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Article

Analysis of Coastal Environmental Vulnerabilities in the Municipality of Niterói, Rio de Janeiro, Brazil, in the Face of Sea Level Rise Projections

by
Vilmar Leandro Dias Ferreira
1,
Elizabeth Santos Pereira
1,
Lucas Pluvie Souza de Mello
1,
Rodrigo Amado Garcia Silva
2 and
Fábio Ferreira Dias
1,*
1
Department of Geoenvironmental Analyses, Geosciences Institute, Fluminense Federal University, Av. Gal. Milton Tavares de Souza, s/nº, Praia Vermelha Campus, Boa Viagem, Niterói 24210-346, Brazil
2
Department of Agricultural and Environmental Engineering, Fluminense Federal University, Av. Gal. Milton Tavares de Souza, s/nº, Praia Vermelha Campus, Boa Viagem, Niterói 24210-346, Brazil
*
Author to whom correspondence should be addressed.
Coasts 2025, 5(1), 11; https://doi.org/10.3390/coasts5010011
Submission received: 22 January 2025 / Revised: 27 February 2025 / Accepted: 6 March 2025 / Published: 20 March 2025
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Abstract

:
It is estimated that around 10% of the world’s population lives in low-lying coastal areas, with an altitude of up to 10 m: considered vulnerable to unequivocal sea level rise, as result of climate change. This study sought to assess the coastal environmental vulnerabilities of the municipality of Niterói, Rio de Janeiro, Brazil, in these lowlands, through of an analysis matrix, considering sea level rise projections for 2100. The matrix was applied to nine areas along the coast and consisted of assigning values from 1 to 4 (4 being the most critical scenario) to four variables: two to natural indicators and two to socio-economic indicators. The index for each area was obtained from the simple average of the values assigned. In general, the areas facing Guanabara Bay were more sensitive in socio-economic terms, due to population densification and lower per capita income. The areas facing the Atlantic Ocean were more vulnerable in natural terms, due to exposure to waves and the presence of the natural systems protected on land located below the 10-m. These issues highlight the importance of using vulnerability analysis tools, which can enable public authorities to plan and organize the actions in each specific situation.

1. Introduction

Coastal areas are poles of attraction for society establishment, in virtue of resources supply, access to maritime trade, was well as recreational and cultural activities [1,2]. These regions, however, have experienced enormous changes in recent decades, driven by population growth, accelerated development [2] and often by disorderly urban expansion, which portrays the need for planning, organization and management of these spaces [3].
It is estimated that around 10% of the world’s population are residents of low-lying coastal zones: areas with altimetric elevations lower than 10 m above mean sea level (MSL) [4]. This combination of densely populated regions, low-lying land and the presence of marine erosion portrays a critical issue of coastal vulnerability [5], defined as “the state of coastal communities, including their social structure, physical assets, economy and environmental support, which makes them more or less susceptible to extreme events” [6].
Changes in sea levels could make life on the coast a high-risk choice [7], as urban settlements and local economies could be severely impacted by flooding, erosion, shoreline alteration [8,9], submergence and saline intrusion into surface or groundwater [10]. The management of coastal areas, to reduce such impacts, therefore presents itself as an enormous challenge [11].
The rise in sea levels as consequences of climate change is unequivocal, according to the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC). The report shows that concentrations of greenhouse gases (GHGs), especially CO2 emitted by human activities, are currently at the highest rate in the last 2 million years [12]. In a scenario projected for 2100, for example, called RCP 2.6 (Representative Concentration Pathway), one estimates that, if the CO2 concentration reaches 421 ppm, there could be an increase in the average temperature of the Earth’s surface up to 1.7 °C, compared to the pre-industrial period (1750), and a variation in the average sea level ranging from 0.26 m to 0.55 m [13].
However, in 2023, the World Meteorological Organization (WMO) registered new records for GHG emissions: CO2 concentrations reached 420 ppm, which represents a 151% increase on pre-industrial levels, and came even closer to the RCP 2.6 projection [14]. In addition, the global average temperature of the Earth’s surface was 1.45 ± 0.12 °C above the 1850–1900 period, making it the hottest year ever recorded in 174 years of observation. As for the effects, the rate of rise in mean sea level has more than doubled since the beginning of satellite records: it increased from 2.13 mm/year in the 1993–2002 period to 4.77 mm/year in the 2014–2023 period [15].
During the 21st century, significant annual average waves are likely to increase in the Southern Ocean, as result of increased wind speeds, and waves generated in the Antarctic Ocean are likely to affect wave heights, periods and directions in adjacent basins [13]. Under these conditions, commercial and fishing ports could become vulnerable [16] and cities with greater exposure of their populations to variations in water levels will tend to face combined hazards caused by more intense winds and increasing storms [17].
In face of these shifts in the climate, regional and national authorities have become more capable of conducting vulnerability assessments, but there are few studies carried out in smaller sections [18]. Thus, maps of potential local vulnerabilities, in face of future sea level rises (SLR), have become excellent tools [19,20]. Coastal planning is often developed and implemented by local authorities, to whom studies on large sections may be necessary, but not sufficient [18].
In this context, this paper addresses the vulnerability degree related to natural and socio-economic aspects along the coast of the municipality of Niterói, state of Rio de Janeiro, Brazil. One analyzed the territory located below the 10-m altimetric contour line, considered vulnerable to rising sea levels, using an environmental vulnerability matrix of, based on concepts from other matrices.

2. Study Area

The Brazilian coastal zone is characterized by different natural environments, located less than 10 m above sea level, which may be affected by the effects of climate change, including: beaches, dunes, coastal plains, barrier islands, lagoons and mangroves [21]. This region is composed of a territorial unit more than 8500 km long [22], which covers 443 municipalities belonging to 17 federal states, according to the latest delimitation of the Brazilian Institute of Geography and Statistics [23]. It also comprises approximately 737,460 km2, which corresponds to around 8.70% of the national territory, where more than 23.77% of the population live: around 48.28 million inhabitants [24].
The municipality of Niterói (Figure 1), located in the metropolitan region of the state of Rio de Janeiro, southeastern Brazil, presents an area of 133.76 km2. In terms of geological and geomorphological characteristics, it is composed of a series of Quaternary sedimentation environments in the coastal strip, associated with depositional systems of continental and transitional marine origin, which led to the development of a coastal plain, where a low zone occupied by lagoons was formed, confined by a barrier-sand formation, in a straight stretch running east-west [25].
As for the political-administrative division, Niterói is made up of 52 neighborhoods, distributed in five Administrative Planning Regions [26], three of which are bathed by marine waters: the Northern Region, the Bay Beaches Region (bathed by Guanabara Bay to the west) and the Oceanic Region (bathed by the Atlantic Ocean to the south) [27]. In terms of occupation, the municipality is divided into two macro-regions: (i) Guanabara Bay, where occupation has been consolidated in a complex and disorderly manner; (ii) Oceanic—an area of recent urban expansion [28].
The climate, according to the Köppen classification, is Aw: tropical, with dry winters and rainy summers [29]. In terms of vegetation, the municipality covers 3 integral protection units and 6 sustainable use units: equivalent to 33% of the territory. However, the alluvial and lowland forest formations have been greatly affected by the process of human occupation. In the Guanabara Bay macro-region, the sandbanks have been completely suppressed, and the mangroves are almost extinct. In the Oceanic macro-region, there are still a few remnants of sandbank. Floodplains have been eliminated or modified by canalization and drainage works, landfills and garbage disposal [30].
Niterói has one of the highest population densities in the Brazilian coastal zone: 3601.74 inhabitants/km2. Between the 2010 and 2021 demographic censuses, the population fell by around 1.2%: from 487,562 to 481,749 inhabitants [24,31]. The municipality is categorized as 100% urban and, in 2010, had the best Municipal Human Development Index (MHDI) in the state of Rio de Janeiro (classified as “very high”), mainly due to the income dimension, according to the United Nations Development Program [32]. However, the percentage of the population with a nominal monthly per capita income of up to ½ the minimum wage (US$125.70, according to the dollar exchange rate in Brazil, on 20 January 2025) in 2010 was 29.5% [24], which indicates great economic disparity between its residents.

3. Material and Methods

Preliminarily, the shapefile of Niterói’s coastal strip up to 10 m high, considered critical in terms of vulnerability to rising sea levels [4,5], was created using the ArcGis platform. The municipality’s contour lines, produced by LIDAR (Light Detection and Ranging) technology and taken from the SIGeo-Niterói website [33], were used for the delimitation.

3.1. Land Use and Land Cover (LU/LC) in the Municipality of Niterói

The quantification of urbanized areas and other classes of LU/LC was obtained by overlaying the shapefile of the 10-m strip produced with the shapefile of the municipality’s LU/LC, also obtained from the SIGeo-Niterói website [33]. Subsequently, the shapefile of the 10-m strip was superimposed on the shapefile of the census sectors, extracted from the IBGE—Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics) website [31], thus allowing quantification of the demographic density and average income of the population, inherent to the lowlands.
We also calculated the absolute population and the number of households for each Administrative Planning Region located below the 10-m altimetric contour line. To get data with maximal precision, the total areas of the census tracts completely enclosed, and the census tracts intercepted by the 10-m elevation curve were calculated using the ArcGis attributes table. Next, only the areas within the 10-m elevation were projected, and the intercepted sectors had their areas recalculated, keeping only the plots below the curve. The percentages obtained between the two areas were multiplied by the population and the number of households in each administrative region, thus obtaining results that were closer to reality.
Other significant attributes related to environmental aspects, in physical, biological, social and economic aspects, were obtained through bibliographic surveys in primary sources, such as the Orla Project [28].

3.2. Coastal Environmental Vulnerabilities in the Municipality of Niterói

The classification of vulnerabilities along the coast, in face of rising sea level, was carried out by analyzing the coastal environmental vulnerability indices—CEVI—(Table 1), in a matrix adapted from the Macro Diagnosis of the Brazilian Coastal and Marine Zone—MDZCM [21].
The CEVI matrix allows assessment of four environmental indicators, two of which are related to natural aspects—physical and biological (degree of exposure to waves and percentage of natural environments protected by law, susceptible to the effects of flooding)—and two related to socio-economic aspects (demographic density and per capita income), composed by the following parameters:
(1) Natural physical aspects: pre-defined concepts from the Niterói Waterfront Project [28] were used, in which the municipality’s waterfront is subdivided and classified according to the degree of exposure to waves, as: sheltered, semi-sheltered, exposed. Waterfronts with a predominance of rocky outcrops or rigid consolidated urban structures were considered to have minimal exposure to waves.
(2) Natural biological aspects: classification inspired by the concepts of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model, used by Arkema et al. [34], in line with the National Conservation Unit System [35], and with the permanent preservation areas (APP’s), represented by sandbanks and mangroves, according to specific national regulations [36]. One considered that, in the medium and long term, the flooding of protected areas could result, even indirectly, in the suppression of biodiversity, loss of life quality for adjacent populations and loss or reduction of natural coastal protection.
The percentages of protected areas located in lowlands were quantified using the ArcGis GIS program, by overlaying the shapefile referring to the 10-m elevation on the shapefiles of the municipality’s Conservation/Preservation Units, available on the SIGeo-Niterói website [33], and on the shapefiles of the permanent protection strips, vectorized for this study, thus obtaining the intersection plots. Sections of conservation/preservation areas located on rocky natural monuments, whose impacts tend to be insignificant, were not considered.
(3 and 4) Socio-economic aspects I and II: IBGE census data and the classification bands adopted by the agency were used, referring to the demographic census carried out in 2010 [31], given that the income data referring to the last census carried out in 2021 is not yet available, nor are the shapefiles of the census sectors. It should also be noted that, quantitatively, the municipality had little change between demographic censuses and showed a reduction in population of approximately 1.2%, which is therefore not very significant.
Population data, in terms of density and income, was analyzed by census tract and their respective neighborhoods and planning regions, defined by the Municipal Master Plan [26]. The mean values of both density and per capita income were calculated only for the census tracts located completely below the 10-m altimetric contour line, taking into account that the variable refers to an average and that, within the sample space, the number of these tracts is very representative: approximately 75% (388 out of a total of 520 included or intercepted by the 10-m elevation curve).
In the case of the per capita income variable, economically vulnerable populations received a higher score, considering that they tend to suffer the effects of the adversities caused by rising sea levels more intensely [18,19,37,38,39].
To obtain the vulnerability index and correlated classification, values from 1 to 4 (4 being the most critical condition) were assigned to the four variables in nine analysis areas (A1 to A9), distributed along the Niterói coastline. The coastal environmental vulnerability index (CEVI) corresponded to the simple average of the values assigned to each area (Index = (V1 + V2 + V3 + V4)/4), resulting in the following classifications: very low, low, medium, high and very high (Table 2).
The analysis areas shown in Table 3 were divided according to LU/LC criteria in terms of population density and the existence of areas considered to be of special interest, i.e., areas potentially vulnerable to variations in sea level and/or the effects of waves, currents and tides.

3.3. Adaptation Proposals

Based on bibliographical research in a wide range of literature, proposals for adaptation/mitigation were suggested, especially for the areas with medium and high vulnerability indices, according to the CEVI matrix.

4. Results and Discussion

4.1. Land Use and Land Cover (LU/LC) in the Municipality of Niterói

In Niterói, the Administrative Planning Regions bathed by marine waters—Norte, Bay beaches and Oceanic—encompasses an area of 46.78 km2, which corresponds to 37.74% of the municipality, distributed as 3.54%, 12.85% and 21.34%, respectively. The lowlands, located up to 10 m above the MSL, cover around 29.94 km2, which represents around 24.15% (almost 1/4) of the municipal area and approximately 64.00% (more than 3/5) of the area of the three administrative regions [33].
The results of LU/LC revealed that in the municipality, the “vegetation cover” class is the most representative, covering 48.18% of the territory, followed by “urban”, which occupies 35.74%, and “disorderly occupation/shantytown”, with 7.48%. In the area below the 10-m level, the “urban” class is the most significant, covering 52.33%, followed by “vegetation cover” with 19.76%, “industrial” with 3.96% and “disorderly occupation/shantytown” with 3.33%. The “beaches” class represent an area of only 1.65% [33].
This scenario indicates the existence of a strong urban concentration on the coastal strip of Niterói. Ribeiro et al. [39] stated that cities usually face specific impacts, depending on how they were designed. The changes expected because of high-water levels are characterized as phenomena associated with both biophysical and socio-economic consequences pertinent to hazards that can severely affect life on the coast [40]. The most direct results tend to be coastal geomorphological adjustments, usually caused by erosion [41], sometimes intensified by the suppression of natural habitats in the provision of coastal protection [1,34,42,43] and increased socio-economic vulnerabilities in low-lying areas related to flooding [44].
Woodruff, Irish and Camargo [45] point out that rising sea level rates will increase extreme flooding caused by tropical cyclones, and storm damage will be greater along populated and dynamic coastlines, where geomorphological changes occur more often. Thus, in virtue of possible future floods, there should be a continuous focus on exposure characteristics [46], as well as on associated risk assessments [19], as flood risks represent the greatest impact on populations [41,44].
In addition, in areas up to 10 m above the municipality’s MSL, there are isolated hills, where populations disorderly occupations are observed, which could be affected, even indirectly, by flooding. Tonmoy and El-Zein [18] pointed out that impacts can occur directly or indirectly, such as the interruption of infrastructure services and public activities, which may affect an estimated number of individuals.
Regarding socio-economic aspects, one observed that the North, Bay Beaches and Oceanic Planning Administrative Regions comprise 87.92% of Niterói’s households and 82.25% of the population. The average population density of these regions is approximately 5978 inhabitants/km2—considerably higher than that of the municipality, which is around 3600 inhabitants/km2—and the average per capita income is R$927.26/inhabitant/month (US$153.50), slightly higher than the municipal average of R$909.11/inhabitant/month (US$150.50) [31].
In particular, the North Region has the lowest per capita income: R$444.43/inhabitant/month (US$73.60). The Bay Beaches region presents the largest number of households (77,198 = 45.00% of the municipal total), the largest population (179,465 = 36.81% of the municipal total), the highest population density (9340 inhabitants/km2) and the highest per capita income (R$1343.77/inhabitant/month) (US$222.50). In contrast, the Oceanic Region has the lowest number of households (22,083 = 12.87% of Niterói), the lowest population (68,987 inhabitants = 14.15%) and the lowest density (1362 inhabitants/km2) [31].
In the lands located up to 10 m above the MSL, the North Region is the second most populous, with 37,564 inhabitants (equivalent to 21.36% of the area of interest and 7.70% of the municipality) and a population density of 6927 inhabitants/km2, but with the lowest per capita income: R$603.06/inhabitant/month (US$99.85). The Bay beaches Region has the largest population (around 108,669 inhabitants = 61.78% of the area of interest and 22.29% of the municipality), the largest number of households (41,881, which corresponds to 64.75% of the area of interest and 24.40% of the municipality), the highest population density (13,901 inhabitants/km2) and the second highest per capita income: R$1208.17/inhabitant/month (US$200.00) [31]. As for the Oceanic Region, the population density is considerably lower (1572 inhabitants/km2), but with the highest per capita income in the municipality: R$1254.63/inhabitant/month (US$207.70) [31].
Vulnerability assessments can be carried out using a set of socio-economic indicators [18,19]. However, in general, populations with better financial conditions tend to have greater capacity to deal with possible disasters [18,19,37,38]. This reveals the need to develop a more comprehensive perception of management related to flood probabilities and associated risks, focused not only on immediate economic benefits, but also with attention to a future guarantee, anticipating developments in the coming decades and centuries [46].

4.2. Vulnerabilities Along the Coastline of the Municipality of Niterói

4.2.1. Natural Physical and Biological Aspects

Following the precepts of the CEVI matrix, a minimum score was given to the A1, A2, A3 and A5 shorelines, belonging to the North and Bay Beaches Administrative Regions, where the effects of the tides predominate, in comparison to waves. One found that these shorelines have been almost completely altered by landfills or rigid containment structures, consisting of walls or rockfills, which occur in isolation or simultaneously, related to intense urbanization. However, there are still some remnants of beach environments, especially in A5. The shore of area A4, classified as semi-sheltered, was given a score of 3. Occasionally, part of this sector is exposed to SW weather events and is therefore hit by waves, but not as intensely as in Oceanic Region [28], probably mitigated by the effects of diffraction, refraction and bottom resistance.
In the Administrative Region facing the Atlantic Ocean, maximum points were awarded to all the study areas—A6, A7, A8 and A9—which correspond to the segments exposed to wave dynamics [28]. The stretch of Brazilian coastline between the municipality of Cabo Frio and Marambaia Island- including Niterói—is highly exposed to southern storm waves, due to its almost E-W alignment [41]. Sometimes, when the SLR is due to storm surge, damage is observed on the region’s beaches, such as what happened in July 2020, when part of the urban structures in Niterói collapsed, in response to highly energetic waves.
In addition, the vulnerability of the Oceanic Region becomes more relevant, due to the geomorphological characteristics of its coastal strip, made up of Holocene/Pleistocene sandy formations [25], which, under waves with increased energy, could experience severe damage caused by erosion, as a result of the negative sedimentary balance, especially in A6, where much of the urbanized land is located on the sandy cordon that shelters the Piratininga Lagoon.
In this case, notwithstanding the classifications pre-defined by the Orla Project [28], numerical methods, such as the Coastal Vulnerability Index (CVI) matrix, can be used to monitor specific variables, such as the rate of erosion/accretion of the coastline, with emphasis on regions where the various effects of SLR are more intense [47].
Regarding natural areas under protection, A1, A2, A3 and A4 received the lowest scores. In A1 and A2, there were no Conservation/Preservation Units. In A1, although there are still some remnants of mangroves, these fragments are scarce and very unrepresentative in terms of their ecosystem function. In A3, there is a sector belonging to an environmental protection area, known as Gragoatá Hill, located in isolation and at a high elevation, and in A4, the protected sectors are made up of rocky material, so these areas are unlikely to be significantly impacted by rising sea levels. Area A5 received a score of 3, since it presents around 42.70% of natural environments under protection, located below the 10-m elevation [30,36].
In the Oceanic Region, areas A6 and A7 received maximum scores. In A6, 94.37% of the preservation/conservation and/or permanent protection units are located below the 10-m elevation, and in A7, 100% are in this range [30,36]. Therefore, these areas of analysis are considerably more vulnerable to the rise in MSL, as there could be complete suppression of the ecosystems (mangroves) that inhabit the surroundings of the Itaipu-Piratininga lagoon complex, as well as the possibility of extinction of the sandbank vegetation, located at the upper elevation, parallel to the beach line, which functions as a type of natural coastal protection. Specifically, A6 shows intense urban pressure on natural environments, as seen in Figure 2.
Although several degraded sections were observed along the edge of the lagoon, in the area represented by A6, mangrove vegetation still occupies around 88.00% of the banks. When it comes to the beach environment, illustrated in Figure 3, around 76.00% of the 2.70 km length is still occupied, at the upper level, by sandbank vegetation [36]. However, in several segments, especially at the eastern and western ends of the beach, this vegetation has been suppressed, most likely because of extreme tidal events, in addition to the presence of urban structures (sidewalks) built on the upper face of the beach, thus damaging the sediment balance.
In A8, a total of 23.28% of the preservation/conservation and/or permanent protection areas were located below the 10-m level, which corresponds to the minimum score in the CEVI matrix [30,36]. In this plot, the mangroves around the Itaipu Lagoon are relatively well preserved, considering that in recent decades, part of the vegetation has been suppressed by urbanization, with landfills and residential construction. In regard of the beach environment, in the northern sector there is still considerable preservation of natural areas, located below the 10-m level, represented by sandbank vegetation and a dune system. In the southern sector, the vegetation is quite degraded or has been replaced by invasive species, as well as various urban settlements, especially the existence of a fishing colony.
At the A9 area 36.02% of the preservation/conservation and/or permanent protection areas are located below the 10-m level [30,36], which corresponds to score 2 on the matrix. This area is located between two rocky outcrops, which belong to the preservation/conservation areas, composed mostly of Atlantic Forest vegetation: Andorinhas Hill and Tiririca Mountain Range [30]. In the beach environment, there is a strip of sandbank vegetation, which runs at a higher elevation, parallel to the beach line, largely degraded by urban development.
In general, the permanent protection areas located in areas A6, A7, A8 and A9, in the Oceanic Region of Niterói, represented by mangroves and sandbanks, tend to be susceptible to the effects of the rise in the MSL more intensely. In studies carried out in the municipality of Mangaratiba, in the south of the state of Rio de Janeiro, Passos et al. [48] pointed out that, in face of rising water levels, the effects are likely to be critical for sandy strips, coastal plains, dunes and restingas, and indicated that the extinction of mangroves is very likely.
It should be noted that the degree of vulnerability is usually assessed positively by the amount of natural protection strips, represented mainly by dunes, sandbanks and mangroves: the more significant these formations are, the lower the vulnerabilities and associated risks for the adjacent areas, as discussed by several authors [1,34,43,48,49,50,51].
In fact, from an immediate or short-term perspective, this role is undeniable. Conversely, from a medium/long-term perspective, considering higher ocean water levels and the consequent suppression of natural protection areas, the greater the susceptibility of local communities and infrastructures will be in the future.

4.2.2. Socio-Economic Aspects

Regarding the population density indicator, the analysis areas facing Guanabara Bay (A1, A2, A3, A4 and A5) are characterized as the most populous in the municipality: in A1, A3 and A5, 6927 inhabitants/km2, 6417 inhabitants/km2 and 7135 inhabitants/km2 were recorded, and obtained a score of 2, according to the CEVI matrix. In A2, 8785 inhabitants/km2 were recorded, which is equivalent to a score of 3 in the matrix. In the area represented by A4, the most populous, 33,269 inhabitants/km2 were recorded and, therefore, the maximum score was assigned [31].
In the analysis areas belonging to the Oceanic Administrative Region, represented in this study by A6, A7, A8 and A9, the lowest demographic densities of the municipality were verified: 2418 inhabitants/km2, in A6; 1291 inhabitants/km2, in A7; 2042 inhabitants/km2, in A8; and 537 inhabitants/km2, in A9 [31]—all within the minimum score range and well below the municipal density of approximately 3600 inhabitants/km2 [31].
Regarding per capita income, areas A1, in the Northern Administrative Region, and A2, in the Bay Beaches Region, obtained the maximum score in the CEVI matrix, with averages of R$603.06/inhabitant/month (US$99.85) and R$621.78/inhabitant/month (US$102.95), respectively. Areas A3 and A5, also belonging to the Bay Beaches Region, received a score of 3, with incomes of R$1208.99/inhabitant/month (US$200.16) and R$1269.67/inhabitant/month (US$210.20), respectively. Area A4, in the same administrative region, was assigned a score of 2, with an average of R$1732.22/inhabitant/month (US$286.79), the highest in the municipality [31].
In the Oceanic Administrative Region, A6 received the maximum score, with an average of R$827.78/inhabitant/month (US$137.05), characterizing it as the third lowest-income area of the analyzed areas in Niterói. A7 obtained a score of 2, with R$1674.87/inhabitant/month (US$277.30): the second highest average income in Niterói. And, in the analyzed areas A8 and A9, very similar averages were verified, of R$1260.86/inhabitant/month (US$208.75) and R$1255.03/inhabitant/month (US$207.79), respectively, both receiving, therefore, a score of 3, according to the proposed matrix [31].
These results reveal that it will be necessary to adopt different adaptation measures, given the increase in sea levels, especially in areas A1, A2 and A6, where the average income of the population is considerably lower than the average income of the other regions, and in A4, where, although the average income is higher, there is a high population density. In the studies developed by Tonmoy and El-Zein [18], for example, when comparing vulnerability scenarios in beach regions of Shoalhaven (Australia), one found that the Collingwood Beach area has the greatest adaptive capacity, because of the higher average family income and the higher average values of properties in a situation of exposure.

4.2.3. Analysis of Coastal Environmental Vulnerabilities

The results obtained from the application of the coastal environmental vulnerability analysis matrix—CEVI-, along the coast of the municipality of Niterói, in the nine analysis areas, are shown in Table 4 and illustrated in Figure 4.
The final classifications obtained by the analysis areas were as follows: areas A1, A3 and A5 were classified as having a “low” degree of vulnerability: A1 and A5 had an index of 2.00; and A3, an index of 1.75 (the lowest among the areas analyzed). Areas A2, A4, A7, A8 and A9 were classified as having a “medium” degree of vulnerability: A2 and A8 had an index of 2.25; A4 and A9, an index of 2.50; and A7, an index of 2.75. Area A6 had a “high” degree of coastal vulnerability, with an index of 3.25, which was the highest index among the areas analyzed.
The analyses showed that the Northern Planning Region and the Bay Beaches Planning Region, both facing Guanabara Bay, are more vulnerable in terms of socio-economic aspects. These regions have high population density and, in certain areas, especially in A1 and A2, economically vulnerable residents. These factors are most likely related to the existence of communities with disorderly occupation/slums, which tend to increase population density and reduce average income. In A4, however, despite the considerably higher density, the higher per capita income tends to reduce susceptibility: the average income in A4 is almost three times that recorded in A1 and A2.
Cazenave and Cozannet [20] highlighted that, in the coming decades, the expected acceleration of SLR in response to continued global warming will exacerbate the vulnerability of many low-lying, densely populated coastal areas and will become a major threat to a significant fraction of people. Ribeiro et al. [39] stressed that in urban centers located in low-lying, flat areas with dense urban structures, very high costs are expected to be incurred due to the impacts caused by flooding resulting from SLR, if adaptation proposals are not considered.
In vulnerability analyses carried out by Dada et al. [52] on the west coast of Africa, between Mauritania and Cameroon, it was found that, although geophysical variables contribute to increased coastal vulnerability, socioeconomic factors, particularly high population growth and unsustainable human development, play a considerably greater role. Hardy and Hauer [38], when projecting flooding scenarios on the coast of Georgia (USA), due to SLR, found an almost doubling of socially vulnerable subpopulations for the period 2010–2050, with a more than fivefold increase in communities at risk (residents of census tracts with high social vulnerability) and at greatest risk (residents of tracts with high social vulnerability and high exposure).
In the Oceanic Planning Region, vulnerabilities are more related to natural physical aspects, due to exposure to the effects of waves, which tend to worsen with rising sea levels, and natural biological aspects, due to the fact that most of the preservation/conservation or permanent protection areas are located below the 10-m elevation mark, and are therefore susceptible to the effects of flooding, especially in A6 and A7. Furthermore, in A6, the impacts tend to be even more critical, because it has a reasonable population density (the highest in the region), concomitantly with a low per capita income, most likely due to the existence of disorderly occupations/slums.
In studies by Arkema et al. [34], it was found that the loss of habitats would double the length of coasts highly exposed to storms and rising sea levels. There would be an increase of more than 1.4 million in the number of vulnerable people living up to 1 km from the coast. In addition, the number of poor families, elderly people and assets highly exposed to hazards would also double. In analyses carried out by Pantusa et al. [43], in the Province of Crotone, Calabria Region (Italy), through the application of the Coastal Vulnerability Index (CVI), it was found that the most vulnerable sectors are those located in areas with coastal erosion conditions, where there has been a reduction in the dune or beach system, and where there is a low percentage of native vegetation cover.
Ferreira et al. [53], in research carried out in the municipality of Niterói, observed possible environmental impacts because of climate change, given an optimistic scenario of a SLR of 0.50 m by 2100, during an event of maximum astronomical tide associated with an event of maximum storm surge. In this scenario, sea waters should reach approximately 1.80 m above the current average level, directly affecting, in the Oceanic Region of Niterói, 2,069,037 m2 of vegetation cover and more than 9000 residents. This will be the most impacted region of the municipality, precisely where the most vulnerable area (A6—Piratininga neighborhood and surroundings) verified in this study is located.

4.3. Adaptation Proposals

In the face of a warming climate, certain events will be potentiated, influenced by the impacts caused by waves and coastal flooding [54]. The most recent records, set out in the Sixth Assessment Report—AR6 [12] and the State of the Climate Report 2023 [55], indicate that ocean heat and global sea levels are the highest ever recorded. The global average sea level was a record for the 12th consecutive year, reaching around 101.4 mm above the 1993 average, when satellite measurements began, which represents an increase of 8.1 ± 1.5 mm compared to 2022.
In this context of increased extreme events, storms will also become more intense and frequent [9]. In May 2024, for example, the state of Rio Grande do Sul (Brazil) experienced one of the worst climate crises in its history, when heavy rains affected, according to the Civil Defense, more than 450 municipalities and more than 2.34 million people. As a result of the exacerbated event, there was severe damage to urban infrastructure, the agricultural and industrial sectors, as well as more than 160 deaths. The most vulnerable populations, including low-income communities and farmers, were disproportionately affected, highlighting pre-existing social and economic inequalities [56].
When coastal regions are characterized by major economic and population growth, a demand for greater security develops [49]. Therefore, in view of the increase in risks due to climate change, appropriate responses are needed, with integrated planning and management aimed at the best mitigating measures. However, there is no simple or general rule for choosing the best protection method to use [1], which can include solutions with rigid or soft structures, or both, in a combination of projects [49,57], as well as other management measures inherent in urban planning.
In beach environments, for example, traditional protection methods can be used: adherent longitudinal defenses, spurs, detached breakwaters, artificial nourishment [1,58], storm barriers [49], among others. In lower energy environments, less traditional measures can act as forms of mitigation, such as geotextiles [1,58], gabions, polypropylene bags [1], stabilization of wetlands [49], etc.
Adaptation to rising sea levels must follow the best standards in Coastal Engineering, also considering integrated coastal zone management. Preventive planning can reduce many future problems [44], because over time it will become increasingly difficult to adequately prepare and implement the most suitable forms of protection [11]. Among the various measures, the effectiveness of the undertaking must always be compared and evaluated on a case-by-case basis, especially regarding costs, which can cover planning and engineering, material, labor, implementation, management and maintenance [49].
In this sense, with regard to the sheltered or semi-sheltered areas represented in this study by those facing Guanabara Bay, specific adaptation measures will be needed for a densely populated urban environment, susceptible to flooding caused by rising sea levels and/or flooding caused by heavy rainfall, with emphasis on the areas with a medium vulnerability index: A2, where there is a low per capita income, and A4, where population density is quite considerable.
To mitigate the effects of heavy rainfall, which tends to cause major flooding and, consequently, damage to public and private property, it is preliminarily suggested that urban drainage systems be improved. In addition, it is suggested to implement an effective large-scale pumping system to remove rainwater, such as those used in New Orleans, USA [49], as in these cases the drainage gradients are reduced due to the rise in the water table [44].
In the case of the areas facing the Atlantic Ocean, in A7, A8 and A9, where the degree of vulnerability was assessed as medium, better control of land use and occupation is needed as a precautionary measure, to reduce the pressure of urban growth on sensitive natural environments protected by law. Conversely, in areas A7 and A8, it will be essential to build physical structures to protect human communities from flooding, especially around the Itaipu-Piratininga lagoon system.
In the case of tidal flats, low-lying areas or mangrove swamps, such as those observed in A7 and A8, Mangor et al. [59] suggest the construction of dikes, characterized as sea defense structures made up of sand, topsoil and grass, suitable for protecting coastal interiors from flooding due to high tides. Another possibility is the construction of coated dikes (with an impermeable layer), suitable for defending sheltered bays or estuaries subject to flooding by meteorological tides. However, this technique requires the installation of pumping stations, as they impair continental drainage [60].
As for A9, this is an area represented exclusively by the Itacoatiara neighborhood, where the most sensitive aspects are related to the sandbank vegetation that runs parallel to the upper level of the beach, which is just over 700 m long. A9 has the lowest population density among the areas analyzed, with a per capita income higher than the municipal average. In view of these characteristics, we suggest the implementation of a detached breakwater as an adaptation measure in the face of changes in wave magnitude and frequency, the best design of which will depend on prior engineering analysis.
With regard to the area covered by A6, classified with the highest degree of vulnerability in the municipality, according to the analyses carried out in this study, the same measures suggested for areas A7 and A8 are indicated for the lagoon sector, i.e., control over LU/LC around the lagoon, which is already very degraded by urbanization, and the implementation of dikes to contain the advance of sea water. For the ocean sector, a combination of methods could be very pertinent in the face of increased wave energy, for example: construction of a detached breakwater, concomitant with artificial nourishment (beach nourishment), as well as maintenance of native vegetation. These measures are shown in the scheme in Figure 5.
However, it is worth noting that the construction of breakwaters, whether submerged or immersed, as a coastal defense measure, must be very well evaluated, always seeking the project with the least possible impact on the environment, as these structures tend to affect beach morphology, hydrodynamics, ecology, tourism and recreation—among other implications [61]. In the cases of A6 and A9, submerged structures may apply better apply, equipped with signs, to mitigate accidents with bathers and boats.
Notwithstanding the measures indicated in this study, it is also suggested that in the next revisions of the Master Plan (which takes place every ten years) and the Municipal Urban Zoning, the municipality’s LU/LC should be readjusted to reduce the pressure on the most sensitive areas in the face of a warming climate and consequent rise in sea levels. As extreme events begin to affect human communities more significantly, relocation and the natural internal migration of people could become new challenges for public administrators if effective planning is not adopted.
Hauer [37] pointed out that, normally, studies of vulnerability in coastal areas related to SLR deal with the fact as an issue exclusively for coastal communities, not portraying the possible impacts on other communities caused by migration and the consequent population redistribution. Simas et al. [56] pointed out that the intensity and frequency of the events will highlight the need for more robust public policies, which are essential for mitigating the effects of climate change, through the construction of resilient infrastructures, the preservation of watersheds and appropriate urban planning.

5. Conclusions

Several authors have used GIS techniques similar to those used in this study, in which polygons are overlaid in order to obtain areas of intersection, so as to quantify the desired data related to vulnerabilities (physical or socio-economic) or impacts on possible flood areas in coastal plains: Tonmoy and El-Zein [18], in Shoalhaven City, south coast of New South Wales, Australia; Ribeiro et al. [39], in Baixa Pombalina, Lisbon, Portugal; Zhang et al. [62], in Florida Keys, USA; among others.
However, it is worth emphasizing the degree of precision related to the socio-economic figures obtained in the analyses carried out in this work, using shapefiles at census sector level. Such precise information made it possible to clearly dimension the susceptibilities of the coastal region of the municipality of Niterói and can serve as support for future decisions in the face of climate change and the unequivocal rise in sea levels.
The analyses presented in this paper were carried out along the coastal strip of the municipality of Niterói, in the portion located below the altimetric level of 10 m, considered to be lowlands. By applying the coastal vulnerability matrix, it was possible to classify the environmental vulnerabilities, referring to natural (physical and biological) and socio-economic (population density and per capita income) aspects, in the three Administrative Planning Regions bordering the sea, which were divided into nine analysis areas.
In general, the North and Bay Beaches Planning Administrative Regions are more susceptible in socio-economic terms, due to the high population density and low per capita income in two of the five areas analysed. In the Oceanic Planning Administrative Region, the most sensitive issues are related to natural aspects, both physical and biological, given the exposure to the sea and the existence of protected areas located on low-lying land, which are therefore susceptible to the advance of marine waters, while at the same time being limited by the intensification of urban growth.
Adaptation measures have been proposed to protect human communities and natural environments from the effects of SLR, especially in areas where the degree of vulnerability has been classified as medium or high. However, preventive measures are needed in terms of planning and management, in order to mitigate the impacts, especially those caused by meteorological events.

Author Contributions

Conceptualization, V.L.D.F., E.S.P., L.P.S.d.M., R.A.G.S. and F.F.D.; Methodology, V.L.D.F., E.S.P., L.P.S.d.M., R.A.G.S. and F.F.D.; Validation, V.L.D.F., E.S.P., L.P.S.d.M., R.A.G.S. and F.F.D.; Formal analysis, V.L.D.F., E.S.P., L.P.S.d.M., R.A.G.S. and F.F.D.; Investigation, V.L.D.F. and F.F.D.; Resources, V.L.D.F. and F.F.D.; Data curation, V.L.D.F. and F.F.D.; Writing—original draft preparation, V.L.D.F. and F.F.D. Writing—review and editing, V.L.D.F., E.S.P., L.P.S.d.M., R.A.G.S. and F.F.D.; Visualization, V.L.D.F. and F.F.D.; Supervision, R.A.G.S. and F.F.D.; Project administration, F.F.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Study area: municipality of Niterói, Rio de Janeiro, Brazil, 2024. Source: Cartographic reference system: SIRGAS 2000; UTM23S; unit: meter.
Figure 1. Study area: municipality of Niterói, Rio de Janeiro, Brazil, 2024. Source: Cartographic reference system: SIRGAS 2000; UTM23S; unit: meter.
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Figure 2. Urbanization on the Holocene/Pleistocene sand formation in Piratininga, Niterói, Brazil.
Figure 2. Urbanization on the Holocene/Pleistocene sand formation in Piratininga, Niterói, Brazil.
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Figure 3. Satellite image of Piratininga beach, Niterói, Brazil, showing urban settlements built on the sand formation. SOURCE: Google Earth.
Figure 3. Satellite image of Piratininga beach, Niterói, Brazil, showing urban settlements built on the sand formation. SOURCE: Google Earth.
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Figure 4. Coastal environmental vulnerability indexes in the municipality of Niterói, Rio de Janeiro, Brazil, obtained from the application of the CEVI matrix, composed of natural (physical and biological) and socio-economic indicators [28,30,31,36].
Figure 4. Coastal environmental vulnerability indexes in the municipality of Niterói, Rio de Janeiro, Brazil, obtained from the application of the CEVI matrix, composed of natural (physical and biological) and socio-economic indicators [28,30,31,36].
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Figure 5. Beach profile scheme, arranged with adaptation measures, suggested for Piratininga beach, in the municipality of Niterói, Rio de Janeiro, Brazil: submerged breakwater (or artificial reef) for the beach sector; and dikes for the lagoon sector.
Figure 5. Beach profile scheme, arranged with adaptation measures, suggested for Piratininga beach, in the municipality of Niterói, Rio de Janeiro, Brazil: submerged breakwater (or artificial reef) for the beach sector; and dikes for the lagoon sector.
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Table 1. Matrix of coastal environmental vulnerability indices—CEVI [21,28,30,31].
Table 1. Matrix of coastal environmental vulnerability indices—CEVI [21,28,30,31].
Matrix of Coastal Environmental Vulnerabilities
AspectsIndicatorsDescriptionVariablesScore
PhisicalDegree of exposure to wavesTypes of waterfronts, according to concepts predefined by the Niterói Waterfront Project.
In cases where there is a predominance of consolidated rigid urban structures (altered shoreline) or a predominance of rocky material, minimum score was applied. 		Predominance of rigid structures.1
Sheltered. 2
Semi-sheltered.3
Exposed.4
BiologicalPercentage of natural areas protected by law susceptible to the effects of floodingProportion of conservation/preservation units or permanent protection strips located below the 10-m elevation.
In cases where there are no protected areas, a minimum weighting was applied, depending on the occurrence of other plant formations. 		Between 0.0% and 24.9%.1
Between 25.0% and 49.9%.2
Between 50.0% and 74.9%.3
Between 75.0% and 100%.4
Socio-economic IDemographic densityAverage population density of the census tracts within the analysis areas, within the 10-m altimetric range.
Weighting based on the classification adopted by the IBGE—synopsis of census sectors.		Up to 3744.20 inhabitants/km2.1
Up to 8253.71 inhabitants/km2.2
Up to 15,264.27 inhabitants/km2.3
Above 15,264.27 inhabitants/km2.4
Socio-economic IIPer capita incomeAverage income per capita per month in the census tracts included in the analysis areas, within the 10-m altimetric range.
Weighting is based on the classification adopted by the IBGE—synopsis of census sectors.
Populations with lower incomes classified as more exposed.		Above R$1800.00/inhabitant/month.1
Up to R$1800.00/inhabitant/month.2
Up to R$1300.00/inhabitant/month.3
Up to R$1000.00/inhabitant/month.4
Table 2. Coastal environmental vulnerability indices and their respective classifications.
Table 2. Coastal environmental vulnerability indices and their respective classifications.
Coastal Environmental Vulnerability Index—CEVI
Application of the Formula CEVI = (V1 + V2 + V3 + V 4)/4Classification
1.00 ≤ V ≤ 1.25 Very Low
1.50 ≤ V ≤ 2.00 Low
2.25 ≤ V ≤ 2.75 Medium
3.00 ≤ V ≤ 3.50High
3.75 ≤ V ≤ 4.00 Very High
Table 3. Administrative Planning Regions, analysis areas and respective neighborhoods in the municipality of Niterói, Rio de Janeiro, Brazil [28].
Table 3. Administrative Planning Regions, analysis areas and respective neighborhoods in the municipality of Niterói, Rio de Janeiro, Brazil [28].
Administrative Planning RegionsAreas of AnalysisNeighborhoods
NorthA1Barreto, Cubango, Engenhoca, Fonseca, I. Conceição, Santana e São Lourenço.
Bay beachesA2Centro, Fátima, Morro do Estado e Ponta d’Areia.
A3Gragoatá, Boa Viagem e São Domingos.
A4Icaraí, Ingá, Pé Pequeno, Santa Rosa e Vital Brasil.
A5Cachoeiras, Charitas, Jurujuba e São Francisco.
OceanicA6Piratininga, Cafubá e Jardim Imbuí.
A7Camboinhas.
A8Itaipu, Maravista e Santo Antônio.
A9Itacoatiara.
Table 4. Results of the application of the coastal environmental vulnerability analysis matrix—CEVI, along the coast of the municipality of Niterói, Rio de Janeiro, Brazil [28,30,31,36].
Table 4. Results of the application of the coastal environmental vulnerability analysis matrix—CEVI, along the coast of the municipality of Niterói, Rio de Janeiro, Brazil [28,30,31,36].
Coastal Environmental Vulnerability Index in the Municipality of Niterói, Rio de Janeiro, Brazil
AreasV1ScoreV2ScoreV3ScoreV4ScoreAverageIndex
A1Changed1Insignificant16.9272603.0642.00Low
A2Changed1Non-existence18.7853621.7842.25Medium
A3Changed1Insignificant16.41721208.9931.75Low
A4Semi-sheltered3Insignificant133.26941732.2222.50Medium
A5Changed142.70%27.13521269.6732.00Low
A6Exposed494.37%42.4181827.7843.25High
A7Exposed4100%41.29111674.8722.75Medium
A8Exposed423.28%12.04211260.8632.25Medium
A9Exposed436.02%253711255.0332.50Medium
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Ferreira, V.L.D.; Pereira, E.S.; Souza de Mello, L.P.; Silva, R.A.G.; Dias, F.F. Analysis of Coastal Environmental Vulnerabilities in the Municipality of Niterói, Rio de Janeiro, Brazil, in the Face of Sea Level Rise Projections. Coasts 2025, 5, 11. https://doi.org/10.3390/coasts5010011

AMA Style

Ferreira VLD, Pereira ES, Souza de Mello LP, Silva RAG, Dias FF. Analysis of Coastal Environmental Vulnerabilities in the Municipality of Niterói, Rio de Janeiro, Brazil, in the Face of Sea Level Rise Projections. Coasts. 2025; 5(1):11. https://doi.org/10.3390/coasts5010011

Chicago/Turabian Style

Ferreira, Vilmar Leandro Dias, Elizabeth Santos Pereira, Lucas Pluvie Souza de Mello, Rodrigo Amado Garcia Silva, and Fábio Ferreira Dias. 2025. "Analysis of Coastal Environmental Vulnerabilities in the Municipality of Niterói, Rio de Janeiro, Brazil, in the Face of Sea Level Rise Projections" Coasts 5, no. 1: 11. https://doi.org/10.3390/coasts5010011

APA Style

Ferreira, V. L. D., Pereira, E. S., Souza de Mello, L. P., Silva, R. A. G., & Dias, F. F. (2025). Analysis of Coastal Environmental Vulnerabilities in the Municipality of Niterói, Rio de Janeiro, Brazil, in the Face of Sea Level Rise Projections. Coasts, 5(1), 11. https://doi.org/10.3390/coasts5010011

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