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Article

The Impacts of Gentrification on Air Pollutant Levels and Child Opportunity Index near New York City Schools

by
Kyung Hwa Jung
1,†,
Zachary Pitkowsky
2,†,
Kira L. Argenio
1,
James W. Quinn
3,
Jeanette A. Stingone
3,
Andrew G. Rundle
3,
Jean-Marie Bruzzese
4,
Steven Chillrud
5,
Matthew Perzanowski
6 and
Stephanie Lovinsky-Desir
1,6,*
1
Division of Pediatric Pulmonology, Department of Pediatrics, College of Physicians and Surgeons, Columbia University, 3959 Broadway, CHC-745, New York, NY 10032, USA
2
Pediatric Residency Program, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Avenue, MLC 5018, Cincinnati, OH 45229, USA
3
Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W. 168 St., New York, NY 10032, USA
4
Columbia University School of Nursing, 560 W. 168 St., New York, NY 10032, USA
5
Lamont-Doherty Earth Observatory, Columbia University, 61 Rt 9W, Palisades, NY 10964, USA
6
Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, 722 W. 168 St., New York, NY 10032, USA
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Environments 2025, 12(6), 199; https://doi.org/10.3390/environments12060199
Submission received: 21 April 2025 / Revised: 3 June 2025 / Accepted: 4 June 2025 / Published: 11 June 2025
(This article belongs to the Special Issue Air Pollution in Urban and Industrial Areas III)
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Abstract

Introduction: Gentrification, commonly defined as low-socioeconomic-status (SES) neighborhoods experiencing rapid increases in rental value, can lead to changes in the built and social neighborhood environment. Schools are an important location for pollutant exposure and child opportunities because children spend significant time in school. Given their central role in both environmental and social contexts, we examined the relationship between gentrification, pollutants, and child opportunity near schools in New York City. Methods: School locations (Ntotal = 1482) were classified into gentrifying (n = 624), non-gentrifying (n = 198), and higher-SES (ineligible for gentrification; n = 660) neighborhoods. Annual average pollutant levels (black carbon (BC), fine particulates (PM2.5), nitrogen dioxide (NO2)) were assessed near schools. Child opportunity index (COI 2.0) was used to evaluate overall opportunity and three domains: education; health/environment; social/economic. Results: On average, pollution was highest in gentrifying neighborhoods compared to non-gentrifying (5–8.6% difference) and higher-SES (4.8–14.8% difference) neighborhoods. Average air pollution levels remained consistently higher in gentrifying neighborhoods both before and after gentrification compared to non-gentrifying and higher-SES neighborhoods. Regarding childhood opportunity, education, and social/economic opportunities were better and health/environment opportunities were worse in gentrifying compared to non-gentrifying neighborhoods. Conclusions: Gentrifying neighborhoods are at risk for higher exposure to pollutants and lower health/environment childhood opportunities compared to other neighborhoods.

1. Introduction

In urban communities like New York City (NYC), school environments contain many sources of ambient pollutants, including traffic-related air pollution (TRAP) [1], since they are frequently located near major roads and truck routes [2]. Additionally, these pollutants are capable of infiltrating indoors [1]. Children typically spend 7–12 h each day in school environments [3], suggesting school settings can be important sources of children’s exposure to TRAP. Furthermore, exposure to pollutants near schools has been linked to airway inflammation among elementary and middle school children [4]. The built environment near schools is influenced by historical factors such as redlining, the discriminatory housing practices from the 1930s [5]. Historical redlining has been associated with higher levels of TRAP, including black carbon (BC), fine particulate matter (PM2.5), and nitrogen dioxide (NO2) near NYC public schools [6,7]). Our previous findings further revealed that the decreasing trend of air pollutants over the last decade was slightly but significantly less apparent in historically redlined neighborhoods, compared to non-redlined neighborhoods [6], suggesting that policy changes to improve air quality do not impact all neighborhoods equitably.
In neighborhoods across the United States (U.S.), exposure to ambient pollutants such as PM2.5 and NO2 is higher in communities with greater proportions of non-white residents compared to majority white communities and amongst residents of lower socioeconomic status (SES) compared to higher-SES neighborhoods [8,9,10]. Gentrification refers to low-SES neighborhoods experiencing rapid increases in rental value that can lead to changes in the built (e.g., green-space) and social (e.g., demographic and economic) environments within a neighborhood that could have unintended consequences. Neighborhoods that undergo gentrification often have lower mean incomes prior to gentrification [11] and are likely to face a high risk of pollution from point sources that were historically concentrated in low income neighborhoods [12]. Gentrification may create greater exposure to pollutants due to rapid changes in demographics, expanding business activity, and changes in mobility patterns. However, there is a gap in knowledge regarding the impacts of gentrification on air pollution exposure, particularly in New York City.
Neighborhood environments play a critical role in shaping child development. Children residing in areas with access to high-quality early childhood education and schools, safe and stable housing, access to healthy nutritious food options, recreational spaces such as parks and playgrounds, and low levels of environmental pollution exposure are more likely to experience better health and developmental outcomes. The Child Opportunity Index (COI) provides a useful method to measure and map neighborhood-level resources and conditions associated with healthy child development. Recent studies have shown that a lower COI was associated with increased mortality, pediatric intensive care unit admission, invasive mechanical ventilation, higher hospital length of stay, and increased hospitalizations for ambulatory care sensitive conditions [13,14].
The objectives of this study were (1) to examine whether air pollutant levels near NYC public schools (i.e., BC, PM2.5, and NO2) differ in gentrifying neighborhoods compared to non-gentrifying and higher-SES neighborhoods and (2) to compare child opportunities within a neighborhood that children need to grow and thrive, assessed by the child opportunity index (COI), by neighborhood gentrification status. We examine both pollutant levels and COI to obtain a multidimensional perspective of the effect of gentrification on children’s environments at school. We hypothesized that (1) NYC schools in gentrifying neighborhoods would have higher air pollutant levels compared to non-gentrifying and higher-SES neighborhoods and (2) child opportunity near NYC schools would differ between gentrifying, non-gentrifying, and higher-SES neighborhoods.

2. Methods

2.1. Study Design

NYC public school information (N = 1941 schools; 2018–2019) was obtained from NYC Open Data [15]. Schools were excluded if they were co-located in the same building as another school (n = 60), were listed as an administrative site only (n = 66), were missing location information (n = 1) or were missing exposure data (n = 332). The remaining school locations (n = 1482) across the five boroughs of NYC were classified into gentrifying (n = 624), non-gentrifying (n = 198), and higher-SES (ineligible for gentrification; n = 660) neighborhoods based on New York University (NYU) Furman Center definitions [16] (Figure 1). Gentrifying neighborhoods were defined as those that were low income in 1990 (below 40% of average NYC household income) and experienced high rental growth between 1990 and 2010–2014 (specifically, rental increases that exceeded the median rental increase in the sub-boroughs). Non-gentrifying neighborhoods were those with low income in 1990 and low rental growth. Higher-SES neighborhoods were in the top 60% of the 1990 average household income, and therefore ineligible for gentrification. The timeline for data sources is included in Figure 2.

2.2. Estimated Air Pollution Levels Based on Land-Use Regression Modeling

Outdoor air pollution data across NYC locations were obtained from the New York City Community Air Survey (NYCCAS) air quality monitoring program. A total of 150 monitoring sites were strategically selected to encompass the diversity of local emission sources, such as traffic and building density, while ensuring spatial representation across NYC [17]. Air pollutant measurements were taken at street level during six separate two-week periods in each season (i.e., winter, spring, summer, and fall) resulting in 48 weeks of distributed monitoring data per year [17]. Land-use regression models were created to estimate annual average pollutant levels across the city [18,19].
Estimated levels of air pollutants (i.e., BC, PM2.5, and NO2) were examined around school locations. The school locations (longitude, latitude) were geocoded to coordinates interpolated along street centerlines. For this analysis, we utilized publicly available Esri grid raster files, containing citywide annual estimates of air pollutants collected between 2009 and 2018, obtained from NYC OpenData [20]. The 300-m raster data were converted into point locations, and point-in-polygon geoprocessing was performed in order to associate the predicted surface grid points to each of the study neighborhood definitions they fell within using Esri ArcGIS Pro (version 2.8x). This process allowed the predicted surface grid points to be averaged within a 250-m buffer around each school location, without assuming a finer level of precision than the original data. We selected a 250 m buffer to represent the immediate environment surrounding each school as an estimate of local sources of pollution, consistent with our previous work [6].

2.3. Child Opportunity Index (COI)

The COI is a composite index measured at the census tract level to capture neighborhood resources and conditions that are important for children’s healthy development [21]. The COI combines 29 variables across three domains of opportunity: (1) education, (2) health and environment, and (3) social and economic. Examples of variables used to create the index include access to quality early childhood education and schools, safe housing, healthy food, air pollution, parks, and playgrounds, etc. The COI 2.0 included data from 2012 to 2017, averaged across the six-year period on a scale of 1–100, with higher scores indicating higher opportunity levels.

2.4. Data Analyses

Analyses were restricted to NYC public schools with a unique District Borough Number (DBN) identifier that had complete estimated air pollutant levels and gentrification status, resulting in a final sample of 1482 schools. Data analysis included summary statistics (e.g., sample means and standard deviations), as well as t-test and ANOVA tests, as appropriate.
Annual average pollutant levels (i.e., BC, PM2.5, and NO2) from 2012 to 2017 were averaged as an indicator of post-gentrification pollution exposure. Percent differences (% Diff) in air pollution levels between gentrifying and comparison groups (i.e., non-gentrifying and higher-SES neighborhoods) were calculated as:
Pollutant   mean   gentrifying − Pollutant   mean   comparison   group Average   of   Pollutant   means   gentrifying   and   comparison   group × 100
A similar analysis was performed for COI where COI mean was substituted for pollutant mean in the formula above. We analyzed the overall COI score as well as the three domain scores (on a scale of 1–100), stratified by gentrification status.
In secondary analysis, to explore trends in air pollution over 10 years post-gentrification we calculated percent decrease in pollutants by subtracting the 2018 pollutant mean from the 2009 pollutant mean and dividing by the average across the two time points. All analyses were performed using SPSS version 29 (Chicago, IL, USA), with statistical significance set at p < 0.05.

3. Results

Violin plots of 2012–2017 average air pollutant levels are presented in Figure 3. The six-year average annual pollutant levels near schools were highest in gentrifying neighborhoods compared to others (Figure 4, BC: 1.09 vs. 1.00 vs. 0.94 m−1 × 10−5, PM2.5: 9.04 vs. 8.66 vs. 8.62 µg/m3, and NO2: 22.3 vs. 20.8 vs. 20.8 ppb for gentrifying vs. non-gentrifying vs. higher SES, respectively; p < 0.05 for all). In general, air pollution exposure near NYC schools in gentrifying neighborhoods, particularly BC, was right-skewed, indicating that a few schools had higher than average pollution exposure. Conversely, pollutant concentrations in non-gentrifying neighborhoods were left-skewed, indicating a few schools experienced lower than average air pollution exposure. In contrast, higher-SES neighborhoods had the widest distribution of pollutant levels, including both the lowest and highest levels across the three pollutants. The percent differences in air pollution between gentrifying and non-gentrifying neighborhoods were 8.6% for BC and 7.0% for NO2, with the smallest difference observed for PM2.5 (% Diff 5.0%) (Figure 3). Comparable percent differences were noted between gentrifying and higher-SES schools (% Diff 14.8% for BC, 4.8% for PM2.5 and 7.0% for NO2) (Figure 3). Significant differences in BC and PM2.5 levels were also observed between non-gentrifying and higher-SES neighborhoods (Figure 3).
Overall COI and domain-specific COIs were also examined by neighborhood gentrification status (Figure 4). Gentrifying neighborhoods had lower overall COI than higher-SES neighborhoods but higher than non-gentrifying neighborhoods (Figure 4. Mean: 15.6, 21.1, and 44.8 for non-gentrifying, gentrifying and higher-SES neighborhoods, respectively; p < 0.01). While the education and social/economic domains showed a similar pattern to the overall COI, the health/environmental domain, which includes factors such as access to green space, hazardous waste, and air pollution was lowest in gentrifying neighborhoods (Figure 4. Mean: 34.1 for gentrifying and 41.4 for both non-gentrifying and higher-SES neighborhoods; p < 0.01).
To explore trends of air pollutants in the years post-gentrification, we compared annual average pollutants between 2009 and 2018. There was a greater decrease in BC over time (43.3–47.6%) compared to PM2.5 and NO2, regardless of gentrification status (Figure 5). The percent decrease in air pollution was smaller in gentrifying neighborhoods compared to non-gentrifying neighborhoods, though the differences were minimal (Figure 5. BC: 45.1% vs. 47.6%; PM2.5: 39.6% vs. 41.3%; NO2: 32.0% vs. 33.1% for gentrifying vs. non-gentrifying, respectively; p < 0.01). Nevertheless, average air pollution levels remained consistently higher in gentrifying neighborhoods after gentrification. In contrast, higher-SES neighborhoods had the lowest air pollution levels throughout the study period, with a smaller decrease over time compared to gentrifying and non-gentrifying neighborhoods (Figure 5. 43.3% for BC, 39.1% PM2.5, and 30.5% for NO2).

4. Discussion

In this study, we found that 42% of NYC public schools (624 out of 1482) were located in gentrifying neighborhoods. Schools in gentrifying neighborhoods had the highest air pollution levels compared to those in non-gentrifying and higher-SES neighborhoods. Additionally, we observed that gentrifying neighborhoods had higher overall childhood opportunity, as well opportunity in the education and social/economic domains, compared to non-gentrifying neighborhoods. However, the relationship was reversed with respect to the health/environment domain with lower opportunity observed in gentrifying compared to non-gentrifying neighborhoods. Overall, schools in both gentrifying and non-gentrifying neighborhoods experienced greater exposure to pollutants and lower child opportunities compared to schools in higher-SES neighborhoods. Within these areas, gentrifying neighborhoods show greater exposure to pollutants and lower health and environmental child opportunity compared to non-gentrifying neighborhoods. These findings suggest that there may be adverse environmental conditions near schools, particularly in gentrifying neighborhoods, that could have an impact on the children within those schools.
Gentrification in NYC has led to significant changes in the environments children operate in, with many displaced children moving to even lower SES neighborhoods while non-displaced children experience some improvements in their residential environments [22]. While studies suggest that gentrification can benefit communities by providing better housing options, improved infrastructure (e.g., roads, parks, public transport), and economic growth, its impact on air pollution remains unclear. A recent study by Hutchings et al. (2023) examined air quality in Detroit and found that improvements in air pollutant levels (e.g., PM2.5 and NO2) over a 40-year period (1980–2020) were lesser in gentrifying neighborhoods than in non-gentrifying neighborhoods [23]. Similarly, we observed that air pollution near NYC schools in gentrifying neighborhoods was higher than non-gentrifying and higher-SES neighborhoods and this difference in pollutant levels was sustained over the decade following gentrification.
Several factors may explain the differences in pollutants between gentrifying and higher- SES neighborhoods. Historical environmental burdens associated with redlining in low- income communities and other government policies have contributed to persistent air pollution disparities. Studies have shown that highways and industrial pollution sources are observed more often in redlined and low income neighborhoods, likely leading to higher diesel exhaust particle (DEP) emissions [24]. Our previous research corroborated this, showing that historically redlined areas in NYC had worse air quality and slightly smaller improvements over time compared to non-redlined neighborhoods [6]. Also, while gentrification stimulates economic growth and infrastructure development, it may also introduce new sources of pollution, such as ongoing construction, business development, increased traffic, and reduced green space. Construction and demolition activities are known to contribute to particulate air pollution, while new businesses attract higher traffic volumes, further worsening air quality [25,26]. Additionally, growth in restaurant density may contribute to elevated PM2.5 levels through cooking-related emissions. However, we acknowledge that these mechanisms may not apply uniformly across all neighborhoods or time periods. The right-skewed distribution of air pollution in gentrifying neighborhoods suggests the presence of very high concentrations, which could be driven by gentrification-related activities in addition to higher pre-gentrification point sources of pollutants. Additionally, limited greenspaces in gentrifying neighborhoods may worsen air quality [27] as greenspaces help to directly filter pollutants and lower temperatures, preventing some pollutant gases from forming [28]. A recent study by Rahaman et al. (2023) demonstrated an inverse association with lower vegetation and higher NO2 levels, as well as a positive association with higher NO2 levels and greater land surface temperature in urban environments in Southeast Asia [29]. However, some research has questioned the impact of specific types of greenspace (i.e., tree canopy vs. grassland) on pollution in urban environments [30]. Furthermore, research on the process known as “green gentrification” has highlighted that marginalized residents can be negatively impacted by increased levels of green space in their communities due to not feeling welcome in new green areas [31], making it challenging to assess the overall impact of green-space. Limited green-space and extreme heat exposure, along with higher pollution levels, could be one plausible explanation for poorer air quality in gentrifying neighborhoods.
Unlike Hutchings et al. (2023), who reported significantly reduced air quality improvement in gentrifying neighborhoods over time (40-years) [23], the differences in percent decrease in air pollution in gentrifying and non-gentrifying neighborhoods observed in our study was minimal. However, our measurements were over a shorter time period (10-years) and did not account for the larger impacts on air quality experienced over the first few decades after the implementation of the Clean Air Act of 1970. Previously, we observed that NYC air quality improved over the past 20 years, likely due to multiple legislative regulations targeting traffic-related air pollution and burning of residual oil in NYC [6,32,33]. However, we found a slightly smaller improvement in air quality in redlined neighborhoods compared to non-redlined neighborhoods, highlighting the residual impact of redlining in NYC [6]. In that same study, we found that removing gentrifying neighborhoods from the analysis resulted in a greater magnitude of difference in pollution changes over time between historically redlined and other neighborhoods, suggesting a potential impact of gentrification on air quality [6]. Isolating the specific sources of these differences is challenging due to multiple factors, including advancements in vehicular emission technology, regulations on residual oil burning, and market-driven transitions in fuel use. Furthermore, the substantial pre-gentrification environmental burdens (e.g., industrial sources, highways) in both gentrifying and non-gentrifying neighborhoods, make it challenging to detect significant differences in air pollution levels between these types of neighborhoods.
In this study, we also examined the impact of gentrification on neighborhood conditions affecting children’s health and well-being. Although COI in gentrifying neighborhoods was in the low opportunity range, NYC schools in gentrifying neighborhoods had a slightly higher overall COI than those in non-gentrifying areas (21.1 vs. 15.6 for gentrifying and non-gentrifying neighborhoods, respectively), suggesting potential benefits of gentrification on children’s quality of life. This was particularly evident in the social and economic domain (e.g., employment, household income, and poverty levels) which are all factors that are expected to improve with gentrification. In contrast, gentrifying neighborhoods ranked lowest in the health and environment domain, which assesses factors such as healthy environments (e.g., access to healthy food and green space), toxic exposures (e.g., hazardous waste, industrial pollutants, air pollution, and extreme heat), and health resources (e.g., health insurance coverage). This aligns with our findings on air pollution, where gentrifying neighborhoods had the highest levels of air pollution among all neighborhood types, suggesting there may be some unintended health and environmental consequences of gentrification. While there are benefits to economic growth in a neighborhood attributable to gentrification, the potential unintended health and environmental consequences, in addition to the displacement of already marginalized populations, should be thoughtfully considered as policy-makers evaluate the impact of neighborhood redevelopment.
We acknowledge several limitations to our study. For one, our findings in NYC may have limited generalizability in other urban communities. And even within NYC, our broad definitions of neighborhoods may not have captured nuances in neighborhood change on a smaller geospatial scale. However, gentrification is occurring in many US cities and thus, our findings suggest that future investigation in other cities is warranted [34]. Also, we defined gentrification based solely on low income and rapid rental growth. A broader definition of gentrification, including factors such as the percentage of residents with a college education, housing values, and employment rates [23] could provide deeper insights into neighborhood changes. Moreover, we analyzed air pollution changes in the decade following the pre-defined gentrification period; however, we were unable to account for additional neighborhood changes during the post-gentrification period. More extensive temporal data before and after gentrification would offer a clearer understanding of its effects and the impact of gentrification on children. Lastly, we did not directly examine other factors that could help to explain air pollution differences, such as changes in traffic volume, new construction, building permits, and green space.

5. Conclusions

Our results shed light on a complex environmental justice issue in NYC. While gentrification may bring some improvements in education and socioeconomic conditions, its impact on pollution, health and environmental conditions need to be examined carefully. Our analyses demonstrated that pollution levels were higher, with less reduction over time in gentrifying compared to non-gentrifying neighborhoods and gentrifying neighborhoods had less health and environmental child opportunity. As more communities are redeveloped in the future, it is important to examine potential unintended consequences that could have significant impacts on child health. Future research should explore extended timeframes and additional environmental factors to better understand the intersection of gentrification and environmental justice in NYC and other gentrifying cities across the US.

Author Contributions

K.H.J. and Z.P. conducted the data analysis and wrote the manuscript. J.W.Q. contributed to the data preparation of the study. K.L.A. contributed to visualization and editing. J.A.S., A.G.R., J.-M.B., S.C. and M.P. provided the critical review and edits. S.L.-D. contributed to the conceptualization, methodology and data analysis as well as the writing, review, and editing. All authors have read and agree to the published version of the manuscript.

Funding

This work was supported by NIH (K01HL140216, P30ES09089), the Robert Wood Johnson Foundation—Amos Medical Faculty Development Award Program, and the NIEHS Center (grant # ES009089). The funding bodies were not involved in the design of the study and collection, analysis, interpretation of data or in the writing of the manuscript.

Data Availability Statement

The data used in this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

None of the authors have financial relationships with a commercial entity that has an interest in the subject of this manuscript. The authors declare that they have no competing interests.

References

  1. Gaffin, J.M.; Petty, C.R.; Hauptman, M.; Kang, C.-M.; Wolfson, J.M.; Abu Awad, Y.; Di, Q.; Lai, P.S.; Sheehan, W.J.; Baxi, S.; et al. Modeling indoor particulate exposures in inner-city school classrooms. J. Expo. Sci. Environ. Epidemiol. 2017, 27, 451–457. [Google Scholar] [CrossRef]
  2. Kingsley, S.L.; Eliot, M.N.; Carlson, L.; Finn, J.; MacIntosh, D.L.; Suh, H.H.; Wellenius, G. Proximity of us schools to major roadways: A nationwide assessment. J. Expo. Sci. Environ. Epidemiol. 2014, 24, 253–259. [Google Scholar] [CrossRef] [PubMed]
  3. Permaul, P.; Phipatanakul, W. School environmental intervention programs. J. Allergy Clin. Immunol. Pract. 2018, 6, 22–29. [Google Scholar] [CrossRef]
  4. Jung, K.H.; Goodwin, K.E.; Perzanowski, M.S.; Chillrud, S.N.; Perera, F.P.; Miller, R.L.; Lovinsky-Desir, S. Personal exposure to black carbon at school and levels of fractional exhaled nitric oxide in new york city. Environ. Health Perspect. 2021, 129, 097005. [Google Scholar] [CrossRef] [PubMed]
  5. Lane, H.M.; Morello-Frosch, R.; Marshall, J.D.; Apte, J.S. Historical redlining is associated with present-day air pollution disparities in u.S. Cities. Environ. Sci. Technol. Lett. 2022, 9, 345–350. [Google Scholar] [CrossRef] [PubMed]
  6. Jung, K.H.; Pitkowsky, Z.; Argenio, K.; Quinn, J.W.; Bruzzese, J.-M.; Miller, R.L.; Chillrud, S.N.; Perzanowski, M.; Stingone, J.A.; Lovinsky-Desir, S. The effects of the historical practice of residential redlining in the united states on recent temporal trends of air pollution near new york city schools. Environ. Int. 2022, 169, 107551. [Google Scholar] [CrossRef]
  7. Jung, K.H.; Argenio, K.L.; Jackson, D.J.; Miller, R.L.; Perzanowski, M.S.; Rundle, A.G.; Bacharier, L.B.; Busse, W.W.; Cohen, R.T.; Visness, C.M.; et al. Home and school pollutant exposure, respiratory outcomes, and influence of historical redlining. J. Allergy Clin. Immunol. 2024, 154, 1159–1168. [Google Scholar] [CrossRef]
  8. Clark, L.P.; Millet, D.B.; Marshall, J.D. Changes in transportation-related air pollution exposures by race-ethnicity and socioeconomic status: Outdoor nitrogen dioxide in the united states in 2000 and 2010. Environ. Health Perspect. 2017, 125, 097012. [Google Scholar] [CrossRef]
  9. Gray, S.C.; Edwards, S.E.; Miranda, M.L. Race, socioeconomic status, and air pollution exposure in north carolina. Environ. Res. 2013, 126, 152–158. [Google Scholar] [CrossRef]
  10. Tessum, C.W.; Paolella, D.A.; Chambliss, S.E.; Apte, J.S.; Hill, J.D.; Marshall, J.D. Pm2.5 polluters disproportionately and systemically affect people of color in the united states. Sci. Adv. 2021, 7, eabf4491. [Google Scholar] [CrossRef]
  11. McKinnish, T.; Walsh, R.; White, T.K. Who gentrifies low-income neighborhoods? J. Urban Econ. 2010, 67, 180–193. [Google Scholar] [CrossRef] [PubMed]
  12. Bradley, A.C.; Croes, B.E.; Harkins, C.; McDonald, B.C.; de Gouw, J.A. Air pollution inequality in the denver metroplex and its relationship to historical redlining. Environ. Sci. Technol. 2024, 58, 4226–4236. [Google Scholar] [CrossRef] [PubMed]
  13. Garg, A.; Sochet, A.A.; Hernandez, R.; Stockwell, D.C. Association of the child opportunity index and inpatient illness severity in the united states, 2018–2019. Acad. Pediatr. 2024, 24, 1101–1109. [Google Scholar] [CrossRef]
  14. Maholtz, D.; Page-Goertz, C.K.; Forbes, M.L.; Nofziger, R.A.; Bigham, M.; McKee, B.; Ramgopal, S.; Pelletier, J.H. Association between the coi and excess health care utilization and costs for acsc. Hosp. Pediatr. 2024, 14, 592–601. [Google Scholar] [CrossRef]
  15. OpenData, N. 2018–2019 School Locations. Available online: https://data.cityofnewyork.us/Education/2018-2019-School-Locations/9ck8-hj3u/data_preview (accessed on 1 July 2021).
  16. NYU Furman Center AoO, 2021. State of New York City’s Housing and Neighborhoods in 2015. 2015. Available online: https://furmancenter.org/files/sotc/NYUFurmanCenter_SOCin2015_9JUNE2016.pdf (accessed on 6 January 2022).
  17. Matte, T.D.; Ross, Z.; Kheirbek, I.; Eisl, H.; Johnson, S.; Gorczynski, J.E.; Kass, D.; Markowitz, S.; Pezeshki, G.; E Clougherty, J. Monitoring intraurban spatial patterns of multiple combustion air pollutants in new york city: Design and implementation. J. Expo. Sci. Environ. Epidemiol. 2013, 23, 223–231. [Google Scholar] [CrossRef]
  18. Clougherty, J.E.; Kheirbek, I.; Eisl, H.M.; Ross, Z.; Pezeshki, G.; Gorczynski, J.E.; Johnson, S.C.; Markowitz, S.; Kass, D.; Matte, T.D. Intra-urban spatial variability in wintertime street-level concentrations of multiple combustion-related air pollutants: The new york city community air survey (nyccas). J. Expo. Sci. Environ. Epidemiol. 2013, 23, 232–240. [Google Scholar] [CrossRef] [PubMed]
  19. Kheirbek, I.; Ito, K.; Neitzel, R.; Kim, J.; Johnson, S.; Ross, Z.; Eisl, H.; Matte, T. Spatial variation in environmental noise and air pollution in new york city. J. Urban Health 2014, 91, 415–431. [Google Scholar] [CrossRef]
  20. OpenData, N. 2022. Available online: https://data.cityofnewyork.us/Environment/NYCCAS-Air-Pollution-Rasters/q68s-8qxv/about_data (accessed on 6 January 2022).
  21. Noelke, C.; McArdle, N.; Baek, M.; Huntington, N.; Huber, R.; Hardy, E.; Acevedo-Garcia, D. Child Opportunity Index 2.0. 2020. Available online: https://www.diversitydatakids.org/research-library/research-brief/how-we-built-it (accessed on 6 January 2022).
  22. Dragan, K.; Ellen, I.; Glied, S.A. Does Gentrification Displace Poor Children? New Evidence from New York City Medicaid Data; National Bureau of Economic Research: Cambridge, MA, USA, 2019. [Google Scholar]
  23. Hutchings, H.; Zhang, Q.; Grady, S.; Mabe, L.; Okereke, I.C. Gentrification and air quality in a large urban county in the united states. Int. J. Environ. Res. Public Health 2023, 20, 4762. [Google Scholar] [CrossRef]
  24. Nardone, A.; Casey, J.A.; Morello-Frosch, R.; Mujahid, M.; Balmes, J.R.; Thakur, N. Associations between historical residential redlining and current age-adjusted rates of emergency department visits due to asthma across eight cities in california: An ecological study. Lancet Planet. Health 2020, 4, e24–e31. [Google Scholar] [CrossRef]
  25. Azarmi, F.; Kumar, P. Ambient exposure to coarse and fine particle emissions from building demolition. Atmos. Environ. 2016, 137, 62–79. [Google Scholar] [CrossRef]
  26. Yan, H.; Li, Q.; Feng, K.; Zhang, L. The characteristics of pm emissions from construction sites during the earthwork and foundation stages: An empirical study evidence. Environ. Sci. Pollut. Res. 2023, 30, 62716–62732. [Google Scholar] [CrossRef] [PubMed]
  27. Rao, M.; George, L.A.; Rosenstiel, T.N.; Shandas, V.; Dinno, A. Assessing the relationship among urban trees, nitrogen dioxide, and respiratory health. Environ. Pollut. 2014, 194, 96–104. [Google Scholar] [CrossRef] [PubMed]
  28. Zupancic, T.; Westmacott, C.; Bulthuis, M. The Impact of Green Space on Heat and Air Pollution in Urban Communities: A Meta-narrative Systematic Review; David Suzuki Foundation: Vancouver, BC, Canada, 2015. [Google Scholar]
  29. Rahaman, S.N.; Ahmed, S.M.; Zeyad, M.; Zim, A.H. Effect of vegetation and land surface temperature on no2 concentration: A google earth engine-based remote sensing approach. Urban Clim. 2023, 47, 101336. [Google Scholar] [CrossRef]
  30. Lovasi, G.S.; O’Neil-Dunne, J.P.; Lu, J.W.; Sheehan, D.; Perzanowski, M.S.; MacFaden, S.W.; King, K.L.; Matte, T.; Miller, R.L.; Hoepner, L.A.; et al. Urban tree canopy and asthma, wheeze, rhinitis, and allergic sensitization to tree pollen in a new york city birth cohort. Environ. Health Perspect. 2013, 121, 494–500. [Google Scholar] [CrossRef]
  31. Jelks, N.T.O.; Jennings, V.; Rigolon, A. Green gentrification and health: A scoping review. Int. J. Environ. Res. Public Health 2021, 18, 907. [Google Scholar] [CrossRef]
  32. Jung, K.H.; Liu, B.; Lovinsky-Desir, S.; Yan, B.; Camann, D.; Sjodin, A.; Li, Z.; Perera, F.; Kinney, P.; Chillrud, S.; et al. Time trends of polycyclic aromatic hydrocarbon exposure in new york city from 2001 to 2012: Assessed by repeat air and urine samples. Environ. Res. 2014, 131, 95–103. [Google Scholar] [CrossRef]
  33. Narvaez, R.F.; Hoepner, L.; Chillrud, S.N.; Yan, B.; Garfinkel, R.; Whyatt, R.; Camann, D.; Perera, F.P.; Kinney, P.L.; Miller, R.L. Spatial and temporal trends of polycyclic aromatic hydrocarbons and other traffic-related airborne pollutants in new york city. Environ. Sci. Technol. 2008, 42, 7330–7335. [Google Scholar] [CrossRef]
  34. Stehlin, J. Cycles of investment: Bicycle infrastructure, gentrification, and the restructuring of the san francisco bay area. Environ. Plan. A 2015, 47, 121–137. [Google Scholar] [CrossRef]
Environments 12 00199 g001
Figure 1. Map of NYC school locations. Dark gray dots are NYC public schools (N = 1482), which were obtained from NYC Open Data. NYC neighborhoods were categorized as gentrifying (dark purple: n = 624), non-gentrifying (Purple: n = 198), and higher socioeconomic status (SES; gray: n = 660) based on NYU Furman Center classification.
Figure 1. Map of NYC school locations. Dark gray dots are NYC public schools (N = 1482), which were obtained from NYC Open Data. NYC neighborhoods were categorized as gentrifying (dark purple: n = 624), non-gentrifying (Purple: n = 198), and higher socioeconomic status (SES; gray: n = 660) based on NYU Furman Center classification.
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Figure 2. Timeline for data sources.
Figure 2. Timeline for data sources.
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Figure 3. Comparisons of traffic-related air pollution (TRAP) concentrations by gentrification status. Annual average of TRAP levels (black carbon [BC] (a), fine particulate matter [PM2.5] (b), and nitrogen dioxide [NO2] (c)) were estimated within a 250−m buffer around schools using NYC Community Air Survey land−use regression models. These estimates were then averaged over a six-year period from 2012 to 2017. Violin plots display the distribution of air pollution levels across gentrifying (n = 624), non-gentrifying (n = 198), and higher socioeconomic status (SES) neighborhoods (n = 660), classified by the NYU Furman Center. Median values are indicated by red lines. A t-test was performed for group comparisons. Colored areas (dark purple, purple, and gray) represent the distribution of air pollution levels across the three neighborhood types. * p-value < 0.05 and ** p-value < 0.01.
Figure 3. Comparisons of traffic-related air pollution (TRAP) concentrations by gentrification status. Annual average of TRAP levels (black carbon [BC] (a), fine particulate matter [PM2.5] (b), and nitrogen dioxide [NO2] (c)) were estimated within a 250−m buffer around schools using NYC Community Air Survey land−use regression models. These estimates were then averaged over a six-year period from 2012 to 2017. Violin plots display the distribution of air pollution levels across gentrifying (n = 624), non-gentrifying (n = 198), and higher socioeconomic status (SES) neighborhoods (n = 660), classified by the NYU Furman Center. Median values are indicated by red lines. A t-test was performed for group comparisons. Colored areas (dark purple, purple, and gray) represent the distribution of air pollution levels across the three neighborhood types. * p-value < 0.05 and ** p-value < 0.01.
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Figure 4. Comparisons of the Child Opportunity Index (COI) and its subdomains based on gentrification status. Violin plots display the distribution of the overall Child Opportunity Index (COI) (a) and its 3 domains (Education (b), Health and Environment (c), and Social and Economic factors (d)) across gentrifying (n = 624), non-gentrifying (n = 198), and higher socioeconomic status (SES) neighborhoods (n = 660), classified by the NYU Furman Center. Median values are indicated by red lines. A t-test was performed for group comparisons. Colored areas (dark purple, purple, and gray) represent the distribution of air pollution levels across the three neighborhood types. ** p-value < 0.01.
Figure 4. Comparisons of the Child Opportunity Index (COI) and its subdomains based on gentrification status. Violin plots display the distribution of the overall Child Opportunity Index (COI) (a) and its 3 domains (Education (b), Health and Environment (c), and Social and Economic factors (d)) across gentrifying (n = 624), non-gentrifying (n = 198), and higher socioeconomic status (SES) neighborhoods (n = 660), classified by the NYU Furman Center. Median values are indicated by red lines. A t-test was performed for group comparisons. Colored areas (dark purple, purple, and gray) represent the distribution of air pollution levels across the three neighborhood types. ** p-value < 0.01.
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Figure 5. Changes in annual average levels of air pollutants (2009−2018). Annual average levels of each pollutant (black carbon [BC] (a), fine particulate matter [PM2.5] (b), and nitrogen dioxide [NO2] (c)) in 2009 and 2018 are plotted by gentrification status. The percent decrease was calculated as the difference between the 2009 and 2018 annual averages, divided by the average of the two values, then multiplied by 100.
Figure 5. Changes in annual average levels of air pollutants (2009−2018). Annual average levels of each pollutant (black carbon [BC] (a), fine particulate matter [PM2.5] (b), and nitrogen dioxide [NO2] (c)) in 2009 and 2018 are plotted by gentrification status. The percent decrease was calculated as the difference between the 2009 and 2018 annual averages, divided by the average of the two values, then multiplied by 100.
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Jung, K.H.; Pitkowsky, Z.; Argenio, K.L.; Quinn, J.W.; Stingone, J.A.; Rundle, A.G.; Bruzzese, J.-M.; Chillrud, S.; Perzanowski, M.; Lovinsky-Desir, S. The Impacts of Gentrification on Air Pollutant Levels and Child Opportunity Index near New York City Schools. Environments 2025, 12, 199. https://doi.org/10.3390/environments12060199

AMA Style

Jung KH, Pitkowsky Z, Argenio KL, Quinn JW, Stingone JA, Rundle AG, Bruzzese J-M, Chillrud S, Perzanowski M, Lovinsky-Desir S. The Impacts of Gentrification on Air Pollutant Levels and Child Opportunity Index near New York City Schools. Environments. 2025; 12(6):199. https://doi.org/10.3390/environments12060199

Chicago/Turabian Style

Jung, Kyung Hwa, Zachary Pitkowsky, Kira L. Argenio, James W. Quinn, Jeanette A. Stingone, Andrew G. Rundle, Jean-Marie Bruzzese, Steven Chillrud, Matthew Perzanowski, and Stephanie Lovinsky-Desir. 2025. "The Impacts of Gentrification on Air Pollutant Levels and Child Opportunity Index near New York City Schools" Environments 12, no. 6: 199. https://doi.org/10.3390/environments12060199

APA Style

Jung, K. H., Pitkowsky, Z., Argenio, K. L., Quinn, J. W., Stingone, J. A., Rundle, A. G., Bruzzese, J.-M., Chillrud, S., Perzanowski, M., & Lovinsky-Desir, S. (2025). The Impacts of Gentrification on Air Pollutant Levels and Child Opportunity Index near New York City Schools. Environments, 12(6), 199. https://doi.org/10.3390/environments12060199

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