179 GeoPlanning Journal of Geomatics and Planning Vol. 10, No. 2, 2023 Planning Perspective Sonic Justice and Tree Equity: Exploring Spatial Correlations between Aviation-Related Noise, Demographics, and Tree Canopy Mayra I. Rodriguez-González1,2*, Kevin G. Torres-Garrido3 1. Hartford County Extension Center, University of Connecticut, Farmington, Connecticut, USA 2. Research on Resilient Cities, Racism and Equity, University of Connecticut in Hartford, Hartford, Connecticut, USA 3. Independent Researcher, former fellow of the Secretaría de Educación Superior, Ciencia, Tecnología e Innovación, Quito, Ecuador DOI: 10.14710/geoplanning.10.2.179-184 Abstract The intricate relationship between aviation-related noise pollution, demographic factors, and tree canopy cover can hold significant implications for targeted interventions promoting environmental equity, sonic justice, and sustainable urban development. This study offers a geospatial exploration of these interconnections within the continental United States by employing National Transportation Noise Pollution data from the United States Department of Transportation alongside tree canopy cover from the United States Geological Survey’s National Land Cover Database and demographic data from the American Community Survey in a correlation analysis. Our analysis reveals stark disparities in noise exposure levels, notably underscoring that low-income and predominantly Hispanic neighborhood shoulder a disproportionate burden of aviation-related noise. Moreover, a correlation between aviation-related noise pollution and low tree canopy cover suggests a potential avenue for utilizing nature as a buffer against heightened noise levels. However, recognizing the delicate equilibrium between fostering a thriving tree canopy and ensuring aviation safety highlights a need for innovative urban planning solutions capable of simultaneously addressing sonic injustice and tree inequity. Copyright © 2023 GJGP-Undip This open access article is distributed under a Creative Commons Attribution (CC-BY-NC-SA) 4.0 International license 1. Introduction Aviation-related noise pollution is a concerning issue. The sound of jet engines and of aircraft taking off and landing can cause elevated noise levels that disturb wildlife habitats and ecosystems (Alquezar & Macedo, 2019). However, the impacts of excessive aviation-related noise are not just felt by local ecosystems. Nearby human communities can also suffer from detrimental health impacts due to heightened exposure (Basner et al., 2017). The impacts of noise pollution on human health have been extensively documented. Individuals living near airports can suffer from disturbed sleep patterns, heightened stress levels, impaired cognitive function, and increased risks of cardiovascular disease and elevated blood pressure (Basner et al., 2017; Kaltenbach et al., 2008). Disadvantaged communities, such as those mostly comprised by racial and ethnic minority groups and low- income residents, experience a disproportionate share of noise-exposure impacts, which can be exacerbated by challenges in healthcare access and housing mobility (Collins et al., 2020; Penman-Aguilar, 2016). In the United States, health inequity is tied to race, ethnicity and income, among other variables. Discriminatory policies and limited financial opportunity relate to high rates of chronic diseases and low life expectancy among historically marginalized populations (Penman-Aguilar, 2016). However, nature can play an important role in reducing these health issues, and, thus, increasing the quality of life of disadvantaged communities. e-ISSN: 2355-6544 Received: 01 November 2023; Accepted: 28 December 2023; Published: 29 December 2023. Keywords: Noise Pollution, Sonic Justice, Tree Equity, Spatial Correlation *Corresponding author(s) email: rodriguezgmayrai@gmail.com https://doi.org/10.14710/geoplanning.10.2.179-184 mailto:rodriguezgmayrai@gmail.com Rodriguez-González and Torres-Garrido. / Geoplanning: Journal of Geomatics and Planning, Vol 10, No 2, 2023, 179-184 DOI: 10.14710/geoplanning.10.2.179-184 180 Nature, with its numerous benefits, plays a vital role in promoting positive mental and physical health by acting as a buffer against noise (Ow & Ghosh, 2017). Trees can play a crucial role in reducing noise pollution through their dense foliage, including leaves, branches and trunks, which act as natural barriers that absorb and deflect sound waves. However, the distribution of trees is often unequal, a phenomenon known as tree inequity, leading to disparities in tree canopy cover, especially in urban areas (Riley & Gardiner, 2020). This inequality disproportionately affects low-income neighborhoods and communities of color, exacerbating environmental disparities and potentially leaving residents in these areas more susceptible to the adverse effects of noise pollution (Riley & Gardiner, 2020). Consequently, urban greening not only promotes overall urban well-being but also addresses sonic injustice (i.e., the disproportionate exposure of disadvantaged communities, such as low- income residents and racial and ethnic minorities) to noise pollution (Collins et al., 2020). While studies have established that socioeconomically vulnerable groups face heightened exposure to noise pollution, further research is necessary to comprehensively understand the specific contributions of various noise sources, such as aviation-related noise, to these disparities (Collins et al., 2020; Trudeau et al., 2023). Additionally, if considering trees as a nature-based solution to combat noise, it is essential to grasp the interconnected dynamics between tree canopy cover, distinct noise sources, and demographic factors including income, race, and ethnicity. To our knowledge, no study has assessed the combined relationship between aviation-related noise, tree canopy cover, and population demographics. Thus, this study aims to assess the spatial correlation between aviation-related noise pollution, tree canopy cover, income, race and ethnicity to gain a better understanding of the relationships between these variables altogether. Through a spatial analysis, we answered the following question: Is there a significant correlation between aviation-related noise pollution, tree canopy cover, and the income, race and ethnicity of residents living near airports? We hypothesized a positive significant relationship between high aviation-related noise pollution, low tree canopy cover, and high percentages of low-income residents and racial and ethnic minorities. 2. Data and Methods This study accounts for all areas within the continental United States that have documented aviation- related noise pollution. Using ArcGIS Pro (Esri, 2023), we performed zone-based summary statistics to estimate mean exposure to aviation-related noise pollution (in decibels) by census block group, the smallest census denomination for the United States. Isolated values of aviation-related noise pollution were downloaded from the Department of Transportation’s National Transportation Noise Pollution public database (United States Department of Transportation – Bureau of Transportation Statistics, 2022) (refer to Table 1 for data details). Table 1. Data Inputs and Sources. Description Data Type Year Origin Download Source National Transportation Noise Pollution (aviation-related noise only) Raster 2020 Department of Transportation United States Department of Transportation – Bureau of Transportation Statistics, 2022 National Land Cover Database Tree Canopy Cover Raster 2020 United States Forest Service United States Geological Survey, 2023 Demographic variables (median household income, population by race, and population with Hispanic origin) Tabular 2017- 2021 American Community Survey 5-Year Data Release Manson et al., 2023a Census Block Groups Polygon (Shapefile) 2020 United States Census Bureau Manson et al., 2023b https://doi.org/10.14710/geoplanning.10.2.179-184 https://www.bts.gov/geospatial/national-transportation-noise-map https://www.bts.gov/geospatial/national-transportation-noise-map https://www.bts.gov/geospatial/national-transportation-noise-map https://www.bts.gov/geospatial/national-transportation-noise-map https://www.mrlc.gov/data/type/tree-canopy https://www.mrlc.gov/data/type/tree-canopy http://doi.org/10.18128/D050.V18.0 http://doi.org/10.18128/D050.V18.0 Rodriguez-González and Torres-Garrido. / Geoplanning: Journal of Geomatics and Planning, Vol 10, No 2, 2023, 179-184 DOI: 10.14710/geoplanning.10.2.179-184 181 A boundary layer for census block groups was downloaded from the open-data website IPUMS National Historical Geographic Information System (Manson et al., 2023a). In ArcGIS Pro, we also performed zone-based summary statistics of tree canopy cover to determine percent per census block group (United States Geological Survey, 2023). Mean aviation-related noise pollution and percent tree canopy were imported along with three demographic variables from the United States American Community Survey (2017-2021), median household income, percent of individuals not white, and percent of Hispanic or Latine individuals (Manson et al., 2023b), into the R statistical language (R Core Team, 2021) to perform a Pearson correlation test between all variables. Demographic data was preprocessed using Microsoft Excel (Microsoft Corporation, 2023). A detailed workflow diagram of our methodology is provided in Figure 1. Data inputs are listed in Table 1. Source: Adapted from Esri, 2023 Figure 1. Processing and Analytical Workflow 3. Result and Discussion 3.1. Sonic Justice The analysis of aviation-related noise pollution in relation to the demographic variables (median household income, percent not white, and percent Hispanic or Latine) revealed that lower-income neighborhoods exhibit higher levels of exposure in noise-polluted areas (Figure 3). Furthermore, despite there being an apparent negative correlation between high levels of aviation-related noise pollution and high percentages of non-white residents, we observed that aviation-related noise pollution also correlates positively with the percent of Hispanic residents (Figure 3). The analysis of aviation-related noise pollution in relation to tree canopy revealed a significant negative correlation between the two (Figure 2 and 3). Areas with reduced tree canopy cover experience higher aviation- related noise pollution levels. Greater percentages of Hispanics correlated with both lower income and less tree canopy access (Figure 3). Thus, lower-income Hispanics are particularly exposed to greater levels of aviation- related noise while simultaneously lacking access to tree canopy cover. https://doi.org/10.14710/geoplanning.10.2.179-184 http://doi.org/10.18128/D050.V18.0 Rodriguez-González and Torres-Garrido. / Geoplanning: Journal of Geomatics and Planning, Vol 10, No 2, 2023, 179-184 DOI: 10.14710/geoplanning.10.2.179-184 182 (a) (b) Source: National Atlas of the United States, 2014; United States Department of Transportation – Bureau of Transportation Statistics, 2022; United States Geological Survey, 2023 Figure 2. (a) Aviation-related Noise Pollution, and (b) Tree Canopy Cover in relation to Airports (for reference purposes) Figure 3. Variable distributions (on the diagonal), bivariate plots with fitted lines (below the diagonal), and correlation values with significance levels represented by asterisks (above the diagonal) for percent tree canopy (“canopy”), mean aviation-related noise pollution (“noise”), median household income (“income”), percent of residents not white (“not white”), and percent of residents who identify as Hispanic or Latine (“Hispanic”). 3.2. Discussion Our study provided valuable insights into the relationships between aviation-related noise pollution, demographic factors, and tree canopy cover across the continental United States at the census block-group level. The analysis revealed the existence of disparities, as block groups that are predominantly low-income and Hispanic disproportionately bear the greatest burden of aviation-related noise pollution while exhibiting low https://doi.org/10.14710/geoplanning.10.2.179-184 https://purl.stanford.edu/hh676zz3630 https://www.bts.gov/geospatial/national-transportation-noise-map Rodriguez-González and Torres-Garrido. / Geoplanning: Journal of Geomatics and Planning, Vol 10, No 2, 2023, 179-184 DOI: 10.14710/geoplanning.10.2.179-184 183 tree canopy access. This is consistent with other studies, which have documented the association of disadvantaged communities with greater noise exposure and with low tree canopy access, separately (Collins et al., 2020; Riley & Gardiner, 2020; Trudeau et al., 2023). Although confounding variables are expected, our findings underscore the critical need to understand how intersecting marginalized identities experience multiple environmental challenges simultaneously and unevenly (in this case, being of Hispanic origin and having a lower income level and experiencing both high exposure to aviation-related noise pollution and low tree canopy access. The analysis of aviation-related noise pollution in relation to tree canopy revealed a significant negative correlation between the two, suggesting that tree canopy cover could be used as a mitigation strategy. Other studies have extensively documented the role that trees play in reducing noise pollution (Ow & Ghosh, 2017), even demonstrating how nature can reduce airport noise while promoting many ecosystem services (Korol et al., 2018). Despite the contributions of nature in buffering against noise, the presence of a tall and dense tree canopy also poses a concern to aviation safety due to reduced visibility for pilots and increased bird habitat that could lead to a greater chance of bird strikes (Metz et al., 2020; Mobini & Sabzehparvar, 2022). This juxtaposition highlights a need for establishing best practices that promote vegetation growth without compromising aviation safety. Knowing best practices for aviation safety standards in this context could support the use of nature-based solutions in mitigating aviation-related noise pollution. Our findings suggest that there is a potential for urban forestry interventions to address both noise pollution and tree canopy disparities simultaneously through strategic tree plantings. However, the delicate balance between promoting tree canopy cover and ensuring aviation safety cannot be overlooked. While tall trees contribute positively to noise reduction and overall environmental well-being (Korol et al., 2018; Ow & Ghosh, 2017), they introduce risks for pilots during takeoff and landing (Metz et al., 2020; Mobini & Sabzehparvar, 2022). This translates into a challenge for urban planning that requires further research to explore the application of strategic tree placement and species selection near airports to find a balance between an abundant and equitable tree canopy and aviation safety. 4. Conclusion The goal of our study was to provide key insights into the intricate connections between aviation-related noise pollution, demographic factors, and tree canopy cover to guide interventions for environmental equity, sonic justice, and sustainable urban development. Our analysis highlighted a disproportionate impact on socio- economically vulnerable populations, particularly those of Hispanic origin and with lower income levels. It emphasized the need for nature-centric mitigation strategies, especially in block groups with low income or predominantly Hispanic populations experiencing excessive noise pollution. However, the correlation between higher noise exposure and lower tree canopy also indicated the potential role of nature as a mitigation strategy, prompting further research to identify the delicate balance between promoting sonic justice and ensuring aviation safety. Based on the key insight of this study, we suggest exploring any of the following as means to better capturing the intricate connections between aviation-related noise pollution, demographic factors, and tree canopy cover: (1) Identifying tree species and placement patterns ideal for optimizing tree canopy cover for noise reduction without increasing aviation hazards; (2) Applying temporal analyses to observe the relationship between aviation-related noise pollution, demographic dynamics, and tree canopy cover over time; (3) Assessing mental and physical health impacts from aviation-related noise exposure and tree canopy access for a more holistic understanding of tradeoffs; (4) Assessing the perspectives of residents affected by aviation-related noise to inform community-driven solutions that promote sonic justice and tree equity simultaneously; (5) By exploring these avenues of research, future studies could lead to a comprehensive understanding of the intricate relationships between aviation-related noise, demographics, and tree canopy, guiding the development of effective strategies that balance environmental, social, and safety considerations for sustainable urban development. https://doi.org/10.14710/geoplanning.10.2.179-184 Rodriguez-González and Torres-Garrido. / Geoplanning: Journal of Geomatics and Planning, Vol 10, No 2, 2023, 179-184 DOI: 10.14710/geoplanning.10.2.179-184 184 5. Acknowledgment All data sources and software used, with exception of ArcGIS Pro and Microsoft Excel, are open source and publicly accessible. Access to ArcGIS Pro and Microsoft Excel was obtained through institutional affiliation of the authors. 6. References Alquezar, R. D., & Macedo, R. H. (2019). Airport noise and wildlife conservation: What are we missing?. Perspectives in ecology and conservation, 17(4), 163-171.[Crossref] Basner, M., Clark, C., Hansell, A., Hileman, J. I., Janssen, S., Shepherd, K., & Sparrow, V. (2017). Aviation noise impacts: state of the science. Noise & health, 19(87), 41. [Crossref] Collins, T. W., Nadybal, S., & Grineski, S. E. (2020). Sonic injustice: Disparate residential exposures to transport noise from road and aviation sources in the continental United States. Journal of Transport Geography, 82, 102604. [Crossref] Esri. (2011). ArcGIS Pro 3.1.0. Redlands, CA: Environmental Systems Research Institute. https://pro.arcgis.com Esri. (2023). How zonal statistics tools work. Redlands, CA: Environmental Systems Research Institute. https://doc. arcgis.com/en/arcgis-online/analyze/how-zonal-statistics-works.htm Kaltenbach, M., Maschke, C., & Klinke, R. (2008). Health consequences of aircraft noise. Deutsches Ärzteblatt International, 105(31-32), 548. [Crossref] Korol, E., Shushunova, N., Feoktistova, O., Shushunova, T., & Rubtsov, O. (2018). Technical and economical factors in green roof using to reduce the aircraft noise. In MATEC Web of Conferences 170 (01081). EDP Sciences. [Crossref] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., & Ruggles, S. (2023a). IPUMS National Historical Geographic Information System: Version 18.0 [2020 Census Block Groups – Shapefile]. Minneapolis, MN: IPUMS. [Crossref] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., & Ruggles, S. (2023b). IPUMS National Historical Geographic Information System: Version 18.0 [2017-2021 American Community Survey – Tabular]. Minneapolis, MN: IPUMS. [Crossref] Metz, I. C., Ellerbroek, J., Mühlhausen, T., Kügler, D., & Hoekstra, J. M. (2020). The bird strike challenge. Aerospace, 7(3), 26. [Crossref] Microsoft Corporation. (2023). Microsoft Excel v. 2311. https://office.microsoft.com/excel Mobini, M., & Sabzehparvar, M. (2022). Visual landing based on the human depth perception in limited visibility and failure of avionic systems. Computational Intelligence and Neuroscience, 2022. [Crossref] National Atlas of the United States. (2014). Global Map: Airports of the United States, 2014. National Atlas of the United States. https://purl.stanford.edu/hh676zz3630 Ow, L. F., & Ghosh, S. (2017). Urban cities and road traffic noise: Reduction through vegetation. Applied Acoustics, 120, 15- 20. [Crossref] Penman-Aguilar, A., Talih, M., Huang, D., Moonesinghe, R., Bouye, K., & Beckles, G. (2016). Measurement of health disparities, health inequities, and social determinants of health to support the advancement of health equity. Journal of public health management and practice: JPHMP, 22(Suppl 1), S33. [Crossref] R Core Team. (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org Riley, C. B., & Gardiner, M. M. (2020). Examining the distributional equity of urban tree canopy cover and ecosystem services across United States cities. PLoS One, 15(2), e0228499. [Crossref] Trudeau, C., King, N., & Guastavino, C. (2023). Investigating sonic injustice: A review of published research. Social Science & Medicine, 115919. [Crossref] United States Department of Transportation – Bureau of Transportation Statistics. (2022). National Transportation Noise Map. https://www.bts.gov/geospatial/national-transportation-noise-map United States Geological Survey. (2023). NLCD CONUS 2020 Tree Canopy Cover. v2021-4. https://www.mrlc.gov https://doi.org/10.14710/geoplanning.10.2.179-184 https://doi.org/10.1016/j.pecon.2019.08.003 https://doi.org/10.4103%2Fnah.NAH_104_16 https://doi.org/10.1016/j.jtrangeo.2019.102604 https://pro.arcgis.com/ https://doc.arcgis.com/en/arcgis-online/analyze/how-zonal-statistics-works.htm https://doc.arcgis.com/en/arcgis-online/analyze/how-zonal-statistics-works.htm https://doi.org/10.3238%2Farztebl.2008.0548 https://doi.org/10.1051/matecconf/201817001081 http://doi.org/10.18128/D050.V18.0 http://doi.org/10.18128/D050.V18.0 https://doi.org/10.3390/aerospace7030026 https://office.microsoft.com/excel https://doi.org/10.1155/2022/4320101 https://purl.stanford.edu/hh676zz3630 https://doi.org/10.1016/j.apacoust.2017.01.007 https://doi.org/10.1097%2FPHH.0000000000000373 https://www.r-project.org/ https://doi.org/10.1371/journal.pone.0228499 https://doi.org/10.1016/j.socscimed.2023.115919 https://www.bts.gov/geospatial/national-transportation-noise-map https://www.mrlc.gov/