG storage and distribution site. After a distribution pipeline rupture caused several LPG tanks to BLEVE, the entire terminal was destroyed. A total of 500 people died and over 7000 sustained injuries (Pietersen, 1988). Similarly to other cases described in this paper, the high number of casualties and the high amount of property loss could have been avoided. The LPG terminal was constructed long before any housing units were built in the area. As time went on, housing areas extended closer to the plant site (Kletz, 2009; Lees, 2012). The worst disaster ever to have come from the process industries was the Bhopal (India) methyl isocyanate (MIC) toxic release in 1984. Over 3800 deaths and tens of thousands injured (Broughton, 2005) describe one of the worst cases of improper LUP practices; 15,000 to 20,000 premature deaths were reported in the subsequent two decades (Sharma, 2005). After the investigation reports were published, the plant location issues became more relevant. The subject remains complex as some of the housing units that crept in closer to the plant’s perimeter were illegally constructed. Nevertheless, the local authorities gave the settlers land ownership to avoid relocation procedures. Another reported problem highlights that for the amounts of MIC at Bhopal, the process plant did not achieve adequate safety distances with respect to the nearest legal residential areas. Furthermore, when

the plant was initially designed, the amounts of hazardous substances produced and stored on site were significantly lower (Puri and Bisaryaa, 2005; Kletz, 2009; Havens et al., 2012; Lees, 2012). Enschede in the Netherlands was home to a fireworks warehouse explosion in the year 2000. The event caused 22 deaths, 950 injured, 500 homes and businesses deemed unusable, and another 1500 homes damaged to a lesser degree (Vierendeels et al., 2011). The lack of proper hazard classification of fireworks made storing such large quantities possible. The event also highlighted improper LUP procedures as local residential areas were built too close to the storage units (French Sustainable Development Ministry, 2009; Vierendeels et al., 2011; Voort et al., 2015). In 2001 the AZF ammonium nitrate explosion in Toulouse (France) killed 31 people and injured 2500, and the total estimated material damage was of 1.5 billion euros (Vierendeels et al., 2011). Among property damage, over 500 houses were deemed uninhabitable. This event highlighted the shortcomings in the French LUP policy at that time. Risk assessments only took into consideration worst-case scenarios without quantifying the probability of such outcomes. The French authorities still rely on a modified consequence-based approach (described below) to LUP with the use of buffer zones. One of the claimed reasons is that the input data needed for a probabilistic approach may not always be site specific (Taveau, 2010; French Sustainable Development Ministry, 2013; Pasman and Reniers, 2014). The Buncefield (UK) oil storage and transfer depot was subject to a VCE (Vapour Cloud Explosion) and subsequent fires in 2005. In the aftermath, 43 injuries were reported as well as excessive property loss for the local inhabitants and businesses (French Ministry of Environment, 2007; Paltrinieri et al., 2012). The Buncefield Major Incident Investigation Board issued the Eighth report on 15 July 2008 entitled “Recommendations on land use planning and the control of societal risk around major hazard sites”. It contained 18 recommendations for improving the LUP system in the UK with emphasis on SR and an overall risk-based approach (Buncefield Major Incident Investigation Board, 2008; Atkinson et al., 2015; Thomas, 2018). All the lessons learned from these chemical disasters contributed to the continuous development of the so-called Seveso Directives, the main legislation in the EU on the prevention and control of chemical accidents. So, one can strongly assert that the consequences of these major industrial accidents represent the building blocks of new Seveso regulations and of their amendments. In 2012 the Seveso-III (Directive 2012/18/EU) was adopted, putting a greater emphasis, compared to its predecessor the Seveso-II (Directive 96/82/EC), on the land-use policies applied in the Member States to ensure appropriate distances between vulnerable areas (e.g., residential, public use and recreational areas, natural protected areas, main transport routes) and establishments falling under the Directive. In the case of existing establishments, if the risk analysis shows the necessity of risk mitigation, additional technical measures have to be implemented by the operator to maintain the risk to persons or the environment at an acceptable level (Directive 2012/18/ EU). Obviously, the acceptable level of risk can be a very subjective issue, depending, on the one hand, on the administrative authority’s objectives and policies, and on the risk perception of the population, on the other hand. Risk perception (which is relative to the observer and is a product of social experience) varies in terms of the degree to which people experience control, fear and lack of knowledge (Kaplan and Garrick, 1981; Petrescu and Petrescu-Mag, 2017) As there is no risk assessment methodology defined in the framework of the Directive, leaving each Member State to decide which type of methodology they prefer to use for LUP purposes, hereinafter, a general description of the main methodologies and examples of LUP criteria in different States are described. Thus, the authors aimed at offering some basic knowledge on these elements used in the case study.

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3. Risk analysis for land-use planning

risk index, one must identify possible accident scenarios, estimate their occurrence probability, and calculate physical effects and possible impacts on the exposed population. The resulting risk criterion may be expressed in terms of location as IR contours or in the form of F–N curves as SR, where F represents the cumulative frequency of accidents and N refers to the number of expected deaths (Jonkman et al., 2003). IR values should ensure that any exposed individual will not be subjected to unacceptable levels of risk, while SR values should not exceed unwanted levels in areas over a given population density (Cozzani et al., 2006; Danish Ministry of the Environment, 2009; Christou et al., 2011; Khakzad and Reniers, 2017). These approaches require extensive amounts of data in each calculation step making them susceptible to varying degrees of uncertainty. In addition, the resulting risk levels are averaged over time. Thus, a simplistic view of inside safe, outside unsafe, should be avoided since risk values may fluctuate over an order of magnitude (Kontic and Kontic, 2009; Pasman and Reniers, 2014). The hybrid method or semi-quantitative method may be considered as a subcategory of risk-based and consequence-based methods. Typically, hybrid methods use a combination of qualitative and quantitative criteria from other approaches. More commonly, scenario frequencies are analysed more loosely, while consequence analysis may be more concrete. In any case, certain combination rules apply. Using a risk matrix is also commonly accepted as a hybrid approach since both frequencies and consequence threshold may be expressed. In some cases, both event frequencies and consequence analysis may be subjected to quantitative calculations and still be regarded as a hybrid approach since, in this case, risk indexes are not further addressed (Danish Ministry of the Environment, 2009; Christou et al., 2011).

3.1. Risk analysis methods Different cultural and historical backgrounds and also national legislative and administrative determinants led to a wide range of methods for addressing the risk and establishing LUP (Demichela et al., 2014). Nevertheless, four specific LUP methods can be distinguished as they have been applied worldwide. The methods include the generic distances method, the consequence-based method, the risk-based or probabilistic method and the hybrid method (Zhou et al., 2014). Apart from regulating major accident hazards, the European Commission does not implicitly specify any method of LUP. As a result, the EU Member States were compelled to choose one of these four approaches as suitable to their socio-political interests. Although technically different, these methods do not necessarily contradict each other, and there are states that choose to apply a combination of criteria from different types of approaches (Khakzad and Reniers, 2017). The generic distance method implies the use of separation distances derived, in part, from simplified consequence-based calculations. To obtain targeted distances, factors such as hazardous substances inventories, historical data, expert judgment, and possible environmental impacts play an important role. Other factors, such as industrial safety measures, plant layout, hazardous installation characteristics, or any detailed risk analysis may not be directly considered or omitted (Kontic and Kontic, 2009; Christou et al., 2011; Khakzad and Reniers, 2017). Also known as the state of the art or best practices approach, this method implies that an industrial plant should not present any risk levels outside its own perimeter. In practice, there are many cases in which probable consequence scenarios may exceed plant boundaries. In such cases, the establishment will take all necessary state of the art precautions in order to minimize risk levels beyond its walls. Finally, if the issue remains unsolved, the implementation of a land-use zoning system will avoid any incompatible areas (Danish Ministry of the Environment, 2009; Christou et al., 2011). The consequence-based method or deterministic method relies on identifying a number of worst credible or conceivable scenarios (Tugnoli et al., 2007). A consequence assessment is made based on these scenarios by calculating physical effect values. The resulting threshold values correspond to specific consequence levels such as high lethality, beginning of lethality, irreversible effects, and reversible effects. Zoning is achieved by overlapping a number of consequence areas to the land-use map. In principle, larger populated areas will be subjected to greater safety distances, while lower populated areas may be developed closer to the process plant. This method does not directly quantify the likelihood of the chosen accident scenarios. Instead, it relies on expert judgment, historical and hazard analysis data for the scenario selection process. In this sense, a number of scenarios may be deemed unlikely and thus, subsequently excluded from further analysis (Cozzani et al., 2006; Danish Ministry of the Environment, 2009; Christou et al., 2011; Khakzad and Reniers, 2017). Within this methodological approach, safety distances are directly dependent on the selected scenarios. Since this approach lacks any specific prioritization procedures, there is no guarantee that the relevant scenarios will be selected. This is especially relevant judging from the perspective that event likelihood is assessed without taking into account human reliability factors. Thus, improper management conditions may result in some unlikely scenarios achieving higher levels of probability (Tugnoli et al., 2013; Jain et al., 2017). Risk-based or probabilistic methods are some of the more sophisticated approaches used for LUP purposes. The quantitative risk assessment (QRA) methods (see also Reniers et al., 2005) are most commonly used, where possible accident scenarios are assessed in terms of foreseeable consequences and frequency of occurrence. To achieve a

3.2. Examples of risk assessment practices for LUP in different states The UK adopted a risk-based approach as early as the 80 s as a response to the Flixborough incident (1974) and other similar events worldwide. The current practice implies the HSE advising to any local authority looking to develop new land within the vicinity of a Seveso establishment. QRA calculations are assessed using HSE specific software for IR index, in the events of fire or explosions scenarios, while relying on a consequence-based approach for toxic dispersion scenarios (Gooijer et al., 2012). Land use may be distributed into 3 zones, inner, middle and outer zones with IR levels of 1*10-5, 1*10-6, and 3*10-7, respectively. A development proximity zone was added after the Buncefield incident (2005) that stretches 150 m from a large-scale petrol storage site. Depending on the type of construction category (a combination between population density and vulnerability) and zoning distribution, the HSE uses a decision matrix to advise against or not advise against a specific development (Gooijer et al., 2012; HSE, 2015; Khakzad and Reniers, 2017). Canada has adopted a similar approach to the UK LUP criteria. IR levels over 1*10-4 are allowed only for the plant perimeter. For levels between 1*10-4 and 1*10-5, warehouses and manufacturing plants and low-density open spaces are permitted. Between 1*10-5 and 1*10-6 low density residential areas, commercial uses and offices are allowed. For levels over 1*10-6 no development restrictions are applied (Major Industrial Accidents Council of Canada, 1995; Khakzad and Reniers, 2017). Flanders also follows risk-based LUP criteria. The Flemish criteria implements both IR and SR indexes. IR levels lower than 1*10−5 are designated for commercial activity areas with low-population density. Levels lower than 1*10-6 can accommodate low-density residential areas while values lower than 1*10-7 are permitted to any land-use types. The SR curve allows a maximum number of casualties for any given scenario frequency, as follows: 1*10-4 for 10 deaths, 1*10-6 for 100 deaths, and 1 × 10-8 for 1000 deaths (Danish Ministry of the Environment, 2009).

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In the Walloon Region, a risk-based methodology was also adopted. The criteria suggest a QRA approach to achieve IR levels. Apart from other QRA methods, the Walloon criteria expresses risk levels in terms of irreversible injuries to an exposed population. Thresholds for overpressure, thermal and toxic effect are calculated following the Walloon Region’s Handbook (Service public de Wallonie, 2017) while event data is collected from the Flemish Handbook of Failure Frequencies of 2009 (Gooijer et al., 2012). The method also requires Phast Risk QRA software from the DNV (Det Norske Veritas) company for IR levels. Facilities may be built or modified only after consulting a decision matrix based on iso-risk curve values and building types. Thus, inside IR levels higher than 1*10−3 no construction is permitted. For IR levels inside 1*10−3 to 1*10-6 construction types may vary from unpopulated or low populated work-related, to highly populated work-related buildings, comprised mostly of autonomous adults. Inside IR levels lower than 1*10-6 any construction types, including buildings accommodating vulnerable people with limited autonomy, are permitted (Gooijer et al., 2012; Delvosalle et al., 2017). The Dutch have a rich history of QRA implementation in LUP. Ever since the 80′s they have been perfecting their method from the early iterations of the “colored books” to the present “Reference Manual Bevi Risk Assessments” – RIVM (2009). In combination with the Safety-NL software, both IR and SR levels are determined. The criteria suggest a distinction between vulnerable objects (e.g., high population density, requiring assistance in evacuations) and objects of limited vulnerability (such as low population density and self-evacuation). Vulnerable objects are allowed in areas with IR ≤ 1*10−6 while objects of limited vulnerability may exceed this target value under certain conditions (Danish Ministry of the Environment, 2009; Gooijer et al., 2012; van Xanten et al., 2014). For SR curves, the target values may not exceed F = 1*10-5 for 10 deaths, F = 1*10-7 for 100 deaths and F = 1*10-9 for 1000 deaths (Danish Ministry of the Environment, 2009). The Italian LUP criterion consists of a hybrid approach combining consequence assessment with scenario probability analysis. No IR or SR indexes are used within this approach. Effect thresholds for fire, explosion and toxic dispersion scenarios are considered, resulting in six levels of consequences. Four probability classes from 1*10-3 to 1*10-6 are used for scenarios identified in the establishment’s SR (Cozzani et al., 2006), a required document from the Seveso Directive. Six landuse categories are defined based on population density and evacuation assisting needs. These three elements are combined within the decision matrix from Ministerial Decree 9 May 2001 to establish whether a specific land-use may be permitted within the Seveso establishment’s vicinity (Romano et al., 2004; Cozzani et al., 2006). Unfortunately, the Italian LUP method does not provide specific guidelines for probability and consequence assessment, as the Dutch or the UK criteria do, even if these last two models represented the inspiration source for the Italian LUP method (Cozzani et al., 2006; Kontic and Kontic, 2009; Sebos et al., 2010; Demichela et al., 2014). The French LUP method underwent heavy changes after the Toulouse accident in 2001. Thus, a hybrid approach was adopted, requiring the assessment of credible scenario probabilities and consequence analysis. The criterion makes use of the MMR (from the French expression “mesures de maîtrise des risques” meaning “measures of risk control”) matrix combining gravity and probability levels. Gravity levels are determined based on three thresholds for thermal, overpressure and toxic effects on a given number of people exposed. Probability levels are defined in five classes ranging from P > 1*10-2 to P < 1*10-5. Scenarios ranked within the MMR matrix are subjected to the PPRT (from French “Plans de prévention des risques technologiques” – “Technological risks prevention plans”) method (Taveau, 2010). The PPRT used for LUP combines probability and consequence levels, similar to the MMR matrix, into seven different zones or “areas”. Depending on the type of construction, and the PPRT colouring scheme, development may or may not be granted (Taveau, 2010; Gooijer et al., 2012).

The German guidelines for LUP (Federal Ministry of Environment, 2010) make use of separation distances. The deterministic approach suggests four distance classes, 200, 500, 900 and 1500 m, based on the type of hazardous substances and the quantities stored within the establishment. The resulting classes are derived from simplified consequence calculations. Thus, a number of standard assumptions like conditions for leakage, ignition probability, atmospheric conditions and effect thresholds are considered. These separation distances are used when there is a lack of detailed knowledge about the establishment in question. If detailed knowledge is available, the method suggests plant specific consequence calculations, in part, similar to the previous case assumptions. Other, less established methods include the Icelandic criteria (Danish Ministry of the Environment, 2009) in which safety distances are derived only for higher-tier Seveso establishments handling explosives. These suggested distances are divided into four classes according to building types and population density. Norway’s Fire and Explosion Prevention Act (Ministry of Justice and Public Security, 2002) states that all onshore hazardous facilities are responsible for implementing risk acceptance criteria. The regulation demands that the criteria should be compliant with the ALARP (As Low As Reasonably Practicable) levels, although it does not specifically offer any guidelines or recommendations in this sense. Thus, on the topic of LUP, no requirements are given by any regulation, apart from the necessity to undertake a risk analysis (Vinnem, 2010). In Romania during the first national risk assessment process in the framework of the Rorisk project (2015–2016) a number of 300 Sevesotype establishments were identified (General Inspectorate for Emergency Situations, 2016). Research studies on LUP revealed serious problems where residential areas are too close to the establishment (Gheorghiu et al., 2014). The MO 3710 has common elements with the Italian LUP criteria, being classified as a hybrid approach. The determination of adequate distances is based on the results of the risk assessment from the SR or MAPP, being the two basic documents required by Law no. 59/2016 (Parliament of Romania, 2016) (the Seveso-III transposed in the Romanian legislation). The main steps to follow are (MO 3710):

• Definition

•

and graphical representation of four impact zones (high lethality, beginning of lethality, irreversible and reversible effects). For each impact zone effect thresholds for fire, explosion and toxic dispersion scenarios are defined, which can lead to certain consequences. In the analysis only scenarios with a frequency between 10-3 – 10-6 events/year are recommended. Scenarios with a higher frequency than 10-3 events/year are not allowed and mitigation measure must be applied. Identification of territorial vulnerable elements–functional zones, classified in four main categories:

Type A: Industrial and storage areas; Type B: Ba – Type A areas and green areas, communal households, smaller transport routes; Bb – Public transport stations with low flux (maximum 100 persons/ hour); sports and leisure facilities with a capacity of maximum 100 persons; Type C: Ca – Type A and B areas and residential areas with maximum double-storied buildings; Cb – Commercial areas with a maximum capacity of 1000 persons; schools; health care institutes with less than 100 persons; sports and leisure facilities with a capacity of maximum 1000 persons; public transport stations with a maximum flux of 1000 persons/hour; Type D: Da – All above mentioned types. 5

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4. Methods

Table 1 Territorial compatibility matrixes (Source: MO 3710).

4.1. Hazard and risk assessment

Compatibility matrix for new Seveso sites Frequency (events/year)

Impact zones Radius of zone IV – Reversible effects (m)

Radius of zone III – Irreversible effects (m)

Radius of zone II – Beginning of lethality (m)

Radius of zone I – High lethality (m)

10−3 – 10-4 10-4 – 10-5 10-5 – 10-6 < 10-6

A A, B A, B, C A, B, C, D

A A A, B A, B, C

A A A A, B

A A A A

The case study focuses on a comparative risk assessment for LUP purposes for an existing Seveso site in Romania (Oltchim chemical plant), using the Romanian LUP criteria from MO 3710 versus a riskbased approach. The main steps of these two approaches are compared and presented in Fig. 1. Consequence and risk-based methods require a selection of relevant accident scenarios to determine whether a Seveso establishment meets the necessary LUP criteria. This selection is based on a systematic hazard assessment process, in which methods such as PHA (Preliminary Hazard Analysis) or HAZOP (Hazard and Operability Study) are used (Gheorghiu et al., 2013). The Romanian LUP criteria requires a physical effects analysis to determine the distances at which certain thresholds for each scenario can be reached, as presented in Table 2. Scenarios depending on the meteorological conditions, such as toxic or flammable gas dispersions, will result in different safety distances. Ministerial Order no. 156/11/12/2017 (Ministry of Internal Affairs, 2017b) (referred to as MO 156 hereinafter) establishes the methodology for the elaboration of emergency plans for Seveso-type sites. Annex 2 of MO 156, paragraph 11, implies the use of two distinct sets of sitespecific meteorological data, average and unfavorable conditions. Considering that scenarios in the emergency plans originate from SRs, the scenarios used in LUP should also be calculated with those two distinct meteorological conditions. The risk-based method involves the calculation of the locationbased IR, which assumes the probability of death for an unprotected individual present in a certain place during the year (Duijm, 2009). For the determination of the territorial compatibility, the authors are proposing two compatibility matrixes, for existing sites presented in Table 3 and for new sites in Table 4. The definitions of the functional zones have been preserved according to MO 3710. In the selection of

Compatibility matrix for existing Seveso sites Frequency (events/year)

Impact zones Radius of zone IV – Reversible effects (m)

Radius of zone III – Irreversible effects (m)

Radius of zone II – Beginning of lethality (m)

Radius of zone I – High lethality (m)

10−3 – 10-4 10-4 – 10-5 10-5 – 10-6 < 10-6

A, A, A, A,

A A, B A, B, C A, B, C, D

A A A, B A, B, C

A A A A, B

B B, C B, C, D B, C, D

Note: A, B, C and D represent the type of the functional areas.

Db – Protected areas; Dc – Protected natural areas;

• Determining the territorial compatibility based on the potentially affected •

vulnerable elements and scenario frequency, using the matrixes from Annex 3 of MO 3710, separately for new and existing establishments, presented in Table 1 of this paper. Use and integration of adequate distances in the land-use and urban planning, a task of the competent authorities.

Fig. 1. Flowchart of the Romanian LUP criteria versus the proposed risk-based approach. 6

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Table 2 Physical effects thresholds for accident scenarios. Scenario

High lethality threshold

Beginning of lethality threshold

Irreversible effects threshold

Reversible effects threshold

Toxic dispersion in air Dynamic heat radiation: Fireball Static heat radiation: pool fire, jet fire Instantaneous heat radiation: flash fire Overpressure from explosions

LC50 Fireball diameter 12,5 kW/m2 LFL 300 mbar

AEGL3 350 kJ/m2 7 kW/m2 50% LFL 140 mbar

AEGL2 200 kJ/m2 5 kW/m2 – 70 mbar

AEGL1 125 kJ/m2 3 kW/m2 – 30 mbar

where: LC50 – lethal concentration from which 50% of the affected population dies; AEGL - Acute Exposure Guideline Levels; LFL – Lower Flammable Limit.

Table 3 Proposed territorial compatibility matrix for existing Seveso sites. Individual risk

IR < 10−6

10−5 > IR ≥ 10-6

10−4 > IR ≥ 10-5

IR ≥ 10−4

Functional zone

A, B, Ca,b, D

A, B, Ca

A

Only inside site boundaries

Table 4 Proposed territorial compatibility matrix for new Seveso sites. Individual risk

IR < 10−6

10−5 > IR ≥ 10-6

IR ≥ 10−5

Functional zone

A, B, Ca,b, D

A, B, Ca

Only inside site boundaries

Fig. 2. The algorithm of the GIS workflow (Source: authors).

the individual risk levels versus the possibly affected functional zones the Flemish and Dutch risk acceptance criteria were considered to be the most appropriate. Societal risk calculations are not included, because of the lack of detailed population data.

to the distribution of population data from county level to land-cover polygons within each county. The resampling method can be described as an areal interpolation, combining land cover information, building densities from the JRC European Settlement Map (2012) and population data (Batista e Silva and Poelman, 2016). The Urban Atlas dataset used included the population data. The GIS analysis was conducted only for the Râmnicu Vâlcea Territorial Administrative Unit (TAU), being the single one with a population over 100,000 inhabitants. Based on these data a GIS model was developed and implemented in ArcGIS 10.3. The schematic structure of the model is presented in Fig. 2. First, the population data was joined with Urban Atlas data, thus resulting in the first parameter of the model. The second input is data from the risk analysis software, consisting of different impact areas in the shape of polygons. The algorithm will process the land-use data in order to re-class the land-use classes into functional zones A, B, C and D according to MO 3710. The classes and corresponding risk areas are presented in Table 5. For some of the Urban Atlas classes there is no equivalent class in

4.2. Territorial compatibility analysis using GIS The GIS analysis stage is based on data from the Urban Atlas 2012, a robust geographical dataset including land-use and land-cover data for almost 700 functional urban areas in 31 European countries, and resampled population data to the level of Copernicus Urban Atlas polygons. The required tables were downloaded from the Copernicus Land Monitoring Service website. The Urban Atlas is available at panEuropean level for Large Urban Zones with more than 100.000 inhabitants (Copernicus Land Monitoring Service, 2019a, 2019b). The population estimation was done by disaggregating census population reported at country-specific geometries (“source geometry”) to the Urban Atlas land-use / land-cover polygons (“target geometry”) (Batista e Silva and Poelman, 2016). In this context, the method refers 7

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Table 5 Adjusting Urban Atlas Land-use classes to Romanian functional zone classes. (Source: authors, based on Urban Atlas land-use classes). No.

Land-use classes (Urban Atlas)

Romanian functional zone classes

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Arable land (annual crops) Construction sites Continuous urban fabric (S.L.: > 80%) Discontinuous dense urban fabric (S.L.: 50% - 80%) Discontinuous low-density urban fabric (S.L.: 10% - 30%) Discontinuous medium density urban fabric (S.L.: 30% - 50%) Discontinuous very low-density urban fabric (S.L.: < 10%) Forests Green urban areas Herbaceous vegetation associations (natural grassland, moors…) Industrial, commercial, public, military and private units Isolated structures Land without current use Mineral extraction and dump sites Open spaces with little or no vegetation (beaches, dunes, bare rocks, glaciers) Other roads and associated land Pastures Permanent crops (vineyards, fruit trees, olive groves) Railways and associated land Sports and leisure facilities Water Wetlands

B A D D C C B B B B A B A A A B B B B C NA NA

Fig. 3. Location of the Seveso site in Râmnicu Vâlcea TAU (Source: authors’ work, using ArcGIS).

the Romanian legislation, and they were marked with NA in Table 5. Besides not having an equivalent class in the Romanian legislation, these Urban Atlas classes (water and wetlands) are particular, because they are not suitable for human habitation, thus, lacking population data. As such, these two classes are not relevant in the risk assessment

approach targeting human populations. As the algorithm will require an intersection between the Urban Atlas classes (including population) and the risk areas, there is a need to obtain new population figures for each intersected polygon. Since there is no detailed population data, an average population density for each

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Fig. 4. Romanian LUP criteria: Effects thresholds intersecting functional zones in Râmnicu Vâlcea TAU – instantaneous chlorine cloud, average meteorological conditions. (Source: authors’ work, based on modelling results and ArcGIS workflow).

Urban Atlas polygon (that later can be used in order to determine the population of each new intersected - Urban Atlas/risk areas- polygon) was done. First, the area of each polygon was determined, and then, the average density by dividing the population to the area was calculated, resulting in the number of people/ km2. The next step is the processing of risk areas. As these are not generated in the GIS environment, the first step was to check and repair geometry errors. After that the polygons were processed in order to avoid overlapping, resulting the final analysis areas. These two data layers were intersected resulting in a new data layer with risk classes and population data. Based on the new areas and population density determined in the previous stage, new population values were calculated for each polygon. The results were integrated using summary statistics, resulting in population numbers and total area for A, B, C and D zones in each impact class determined with Effects and Riskcurves.

in the Getic Sub-Carphatian Depression, central-eastern part of Vâlcea county and the south-western corner of the Râmnicu-Vâlcea TAU. Various materials are produced there, from inorganic chlorine-based products (e.g., liquefied chlorine, hydrochloric acid, liquid and solid caustic soda) to macromolecular products (polyether polyols, vinyl chloride monomer, polyvinyl chloride etc.) and organic synthesis products (propylene glycol, oxo alcohols etc.) (Oltchim, 2018b). The main raw material used in the chemical processes is salt, deposits being located at only 8 km away. This was one of the main reasons when the plant’s location was chosen, among other important criteria, such as the main road that connects the Transylvania and Oltenia regions, the proximity of the water source from the Olt river and the work force from Râmnicu-Vâlcea city. In contrast with these economic benefits, the proximity of the site to residential areas can present a higher risk and it can lead to LUP problems. As it can be observed from Fig. 3 the site is very close to residential areas, the first houses being located about 500 m both on the south-eastern and northwestern parts of the plant. Near the industrial site the Olt valley has a NE – SW direction, but along the river the orientation of the valley changes to N–S. From the Olt Corridor a series of valleys formed by its tributaries are detached, with the Sâmnic Valley being located to the northeast of the site and the Sărata and Govora Valleys to the west. The altitude varies between

5. Case study 5.1. Description of the study area The Oltchim site, one of the biggest chemical plants in Romania, was constructed in the 1960s, being located on the Olt River’s Corridor 9

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Fig. 5. Romanian LUP criteria: Effects thresholds intersecting functional zones in Râmnicu Vâlcea TAU – instantaneous chlorine cloud, unfavorable meteorological conditions. (Source: authors’ work, based on modelling results and ArcGIS workflow).

350–450 m in the inter-stream areas and about 210 m east of the studied site, in the Olt floodplain (Bălteanu et al., 2003). This topography is highly influencing the circulation of air masses, and, in the event of a chemical accident, the path of the toxic cloud. The average wind rose indicates the south direction as dominant (13.5%), followed by the northern one (10.2%), the average atmospheric calm being quite high in the region (37.4% of the cases). Annual average speeds are generally small, below 2.0 m/s. The strongest wind blows on average from the north (2 m/s), and the weakest in the eastern direction (0.9 m/s) (National Meteorological Administration of Romania, 2019a). The main watercourse that crosses the city of Râmnicu Vâlcea is the Olt River, which is one of the most important rivers in Romania. A lot of channelization works and reservoirs have altered the natural condition of the river substantially, with Govora Lake being located in the immediate vicinity of the site (Dinu, 1999). Due to these reservoirs, the risk of floods in this area is insignificant (Rorisk, 2016). The land-use shows a rather high complexity, mainly commanded by the underlying landforms. Thus, the adjacent Olt River flood-plain and terraces are covered by arable lands and built-up areas (industrial and residential). On the other hand, the broad-leaved oak forests stretch on vast territories in the east and southwest inter-stream areas. The

pastures on the hills of the western side also have a high percentage. 5.2. Scenario selection and risk analysis To develop the case study, a hypothetical situation considering the presence of only two storage vessels, one 80 m3 horizontal cylindrical vessel storing liquefied chlorine and one 2000 m3 spherical vessel containing propylene, was analyzed within the same Seveso site. In reality, the risk assessment should take into consideration all equipment, storing or processing dangerous substances, relevant to safety. All data used in the study is publicly available at the operators’ website (Oltchim, 2018a). For the chlorine storage tank, as a primary source in selecting the relevant scenarios a catastrophic mechanical rupture was considered. The event describes a full loss of containment followed by an instantaneous formation of a toxic cloud. Most of the liquefied chlorine forms a puddle that in turn evaporates gradually into gas, feeding continuously the toxic cloud. For the propylene storage tank, a BLEVE scenario with the formation of a fireball was deemed relevant. Because of the lack of publicly available site-specific information,

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Fig. 6. Romanian LUP criteria: Effects thresholds intersecting functional zones in Râmnicu Vâlcea TAU – propylene tank BLEVE scenario. (Source: authors’ work, based on modelling results and ArcGIS workflow).

scenario frequencies from generic event frequency data sets available in literature were selected. For the chlorine storage tank catastrophic rupture a frequency F = 5*10-6 events/year was selected, while for the propylene tank BLEVE a frequency F = 1*10-5 events/year (HSE, 2012) was selected. Considering the Romanian LUP criteria, in both cases the frequency was higher than the limit of 10-6 events/year and, therefore, both scenarios were analyzed in terms of territorial compatibility. The toxic release scenario was divided into “instantaneous cloud” dispersion and cloud dispersion from evaporating pool, both cases analyzed using two sets of site-specific meteorological data. The physical effects analysis was conducted using the modelling software Effects, from TNO Built Environment and Geosciences - the Netherlands. The risk-based method requires the use of a larger set of meteorological data. In this case, 5-year site-specific daily average data were used (National Meteorological Administration of Romania, 2019b). As a result, the IR was calculated and represented on maps in the form of isorisk curves, using Riskcurves software (TNO).

Fig. 4 shows the possibly affected functional zones (A, B, C, D) in the event of a toxic dispersion of instantaneously formed chlorine cloud in average meteorological conditions, while Fig. 5 presents the case of unfavorable conditions. One can observe that in both meteorological conditions the effects thresholds can extend outside Râmnicu Vâlcea TAU, covering very large areas. Compared to average conditions, in case of unfavorable conditions the distances for thresholds are almost double. The explanation resides in the fact that stable atmospheric conditions and low wind speed have a negative influence on the dispersion process. In both cases, using the matrix presented in Table 1, a territorial incompatibility is found. The results obtained for the cloud dispersion from evaporating pool are similar to the ones mentioned above, therefore they were not presented in this study. Fig. 6 presents the results obtained for the propylene tank BLEVE scenario, using the Romanian LUP criteria. Compared to the chlorine toxic dispersion scenario, one can observe much smaller affected areas. With the exception of a very small area to the north, representing the reversible effects, all the rest of the areas are inside Râmnicu Vâlcea TAU. Nevertheless, the high lethality area intersecting functional zones B and C results in territorial incompatibility when using the matrix from Table 1. The results of the analysis using the risk-based approach are presented in Fig. 7. In this case, all the scenarios are represented in a single

6. Results and discussions The results of the physical effects calculations combined with GIS analysis, considering the Romanian LUP criteria are presented below. 11

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Fig. 7. Risk-based approach results – IR iso-curves. (Source: authors’ work, based on modelling results and ArcGIS workflow).

figure in the form of IR iso-curves cumulating the risks. It can be observed that IR levels higher than 10-5 deaths/year (red curve) reached outside the boundaries of the establishment, affecting functional zones of all four categories. Based on the proposed territorial compatibility matrix (Table 3) the risk is not acceptable. Table 6 summarizes the results for all the scenarios analyzed using the Romanian LUP criteria. The surfaces corresponding to each threshold intersected with functional zones and calculated population in TAU Râmnicu Vâlcea were listed and incompatibilities were marked with red colour. Table 7 present the results obtained using the proposed risk-based LUP criteria. As long as there is no nationally implemented risk assessment methodology for the elaboration of SRs or MAPPs, the selection of relevant accident scenarios for LUP will always be a subject of debate. Thus, it seems fair to take the maximum distances resulting from the analysis, in this case, the ones from the instantaneous cloud dispersion in unfavorable conditions. For High lethality threshold a total surface of 6.88 km2 was found incompatible with the present functional zones in TAU Râmnicu Vâlcea, while for Beginning of lethality threshold: 142.31 km2; for Irreversible effects threshold: 1.85 km2; for Reversible effects threshold no values could be determined, the subjected area being outside of the TAU limits. The BLEVE scenario resulted in much

smaller distances, therefore the territorial compatibility of the site was assessed based on the previous scenario. When using the proposed risk-based LUP criteria, the total incompatible surface within IR ≥ 10-5 was only 0.373 km2, while for 105 > IR ≥ 10-6 was 0.004 km2. For IR < 10-6 no incompatibility was found. The analysis showed territorial incompatibility in both cases. Even if the thresholds in the two methods are not directly comparable, the problematic areas were significantly smaller when using the risk-based criteria. In the case of territorial incompatibility, the authorities responsible for LUP together with competent authorities for applying the provisions of Law no. 59/2016 take measures to enforce additional technical requirements for risk reduction and vulnerability mitigation (MO 3710). When applying the Romanian LUP criteria, more expensive risk reduction measures would be necessary to obtain compatibility. Table 8 is summarizing the necessary data, strengths and limitations of the two LUP criteria applied in the study. Furthermore, the following problems have been identified: (a) Without a well-established risk assessment methodology, the selection of scenarios for territorial compatibility analysis can be very subjective. (b) There is no guideline in the Romanian legislation on how to assess

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Table 6 Territorial compatibility results for the scenarios using the Romanian LUP criteria. (Source: authors’ work, based on modelling results and ArcGIS workflow)

the frequencies of scenarios. One can chose to use generic frequency data or more complex probabilistic methods (fault trees and event trees) resulting in different frequency values. It is also a risk that, due to subjectivity in frequency estimation, when using generic data, some relevant scenarios will not be analyzed, if their values fall under the 10-6 events/year limit. (c) The AEGL thresholds are not suitable for territorial compatibility analysis. AEGLs are exposure guidelines designed for use in emergencies involving dangerous chemical substances where population

is exposed to a hazardous airborne chemical (NOAA, 2018). (d) It is not mentioned which exposure periods and corresponding AEGLs should be used. (e) There is no official and sufficiently detailed data on population and functional zones to be used in the analysis. Consequently, a limitation in GIS analysis is that the Urban Atlas provides data for TAUs which have more than 100,000 inhabitants. Thus, our analysis focuses only on Râmnicu Vâlcea TAU, but potentially affected areas can include other TAUs. 13

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Table 7 Results of GIS analysis using the risk-based LUP criteria. (Source: authors’ work, based on modelling results and ArcGIS workflow).

Table 8 Necessary data, strengths and limitations of the LUP criteria.

Necessary data

Romanian LUP criteria

Proposed LUP criteria

- two sets of local meteorological data including: wind speed, temperature, relative humidity, atmospheric stability class, solar heat radiation;

- a larger set of local meteorological data including: wind direction, wind speed and stability class distribution, temperature, relative humidity, for a longer period; - process-related data - event frequency data - land-use data; - toxicological data for Probit functions; - a single IR map to be analyzed for territorial compatibility; - more comprehensive LUP map, leading to easier decision making process; - more reasonable results, based on exposure calculations; - risk ranking of scenarios according to their contribution in the overall risk; - processing of raw meteorological data can be time consuming; - expensive meteorological data; - complex and expensive modeling software required;

- process related data; - event frequency data; - land-use data; Strengths

- physical effects analysis is less time consuming; - cheap meteorological data; - less complex modeling software can be used;

Limitations

- more time consuming LUP due to mapping of each individual scenario; - analysis may result in territorial incompatibilities due to overestimated safety distances;

sources of political power, knowledge of risks can have a political significance (Shrivastava, 1995). As public safety in Romania is deficient, due to legislative gaps, therefore authors outline a set of recommendations for stakeholders, in general, and for policy-makers, in particular, who are responsible for enforcing safety standards:

(f) Land-use classes from Urban Atlas and those from Romanian MO 3710 do not correspond. In the Urban Atlas there are 27 classes, Romanian legislation includes only 4. Consequently, an adjustment has to be made in order to reclassify Urban Atlas classes according to national legislation. This can lead to inconsistencies between classes. (g) The models used do not consider complex terrain topography, assuming that the dispersion can take place in each wind directions in the same manner, resulting in very large areas. (h) The environmental effects and consequences of a possible chemical accident in these two approaches are not considered. Therefore, it is almost impossible to quantify these consequences when the thresholds intersect functional zone type D with natural protected areas.

(i) Development and adoption in the Romanian legislation of welldefined and tested risk assessment methodology is of utmost importance and this methodology should stand at the basis of Safety Reports, Major-Accident Prevention Policies, Emergency Planning and LUP. (ii) The authors strongly recommend the adoption of a risk-based method for LUP purposes, which gives more realistic results of possibly affected areas, considering both consequences (based on exposure period) and frequencies in the calculation of risk. The combination of risk modelling and GIS technique can ease the process of compatibility analysis and decision-making. (iii) In case of the adoption of a risk-based method, different compatibility matrices are recommended for existing and for new Seveso establishments, the criteria being more restrictive for the latter. Preliminary risk assessment results should be used in order to choose the optimal location of hazardous equipment.

7. Conclusions Trends in the risk assessment methods show that they evolve towards easy-to-use tools based on the determination of risk indexes (Băbuţ, 2011). Within this dynamic context, the overall aim of the paper was to contribute to the clarification of some methodological aspects regarding an integrated approach of the risk assessment for an industrial site. Consequently, the paper presents an important topic of process industry, the risks related to the use of dangerous substances in chemical processes, the main assessment concepts and their use in LUP activities. The outcomes of the study can provide guidance on the appropriateness of risk assessment methodology that, above everything else, needs to address public safety. At first sight, one might think that, from a practical perspective, the significance of such research is obvious for the safety engineers committed to continuous safety assurance in operating installations and equipment, in reducing the risk of accidents generated by the storage and handling of hazardous substances on site. However, as knowledge and expertise in general are considered also as

A significant contribution of a future study will be the validation of the risk-based method, as well as the sensitivity and uncertainty analysis, which represent important steps towards the acceptance of the method as a Decision Support Tool. Finally, the authors hope that the herein proposed risk assessment method, besides bridging knowledge gaps in the field of public safety, has the potential to transform itself into lex ferenda (future law) or policy strategies targeting a more effective way of addressing LUP based on a risk-based method, not only in Romania, but also in other countries that face similar risk assessment challenges.

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Acknowledgements

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