While the health impacts of larger particulate matter, such as PM₁₀ and PM₂.₅, have been studied extensively, research regarding ultrafine particles (UFPs or PM₀.₁) and particle surface area concentration (PSC) is lacking. This case-crossover study assessed the associations between exposure to PSC and UFP number concentration (UFPnc) and hospital admissions for cardiovascular diseases (CVDs) in New York State (NYS), 2013–2018. We used a time-stratified case-crossover design to compare the PSC and UFPnc levels between hospitalization days and control days (similar days without admissions) for each CVD case. We utilized NYS hospital discharge data to identify all CVD cases who resided in NYS. UFP simulation data from GEOS-Chem-APM, a state-of-the-art chemical transport model, was used to define PSC and UFPnc. Using a multi-pollutant model and conditional logistic regression, we assessed excess risk (ER)% per inter-quartile change of PSC and UFPnc after controlling for meteorological factors, co-pollutants, and time-varying variables. We found immediate and lasting associations between PSC and overall CVDs (lag0–lag0-6: ERs% (95% CI%) ranges: 0.4 (0.1,0.7) - 0.9 (0.7–1.2), and delayed and prolonged ERs%: 0.1–0.3 (95% CIs: 0.1–0.5) between UFPnc and CVDs (lag0-3–lag0-6). Exposure to larger PSC was associated with immediate ER increases in stroke, hypertension, and ischemic heart diseases (1.1%, 0.7%, 0.8%, respectively, all p < 0.05). The adverse effects of PSC on CVDs were highest among children (5–17 years old), in the fall and winter, and during cold temperatures. In conclusion, we found an immediate, lasting effects of PSC on overall CVDs and a delayed, prolonged impact of UFPnc. PSC was a more sensitive indicator than UFPnc. The PSC effects were higher among certain CVD subtypes, in children, in certain seasons, and during cold days. Further studies are needed to validate our findings and evaluate the long-term effects.

Satellite-derived aerosol optical depth (AOD) has been widely used to predict ground-level fine particulate matter (PM₂.₅) concentrations, although its utility can be limited due to missing values. Despite recent attempts to address this issue by imputing missing satellite AOD values, the uncertainty associated with the AOD imputation and its impacts on PM₂.₅ predictions have been understudied. To fill this gap, we developed a missing data imputation model for the AOD derived from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) and PM₂.₅ prediction models using several machine learning methods. We also examined how the uncertainty associated with the imputed AOD and a choice of machine learning algorithm were propagated to PM₂.₅ predictions. The application of the proposed imputation model to the data from New York State in the U.S. achieved a superior performance than those related studies, with a cross-validated R² of 0.94 and a Root Mean Square Error of 0.017. We also found that there was considerable uncertainty in PM₂.₅ predictions associated with the use of imputed AOD values, although it was not as high as the uncertainty from the machine learning algorithms used in PM₂.₅ prediction models. We concluded that the quantification of uncertainties for both AOD imputation and its propagation to AOD-based PM₂.₅ prediction is necessary for accurate and reliable PM₂.₅ predictions.

Pregnant women are widely exposed to organophosphate (OP) pesticides, which are potentially neurotoxicant for the developing fetus. We aimed to identify principal demographic and dietary predictors of OP pesticide exposure among 450 pregnant women participating in the New York University Children’s Health and Environment Study (enrolled 2016–19). Urinary concentrations of six dialkyl phosphate (DAP) metabolites (3 dimethyl (DM) metabolites and 3 diethyl (DE) metabolites) of OP pesticides were determined at three time points across pregnancy. At mid-gestation, the Diet History Questionnaire II was used to assess women’s dietary intake over the past year. Demographic characteristics were obtained using questionnaires and/or electronic health records. We used linear mixed models to evaluate the associations of demographic and food groups with DAP metabolite levels, and partial-linear single-index (PLSI) models to analyze the contribution proportions of food groups to DAP metabolite concentrations and the dose-response relationships between them. We observed that pregnant women in NYC had lower levels of OP pesticide metabolites than pregnant populations in Europe, Asia, and other regions in the U.S. Having lower pre-pregnancy body mass index and being Asian, employed, and single were associated with higher DAP metabolite concentrations. Fruit and grain intakes were associated with higher ∑DM, ∑DE, and ∑DAP levels. ∑DE concentrations increased 9.0% (95% confidence interval (CI) = 1.2%, 17.4%) per two-fold increase in dairy consumption, whereas ∑DE concentrations decreased 1.8% (95%CI = −3.1%, −0.4%) per two-fold increase in seafood consumption. The PLSI model indicated that among the food mixture, fruit and grains were the main food groups contributed to higher levels of ∑DAP, while meat contributed to lower levels of ∑DAP. The contribution proportions of fruit, grains, and meat were 18.7%, 17.9%, and 39.3%, respectively. Our results suggest that fruit, grains, and meat are major dietary components associated with OP pesticide exposure in urban pregnant women.

Food carts are common along streets in cities throughout the world. In North America, food cart vendors generally use propane, charcoal, or both propane and charcoal (P and C) for food preparation. Although cooking emissions are known to be a major source of indoor air pollution, there is limited knowledge on outdoor cooking’s impact on the ambient environment and, in particular, the relative contribution of the different cooking fuels. This field study investigated the air pollution the public is exposed to in the micro-environment around 19 food carts classified into 3 groups: propane, charcoal, and P and C carts. Concentrations near the food carts were measured using both real-time and filter-based methods. Mean real-time concentrations of PM₂.₅, BC₂.₅, and particle counts were highest near the charcoal food carts: 196 μg/m³, 5.49 μg/m³, and 69,000 particles/cm³, respectively, with peak exposures of 1520 μg/m³, 67.9 μg/m³, and 235,000 particles/cm³, respectively. In order of pollution emission impacts: charcoal > P and C > propane carts. Thus, significant differences in air pollution emissions occurred in the vicinity of mobile food carts, depending on the fuel used in food preparation. Local air pollution polices should consider these emission factors in regulating food cart vendor operations.

Dissolved organic carbon (DOC) is not only a critical component of global and regional carbon budgets, but also an important precursor for carcinogenic disinfection byproducts (DBP) generated during drinking water disinfection process. The lack of process based watershed scale model for carbon cycling has been a limiting factor impeding effective watershed management to control DOC fluxes to source waters. Here, we integrated terrestrial and aquatic carbon processes into the widely tested Soil and Water Assessment Tool (SWAT) watershed model to enable watershed-scale DOC modeling (referred to as SWAT-DOC hereafter). The modifications to SWAT mainly fall into two groups: (1) DOC production in soils and its transport to aquatic environment by different hydrologic processes, and (2) riverine transformation of DOC and their interactions with particular organic carbon (POC), inorganic carbon and algae (floating and bottom). We tested the new SWAT-DOC model in the Cannonsville watershed, which is part of the New York City (NYC) water supply system, using long-term DOC load data (from 1998 to 2012) derived from 1399 DOC samplings. The calibration and verification results indicate that SWAT-DOC achieved satisfactory performance for both streamflow and DOC at daily and monthly temporal scales. The parameter sensitivity analysis indicates that DOC loads in the Cannonsville watershed are controlled by the DOC production in soils and its transport in both terrestrial and aquatic environments. Further model uncertainty analysis indicates high uncertainties associated with peak DOC loads, which are attributed to underestimation of high streamflows. Therefore, future efforts to enhance SWAT-DOC to better represent runoff generation processes hold promise to further improve DOC load simulation. Overall, the wide use of SWAT and the satisfactory performance of SWAT-DOC make it a useful tool for DOC modeling and mitigation at the watershed scale.

Polybrominated diphenyl ethers (PBDEs) are environmentally persistent chemicals that structurally resemble legacy pollutants, such as polychlorinated biphenyls (PCBs). PBDEs were added to consumer products for over 30 years, before being phased out due to evidence of toxicity. We examined temporal changes in prenatal exposure to PBDEs, as well as other sources of variation. We measured PBDEs in umbilical cord plasma from 327 minority infants born in New York City between 1998 and 2006. We used linear regression to examine changes in concentrations over time and in relation to lifestyle characteristics collected during pregnancy. We detected BDE-47 in 80% of samples with a geometric mean concentration of 14.1 ng/g lipid. Ethnicity was the major determinant of PBDE exposure; African American infants had 58% higher geometric mean cord plasma concentrations of BDE-47 (p < 0.01) compared to Dominican infants. Notably, African American mothers were more likely to be born in the United States, which itself was associated with 40% (p < 0.01) higher concentrations. We observed small decreases in PBDE concentrations by date of birth and no difference before and after their phase-out in 2004. Final multivariable models explained 8–12% of variability in PBDE concentrations depending on the congener. Our finding that prenatal exposure to PBDEs decreased only modestly between 1998 and 2006 is consistent with the persistent properties of PBDEs and their ongoing release from existing consumer products.

Previous studies reported triggering of acute cardiovascular events by short-term increasedPM₂.₅ concentrations. From 2007 to 2013, national and New York state air quality policies and economic influences resulted in reduced concentrations of PM₂.₅ and other pollutants across the state. We estimated the rate of cardiovascular hospital admissions associated with increased PM₂.₅ concentrations in the previous 1–7 days, and evaluated whether they differed before (2005–2007), during (2008–2013), and after these concentration changes (2014–2016).Using the Statewide Planning and Research Cooperative System (SPARCS) database, we retained all hospital admissions with a primary diagnosis of nine cardiovascular disease (CVD) subtypes, for residents living within 15 miles of PM₂.₅ monitoring sites in Buffalo, Rochester, Albany, Queens, Bronx, and Manhattan from 2005 to 2016 (N = 1,922,918). We used a case-crossover design and conditional logistic regression to estimate the admission rate for total CVD, and nine specific subtypes, associated with increased PM₂.₅ concentrations.Interquartile range (IQR) increases in PM₂.₅ on the same and previous 6 days were associated with 0.6%–1.2% increases in CVD admission rate (2005–2016). There were similar patterns for cardiac arrhythmia, ischemic stroke, congestive heart failure, ischemic heart disease (IHD), and myocardial infarction (MI). Ambient PM₂.₅ concentrations and annual total CVD admission rates decreased across the period. However, the excess rate of IHD admissions associated with each IQR increase in PM₂.₅ in previous 2 days was larger in the after period (2.8%; 95%CI = 1.5%–4.0%) than in the during (0.6%; 95%CI = 0.0%–1.2%) or before periods (0.8%; 95%CI = 0.2%–1.3%), with similar patterns for total CVD and MI, but not other subtypes.While pollutant concentrations and CVD admission rates decreased after emission changes, the same PM₂.₅ mass was associated with a higher rate of ischemic heart disease events. Future work should confirm these findings in another population, and investigate whether specific PM components and/or sources trigger IHD events.

Initiatives to displace petroleum and climate change mitigation have driven a recent increase in space heating with biomass combustion. However, there is ample evidence that biomass combustion emits significant quantities of health damaging pollutants. We investigated the near-source micro-environmental air quality impact of a biomass-fueled combined heat and power system equipped with an electrostatic precipitator (ESP) in Syracuse, NY. Two rooftop sampling stations with PM2.5 and CO2 analyzers were established in such that one could capture the plume while the other one served as the background for comparison depending on the wind direction. Four sonic anemometers were deployed around the stack to quantify spatially and temporally resolved local wind patterns. Fuel-based emission factors were derived based on near-source measurement. The Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model was then applied to simulate the spatial variations of primary PM2.5 without ESP. Our analysis shows that the absence of ESP could lead to an almost 7 times increase in near-source primary PM2.5 concentrations with a maximum concentration above 100 μg m−3 at the building rooftop. The above-ground “hotspots” would pose potential health risks to building occupants since particles could penetrate indoors via infiltration, natural ventilation, and fresh air intakes on the rooftop of multiple buildings. Our results demonstrated the importance of emission control for biomass combustion systems in urban area, and the need to take above-ground pollutant “hotspots” into account when permitting distributed generation. The effects of ambient wind speed and stack temperature, the suitability of airport meteorological data on micro-environmental air quality were explored, and the implications on mitigating near-source air pollution were discussed.

Although the adverse impact of fine particulate matter (i.e., PM2.5) on human health has been well acknowledged, little is known of the health effects of its specific constituents. Over the past decade, the annual average dust concentrations in Beijing were approximately ∼14 μg m−3, a value that poses a great threat to the city's 20 million residents. In this study, we quantify the potential long-term health damages in Beijing resulting from the dust exposure that occurred from 2000 to 2011. Each year in Beijing, nearly 4000 (95% CI: 1000–7000) premature deaths may be associated with long-term dust exposure, and ∼20% of these deaths are attributed to lung cancer. A decomposition analysis of the inter-annual variability of premature deaths in Beijing indicates that dust concentrations determine the year-to-year tendency, whereas population growth and lung cancer mortality rates drive the increasing tendency of premature death. We suggest that if Beijing takes effective measures towards reducing dust concentrations (e.g., controlling the resuspension of road dust and the fugitive dust from construction sites) to a level comparable to that of New York City's, the associated premature deaths will be significantly reduced. This recommendation offers “low-hanging fruit” suggestions for pollution control that would greatly benefit the public health in Beijing.

Bromophenols (BRPs) have been widely detected in human tissues, however, relative proportions from natural products and/or anthropogenic flame retardants are not clear. 21 polybrominated diphenyl ethers (PBDEs), 15 MeO/OH-PBDEs, and 10 BRPs were simultaneously quantified in adipose collected from people from New York City, USA. An in vitro assay utilizing human liver microsomes was performed for detected predominant organobromine. High concentrations of 2,4,6-triBRP and PBDEs were observed, and extremely low concentrations of naturally occurring MeO/OH-PBDEs were detected. Similar biotransformatioin rates of BRPs and MeO/OH-PBDEs indicated that the relative high concentration of 2,4,6-triBRP in humans was not of natural origin. Significant correlation observed between concentrations of 2,4,6-triBRP and BDE-209 suggested that the two chemicals may share a common source. Both 2,4,6-triBRP and BDE-209 were detected in commercial ABS resins, suggesting that plastic products made from ABS resins could be potential sources of co-exposure of the two compounds for humans.