ANDY HONG

Hong, Andy, Byoungjun Kim, and Michael Widener

Noise is one of the most frequently complained nuisances and public health hazards in many cities (Adams et al., 2006). Chronic exposure to noise is known to increase stress levels (Schmidt et al., 2013), and even low-level background noise can cause annoyance, increase stress levels, and decrease work productivity (Baliatsas, van Kamp, van Poll, & Yzermans, 2016). While noise from traffic sources is often monitored and managed by physical intervention, noise from construction is often regulated by noise control bylaws, which typically prohibits construction activities during sleeping hours and holidays. Although construction activities are occasional across the city, citizens may be exposed to such nuisance consistently, especially when the city is growing rapidly. Given this background, this study investigates spatiotemporal relationship between urban development and neighborhood noise. We first assess the urban development patterns from the historical inventory of major development projects (2005 – 2016) in British Columbia. To understand neighborhood noise, this study takes advantage of a crowd-sourced 3-1-1 call data, a general hotline regarding maintenance issues in the city. Testing the linkage between building construction data with crowd-sourced noise data is a novel approach to examine the impact of urban developments on acoustical environments. Results inform planning policies and decisions for determining how effective urban noise regulations are and where to target more consorted effort to mitigate noise pollution in a rapidly growing city.

Publications

Preparing a manuscript for submission to Environment and Planning A

Andy Hong, Suresh Ratnam, Scott Fruin

Open streets initiatives, which temporarily close streets to car traffic but open to other modes of transport, have recently gained popularity as a means of promoting physical activity and bicycling. However, few studies have examined the impact of open streets on air pollution. This study investigates air pollution and traffic impacts of three open streets events in Los Angeles, California. Using a real-time mobile monitoring platform and a backpack outfitted with portable instruments, air pollution (particulate mass below 2.5 and 10 um; ultrafine particle number (UFP); black carbon; and particle-bound polycyclic aromatic hydrocarbons)  was measured before, during, and after each CicLAvia event. Results show that the CicLAvia events generally served as a traffic magnet, creating more traffic congestion than what is seen on typical Sundays. Events in Culver City and Downtown Los Angeles (DTLA) showed lower speeds and a 21 - 23% reduction in PM10,  but increased traffic and an 18% and 30% increase in UFP during the Culver City and DTLA events, respectively. Overall, however,  results indicate that large-scale events that close selected streets to traffic, while attracting significant numbers of vehicles and disrupting normal traffic flow on adjacent streets, can successfully have minor impacts to air quality if the average fleet emissions are as low as they are currently in Los Angeles.  

Publications

• Manuscript competed, scheduled to be submitted to the Science of the Total Environment in Winter 2017

Authors: Andy Hong

Light rail transit (LRT) has a reputation for being greener and healthier than automobile. However, very few empirical studies have examined the effects of shift from car to LRT on air pollution exposure. In this paper, I ask how much reduction of air pollution exposure can be achieved through mode shift from car to LRT. To answer this question, I conduct a controlled experiment using four plausible scenarios of mode shift and compare the differences through field measurements and Monte Carlo simulations. Results suggest that the effects of mode shift can be significantly altered by individual micro behaviors, such as ventilation setting and travel route choice. Results inform future research and practice regarding the importance of commuter’s micro behavior in assessing the health effects of mode shift from car to LRT.

Publications

• Manuscript under submission in Transportation Research Part D.

Andy Hong, Lisa Schweitzer, Lindsey Marr, Wan Yang

Large cities in the United States face multiple challenges in meeting federal air quality standards. One difficulty arises from the uncertainties in evaluating traffic-related air pollution, especially the formation of secondary pollutants such as ozone and some particulate matter. Current air quality models are not well suited to evaluate the impact of a short-term traffic change on air quality. Using regional traffic and ambient air quality data from Southern California, we examine the impact of a two-day freeway closure on traffic and several criteria air pollutants (CO, NO2, O3, PM10, PM2.5). The results indicate that regional traffic decreased about 14% on average during the closure. Daily average PM2.5 levels decreased by about 32%, and daily 8 h maximum ozone levels decreased by about 16%. However, the daily 1 h maximum NO2 concentration was higher at some sites during the closure. Despite the mixed results with NO2, this study provides empirical evidence to support traffic reduction as an effective strategy to address chronic air pollution problems, especially with regard to ozone, in Southern California.

Publications

• Hong, Andy, Lisa Schweitzer, Lindsey Marr, Wan Yang. Impact of temporary freeway closure on regional air quality: A lesson from Carmageddon in Los Angeles, United States. Environmental Science and Technology, 2015

Authors: Andy Hong, Christine Bae

The increase in urban bicycling facilities raises public health concerns for potential exposure of bicyclists to traffic emissions. For an assessment of bicyclists’ exposure to local traffic emissions, a hybrid approach is presented; it combines personal monitoring and a land use regression (LUR) model. Black carbon, a proxy variable for traffic-related air pollution, was measured with an Aethalometer along the predesignated bicycle route in Seattle, Washington, for 10 days, during a.m. and p.m. peak hours (20 sampling campaigns). Descriptive statistics and three-dimensional pollution maps were used to explore temporal variations and to identify pollution hot spots. The LUR model was developed to quantify the influence of spatial covariates on black carbon concentrations along the designated route. The results indicated that the black carbon concentrations fluctuated throughout the sampling periods and showed statistically significant diurnal and monthly patterns. The hot spot analysis suggests that proximity to traffic and other physical environments have important impacts on bicyclists’ exposure and demand further investigation on the localized effects of traffic emissions on exposure levels. The LUR model explains 46% of the variations in black carbon concentrations, and significant relationships are found with types of bicycle route facility, wind speed, length of truck routes, and transportation and utility land uses. This research is the first application of the LUR approach in quantifying bicyclists’ exposure to air pollution in transport microenvironments. This study provides a rationale for encouraging municipalities to develop effective strategies to mitigate the health risks of exposure to local traffic emissions in complex urban bicycling environments.

Publications
Hong, E. Andy and Bae, C.-H Christine. 2012. Exposure of bicyclists to air pollution in Seattle, Washington: Hybrid analysis using personal monitoring and land use regression. Transportation Research Record, No. 2270, pp. 59-66.