ZIP Code-Level Estimation of Air Quality and Health Risk Due to Particulate Matter Pollution in New York City

Major air pollution and climate policies in NYC and trends in NYC air quality 1998-2021

Introduction

Air pollution poses serious health risks to humans, with particular harm to children.

Objectives

To address the gap in understanding the efficacy of policies to reduce exposure to air pollution, we sought to assess the temporal relationship between the enactment of major air pollution and climate policies in NYC and trends in air quality during the period 1998-2021. We used previously available data from citywide monitoring and new data from the Columbia Center for Children's Environmental Health (CCCEH) longitudinal cohort studies of mothers and children living in communities in Northern Manhattan and the South Bronx.

Methods

We utilized publicly available citywide air monitoring data for particulate matter (PM2.5) and nitrogen dioxide (NO2) from 2009 to 2021 from the New York City Community Air Survey (NYCCAS) database and CCCEH cohort data on residential exposure to PM2.5 and NO2 and personal exposure to polycyclic aromatic hydrocarbons (PAH) during pregnancies occurring from 1998-2016 and 1998-2021, respectively. We compared annual and overall reductions in PM2.5 and NO2 citywide and reductions in PAH concentrations in the cohort studies.

Results

As previously reported, annual average concentrations of pollutants in NYC dropped significantly over time. Between 1998 and 2021, PM2.5 and NO2 concentrations were reduced citywide by 37 and 31%, respectively. In our CCCEH cohorts, between 1998 and 2016, the annual average PM2.5 and NO2 concentrations also decreased significantly by 51 and 48%, respectively. Between 1998 and 2020, PAH concentrations decreased significantly by 66%.

Discussion/conclusion

While it is not possible to link improved air quality to a single policy, our analysis provides evidence of a cumulative beneficial effect of clean air and climate policies enacted between 1998 and 2021 both city-wide and in our cohorts residing in communities that have been disproportionately affected by air pollution. There are important implications for health benefits, particularly for children, who are known to be especially vulnerable to these exposures. The results support further environmental and social policy changes to prevent the serious health impacts of air pollution from fossil fuel emissions.

Applying data science methodologies with artificial intelligence variant reinterpretation to map and estimate genetic disorder prevalence utilizing clinical data

Data science methodologies can be utilized to ascertain and analyze clinical genetic data that is often unstructured and rarely used outside of patient encounters. Genetic variants from all genetic testing resulting to a large pediatric healthcare system for a 5-year period were obtained and reinterpreted utilizing the previously validated Franklin© Artificial Intelligence (AI). Using PowerBI©, the data were further matched to patients in the electronic healthcare record to associate with demographic data to generate a variant data table and mapped by ZIP codes. Three thousand and sixty-five variants were identified and 98% were matched to patients with geographic data. Franklin© changed the interpretation for 24% of variants. One hundred and fifty-six clinically actionable variant reinterpretations were made. A total of 739 Mendelian genetic disorders were identified with disorder prevalence estimation. Mapping of variants demonstrated hot-spots for pathogenic genetic variation such as PEX6-associated Zellweger Spectrum Disorder. Seven patients were identified with Bardet-Biedl syndrome and seven patients with Rett syndrome amenable to newly FDA-approved therapeutics. Utilizing readily available software we developed a database and Exploratory Data Analysis (EDA) methodology enabling us to systematically reinterpret variants, estimate variant prevalence, identify conditions amenable to new treatments, and localize geographies enriched for pathogenic variants.

Accountability analysis of health benefits related to National Action Plan on Air Pollution Prevention and Control in China

China is one of the largest producers and consumers of coal in the world. The National Action Plan on Air Pollution Prevention and Control in China (2013-2017) particularly aimed to reduce emissions from coal combustion. Here, we show whether the acute health effects of PM2.5 changed from 2013 to 2018 and factors that might account for any observed changes in the Beijing-Tianjin-Hebei (BTH) and the surrounding areas where there were major reductions in PM2.5 concentrations. We used a two-stage analysis strategy, with a quasi-Poisson regression model and a random effects meta-analysis, to assess the effects of PM2.5 on mortality in the 47 counties of BTH. We found that the mean daily PM2.5 levels and the SO42- component ratio dramatically decreased in the study period, which was likely related to the control of coal emissions. Subsequently, the acute effects of PM2.5 were significantly decreased for total and circulatory mortality. A 10 μg/m3 increase in PM2.5 concentrations was associated with a 0.16% (95% CI: 0.08, 0.24%) and 0.02% (95% CI: -0.09, 0.13%) increase in mortality from 2013 to 2015 and from 2016 to 2018, respectively. The changes in air pollution sources or PM2.5 components appeared to have played a core role in reducing the health effects. The air pollution control measures implemented recently targeting coal emissions taken in China may have resulted in significant health benefits.

Communities catalyzing change with data to mitigate an invisible menace, traffic-related air pollution

OBJECTIVES

To identify strategies and tactics communities use to translate research into environmental health action.

METHODS

We employed a qualitative case study design to explore public health action conducted by residents, organizers, and public health planners in two Massachusetts communities as part of a community based participatory (CBPR) research study. Data sources included key informant interviews (n = 24), reports and direct observation of research and community meetings (n = 10) and project meeting minutes from 2016-2021. Data were coded deductively drawing on the community organizing and implementation frameworks.

RESULTS

In Boston Chinatown, partners drew broad participation from community-based organizations, residents, and municipal leaders, which resulted in air pollution mitigation efforts being embedded in the master planning process. In Somerville, partners focused on change at multiple levels, developer behavior, and separate from the funded research, local legislative efforts, and litigation.

CONCLUSIONS

CBPR affords communities the ability to environmental health efforts in a way that is locally meaningful, leveraging their respective strengths. External facilitation can support the continuity and sustainment of community led CBPR efforts.

Dynamic Traffic Data in Machine-Learning Air Quality Mapping Improves Environmental Justice Assessment

Air pollution poses a critical public health threat around many megacities but in an uneven manner. Conventional models are limited to depict the highly spatial- and time-varying patterns of ambient pollutant exposures at the community scale for megacities. Here, we developed a machine-learning approach that leverages the dynamic traffic profiles to continuously estimate community-level year-long air pollutant concentrations in Los Angeles, U.S. We found the introduction of real-world dynamic traffic data significantly improved the spatial fidelity of nitrogen dioxide (NO2), maximum daily 8-h average ozone (MDA8 O3), and fine particulate matter (PM2.5) simulations by 47%, 4%, and 15%, respectively. We successfully captured PM2.5 levels exceeding limits due to heavy traffic activities and providing an "out-of-limit map" tool to identify exposure disparities within highly polluted communities. In contrast, the model without real-world dynamic traffic data lacks the ability to capture the traffic-induced exposure disparities and significantly underestimate residents' exposure to PM2.5. The underestimations are more severe for disadvantaged communities such as black and low-income groups, showing the significance of incorporating real-time traffic data in exposure disparity assessment.

Size distribution and lung-deposition of ambient particulate matter oxidative potential: A contrast between dithiothreitol and ascorbic acid assays

Particulate matter (PM) inhaled into human lungs causes oxidative stress and adverse health effects through antioxidant depletion (oxidative potential, OP). However, there is limited knowledge regarding the association between the lung-deposited dose (LDD) of PM and OP in extrathoracic (ET), tracheobronchial (TB), and pulmonary (P) regions of human lungs. Dithiothreitol (DTT) and ascorbic acid (AA) assays were employed to measure the OP of PM size fractions to investigate OP distribution in human lungs and identify the chemical drivers. Quasi-ultrafine particles (quasi-UFP, ≤0.49 μm) exhibited high OP deposition in the TB and P regions, while coarse particles (CP, ≥3.0 μm) dominated in the ET region. A plot of extrinsic (per air volume) and intrinsic (per PM mass) OP versus LDD revealed that the OP for fine and coarse particles was greatest in the ET region, whereas the OP of quasi-UFP was greatest in alveoli. The study also demonstrated that extrinsic OP and PM doses are not strongly related. The decline in OP with increasing PM dose reveals the need for further investigation of the antagonistic effects of the chemical compositions. Overall, the results presented herein help address the gap in knowledge regarding the association between the OP and LDD of ambient particles in specific regions of human lungs.

The impact of the air pollution on health in New York City

New York City is attempting to find a solution to an issue that many states and cities face: how to minimize air pollution so that it has fewer negative impacts on human health. Despite having the highest population in the United States (US), New York City typically has reasonably clean air. As the City and State of New York have worked to reduce emissions from local and regional sources, the air quality in New York City has improved during the past few decades. Despite these advancements, air pollution still poses a severe hazard to the health of everyone living in New York's environment. Various diseases including respiratory, circulatory, neurological, gastrointestinal, and urinary illnesses, which can be fatal, are intimately associated with air pollution. This review article will concentrate on how air pollution affects respiratory diseases such as asthma in children. In addition to analyzing the severe effects of air pollution on the vulnerable population, this review article will highlight the health repercussions of air pollution on New York City and its residents. furthermore, we argue for potential ideas and discoveries while also putting up a policy option to lower air pollution.

Towards sustainable and net-zero cities: A review of environmental modelling and monitoring tools for optimizing emissions reduction strategies for improved air quality in urban areas

Climate change is a defining challenge for today's society and its consequences pose a great threat to humanity. Cities are major contributors to climate change, accounting for over 70% of global greenhouse gas emissions. With urbanization occurring at a rapid rate worldwide, cities will play a key role in mitigating emissions and addressing climate change. Greenhouse gas emissions are strongly interlinked with air quality as they share emission sources. Consequently, there is a great opportunity to develop policies which maximize the co-benefits of emissions reductions on air quality and health. As such, a narrative meta-review is conducted to highlight state-of-the-art monitoring and modelling tools which can inform and monitor progress towards greenhouse gas emission and air pollution reduction targets. Urban greenspace will play an important role in the transition to net-zero as it promotes sustainable and active transport modes. Therefore, we explore advancements in urban greenspace quantification methods which can aid strategic developments. There is great potential to harness technological advancements to better understand the impact of greenhouse gas reduction strategies on air quality and subsequently inform the optimal design of these strategies going forward. An integrated approach to greenhouse gas emission and air pollution reduction will create sustainable, net-zero and healthy future cities.

The Effects of Wildfire Smoke on Asthma and Allergy

PURPOSE OF REVIEW

To review the recent literature on the effects of wildfire smoke (WFS) exposure on asthma and allergic disease, and on potential mechanisms of disease.

RECENT FINDINGS

Spatiotemporal modeling and increased ground-level monitoring data are allowing a more detailed picture of the health effects of WFS exposure to emerge, especially with regard to asthma. There is also epidemiologic and some experimental evidence to suggest that WFS exposure increases allergic predisposition and upper airway or sinonasal disease, though much of the literature in this area is focused more generally on PM2.5 and is not specific for WFS. Experimental evidence for mechanisms includes disruption of epithelial integrity with downstream effects on inflammatory or immune pathways, but experimental models to date have not consistently reflected human disease in this area. Exposure to WFS has an acute detrimental effect on asthma. Potential mechanisms are suggested by in vitro and animal studies.

A hyperlocal hybrid data fusion near-road PM2.5 and NO2 annual risk and environmental justice assessment across the United States

Exposure to traffic-related air pollutants (TRAPs) has been associated with numerous adverse health effects. TRAP concentrations are highest meters away from major roads, and disproportionately affect minority (i.e., non-white) populations often considered the most vulnerable to TRAP exposure. To demonstrate an improved assessment of on-road emissions and to quantify exposure inequity in this population, we develop and apply a hybrid data fusion approach that utilizes the combined strength of air quality observations and regional/local scale models to estimate air pollution exposures at census block resolution for the entire U.S. We use the regional photochemical grid model CMAQ (Community Multiscale Air Quality) to predict the spatiotemporal impacts at local/regional scales, and the local scale dispersion model, R-LINE (Research LINE source) to estimate concentrations that capture the sharp TRAP gradients from roads. We further apply the Regionalized Air quality Model Performance (RAMP) Hybrid data fusion technique to consider the model's nonhomogeneous, nonlinear performance to not only improve exposure estimates, but also achieve significant model performance improvement. With a R2 of 0.51 for PM2.5 and 0.81 for NO2, the RAMP hybrid method improved R2 by ~0.2 for both pollutants (an increase of up to ~70% for PM2.5 and ~31% NO2). Using the RAMP Hybrid method, we estimate 264,516 [95% confidence interval [CI], 223,506-307,577] premature deaths attributable to PM2.5 from all sources, a ~1% overall decrease in CMAQ-estimated premature mortality compared to RAMP Hybrid, despite increases and decreases in some locations. For NO2, RAMP Hybrid estimates 138,550 [69,275-207,826] premature deaths, a ~19% increase (22,576 [11,288 - 33,864]) compared to CMAQ. Finally, using our RAMP hybrid method to estimate exposure inequity across the U.S., we estimate that Minorities within 100 m from major roads are exposed to up to 15% more PM2.5 and up to 35% more NO2 than their White counterparts.

Advances in Simulating the Global Spatial Heterogeneity of Air Quality and Source Sector Contributions: Insights into the Global South

High-resolution simulations are essential to resolve fine-scale air pollution patterns due to localized emissions, nonlinear chemical feedbacks, and complex meteorology. However, high-resolution global simulations of air quality remain rare, especially of the Global South. Here, we exploit recent developments to the GEOS-Chem model in its high-performance implementation to conduct 1-year simulations in 2015 at cubed-sphere C360 (∼25 km) and C48 (∼200 km) resolutions. We investigate the resolution dependence of population exposure and sectoral contributions to surface fine particulate matter (PM2.5) and nitrogen dioxide (NO2), focusing on understudied regions. Our results indicate pronounced spatial heterogeneity at high resolution (C360) with large global population-weighted normalized root-mean-square difference (PW-NRMSD) across resolutions for primary (62-126%) and secondary (26-35%) PM2.5 species. Developing regions are more sensitive to spatial resolution resulting from sparse pollution hotspots, with PW-NRMSD for PM2.5 in the Global South (33%), 1.3 times higher than globally. The PW-NRMSD for PM2.5 for discrete southern cities (49%) is substantially higher than for more clustered northern cities (28%). We find that the relative order of sectoral contributions to population exposure depends on simulation resolution, with implications for location-specific air pollution control strategies.

Micromobility Vehicles, Obstructions, and Rider Safety Behaviors in New York City Bike Lanes

Micromobility vehicles (MMVs) have become increasingly popular, particularly in urban areas where infrastructure has improved in recent years to facilitate their use. The purpose of this study was to observe protected bike lanes in 10 zones of Manhattan, NYC to: (1) describe the MMVs in bike lanes by type, phone and helmet use; and (2) document MMV users' responses to obstructions. Approximately 1 in 4 of all riders (260/998) were wearing a helmet. Fewer than 2% were observed using a phone while moving. Fewer than 9% of Citi Bike users were wearing a helmet. In contrast, over one-third of non-Citi Bike users were wearing a helmet (228 of 670, 34.03%). This difference was determined to be significant by a chi-squared test (a = 0.05) with a p-value less than 0.0001. Of the 988 MMVs observed in this study, 398 (40.28%) were motorized and 590 (59.72%) were non-motorized. A similar proportion of users of motorized riders versus non-motorized vehicles were wearing a helmet (28.14%, 112/398 versus 24.41%, 144/590). A total of 232 riders (23.50%) encountered an obstruction in their bike lane. Of these obstructions in a bike lane, 82.33% (191/232) were a car/vehicle and 17.67% (41/232) was garbage. A large majority of riders (87.93%) reacted by riding into the traffic lane. These findings suggest that further research and local education, enforcement, and legislative efforts are needed to examine and implement best practices in the safe operation of MMVs, decreasing bike lane obstructions, promoting helmet use, and raising awareness of MMV legislation.

Assessment of the health benefits to children of a transportation climate policy in New York City

BACKGROUND

Assessments of health and environmental effects of clean air and climate policies have revealed substantial health benefits due to reductions in air pollution, but have included few pediatric outcomes or assessed benefits at the neighborhood level.

OBJECTIVES

We estimated benefits across a suite of child health outcomes in 42 New York City (NYC) neighborhoods under the proposed regional Transportation and Climate Initiative. We also estimated their distribution across racial/ethnic and socioeconomic groups.

METHODS

We estimated changes in ambient fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations associated with on-road emissions under nine different predefined cap-and-invest scenarios. Health outcomes, including selected adverse birth, respiratory, and neurodevelopmental outcomes, were estimated using a program similar to the U.S. EPA BenMAP program. We stratified the associated monetized benefits across racial/ethnic and socioeconomic groups.

RESULTS

The benefits varied widely over the different cap-and-investment scenarios. For a 25% reduction in carbon emissions from 2022 to 2032 and a strategy prioritizing public transit investments, NYC would have an estimated 48 fewer medical visits for childhood asthma, 13,000 avoided asthma exacerbations not requiring medical visits, 640 fewer respiratory illnesses unrelated to asthma, and 9 avoided adverse birth outcomes (infant mortality, preterm birth, and term low birth weight) annually, starting in 2032. The total estimated annual avoided costs are $22 million. City-wide, Black and Hispanic children would experience 1.7 times the health benefits per capita than White and Non-Hispanic White children, respectively. Under the same scenario, neighborhoods experiencing the highest poverty rates in NYC would experience about 2.5 times the health benefits per capita than the lowest poverty neighborhoods.

CONCLUSION

A cap-and-invest strategy to reduce carbon emissions from the transportation sector could provide substantial health and monetized benefits to children in NYC through reductions in criteria pollutant concentrations, with greater benefits among Black and Hispanic children.