Dataset Information

Characterizing Nitrogen Oxides and Fine Particulate Matter near Major Highways in the United States Using the National Near-Road Monitoring Network.

ABSTRACT: As part of the United States Environmental Protection Agency's 2010 Nitrogen Dioxide (NO₂) National Ambient Air Quality Standards (NAAQS) review, a national network of near-road sites was established to characterize pollutant behavior, interaction, and dispersion in the ambient near-road environment. Using spatial interpolation to estimate the near-road concentration increments of NO₂ and particulate matter with an aerodynamic diameter of 2.5 ?m and less (PM_2.5) relative to nearby non-near-road monitors, we found that the 2013-2018 national average increment is 6.9 ppb and 1.0 ?g m^-3 for NO₂ and PM_2.5, respectively. Analyses of the hourly near-road NO₂, nitric oxide (NO), and PM_2.5 increments showed distinct diurnal cycles; the NO₂ increment peaks at ?9 ppb during the early afternoon (2-4 pm local time) while the NO and PM_2.5 increments peak during the morning rush hour (5-8 am local time) at 25 ppb and 1.8 ?g m^-3 for NO and PM_2.5, respectively. Although long-term trends are not yet available for this network of sites, a similar analysis of the NO₂ and PM_2.5 increment at a quasi-near-road site outside of the official network in Elizabeth, NJ showed gradual decreases in the increment over time since the mid-2000s.

SUBMITTER: Gantt B

PROVIDER: S-EPMC7938425 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Characterizing Nitrogen Oxides and Fine Particulate Matter near Major Highways in the United States Using the National Near-Road Monitoring Network.

Gantt Brett B Owen R Chris RC Watkins Nealson N

Environmental science & technology 20210210 5

As part of the United States Environmental Protection Agency's 2010 Nitrogen Dioxide (NO2) National Ambient Air Quality Standards (NAAQS) review, a national network of near-road sites was established to characterize pollutant behavior, interaction, and dispersion in the ambient near-road environment. Using spatial interpolation to estimate the near-road concentration increments of NO2 and particulate matter with an aerodynamic diameter of 2.5 μm and less (PM2.5) ...[more]

PMID: 33566613

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Project description:ImportanceThe association between short-term exposure to air pollution and mortality has been widely documented worldwide; however, few studies have applied causal modeling approaches to account for unmeasured confounders that vary across time and space.ObjectiveTo estimate the association between short-term changes in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations and changes in daily all-cause mortality rates using a causal modeling approach.Design, setting, and participantsThis cross-sectional study used air pollution and mortality data from Jiangsu, China; California; central-southern Italy; and Germany with interactive fixed-effects models to control for both measured and unmeasured spatiotemporal confounders. A total of 8 963 352 deaths in these 4 regions from January 1, 2015, to December 31, 2019, were included in the study. Data were analyzed from June 1, 2021, to October 30, 2023.ExposureDay-to-day changes in county- or municipality-level mean PM2.5 and NO2 concentrations.Main outcomes and measuresDay-to-day changes in county- or municipality-level all-cause mortality rates.ResultsAmong the 8 963 352 deaths in the 4 study regions, a 10-μg/m3 increase in daily PM2.5 concentration was associated with an increase in daily all-cause deaths per 100 000 people of 0.01 (95% CI, 0.001-0.01) in Jiangsu, 0.03 (95% CI, 0.004-0.05) in California, 0.10 (95% CI, 0.07-0.14) in central-southern Italy, and 0.04 (95% CI, 0.02- 0.05) in Germany. The corresponding increases in mortality rates for a 10-μg/m3 increase in NO2 concentration were 0.04 (95% CI, 0.03-0.05) in Jiangsu, 0.03 (95% CI, 0.01-0.04) in California, 0.10 (95% CI, 0.05-0.15) in central-southern Italy, and 0.05 (95% CI, 0.04-0.06) in Germany. Significant effect modifications by age were observed in all regions, by sex in Germany (eg, 0.05 [95% CI, 0.03-0.06] for females in the single-pollutant model of PM2.5), and by urbanicity in Jiangsu (0.07 [95% CI, 0.04-0.10] for rural counties in the 2-pollutant model of NO2).Conclusions and relevanceThe findings of this cross-sectional study contribute to the growing body of evidence that increases in short-term exposures to PM2.5 and NO2 may be associated with increases in all-cause mortality rates. The interactive fixed-effects model, which controls for unmeasured spatial and temporal confounders, including unmeasured time-varying confounders in different spatial units, can be used to estimate associations between changes in short-term exposure to air pollution and changes in health outcomes.

Project description:ObjectiveAmbient fine particulate matter (PM2.5) pollution is currently a major public health concern in Chinese urban areas. However, PM2.5 exposure primarily occurs indoors. Given such, we conducted this study to characterize the indoor-outdoor relationship of PM2.5 mass concentrations for urban residences in Beijing.MethodsIn this study, 24-h real-time indoor and ambient PM2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The diurnal variation of pollutant concentrations was characterized. Pearson correlation analysis was used to examine the correlation between indoor and ambient PM2.5 mass concentrations. Regression analysis with ordinary least square was employed to characterize the influences of a variety of factors on PM2.5 mass concentration.ResultsHourly ambient PM2.5 mass concentrations were 3-280 ?g/m3 with a median of 58 ?g/m3, and hourly indoor counterpart were 4-193 ?g/m3 with a median of 34 ?g/m3. The median indoor/ambient ratio of PM2.5 mass concentration was 0.62. The diurnal variation of residential indoor and ambient PM2.5 mass concentrations tracked with each other well. Strong correlation was found between indoor and ambient PM2.5 mass concentrations on the community basis (coefficients: r ? 0.90, p < 0.0001), and the ambient data explained ? 84% variance of the indoor data. Regression analysis suggested that the variables, such as traffic conditions, indoor smoking activities, indoor cleaning activities, indoor plants and number of occupants, had significant influences on the indoor PM2.5 mass concentrations.ConclusionsPM2.5 of ambient origin made dominant contribution to residential indoor PM2.5 exposure in the non-heating season under the high ambient fine particle pollution condition. Nonetheless, the large inter-residence variability of infiltration factor of ambient PM2.5 raised the concern of exposure misclassification when using ambient PM2.5 mass concentrations as exposure surrogates. PM2.5 of indoor origin still had minor influence on indoor PM2.5 mass concentrations, particularly at 11:00-13:00 and 22:00-0:00. The predictive models suggested that particles from traffic emission, secondary aerosols, particles from indoor smoking, resuspended particles due to indoor cleaning and particles related to indoor plants contributed to indoor PM2.5 mass concentrations in this study. Real-time ventilation measurements and improvement of questionnaire design to involve more variables subject to built environment were recommended to enhance the performance of the predictive models.

Dataset Information

Characterizing Nitrogen Oxides and Fine Particulate Matter near Major Highways in the United States Using the National Near-Road Monitoring Network.

Publications

Characterizing Nitrogen Oxides and Fine Particulate Matter near Major Highways in the United States Using the National Near-Road Monitoring Network.

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