Douglas Houston

Performances of Different Global Positioning System Devices for Time-Location Tracking in Air Pollution Epidemiological Studies

Background Peoples time-location patterns are important in air pollution exposure assessment because pollution levels may vary considerably by location. A growing number of studies are using global positioning systems (GPS) to track peoples time-location patterns. Many portable GPS units that archive location are commercially available at a cost that makes their use feasible for epidemiological studies. Methods We evaluated the performance of five portable GPS data loggers and two GPS cell phones by examining positional accuracy in typical locations (indoor, outdoor, in-vehicle) and factors that influence satellite reception (building material, building type), acquisition time (cold and warm start), battery life, and adequacy of memory for data storage. We examined stationary locations (eg, indoor, outdoor) and mobile environments (eg, walking, traveling by vehicle or bus) and compared GPS locations to highly-resolved US Geological Survey (USGS) and Digital Orthophoto Quarter Quadrangle (DOQQ) maps. Results The battery life of our tested instruments ranged from <9 hours to 48 hours. The acquisition of location time after startup ranged from a few seconds to >20 minutes and varied significantly by building structure type and by cold or warm start. No GPS device was found to have consistently superior performance with regard to spatial accuracy and signal loss. At fixed outdoor locations, 65%-95% of GPS points fell within 20-m of the corresponding DOQQ locations for all the devices. At fixed indoor locations, 50%-80% of GPS points fell within 20-m of the corresponding DOQQ locations for all the devices except one. Most of the GPS devices performed well during commuting on a freeway, with >80% of points within 10-m of the DOQQ route, but the performance was significantly impacted by surrounding structures on surface streets in highly urbanized areas. Conclusions All the tested GPS devices had limitations, but we identified several devices which showed promising performance for tracking subjects’ time location patterns in epidemiological studies.

Automated time activity classification based on global positioning system (GPS) tracking data

BackgroundAir pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify peoples major time activity patterns from continuous GPS tracking data.MethodsWe developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model.ResultsIndoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data.ConclusionsOur models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns.

Can compact rail transit corridors transform the automobile city? Planning for more sustainable travel in Los Angeles

Directing growth towards compact rail corridors has become a key strategy for redirecting auto-oriented regions towards denser, mixed-use communities that support sustainable travel. Few have examined how travel of near-rail residents varies within corridors or whether corridor land use–travel interactions diverge from regional averages. The Los Angeles region has made substantial investments in transit-oriented development, and our survey analysis indicates that although rail corridor residents drove less and rode public transit more than the county average, households in an older subway corridor with more near-transit development had about 11 fewer daily miles driven and higher transit ridership than households along a newer light rail line, a difference likely associated with development patterns and the composition and preferences of residents. Rail transit corridors are not created equally, and transit providers and community planners should consider the social and development context of corridors in efforts to improve transit access and maximise development.

Disparities in exposure to automobile and truck traffic and vehicle emissions near the Los Angeles-long beach port complex

OBJECTIVES We assessed how traffic and mobile-source air pollution impacts are distributed across racial/ethnic and socioeconomically diverse groups in port-adjacent communities in southern Los Angeles County, which may experience divergent levels of exposure to port-related heavy-duty diesel truck traffic because of existing residential and land use patterns. METHODS We used spatial regression techniques to assess the association of neighborhood racial/ethnic and socioeconomic composition with residential parcel-level traffic and vehicle-related fine particulate matter exposure after accounting for built environment and land use factors. RESULTS After controlling for factors associated with traffic generation, we found that a higher percentage of nearby Black and Asian/Pacific Islander residents was associated with higher exposure, a higher percentage of Hispanic residents was associated with higher traffic exposure but lower vehicle particulate matter exposure, and areas with lower socioeconomic status experienced lower exposure. CONCLUSIONS Disparities in traffic and vehicle particulate matter exposure are nuanced depending on the exposure metric used, the distribution of the traffic and emissions, and pollutant dispersal patterns. Future comparative research is needed to assess potential disparities in other transportation and goods movement corridors.

Driving reduction after the introduction of light rail transit: Evidence from an experimental-control group evaluation of the Los Angeles Expo Line:

There is a pressing need to estimate the magnitude and dynamics of the behavioural effects of transportation investments and policy. This article innovates by applying an experimental-control group research design to the case of new light rail transit service in Los Angeles, California. Only a handful of previous studies use an experimental design to assess impacts of light rail transit, and this is the first to use an experimental design to measure impacts on vehicle miles travelled, a key determinant of greenhouse gas emissions from the transport sector. We administered an annual seven-day travel study to a panel of households in the vicinity of Los Angeles’ Expo light rail line before the 2012 start of rail service and twice after the line opened. We find that households living within walking distance (1 km) of the new light rail drove approximately 10 fewer miles per day relative to control households farther away. Rail transit trips among near-station households approximately tripled relative to households beyond walking distance. Such driving reductions among households within walking distance of new rail transit stations suggest that Los Angeles’ large rail transit investment, coupled with land use policy, has the potential to help achieve climate change policy goals. More broadly, experimental evaluation can provide insights into causality and patterns of travel behaviour change associated with planning policies.

Refining Time-Activity Classification of Human Subjects Using the Global Positioning System

Background Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns. Methods Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods. Results Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions. Conclusions The random forests classification model can achieve high accuracy for the four major time-activity categories. The model also performed well with just GPS, road and tax parcel data. However, caution is warranted when generalizing the model developed from a small number of subjects to other populations.

Can New Light Rail Reduce Personal Vehicle Carbon Emissions? A Before‐After, Experimental‐Control Evaluation in Los Angeles

This paper uses a before‐after, experimental‐control group method to evaluate the impacts of the newly opened Expo light rail transit line in Los Angeles on personal vehicle greenhouse gas (GHG) emissions. We applied the California Air Resources Boards EMFAC 2011 emission model to estimate the amount of daily average CO2 emissions from personal vehicle travel for 160 households across two waves, before and after the light rail opened. The 160 households were part of an experimental–control group research design. Approximately half of the households live within a half‐mile of new Expo light rail stations (the experimental group) and the balance of the sampled households live beyond a half‐mile from Expo light rail stations (the control group). Households tracked odometer mileage for all household vehicles for seven days in two sample waves, before the Expo Line opened (fall, 2011) and after the Expo Line opened (fall, 2012). Our analysis indicates that opening the Expo Line had a statistically significant impact on average daily CO2 emissions from motor vehicles. We found that the CO2 emission of households who reside within a half‐mile of an Expo Line station was 27.17 percent smaller than those living more than a half‐mile from a station after the opening of the light rail, while no significant difference exists before the opening. A difference‐in‐difference model suggests that the opening of the Expo Line is associated with 3,145 g less of household vehicle CO2 emissions per day as a treatment effect. A sensitivity analysis indicates that the emission reduction effect is also present when the experimental group of households is redefined to be those living within a kilometer from the new light rail stations.

Arts Accessibility to Major Museums and Cultural/Ethnic Institutions in Los Angeles: Can School Tours Overcome Neighborhood Disparities?

Major arts and cultural institutions have expanded their exhibits and programs to reflect societys growing diversity, but we know little about potential neighborhood disparities in arts participation within metropolitan areas and how it varies across institutions and different forms of engagement. Unlike membership, which tends to be ‘market’ driven, museum school tour programs often target underserved schools to engage diverse communities. We provide the first assessment to our knowledge of whether school tours provide a counterweight to more expensive forms of participation and whether ethnic-oriented institutions have been able to overcome the distance that often separates disadvantaged communities from institutions. Our analysis of participation rates for five major institutions in Los Angeles, California, indicates that, despite progress, barriers persist. Although affluent areas provide an important membership base, school tours offer a valuable tool for attracting traditional and ethnic-specific audiences and communities. The results support greater integration of city and cultural planning and suggest that institutions should redouble efforts to overcome sociocultural and geographic barriers.

Safe Routes to Play? Pedestrian and Bicyclist Crashes Near Parks in Los Angeles

BACKGROUND Areas near parks may present active travelers with higher risks than in other areas due to the confluence of more pedestrians and bicyclists, younger travelers, and the potential for increased traffic volumes. These risks may be amplified in low-income and minority neighborhoods due to generally higher rates of active travel or lack of safety infrastructure. This paper examines active travel crashes near parks and builds on existing research around disparities in park access and extends research from the Safe Routes to School and Safe Routes to Transit movements to parks. METHODS We utilized the Green Visions Parks coverage, encompassing Los Angeles County and several other cities in the LA Metropolitan area. We used negative bionomial regression modeling techniques and ten years of geolocated pedestrian and bicyclist crash data to assess the number of active travel injuries within a quarter mile (~400m) buffer around parks. We controlled for differential exposures to active travel using travel survey data and Bayesian smoothing models. RESULTS Of 1,311,736 parties involved in 608,530 crashes, there were 896,359 injuries and 7317 fatalities. The number of active travel crash injuries is higher within a quarter-mile of a park, with a ratio of 1.52 per 100,000 residents, compared to areas outside that buffer. This higher rate near parks is amplified in neighborhoods with high proportions of minority and low-income residents. Higher traffic levels are highly predictive of active travel crash injuries. CONCLUSIONS Planners should consider the higher risks of active travel near parks and the socioeconomic modification of these risks. Additional traffic calming and safety infrastructure may be needed to provide safe routes to parks.

Environmental justice: Progress derailed

An introduction is presented for a study appearing in the issue on progress of environmental justice under polices from the U.S. Environmental Protection Agency (EPA) regarding emitting particulate matter (PM).