Chris Chaeha Lim

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• Kim, H., & Lim, C. C. (2025). Toward equitable environmental exposure modeling through convergence of data, open, and citizen sciences: an example of air pollution exposure modeling amidst increasing wildfire smoke. Environmental Research, 286(Issue). doi:10.1016/j.envres.2025.122881
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  Exposure modeling is critical in environmental epidemiology and human health but may face challenges (e.g., skewed data, unequal error, context-insensitive validation, and computational demands). Modeling decisions reflect the intended use of the models and the values that modelers prioritize. We aimed to provide a conceptual framework and machine learning (ML) modeling protocols that address these issues. With 500m-gridded hourly PM2.5 and O3 levels in Illinois before, during, and after the 2023 Canadian wildfire season as a motivating example, we conducted modeling experiments to evaluate modeling methods, guided by three domains we propose based on theories of science: 1) Data Diversity, leveraging open and citizen science data to enhance inclusivity, parsimony, and representativeness; 2) Equitable Accuracy, ensuring fairly distributed uncertainties across subpopulations; and 3) Sustainable Modeling, balancing accuracy with reducing computational demands to promote accessibility for under-resourced researchers. We found that ML with publicly available data can achieve high accuracy. Depending on methods, performance may vary substantially, even with identical input data. Large but skewed data may reduce performance. Misuse of cross-validation protocols can underestimate prediction error; although we observed R2s of ∼98 %, the modeled estimates varied significantly, indicating the need for careful model validation. By using new modeling protocols including representativeness-considered training and validation data and a new loss function, we achieved high agreement between estimates and ground-based measurements (e.g., R2 = ∼90 % for PM2.5; ∼80 % for O3), equally distributed errors across sociodemographic strata and urban–rural divides, and reduction in computation time—from several weeks or months to a few days.
• Kim, S., Gurmu, B. L., Kim, M., Song, C., Lee, M. R., Lim, C. C., Rule, A. M., & Yang, K. I. (2025). Effect of indoor air quality on potential risk of obstructive sleep apnea: results from Korea National Health and Nutrition Examination Survey. BMC Public Health, 25(Issue 1). doi:10.1186/s12889-025-22127-2
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  Background: Using nationally representative data from the 2020–2021 Korea National Health and Nutrition Examination Survey, we examined associations between indoor air pollutant exposure and potential obstructive sleep apnea (OSA) risk, estimated by STOP-BANG questionnaire scores. Methods: We included 1,501 participants who completed the STOP-BANG questionnaire and consented to in-home air quality measurements per Korea’s Indoor Air Quality (IAQ) standards. Data were weighted for national representativeness, and multivariate logistic regression models identified determinants of potential OSA risk with adjusted odds ratios and 95% confidence intervals. Results: From our adjusted model, odds ratios (95% CI) for OSA risk with a unit increase in age were 1.07 (1.05–1.09) for men and 1.04 (1.01–1.07) for women, respectively. The ratios with systolic blood pressure were 1.05 (1.03–1.06) and 1.01 (0.99–1.02), and those with body mass index (BMI, Kg/m2) were 1.12 (1.01–1.24) and 1.08 (0.95–1.22) respectively. Unit increase in indoor formaldehyde (HCHO) exposure raised OSA risk by 1.02 (1.00–1.02) fold in men, after controlling for socioeconomic and behavioural factors as well as other common indoor pollutants (CO2, PM2.5 and Toluene) and outdoor PM2.5. No significant association was obtained from women’s data. Conclusions: Our study found a potential association between elevated indoor HCHO levels and increased OSA risk in men. These findings highlight the importance of indoor air quality in OSA prevention, supporting the future development of more effective prevention models and interventions.
• Estacio, I., Lim, C., Onitsuka, K., & Hoshino, S. (2024). Predicting the future through observations of the past: Concretizing the role of Geosimulation for holistic geospatial knowledge. Geomatica, 76(2). doi:10.1016/j.geomat.2024.100012
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  Geomatics can be generally defined as the knowledge and ability of utilizing geospatial data for analyzing and forecasting the state of the environment to inform environmental management. However, current applications of Geomatics only span from data acquisition to spatial analysis and exclude the capabilities of Geosimulation. To concretize the role of Geosimulation in Geomatics for obtaining geospatial knowledge, we write this paper with two main objectives. First, we establish the Geomatics framework, a set of tasks utilizing geospatial data that aims to provide holistic geospatial knowledge of the environment. This set of tasks are specifically composed of data acquisition, spatial analysis, and Geosimulation. This proposed framework also brings forward our second objective which is to present Geomatics as an approach for holistically informing environmental management by predicting the future through observations of the past. To provide sample applications of the Geomatics framework for obtaining holistic geospatial knowledge, we provide three case studies of research projects that followed the Geomatics framework for informing environmental management actions. As Geomatics can play a major role in addressing the effects of climate change, we also presented a future template for the application of the Geomatics framework for mitigating and adapting to the effects of climate change. We anticipate three implications of adopting this Geomatics framework: the widening of the environmental application of Geomatics, the establishment of a methodological workflow for informing environmental management, and the enhancement of the collaboration between Geosimulation and other spatial science fields. We conclude the paper by advocating the adoption of this framework as we posit that this new perspective in Geomatics will also strengthen the teaching of the environmental applications of geospatial knowledge.
• Song, C., Lim, C., Gurmu, B., Kim, M., Lee, S., Park, J., & Kim, S. (2023). Comparison of Personal or Indoor PM2.5 Exposure Level to That of Outdoor: Over Four Seasons in Selected Urban, Industrial, and Rural Areas of South Korea: (K-IOP Study). International Journal of Environmental Research and Public Health, 20(17). doi:10.3390/ijerph20176684
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  This study aimed to compare the distribution of indoor, outdoor, and personal PM2.5 (particulate matter ≤ 2.5 μm) hourly concentrations measured simultaneously among 81 nonsmoking elderly participants (65 years or older) living in urban, industrial, or rural areas over 4 seasons (2 weeks per season) from November 2021 to July 2022). PM2.5 measurements were conducted using low-cost sensors with quality control and quality assurance tests. Seasonal outdoor PM2.5 levels were 16.4 (9.1–29.6) μg/m3, 20.5 (13.0–38.0) μg/m3, 18.2 (10.2–31.8) μg/m3, and 9.5 (3.8–18.7) μg/m3 for fall, winter, spring, and summer, respectively. For indoor PM2.5, the median seasonal range was 5.9–7.5 μg/m3, and the median personal PM2.5 exposure concentration was 8.0–9.4 μg/m3. This study provided seasonal distributions of IO (ratio of indoor to outdoor PM2.5 concentration) and PO (ratio of personal to outdoor PM2.5 concentration) using a total of 94,676 paired data points. The median seasonal IO ranged from 0.30 to 0.51 in fall, winter, and spring; its value of summer was 0.70. The median PO by season and study area were close to 1.0 in summer while it ranged 0.5 to 0.7 in other seasons, statistically significantly lower (p < 0.05) than that in summer. Our study has revealed that the real-world exposure level to PM2.5 among our elderly study participants might be lower than what was initially expected based on the outdoor data for most of the time. Further investigation may need to identify the reasons for the discrepancy, personal behavior patterns, and the effectiveness of any indoor air quality control system.
• Son, J., Choi, H. M., Fong, K. C., Heo, S., Lim, C. C., & Bell, M. L. (2021). The roles of residential greenness in the association between air pollution and health: a systematic review. Environmental Research Letters.
• Bell, M. L., Heo, S., & Lim, C. C. (2020). Relationships between Local Green Space and Human Mobility Patterns during COVID-19 for Maryland and California, USA. Sustainability, 12(22), 9401. doi:10.3390/su12229401
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  Human mobility is a significant factor for disease transmission. Little is known about how the environment influences mobility during a pandemic. The aim of this study was to investigate an effect of green space on mobility reductions during the early stage of the COVID-19 pandemic in Maryland and California, USA. For 230 minor civil divisions (MCD) in Maryland and 341 census county divisions (CCD) in California, we obtained mobility data from Facebook Data for Good aggregating information of people using the Facebook app on their mobile phones with location history active. The users’ movement between two locations was used to calculate the number of users that traveled into an MCD (or CCD) for each day in the daytime hours between 11 March and 26 April 2020. Each MCD’s (CCD’s) vegetation level was estimated as the average Enhanced Vegetation Index (EVI) level for 1 January through 31 March 2020. We calculated the number of state and local parks, food retail establishments, and hospitals for each MCD (CCD). Results showed that the daily percent changes in the number of travels declined during the study period. This mobility reduction was significantly lower in Maryland MCDs with state parks (p-value = 0.045), in California CCDs with local-scale parks (p-value = 0.048). EVI showed no association with mobility in both states. This finding has implications for the potential impacts of green space on mobility under an outbreak. Future studies are needed to explore these findings and to investigate changes in health effects of green space during a pandemic.
• Hayes, R., Lim, C., Zhang, Y., Cromar, K., Shao, Y., Reynolds, H., Silverman, D., Jones, R., Park, Y., Jerrett, M., Ahn, J., & Thurston, G. (2020). PM2.5 air pollution and cause-specific cardiovascular disease mortality. International Journal of Epidemiology, 49(1). doi:10.1093/ije/dyz114
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  Background: Ambient air pollution is a modifiable risk factor for cardiovascular disease, yet uncertainty remains about the size of risks at lower levels of fine particulate matter (PM2.5) exposure which now occur in the USA and elsewhere. Methods: We investigated the relationship of ambient PM2.5 exposure with cause-specific cardiovascular disease mortality in 565 477 men and women, aged 50 to 71 years, from the National Institutes of Health-AARP Diet and Health Study. During 7.5 x 106 person-years of follow up, 41 286 cardiovascular disease deaths, including 23 328 ischaemic heart disease (IHD) and 5894 stroke deaths, were ascertained using the National Death Index. PM2.5 was estimated using a hybrid land use regression (LUR) geostatistical model. Multivariate Cox regression models were used to estimate relative risks (RRs) and 95% confidence intervals (CI). Results: Each increase of 10 μg/m3 PM2.5 (overall range, 2.9-28.0 μg/m3) was associated, in fully adjusted models, with a 16% increase in mortality from ischaemic heart disease [hazard ratio (HR) 1.16; 95% CI 1.09-1.22] and a 14% increase in mortality from stroke (HR 1.14; CI 1.02-1.27). Compared with PM2.5 exposure
• Son, J., Fong, K., Heo, S., Kim, H., Lim, C., & Bell, M. (2020). Reductions in mortality resulting from reduced air pollution levels due to COVID-19 mitigation measures. Science of the Total Environment, 744(Issue). doi:10.1016/j.scitotenv.2020.141012
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  To control the novel coronavirus disease (COVID-19) outbreak, state and local governments in the United States have implemented several mitigation efforts that resulted in lower emissions of traffic-related air pollutants. This study examined the impacts of COVID-19 mitigation measures on air pollution levels and the subsequent reductions in mortality for urban areas in 10 US states and the District of Columbia. We calculated changes in levels of particulate matter with aerodynamic diameter no larger than 2.5 μm (PM2.5) during mitigation period versus the baseline period (pre-mitigation measure) using the difference-in-difference approach and the estimated avoided total and cause-specific mortality attributable to these changes in PM2.5 by state and district. We found that PM2.5 concentration during the mitigation period decreased for most states (except for 3 states) and the capital. Decreases of average PM2.5 concentration ranged from 0.25 μg/m3 (4.3%) in Maryland to 4.20 μg/m3 (45.1%) in California. On average, PM2.5 levels across 7 states and the capital reduced by 12.8%. We estimated that PM2.5 reduction during the mitigation period lowered air pollution-related total and cause-specific deaths. An estimated 483 (95% CI: 307, 665) PM2.5-related deaths was avoided in the urban areas of California. Our findings have implications for the effects of mitigation efforts and provide insight into the mortality reductions can be achieved from reduced air pollution levels.
• Lim, C., Hayes, R., Ahn, J., Shao, Y., Silverman, D., Jones, R., & Thurston, G. (2019). Mediterranean Diet and the Association between Air Pollution and Cardiovascular Disease Mortality Risk. Circulation, 139(15). doi:10.1161/circulationaha.118.035742
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  Background: Recent experimental evidence suggests that nutritional supplementation can blunt adverse cardiopulmonary effects induced by acute air pollution exposure. However, whether usual individual dietary patterns can modify the association between long-term air pollution exposure and health outcomes has not been previously investigated. We assessed, in a large cohort with detailed diet information at the individual level, whether a Mediterranean diet modifies the association between long-term exposure to ambient air pollution and cardiovascular disease mortality risk. Methods: The National Institutes of Health-American Association for Retired Persons Diet and Health Study, a prospective cohort (N=548 845) across 6 states and 2 cities in the United States and with a follow-up period of 17 years (1995-2011), was linked to estimates of annual average exposures to fine particulate matter and nitrogen dioxide at the residential census-tract level. The alternative Mediterranean Diet Index, which uses a 9-point scale to assess conformity with a Mediterranean-style diet, was constructed for each participant from information in cohort baseline dietary questionnaires. We evaluated mortality risks for cardiovascular disease, ischemic heart disease, cerebrovascular disease, or cardiac arrest associated with long-term air pollution exposure. Effect modification of the associations between exposure and the mortality outcomes by alternative Mediterranean Diet Index was examined via interaction terms. Results: For fine particulate matter, we observed elevated and significant associations with cardiovascular disease (hazard ratio [HR] per 10 μg/m3, 1.13; 95% CI, 1.08-1.18), ischemic heart disease (HR, 1.16; 95% CI, 1.10-1.23), and cerebrovascular disease (HR, 1.15; 95% CI, 1.03-1.28). For nitrogen dioxide, we found significant associations with cardiovascular disease (HR per 10 ppb, 1.06; 95% CI, 1.04-1.08) and ischemic heart disease (HR, 1.08; 95% CI, 1.05-1.11). Analyses indicated that Mediterranean diet modified these relationships, as those with a higher alternative Mediterranean Diet Index score had significantly lower rates of cardiovascular disease mortality associated with long-term air pollution exposure (P-interaction
• Lim, C., Hayes, R., Ahn, J., Shao, Y., Silverman, D., Jones, R., Garcia, C., Bell, M., & Thurston, G. (2019). Long-term exposure to ozone and cause-specific mortality risk in the United States. American Journal of Respiratory and Critical Care Medicine, 200(8). doi:10.1164/rccm.201806-1161oc
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  Rationale: Many studies have linked short-term exposure to ozone (O3) with morbidity and mortality, but epidemiologic evidence of associations between long-term O3 exposure and mortality is more limited. Objectives: To investigate associations of long-term (annual or warm season average of daily 8-h maximum concentrations) O3 exposure with all-cause and cause-specific mortality in the NIH-AARP Diet and Health Study, a large prospective cohort of U.S. adults with 17 years of follow-up from 1995 to 2011. Methods: The cohort (n = 548,780) was linked to census tract–level estimates for O3. Associations between long-term O3 exposure (averaged values from 2002 to 2010) and multiple causes of death were evaluated using multivariate Cox proportional hazards models, adjusted for individual- and census tract–level covariates, and potentially confounding copollutants and temperature. Measurements and Main Results: Long-term annual average exposure to O3 was significantly associated with deaths caused by cardiovascular disease (per 10 ppb; hazard ratio [HR], 1.03; 95% confidence interval [CI], 1.01–1.06), ischemic heart disease (HR, 1.06; 95% CI, 1.02–1.09), respiratory disease (HR, 1.04; 95% CI, 1.00–1.09), and chronic obstructive pulmonary disease (HR, 1.09; 95% CI, 1.03–1.15) in single-pollutant models. The results were robust to alternative models and adjustment for copollutants (fine particulate matter and nitrogen dioxide), although some evidence of confounding by temperature was observed. Significantly elevated respiratory disease mortality risk associated with long-term O3 exposure was found among those living in locations with high temperature (Pinteraction , 0.05). Conclusions: This study found that long-term exposure to O3 is associated with increased risk for multiple causes of mortality, suggesting that establishment of annual and/or seasonal federal O3 standards is needed to more adequately protect public health from ambient O3 exposures.
• Lim, C., Kim, H., Vilcassim, M., Thurston, G., Gordon, T., Chen, L., Lee, K., Heimbinder, M., & Kim, S. (2019). Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea. Environment International, 131(Issue). doi:10.1016/j.envint.2019.105022
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  Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (
• Ruzmyn Vilcassim, M., Thurston, G., Chen, L., Lim, C., & Gordon, T. (2019). Exposure to greater air pollution when traveling abroad is associated with decreased lung function. American Journal of Respiratory and Critical Care Medicine, 199(12). doi:10.1164/rccm.201811-2235le
• Vilcassim, M., Thurston, G., Chen, L., Lim, C., Saunders, E., Yao, Y., & Gordon, T. (2019). Exposure to air pollution is associated with adverse cardiopulmonary health effects in international travellers. Journal of Travel Medicine, 26(5). doi:10.1093/jtm/taz032
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  Background: With the number of annual global travellers reaching 1.2 billion, many individuals encounter greater levels of air pollution when they travel abroad to megacities around the world. This study's objective was to determine if visits to cities abroad with greater levels of air pollution adversely impact cardiopulmonary health. Methods: A total of 34 non-smoking healthy adult participants who travelled abroad to selected cities from the New York City (NYC) metropolitan area were pre-trained to measure lung function, blood pressure and heart rate (HR)/HR variability (HRV) and record symptoms before, during and after travelling abroad. Outdoor particulate matter (PM)2.5 concentrations were obtained from central monitors in each city. Associations between PM exposure concentrations and cardiopulmonary health endpoints were analysed using a mixed effects statistical design. Results: East and South Asian cities had significantly higher PM2.5 concentrations compared with pre-travel NYC PM2.5 levels, with maximum concentrations reaching 503 μg/m3. PM exposure-related associations for lung function were statistically significant and strongest between evening Forced Expiratory Volume in the first second (FEV1) and same-day morning PM2.5 concentrations; a 10-μg/m3 increase in outdoor PM2.5 was associated with a mean decrease of 7 mL. Travel to a highly polluted city (PM2.5 > 100 μg/m3) was associated with a 209-ml reduction in evening FEV1 compared with a low polluted city (PM2.5 < 35 μg/m3). In general, participants who travelled to East and South Asian cities experienced increased respiratory symptoms/scores and changes in HR and HRV. Conclusions: Exposure to increased levels of PM2.5 in cities abroad caused small but statistically significant acute changes in cardiopulmonary function and respiratory symptoms in healthy young adults. These data suggest that travel-related exposure to increased PM2.5 adversely impacts cardiopulmonary health, which may be particularly important for travellers with pre-existing respiratory or cardiac disease.
• Burnett, R., Chen, H., Szyszkowicz, M., Fann, N., Hubbell, B., Pope, C. A., Apte, J. S., Brauer, M., Cohen, A., Weichenthal, S., Coggins, J., Di, Q., Brunekreef, B., Frostad, J., Lim, S. S., Kan, H., Walker, K. D., Thurston, G. D., Hayes, R. B., , Lim, C. C., et al. (2018). Global estimates of mortality associated with longterm exposure to outdoor fine particulate matter. Proceedings of the National Academy of Sciences of the United States of America, 115(Issue 38). doi:10.1073/pnas.1803222115
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  Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
• Lim, C., Hayes, R., Ahn, J., Shao, Y., Silverman, D., Jones, R., Garcia, C., & Thurston, G. (2018). Association between long-term exposure to ambient air pollution and diabetes mortality in the US. Environmental Research, 165(Issue). doi:10.1016/j.envres.2018.04.011
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  Objective: Recent mechanistic and epidemiological evidence implicates air pollution as a potential risk factor for diabetes; however, mortality risks have not been evaluated in a large US cohort assessing exposures to multiple pollutants with detailed consideration of personal risk factors for diabetes. Research design and methods: We assessed the effects of long-term ambient air pollution exposures on diabetes mortality in the NIH-AARP Diet and Health Study, a cohort of approximately a half million subjects across the contiguous U.S. The cohort, with a follow-up period between 1995 and 2011, was linked to residential census tract estimates for annual mean concentration levels of PM2.5, NO2, and O3. Associations between the air pollutants and the risk of diabetes mortality (N = 3598) were evaluated using multivariate Cox proportional hazards models adjusted for both individual-level and census-level contextual covariates. Results: Diabetes mortality was significantly associated with increasing levels of both PM2.5 (HR = 1.19; 95% CI: 1.03–1.39 per 10 μg/m3) and NO2 (HR = 1.09; 95% CI: 1.01–1.18 per 10 ppb). The strength of the relationship was robust to alternate exposure assessments and model specifications. We also observed significant effect modification, with elevated mortality risks observed among those with higher BMI and lower levels of fruit consumption. Conclusions: We found that long-term exposure to PM2.5 and NO2, but not O3, is related to increased risk of diabetes mortality in the U.S, with attenuation of adverse effects by lower BMI and higher fruit consumption, suggesting that air pollution is involved in the etiology and/or control of diabetes.
• Lim, C., Thurston, G., Shamy, M., Alghamdi, M., Khoder, M., Mohorjy, A., Alkhalaf, A., Brocato, J., Chen, L., & Costa, M. (2018). Temporal variations of fine and coarse particulate matter sources in Jeddah, Saudi Arabia. Journal of the Air and Waste Management Association, 68(2). doi:10.1080/10962247.2017.1344158
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  This study provides the first comprehensive analysis of the seasonal variations and weekday/weekend differences in fine (aerodynamic diameter
• Shamy, M., Alghamdi, M., Khoder, M., Mohorjy, A., Alkhatim, A., Alkhalaf, A., Brocato, J., Chen, L., Thurston, G., Lim, C., & Costa, M. (2018). Association between exposure to ambient air particulates and metabolic syndrome components in a Saudi Arabian population. International Journal of Environmental Research and Public Health, 15(1). doi:10.3390/ijerph15010027
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  Recent epidemiological evidence suggests that exposure to particulates may be a factor in the etiology of metabolic syndrome (MetS). In this novel study, we investigated the relationship between particulate levels and prevalence of MetS component abnormalities (hypertension, hyperglycemia, obesity) in a recruited cohort (N = 2025) in Jeddah, Saudi Arabia. We observed significant associations between a 10 µg/m3 increase in PM2.5 and increased risks for MetS (Risk Ratio (RR): 1.12; 95% Confidence Interval (CI): 1.06–1.19), hyperglycemia (RR: 1.08; 95% CI: 1.03–1.14), and hypertension (RR: 1.09; 95% CI: 1.04–1.14). PM2.5 from soil/road dust was found to be associated with hyperglycemia (RR: 1.12; 95% CI: 1.06–1.19) and hypertension (RR: 1.11; 95% CI: 1.05–1.18), while PM2.5 from traffic was associated with hyperglycemia (RR: 1.33; 95% CI: 1.05–1.71). We did not observe any health associations with source-specific mass exposures. Our findings suggest that exposure to specific elemental components of PM2.5, especially Ni, may contribute to the development of cardiometabolic disorders.
• Thurston, G., Ahn, J., Cromar, K., Shao, Y., Reynolds, H., Jerrett, M., Lim, C., Shanley, R., Park, Y., & Hayes, R. (2016). Ambient particulate matter air pollution exposure and mortality in the NIH-AARP diet and health cohort. Environmental Health Perspectives, 124(4). doi:10.1289/ehp.1509676
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  Background: Outdoor fine particulate matter (≤ 2.5 μm; PM2.5) has been identified as a global health threat, but the number of large U.S. prospective cohort studies with individual participant data remains limited, especially at lower recent exposures. Objectives: We aimed to test the relationship between long-term exposure PM2.5 and death risk from all nonaccidental causes, cardiovascular (CVD), and respiratory diseases in 517,041 men and women enrolled in the National Institutes of Health-AARP cohort. Methods: Individual participant data were linked with residence PM2.5 exposure estimates across the continental United States for a 2000–2009 follow-up period when matching census tract–level PM2.5 exposure data were available. Participants enrolled ranged from 50 to 71 years of age, residing in six U.S. states and two cities. Cox proportional hazard models yielded hazard ratio (HR) estimates per 10 μg/m3 of PM2.5 exposure. Results: PM2.5 exposure was significantly associated with total mortality (HR = 1.03; 95% CI: 1.00, 1.05) and CVD mortality (HR = 1.10; 95% CI: 1.05, 1.15), but the association with respiratory mortality was not statistically significant (HR = 1.05; 95% CI: 0.98, 1.13). A significant association was found with respiratory mortality only among never smokers (HR = 1.27; 95% CI: 1.03, 1.56). Associations with 10-μg/m3 PM2.5 exposures in yearly participant residential annual mean, or in metropolitan area-wide mean, were consistent with baseline exposure model results. Associations with PM2.5 were similar when adjusted for ozone exposures. Analyses of California residents alone also yielded statistically significant PM2.5mortality HRs for total and CVD mortality. Conclusions: Long-term exposure to PM2.5 air pollution was associated with an increased risk of total and CVD mortality, providing an independent test of the PM2.5–mortality relationship in a new large U.S. prospective cohort experiencing lower post-2000 PM2.5 exposure levels.

Proceedings Publications

• Estacio, I., Hoover, J., Li, X., Lim, C., & Román-Palacios, C. (2024). Open-source automatic extraction of Urban Green Space: Application to assessing improvement in green space access. In 2024 ISPRS TC II Mid-term Symposium on The Role of Photogrammetry for a Sustainable World, 10.
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  Urban Green Space (UGS) is vital for improving the public health and sustainability of cities. Vector data on UGS such as open data from governments and OpenStreetMap are available for retrieval by interested users, but the availability of UGS data is still limited on global and temporal scales. This study develops the UGS Extractor, a web-based application for the automatic extraction of UGS given user inputs of Area of Interest and Date of Interest. To accommodate various types of green spaces, such as parks or lawns, the application additionally allows users to set parameters for the minimum size of each UGS and the Minimum Urban Neighbor Density, enabling customization of what qualifies as UGS. The UGS Extractor implements a methodological framework that applies object-based image processing, edge detection and extraction, and image neighborhood analysis on the near real-time 10m Dynamic World collection of Land Use/Land Cover images. The application's utility was demonstrated through two case studies. In the first, the UGS Extractor accurately mapped major parks when compared to open data sources in New Orleans, USA. In the second, the UGS Extractor demonstrated significant increases in the total area of UGS from 2015 to 2023 in Songdo, South Korea, which consequently improved green space accessibility. These results underscore the UGS Extractor's utility in extracting specific types of UGS and analyzing their temporal trends. This user-friendly application overall offers higher spatial resolution compared to publicly available satellite-based methods while facilitating temporal studies not possible with vector datasets.

Presentations

• Lim, C. C. (2022, May). Greening Schoolyards and Academic Performance in New York City.. Children and Nature Network Inside-Out Conference.

Creative Productions

• Lim, C. C. (2021. Community Air Mapping Project for Envioronmental JusticeNew York City Environmental Justice Alliance. https://nyc-eja.org/wp-content/uploads/2021/02/CAMP-EJ-2020-Report-Final-021821-Reduced.pdf
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  Lead data analysis and interpretation for a report on air pollution exposures in environmental justice neighborhoods in New York City