Traffic Sites Research Articles

Researching particulate matter characteristics for mitigating health risks generated by road vehicles

Research of PM (particulate matter) emissions is very important in crowded areas with high values of road traffic and industrial sites because may affect the health significantly. To mitigate the health risks generated by motor vehicles, the present paper shows the applied research on this topic with the practical results. The first important objective of the paper is to study the characteristics related to particulate matter in emissions generated by a car in actual road traffic test. The second objective is to compare the results from cold and warm operation regimes. It is important to know the trendline of PM emissions during operation due to their influence upon health. The PM amount is influenced by engine speed, fuel consumption and other operational factors. High levels of PM were recorded at 1500 rpm because it was the upper point in which the gear ratio has been changed.

Contributions of traffic emissions and new particle formation to the ultrafine particle size distribution in the megacity of Beijing

The important role of traffic emissions in air pollution has been widely recognized. However, the corresponding contributions to the ultrafine particle distribution and new particle formation (NPF) are poorly understood due to the mixed influences of various sources. Measurements of particle evolution and NPF were made at a heavy traffic site near the 5th Ring Road of Beijing from August 2017 to October 2019. A positive matrix factorization receptor model (version 5.0) consisting of the log-normal fit method and the k-means clustering method was used to identify and quantify the major sources of particle number concentrations. Based on the characteristics of NPF, additional analyses were performed to identify formation sources, including back-trajectory clustering and correlations between auxiliary variables and the relative contributions of all resolved factors. Traffic emissions mainly influenced Aitken mode (25–100 nm) particles (>60%), and NPF significantly contributed to the ultrafine particle distribution (47.2%). Additionally, regional transport notably affected the occurrence of NPF at the observation site, with northwest airmass transport influencing the nucleation mode the most and southeast airmass transport influencing the Aitken mode the most.

Source apportionment of atmospheric PM<sub>10</sub> oxidative potential: synthesis of 15 year-round urban datasets in France

Abstract. Reactive oxygen species (ROS) carried or induced by particulate matter (PM) are suspected of inducing oxidative stress in vivo, leading to adverse health impacts such as respiratory or cardiovascular diseases. The oxidative potential (OP) of PM, displaying the ability of PM to oxidize the lung environment, is gaining strong interest in examining health risks associated with PM exposure. In this study, OP was measured by two different acellular assays (dithiothreitol, DTT, and ascorbic acid, AA) on PM10 filter samples from 15 yearly time series of filters collected at 14 different locations in France between 2013 and 2018, including urban, traffic and Alpine valley site typologies. A detailed chemical speciation was also performed on the same samples, allowing the source apportionment of PM using positive matrix factorization (PMF) for each series, for a total number of more than 1700 samples. This study then provides a large-scale synthesis of the source apportionment of OP using coupled PMF and multiple linear regression (MLR) models. The primary road traffic, biomass burning, dust, MSA-rich, and primary biogenic sources had distinct positive redox activity towards the OPDTT assay, whereas biomass burning and road traffic sources only display significant activity for the OPAA assay. The daily median source contribution to the total OPDTT highlighted the dominant influence of the primary road traffic source. Both the biomass burning and the road traffic sources contributed evenly to the observed OPAA. Therefore, it appears clear that residential wood burning and road traffic are the two main target sources to be prioritized in order to decrease significantly the OP in western Europe and, if the OP is a good proxy of human health impact, to lower the health risks from PM exposure.

Knowledge of osteopathic manipulative medicine and osteopathic physicians in a New York South Asian community.

Research regarding patient awareness of osteopathic manipulative medicine (OMM) can help identify barriers and factors limiting patient knowledge. Levels of knowledge about OMM and osteopathic physicians have been studied in New York's Chinese and Korean populations, but have not previously been investigated in the South Asian population. To assess the knowledge of OMM and osteopathic physicians within a South Asian community of New York. A cross-sectional study was designed in which a culturally appropriate survey, provided in both English and Hindi, was administered to study participants in order to measure knowledge of osteopathic medicine. The study utilized convenience sampling and distributed surveys to individuals who identified themselves of South Asian descent at high traffic sites in Hicksville, New York. The survey contained 10 questions, assessing the individual's knowledge of osteopathic medicine. The Kruskal-Wallis and Chi-Square tests were employed to determine statistical significance of the data obtained from the surveys. The survey was conducted on 100 participants inHicksville, New York. The respondent demographics included 53 males and 47 females with an average age of 41.2±16.3 years old. There were 34 (34%) participants who had heard of osteopathic manipulative medicine (OMM) and 26 (26%) participants who had knowledge of doctor of osteopathic medicine (DO) physicians. Respondents were found more likely to have knowledge of DOs if they were born in the United States (US) vs. other countries (US, 8 of 14 [57.1%] vs. others, 18 of 86 [20.9%]; p=0.006) or lived longer in the US (11 of 26 [42.3%], p=0.039). Participants who spoke a non-English primary language were also found less likely to have knowledge of DOs as they made up 46 of the 58 respondents who indicated no knowledge (79.3%, p=0.042). A general lack of knowledge of DOs and OMM exists within the South Asian community of Hicksville, New York and lower levels of awareness were found among participants who were male, born outside the US, had a language other than English as their primary language, and had spent less time in the US. Additional educational resources may be implemented to increase awareness of DOs and OMM among this and similar communities.

Added Value of Vaisala AQT530 Sensors as a Part of a Sensor Network for Comprehensive Air Quality Monitoring

Poor air quality influences the quality of life in the urban environment. The regulatory observation stations provide the backbone for the city administration to monitor urban air quality. Recently a suite of cost-effective air quality sensors has emerged to provide novel insights into the spatio-temporal variability of aerosol particles and trace gases. Particularly in low concentrations these sensors might suffer from issues related e.g., to high detection limits, concentration drifts and interdependency between the observed trace gases and environmental parameters. In this study we characterize the optical particle detector used in AQT530 (Vaisala Ltd.) air quality sensor in the laboratory. We perform a measurement campaign with a network of AQT530 sensors in Helsinki, Finland in 2020–2021 and present a long-term performance evaluation of five sensors for particulate (PM10, PM2.5) and gaseous (NO2, NO, CO, O3) components during a half-year co-location study with reference instruments at an urban traffic site. Furthermore, short-term (3–5 weeks) co-location tests were performed for 25 sensors to provide sensor-specific correction equations for the fine-tuning of selected pollutants in the sensor network. We showcase the added value of the verified network of 25 sensor units to address the spatial variability of trace gases and aerosol mass concentrations in an urban environment. The analysis assesses road and harbor traffic monitoring, local construction dust monitoring, aerosol concentrations from fireworks, impact of sub-urban small scale wood combustion and detection of long-range transport episodes on a city scale. Our analysis illustrates that the calibrated network of Vaisala AQT530 air quality sensors provide new insights into the spatio-temporal variability of air pollution within the city. This information is beneficial to, for example, optimization of road dust and construction dust emission control as well as provides data to tackle air quality problems arising from traffic exhaust and localized wood combustion emissions in the residential areas.

Relationship of particle density and organic content in sieve fractions of road-deposited sediments from varying traffic sites based on a novel data set

Pollutants (e.g. heavy metals) are to a large extent bound to particles in runoff from traffic areas. Sedimentation is the prevailing process of treatment in most cases. The effectiveness of treatment depends largely on the characteristics of the particles, especially their size and density. Road-deposited sediments (RDS) are the main source of solids in runoff. The sizes and density vary over a wide range, as the particles are composed of mineral and organic components of different origin (e.g. tire and road wear, plant debris, erosion from surrounding areas, atmospheric deposition). While many previous studies have dealt with particle-size distributions, there are still relatively few studies on density. The aim of this study was to investigate the relationship between particle size, organic content and density in RDS on a large data set from different sites and the influence of site-specific conditions on the composition. In addition, it should be checked whether the loss on ignition (LOI) is suitable as a surrogate parameter for density. Density was obtained by gas pycnometry, LOI by ignition in a muffle furnace at 550 °C. In total, 85 RDS samples were collected at 11 sites over a 5 year period and sieved into ten sieve fractions <2000 μm. Each sieve fraction was analyzed for LOI and density (n = 848). This novel data set covers a wide range of boundary conditions in terms of traffic intensity and surrounding vegetation. The results show that there is a strong negative linear correlation of density and LOI independent of particle size <2000 μm (R2 = 0.867). LOI is an applicable surrogate parameter for density in RDS. Site-specifically traffic and vegetation proved significant sources of organic content and density in the multicomponent mixtures in form of tire wear and plant debris.

NPAHs and OPAHs in the atmosphere of two central European cities: Seasonality, urban-to-background gradients, cancer risks and gas-to-particle partitioning

Derivatives of polycyclic aromatic hydrocarbons (PAHs) such as nitrated- and oxygenated-PAHs (NPAHs and OPAHs) could be even more toxic and harmful for the environment and humans than PAHs. We assessed the spatial and seasonal variations of NPAHs and OPAHs atmospheric levels, their cancer risks and their gas-to-particle partitioning. To this end, about 250 samples of fine particulate matter (PM2.5) and 50 gaseous samples were collected in 2017 in central Europe in the cities of Brno and Ljubljana (two traffic and two urban background sites) as well as one rural site.The average particulate concentrations were ranging from below limit of quantification to 593 pg m−3 for Σ9NPAHs and from 1.64 to 4330 pg m−3 for Σ11OPAHs, with significantly higher concentrations in winter compared to summer.In winter, the particulate levels of NPAHs and OPAHs were higher at the traffic site compared to the urban background site in Brno while the opposite was found in Ljubljana. NPAHs and OPAHs particulate levels were influenced by the meteorological parameters and co-varied with several air pollutants. The significance of secondary formation on the occurrence of some NPAHs and OPAHs is indicated. In winter, 27–47% of samples collected at all sites were above the acceptable lifetime carcinogenic risk. The gas-particle partitioning of NPAHs and OPAHs was influenced by their physico-chemical properties, the season and the site-specific aerosol composition. Three NPAHs and five OPAHs had higher particulate mass fractions at the traffic site, suggesting they could be primarily emitted as particles from vehicle traffic and subsequently partitioning to the gas phase along air transport. This study underlines the importance of inclusion of the gas phase in addition to the particulate phase when assessing the atmospheric fate of polycyclic aromatic compounds and also when assessing the related health risk.

A bivariate extreme value model for estimating crash frequency by severity using traffic conflicts

Estimating crash frequency by severity levels using traffic conflicts remains relatively unexplored in conflict-based traffic safety assessment, limiting its application scope and appeal compared to traditional methods. No studies to date have predicted the frequency of severe and non-severe crashes utilizing traffic conflicts. This study aims to address this critical gap and stimulate discussion and development in this critical area. The study estimates the frequency of severe crashes and non-severe crashes by jointly modeling the indicators of crash frequency, namely, Time to Collision (TTC) and Modified Time to Collision (MTTC), and crash severity, namely, predicted post-collision change in velocity (Delta-V or Δv), using bivariate Extreme Value. Severe crashes here are defined as crashes with a Maximum Abbreviated Injury Scale rating of greater than or equal to 3. Rear-end conflict data (TTC ≤ 3.0 s) were collected for two days (12 h each day) from two four-legged signalized intersections in Brisbane, Australia. Bivariate peak-over-threshold models for both TTC and MTTC indicators, combined with Delta-V, were estimated. Alternatively, another univariate approach was also attempted where the probability of crash occurrence was estimated using the univariate peak-over-threshold model with TTC (or MTTC) and then multiplied with the injury probability estimated from Delta-V to estimate the frequencies of severe and non-severe injury crashes. The study results demonstrate that the bivariate approach is more advantageous than the univariate approach due to a superior statistical fit to the data and more precise estimations of crash frequencies by severity levels. Both TTC and MTTC indicators, in combination with Delta-V, provide comparable results using the bivariate approach owing to the weak asymptotic dependence between the frequency and severity indicators. Comparing the combined dataset model of the two intersections with the intersection-based models shows that sharing information between similar traffic sites improves the accuracy and precision of prediction.

Exploring the Impact of Driver Adherence to Speed Limits and the Interdependence of Roadside Collisions in an Urban Environment: An Agent-Based Modelling Approach

Roadside collisions are a significant problem faced by all countries. Urbanisation has led to an increase in traffic congestion and roadside vehicle collisions. According to the UK Government’s Department for Transport, most vehicle collisions occur on urban roads, with empirical evidence showing drivers are more likely to break local and fixed speed limits in urban environments. Analysis conducted by the Department for Transport found that the UK’s accident prevention measure’s cost is estimated to be £33bn per year. Therefore, there is a strong motivation to investigate the causes of roadside collisions in urban environments to better prepare traffic management, support local council policies, and ultimately reduce collision rates. This study utilises agent-based modelling as a tool to plan, experiment and investigate the relationship between speeding and vehicle density with collisions. The study found that higher traffic density results in more vehicles travelling at a slower speed, regardless of the degree to which drivers comply with speed restrictions. Secondly, collisions increase linearly as speed compliance is reduced for all densities. Collisions are lowest when all vehicles comply with speed limits for all densities. Lastly, higher global traffic densities result in higher local traffic densities near-collision sites across all adherence levels, increasing the likelihood of congestion around these sites. This work, when extended to real-world applications using empirical data, can support effective road safety policies.

A fuel-based method for updating mobile source emissions during the COVID-19 pandemic

The COVID-19 pandemic and ensuing lockdown of many US States resulted in rapid changes to motor vehicle traffic and their associated emissions. This presents a challenge for air quality modelling and forecasting during this period, in that transportation emission inventories need to be updated in near real-time. Here, we update the previously developed fuel-based inventory of vehicle emissions (FIVE) to account for changes due to COVID-19 lockdowns. We first construct a 2020 business-as-usual (BAU) case inventory and adjust the emissions for a COVID-19 case using monthly fuel sales information. We evaluate cellular phone-based mobility data products (Google COVID-19 Community Mobility, Apple COVID-19 Mobility Trends) in comparison to embedded traffic monitoring sites in four US cities. We find that mobility datasets tend to overestimate traffic reductions in April 2020 (i.e. lockdown period), while fuel sales adjustments are more similar to changes observed by traffic monitors; for example, mobility-based methods for scaling emissions result in an approximately two-times greater estimate of on-road nitrogen oxide (NO x ) reductions in April 2020 than we find using a fuel-based method. Overall, FIVE estimates a 20%–25% reduction in mobile source NO x emissions in April 2020 versus BAU, and a smaller 6%–7% drop by July. Reductions in April showed considerable spatial heterogeneity, ranging from 6% to 39% at the state level. Similar decreases are found for carbon monoxide (CO) and volatile organic compounds. Decreases to mobile source NO x emissions are expected to lower total US anthropogenic emissions by 9%–12% and 3%–4% in April and July, respectively, with larger relative impacts in urban areas. Changes to diurnal and day-of-week patterns of light- and heavy-duty vehicular traffic are evaluated and found to be relatively minor. Beyond the applicability to modelling air quality in 2020, this work also represents a methodology for quickly updating US transportation inventories and for calibrating mobility-based estimates of emissions.

Pollution and health risk assessment of arsenic in street dust and soil from an industrial zone

Taking an industrial area in Wuhan as the research object, single factor index, Geoaccumulation index and EPA health risk model are utilized to evaluate the pollution pattern and health risk of arsenic (As) in street dust with different particle fractions and soil. The results showed that the content of As in street dust increased with the decrease of particle size. The average content of As in street dust with fine particle fraction and soil exceeded the soil background value of Hubei Province, but did not exceed the screening value of “Soil Environmental Quality Construction Site Soil Pollution Risk Control Standards (Trial)”. The content of As in soil had a high correlation with that of dust with < 63 particle fraction at the corresponding point, with high fit degree (R2=0.6012). There was moderate to heavy pollution of As in areas surrounding industrial enterprises like Wuhan Iron and Steel, cement plants, and areas with high traffic flow and construction sites. The As of street dust and soil at some points posed a non-carcinogenic risk to children, but no carcinogenic risk. The ingestion pathway was the largest non-carcinogenic exposure route of As in street dust and soil from the research area.

Air ambulance base development for responding to traffic accidents in Iran

Background: Road Traffic accidents are one of the most common accidents killing 1.35 million people annually around the globe. Approximately 86% of deaths occur from trauma before hospitalization. In such circumstances as a pre-hospital service, air ambulance can play an important role in accessing the patients and transferring them from the accident scene securing survival of patients. Objective: This study aimed to identify the affecting factors in-air ambulance response to traffic accident sites. Methods: This qualitative study conducted from November 6, 2019 to April 6, 2020, in which a semi-structured interview was carried out on 17 participants. To analyze the data of this qualitative study, the Graneheim and Lundman method was used, and a conventional content analysis approach was employed. Results: The majority 41% were in the age range of 30-40 years. Individuals with a master's or doctoral degree made up 70% of the participants. People with 11-20 years of work experience made up 52% and 58% of the participants were at the managerial level. Factors influencing the development of air ambulance bases in 6 main categories, included resources and infrastructure, training of specialized personnel, indicators and standards, information and communication, safety and security, and management factors were studied. Conclusion: Based on the findings, infrastructure improvement and allocation of resources as well as training specialized forces can play an important role in developing air ambulance bases in Iran, Further research is needed to develop a measurement tool to evaluate the affecting factors before establishing air ambulance bases in Iran.

EXPLORING LOCATION DETERMINANTS OF ASIA’S UNIQUE BEVERAGE SHOPS BASED ON A HYBRID MADM MODEL

Identifying relevant location determinants is a good starting point for shop operators, help to increase profitability and, thus, avoiding business failure. Traditional Analytic Hierarchy Process (AHP) or the Analytic Network Process (ANP) have shortages that require improvement. Herein, Decision-Making Trial and Evaluation Laboratory (DEMATEL), ANP based on DEMATEL (DANP), and modified Vlse Kriterijumska Optimizacija I Kompromisno Resenje (modified VIKOR) are used to construct a hybrid multiple-attribute decision making (MADM) model, encompassing three dimensions and thirteen criteria in exploring the location determinants of Asia’s unique Bubble Tea Shops (BTSs) and to evaluate three preselected alternatives in Nanjing, China. The empirical findings of the DEMATEL method reveal that traffic traits (D1) and site traits (D2) are critical to BTSs, and that once these are enhanced, shop traits (D3) are also improved. Criteria deemed as important, based on the DEMATEL and DANP methodology, are (in descending order): proximity to a street corner (C2), proximity to public transportation systems (C1), road width (C3), proximity to communities (C5), proximity to commercial areas (C6), types of shop (C9), and proximity to schools (C7). Different decision-making rankings among alternatives are indicated based upon the modified VIKOR method and corresponding strategies for improvement are presented.

Ambient air particulates and Hg(p) concentrations and dry depositions estimations, distributions for various particles sizes ranges

Ambient air TSP concentrations, dry deposition fluxes and particulate-bound mercury (Hg(p)) concentrations were measured and analyzed at a complex (traffic, residential and commercial) site. Zhang and He’s model[ 1 ] was used to predict the dry deposition fluxes of ambient air particulates and Hg(p) at this complex site. The results revealed that October had the highest mean particulate concentration and lowest Hp(p) concentration and dry deposition flux. The mean calculated dry deposition fluxes of PM2.5 and PM2.5-10 accounted for 1%–2% and 0.06%–5% of the average total calculated dry deposition particle flux, respectively. The average calculated particle dry depositions flux of PM10+, accounted for 93%–99% of the average total calculated dry depositions particle flux. Finally, the model of Zhang and He underestimated the ambient air dry depositions fluxes of both particulates and Hg(p) for all particles sizes (PM2.5, PM2.5-10, PM10 +) at the mixed site in this study. Better results concerning the dry deposition fluxes of pollutants were obtained as the particles size increased.

Inositol triphosphate-triggered calcium release blocks lipid exchange at endoplasmic reticulum-Golgi contact sites

Vesicular traffic and membrane contact sites between organelles enable the exchange of proteins, lipids, and metabolites. Recruitment of tethers to contact sites between the endoplasmic reticulum (ER) and the plasma membrane is often triggered by calcium. Here we reveal a function for calcium in the repression of cholesterol export at membrane contact sites between the ER and the Golgi complex. We show that calcium efflux from ER stores induced by inositol-triphosphate [IP3] accumulation upon loss of the inositol 5-phosphatase INPP5A or receptor signaling triggers depletion of cholesterol and associated Gb3 from the cell surface, resulting in a blockade of clathrin-independent endocytosis (CIE) of Shiga toxin. This phenotype is caused by the calcium-induced dissociation of oxysterol binding protein (OSBP) from the Golgi complex and from VAP-containing membrane contact sites. Our findings reveal a crucial function for INPP5A-mediated IP3 hydrolysis in the control of lipid exchange at membrane contact sites.

Multi-Objective Evaluation Model of Single-Lane Roundabouts

Mobility, safety, and environmental sustainability are priorities in the geometric design of roundabouts. This paper presents a multi-objective optimization model that determines the geometric design elements of single-lane roundabouts using all three objectives. The user can specify weights for the objectives, or the model can determine the optimal weights. Mobility is defined in terms of roundabout delay and modeled using the United Kingdom empirical model. Safety is modeled in terms of collision frequency based on the methodology of the Highway Safety Manual. Environmental sustainability is represented by vehicle emissions (nitrogen oxides, hydrocarbons, carbon dioxide, and carbon monoxide) and is modeled using the vehicle-specific power methodology. The proposed model directly identifies the optimal geometric dimensions (decision variables) of the roundabout, including entry width, exit width, approach half-width, circulatory width, effective flare length, entry radius, entry angle, and inscribed circle diameter. The input data to the model include traffic data, site conditions, and limitations based on design guidelines. Application of the proposed model is illustrated using two actual roundabouts. The comparison results show that the proposed model provides substantial improvements in safety, mobility, and environmental sustainability compared with existing conditions. In addition, the model requires much less effort to apply compared with the traditional iterative method, and as such should be of interest to highway designers.

Simulation of U-turn traffic based on VISSIM and PARAMICS micro simulation

Traffic simulation models are one of the most important tools that are widely used to analyse and manage transport systems. These tools are used to model complex traffic sites and evaluate various traffic alternatives and testing their effect prior to application in real sites. Median U- turn is an example of such complicated sites. There are many microsimulation tools such as VISSIM, ALIMSUN and PARAMICS. The goal of this study is to develop the simulation model of median U-turns and compares between VISSIM and PARAMICS models. The data were collect from two-selected site at Al-Diwaniyah city, Iraq. The data used in verification of the developed model represent the through traffic volumes and turning traffic volumes at both directions as well as the average queue length created at the U-turn site. The calibration and validation process of the developed models show that both VISSIM and PARAMICS models can provides reasonable approximation for real traffic at the selected site. Further research is needed to examine these tools based on additional sites and to apply such tools to examine different scenarios to enhance traffic conditions at U-turn sites.

Changes in air pollutants during the COVID-19 lockdown in Beijing: Insights from a machine-learning technique and implications for future control policy

The COVID-19 lockdowns led to abrupt reductions in human-related emissions worldwide and had an unintended impact on air quality improvement. However, quantifying this impact is difficult as meteorological conditions may mask the real effect of changes in emissions on the observed concentrations of pollutants. Based on the air quality and meteorological data at 35 sites in Beijing from 2015 to 2020, a machine learning technique was applied to decouple the impacts of meteorology and emissions on the concentrations of air pollutants. The results showed that the real (“deweathered”) concentrations of air pollutants (expect for O3) dropped significantly due to lockdown measures. Compared with the scenario without lockdowns (predicted concentrations), the observed values of PM2.5, PM10, SO2, NO2, and CO during lockdowns decreased by 39.4%, 50.1%, 51.8%, 43.1%, and 35.1%, respectively. In addition, a significant decline for NO2 and CO was found at the background sites (51% and 37.8%) rather than the traffic sites (37.1% and 35.5%), which is different from the common belief. While the primary emissions reduced during the lockdown period, episodic haze events still occurred due to unfavorable meteorological conditions. Thus, developing an optimized strategy to tackle air pollution in Beijing is essential in the future.摘要基于2015–2020年北京35个环境空气站和20个气象站观测资料, 应用机器学习方法 (随机森林算法) 分离了气象条件和源排放对大气污染物浓度的影响. 结果发现, 为应对疫情采取的隔离措施使北京2020年春节期间大气污染物浓度降低了35.1%–51.8%; 其中, 背景站氮氧化物和一氧化碳浓度的降幅最大, 超过了以往报道较多的交通站点. 同时, 2020年春节期间的气象条件不利于污染物扩散, 导致多次霾污染事件发生.为进一步改善北京空气质量, 未来需要优化减排策略.

Fast and High Precise Spatial Documentation of Traffic Accident Site Using Only Low-Cost RPAS

Traffic accident documentation worldwide is generally done by conventional methods (e.g., surveying wheel and steel tapeline) followed by sketch and plan creation. These conventional methods are time-consuming and inaccurate; therefore, they can possibly be replaced by advanced modern methods, using the remotely piloted aircraft system (RPAS) for obtaining data, as well as the structure from motion (SfM) for processing. For the proof of concept, we designed and performed an experiment using low-cost multi-rotor RPAS on an arranged traffic accident involving three cars. The result of this experiment was an accurate 3D model with the possibility of precise measurement. The differences in distances and reference objects’ dimensions were in general below 1% compared to real values. The presented method is time-saving (requiring 85% less time), more precise, and more efficient compared to conventional methods. Moreover, it allows better data reusability, thus is very suitable and can be recommended for usage in routine situations in traffic accident documentation.

Pollution and Risk Assessment of Polycyclic Aromatic Hydrocarbons (Pahs) in Agricultural Soil along a Highway of Jilin Province, China

ABSTRACT The agricultural area adjacent to highways experienced high threat ofpersistent organic pollutants (POPs), which are fromvehicle exhaust, asphalt, and tyre wear.To analyze the presence, distribution patterns, ecological risk and sources of polycyclic aromatic hydrocarbons (PAHs), soil samples were collected in farmland along a highway in Jilin province, China and analyzed for 16 PAHs. The concentration of ∑16PAHs in soil at traffic sites ranged from 781.83-3659.21 ng/g dry weight with the mean value of 2263.78 ng/g, respectively.The PAHs patterns were generally dominated by the high molecular weight (HMW) PAHs, which represented about 65.82% of the total PAHs in traffic sites and 53.52% in control sites of the total 16 PAHs in soil samples. The sources of PAHs in soilwere mainly contaminated by mixed petroleum and combustion. Ecological risk assessment indicated that there were18.33% of the soil samples belong to Moderate-risk 2, and 81.67% of soil samples belong to High-risk. Through the diagnostic ratio analysis, some clean-up measures should be consideredto mitigate local food production risks.