Road traffic and landscape characteristics predict the occurrence of native halophytes on roadside verges.
Ontology highlight
ABSTRACT:
SUBMITTER: Fekete R
PROVIDER: S-EPMC8789788 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Roadside vegetation has been shown to impact downwind, near-road air quality, with some studies identifying reductions in air pollution concentrations and others indicating increases in pollutant levels when vegetation is present. These widely contradictory results have resulted in confusion regarding the capability of vegetative barriers to mitigate near-road air pollution, which numerous studies have associated with significant adverse human health effects. Roadside vegetation studies have investigated the impact of many different types and conditions of vegetation barriers and urban forests, including preserved, existing vegetation stands usually consisting of mixtures of trees and shrubs or plantings of individual trees. A study was conducted along a highway with differing vegetation characteristics to identify if and how the changing characteristics affected downwind air quality. The results indicated that roadside vegetation needed to be of sufficient height, thickness, and coverage to achieve downwind air pollutant reductions. A vegetation stand which was highly porous and contained large gaps within the stand structure had increased downwind pollutant concentrations. These field study results were consistent with other studies that the roadside vegetation could lead to reductions in average, downwind pollutant concentrations by as much as 50% when this vegetation was thick with no gaps or openings. However, the presence of highly porous vegetation with gaps resulted in similar or sometimes higher concentrations than measured in a clearing with no vegetation. The combination of air quality and meteorological measurements indicated that the vegetation affects downwind pollutant concentrations through attenuation of meteorological and vehicle-induced turbulence as air passes through the vegetation, enhanced mixing as portions of the traffic pollution plume are blocked and forced over the vegetation, and through particulate deposition onto leaf and branch surfaces. Computational fluid dynamic modeling highlighted that density of the vegetation barrier affects pollutant levels, with a leaf area density of 3.0 m2 m-3 or higher needed to ensure downwind pollutant reductions for airborne particulate matter. These results show that roadside bushes and trees can be preserved or planted along highways and other localized pollution sources to mitigate air quality and human health impacts near the source if the planting adheres to important characteristics of height, thickness, and density with full coverage from the ground to the top of the canopy. The results also highlight the importance of planting denser vegetation and maintaining the integrity and structure of these vegetation barriers to achieve pollution reductions and not contribute to unintended increases in downwind air pollutant concentrations.
| S-EPMC7339705 | biostudies-literature
Project description:Road traffic injuries are a leading cause of morbidity and mortality globally. Understanding circumstances leading to road traffic injury is crucial to improve road safety, and implement countermeasures to reduce the incidence and severity of road trauma. We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. Data were extracted from the Victorian State Trauma Registry for motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians with a no-fault compensation claim, aged > = 16 years and injured 2010-2016. People with intentional injury, serious head injury, no compensation claim/missing injury event description or who died < = 12-months post-injury were excluded, resulting in a sample of 2,486. Text mining of the injury event using QDA Miner and Wordstat was used to classify crash circumstances for each road user group. Crashes in which no other was at fault included circumstances involving lost control or avoiding a hazard, mechanical failure or medical conditions. Collisions in which another was predominantly at fault occurred at intersections with another vehicle entering from an adjacent direction, and head-on collisions. Crashes with higher prevalence of unknown fault included multi-vehicle collisions, pedal cyclists injured in rear-end collisions, and pedestrians hit while crossing the road or navigating slow traffic areas. We discuss several methods to promote road safety and to reduce the incidence and severity of road traffic injuries. Our recommendations take into consideration the incidence and impact of road trauma for different types of road users, and include engineering and infrastructure controls through to interventions targeting or accommodating human behaviour.
| S-EPMC7840051 | biostudies-literature
Project description:Road traffic mortalities (RTMs), a leading cause of death globally, mostly occur in low- and middle-income countries, and having sufficient healthcare resources could lower the number of these fatalities. Our study aimed to illustrate the incidence of RTMs per 100,000 population and to compare the distribution of healthcare resources from 2011 to 2021 with rates of RTMs in the 77 provinces of Thailand. We divided the population into adults (≥ 15 years) and children (0-14 years). Lorenz curve and Gini coefficient were used to measure the level of distribution and equality of hospital resources and in relation to RTMs across the country. The average number of deaths was 30.34 per 100,000 per year, with male predominance. The RTM rates for adults and children were 32.71 and 19.08 per 100,000 respectively, and motorcycle accidents accounted for the largest percentage of deaths across all age groups. The Gini coefficient showed that operating rooms (0.42) were the least equally distributed hospital resource, while physicians were the most equally distributed (0.34). Anomalies were identified between the distribution of RTMs and available hospital resources. We hope our study will be beneficial in reallocating these resources more fairly to reflect the different numbers of traffic accidents in each province with the aim of reducing lower traffic-related deaths.
| S-EPMC9686261 | biostudies-literature
Project description:BackgroundRoad traffic injury (RTI) is a significant yet poorly characterized cause of morbidity and mortality in the Middle East. This hospital-based-study examined RTI in Lebanon and provided an understanding of their characteristics.MethodsWe collected prospective RTI data from three participating hospitals over 3 months using a designed tool based on Canadian CHIRPP and WHO tools. We performed logistic regression analysis to examine the relationship between contributing risk factors (age, sex) and injury types as well as the association of safety measures used (seatbelts or helmets) and body parts injured.ResultsA total of 153 patients were collected. Male preponderance with 72%, with mean age 32.6 (SD = 14.9) years. RTI was highest among passengers aged 15 to 29 (48%). Motorcyclists comprised the greatest injury proportion (38%), followed by vehicle-occupants (35%), and pedestrians (25%) (P = .04). Hip injuries represented the most affected body part (48.7%), followed by head/neck (38.2%). Only 31% (n = 47) of victims applied safety measures (seatbelts or helmets). Six drivers (7%) reported cell phone use at collision. The use of safety measures was associated with a substantial reduction in head/neck injuries (P = .03), spine injuries (P = .049), and lower risk of traumatic brain injury (TBI) (P = .02).ConclusionsRTI is a major health problem in Lebanon. Safety measures, though poorly adhered to, were associated with less severe injuries, and should be further promoted via awareness campaigns and enforcement. Trauma registries are needed to assess the RTI burden and inform safety interventions and quality-of-care improvement programs.
| S-EPMC8611407 | biostudies-literature
Project description:An increasing number of children are exposed to road traffic noise levels that may lead to adverse effects on health and daily functioning. Childhood is a period of intense growth and brain maturation, and children may therefore be especially vulnerable to road traffic noise. The objective of the present study was to examine whether road traffic noise was associated with reported inattention symptoms in children, and whether this association was mediated by sleep duration.This study was based on the Norwegian Mother and Child Cohort Study conducted by the Norwegian Institute of Public Health. Parental reports of children's inattention at age 8 were linked to modelled levels of residential road traffic noise. We investigated the association between inattention and noise exposure during pregnancy (n = 1934), noise exposure averaged over 5 years (age 3 to 8 years; n = 1384) and noise exposure at age 8 years (n = 1384), using fractional logit response models. The participants were children from Oslo, Norway.An association with inattention at age 8 years was found for road traffic noise exposure at age 8 years (coef = .0083, CI = [.0012, .0154]; 1.2% point increase in inattention score per 10 dB increase in noise level), road traffic noise exposure average for the last 5 years (coef = .0090, CI = [.0016, .0164]; 1.3% point increase/10 dB), and for pregnancy road traffic noise exposure for boys (coef = .0091, CI = [.0010, .0171]), but not girls (coef = -.0021, CI = [-.0094, .0053]). Criteria for doing mediation analyses were not fulfilled.Results indicate that road traffic noise has a negative impact on children's inattention. We found no mediation by sleep duration.
| S-EPMC5698983 | biostudies-literature
Project description:BackgroundTo present the new trends in epidemiology of road traffic injuries (RTIs) during the Coronavirus disease 2019 (COVID-19) pandemic in Suzhou.MethodsPre-hospital records of RTIs from January to May in 2020 and the same period in 2019 were obtained from the database of Suzhou pre-hospital emergency center, Jiangsu, China. Data were extracted for analysis, including demographic characteristics, pre-hospital vital signs, transport, shock index, consciousness, pre-hospital death. A retrospective study comparing epidemiological characteristics of RTIs in Suzhou during the 5-month period in 2020 to the parallel period in 2019 was performed.ResultsA total of 7288 RTIs in 2020 and 8869 in 2019 met inclusion criteria. The overall volume of RTIs has statistical difference between the 2 years (p < 0.001), with fewer RTIs in 2020 compared with 2019. Electric bicycle related RTIs increased during the pandemic (2641, 36.24% vs 2380, 26.84%, p < 0.001), with a higher incidence of RTIs with disorder of consciousness (DOC) (7.22% vs 6.13%, p = 0.006).ConclusionsUnder the impact of COVID-19, the total number of RTIs in Suzhou from January to May 2020 decreased. This observation was coupled with a rise in electric bicycle related injuries and an increase in the incidence of RTIs with DOC.
| S-EPMC8312208 | biostudies-literature
Project description:BackgroundRoad traffic accidents are one of the serious disasters that cause public injury, fatality and great economic loss. They are a growing public health problem around the world.ObjectivesThe aim of this study was to determine epidemiological characteristics, tendency and possible influencing factors of road traffic injuries (RTIs) in China, so as to give target suggestions on preventative measures.MethodsRoad traffic accident data were obtained from National Bureau of Statistics of China and Ministry of Transport of the People's Republic of China. Descriptive statistic such as RTIs frequency, trends of different accident types from 2007 to 2016; the RTIs difference between different regions and road surfaces were compared; and the possible influencing factors of RTIs were also explored.ResultsOver the past decade, with the mileage of constructed highway increased, the frequency of road traffic accidents have declined substantially in China, and the death toll from road traffic accidents with motor vehicles has declined from 2007 to 2015, Conversely, the number of deaths from non-motor vehicle accidents has risen rapidly since 2012. Our study showed that the traffic accident related mortality in Guizhou province was different from the level of the whole nation, and the Eastern, Central and Western areas of China were all significantly different (P < 0.001). Linear regression suggested a significant affected of gross domestic product (GDP)-per-capita, education level, the number of health institutions, populations, and car ownership status on traffic accident death tolls (P < 0.001). Moreover, cement concrete pavement roads were associated with the highest occurrence rates of RTI, and RTIs was statistically significant (P < 0.001) on different road surfaces.ConclusionEven though the frequency of road traffic accidents has declined, RTIs remain an urgent public health problem in China. Thus, the government should give some target preventative measures to reduce RTIs, aiming at different regions, the increasing trend of the death toll related to non-motor vehicles and the highest occurrence on cement concrete pavement roads.
| S-EPMC6688591 | biostudies-literature
Project description:Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.
| S-EPMC3929915 | biostudies-literature
Project description:Accurate estimation of traffic emissions and analysis of spatio-temporal distribution on urban roads play a crucial role in the development of low-carbon transportation system. Traditionally, a region's emission characteristics have been studied using numerous emission models with GPS-based spatio-temporal data. Due to the heavy data processing needs of GPS-based data, emission characteristics for a large region have been studied by dividing the region into a limited number of smaller areas or units. Additionally, GPS data are based on a few vehicles in the traffic which does not fully reflect road conditions. This paper proposed an approach that can be used to study and calculate the spatio-temporal emission pattern of a region at a roadway section level by using Baidu's online traffic data and COPERT model. The proposed method can be used to estimate road-level emission patterns while avoiding the impact of redundant data in large datasets, making the dataset more reliable, applicable, and scalable. The proposed approach has been demonstrated through a study of spatio-temporal emission patterns in the Qiaoxi district within city of Shijiazhuang, China. Online data crawling technology was used to obtain data on urban road traffic speed and driving distance. The linear reference technology was used to construct a two-layer road network model to conduct the coupling and matching of traffic data with the road network data. The COPERT model was implemented to calculate the average traffic emissions on each road in the road network, and a traffic emission intensity index was proposed to quantify the CO, VOC, NOx and CO2 emissions on urban roads in the study area. The analysis results show that the traffic emission intensity of the expressway, trunk road, secondary road, and branch road is high during the morning peak (7 AM-9 AM) and evening peak (5 PM-7 PM). The sections with higher traffic emission intensity are mainly concentrated on the main roads and secondary roads such as Jiefang South Street, Shitong Road and Xinhua Road. Nearly one-third of 2nd Ring and 3rd Ring roads also have relatively high emission intensity. The research results provide new ideas for estimating traffic emissions in urban road networks and analyzing the spatio-temporal distribution of traffic emissions. The research results can also provide a decision-making basis for traffic management departments to formulate energy-saving and emission-reduction measures and promote the development of urban green and low-carbon transportation.
| S-EPMC10718443 | biostudies-literature
Project description:BackgroundBoth road safety campaigns and epidemiological research into social differences in road traffic injury risk often assume that road traffic injuries occur close to home. While previous work has examined distance from home to site of collision for child pedestrians in local areas, less is known about the geographic distribution of road traffic injuries from other modes. This study explores the distribution of the distance between home residence and collision site (crash distance) by mode of transport, geographic area, and social characteristics in England.MethodsUsing 10 years of road casualty data collected by the police, we examined the distribution of crash distance by age, sex, injury severity, area deprivation, urban/rural status, year, day of week, and, in London only, ethnic group.Results54% of pedestrians, 39% of cyclists, 17% of powered two-wheeler riders and 16% of car occupants were injured within 1 km of home. 82% of pedestrians, 83% of cyclists, 54% of powered two-wheeler and 53% of car occupants were injured within 5 km of home. We found some social and geographic differences in crash distance: for all transport modes injuries tended to occur closer to home in more deprived or urban areas; younger and older pedestrians and cyclists were also injured closer to home. Crash distance appears to have increased over time for pedestrian, cyclist and car occupant injuries, but has decreased over time for powered two-wheeler injuries.ConclusionsInjuries from all travel modes tend to occur quite close to home, supporting assumptions made in epidemiological and road safety education literature. However, the trend for increasing crash distance and the social differences identified may have methodological implications for future epidemiological studies on social differences in injury risk.
| S-EPMC3680192 | biostudies-literature