Assessment of Literacy to Biotechnological Solutions for Environmental Sustainability in Portugal

Abstract

In today’s world, the importance of preserving the environment has become increasingly evident. As a result, more sustainable solutions and techniques are being developed to combat environmental destruction. Higher education institutions are now including environmental themes in their technological courses to promote sustainable behavior and indirectly enhance environmental literacy among the population. This study aims to evaluate the level of literacy to biotechnological solutions for environmental sustainability in four areas, namely Air Pollution, Aquatic Pollution, Global Warming, and Energy Resources. A questionnaire was developed and distributed to a sample consisting of 471 individuals of both genders, age range between 15 and 78 years old, to collect data characterizing the sample and assess their literacy in environmental issues. The questionnaire was distributed in Portugal, and the participants were asked to indicate their level of agreement with several statements related to the aforementioned environmental themes. The findings suggest that literacy regarding biotechnological solutions for environmental sustainability is influenced by age group and academic qualifications. The age group above 65 years old is the one with the lowest levels of literacy, exhibiting frequencies of response I don’t know exceeding 50% in 10 out of the 22 issues present in the questionnaire. The findings also suggest that the levels of literacy are higher in the thematic areas of Global Warming and Aquatic Pollution and lower in the thematic areas of Air Pollution and Energy Resources, with lower levels of literacy in the issues that have not been widely disseminated by the media. Additionally, a model based on Artificial Neural Networks was presented to predict literacy to biotechnological solutions for environmental sustainability. The proposed model performs well, achieving accuracy rates of 90.8% for the training set and 86.6% for the test set.

1. Introduction

Since the mid-1980s, humankind has repeatedly fallen short of achieving the goal of sustainability. Highly developed human societies have consumed more resources than the planet can produce, leading to amounts of pollution that exceed the Earth’s ability to absorb and purify [1,2]. Notwithstanding all the policies implemented by governments and non-governmental organizations, the evidence indicates that human efforts are insufficient to prevent serious climate change or global warming. While these measures are crucial, they will not suffice if the population is not aware of the importance of being environmentally conscious. This awareness necessitates an appropriate environmental education policy that mobilizes the population towards a shared goal—the planet’s sustainability [3,4].

Disinger and Roth [5] suggested approximately thirty years ago that being environmentally literate entails the ability to comprehend and interpret the balance of environmental systems and taking appropriate action to preserve, restore, or improve their health. Currently, there is a widespread agreement that environmental literacy requires knowledge of environmental concepts, issues, and problems, as well as the appropriate competencies, skills, and behavioral strategies to make informed decisions in various environmental contexts. Thus, environmental literacy involves the mastery of four interrelated components: knowledge, attitudes, skills, and environmentally conscious behaviors [6,7,8]. Furthermore, environmental literacy encompasses a wide range of thematic areas related to the understanding and knowledge of environmental issues such as Air Pollution, Aquatic Pollution, Global Warming, and Energy Resources, just to name a few:

• Air Pollution has extensive and harmful effects on human health and is one of the most important problems for the global community and urban sustainability [9]. One of its main consequences is related to the deterioration of outdoor air quality, which plays an important role in public health and can affect the quality of life of populations [10]. Atmospheric pollution is caused by a mixture of chemicals released into the atmosphere or resulting from chemical reactions that occur within it, altering the natural composition of the atmosphere. These pollutants can have varying degrees of impact on air quality, depending on their chemical composition, concentration, and meteorological conditions [9,10];
• Aquatic Pollution has significantly increased in recent decades due to unplanned urbanization, rapid population growth, and increased industrialization [11,12]. The uncontrolled introduction of various pollutants into the aquatic environment is currently one of the problems that should receive top priority on a global scale in order to ensure the preservation of sources of drinking water in all countries, regardless of whether they are developed or developing countries [11,12];
• Global Warming is a widespread climatic phenomenon characterized by an increase in the average global surface temperature caused by internal and/or external factors. Internal factors are complex and associated with chaotic nonlinear climate systems, which means they are variable due to factors such as solar activity, atmospheric physicochemical composition, tectonics, and volcanism. External factors are anthropogenic and related to greenhouse gas emissions resulting from the use of fossil fuels (mainly coal and petroleum derivatives) by industries, refineries, and transportation, as well as from burning activities [13];
• Energy Resources are related to the increasing industrialization of societies, that have led to an unrestrained increase in energy consumption over time. However, the increasing energy needs have not been met with the necessary investment in renewable energy sources, which are more environmentally friendly. Consequently, the demand and exploitation of fossil fuels as the primary energy source have continued to rise. This has resulted in the depletion of these resources and an increase in environmental degradation [14].

Biotechnology can play a significant role in promoting global sustainability by creating environmentally friendly products and solutions that can address pressing environmental challenges such as climate change, pollution, and resource depletion [15,16]. Indeed, improving awareness and understanding of biotechnology’s role in promoting global sustainability is essential for encouraging sustainable behaviors and environmentally friendly policies. Therefore, assessing the level of literacy of the population to biotechnological solutions for environmental sustainability is crucial for promoting sustainable decision-making, reducing unnecessary resource allocation, and identifying areas for targeted educational initiatives. Furthermore, such an assessment can help policymakers to develop effective strategies for promoting the adoption and implementation of biotechnological solutions for environmental sustainability, which can lead to significant social and environmental benefits. Thus, this study aims to evaluate the level of literacy in a sample of the Portuguese population regarding biotechnological solutions for environmental sustainability. It also aims to create a predictive model to manage their literacy. This model is designed to function as a learning system that simplifies the analysis of environmental literacy data and facilitates the identification of potential areas for improvement.

2. State of Art

The concept of environmental sustainability entails preserving the natural resources and ecosystems of the planet while meeting the present requirements without jeopardizing the ability of future generations to meet their own necessities [17]. Thus, it is essential to address environmental sustainability to tackle global challenges, including climate change, resource depletion, and biodiversity loss.

In 2015, the United Nations set out 17 Sustainable Development Goals (SDGs) to guide global efforts towards sustainable development [18]. Among these goals are several that are directly related to environmental sustainability, including Clean Water and Sanitation (SDG 6), Affordable and Clean Energy (SDG 7), Sustainable Cities and Communities (SDG 11), Responsible Consumption and Production (SDG 12), Climate Action (SDG 13), Life Below Water (SDG 14), and Life on Land (SDG 15).

The achievement of environmental sustainability goals requires a comprehensive and varied approach that involves multiple stakeholders, including governments, businesses, civil society organizations, and individuals [18]. Governments play a critical role in setting policies and regulations that promote sustainable development and in providing the necessary resources and support to enable individuals and organizations to act towards this goal. It also involves investing in research and development to find new ways to address environmental challenges and support the transition to a more sustainable economy. Businesses also had an important role to play in promoting environmental sustainability. By adopting sustainable practices, businesses can reduce their environmental footprint and contribute to the overall goal of reducing greenhouse gas emissions. This can include reducing energy and resource use, promoting sustainable transportation, and investing in renewable energy sources. Civil society organizations also play a critical role in promoting environmental sustainability. They can engage in advocacy and education efforts to raise awareness about the importance of environmental sustainability and work to hold governments and businesses accountable for their actions. At the individual level, there are many actions that people can take to promote environmental sustainability. This can include reducing energy and resource use at home, using sustainable transportation options such as cycling or public transport, and supporting sustainable businesses and organizations [18].

2.1. Biotechnological Solutions for Environmental Sustainability

Biotechnology seeks to develop innovative products and provide solutions aiming to solve pressing problems facing humanity. It is a multidisciplinary field that harnesses the power of living organisms, cells, and their processes to develop innovative products and solutions that can benefit society. The biotechnological-based processes employ advanced techniques such as genetic engineering, bioprocessing, and other methods to modify and optimize living organisms for specific applications. These can range from healthcare and medicine to food production and environmental sustainability, just to name a few [19,20,21,22]. Indeed, biotechnology is playing an increasingly important role in promoting environmental sustainability, particularly through the development of alternative energy sources such as biofuels, which aim to reduce greenhouse gas emissions and mitigate climate change.

Four generations of biofuels can be distinguished based on the biomaterials and production methods employed. The first generation of biofuels refers to those obtained from edible feedstocks such as starch-based or sugar-based feedstocks. The production processes typically involve simple methods of extraction and refinement, but the use of food crops for their production has been criticized for contributing to food scarcity, potentially resulting in price increases. Additionally, it can cause competition for land use, contributing to deforestation [23,24].

The second generation of biofuels is produced from lignocellulosic or carbohydrate biomass through advanced conversion technologies such as gasification and pyrolysis [25]. They are considered more sustainable than first-generation biofuels because they do not compete with food production. However, despite not requiring agricultural land, they still require significant amounts of water and energy to be produced [23,24].

Third-generation biofuels are produced from non-food sources, such as microalgae, which can be grown using wastewater or saltwater and do not compete with food production. Other feedstocks used for third-generation biofuels include waste products or byproducts, such as fish oil, animal fat, and waste cooking oil. The use of microalgae offers several advantages, such as higher growth and productivity, no need for agricultural land, higher oil content, and less impact on food supply [24,25]. Nevertheless, the cultivation of microalgae necessitates a substantial quantity of freshwater and nutrients, which can drive up production costs. Additionally, the expenses involved in harvesting, drying, and extraction processes should also be considered [25,26,27]. Although the use of wastewater as a cultivation medium can lower costs, it poses a risk of microalgae chemical contamination [24].

The advances in molecular biology, genetic engineering, and interdisciplinary physicochemical approaches enable the possibility of modifying organisms focused on specific goals. The production of fourth-generation biofuels is based on the utilization of genetically modified organisms, such as macroalgae, microalgae, and cyanobacteria. These organisms are genetically engineered to enhance their ability to capture carbon dioxide, resulting in the accumulation of higher levels of lipids and carbohydrates, leading to more efficient biofuel production [25,28]. The fourth-generation biofuels offer significant potential as they do not compete with food production [23,25]. Additionally, microalgae can capture more greenhouse gases compared to first and second-generation feedstocks. However, the major drawback is the high energy input required to convert microalgae into biofuel. Currently, the energy is still primarily obtained from fossil fuels, contributing to the increase of greenhouse gas emissions, and contradicting the SDGs [23,24].

Wastewater treatment is a pressing concern for environmental conservation and public health. Biotechnology-based solutions have proven to be promising, allowing not only the treatment of wastewater but also providing value-added products, such as biofuels or biofertilizers [29,30,31,32].

Biotechnology also plays a significant role in promoting sustainable agricultural practices and reducing the environmental impact of farming. Through the development and application of biotechnological solutions, such as genetic engineering [33,34,35], biopesticides [36,37], and biofertilizers [38,39], farmers can improve crop yields while minimizing the use of resources such as water, fertilizer, and pesticides.

The use of biotechnology is not limited to energy, waste treatment, and agriculture issues, but it also extends to the development of eco-friendly materials. Bioplastics, produced using biotechnology, are a good example of eco-friendly materials that can significantly reduce plastic waste in landfills and oceans once many of them are biodegradable. Under controlled microbial composting conditions, the complete biodegradation of these types of plastics takes around 3–6 months. Bioplastics are produced from renewable resources and use biopolymers such as polyhydroxyalkanoate, polylactic acid, poly-3-hydroxybutyrate, polyamide 11, polyhydroxyurethanes, as well as cellulose-based, starch-based, protein, and lipid-based biopolymers [40,41,42]. Bioplastics have a wide range of applications, including biodegradable food packaging, compostable cutlery, biocomposite automobile interior parts, and disposable biomedical tools, just to name a few [40,41,42].

Biodiversity conservation and ecosystem restoration are areas where biotechnology also has a crucial role. New methods are being developed for the preservation of endangered species and restoration of damaged ecosystems. Bioremediation involves the use of living organisms to break down pollutants and contaminants into materials such as water, fatty acids, carbon dioxide, and biomass [43,44,45]. It can be carried out on-site (in situ bioremediation) or off-site by removing contaminated soil, water, or sediment to a controlled environment (ex situ bioremediation). Bioremediation is a green technique that offers various advantages over other remediation procedures. As it is based on natural processes, in situ bioremediation causes less damage to ecosystems, and since it frequently occurs underground, it avoids disturbances to surrounding areas [43,44,45].

2.2. Environmental Literacy

Traditionally, literacy has been defined as the ability to read and write. Although it was originally defined as a broad concept, the term literacy has been increasingly applied in specific contexts, such as science, politics, health, environment, and informatics, just to name a few. The definition of environmental literacy has evolved over time and has been addressed by several authors. According to Roth [46], this concept includes components such as environmental awareness and sensitivity, a deep comprehension of potential solutions to environmental problems, environmentally relevant values, motivation, skills, and competencies to safeguard the environment, and a willingness to take action. Hollweg et al. [8] state that the concept of environmental literacy combines environmental knowledge, attitudes, motivation, cognitive abilities, skills, and confidence, which enable individuals to make informed decisions within environmental contexts. Individuals with high levels of environmental literacy are willing to take action to improve the well-being of individuals, communities, and the environment and can participate actively in civic life. In fact, the development of environmental literacy relies heavily on the implementation of effective environmental education programs [47,48].

The evaluation of environmental literacy has been the subject of numerous studies conducted in different countries across the world, using distinct population samples (e.g., university students [6,49], middle school students [50,51,52], and general population [7,53]). However, these studies addressed environmental literacy in a global way and did not focus on thematic areas. Furthermore, they are centered on assessing the attitudes and behaviors of the population, emphasizing the interconnection between environmental literacy, health, and the adoption of healthy lifestyles.

Sasa et al. [6] conducted a research study to assess the environmental literacy of students at Applied Science Private University in Jordan and investigate how demographic factors influence their level of environmental literacy. The results of this study revealed that students had a high level of environmental knowledge regarding energy, pollution, and recycling, whereas their knowledge was moderately developed in areas such as environmental concerns, ecology, water scarcity, global warming, and ozone layer depletion. The study identified lower mean scores in relation to the time of garden irrigation and flue gas. Additionally, the findings demonstrated that factors such as gender, faculty, cumulative average, and income level did not have any significant influence on students’ environmental literacy.

Carducci et al. [49] investigated the factors influencing health-related pro-environmental behaviors among Italian university students. The study found that over 70% of students had positive attitudes towards pro-environmental behaviors, which were positively associated with health risk perception, internal locus of control, and health literacy. However, the authors concluded that the adoption of such behaviors was low, with only around 20% of students engaging in most behaviors, except for the separate collection of waste (which had a 60% adoption rate). External obstacles such as lack of time, cost, and support were identified as the main reasons for the low adoption rate. Although health-related aspects were linked to pro-environmental attitudes, their association with pro-environmental behaviors was found to be weaker due to the complexity of the factors that determine behavior.

Miftahuddin et al. [50] investigated the environmental literacy profile of junior high school students. According to this study, junior high school students’ average environmental literacy was 49.95%, which was considered sufficient. Different environmental literacy indicators had different average scores, with ecological knowledge at 9.15% (sufficient), cognitive skills at 4.23% (low), environmental awareness at 80.11% (good), and environmentally responsible behavior at 70.75% (good).

Cincera et al. [51] conducted a study with students of 6th, 8th, and 9th graders in the Czech Republic and found the existence of notable disparities between the participants of outdoor environmental education programs, school eco-clubs, or non-formal education youth clubs that focus on nature, as opposed to those who did not engage in these activities.

Akçay et al. [52] investigated the environmental literacy levels of middle school students in Turkey. The study employed an environmental literacy scale to compare the environmental literacy levels of students based on various variables. The findings suggest that the overall environmental literacy level of middle school students is good, with female students displaying a better level of environmental literacy than male students. Although there was no significant difference observed in environmental literacy levels across different class levels, public school students scored higher than private school students. In addition, students living in city centers had higher environmental literacy scores than those living in villages. The study also revealed that students who follow environment-related magazines, social media, or television have significantly higher environmental literacy levels than those who do not. Furthermore, students who believe that environmental education at schools is sufficient to display a higher level of environmentally responsible behavior compared to those who do not [52].

Hou et al. [53] conducted a study to assess the level of Ambient Air Pollution Health Literacy (AAPHL) among the population residing in Taiwan, specifically in three health contexts: healthcare, disease prevention, and health promotion. The results showed that people in Taiwan had only a moderate level of AAPHL, and various factors such as education, living arrangement, marital status, and area of living were significantly associated with AAPHL. In future educational interventions aimed at improving the AAPHL in the community, these factors should be considered.

Biswas [7] carried out a study focused on assessing environmental literacy, environmental attitudes, and sustainable/healthy living practices. The results suggest that the development of an environmental attitude is closely linked to exposure to environmental awareness programs. The study recommends that higher education institutions, government, and non-governmental organizations collaborate to promote environmental literacy. The findings highlight the interconnections among education, attitudes, and sustainable living. Environmental literacy is recognized as a critical starting point to initiate positive and strong links between the environment, education, and health and to bring about change.

2.3. Artificial Neural Network-Driven Methodology

Artificial Neural Networks (ANNs) are a type of machine learning algorithm that is inspired by the structure and function of the human brain. They are specifically designed to recognize patterns and relationships in data, learn from examples, and use that knowledge to make predictions or decisions. ANNs are made up of numerous interconnected nodes that process and transmit information. Each node receives input from other nodes or external sources, applies an activation function to the input, and then sends the output to other nodes. The connections between the nodes have weights, which are adjusted during training to improve the network’s performance. An ANN architecture widely used is the multilayer perceptron (MLP), which arranges artificial neurons into layers with unidirectional connections. MLP design is commonly achieved through trial-and-error, and several methods have been proposed to attain this goal, such as hill-climbing approaches that adjust the initial architecture to minimize an internal error measure [54,55,56]. Over the past few years, ANNs have been successfully used in a variety of domains, including environmental sciences [57,58,59,60], healthcare [61,62,63], and production [64,65].

3. Materials and Methods

3.1. Research Design

The assessment of environmental literacy levels regarding biotechnological solutions is crucial for fostering environmental sustainability. To achieve this, a study was designed. Its objectives are, on the one hand, to assess the level of literacy of the Portuguese population in relation to biotechnological solutions for environmental sustainability and, on the other hand, to create a predictive model to manage their literacy. Thus, it is intended to answer the following research question:

• What is the population’s literacy to biotechnological solutions for environmental sustainability?

Considering the research question and the fact that the majority of questionnaires found in the literature primarily assess the attitudes and behaviors of the population with a focus on the interconnection between environmental literacy, health, and the adoption of healthy lifestyles, a questionnaire was designed, validated, and applied to a random sample of individuals of both genders, spanning various ages, educational backgrounds, and regions in Portugal.

In the design of the questionnaire, four central thematic areas were considered (i.e., Air Pollution, Aquatic Pollution, Global Warming, and Energy Resources) to enable the utilization of the methodology proposed by Fernandes et al. [66] to convert non-numerical data into numerical data. These points are presented detailed in subsections Section 3.2. Data collection, Section 3.3. Participants and Section 3.4. Qualitative data processing.

3.2. Data Collection

The questionnaire survey was selected based on a careful evaluation of the advantages and limitations of possible techniques. The decision to use the questionnaire survey was supported by its simplicity, and versatility. Moreover, the questionnaire survey possesses a clearly delineated structure and facilitates the conversion of qualitative feedback given by participants into quantitative data [67,68,69,70].

The questionnaire developed for this research is composed of two parts. The first part collects sociodemographic information, such as age, gender, educational background, and place of residence. The second part includes a set of statements (

Table 1. Categorization of statements in Part II of the questionnaire by thematic areas.

Air Pollution	S1	Using biofuels reduces atmospheric emissions of polluting gases.
	S2	Decreasing combustion engine usage can contribute to the reduction of air pollution.
	S3	Using biofilters aids in reducing atmospheric pollution.
	S4	Using activated carbon can aid in retaining polluting gases.
	S5	Catalytic converters in motor vehicles reduce emissions of polluting gases.
	S6	Using pesticides/fertilizers leads to air contamination.
Aquatic Pollution	S7	Using microorganisms can quicken the process of water purification in the occurrence of oil spills in the oceans.
	S8	Using specific plants can aid in decontaminating watercourses.
	S9	Using fertilizers and pesticides in agriculture can lead to contamination of water bodies.
	S10	Releasing chemicals into domestic sewage can contaminate natural waters.
	S11	Directly discharging industrial waste into watercourses can lead to the death of living organisms.
	S12	Promoting environmental consciousness among beach users can contribute to reducing water pollution.
Global Warming	S13	The main factor responsible for global warming is the use of fossil fuels.
	S14	The melting of glaciers is occurring rapidly due to the warming of the planet.
	S15	Urban expansion has led to deforestation, contributing to the greenhouse effect.
	S16	The excessive use of CFCs contributes to ozone hole growth.
	S17	Adopting sustainable behaviors is an asset for environmental preservation and improving quality of life.
Energy Resources	S18	Using renewable energies aids in protecting the environment.
	S19	The utilization of biogas as an energy source is progressively increasing.
	S20	Renewable energies are inexhaustible.
	S21	The lower environmental impact of renewable energies makes them a better choice.
	S22	Using alternative energies contributes to reducing carbon dioxide emissions.

) on the four subjects covered in the research (i.e., Air Pollution, Aquatic Pollution, Global Warming, and Energy Resources), for which participants were asked to provide their opinion. In contrast to the descriptive nature of the answers in the first part, the second part utilized a Likert scale with five levels (i.e., strongly agree, agree, disagree, strongly disagree, and I don’t know).

Following Bell’s guidelines [71], a panel of experts evaluated and recommended changes to the questionnaire, which were incorporated into an updated version. The revised version was then tested for validity and comprehension issues with a restricted group of participants outside the sample.

The revised questionnaire was administered individually and in a physical format to each participant in the sample (i.e., offline). A total of 471 questionnaires were returned out of the 500 distributed, corresponding to a return rate of 94.2%.

3.3. Participants

The study used a sample comprising 471 participants, ranging in age from 15 to 78 years old, with an average age of 40 ± 16 years old.

Table 2. Distribution of participants by age group, gender, academic qualifications, and regions of Portugal.

Variable	Class	Frequency
Age (years old)	≤25	98
	[26, 40]	145
	[41, 50]	121
	[51, 65]	66
	>65	41
Gender	Female	281
	Male	190
Academic Qualifications	Basic Education	211
	Secondary Education	174
	High Education	63
	Post-Graduate Education	23
Region of Portugal	Northern	108
	Central	153
	Southern	210

displays the distribution of participants by age group, gender, academic qualifications, and regions of Portugal. The analysis of Table 2 shows that 20.8% of participants were under 25 years old, 30.8% were between 26 and 40 years old, 25.7% were between 41 and 50 years old, 14.0% were between 51 and 65 years old, 8.7% were above 65 years old. Out of the total sample, 59.7% were female, and 40.3% were male. With regards to academic qualifications, 44.8% of the sample completed basic education, 36.9% finished secondary education, 13.4% obtained a degree, and 4.9% hold a post-graduate degree. In relation to the place of residence, 22.9%, 32.5%, and 44.6% are, respectively, from the northern, central, and southern regions of Portugal.

3.4. Qualitative Data Processing

The data collected in part II of the questionnaire is non-numerical in nature and has been rated on a Likert scale with five levels. The non-numerical data was transformed into numerical data by following the methodological approach recommended by Fernandes et al. [66]. The k responses on a specific topic are represented in a circle with a radius of $1/\sqrt{\pi }$, divided into k sections, with each response option indicated by a mark on the axis, as shown in subsection Section 4.3. Literacy assessment.

3.5. Artificial Neural Networks

ANNs-based models were developed using the WEKA software, with the parameters’ default settings left unaltered [72,73]. In the learning stage, the backpropagation algorithm and the logistic activation function were used [54,55,56]. The statistical significance of the outcomes was guaranteed by conducting twenty-five replicates in all tests. Each simulation involved the random division of data into two exclusive partitions. The training set (comprising 67% of the available data) and the test set (including the leftover examples). During the model development process, the former set of data was used, while the latter set was used to evaluate its ability to generalize.

3.6. Ethical Aspects

The study was carried out in compliance with the prevailing legal regulations. All participants were informed about the objectives of the research and gave their consent to complete the questionnaire.

4. Results and Discussion

In this section, the results obtained in a study aiming to assess literacy to biotechnological solutions for environmental sustainability conducted in Portugal are presented. Among the 500 questionnaires distributed, 29 (5.8%) were discarded from the study due to the absence of responses to the second section. Therefore, the results presented below are based on the responses of 471 participants.

4.1. Frequency of Response Analysis

The graph presented in Figure 1 shows the frequencies of responses relative to the statements included in the Air Pollution theme. Its analysis shows that the response most often given to statements 1, 3, 4, 5, and 6 was agree, and the mean values for Likert scale responses varied between 3.04 and 3.23. In the case of statement 1 (related to the use of biofuels), the response frequency was 60.1%. Regarding statement 3 (related to the use of biofilters), the respective frequency was 52.6%. Concerning statement 4 (related to the use of activated carbon), 36.3% of participants selected the option agree, while for statements 5 (related to the use of catalytic converters) and 6 (related to contamination by pesticides/fertilizers), those frequencies were 61.8% and 67.3%, respectively. In statement 2 (related to the use of combustion engines), the most chosen option was strongly agree (52.7%), followed by the option agree (43.7%). In this case, the mean value for Likert scale responses was 3.52.

None of the participants who chose the option strongly disagree. The option disagree was selected by less than 2% of participants for statements 1, 2, and 3, while for statements 4 and 6, more than 10% of participants marked this option.

Finally, it is worth highlighting that the option I don’t know was selected in all statements. Statement 4 obtained the highest number of responses I don’t know, with 32.7%, followed by statements 3 and 5, both with 27.4%, and statement 1, with 21.9%. Concerning statements 6 and 2, this percentage was lower (i.e., 7.2% and 1.7%, respectively).

The results presented in Figure 1 shows that the issues related to biofuels, biofilters, activated carbon, and catalytic converters are unknown to a considerable percentage of participants. However, they show that the level of literacy regarding some issues (combustion engines and pesticides/fertilizers) of the topic of Air Pollution is high. These results are in accordance with those obtained by other authors who have conducted studies on this subject [6,52,53].

The graph presented in Figure 2 shows the frequency of responses related to the statements included in the topic of Aquatic Pollution. Its analysis shows that the response most frequently given to statements 7, 8, 9, 10, and 12 was agree, and the mean values for Likert scale responses varied between 3.11 and 3.44. In the case of statement 7 (related to the use of microorganisms for decontamination), the frequency of response was 43.5%. Regarding statement 8 (related to the use of plants for decontamination), the respective frequency was 51.0%. Concerning statement 9 (related to pollution by fertilizers/pesticides), 60.1% of participants selected the option agree, while in statements 10 (related to contamination by chemical products) and 12 (related to the environmental awareness of beach users), these frequencies were 67.3% and 54.6%, respectively. In statement 11 (related to the dumping of industrial sewage), the most chosen option was strongly agree (67.3%). In this case, the mean value for Likert scale responses was 3.67. It should be noted that in statement 12, most participants answered agree (54.6%), but there was also a high percentage (43.5%) who answered strongly agree.

None of the participants chose the option strongly disagree. The option disagree was selected by less than 2% of participants for statements 7 and 9 (i.e., 1.9% and 1.7%, respectively), while for statement 8, this option was ticked by 10.8% of participants. Finally, with regard to the option I don’t know, statements 7 and 8 obtained the highest percentage of responses I don’t know (36.3% and 18.2%, respectively). For the remaining statements, this percentage did not exceed 6%.

The results obtained regarding the topic of Aquatic Pollution (Figure 2) show that the issues related to bioremediation/phytoremediation are unknown to a considerable percentage of participants. However, when considered as a whole, the results show high levels of literacy regarding this topic. This result disagrees with those obtained by O’Halloran and Silver [74] and Steel et al. [75]. This discrepancy may be related to the fact that the samples include individuals from different countries with very different habits and cultures.

The graph presented in Figure 3 shows the frequency of responses related to statements included in the theme of Global Warming. The analysis of the graph shows that the response most often given to statements 13, 14, 15, and 16 was agree, and the mean values for Likert scale responses varied between 3.27 and 3.42. In the case of statement 13 (related to the use of fossil fuels), the frequency of response was 63.7%. Concerning statement 14 (related to polar ice melting), the respective frequency was 60.1%, whereas for statement 15 (related to deforestation) and statement 16 (related to the use of CFCs), the frequency of response was 58.2% and 49.9%, respectively. Regarding statement 17 (related to adopting more sustainable behaviors), the most chosen option was strongly agree (51.0%), followed by the option agree (49.0%). In this case, the mean value for Likert scale responses was 3.51. Regarding the options strongly disagree and disagree, it was not chosen by any of the participants, except for statements 14 and 15, where the option disagree was marked by 1.9% and 1.7% of participants, respectively.

In this set of statements, the one in which the option I don’t know was chosen by the highest percentage of participants was statement 16, with 31.0%, followed by statements 13 and 15, both with 12.7%. In the remaining statements, this percentage did not exceed 2%.

The overall analysis of the results presented in Figure 3 shows that participants exhibit a high level of literacy regarding some issues (glaciers melting and adoption of sustainable behaviors) of the topic of Global Warming. However, a high percentage of participants are unaware of the role of CFC in the depletion of the ozone layer. These findings are consistent with the results reported by other authors [6,49,50].

The graph presented in Figure 4 shows the frequency of responses related to the statements included in the topic of Energy Resources. Upon analyzing the graph, it can be observed that the option agree was the most selected in all statements of this group, and the mean values for Likert scale responses varied between 2.89 and 3.49. In the case of statement 18 (related to the use of renewable energy), the percentage of participants who selected this option was 54.6%. In statements 19 (related to the use of biogas) and 20 (related to the inexhaustibility of renewable energy), the percentage of responses agree was 47.3%, while in statements 21 (related to the environmental impact of renewable energy) and 22 (related to CO₂ emissions) the percentage of responses agree were 67.3% and 43.7%, respectively. Furthermore, it can be noted that for statements 18, 21, and 22, the second most commonly selected option was strongly agree, with percentages of 43.5%, 21.9%, and 41.8%, respectively.

It should also be noted that statement 20 was the only one in which the option strongly disagree was selected (3.6%). Concerning the option disagree, it was marked by 1.7% and 14.4% of participants in statements 19 and 20, respectively.

Finally, with regard to the option I don’t know, statements 19 and 20 obtained the highest number of responses (45.5% and 21.9%, respectively). In statements 21 and 22, this percentage was not beyond 15%, and it was only 1.9% in statement 18.

The results depicted in Figure 4 indicate that a relatively high percentage of participants demonstrate a lack of knowledge regarding issues related to biogas and the inexhaustibility of renewable energy. Nevertheless, with respect to the remaining issues covered under the topic of Energy Resources, the results demonstrate a high/medium level of literacy. These outcomes are consistent with findings reported by other authors who have conducted studies on this subject [6,50,52].

4.2. Influence of Socio-Demographic Characteristics

To examine the impact of participants’ socio-demographic characteristics on their literacy to biotechnological solutions for environmental sustainability, the responses obtained in the second part of the questionnaire were analyzed separately according to age group (

Table 3. Frequencies of responses (%) related to the statements included in Part II of the questionnaire by thematic areas and age groups.

Response Options	Age Groups	Statements
		Air Pollution						Aquatic Pollution						Global Warming					Energy Resources
		S1	S2	S3	S4	S5	S6	S7	S8	S9	S10	S11	S12	S13	S14	S15	S16	S17	S18	S19	S20	S21	S22
Strongly disagree	≤25	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	5.1	0.0	0.0
	[26, 40]	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.4	0.0	0.0
	[41, 50]	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.8	0.0	0.0
	[51, 65]	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6.1	0.0	0.0
	>65	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	12.2	0.0	0.0
Disagree	≤25	2.0	3.1	3.1	2.0	0.0	9.2	1.0	21.4	2.0	0.0	0.0	0.0	0.0	2.1	1.0	0.0	0.0	0.0	3.1	19.4	0.0	0.0
	[26, 40]	1.4	1.4	0.7	15.9	0.0	9.0	0.0	5.5	1.4	0.0	0.0	0.0	0.0	0.7	0.7	0.0	0.0	0.0	1.4	13.1	0.0	0.0
	[41, 50]	0.8	1.7	0.8	15.7	0.0	12.4	1.7	5.8	1.6	0.0	0.0	0.0	0.0	0.8	0.8	0.0	0.0	0.0	0.0	11.6	0.0	0.0
	[51, 65]	1.5	1.5	1.5	22.7	0.0	12.1	4.5	7.6	1.5	0.0	0.0	0.0	0.0	3.0	3.0	0.0	0.0	0.0	0.0	13.6	0.0	0.0
	>65	4.9	2.4	4.9	2.4	0.0	17.0	7.3	24.4	2.4	0.0	0.0	0.0	0.0	7.3	7.3	0.0	0.0	0.0	7.3	17.1	0.0	0.0
Agree	≤25	54.1	51.0	26.5	22.5	58.2	70.4	40.8	40.8	68.4	71.4	57.1	55.1	60.2	64.3	56.1	36.7	55.1	61.2	22.4	38.8	59.2	36.7
	[26, 40]	66.9	40.0	69.0	48.9	69.7	73.8	51.0	61.4	56.5	66.2	22.1	53.1	67.6	59.3	62.8	44.1	47.6	51.0	60.7	55.2	73.1	49.6
	[41, 50]	70.2	44.6	66.1	48.8	70.2	60.3	47.1	54.5	55.4	66.9	21.5	53.7	67.8	59.5	62.8	44.6	43.8	50.4	60.3	57.9	73.6	46.3
	[51, 65]	63.6	43.9	59.1	25.8	51.5	65.2	37.9	51.5	59.1	63.6	24.2	51.5	63.6	56.1	57.6	43.9	48.5	50.0	56.0	47.0	71.2	48.5
	>65	14.6	36.6	7.3	4.9	34.1	61.0	22.0	26.8	68.3	68.3	58.5	65.9	46.3	61.0	34.2	12.2	56.1	70.7	4.9	9.7	41.5	24.4
Strongly agree	≤25	5.1	43.9	7.1	11.2	10.2	13.3	11.2	15.3	22.5	23.5	42.9	42.9	21.4	31.6	23.5	17.4	44.9	35.7	3.1	7.1	17.3	29.6
	[26, 40]	22.1	57.9	20.0	22.1	11.7	14.5	22.1	21.4	40.0	30.3	77.9	44.8	25.5	40.0	30.3	35.9	52.4	48.3	6.9	16.5	25.5	48.3
	[41, 50]	20.7	53.7	26.5	23.1	11.6	15.7	22.3	22.3	41.3	30.6	78.5	44.6	25.6	39.7	30.6	36.4	56.2	49.6	8.3	16.5	26.4	52.0
	[51, 65]	18.2	53.1	21.2	22.7	12.1	15.1	21.2	21.2	37.9	28.8	75.8	47.0	25.8	39.4	28.8	34.9	51.5	47.0	6.1	13.6	24.3	47.0
	>65	7.3	51.2	9.8	0.0	4.9	12.2	4.9	17.1	19.5	14.6	41.5	31.7	12.2	19.5	14.6	2.4	43.9	22.0	0.0	0.0	2.4	9.8
I don’t know	≤25	38.8	2.0	63.3	64.3	31.6	7.1	47.0	22.5	7.1	5.1	0.0	2.0	18.4	2.0	19.4	45.9	0.0	3.1	71.4	29.6	23.5	33.7
	[26, 40]	9.6	0.7	10.3	13.1	18.6	2.7	26.9	11.7	2.1	3.5	0.0	2.1	6.9	0.0	6.2	20.0	0.0	0.7	31.0	13.8	1.4	2.1
	[41, 50]	8.3	0.0	6.6	12.4	18.2	11.6	28.9	17.4	1.7	2.5	0.0	1.7	6.6	0.0	5.8	19.0	0.0	0.0	31.4	13.2	0.0	1.7
	[51, 65]	16.7	1.5	18.2	28.8	36.4	7.6	36.4	19.7	1.5	7.6	0.0	1.5	10.6	1.5	10.6	21.2	0.0	3.0	37.9	19.7	4.5	4.5
	>65	73.2	9.8	78.0	92.7	61.0	9.8	65.8	31.7	9.8	17.1	0.0	2.4	41.5	12.2	43.9	85.4	0.0	7.3	87.8	61.0	56.1	65.8

), gender (

Table 4. Frequencies of responses (%) related to the statements included in Part II of the questionnaire by thematic areas and gender.

Response Options	Gender	Statements
		Air Pollution						Aquatic Pollution						Global Warming					Energy Resources
		S1	S2	S3	S4	S5	S6	S7	S8	S9	S10	S11	S12	S13	S14	S15	S16	S17	S18	S19	S20	S21	S22
Strongly disagree	Female	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	3.6	0.0	0.0
	Male	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	3.7	0.0	0.0
Disagree	Female	1.8	1.8	1.4	12.1	0.0	10.7	1.8	10.3	1.8	0.0	0.0	0.0	0.0	1.4	1.1	0.0	0.0	0.0	1.8	14.6	0.0	0.0
	Male	1.6	2.1	2.1	13.7	0.0	11.6	2.1	11.6	1.6	0.0	0.0	0.0	0.0	2.6	2.6	0.0	0.0	0.0	1.6	14.2	0.0	0.0
Agree	Female	59.4	43.4	53.0	35.6	61.9	68.0	43.7	50.9	60.8	67.3	32.0	54.1	64.4	60.1	58.7	40.2	48.4	54.8	47.0	47.0	67.3	43.8
	Male	61.0	44.2	52.1	37.3	61.6	66.3	43.2	51.1	58.9	67.4	33.7	55.3	62.6	60.0	57.4	39.5	50.0	54.2	47.9	47.9	67.4	43.7
Strongly agree	Female	17.1	53.0	18.9	18.9	10.3	14.2	17.8	20.7	34.2	27.7	68.0	44.1	23.5	36.7	27.4	29.5	51.6	43.4	5.3	13.1	21.7	41.3
	Male	15.3	52.1	17.4	17.4	11.6	14.7	18.9	18.9	35.3	26.8	66.3	42.6	23.7	35.8	26.3	28.4	50.0	43.7	5.8	12.1	22.1	42.6
I don’t know	Female	21.7	1.8	26.7	33.4	27.8	7.1	36.7	18.1	3.2	5.0	0.0	1.8	12.1	1.8	12.8	30.3	0.0	1.8	45.9	21.7	11.0	14.9
	Male	22.1	1.6	28.4	31.6	26.8	7.4	35.8	18.4	4.2	5.8	0.0	2.1	13.7	1.6	13.7	32.1	0.0	2.1	44.7	22.1	10.5	13.7

), academic qualifications (

Table 5. Frequencies of responses (%) related to the statements included in Part II of the questionnaire by thematic areas and academic qualifications.

Response Options	Academic Qualifications	Statements
		Air Pollution						Aquatic Pollution						Global Warming					Energy Resources
		S1	S2	S3	S4	S5	S6	S7	S8	S9	S10	S11	S12	S13	S14	S15	S16	S17	S18	S19	S20	S21	S22
Strongly disagree	Basic ed.	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	4.8	0.0	0.0
	Secondary ed.	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	3.4	0.0	0.0
	High ed.	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.6	0.0	0.0
	Post-graduate ed.	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
Disagree	Basic ed.	2.8	2.8	2.4	17.5	0.0	14.7	3.3	16.1	2.9	0.0	0.0	0.0	0.0	3.3	2.4	0.0	0.0	0.0	2.9	17.5	0.0	0.0
	Secondary ed.	1.1	1.7	1.7	12.1	0.0	11.5	1.2	9.2	1.2	0.0	0.0	0.0	0.0	1.2	1.7	0.0	0.0	0.0	1.2	16.1	0.0	0.0
	High ed.	0.0	0.0	0.0	3.2	0.0	1.6	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	4.7	0.0	0.0
	Post-graduate ed.	0.0	0.0	0.0	0.0	0.0	0.0	0.0	4.4	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
Agree	Basic ed.	66.4	72.0	60.6	40.8	67.3	71.6	49.3	56.4	81.5	85.3	44.5	66.8	72.0	73.9	72.0	47.9	64.5	65.4	41.2	51.2	77.7	55.0
	Secondary ed.	63.2	21.9	50.6	36.2	62.6	73.6	44.8	52.9	54.0	62.6	27.0	51.1	62.7	55.7	57.5	37.4	43.7	52.9	44.8	47.7	71.3	35.6
	High ed.	39.7	20.6	39.7	25.4	47.6	47.6	28.6	34.9	20.6	33.3	17.5	31.7	46.0	36.5	27.0	28.6	25.4	34.9	69.8	38.1	36.5	34.9
	Post-graduate ed.	34.8	13.0	30.5	26.1	43.5	34.8	21.8	30.4	17.4	30.4	8.7	30.4	43.5	30.4	21.7	17.4	13.0	21.7	60.9	34.8	26.1	26.1
Strongly agree	Basic ed.	4.3	22.8	5.7	4.7	0.9	4.2	4.7	4.7	10.9	7.6	55.5	30.8	12.3	20.4	10.4	15.6	35.5	32.2	0.0	1.4	8.5	28.9
	Secondary ed.	10.3	74.7	13.2	9.8	2.3	6.9	9.2	16.6	40.8	31.6	73.0	46.6	22.4	41.4	25.3	25.3	56.3	44.8	1.1	5.2	16.1	45.4
	High ed.	57.1	79.4	57.1	68.2	50.8	50.8	68.2	63.5	79.4	66.7	82.5	68.3	52.4	63.5	71.4	66.7	74.6	65.1	25.4	52.4	63.5	63.5
	Post-graduate ed.	60.9	87.0	65.2	69.6	56.5	65.2	73.9	65.2	82.6	69.6	91.3	69.6	56.5	69.6	78.3	78.3	87.0	78.3	34.8	65.2	73.9	73.9
I don’t know	Basic ed.	26.5	2.4	31.3	37.0	31.8	9.5	42.7	22.8	4.7	7.1	0.0	2.4	15.7	2.4	15.2	36.5	0.0	2.4	55.9	25.1	13.8	16.1
	Secondary ed.	25.4	1.7	34.5	41.9	35.1	8.0	44.8	21.3	4.0	5.8	0.0	2.3	14.9	1.7	15.5	37.3	0.0	2.3	52.9	27.6	12.6	19.0
	High ed.	3.2	0.0	3.2	3.2	1.6	0.0	3.2	1.6	0.0	0.0	0.0	0.0	1.6	0.0	1.6	4.7	0.0	0.0	4.8	3.2	0.0	1.6
	Post-graduate ed.	4.3	0.0	4.3	4.3	0.0	0.0	4.3	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	4.3	0.0	0.0	4.3	0.0	0.0	0.0

), and regions of Portugal (

Table 6. Frequencies of responses (%) related to the statements included in Part II of the questionnaire by thematic areas and regions of Portugal.

Response Options	Regions of Portugal	Statements
		Air Pollution						Aquatic Pollution						Global Warming					Energy Resources
		S1	S2	S3	S4	S5	S6	S7	S8	S9	S10	S11	S12	S13	S14	S15	S16	S17	S18	S19	S20	S21	S22
Strongly disagree	Northern	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	2.8	0.0	0.0
	Central	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	3.9	0.0	0.0
	Southern	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	3.8	0.0	0.0
Disagree	Northern	1.8	1.8	1.8	13.0	0.0	11.1	1.9	11.1	1.8	0.0	0.0	0.0	0.0	1.8	1.8	0.0	0.0	0.0	1.8	14.8	0.0	0.0
	Central	2.0	2.0	1.3	12.4	0.0	11.1	2.0	10.4	1.3	0.0	0.0	0.0	0.0	2.0	2.0	0.0	0.0	0.0	2.0	14.4	0.0	0.0
	Southern	1.4	1.9	1.9	12.9	0.0	11.0	1.9	10.9	1.9	0.0	0.0	0.0	0.0	1.9	1.4	0.0	0.0	0.0	1.4	14.3	0.0	0.0
Agree	Northern	60.2	43.5	52.8	36.1	62.0	67.6	43.5	50.9	60.2	67.6	32.4	54.6	63.9	60.2	58.3	39.8	49.1	54.6	47.2	47.2	67.6	43.5
	Central	60.1	43.8	52.9	36.6	61.4	67.3	43.1	51.0	60.1	67.3	32.7	54.2	63.4	60.1	58.2	39.9	49.0	54.2	47.0	47.7	67.3	43.8
	Southern	60.0	43.8	52.4	36.2	61.9	67.1	43.8	51.0	60.0	67.2	32.9	54.8	63.8	60.0	58.1	40.0	49.0	54.8	47.6	47.1	67.1	43.8
Strongly agree	Northern	16.7	52.8	18.5	18.5	11.1	13.9	18.5	19.5	34.3	26.9	67.6	43.5	23.1	36.2	26.9	28.7	50.9	43.5	5.6	13.0	22.2	41.7
	Central	16.3	52.2	18.3	18.3	10.5	14.4	18.3	20.3	34.7	27.5	67.3	43.8	24.2	36.6	27.4	29.4	51.0	43.8	5.2	12.4	21.6	41.8
	Southern	16.2	52.9	18.1	18.1	11.0	14.8	18.1	20.0	34.8	27.6	67.1	43.3	23.3	36.2	27.6	29.0	51.0	43.3	5.7	12.9	21.9	41.9
I don’t know	Northern	21.3	1.9	26.9	32.4	26.9	7.4	36.1	18.5	3.7	5.5	0.0	1.9	13.0	1.8	13.0	31.5	0.0	1.9	45.4	22.2	10.2	14.8
	Central	21.6	2.0	27.5	32.7	28.1	7.2	36.6	18.3	3.9	5.2	0.0	2.0	12.4	1.3	12.4	30.7	0.0	2.0	45.8	21.6	11.1	14.4
	Southern	22.4	1.4	27.6	32.8	27.1	7.1	36.2	18.1	3.3	5.2	0.0	1.9	12.9	1.9	12.9	31.0	0.0	1.9	45.3	21.9	11.0	14.3

).

The analysis of Table 3 reveals that the option I don’t know was predominantly selected by participants included in the age group above 65 years old. Particularly noteworthy are statements 3, 4, 16, and 19, where this option was chosen by over 75% of these participants, and statements 1, 5, 7, 20, 21, and 22, where the aforementioned option was selected by over 50% of these participants. The option I don’t know was also chosen by a considerable number of participants in the age group under 25 years old. In fact, this option was selected by more than 45% of these participants in statements 3, 4, 7, 16, and 19. Regarding the option I don’t know, the difference between the frequencies of response provided by participants in the age groups of 26 to 40 years old and 41 to 50 years old was less than 3%, except for statements 3, 6, and 8, where the difference was 3.7%, 8.9%, and 5.7%, respectively. Concerning the option strongly agree, it was found that the age groups under 25 years old and above 65 years old exhibit lower frequencies of response than the other age groups. Additionally, the difference between the frequencies of response provided by participants in the age groups of 26 to 40 years old, 41 to 50 years old, and 51 to 65 years old do not exceed 5%.

Regarding the influence of gender on literacy to biotechnological solutions for environmental sustainability, the analysis of Table 4 shows that the difference between the frequencies of responses given in Part II of the questionnaire by women and men was less than 2%. These findings are consistent with the results reported by Sasa et al. [6], which point out that gender does not influence literacy levels.

Concerning the influence of academic qualifications, the analysis of Table 5 reveals that the option I don’t know was mainly selected by both participants who completed basic education and those who completed secondary education. It should be noted that in statement 19, this option was chosen by more than 50% of these participants. Conversely, the option I don’t know was selected by less than 5% of participants with a degree or a post-graduation. The option strongly agree, in turn, was chosen by more than 50% of participants with a degree or post-graduation, except for statement 19, which was ticked by less than 35% of these participants. In the case of participants with secondary education, the frequency of the response strongly agree was less than 50%, except for statements 2, 11, and 17, where these percentages were 74.7%, 73.0%, and 56.3%, respectively. Regarding participants with basic education, the frequency of this response was less than 33%, except for statements 11 and 17, where these percentages were 55.5% and 35.5%, respectively. Finally, excluding statement 19, the option agree was selected by a higher percentage of participants with basic or secondary education than those with a degree or a post-graduation. These outcomes are in agreement with the results reported by other authors [7,53], who have found positive correlations between the levels of education and the levels of environmental literacy.

Regarding the influence of the place of residence on literacy to biotechnological solutions for environmental sustainability, the analysis of Table 6 shows that the difference between the frequencies of responses given in Part II of the questionnaire was less than 2%, regardless of the region of Portugal where the participants’ residence is located. Regarding the place of residence, some studies have examined the influence of urban and rural areas and concluded that this socio-demographic variable influences environmental literacy levels [52,53]. However, it is important to note that the results of the present study cannot be directly compared to those studies as this research considers geographical regions of Portugal, which encompass both urban and rural areas.

4.3. Literacy Assessment

Figure 5 shows the options ticked by participant one to the second part of the questionnaire, whereas Figure 6 displays the quantification of participant one’s non-numerical information, which was carried out according to the methodological approach recommended by Fernandes et al. [66]. The procedure can be demonstrated by analyzing the selections made by participant one for the statements included in the thematic area of Air Pollution. Thus, to display the selections of the six statements included in the aforementioned thematic area, a circle with a radius of $1/\sqrt{\pi }$ was divided into six sections, with each response option corresponding to a mark on the axis (Figure 6). Considering that participant one ticked agree for statements 1, 3, and 5, the correspondent area assigned to each selected response is calculated as $\frac{1}{6}\pi {\left(\frac{3}{4\sqrt{\pi }}\right)}^2=0.09$. Regarding statement 2, the option selected was strongly agree, corresponding to the area $\frac{1}{6}\pi {\left(\frac{4}{4\sqrt{\pi }}\right)}^2=0.17$. In the case of statement 4, the option ticked was I don’t know, resulting in an area of zero. Finally, for statement 6, the option disagree was selected, corresponding to the area $\frac{1}{6}\pi {\left(\frac{2}{4\sqrt{\pi }}\right)}^2=0.05$. The quantitative value that corresponds to the options selected by participant one for the Air Pollution statements set is equal to the sum of the individual areas, i.e., 0.49. The process for the other thematic areas is similar, and the resulting values are listed in

Table 7. Excerpt of the data base used in Literacy (to biotechnological solutions for environmental sustainability) Evaluation.

Participant	Air Pollution	Aquatic Pollution	Global Warming	Energy Resources
1	0.49	0.69	0.54	0.48
2	0.71	0.70	0.91	0.55
3	0.36	0.49	0.45	0.39
…	…	…	…	…
471	0.23	0.43	0.42	0.42

.

The values present in Table 7 were used as input variables to training ANNs to predict literacy to biotechnological solutions for environmental sustainability. RNAs are computational tools inspired by the functioning of the human brain. The unidirectional architecture is one of the most widespread network architectures, in which artificial neurons (or nodes) are arranged in layers with only direct connections [54,55,56]. In order to determine the most effective ANN for evaluating literacy to biotechnological solutions for environmental sustainability, different network structures were elaborated and evaluated. The coincidence matrices were used to compare the performance of the ANN models. Out of the various network topologies that were evaluated, the 4-3-1-1 network (Figure 7) exhibited the most favorable response.

Table 8. Matrix of coincidences regarding 4-3-1-1 ANN model for the evaluation literacy to biotechnological solutions for environmental sustainability.

	Predict	Training			Test
Target		Low	Medium	High	Low	Medium	High
Low		71	7	1	35	5	0
Medium		10	158	7	8	72	5
High		0	4	56	0	3	29

provides the coincidence matrix for the ANN model depicted in Figure 7, with the values representing the average of 25 experiments. Based on the values presented in Table 8, the model’s accuracy was calculated for both the training set (90.8%, corresponding to 285 correctly classified out of 314) and the test set (86.6%, corresponding to 136 properly labeled out of 157). Thus, the 4-3-1-1 ANN model exhibits high performance in the evaluation of literacy to biotechnological solutions for environmental sustainability, with accuracy rates surpassing 85%.

The overall interpretation of Table 8 in terms of columns allows evaluating the number of participants identified by the model at each literacy level (i.e., low, medium, or high). Thus, the model identifies 124 participants as having a low level of literacy, which corresponds to 26.3% of the sample. Out of the identified cases, 106 were correctly classified, while the remaining 18 participants classified as low had a medium level of literacy. Regarding the 249 participants identified by the model as having a medium level of literacy (52.9% of the sample), 230 were correctly classified, while 12 were wrongly classified as low and 7 as high. Finally, concerning the 98 participants identified by the model as having a high level of literacy (20.8% of the sample), 85 were correctly classified, while 12 were wrongly classified as medium and one as low. Based on the values presented earlier, it is possible to compute the confidence that can be placed in the model’s predictions. Thus, regarding the prediction of the participants with levels of literacy low, medium, and high, the confidence in the model’s responses is 85.5%, 92.4%, and 86.7%, respectively.

In addition, the overall interpretation of Table 8 in terms of rows allows for evaluating the model’s performance regarding the actual number of participants at each literacy level. Thus, out of the 119 participants with low levels of literacy (25.3% of the sample), the model correctly identified 106, while 12 participants were wrongly classified as medium and one as high. Regarding the 260 participants with a medium level of literacy (55.2% of the sample), the model identified 230 correctly, whereas 18 were wrongly classified as low and 12 as high. Finally, concerning the 92 participants with high levels of literacy (19.5% of the sample), the model identified 85 correctly, whereas 7 were wrongly classified as medium.

Aiming to calculate the sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) of the 4-3-1-1 ANN model, the coincidence matrix for every potential output was created (

Table 9. Coincidence matrix regarding each output class of the 4-3-1-1 ANN model for the evaluation literacy to biotechnological solutions for environmental sustainability.

Target	Predictive				Target	Predictive				Target	Predictive
	Training Set		Test Set			Training Set		Test Set			Training Set		Test Set
	Low	No-Low	Low	No-Low		Medium	No-Medium	Medium	No-Medium		High	No-High	High	No-High
Low	71	8	35	5	Medium	158	17	72	13	High	56	4	29	3
No-Low	10	225	8	109	No-Medium	11	128	8	64	No-High	8	246	5	120

). Sensitivity is a measure of the proportion of positive cases (i.e., Low, Medium, or High) that are well labeled as positive, whereas specificity refers to the proportion of negative cases (i.e., No-Low, No-Medium, or No-High) that are well classified as negative. PPV indicates the proportion of correctly classified Low, Medium, or High cases, while NPV reflects the proportion of accurately labeled No-Low, No-Medium, or No-High cases [76,77].

Table 10. Sensitivity, Specificity, Positive Predictive Value (PPV), and Negative Predictive Value (NPV) for each output class of the ANN model, split by training and test.

Output	Training Set				Test Set
	Sensitivity	Specificity	PPV	NPV	Sensitivity	Specificity	PPV	NPV
Low	0.90	0.96	0.88	0.97	0.88	0.93	0.81	0.96
Medium	0.90	0.92	0.93	0.88	0.85	0.89	0.90	0.83
High	0.93	0.97	0.88	0.98	0.91	0.96	0.85	0.98

presents the values computed for the metrics mentioned above. The high values of sensitivity and specificity, ranging from 0.85 to 0.97, suggesting that the model performs well in assessing the levels of literacy for biotechnological solutions for environmental sustainability. This statement is supported by the values obtained for PPV and NPV, which also show high values ranging from 0.81 to 0.97.

The sensitivity analysis based on variance [78] was performed to examine the impact of ANN inputs on the outputs. The resulting relative importance (RI) of each input provides insights into their influence on the outputs. The results show that the literacy to biotechnological solutions for environmental sustainability is strongest affected by the topics Energy Resources (RI = 0.35) and Air Pollution (RI = 0.30), whereas the topics Global Warming (RI = 0.21) and Aquatic Pollution (RI = 0.14) have a lesser influence. These findings are corroborated by those reported in Section 4.1. In fact, the high number of responses I don’t know to Energy Resources and Air Pollution topics means that even minor changes in the responses to these topics can have a strong impact on literacy levels.

5. Conclusions

Achieving environmental sustainability has become more pressing than ever. Nonetheless, it requires the active participation of individuals through the adoption of environmentally-friendly behaviors. To fulfill this intention, it is of utmost importance to create awareness among the population regarding the environmental crisis. Indeed, the population’s engagement in sustainable actions is more effective when they possess a thorough knowledge of environmental sustainability issues. This study evaluated the level of literacy in a sample of the Portuguese population regarding biotechnological solutions for environmental sustainability, and the results obtained allow us to draw some conclusions. Thus, literacy regarding biotechnological solutions for environmental sustainability is influenced by age group. Specifically, participants above 65 years old demonstrate a lack of knowledge regarding issues such as biofuels, biofilters, activated carbon, catalytic converters, bioremediation, the role of CFCs in ozone depletion, and the benefits of renewable energy, with over 50% reporting unfamiliarity. Similarly, participants under 25 years old also show a lack of knowledge, with more than 45% indicating unawareness of issues related to biofilters, activated carbon, biogas, bioremediation, and the role of CFCs in ozone depletion. Conversely, the participants in the age groups of 26 to 40 years old and 41 to 50 years old reveal high levels of literacy regarding biotechnological solutions for environmental sustainability, with over 67% of responses agree or strongly agree.

Furthermore, literacy to biotechnological solutions for environmental sustainability is also influenced by academic qualifications. In fact, both participants who completed basic education and those who completed secondary education demonstrate a lack of knowledge regarding the same issues mentioned earlier, with over 30% reporting unfamiliarity. Conversely, the participants with a degree or a post-graduation reveal high levels of literacy regarding biotechnological solutions for environmental sustainability, with over 90% of responses being agree or strongly agree.

Additionally, literacy to biotechnological solutions for environmental sustainability is not influenced by both gender and place of residence. In fact, the difference between the frequencies of responses given in Part II of the questionnaire by women and men and by the participants from the different regions of Portugal is less than 2%.

The comparative analysis of the global results by thematic areas showed that the levels of literacy to biotechnological solutions for environmental sustainability are higher in the topics of Global Warming and Aquatic Pollution and lower in the topics of Air Pollution and Energy Resources. Specifically, with over 85% of responses being agree or strongly agree, the participants reveal high levels of literacy regarding some issues of the topic Global Warming (fossil fuels, glaciers melting, deforestation, and adoption of sustainable behaviors). This is similar in some issues of the topic of Aquatic Pollution (pollution by fertilizers/pesticides, contamination by chemicals, the dumping of industrial sewage, and environmental awareness of beach users). In the topic of Energy Resources, the participants revealed high levels of literacy regarding some issues (use of renewable energy; environmental impact of renewable energy, CO₂ emissions), and in the topic of Air Pollution in the issue related to the use of combustion engines.

Conversely, with over 33% of responses I don’t know, strongly disagree, or disagree, the participants reveal unaware of some issues on the topic of Energy Resources (use of biogas; and inexhaustibility of renewable energy). Similarly, on the topic of Air Pollution the participants revealed unawareness of the issue related to the use of activated carbon, and, in the topic of Aquatic Pollution, the issue related to the use of microorganisms for decontamination. This global analysis demonstrates that the participants have good levels of literacy on topics that have been frequently covered by the media and are commonly discussed in public. Conversely, they show a significant lack of literacy in issues that have not been widely publicized.

This study also presents an innovative approach to managing literacy to biotechnological solutions for environmental sustainability based on the ANN paradigm. The effectiveness of the suggested approach is satisfactory, achieving an accuracy rate exceeding 85% and sensitivities and specificities ranging from 0.85 to 0.97. Furthermore, the confidence in the model’s responses in the prediction of the levels of literacy is 85.5%, 92.4%, and 86.7% for low, medium, and high, respectively.

The results obtained for a sample of the Portuguese population allowed us to characterize the levels of literacy on biotechnological solutions for environmental sustainability, providing an answer to the research question that guided this study.

The main contribution of this work is the identification of the topics in which literacy levels are lower. With this knowledge, partnerships can be established between higher education institutions, governments, and non-governmental organizations capable of promoting outreach and training initiatives aimed at the general population regarding lesser-known topics, considering the age groups of the target audience. Additionally, the environmental education component in school curriculum programs must be strengthened, mainly in basic and secondary education.

Future work should involve expanding the questionnaire to include other environmental topics to broaden the study scope and to extend the study using a larger and more diversified sample of the Portuguese population. Moreover, Part I of the questionnaire should be expanded to include other socio-demographic characteristics such as income, occupation, living arrangement, marital status, or hobbies and pastimes.