ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on July 30, 2008
ICES Journal of Marine Science: Journal du Conseil 2008 65(8):1436-1441; doi:10.1093/icesjms/fsn117
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This article appears in the following ICES Journal of Marine Science issue: Marine Environmental Indicators: Utility in Meeting Regulatory Needs [View the issue table of contents]
Development of a multistep indicator-based approach (MIBA) for the assessment of environmental quality of harbours
1 Department for the Study of Territory and Its Resources (DIPTERIS), University of Genoa, Corso Europa 26, 16132 Genoa, Italy
2 Department of Biology (DIBIO), University of Genoa, Viale Benedetto XV, 16132 Genoa, Italy
Correspondence to V. Marin: tel: +39 010 353 8069; fax: +39 010 353 8066; e-mail: marin{at}dipteris.unige.it
Marin, V., Moreno, M., Vassallo, P., Vezzulli, L., and Fabiano, M. 2008. Development of a multistep indicator-based approach (MIBA) for the assessment of environmental quality of harbours. – ICES Journal of Marine Science, 65: 1436–1441.Environmental pollution in harbours can have detrimental effects on the port, its users, and the surrounding environment. Despite these risks, the Italian legal framework for marine environmental quality does not apply to harbours and marinas, so monitoring is not mandatory. With the aim of supporting environmentally sound management, we propose an indicator-based protocol to assess the environmental quality of harbours through the development of a flexible and site-specific multistep indicator-based approach (MIBA), which gives special consideration to local features. MIBA comprises three steps: (1) development of a simple tool for harbour-specific identification of vulnerable areas and for designing monitoring schemes; (2) selection of suitable environmental quality indicators of different levels of complexity and applicability to the typologies of risks involved; and (3) development of a user-friendly interpretation scheme based on categorical risk values and a visualization code. The approach has been tested in two case studies in marinas located in the Ligurian Sea (Italy).
Keywords: environmental management systems, harbour, indicators, monitoring, sediment quality, water quality
Received 11 November 2007; accepted 15 May 2008; advance access publication 30 July 2008.
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Introduction |
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 Top Introduction Assessing environmental quality...DiscussionReferences |
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Harbours are the final destination of many environmental contaminants that derive mostly from human activities, such as dredging, cargo handling, ship discharge, and disposal of untreated ship, domestic, and industrial wastes. Depending on the number and nature of contamination sources, as well as port design and hydrodynamic regime, the pollution load and its typology can differ markedly within and among harbours. Water and sediment contamination not only affects the quality within the port itself, but can also have detrimental effects on the surrounding environment and ultimately on human health. Despite these risks, Italian regulations do not mandate monitoring in harbours and marinas; until now, environmentally sound management of harbours has depended solely on voluntary monitoring by local authorities and private managers.
Environmentally sound management policies for harbours and recreational boating have been developed worldwide in recent years. The Clean Marina Initiative in the US is one example (http://cleanmarinas.noaa.gov), based on a set of management measures for controlling pollution from various non-point sources, as defined by the Environmental Protection Agency (EPA, 1993, 2001). Many US marinas have voluntarily adopted its requirements, so receiving Clean Marina awards (EPA, 1996). In recent years, similar programmes based on the adoption of voluntary accreditation systems or awards have been promoted in other countries, such as the Australian Clean Marina Programme (http://www.marinas.net.au/clean_about.php) and the Blue Flag Award, which in 2007 involved 640 marinas worldwide, including 55 in Italy (http://www.blueflag.org).
In Italy, environmental concerns about the rapid development of the nautical pleasure-craft sector have increased in recent years. In particular, environmentally sound management of harbours and marinas is emerging as a priority in the Ligurian Sea (northwest Mediterranean), an important region for coastal tourism and recreational boating, with the capacity for >14 000 boats in 56 marinas. Local administrators are addressing this development, especially because the Regional Coastal Plan anticipates the possible addition of almost 10 000 new berths within the next few years (Ligurian Region, 1999).
Within the framework of an environmental protection plan (the RAMOGE Agreement; Saint Raphaël, Monaco, and Genoa) signed by the governments of France, Italy, and Monaco for the coastal area of the Provence–Alpes–Côte d’Azur Region, the Principality of Monaco, and the Ligurian Region, RAMOGE (2001) reported on a first attempt to define guidelines for the sustainable development of the nautical-tourism sector. In 2004, the EU financed the LIFE Project PHAROS (Playgrounds, Harbours, and Research of Sustainability; www.lifepharos.it), aimed at testing best practices for the sustainable management of tourist facilities and identifying a methodology for registering marinas under the Eco-Management and Audit Scheme (EMAS), according to EU standards (EC Regulation No. 761/2001). Within this project, an indicator-based protocol has been developed to assess the environmental quality of harbours through the development of a flexible and site-specific multistep indicator-based approach (MIBA).
We describe the main characteristics of the approach, which has been tested in two case studies of marinas in the Ligurian Sea. The results of the application have been included in the Initial Environmental Review and in the Environmental Management System for the EMAS registration of the two marinas.
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Assessing environmental quality of harbours |
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TopIntroductionAssessing environmental quality...DiscussionReferences |
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The approach gives special consideration to local features and consists of three steps: (1) identification of vulnerable areas; (2) selection of suitable environmental quality indicators; and (3) communication of results.
Step 1: identification of vulnerable areas
Environmental disturbance in harbours may vary over small spatial scales, owing to the position and magnitude of pollution sources (e.g. sewage outfalls, fuel stations, maritime traffic), river inputs, tidal regime, and water circulation, the last-named being dependent on location, shape, and size of the harbour (Fabiano et al., 2006). This combination of factors makes harbours representative of highly heterogeneous environments in terms of levels of disturbance, pollution, and oxygen concentration (Estacio et al., 1997; Moreno et al., 2008). Therefore, identifying areas that are subject to different levels of environmental risk is a useful primary step in the correct assessment of environmental quality and the planning of monitoring schemes.
We developed a simple tool for making preliminary assessments. Harbour vulnerability (HV) was defined as the likelihood of negative environmental changes that result from human activity. HV was quantified by developing a numerical index that accounts for specific morphological features (as an indirect measurement of water stagnancy) and the position, size, and typology of pollution sources. The calculations use three main parameters: (i) the distance between the site and waste sources; (ii) the distance between the site and port mouth; and (iii) the presence and position of a wharf. The algorithm is reported in Fabiano et al. (2006) and Vassallo et al. (2006). The parameters are calculated separately and are independent and uncorrelated. After all parameters are calculated, they are standardized on a 1–100 scale. The distance from a pollution source is considered to reduce vulnerability, so is standardized on an inverse scale. An integrated HV value is then obtained for each harbour zone by simple summation. Lastly, standardization of the output makes HV a relative measure for each individual harbour, ranging from a minimum to a maximum value. As final output, the tool can produce vulnerability maps automatically, using Matlab (MathWorks, Inc.). Alternatively, a simple guideline is available to assist manual calculation. The output provides a first indication of the risk classes to be targeted (see below) and can thereby guide the selection of the number and location of sampling stations and of a suitable sampling frequency for setting up a monitoring plan.
Step 2: selection of an indicator set
The next step is to identify a list of specific indicators. We selected these from a draft list of eligible indicators that was based on both peer-reviewed and grey scientific literature, also taking into account the specific guidelines from environmental agencies (e.g. European Environment Agency, US Environmental Protection Agency, and National Oceanic and Atmospheric Administration) and existing national and international legal directives for marine and coastal quality assessment. The draft was presented to a panel of expert reviewers whose comments, after careful consideration, were used to produce a final list of 52 indicators together with suggested reference scores or thresholds (Table 1). The indicators included a selection of benthic-community-based indicators (Bongers, 1990; Borja et al., 2000; Simbora and Zenetos, 2002; Rosenberg et al., 2004), which address the ecological status as a whole (following recommendations provided in European environmental directives), but they require skilled labour. A technical fact sheet for each indicator was prepared, including definitions, main legal and bibliographic references, and proposed thresholds and suggestions for their specific application in harbours (Fabiano et al., 2006).
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Before selection, the indicators had been classified according to three groups, targeting different types of risk: dystrophic, chemical, and microbiological. This greatly helped in their interpretation in terms of classifying quality status. Indicators were also classified according to whether they related to water or sediment measurements, because these two compartments provide different but complementary information. Specifically, the aquatic compartment reflects the environmental state at the time of sampling and may be highly variable in relation to climatic, environmental, and human-linked variables. In contrast, sediments are the final storage place where pollutants accumulate, so serving as a temporally integrated record that is less influenced by variations in pollution load in the recent past (Vezzulli and Fabiano, 2006).
Because of the voluntary nature of applying the protocol and the cost benefits involved, the indicators were also classified according to three levels (I–III) of effort involved in obtaining useful information on environmental quality. These levels are associated with different degrees of complexity, ranging from easy-to-apply and less informative to time-consuming, skill-requiring, and more informative indicators (Table 1).
The application of Level I indicators is proposed as the minimum requisite for implementation of an Environmental Management System (EMS) for EMAS registration. In fact, these can be monitored easily and at low cost by local harbour authorities without requiring specific skills, but are still capable of identifying critical situations in the port basin, especially when monitored frequently. The main obstacle to this approach is its low sensitivity: these indicators can only signal an unacceptable environmental quality when it has already become manifest. To obtain environmental awards, bad situations must be avoided and a more extensive monitoring plan must be implemented, incorporating Level II indicators. These are also required to undertake the complete Initial Environmental Review foreseen by the EMAS procedure. When critical situations do occur, a monitoring plan involving Level III indicators should help to pinpoint the actual causes of the problem. Importantly, higher level indicators might be selected based on lower level ones in relation to risk typology. For instance, the hierarchic sequence for dystrophic risk might be: I (bed smells)
II (redox potential at the sediment–water interface)III (Acide Volatile Sulphide) (Table 1).
Step 3: communication of results
To influence management effectively, elaborate monitoring results must be translated for managers so as to be easily understood and communicated. Towards this goal, we developed a user-friendly interpretation scheme based on categorical risk classes. For Level I indicators, the presence–absence criterion was applied to indicate bad or good quality, respectively. The threshold values for Level II and III indicators (Table 1) were used to classify environmental quality status as (i) good, (ii) alerting, and (iii) warning. These classes largely correspond to the range of values observed in coastal marine systems that are (i) largely unaffected by human activities, (ii) clearly influenced, and (iii) experiencing severe environmental problems, respectively. This system can be easily transposed into a visualization code using colours or symbols (Table 2), which will facilitate data interpretation and communication to the general public, and could be used in the Initial Environmental Review and in the public Environmental Statement requested by EMAS.
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Application
The tool developed in Step 1 was tested by computing HV maps for two marinas located in the Ligurian Sea: Marina degli Aregai (Santo Stefano al mare) and Portosole (Sanremo) using digitalized port coastline and contour imaging with an appropriate colour scale (Figure 1). In Marina degli Aregai, HV was mainly linked to the presence of a fuel station and a shipyard. In Portosole, HV depended largely on the degree of water stagnancy, which could lead to the accumulation of pollutants even from minor sources, whereas another vulnerable area was related to the proximity of the entrance because of a nearby commercial harbour. In both marinas, the inner areas were identified as being most vulnerable.
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The protocol developed in Steps 2 and 3 was tested in the two marinas by assessing a subset of the indicators for which data were collected on two occasions (summer and winter) at sampling stations located in the different HV areas (for details see Fabiano et al., 2006; Moreno et al., 2006, 2008). The monitoring highlighted warning situations only in terms of dystrophic risk (redox potential) in both marinas and of chemical risk related to mercury in Marina degli Aregai. The results corresponded broadly to the HV areas detected by Step 1 in Portosole, whereas at Marina degli Aregai, some discrepancies were found (Table 2).
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Discussion |
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TopIntroductionAssessing environmental quality...DiscussionReferences |
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A major goal of harbour environmental monitoring programmes is to assess site-specific risks correctly and to suggest ways to reduce these risks. In addition, monitoring programmes should detect short-term (hours or days) risk-related events successfully, but the economic and logistic demands made on available resources must be sustainable. The MIBA approach was developed based on these concepts to help administrators and authorities pursue environmentally sound management of harbours. The application of the protocol in the two case studies demonstrated the potential value of this approach. First, identification of vulnerable areas to provide a preliminary assessment of site-specific harbour features also provides an early indication of the risk classes to be targeted (Figure 1), so can provide a useful guide for local managers to select sampling stations and frequency. Although a close correspondence was found between the HV areas detected in Step 1 and the dystrophic risk suggested by indicator values obtained in Steps 2 and 3 at the two harbours, some mismatches also emerged. Some of these may be explained by the occurrence of unforeseen events. For instance, the worst conditions according to the indicator values were at Stations 3 and 4 at Marina degli Aregai, while the HV map suggested a low vulnerability. This may have been the result of a storm that occurred just before sampling time, which could have resulted in an accumulation of organic matter from the port outlet. In other cases, more complex factors not accounted for in the simplistic HV evaluation, such as the synergistic–antagonistic interaction of pollutants, might be responsible for mismatches. Cues for additional problems may only be highlighted by the experimental assessment of selected indicators (Steps 2 and 3). Community indicators are particularly suited for this purpose, because they integrate the effects of different pollutants and their interactions on biological assemblages (Rosenberg et al., 2004). It is worth noting that "good" threshold values for community indicators were selected to match a general healthy state found in pristine coastal marine environment, whereas "warning" values mostly matched highly compromised environmental conditions (see Table 1 for references). Because harbours, by their very nature, can hardly be expected to contain a "pristine" environment, the "alerting" score can generally be expected for harbours that are not highly compromised, as was the case in both harbours investigated (Table 2).
In conclusion, we emphasize that the application of the MIBA protocol must be backed up by a response system that undertakes appropriate management actions. This implies a correct interpretation of the monitoring output, for instance in the form of a catalogue of recommended measures, and eventually the institution of an advisory group of experts mandated to assist during subsequent mitigation or recovery phases.
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Acknowledgements |
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We thank the Ligurian Region (especially Daniela Minetti and Laura Muraglia), the Marina degli Aregai and Portosole, project partners, and all those who supported the study by participating in the expert panel for indicator selection. The research was funded by the EU within the LIFE Environment Programme as Project PHAROS: "Playgrounds, Harbours, and Research of Sustainability" (ENV/IT/00437).
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  M. Moreno, L. Vezzulli, V. Marin, P. Laconi, G. Albertelli, and M. Fabiano The use of meiofauna diversity as an indicator of pollution in harbours ICES J. Mar. Sci., November 1, 2008; 65(8): 1428 - 1435. [Abstract] [Full Text] [PDF]
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