ENVIRONMENTAL PRESSURE OF MAJOR TOURISM INFRASTRUCTURES: MARINAS

    Panel 1
    Update date
    Authors

    Giovanni Finocchiaro, Silvia Iaccarino

    Abstract
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    Abstract

    Coastal tourism infrastructures, and in particular marinas, exert significant pressures on marine and coastal ecosystems. The indicator assesses the potential environmental pressure associated with marinas through the total number of berths and their density per kilometre of coastline at the regional level. Based on 2023 data, the total number of berths in Italy amounts to 161,778, with a national average density of 19.6 berths per km of coastline, showing an increase compared to 2022 and a strongly uneven territorial distribution.

    Description

    Ports serve as key tourist attractions along the coast, enhancing the value of local tourism services and attracting specific types of tourists. However, the construction of marinas can harm coastal ecosystems and impact shoreline morphology.

    The size of a marina, in terms of number of berths, serves as a key indicator of usage intensity. The greater the number of berths in a marina, the higher the potential for:

    • Pollution from boat maintenance activities
    • Environmental stress caused by recreational maritime activities

    Studies have shown that antifouling paint residues are commonly found in marina sediments, posing a threat to the local marine environment.

    This indicator presents, for coastal regions, the number of berths per kilometer of coastline.

    Purpose

    To monitor the potential pressure exerted by marinas on local marine environments.

    Policy relevance and utility for users
    It is of national scope or applicable to environmental issues at the regional level but of national significance.
    It is able to describe the trend without necessarily providing an evaluation of it.
    It is simple and easy to interpret.
    It provides a representative overview of environmental conditions, environmental pressures, and societal responses.
    It provides a basis for international comparisons
    Analytical soundness
    Be based on international standards and international consensus about its validity;
    Be theoretically well founded in technical and scientific terms
    Presents reliability and validity of measurement and data collection methods
    Temporal comparability
    Spatial comparability
    Measurability (data)
    Adequately documented and of known quality
    Updated at regular intervals in accordance with reliable procedures
    Readily available or made available at a reasonable cost/benefit ratio
    An “adequate” spatial coverage
    An “appropriate” temporal coverage
    Main regulatory references and objectives

    There are no mandatory compliance targets for this indicator. However, it falls within the broader regulatory framework of European and national policies on sustainable tourism, as well as EU regulations on marine-coastal ecosystems (e.g., Marine Strategy Framework Directive, Habitat Directive, and national/local spatial planning regulations).

    DPSIR
    Pressure
    Impact
    Indicator type
    Descriptive (A)
    References

    Anthony, E. J. (1997): The status of beaches and shoreline development options on the French Riviera: a perspective and a prognosis. Journal of Coastal Conservation 3: 169-178.

    Cassi, R., Tolosa, I. & De Mora, S. (2008): A survey of antifoulants in sediments from Ports and Marinas along the French Mediterranean coast. Marine Pollution Bulletin 56 (11): 1943-1948.

    Konstantinou, I. K. & Albanis, T. A. (2004): Worldwide occurrence and effects of antifouling paint booster biocides in the aquatic environment: a review. Environment International 30: 235-248.

    Martínez, K., Ferrer, I., Hernando, M. D., Fernández-Alba, A. R., Marcé, R. M., Borrull, F. & Barceló. D. (2001): Occurrence of Antifouling Biocides in the Spanish Mediterranean Marine Environment. Environmental Technology 22 (5): 543-552.

    Data source

    ISPRA  

    MIT (Ministry of Infrastructure and Transport)

    Data collection frequency
    Yearly
    Spatial coverage

    Coastal regions

    Time coverage

    2010-2023

    Processing methodology
    • Number of berths per region.
    • Types of structures.
    • Length-based classification.
    • Percentage distribution per kilometer of coastline.
    Update frequency
    Year
    Data quality

    This indicator aligns with the European equivalent identified by the Eionet network, coordinated by the European Environment Agency, as a potential reporting mechanism on Tourism and Environment.

    The quality of the information is high, thanks to the authority of the data sources, which ensure good measurability and comparability over time and space.

    Status
    Poor
    Trend
    Negative
    State assessment/description

    In 2023, Italy has a total of 161,778 berths, with an average density of 19.6 berths per kilometre of coastline. The regional picture highlights strong differences: Friuli-Venezia Giulia shows density values exceeding 130 berths per km of coastline, while Liguria, with 24,853 berths, records a density of 65.7 berths per km. By contrast, Sardinia (8.5 berths/km), Calabria (9.2 berths/km), and Sicily (11.1 berths/km) register significantly lower levels. Overall, the status is assessed as poor, in relation to the high infrastructural concentration in specific coastal areas and the associated potential environmental impacts (Table 1).

    Trend assessment/description

    Over the period 2010–2023, the number of berths in Italy shows an overall increasing trend, indicating a progressive strengthening of infrastructural endowment supporting recreational boating and coastal tourism. This dynamic reflects, on the one hand, a growing demand for tourism and recreational services linked to the sea, with potential positive effects in economic and employment terms at the local level.

    From an environmental perspective, however, the structural increase in berths entails a rise in potential pressure on coastal ecosystems, particularly in areas already characterized by high infrastructural density. Although the change observed in the 2022–2023 comparison is limited, it fits within a long-term trend that requires attention in terms of planning and sustainable management.

    Overall, the trend is assessed as moderately negative from an environmental point of view, while acknowledging the role of marinas as a driver of economic development and tourist attractiveness of coastal areas (Figure 1).

    Comments

    In 2023, the distribution of berths along the Italian coastline shows marked territorial unevenness, as illustrated in Figure 2, with a strong concentration of infrastructures in some northern and central regions and significantly lower values in island and southern regions. This configuration reflects different models of development of recreational boating and diverse geomorphological and settlement characteristics of the coastlines.

    The spatial interpretation of the indicator highlights that potential environmental pressure is not evenly distributed, but is locally significant in areas with the highest density of marinas. These elements underline the importance of differentiated coastal planning policies, aimed at balancing tourism and economic development needs with the protection of marine and coastal ecosystems.

    Data
    Headline

    Table 1: Number of berths by region, type of structure and length classes and percentage of distribution per km of coast (30/9/2023)

    Data source

    ISPRA processing on MIT and ISPRA data

    Note

    The structures intended for pleasure boating can be classified based on art. 2 of the Presidential Decree. 2 December 1997 n.509, in three types: tourist port, tourist landing place and mooring point

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    Headline

    Figure 1: Number of berths in Italy Source ISPRA processing on ISPRA and MIT data

    Data source

    ISPRA processing on ISPRA and MIT data

    Thumbnail
    Headline

    Figure 2: Number of berths per kilometer of regional coast (2022-2023)

    Data source

    ISPRA processing on ISPRA and MIT data

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