Sources of Tobacco Smoke Exposure and Their Associations With Serum Cotinine Levels Among US Children and Adolescents.

INTRODUCTION: We assessed tobacco smoke exposure (TSE) levels based on private and public locations of TSE according to race and ethnicity among US school-aged children ages 6-11 years and adolescents ages 12-17 years. AIMS AND METHODS: Data were from 5296 children and adolescents who participated in the National Health and Nutrition Examination Survey (NHANES) 2013-2018. Racial and ethnic groups were non-Hispanic white, black, other or multiracial, and Hispanic. NHANES assessed serum cotinine and the following TSE locations: homes and whether smokers did not smoke indoors (home thirdhand smoke [THS] exposure proxy) or smoked indoors (secondhand [SHS] and THS exposure proxy), cars, in other homes, restaurants, or any other indoor area. We used stratified weighted linear regression models by racial and ethnic groups and assessed the variance in cotinine levels explained by each location within each age group. RESULTS: Among 6-11-year-olds, exposure to home THS only and home SHS + THS predicted higher log-cotinine among all racial and ethnic groups. Non-Hispanic white children exposed to car TSE had higher log-cotinine (ß = 1.64, 95% confidence interval [CI] = 0.91% to 2.37%) compared to those unexposed. Non-Hispanic other/multiracial children exposed to restaurant TSE had higher log-cotinine (ß = 1.13, 95% CI = 0.23% to 2.03%) compared to those unexposed. Among 12-17-year-olds, home SHS + THS exposure predicted higher log-cotinine among all racial and ethnic groups, except for non-Hispanic black adolescents. Car TSE predicted higher log-cotinine among all racial and ethnic groups. Non-Hispanic black adolescents with TSE in another indoor area had higher log-cotinine (ß = 2.84, 95% CI = 0.85% to 4.83%) compared to those unexposed. CONCLUSIONS: TSE location was uniquely associated with cotinine levels by race and ethnicity. Smoke-free home and car legislation are needed to reduce TSE among children and adolescents of all racial and ethnic backgrounds. IMPLICATIONS: Racial and ethnic disparities in TSE trends have remained stable among US children and adolescents over time. This study's results indicate that TSE locations differentially contribute to biochemically measured TSE within racial and ethnic groups. Home TSE significantly contributed to cotinine levels among school-aged children 6-11 years old, and car TSE significantly contributed to cotinine levels among adolescents 12-17 years old. Racial and ethnic differences in locations of TSE were observed among each age group. Study findings provide unique insight into TSE sources, and indicate that home and car smoke-free legislation have great potential to reduce TSE among youth of all racial and ethnic backgrounds.

Beyond the dichotomy: How ride-hailing competes with and complements public transport.

Since ride-hailing has become an important travel alternative in many cities worldwide, a fervent debate is underway on whether it competes with or complements public transport services. We use Uber trip data in six cities in the United States and Europe to identify the most attractive public transport alternative for each ride. We then address the following questions: (i) How does ride-hailing travel time and cost compare to the fastest public transport alternative? (ii) What proportion of ride-hailing trips do not have a viable public transport alternative? (iii) How does ride-hailing change overall service accessibility? (iv) What is the relation between demand share and relative competition between the two alternatives? Our findings suggest that the dichotomy-competing with or complementing-is false. Though the vast majority of ride-hailing trips have a viable public transport alternative, between 20% and 40% of them have no viable public transport alternative. The increased service accessibility attributed to the inclusion of ride-hailing is greater in our US cities than in their European counterparts. Demand split is directly related to the relative competitiveness of travel times i.e. when public transport travel times are competitive ride-hailing demand share is low and vice-versa.

Markovian city-scale modelling and mitigation of micro-particles from tires.

The recent uptake in popularity in vehicles with zero tailpipe emissions is a welcome development in the fight against traffic induced airborne pollutants. As vehicle fleets become electrified, and tailpipe emissions become less prevalent, non-tailpipe emissions (from tires and brake disks) will become the dominant source of traffic related emissions, and will in all likelihood become a major concern for human health. This trend is likely to be exacerbated by the heavier weight of electric vehicles, their increased power, and their increased torque capabilities, when compared with traditional vehicles. While the problem of emissions from tire wear is well-known, issues around the process of tire abrasion, its impact on the environment, and modelling and mitigation measures, remain relatively unexplored. Work on this topic has proceeded in several discrete directions including: on-vehicle collection methods; vehicle tire-wear abatement algorithms and controlling the ride characteristics of a vehicle, all with a view to abating tire emissions. Additional approaches include access control mechanisms to manage aggregate tire emissions in a geofenced area with other notable work focussing on understanding the particle size distribution of tire generated PM, the degree to which particles become airborne, and the health impacts of tire emissions. While such efforts are already underway, the problem of developing models to predict the aggregate picture of a network of vehicles at the scale of a city, has yet to be considered. Our objective in this paper is to present one such model, built using ideas from Markov chains. Applications of our modelling approach are given toward the end of this note, both to illustrate the utility of the proposed method, and to illustrate its application as part of a method to collect tire dust particles.

Assessment of end-of-life vehicle recycling: Remanufacturing waste sheet steel into mesh sheet.

The automobile industry contributes significantly to global energy use and carbon emissions. Hence, there are significant economic and environmental benefits in recovering materials from end-of-life vehicles (ELVs). Here, the remanufacturing of waste steel sheet (WSS) from ELVs into useful mesh steel sheet (MSS) for metal forming applications was evaluated based on its technological, economic, and environmental feasibility. A remanufacturing plant with a dismantling capacity of over 30,171 ELV/year and a recovery capacity of 1000 m2/d of WSS was used as a case study. Remanufacturing can achieve a total reduction of ~3800 kg CO2/ELV and an economic benefit of ~775 USD/ELV compared with conventional recycling. The calculated feasibility indexes were similar to or exceeded standard feasibility thresholds, indicating that WSS remanufacturing is a viable sustainable development route and has synergistic benefits when combined with existing recycling plants, especially in developing countries as small-to-medium enterprises.

Comparison of motor vehicle-involved e-scooter and bicycle crashes using standardized crash typology.

INTRODUCTION: The market share of e-scooters in the United States has proliferated in cities: 86 million trips were made on shared e-scooters in 2019, a more than 100% increase compared to 2018. However, the interaction of e-scooters with other road users and infrastructure remains uncertain. METHOD: This study scrutinized 52 e-scooter and 79 bicycle police-reported crashes in Nashville, Tennessee, from April 2018 to April 2020 from the Tennessee Integrated Traffic Analysis Network (TITAN) database. We used descriptive analysis and a recent prototype version of the Pedestrian and Bicycle Crash Analysis Tool (PBCAT) to classify crashes based on the locations of the crashes relative to roadway segments or intersections, as well as the maneuver of the motor vehicle and e-scooter/bicycle relative to the motor vehicle. RESULTS: Two crash typologies can explain the majority of e-scooter crashes, while bicycle crashes are distributed over several crash typologies. Additionally, 1 in 10 e-scooter- and bicycle-motor vehicle crashes leads to the injury or fatality of the e-scooter rider or bicyclist. Furthermore, we noted statistically significant differences in spatial and temporal distribution, demographics, lighting conditions, and crash distance from home for e-scooter and bicycle crashes. CONCLUSIONS: The police crash report provides a comprehensive picture of e-scooter safety complementing existing literature. We found that e-scooter crash characteristics do not fully overlap with features of bicycle crashes. PRACTICAL IMPLICATIONS: A generalized engineering, education, and enforcement treatment to reduce and prevent e-scooter and bicycle crashes, injuries, and fatalities might not result in equal outcomes for each mode. More rigorous enforcement could be implemented to deter e-scooters riders under the age of 18 years and e-scooter safety campaigns could target female riders.

Large-scale simulation of traffic flow using Markov model.

Modeling and simulating movement of vehicles in established transportation infrastructures, especially in large urban road networks is an important task. It helps in understanding and handling traffic problems, optimizing traffic regulations and adapting the traffic management in real time for unexpected disaster events. A mathematically rigorous stochastic model that can be used for traffic analysis was proposed earlier by other researchers which is based on an interplay between graph and Markov chain theories. This model provides a transition probability matrix which describes the traffic's dynamic with its unique stationary distribution of the vehicles on the road network. In this paper, a new parametrization is presented for this model by introducing the concept of two-dimensional stationary distribution which can handle the traffic's dynamic together with the vehicles' distribution. In addition, the weighted least squares estimation method is applied for estimating this new parameter matrix using trajectory data. In a case study, we apply our method on the Taxi Trajectory Prediction dataset and road network data from the OpenStreetMap project, both available publicly. To test our approach, we have implemented the proposed model in software. We have run simulations in medium and large scales and both the model and estimation procedure, based on artificial and real datasets, have been proved satisfactory and superior to the frequency based maximum likelihood method. In a real application, we have unfolded a stationary distribution on the map graph of Porto, based on the dataset. The approach described here combines techniques which, when used together to analyze traffic on large road networks, has not previously been reported.

Matching algorithm for improving ride-sharing by incorporating route splits and social factors.

Increasing traffic congestion and the advancements in technology have fostered the growth of alternative transportation modes such as dynamic ride-sharing. Smartphone technologies have enabled dynamic ride-sharing to thrive, as this type of transportation aims to establish ride matches between people with similar routes and schedules on short notice. Many automated matching methods are designed to improve system performance; such methods include minimizing process time, minimizing total system cost or maximizing total distance savings. However, the results may not provide the maximum benefits for the participants. This paper intends to develop an algorithm for optimizing matches when considering participants' gender, age, employment status and social tendencies. The proposed matching algorithm also splits unmatched parts of drivers' routes and creates new travel requests to find additional matches using these unmatched parts. Accordingly, this paper performs an extensive simulation study to assess the performance of the proposed algorithm. The simulation results indicate that route splits may increase the number of matches significantly when there is a shortage of drivers. Furthermore, the paper demonstrates the effects and potential benefits of utilizing a social compatibility score in the objective function.

The effect of speed limit reductions in urban areas on cyclists' injuries in collisions with cars.

Objective: Impact speed is one of the most important factors explaining the severity of injuries to cyclists when they collide with passenger cars. To reduce injury severity (especially for vulnerable road users), since 2008, Swedish municipalities have the authority to lower the speed limit to 30 or 40 km/h in urban areas as appropriate. The aim of this study was to evaluate how this speed limit reduction has influenced the injury severity for cyclists in this type of collision.Method: Data from 1,953 collisions between bicycles and passenger cars were collected using information from third-party-liability insurance claims from 2005 to 2017. The change of speed limit distribution, influenced by the reduction of speed limits in urban areas, where car-to-cyclist collisions occurred was studied. Following that, injury severity for cyclists was evaluated regarding collisions occurring in areas with different speed limits.Results: The results show that, in collisions with cars, cyclists have a significantly lower risk of a moderate-to-fatal (MAIS 2+) injury when the speed limit is 30-40 km/h compared to 50-60 km/h. During the last decade, while the speed-limit has been lowered on many road-sections in urban areas from 50-60 km/h to 30-40 km/h the risk of a cyclist getting a MAIS 2+ injury decreased by 25%. In 2005 to 2011, 16% of the crashes happened on a road with a speed limit of 30-40 km/h; in 2016-2017, this percentage had increased to approximately 50%. Thus, in recent years more crashes occurred on roads with lower speed limits, and in these crashes, there was a lower risk of severe injuries to cyclists. Unfortunately, it was not possible to evaluate the risk of a crash for specific speed limits; since one limitation of this study was the lack of exposure data, nor do we know the impact speed or the actual speed of the vehicles.Conclusions: This study is an important follow-up on the implementation of measures that can influence bicycle safety. The insurance data used, made it possible to quantify a positive effect on injury severity for cyclists in passenger car-to-cyclist collisions when the speed limit was reduced in urban areas. Insurance claims cover collisions of all crash severity, so they include data covering all types of injuries-not just the most severe/fatal ones. This aspect is especially important in the speed intervals evaluated here, since moderate (MAIS 2) injuries are very frequent in lower-speed crashes and even these injuries can result in long-term consequences.

Built environment and physical activity among adolescents: the moderating effects of neighborhood safety and social support.

BACKGROUND: Increasing emphasis has been placed on improving physical activity levels through multilevel interventions. This study aims to examine moderating effects of neighborhood safety (crime and traffic) and social support (from parent and sibling/peer) for physical activity in the relationship between the built environment and moderate-to-vigorous physical activity (MVPA) outside school hours among adolescents in Melbourne. METHODS: Data were from the NEighbourhood Activity in Youth study conducted among adolescents in Melbourne, Australia (n = 358, 15.3 (SD = 1.5) years). MVPA outside school hours was assessed by accelerometer. Built environment features within 1 km and 2 km residential buffers including recreation facilities, park area, and walkability and its components were assessed using Geographic Information Systems. Neighborhood safety, social support for physical activity and sociodemographic information were self-reported by adolescents. Multilevel linear regression models were used to estimate associations. RESULTS: Support for physical activity from sibling/peer positively moderated the relationship between recreation facilities (1 km), residential density (2 km) and MVPA. Recreation facility (count within 2 km), walkability (1 km and 2 km) and residential density (1 km) had significant positive associations with MVPA outside school hours. CONCLUSION: The built environment appeared to have stronger facilitating effects on MVPA among adolescents who had favourable support for physical activity from their sibling or peer. Multilevel interventions that target the built environment and social factors are needed to promote MVPA outside school hours among adolescents.

Quantifying the Impacts of Economic Progress, Economic Structure, Urbanization Process, and Number of Vehicles on PM2.5 Concentration: A Provincial Panel Data Model Analysis of China.

With the rapid development of China's economy, the environmental problems are becoming increasingly prominent, especially the PM2.5 (particulate matter with diameter smaller than 2.5 µm) concentrations that have exerted adverse influences on human health. Considering the fact that PM2.5 concentrations are mainly caused by anthropogenic activities, this paper selected economic growth, economic structure, urbanization, and the number of civil vehicles as the primary factors and then explored the nexus between those variables and PM2.5 concentrations by employing a panel data model for 31 Chinese provinces. The estimated model showed that: (1) the coefficients of the variables for provinces located in North, Central, and East China were larger than that of other provinces; (2) GDP per capita made the largest contribution to PM2.5 concentrations, while the number of civil vehicles made the least contribution; and (3) the higher the development level of a factor, the greater the contribution it makes to PM2.5 concentrations. It was also found that a bi-directional Granger causal nexus exists between PM2.5 concentrations and economic progress as well as between PM2.5 concentrations and the urbanization process for all provinces. Policy recommendations were finally obtained through empirical discussions, which include that provincial governments should adjust the economic and industrial development patterns, restrict immigration to intensive urban areas, decrease the successful proportion of vehicle licenses, and promote electric vehicles as a substitute to petrol vehicles.

Investigation of household private car ownership considering interdependent consumer preference.

People are connected by various social networks, resulting in the interdependence of consumer choice. Therefore, it is very important and realistic to assume choice interdependence in private car ownership modeling. In this paper, we investigate the interdependence of private car ownership choice using a spatial autoregressive binary probit model estimated by the Bayesian Markov chain Monte Carlo (MCMC) method. Constructing the autoregressive matrix demographically shows that the private car ownership choice of a household is dependent on other household choices. Compared with the pure binary probit model estimated by the MCMC method, the spatial autoregressive model achieves a significant improvement both in loglikelihood value and log marginal density value, which are calculated using the importance sampling method of Newton and Raftery, from approximately -202 to approximately -63 and from -208 to -145, respectively. Moreover, the results indicated by the spatial autoregressive probit model suggest that the number of children, the ownership of an apartment or the availability of a parking lot are positively and significantly associated with the private car ownership level. To test the out-of-sample performance of the model, we estimate the model using 600 data points and test it using another 148 data points. The results indicate that the predictive power is greatly improved. Finally, we analyze the augmented parameter and discover that it is associated with the parking variable in addition to the license variable.

Modal Shift from Cars and Promotion of Walking by Providing Pedometers in Yokohama City, Japan.

Mobility management is a transportation policy aiming to change travel behavior from car use to sustainable transportation modes while increasing people's physical activity. Providing pedometers and visualizing step counts, popular interventions in public health practice, may constitute a mobility management program. However, the ease of modal shifts and changeability of walking habits differ across neighborhood environments. Using questionnaire data from 2023 middle-aged and older participants from Yokohama, Japan, in May 2017, this study examined (1) the relationship between the physical and social environments of Yokohama Walking Point Program participants who volunteered to use free pedometers and their modal shifts from cars to walking and public transport, and (2) whether participants' modal shifts were associated with increases in step counts. Multivariate categorical regression analyses identified the frequency of greetings and conversations with neighbors as well as health motivation as important explanatory variables in both analyses. Participants living in neighborhoods far from railway stations and in neighborhoods with a high bus stop density tended to shift to walking and public transport, a modal shift that was highly associated with increased step counts. These results suggest that mobility management should be promoted in collaboration with public health and city planning professionals.

Pay or prevent? Human safety, costs to society and legal perspectives on animal-vehicle collisions in São Paulo state, Brazil.

Direct road mortality and the barrier effect of roads are typically identified as one of the greatest threats to wildlife. In addition, collisions with large mammals are also a threat to human safety and represent an economic cost to society. We documented and explored the effects of animal-vehicle crashes on human safety in São Paulo State, Brazil. We estimated the costs of these crashes to society, and we summarized the legal perspectives. On average, the Military Highway Police of São Paulo reported 2,611 animal-vehicle crashes per year (3.3% of total crashes), and 18.5% of these resulted in human injuries or fatalities. The total annual cost to society was estimated at R$ 56,550,642 (US $ 25,144,794). The average cost for an animal-vehicle crash, regardless of whether human injuries and fatalities occurred, was R$ 21,656 (US $ 9,629). The Brazilian legal system overwhelmingly (91.7% of the cases) holds the road administrator liable for animal-vehicle collisions, both with wild and domestic species. On average, road administrators spent R$ 2,463,380 (US $ 1,005,051) per year compensating victims. The logical conclusion is that the Brazilian legal system expects road administrators to keep animals, both wild and domestic species, off the road. We suggest an improved coordination between the laws that relate to animal-vehicle collisions and human safety, and the process for environmental licenses that focusses on reducing collisions with wildlife and providing habitat connectivity. In addition, we suggest better management practices, raising awareness and social change with regard to abandoned domesticated animals including horses, cattle, and dogs. This should ultimately result in a road system with improved human safety, reduced unnatural mortality for both domestic and wild animal species, safe crossing opportunities for wildlife, and reduced monetary costs to society.

Concentrations of particulate matter, carbon dioxide, VOCs and risk assessment inside Korean taxis and ships.

The objective of this study was to investigate the concentration distribution of indoor air pollutants in taxis and ships (passengers) which are frequently used for public transportation and recreational activities in South Korea. In addition, it aimed to assess air quality factors to establish and evaluate the health risks of exposure to polluted indoor air. Particulate matter (PM10) concentrations were not affected by the number of passengers, time of day, and driving characteristics because there were only a few passengers (2 to 4 people) and the space was confined. In the ships, indoor air pollutants responded more sensitively to the operation characteristics depending on the time of sailing (i.e., anchoring and departure, movement of vehicles on the ship, movement of passengers, combustion in the shop, and ventilation) than to the number of people boarding and alighting. The carbon dioxide concentrations in different ship rooms did not vary according to season and degree of congestion; however, there were differences between different ships. These differences may result from the size, type, and operating characteristics of the ships. Volatile organic compounds (VOCs) and aldehydes in new taxis exceeded the standard levels during summer. VOC concentrations in ships were particularly high during summer when the outdoor temperature was high. Similar observations were made for other means of transportation. The risk assessment depended on the means of transportation and demonstrated that mortality risks due to PM10 and excess carcinogenic and non-carcinogenic risks from VOCs and aldehydes were within safety levels.

Understanding the effects of trip patterns on spatially aggregated crashes with large-scale taxi GPS data.

The primary objective of this study was to investigate how trip pattern variables extracted from large-scale taxi GPS data contribute to the spatially aggregated crashes in urban areas. The following five types of data were collected: crash data, large-scale taxi GPS data, road network attributes, land use features and social-demographic data. A data-driven modeling approach based on Latent Dirichlet Allocation (LDA) was proposed for discovering hidden trip patterns from a taxi GPS dataset, and a total of fifty trip patterns were identified. The collected data and the identified trip patterns were further aggregated into167 ZIP Code Tabulation Areas (ZCTA). Random forest technique was used to identify the factors that contributed to total, PDO and fatal-plus-injury crashes in the selected ZCTAs during the study period. Geographically weighted Poisson regression (GWPR) models were then developed to establish a relationship between the crashes and the contributing factors selected by the random forest technique. Comparative analyses were conducted to compare the performance of the GWPR models that considered traditional traffic exposure variables only, trip pattern variables only, and both traditional exposure and trip pattern variables. The model specification results suggest that the trip pattern variables significantly affected the crash counts in the selected ZCTAs, and the models that considered both the traditional traffic exposure and the trip pattern variables had the best goodness-of-fit in terms of the lowest MAD and AICc values.

Live and Let Die? Life Cycle Human Health Impacts from the Use of Tire Studs.

Studded tires are used in a number of countries during winter in order to prevent accidents. The use of tire studs is controversial and debated because of human health impacts from increased road particle emissions. The aims of this study are to assess whether the use of tire studs in a Scandinavian studded passenger car actually avoids or causes health impacts from a broader life cycle perspective, and to assess the distribution of these impacts over the life cycle. Life cycle assessment is applied and the disability-adjusted life years indicator is used to quantify the following five types of health impacts: (1) impacts saved in the use phase, (2) particle emissions in the use phase, (3) production system emissions, (4) occupational accidents in the production system, and (5) conflict casualties from revenues of cobalt mining. The results show that the health benefits in the use phase in general are outweighed by the negative impacts during the life cycle. The largest contribution to these negative human health impacts are from use phase particle emissions (67⁻77%) and occupational accidents during artisanal cobalt mining (8⁻18%). About 23⁻33% of the negative impacts occur outside Scandinavia, where the benefits occur. The results inform the current debate and highlight the need for research on alternatives to tire studs with a positive net health balance.

Effects of vehicle gap changes on fuel economy and emission performance of the traffic flow in the ACC strategy.

This paper focuses on the effects of vehicle gap changes on fuel and emission performance of the simulated traffic flow in the adaptive cruise control (ACC) strategy. Firstly, the close correlation of vehicle gap changes and the host car's behaviors was explored with the measured car-following data. Secondly, the correlation between the host car's velocity and vehicle gap changes with different memory steps was also explored to develop the nth car's optimal velocity function. Thirdly, a microscopic traffic simulation program was created for analyzing the traffic flow evolution process and approximately estimating the fuel consumptions and exhaust emissions. As a result, it was seen that vehicle gap changes with memory significantly affect fuel economy and emission performance of the simulated traffic flow in the ACC strategy, which can result in low fuel consumptions and exhaust emissions. This study is an incremental step forward for designing the control strategy of the ACC system.

Carbon emissions tax policy of urban road traffic and its application in Panjin, China.

How to effectively solve traffic congestion and transportation pollution in urban development is a main research emphasis for transportation management agencies. A carbon emissions tax can affect travelers' generalized costs and will lead to changes in passenger demand, mode choice and traffic flow equilibrium in road networks, which are of significance in green travel and low-carbon transportation management. This paper first established a mesoscopic model to calculate the carbon emissions tax and determined the value of this charge in China, which was based on road traffic flow, vehicle speed, and carbon emissions. Referring to existing research results to calibrate the value of time, this paper modified the traveler's generalized cost function, including the carbon emissions tax, fuel surcharge and travel time cost, which can be used in the travel impedance model with the consideration of the carbon emissions tax. Then, a method for analyzing urban road network traffic flow distribution was put forward, and a joint traffic distribution model was established, which considered the relationship between private cars and taxis. Finally, this paper took the city of Panjin as an example to analyze the road traffic carbon emissions tax's impact. The results illustrated that the carbon emissions tax has a positive effect on road network flow equilibrium and carbon emission reduction. This paper will have good reference value and practical significance for the calculation and implementation of urban traffic carbon emissions taxes in China.