https://orcid.org/0000-0002-9646-0161
Figures
Abstract
Air pollution is a risk factor associated with various adverse effects on physical and mental health. The aim of the present study was to predict whether the perception of green areas, trust in scientists and climate anxiety have an impact on the perception of the effects of air pollution on health (PAPH). Our sample was composed of communities of populated hills in Peru N = 1088. We used the survey method, a non-probabilistic sampling design by quotas and face-to-face interviews. The results show that the variables analyzed have a significant positive impact, explaining 26% of the PAPH variance. Gender, age, educational level, perception of green spaces, trust in scientists and climate anxiety were identified as significant predictors. Climate anxiety was a variable that explained more of the variance compared to sociodemographics, perception of green spaces and trust in scientists. The main findings are discussed and highlight the importance of emotional factors in air pollution risk perception and their implications for policy and communication strategies to tackle environmental threats such as air pollution and health effects.
Citation: Monge-Rodriguez FS, Huaman ET, Ibarra EM, Horna D, Montalvo M, Mendoza D (2026) The impact of green space perception, trust in scientists and climate anxiety in predicting the perception of air pollution health effects. PLOS Clim 5(6): e0000683. https://doi.org/10.1371/journal.pclm.0000683
Editor: Alessandro Del Ponte, Chapman University, UNITED STATES OF AMERICA
Received: June 24, 2025; Accepted: April 8, 2026; Published: June 9, 2026
Copyright: © 2026 Monge-Rodriguez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The authors declare that the data will be available through a link on the OSF platform: https://osf.io/5dkhq/overview.
Funding: This study has been financed by PROCIENCIA: Project AIRE: Atmospheric CONTAmInAmInAtIon In populated areas through grant number PE501082689-2023 under financial scheme E041-2023-01.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Air pollution is one of the greatest environmental risks to public health currently facing humanity [1]. Actually, represents a risk factor associated with several adverse health effects, such as respiratory diseases, cardiovascular diseases, indirect effects on mental health and premature mortality especially in vulnerable populations [2]. Latin America register large amounts of particulate air pollutants including total suspended particles spread in the cities (lead, carbon monoxide, among others), the streets have high concentrations of carbon monoxide up to 14.6 mg/m, exceeding the Cuban regulations (5 mg/m) [3,4]. This context is conducive to an increase in acute respiratory diseases related to high PM10 concentration levels [5] and could increase the mortality rate [6]. Besides these impacts on health, there are other negative effects of pollution, such the economy, fauna and flora, on the greenhouse effect, among others [3,7]. Peru has poor air quality, with Lima, the capital city, as one of the cities with the worst air quality in Latin America, showing up to 9.1 times higher than the annual reference value of PM2.5 of the WHO [8]. The city of Cusco [9] has reported high levels of PM2.5 particulate matter concentration. In addition, the IQAir report [10] indicates that air pollution in Cusco is 2.9 times higher than the reference value provided by the WHO.
In urban environments, vehicular traffic is one of the main anthropogenic sources of particulate matter (PM), especially PM10 and PM2.5, which are considered the most critical for public health [11]. It is estimated that more than 90% of the global population is exposed to PM2.5 concentrations above the limits recommended by the World Health Organization (5 µg/m³ annual mean) [12]. In some Latin American cities, such as Lima and Cusco, these levels can exceed 45 µg/m³ and 14.5 µg/m³, respectively [12]. Vehicular emissions produce carbonaceous particles through incomplete fuel combustion, contributing significantly to ambient PM levels [11]. PM concentrations decrease exponentially with distance from the emission source, indicating that exposure is highest near roadways and in narrow urban canyons [11]. Moreover, studies show that meadows can accumulate between 6.9 and 9.5 g/m² of PM, surpassing traditional lawns due to their higher biomass and canopy density [11]. However, urban vegetation must be planned carefully: models have shown that trees placed in street canyons can reduce wind speed and dispersion by up to 50%, leading to local increases in pollutant concentrations of up to 20% for NO2 and PM2.5, depending on tree density and canyon geometry [13]. These dynamics underscore the need to implement context-specific solutions that consider local meteorology, street layout, and vegetation type to effectively reduce human exposure to air pollution.
Several studies have shown that air pollution is recognized as a critical environmental determinant of health [14] and how people perceive it is linked to concerns and awareness of climate change [15]. Green spaces such as parks, urban forests, and community gardens are spaces for recreation and socialization [16] and are recognized for their potential to mitigate some of the harmful effects of air pollution and climate change [14], as they improve air quality, promote physical activity [17], and promote mental well-being [18]. In this sense, the study on the perception of green spaces is necessary because green spaces can shape the behaviors of people and influence the decision to spend more time outdoors and to engage in more physical activity [19] or support environmental programs or policies which in turn can influence public health [20].
Trust in scientists is a critical factor in the development of policies and public engagement with the problems and threats of air pollution and climate change [21]. Studies show that trust in scientists plays a crucial role in how people perceive environmental risks and their commitment to developing behaviors that can protect them [22]. Despite solid empirical evidence on public recognition of these risks linked to air pollution, adaptation or mitigation strategies are not uniformly applied, especially among vulnerable populations [22]. This could be explained by the different ways in which people tend to trust what scientists say or communicate, which can bias their judgement on how to interpret scientific information and, as a result, lead them to make decisions that could affect their health [23]. Furthermore, trust in science differs in terms of sociocultural contexts, audiences and impact on public policy [24]. Studies reported that trust in science can guide people, governments and other social agents in relevant issues such as public health or the search for new technologies to address climate change [25].
Overall, in the context of air pollution, low public trust in the discourse of scientists can lead to skepticism about pollution data and, as a result, develop attitudes of resistance to public health recommendations and show less support for environmental regulatory programs. On the other hand, trust in scientists is associated with greater willingness to receive science-based information and favorable disposition to adopt health-protective behaviors [26].
The integration of air pollution, health, and climate anxiety represents an emerging area of study that requires an interdisciplinary approach. Climate anxiety is indirectly linked to environmental risks and is currently a focus of attention for various academics studying emotional factors such as concern about climate change and air pollution [27]. Although the effects on physical health are well established, little is known about the effects on psychological dimensions associated with environmental impacts. Climate anxiety is defined as chronic fear or distress related to environmental change and the anticipated consequences of the climate crisis [28,29]. Climate anxiety is particularly relevant in the context of air pollution, as polluted air is both a direct threat to health and evidence of climate change [29]. Environments with high concentrations of air-polluting microparticles could increase people’s awareness of the risks and consequently exacerbate emotional responses such as fear, concern and ecological anxiety [30]. Furthermore, climate anxiety can influence health-related behaviors and support for public policies [31].
As far as we are currently aware, the evidence on the study of these variables has been addressed in isolation. The present study was aimed at analyzing the impact of the perception of green areas, trust in scientists and climate anxiety on the perception of the effects of air pollution on health. In addition, sociodemographic factors were included. In this sense, our study aims to fill this knowledge gap.
Materials and methods
Study area
This study focuses on two Peruvian cities with significant air quality challenges: Lima, the coastal capital with high population density and vehicular emissions, and Cusco, a high-altitude city with narrow streets and complex topography. Figs 1 and 2 show the selected urban areas analyzed in each city.
The base layer of the map was sourced from OpenStreetMap (https://www.openstreetmap.org/search?query=lima%2C+peru&zoom=10&minlon=8.112030029296877&minlat=45.00365115687186&maxlon=9.911041259765627&maxlat=45.80678584211672#map=12/-12.0489/-77.0828). Public domain data from Natural Earth is used under the terms described at https://www.openstreetmap.org/copyright.
The base layer of the map was sourced from OpenStreetMap (https://www.openstreetmap.org/node/59115290#map=14/-13.52765/-71.96955). Public domain data from Natural Earth is used under the terms described at https://www.openstreetmap.org/copyright.
Methods
Ethics statement.
The study was approved by the Universidad de Ingeniería y Tecnología (UTEC) and the Institutional Committee on Institutional Research Ethics of the University of Engineering and Technology (CIEI-UTEC), with Resolution No. 001–2024-CIEI-UTEC. There has not been any deviation from the ethics protocol during the study. All participants and respondents signed an informed consent document in person.
Participants
The participants were inhabitants of populated hills in the district of Cusco and Santiago in the Cusco region, and the district of Rimac and San Juan de Lurigancho in the capital Lima - Perú. The transactional survey method was used, data were collected between September and November 2024. Face-to-face surveys were applied using the digital survey platform “Zohosurvey”. In total, 1152 people over 18 years of age participated, from which a sample of N = 1088 was obtained based on the inclusion and exclusion criteria. Of the sample collected, 54.87% were female (n = 597) and 45.13% male (n = 491); 54.41% were young people between 18 and 35 years old, 42.46% were adults between 36 and 65 years old, and 3.13% were adults over 65 years old; likewise, 41.64% had a university education, 30.15% had a technical education, 24.45% had secondary education and 3.4% had primary education. Finally, 534 participants were from the Cusco region (49.08%) and 554 from Lima (50.92%).
Measurements
Questionnaire of perception of the effects of air pollution on health [32].
A 22-item instrument with two dimensions: (1) discomfort and perceived symptoms, and (2) perception of risks to health and quality of life. This evaluates the perception of air pollution on health, with a Likert-type response scale (1 = Not at all/ 7 = Quite a lot), evidencing an excellent internal consistency of.91 in the sample studied.
Green Areas Perception Questionnaire [33].
A 7-item, single-dimension questionnaire, with a response scale of 1 = Not at all to 5 = Quite a lot. This evaluates the perceived characteristics of green spaces and/or areas. The internal consistency of this instrument was.89 for the study.
Trust in Scientists Questionnaire [24].
A unidimensional 12-item instrument, with a Likert-type response scale from 1 to 5. It assesses public trust in people involved in science (medicine, chemistry, physics, economics, history, psychology, among others). Reliability analyses of this instrument showed an excellent internal consistency of.90.
CASS-S Climate Anxiety Questionnaire [34].
A measure of climate anxiety and its impacts on personal well-being of only 4 items, whose rating is based on a five-point Likert-type scale from 1 = “Never” to 5 = “Almost Always”. Similarly, the instrument presented a good internal consistency of.73 for this study. Please see appendix S1 Table for a full questionnaire.
Procedure
The CAPI (Computer-assisted personal interviewing) method was used for data collection, the surveys were submitted online through the virtual platform Zohosurvey and were administered by 4 interviewers trained for this purpose. Before collecting the main sample, a pilot study of n = 62 participants was carried out in order to validate the content of the instruments. Afterwards, face-to-face interviews were conducted in Cusco and Lima, the average time for each interview was 25 minutes.
Data analysis
The data presented a non-normal distribution (Please see appendix S1 Fig). Spearman’s Rho test was applied for correlation analysis. Likewise, the mean and standard deviation were extracted for descriptive analysis. For the hierarchical multiple regression analysis, 4 models were postulated, in which the Beta coefficient was considered to compare the magnitude of the influence of the independent variables on the dependent variable; the R2 to evaluate how well each of the models predicts the values of the dependent variable; the adjusted R2 to evaluate the predictive capacity of the proposed models considering their complexity; and the F change value to evaluate the interactions between the variables. All the analyses were performed in the RStudio software version 4.3.1 [35], with its different statistical packages.
Results
Descriptive results
Table 1 shows the results of the perception of the effects of air pollution on health. Most of the participants report a high concern for their health (96.8%) between occasionally, frequently and always. 95.6% feel the need to wash their hands and face occasionally, frequently and always; 95.1% used to ventilate their homes, 92.3% reported that the sky has become more cloudy in recent days, 91% indicated that lately they tend to drink more water than before, 88.8% prefer to stay at home instead of going outside, 89.1% of the respondents perceive that their quality of life is degrading and notice that the curtains are dirty lately due to air pollution, and 89.5% of the participants report that they feel an unpleasant smell when going outside or in the street. On the other hand, in relation to health symptoms, the participants indicate that they present them occasionally, frequently and always, being these: red eyes (62.5%), sneezing (83.4%), throat cough (61.6%), dry cough (69.7%), breathing difficulties (54.1%) and 66.1% nose irritation. In general, most of the participants perceive air pollution as a high risk to their health, reflecting a great concern about it.
Table 2 shows the results of the perception of green areas. 73% of the participants consider that green areas play an important role in mitigating high temperatures in summer and/or sunny days. 74% of the participants refer that green areas contribute to the reduction of air pollution, from a regular to quite a lot. 81% consider that green areas play an important role in improving the visual appearance of the area. Approximately 75% say that green areas contribute significantly to the recreation of visitors and that they are a refuge for animals and plants. Finally, 63% consider that green areas help to alleviate traffic noise. In this sense, the vast majority of participants perceive green areas positively, highlighting their importance for life.
Table 3 shows the results regarding trust in scientists. A total of 67.9% of the participants maintain that scientists are intelligent. 55.7% reported that most scientists are prepared to develop high quality research and that they are experts in their work. 44.4% consider that scientists are interested in improving people’s lives, and 38.5% indicate that they are also concerned about people’s well-being. 35% of the participants consider that scientists are honest, that they pay attention to the opinion of society and that they are considerate of people’s interests. On the other hand, 29.3% indicate that scientists are not honest, 32% consider that they do not pay attention to the opinion of others, and 26.2% perceive scientists to be inconsiderate of the interests of the population. Next, participants reported 37.3% that scientists are ethical and 34.5% consider them to be sincere. Thirty-three point two percent indicate that scientists are willing to be transparent, however, 29% report the opposite, i.e., they claim that they are not transparent, 31.2% of the participants consider that scientists are open to constructive criticism, while a higher percentage (36%) indicate the opposite. Overall, a regular percentage of participants reported that they trust scientists, while a relatively lower percentage reflected distrust in the activities carried out by scientists.
Table 4 shows the results of climate anxiety. 57.2% of the participants report having difficulty concentrating and sleeping when they think about climate change and its possible future consequences; occasionally, almost always and always. 46.3% indicate that their concerns about climate change interfere with their ability to carry out work and/or academic activities. 48.9% say that their concerns about climate change make it difficult to have fun with friends and/or family occasionally, almost always and always. Finally, 30.3% report that they cry or are made to cry by the thought of climate change and its possible future consequences, while the rest of the percentage indicate the opposite. Therefore, the item that is most striking is the presence of difficulties in sleeping and concentrating when thinking about climate change, which is evidence of the existence of climate anxiety in the participants. Overall, a considerable percentage of the participants experience at some point in their lives symptoms of anxiety related to climate change.
Correlation analysis
Table 5 shows significant positive correlations for most of the variables. Perception of Air Pollution on Health (PAPH) is positively related to Perception of green areas at r = .19**, meaning that a higher perception of health risk from air pollution is associated with a positive perception of green areas. Likewise, PAPH is related to climate anxiety positively and at a moderate intensity (r = .48**), indicating that a greater perception of air pollution for health is associated with greater climate anxiety. On the other hand, the perception of green areas is positively correlated with trust in scientists (r = .24**), evidencing that the greater the perception and valuation of green areas, the greater the trust in people dedicated to science. Similarly, there is a significant positive correlation between the perception of green areas and climate anxiety (r = .18**), indicating that a higher valuation and perception of green areas is associated with climate anxiety, reflecting the association between the importance of green areas and concern about climate change.
On the other hand, a non-significant negative correlation was observed between perception of air pollution for health and confidence in science (r = -.04), and a non-significant weak correlation between confidence in science and climate anxiety (r = .04).
Predictive analysis
Table 6 shows the hierarchical multiple regression analysis between the variables, with the perception of the effects of air pollution on health (PAPH) as the predicted or dependent variable. Model 1 shows the sociodemographic variables, with gender, age and educational level being significant predictors, explaining 5% of the variance in PAPH (p < 0.001, Adj. R2 = 0.05). In other words, being female, older and having a higher level of education is associated with a greater perception of the health risks of air pollution.
Model 2 assesses whether the perception of green areas explains any variation in PAPH in addition to sociodemographic variables. The perception of green areas is a significant predictor of PAPH, explaining 8% of its variance (F-change = 33.2, p < 0.001, Adj. R2 = 0.078). Therefore, when people perceive green spaces such as parks or wooded areas as important, they also perceive air pollution as posing a greater risk to health.
On the other hand, model 3 explored the influence of trust in scientists on PAPH beyond sociodemographic variables and the perception of green areas, significantly explaining 8% of the variance in PAPH (F-change = 9.8, p < 0.01, Adj. R2 = 0.085), indicating that greater trust in scientists is associated with a greater perception of the health risk of air pollution.
Finally, model 4 explored the explanatory power of climate anxiety on PAPH in addition to sociodemographic factors, perception of green areas, and trust in scientists, finding that it significantly predicts 26% of the variance in PAPH (F-change 254.9, p < 0.001, Adj. R2 = 0.259). Furthermore, climate anxiety independently predicts PAPH by 43%. Consequently, model 4 presents the highest prediction index of the perception of air pollution risk to health, with climate anxiety being the strongest predictor of PAPH.
Discussion
The objective of this study was aimed at analyzing the impact of the perception of green areas, trust in scientists, climate anxiety, and sociodemographic factors such as gender, age, political orientation, and educational level, using the variable perception of the effects of air pollution on health as a criterion. A sample of residents of populated hills in two representative cities in Peru was used, and the present study validated the predictive and explanatory power of the model. It is important to highlight the scarcity of this type of study in developing countries that focus on air pollution and its effects on health, especially in vulnerable populations such as Peru [37].
Sociodemographic
Most sociodemographic factors were found to be significant predictors, such as gender, age, and educational level. Older women with higher educational levels were associated with a greater perception of the health risks of air pollution, which is consistent with previous studies [38]. However, other studies reported that young populations are the most sensitive in environments exposed to air pollution and its implications for physical and mental health [14,17]. Furthermore, educational level was found to be a significant predictor, implying that a person with a higher educational level is more aware of air pollutants and their relationship to symptoms such as red eyes, sneezing, throat cough, dry cough, breathing difficulties, and nose irritation. These results are consistent with those of [17]. Therefore, one would expect them to be more willing to support health policies [20]. and to have greater confidence in scientists [21,22]. Although political orientation is considered a strong predictor in environmental studies [20,23], this factor is not relevant in our study.
Perception of green spaces
As we know, there are few studies on the perception of green spaces and air pollution in Latin American countries [39]. Our study reported that the perception of green areas is a significant predictor of PAPH. People who perceive green spaces such as parks or wooded areas as important also perceive air pollution as a greater risk to health. Previous studies have reported similar findings [3]. Participants expressed high levels of concern about air pollution and health. They perceived that green areas help mitigate high temperatures on sunny days, reduce air pollution, aid in recreation, improve the visual appearance of the area, alleviate traffic noise, and provide a refuge for animals and plants. These findings coincide with [17], who reported a positive perception of green areas among their participants. They are also consistent with the findings of [16], who found that green areas are perceived as spaces for recreation and socialization. Along the same lines, [40] reported that the creation and management of green spaces should be based on the needs of users, as an important source of well-being. However, in countries such as Peru, many of these spaces are excluded and used for other purposes.
Trust in scientists
There is increasing attention on trust in scientists because public perceptions largely determine the assessment of air pollution risks, which in turn influences how people interpret environmental data and recommendations [24,41]. In the present study, trust in scientists was found to be a significant predictor of PAPH, with people who have greater trust in scientists having a higher perception of the health risks of air pollution. These findings are consistent with the studies by Liu and collaborators [42]. Participants showed trust in scientists’ activities such as intelligence, preparedness, interest in improving life, honesty, ethics, sincerity and transparency. These results are consistent with Lidskog [43], as a higher level of trust leads to a more objective perception of air quality and associated health risks. On the contrary, it is striking that some express negative opinions about scientists, particularly their lack of consideration for the interests of the population and lack of transparency. Lack of trust in the data and communication generated by science often translates into public resistance to supporting programmes or policies that address the health consequences of air pollution [38,44]. Furthermore, lack of trust in science is influenced by conspiracy theories, as these undermine support for the work of scientists and the promotion of policies [45,46]. Therefore, there is no doubt that trust in science is relevant because it helps bridge the gaps between public concerns about the health risks of air pollution and the proposal of effective programmes [25].
Climate anxiety
While traditional studies support the importance of cognitive factors as predictors of risk perception of environmental problems such as air pollution, minimizing the role of emotions [47,48], the present study found that the emotional factor of climate anxiety is the most important predictor of PAPH. In other words, people with higher levels of climate anxiety tend to show greater sensitivity to air pollution and its effects on health. These results are consistent with those of Reese [49] and Yang [50], who found that a greater perception of environmental risks correlates with greater climate anxiety, thereby influencing how people assess the risks of air pollution. In our study, participants reported having difficulty concentrating and sleeping when thinking about PAPH. In addition, they reported interference with their ability to perform work and/or academic activities, difficulty enjoying themselves with friends and/or family, and the urge to cry. These findings are consistent with several studies [27,51–53]. Moreover, reported high levels of climate anxiety in his study, with women being more prevalent. It is important to note that the presence of climate anxiety could positively influence adaptation and mitigation measures because it is associated with adaptive behaviors in environmental risk scenarios [54] and is a powerful predictor of interest in environmental sustainability [55]. It is important to note in our study that climate anxiety and the perception of the effects of air pollution on health are moderated by the perception of green spaces and trust in scientists.
Implications for risk communication policies
This study has integrated variables such as perception of green spaces, trust in scientists, climate anxiety, and perception of the effects of air pollution on health, thus providing valuable input for strengthening risk communication programmes and policy plans, promoting trust in scientists, and encouraging health programmes, especially in vulnerable populations [56]. In fact, studies show that when people have access to green spaces, they can cushion the psychological impacts of urban stressors such as climate anxiety and the effects of air pollution on health, and guide policy support that promotes protective behaviors [17,57]. On this basis, local and national decision-makers could implement communication plans and mitigation and adaptation strategies, taking into account the public perceptions and their predictors evidenced in this study, such as the emotional factors that can help build policies tailored to the needs of a population [30], and encourage public support for the promotion of mitigation actions and sustainable lifestyles [31]. Along the same lines, trust in scientists is a factor that influences the perception of air pollution and promotes support for environmental policies [58]. This is very relevant to include in future science communication plans because scientific consensus is being questioned by communities that are exposed to fake news or have experienced environmental injustice. Trust deficits in science can undermine the effectiveness of communication strategies and reinforce scepticism and the spread of conspiracy theories that negatively impact physical and mental health [23,59]. As observed in the present study, climate anxiety can increase the relevance of the perception of air pollution and its effects on health and, consequently, increase the perception of personal and social health risks [29]. On the other hand, inaction by politicians and decision-makers could encourage maladaptive outcomes, such as a lack of trust in science and rejection of mitigation or adaptation proposals or programmes [60].
Overall, explaining the interaction of these factors emphasizes the need to promote the design of effective communication policies and plans that must be evidence-based in the first place, but should not neglect qualitative studies that can give a better understanding of how people feel or express their ideas in these contexts. This approach to communication policies is essential to promote the engagement of people and communities to support resilience policies and thus have an effective way to address this major threat of air pollution and its health effects.
Supporting information
S1 Fig. Graphical assessment of normality in study variables.
https://doi.org/10.1371/journal.pclm.0000683.s002
(DOCX)
S1 Checklist. Inclusivity in global research.
https://doi.org/10.1371/journal.pclm.0000683.s003
(DOCX)
Acknowledgments
We would like to thank Sharoom Echegaray, Youri Villanueva, Danicka Castillo, Frederick Cesar Mamani, Cristian Giovanni Oyola, Maria Fernanda Delgado, Sheyla Machacca, Gabriela Olivares, Miriam Hefzi Ba Mamani, Edu Ojeda Carpio, and Juan Mejía for providing additional support and perspective on our study. Finally, thank you to all the participants for sharing your time.
References
- 1.
World Health Organization. Mental health and climate change: policy brief [Internet]. Geneva: World Health Organization; 2022 [cited 2025 Jun 9]. Available from: https://www.who.int/publications/i/item/9789240045125
- 2. Hoffmann B, Boogaard H, de Nazelle A, Andersen ZJ, Abramson M, Brauer M, et al. WHO air quality guidelines 2021-aiming for healthier air for all: a joint statement by medical, public health, scientific societies and patient representative organisations. Int J Public Health. 2021;66:1604465. pmid:34630006
- 3. Romero Placeres M, Francisca Diego Olite L, Álvarez Toste D. Revisión bibliográfica: La contaminación del aire, su repercusión como problema de salud. Rev Cubana Hig Epidemiol. 2006;44(2). Available from: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1561-30032006000200008
- 4. Serio L, Puccetti C, Oderigo J. Revisión de los monitoreos de calidad del aire en la Ciudad de Buenos Aires = Review of air quality monitoring in the City of Buenos Aires. Rev Fac Agron UBA. 2020;40(1). Available from: http://agronomiayambiente.agro.uba.ar/index.php/AyA/article/view/128
- 5. Ubilla C, Yohannessen K. Contaminación atmosférica: efectos en la salud respiratoria en el niño. Rev Med Clin Condes. 2017;28(1):111–8.
- 6. Ballester Díez F, Tenías JM, Pérez-Hoyos S. Efectos de la contaminación atmosférica sobre la salud: una introducción. Rev Esp Salud Publica. 1999;73(2):109–21.
- 7. Marin T. Quantitative analysis of environmental indicators in South American countries for 2020: trends and associations. Rev Cient Estelí, Medio Ambiente, Tecnología y Desarrollo Humano. 2024;13(51):167–81.
- 8.
IQAir. Los países más contaminados del mundo en 2024: clasificación de PM2.5 [Internet]; 2024 [cited 2025 Jun 4]. Available from: https://www.iqair.com/world-most-polluted-countries
- 9. Warthon Olarte BS, Zamalloa Ponce de Leon AI, Warthon Ascarza JL, Miranda Hankgo IC, Quispe Ccolque IR, Ramos Salcedo VF. Evaluación de la contaminación del aire por material particulado PM2.5 en la ciudad del Cusco respecto de los índices de calidad del aire entre 2017 y 2018. Ambiente Comp Soc. 2024;6(1):1–15.
- 10.
IQAir. Air quality in Cusco [Internet]; 2025 [cited 2025 Jun 3]. Available from: https://www.iqair.com/peru/cusco/cusco
- 11. Przybysz A, Popek R, Stankiewicz-Kosyl M, Zhu CY, Małecka-Przybysz M, Maulidyawati T, et al. Where trees cannot grow - Particulate matter accumulation by urban meadows. Sci Total Environ. 2021;785:147310. pmid:33932673
- 12. Sokhi RS, et al. Advances in air quality research – current and emerging challenges. Atmos Chem Phys. 2022;22:4615–703.
- 13. Vos PEJ, Maiheu B, Vankerkom J, Janssen S. Improving local air quality in cities: to tree or not to tree? Environ Pollut. 2013;183:113–22. pmid:23194646
- 14. Xu H, Jia Y, Sun Z, Su J, Liu QS, Zhou Q, et al. Environmental pollution, a hidden culprit for health issues. Eco Environ Health. 2022;1(1):31–45. pmid:38078200
- 15. Tvinnereim E, Liu X, Jamelske EM. Public perceptions of air pollution and climate change: different manifestations, similar causes, and concerns. Clim Change. 2016;140(3–4):399–412.
- 16. Kweon BS, Sullivan WC, Wiley AR. Green common spaces and the social integration of inner-city older adults. Environ Behav. 1998;30(6):832–58.
- 17. Lafortezza R, Carrus G, Sanesi G, Davies C. Benefits and well-being perceived by people visiting green spaces in periods of heat stress. Urban For Urban Green. 2009;8(2):97–108.
- 18. Hartig T, Mitchell R, De Vries S, Frumkin H. Nature and health. Annu Rev Public Health. 2014;35(1):207–28.
- 19.
Pretty J, Griffin M, Sellens M, Pretty C. Green exercise: complementary roles of nature, exercise and diet in physical and emotional well-being and implications for public health policy [Internet]; 2003 [cited 2025 Jun 3]. Available from: https://www.scirp.org/reference/referencespapers?referenceid=3565535
- 20. Huang L, Wu Z, Kang N. Study on the correlation between perception and utilization of green spaces in residential areas and residents’ self-rated health under different vegetation coverage rates: a case study from the central city of Beijing. Sustainability. 2025;17(8):3751.
- 21. Intemann K. Science communication and public trust in science. Interdiscip Sci Rev. 2023;48(2):350–65.
- 22. Siegrist M. Trust and risk perception: a critical review of the literature. Risk Anal. 2021;41(3):480–90. pmid:31046144
- 23. Gauchat G. The cultural authority of science: public trust and acceptance of organized science. Public Underst Sci. 2011;20(6):751–70. pmid:22397083
- 24. Cologna V, Mede NG, Berger S, Besley J, Brick C, Joubert M, et al. Trust in scientists and their role in society across 68 countries. Nat Hum Behav. 2025;9(4):713–30. pmid:39833424
- 25. Mede NG, Cologna V, Berger S, Besley J, Brick C, Joubert M, et al. Perceptions of science, science communication, and climate change attitudes in 68 countries - the TISP dataset. Sci Data. 2025;12(1):114. pmid:39833242
- 26.
Lofstedt RE. Risk management in post-trust societies. Abingdon: Routledge; 2012. Available from: https://www.routledge.com/Risk-Management-in-Post-Trust-Societies/Lofstedt/p/book/9781844077021?srsltid=AfmBOoq66UFJEE6dQM-9wbsW1lkvgZRXs7LPGHgzreAd5nexjU-Jedpo
- 27.
Poushter J, Huang C. Climate change still seen as the top global threat, but cyberattacks a rising concern [Internet]. Pew Research Center; 2019 [cited 2025 Jun 9]. Available from: https://www.pewresearch.org
- 28. Sri A, Bhugra D, Persaud A, Tribe R, Gnanapragasam S, Castaldelli-Maia JM, et al. Global mental health and climate change: a geo-psychiatry perspectiv. Asian J Psychiatr. 2023;84:103562. pmid:37030088
- 29. Clayton S. Climate anxiety: psychological responses to climate change. J Anxiety Disord. 2020;74:102263. pmid:32623280
- 30. Catalán-Vázquez M, Riojas-Rodríguez H, Jarillo-Soto EC, Sociol E, Delgadillo-Gutiérrez J. Percepción de riesgo a la salud por contaminación del aire en adolescentes de la Ciudad de México. Salud Pública Méx. 2009;51(2). Available from: https://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S0036-36342009000200011
- 31. Mata F, Jesus MS, Cano-Díaz C, Dos-Santos M. European citizens’ worries and self-responsibility towards climate change. Sustainability. 2023;15(8):6862.
- 32. Deguen S, Ségala C, Pédrono G, Mesbah M. A new air quality perception scale for global assessment of air pollution health effects. Risk Anal. 2012;32(12):2043–54. pmid:22852801
- 33. Kothencz G, Kolcsár R, Cabrera-Barona P, Szilassi P. Urban green space perception and its contribution to well-being. Int J Environ Res Public Health. 2017;14(7):766. pmid:28704969
- 34. Wu J, Long D, Hafez N, Maloney J, Lim Y, Samji H. Development and validation of a youth climate anxiety scale for the Youth Development Instrument survey. Int J Ment Health Nurs. 2023;32(6):1473–83. pmid:37605318
- 35.
R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available from: https://www.r-project.org/
- 36. Cumming G. The new statistics: why and how. Psychol Sci. 2014;25(1):7–29. pmid:24220629
- 37. Elshirbiny H, Abrahamse W. Public risk perception of climate change in Egypt: a mixed methods study of predictors and implications. J Environ Stud Sci. 2020;10(3):242–54.
- 38. Yang H, Huang X, Westervelt DM, Horowitz L, Peng W. Socio-demographic factors shaping the future global health burden from air pollution. Nat Sustain. 2023;6(1):58–68.
- 39. Cardinali M, Beenackers MA, van Timmeren A, Pottgiesser U. Urban green spaces, self-rated air pollution and health: a sensitivity analysis of green space characteristics and proximity in four European cities. Health Place. 2024;89:103300. pmid:38924920
- 40. Jim CY, Chen WY. Perception and attitude of residents toward urban green spaces in Guangzhou (China). Environ Manage. 2006;38(3):338–49. pmid:16752045
- 41. Algan Y, Cohen D, Davoine E, Foucault M, Stantcheva S. Trust in scientists in times of pandemic: panel evidence from 12 countries. Proc Natl Acad Sci U S A. 2021;118(40):e2108576118. pmid:34580225
- 42. Liu X, Ding T, Zhang Y, Vedlitz A. Tainted trust: air pollution and political trust in China. Environ Polit. 2025;34(2):299–319.
- 43. Lidskog R. In science we trust? On the relation between scientific knowledge, risk consciousness and public trust. Acta Sociol. 1996;39(1):31–56.
- 44. Fairbrother M. Trust and public support for environmental protection in diverse national contexts. Sociol Sci. 2016;3:17.
- 45. Biddlestone M, Azevedo F, van der Linden S. Climate of conspiracy: a meta-analysis of the consequences of belief in conspiracy theories about climate change. Curr Opin Psychol. 2022;46:101390. pmid:35802986
- 46. Cvitanovic C, Shellock RJ, Mackay M, van Putten EI, Karcher DB, Dickey-Collas M, et al. Strategies for building and managing ‘trust’ to enable knowledge exchange at the interface of environmental science and policy. Environ Sci Policy. 2021;123:179–89.
- 47. Slovic P. Perception of risk. Science. 1987;236(4799):280–5. pmid:3563507
- 48. Cori L, Donzelli G, Gorini F, Bianchi F, Curzio O. Risk perception of air pollution: a systematic review focused on particulate matter exposure. Int J Environ Res Public Health. 2020;17(17):6424. pmid:32899325
- 49. Reese G, Rueff M, Wullenkord MC. No risk, no fun…ctioning? Perceived climate risks, but not nature connectedness or self-efficacy predict climate anxiety. Front Clim. 2023;5:1158451.
- 50. Yang G, Zuo Y, Cheng H, Zhang L. How environmental perception influence depression and anxiety: the mediating role of social interaction. BMC Public Health. 2025;25(1):1216. pmid:40165168
- 51. Jalin H, Chandès C, Boudoukha AH, Jacob A, Poinsot R, Congard A. Better understanding eco-anxiety: creation and validation of EMEA scale. Eur Rev Appl Psychol. 2025;75(1):101010.
- 52. Van der Linden S. Determinants and measurement of climate change risk perception, worry, and concern. SSRN Electron J. 2017:2–53.
- 53. Hogg TL, Stanley SK, O’Brien LV. Synthesising psychometric evidence for the Climate Anxiety Scale and Hogg Eco-Anxiety Scale. J Environ Psychol. 2023;88:102003.
- 54. Arya B, Kumar H. An investigation of climate change, eco-anxiety and risk perception in the context of theory of planned behaviour. IOP Conf Ser: Earth Environ Sci. 2023;1279(1):012020.
- 55. Chung SJ, Jang SJ, Lee H. Eco-anxiety and environmental sustainability interest: a secondary data analysis. Int J Ment Health Nurs. 2023;32(6):1462–72. pmid:37021349
- 56. Coronel J, Marzo N. La promoción de salud para creación de entornos saludables en América Latina. Medisa. 2017:3415–23. Available from: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1029-30192017001200016
- 57. Markevych I, Schoierer J, Hartig T, Chudnovsky A, Hystad P, Dzhambov AM, et al. Exploring pathways linking greenspace to health: theoretical and methodological guidance. Environ Res. 2017;158:301–17. pmid:28672128
- 58. Siegrist M, Zingg A. The role of public trust during pandemics: implications for crisis communication. Eur Psychol. 2014;19(1):23–32.
- 59. Yang X. The influence of trust on the public’s environmental risk perception: evidence from China. Local Environ. 2023;28(6):728–38.
- 60. Riley R, de Preux L, Capella P, Mejia C, Kajikawa Y, de Nazelle A. How do we effectively communicate air pollution to change public attitudes and behaviours? A review. Sustain Sci. 2021;16(6):2027–47.