Real-Time Prediction of Size-Resolved Ultrafine Particulate Matter on Freeways (original) (raw)
Related papers
2017
1 2 The public raises concerns about the exposure to particulate matter (PM) which has been strongly 3 associated with illness and mortality. However, most of the studies rely on the measurements from 4 stationary monitoring sites which cannot capture the actual PM exposure for those people in or 5 near the source. In this study, we first set up a comprehensive mobile monitoring platform to 6 measure both PM concentration and traffic conditions on some major highways in Southern 7 California. Then, we developed an integrated database to fuse different data sources and to 8 facilitate the investigation of relationship between traffic conditions and highway PM 9 concentration. Using the fused datasets and combining with Emission FACtor (EMFAC) model, 10 contour plots based on estimated PM emissions were generated with the overlay of particle 11 concentration measurements. Analyses of the results indicate that there are numerous particle 12 concentration peaks cause by traffic congesti...
Atmospheric Environment, 2012
Ultrafine particles (UFP; aerodynamic diameter < 0.1 mm) are a ubiquitous exposure in the urban environment and are elevated near highways. Most epidemiological studies of UFP health effects use central site monitoring data, which may misclassify exposure. Our aims were to: (1) examine the relationship between distant and proximate monitoring sites and their ability to predict hourly UFP concentration measured at residences in an urban community with a major interstate highway and; (2) determine if meteorology and proximity to traffic improve explanatory power. Short-term (1e3 weeks) residential monitoring of UFP concentration was conducted at 18 homes. Long-term monitoring was conducted at two near-highway monitoring sites and a central site. We created models of outdoor residential UFP concentration based on concentrations at the near-highway site, at the central site, at both sites together and without fixed sites. UFP concentration at residential sites was more highly correlated with those at a near-highway site than a central site. In regression models of each site alone, a 10% increase in UFP concentration at a near-highway site was associated with a 6% (95% CI: 6%, 7%) increase at residences while a 10% increase in UFP concentration at the central site was associated with a 3% (95% CI: 2%, 3%) increase at residences. A model including both sites showed minimal change in the magnitude of the association between the near-highway site and the residences, but the estimated association with UFP concentration at the central site was substantially attenuated. These associations remained after adjustment for other significant predictors of residential UFP concentration, including distance from highway, wind speed, wind direction, highway traffic volume and precipitation. The use of a central site as an estimate of personal exposure for populations near local emissions of traffic-related air pollutants may result in exposure misclassification.
An Hourly Regression Model for Ultrafine Particles in a Near-Highway Urban Area
Environmental Science & Technology, 2014
Estimating ultrafine particle number concentrations (PNC) near highways for exposure assessment in chronic health studies requires models capable of capturing PNC spatial and temporal variations over the course of a full year. The objectives of this work were to describe the relationship between near-highway PNC and potential predictors, and to build and validate hourly log-linear regression models. PNC was measured near Interstate 93 (I-93) in Somerville, MA (USA) using a mobile monitoring platform driven for 234 hours on 43 days between August 2009 and September 2010. Compared to urban background, PNC levels were consistently elevated within 100-200 m of I-93, with gradients impacted by meteorological and traffic conditions. Temporal and spatial variables including wind speed and direction, temperature, highway traffic, and distance to I-93 and major roads contributed significantly to the full regression model. Cross-validated model R 2 values ranged from 0.38-0.47, with higher values achieved (0.43-0.53) when short-duration PNC spikes were removed. The model predicts highest PNC near major roads and on cold days with low wind speeds. The model allows estimation of hourly ambient PNC at 20-m resolution in a near-highway neighborhood.
Modeling the Concentrations of On-Road Air Pollutants in Southern California
High concentrations of air pollutants on roadways, relative to ambient concentrations, contribute significantly to total personal exposure. Estimation of these exposures requires measurements or prediction of roadway concentrations. Our study develops, compares, and evaluates linear regression and nonlinear generalized additive models (GAMs) to estimate on-road concentrations of four key air pollutants, particle-bound polycyclic aromatic hydrocarbons (PB-PAH), particle number count (PNC), nitrogen oxides (NO x ), and particulate matter with diameter <2.5 μm (PM 2.5 ) using traffic, meteorology, and elevation variables. Critical predictors included wind speed and direction for all the pollutants, traffic-related variables for PB-PAH, PNC, and NO x , and air temperatures and relative humidity for PM 2.5 . GAMs explained 50%, 55%, 46%, and 71% of the variance for log or square-root transformed concentrations of PB-PAH, PNC, NO x , and PM 2.5 , respectively, an improvement of 5% to over 15% over the linear models. Accounting for temporal autocorrelation in the GAMs further improved the prediction, explaining 57−89% of the variance. We concluded that traffic and meteorological data are good predictors in estimating on-road traffic-related air pollutant concentrations and GAMs perform better for nonlinear variables, such as meteorological parameters.
Atmospheric Environment, 2012
h i g h l i g h t s < UFP size distributions were measured in real-time with a mobile platform. < Wind direction shown critical to ultrafine number and size downwind of freeways. < Particle number decreases up to half as winds deviate from perpendicular. < Particle size also increases, further reducing lung deposition and dose by w15%. a b s t r a c t High ambient ultrafine particle (UFP) concentrations may play an important role in the adverse health effects associated with living near busy roadways. However, UFP size distributions change rapidly as vehicle emissions dilute and age. These size changes can influence UFP lung deposition rates and dose because deposition in the respiratory system is a strong function of particle size. Few studies to date have measured and characterized changes in near-road UFP size distributions in real-time, thus missing transient variations in size distribution due to short-term fluctuations in wind speed, direction, or particle dynamics. In this study we measured important wind direction effects on near-freeway UFP size distributions and gradients using a mobile platform with 5-s time resolution. Compared to more commonly measured perpendicular (downwind) conditions, parallel wind conditions appeared to promote formation of broader and larger size distributions of roughly one-half the particle concentration. Particles during more parallel wind conditions also changed less in size with downwind distance and the fraction of lung-deposited particle number was calculated to be 15% lower than for downwind conditions, giving a combined decrease of about 60%. In addition, a multivariate analysis of several variables found meteorology, particularly wind direction and temperature, to be important in predicting UFP concentrations within 150 m of a freeway (R 2 ¼ 0.46, p ¼ 0.014).
Atmospheric Environment, 2009
Ultrafine particles (UFPs, diameter < 100 nm) and co-emitted pollutants from traffic are a potential health threat to nearby populations. During summertime in Raleigh, North Carolina, UFPs were simultaneously measured upwind and downwind of a major roadway using a spatial matrix of five portable industrial hygiene samplers (measuring total counts of 20-1000 nm particles). While the upper sampling range of the portable samplers extends past the defined ''ultrafine'' upper limit (100 nm), the 20-1000 nm number counts had high correlation (Pearson R ¼ 0.7-0.9) with UFPs (10-70 nm) measured by a co-located research-grade analyzer and thus appear to be driven by the ultrafine range. Highest UFP concentrations were observed during weekday morning work commutes, with levels at 20 m downwind from the road nearly fivefold higher than at an upwind station. A strong downwind spatial gradient was observed, linearly approximated over the first 100 m as an 8% drop in UFP counts per 10 m distance. This result agreed well with UFP spatial gradients estimated from past studies (ranging 5-12% drop per 10 m). Linear regression of other vehicle-related air pollutants measured in near real-time (10-min averages) against UFPs yielded moderate to high correlation with benzene (R 2 ¼ 0.76), toluene (R 2 ¼ 0.49), carbon monoxide (R 2 ¼ 0.74), nitric oxide (R 2 ¼ 0.80), and black carbon (R 2 ¼ 0.65). Overall, these results support the notion that near-road levels of UFPs are heavily influenced by traffic emissions and correlate with other vehicle-produced pollutants, including certain air toxics.
Modeling Spatial Patterns of Traffic-Related Air Pollutants in Complex Urban Terrain
Environmental Health Perspectives, 2011
The relationship between traffic emissions and mobile-source air pollutant concentrations is highly variable over space and time and therefore difficult to model accurately, especially in urban settings with complex terrain. Regression-based approaches using continuous real-time mobile measurements may be able to characterize spatiotemporal variability in trafficrelated pollutant concentrations but require methods to incorporate temporally varying meteorology and source strength in a physically interpretable fashion. oBjective: We developed a statistical model to assess the joint impact of both meteorology and traffic on measured concentrations of mobile-source air pollutants over space and time. Methods: In this study, traffic-related air pollutants were continuously measured in the Williamsburg neighborhood of Brooklyn, New York (USA), which is affected by traffic on a large bridge and major highway. One-minute average concentrations of ultrafine particulate matter (UFP), fine particulate matter [≤ 2.5 μm in aerodynamic diameter (PM 2.5 )], and particle-bound polycyclic aromatic hydrocarbons were measured using a mobile-monitoring protocol. Regression modeling approaches to quantify the influence of meteorology, traffic volume, and proximity to major roadways on pollutant concentrations were used. These models incorporated techniques to capture spatial variability, long-and short-term temporal trends, and multiple sources. results: We observed spatial heterogeneity of both UFP and PM 2.5 concentrations. A variety of statistical methods consistently found a 15-20% decrease in UFP concentrations within the first 100 m from each of the two major roadways. For PM 2.5 , temporal variability dominated spatial variability, but we observed a consistent linear decrease in concentrations from the roadways. conclusions: The combination of mobile monitoring and regression analysis was able to quantify local source contributions relative to background while accounting for physically interpretable parameters. Our results provide insight into urban exposure gradients.
Environmental Research, 2014
Background: Increasing evidence suggests that ultrafine particles (UFPs) may contribute to cardiorespiratory morbidity. We examined the relationship between near road UFPs and several traffic and built environment factors to identify predictors that may be used to estimate exposures in population-based studies. Black carbon (BC) was also examined. Methods: Data were collected on up to 6 occasions at 73 sites in Montreal, Canada over 6-week period during summer, 2012. After excluding highly correlated variables, road width, truck ratio (trucks/total traffic), building height, land zoning parameters, and meteorological factors were evaluated. Randomeffect models were used to estimate percent changes in UFP and BC concentrations with interquartile changes in each candidate predictor adjusted for meteorological factors. Results: Mean pollutant concentrations varied substantially across sites (UFP range: 1977-94, 798 particles/cm 3 ; BC range: 29-9460 ng/m 3 ). After adjusting for meteorology, interquartile increases in road width (14%, 95% CI: 0, 30), building height (13%, 95% CI: 5, 22), and truck ratio (13%, 95% CI: 3, 23) were the most important predictors of mean UFP concentrations. Road width (28%, 95% CI: 9, 51) and industrial zoning (18%, 95% CI: 2, 37) were the strongest predictors of maximum UFP concentrations. Industrial zoning (35%, 95% CI: 9, 67) was the strongest predictor of BC. Conclusions: A number of traffic and built environmental factors were identified as important predictors of near road UFP and BC concentrations. Exposure models incorporating these factors may be useful in evaluating the health effects of traffic related air pollution. Crown
Resolving Local-Scale Emissions for Modeling Air Quality near Roadways
Journal of The Air & Waste Management Association, 2008
A large body of literature published in recent years suggests increased health risk due to exposure of people to air pollution in close proximity to roadways. As a result, there is a need to more accurately represent the spatial concentration gradients near roadways to develop mitigation strategies. In this paper, we present a practical, readily adaptable methodology, using a "bottom-up" approach to develop a detailed highway vehicle emission inventory that includes emissions for individual road links. This methodology also takes advantage of geographic information system (GIS) software to improve the spatial accuracy of the activity information obtained from a Travel Demand Model. In addition, we present an air quality modeling application of this methodology in New Haven, CT. This application uses a hybrid modeling approach, in which a regional grid-based model is used to characterize average local ambient concentrations, and a Gaussian dispersion model is used to provide texture within the modeling domain because of spatial gradients associated with highway vehicle emissions and other local sources. Modeling results show substantial heterogeneity of pollutant concentrations within the modeling domain and strong spatial gradients associated with roadways, particularly for pollutants dominated by direct emissions.
A wide area of air pollutant impact downwind of a freeway during pre-sunrise hours
Atmospheric Environment, 2009
We have observed a wide area of air pollutant impact downwind of a freeway during pre-sunrise hours in both winter and summer seasons. In contrast, previous studies have shown much sharper air pollutant gradients downwind of freeways, with levels above background concentrations extending only 300 m downwind of roadways during the day and up to 500 m at night. In this study, real-time air pollutant concentrations were measured along a 3600 m transect normal to an elevated freeway 1-2 h before sunrise using an electric vehicle mobile platform equipped with fast-response instruments. In winter pre-sunrise hours, the peak ultrafine particle (UFP) concentration (w95 000 cm À3 ) occurred immediately downwind of the freeway. However, downwind UFP concentrations as high as w40 000 cm À3 extended at least 1200 m from the freeway, and did not reach background levels (w15 000 cm À3 ) until a distance of about 2600 m. UFP concentrations were also elevated over background levels up to 600 m upwind of the freeway. Other pollutants, such as NO and particle-bound polycyclic aromatic hydrocarbons, exhibited similar long-distance downwind concentration gradients. In contrast, air pollutant concentrations measured on the same route after sunrise, in the morning and afternoon, exhibited the typical daytime downwind decrease to background levels within w300 m as found in earlier studies. Although pre-sunrise traffic volumes on the freeway were much lower than daytime congestion peaks, downwind UFP concentrations were significantly higher during pre-sunrise hours than during the daytime. UFP and NO concentrations were also strongly correlated with traffic counts on the freeway. We associate these elevated pre-sunrise concentrations over a wide area with a nocturnal surface temperature inversion, low wind speeds, and high relative humidity. Observation of such wide air pollutant impact area downwind of a major roadway prior to sunrise has important exposure assessment implications since it demonstrates extensive roadway impacts on residential areas during pre-sunrise hours, when most people are at home.