Land transportation is a major source of heavy metal contamination along the roadside, posing significant risks to human health through inhalation, oral ingestion, and dermal contact. Therefore, this study has been designed to determine the concentrations of vehicular released heavy metals (Cd, Pb, Ni, and Cu) in roadside soil and leaves of two commonly growing native plant species (Calotropis procera and Nerium oleander).Two busy roads i.e., Lahore-Okara road (N-5) and Okara-Faisalabad roads (OFR) in Punjab, Pakistan, were selected for the study. The data were collected from five sites along each road during four seasons. Control samples were collected ~ 50 m away from road. The metal content i.e. lead (Pb), cadmium (Cd) nickel (Ni) and copper (Cu) were determined in the plant leaves and soil by using Atomic Absorption Spectrophotometer (AAS). Significantly high amount of all studied heavy metals were observed in soil and plant leaves along both roads in contrast to control ones. The mean concentration of metals in soil ranged as Cd (2.20-6.83 mg/kg), Pb (4.53-15.29 mg/kg), Ni (29.78-101.26 mg/kg), and Cu (61.68-138.46 mg/kg) and in plant leaves Cd (0.093-0.53 mg/kg), Pb (4.31-16.34 mg/kg), Ni (4.13-16.34 mg/kg) and Cu (2.98-32.74 mg/kg). Among roads, higher metal contamination was noted along N-5 road. Significant temporal variations were also noted in metal contamination along both roads. The order of metal contamination in soil and plant leaves in different seasons was summer > autumn > spring > winter. Furthermore, the metal accumulation potential of Calotropis procera was higher than that of Nerium oleander. Therefore, for sustainable management of metal contamination, the plantation of Calotropis procera is recommended along roadsides.

Exposure to traffic-related air pollution (TRAP) generates oxidative stress, with downstream effects at the metabolic level. Human studies of traffic density and metabolomic markers, however, are rare. The main objective of this study was to evaluate the cross-sectional association between traffic density in the street of residence with oxidative stress and metabolomic profiles measured in a population-based sample from Spain. We also explored in silico the potential biological implications of the findings. Secondarily, we assessed the contribution of oxidative stress to the association between exposure to traffic density and variation in plasma metabolite levels. Traffic density was defined as the average daily traffic volume over an entire year within a buffer of 50 m around the participants\' residence. Plasma metabolomic profiles and urine oxidative stress biomarkers were measured in samples from 1181 Hortega Study participants by nuclear magnetic resonance spectroscopy and high-performance liquid chromatography, respectively. Traffic density was associated with 7 (out of 49) plasma metabolites, including amino acids, fatty acids, products of bacterial and energy metabolism and fluid balance metabolites. Regarding urine oxidative stress biomarkers, traffic associations were positive for GSSG/GSH% and negative for MDA. A total of 12 KEGG pathways were linked to traffic-related metabolites. In a protein network from genes included in over-represented pathways and 63 redox-related candidate genes, we observed relevant proteins from the glutathione cycle. GSSG/GSH% and MDA accounted for 14.6% and 12.2% of changes in isobutyrate and the CH2CH2CO fatty acid moiety, respectively, which is attributable to traffic exposure. At the population level, exposure to traffic density was associated with specific urine oxidative stress and plasma metabolites. Although our results support a role of oxidative stress as a biological intermediary of traffic-related metabolic alterations, with potential implications for the co-bacterial and lipid metabolism, additional mechanistic and prospective studies are needed to confirm our findings.

Roads and traffic are important elements of urbanization, but their spatial associations with surface water quality in watersheds have been seldom studied. In this study, the spatially varying associations of three urbanization indicators, including road density, traffic density, and percentages of urban land, with twenty water quality indicators, including dissolved oxygen (DO), specific conductance (SC), dissolved solids (DS), suspended solids (SS), biochemical oxygen demand (BOD), dissolved nutrients, dissolved ions, heavy metals, and coliform bacteria, across the watersheds in the northern part of the state of Georgia, USA, have been examined by a conventional statistical method, ordinary least squares regression (OLS), and a spatial statistical method, geographically weighted regression (GWR). The results from OLS show that the urbanization indicators all have significant positive associations with the majority of the studied water pollutants, indicating that water pollution is significantly contributed by human activities related to urbanization in northern Georgia. In contrast, GWR results show that the associations vary across the watersheds affected by their urbanization levels. Significant positive associations are found between each urbanization indicator and each of the studied water pollutants, but not in all watersheds. The associations of suspended solids, nitrogen nutrients, and coliform bacteria with all three urbanization indicators are more significant in less-urbanized watersheds, while the associations of dissolved ions, BOD, and orthophosphate (PO4) with road density and traffic density are more significant than those with urban land in more-urbanized watersheds, indicating that those water pollutants are more contributed by human activities associated with roads and traffic than other activities in more-urbanized areas. As a pilot study to explore how and why the associations of surface water quality with roads and traffic change across watersheds with different urbanization levels, its findings suggest that the policies of watershed management, land-use planning, and transportation planning should be tailored in local areas based on the locally important water pollutants and their associated urbanization indicators.

Stay-at-home orders - imposed to prevent the spread of COVID-19 - drastically changed the way highways operate. Despite lower traffic volumes during these times, the rate of fatal and serious injury crashes increased significantly across the United States due to increased speeding on roads with less traffic congestion and lower levels of speed enforcement. This paper uses a mixed effect binomial regression model to investigate the impact of stay-at-home orders on odds of speeding on urban limited access highway segments in Maine and Connecticut. This paper also establishes a link between traffic density and the odds of speeding. For this purpose, hourly speed and volume probe data were collected on limited access highway segments for the U.S. states of Maine and Connecticut to estimate the traffic density. The traffic density was then combined with the roadway geometric characteristics, speed limit, as well as dummy variables denoting the time of the week, time of the day, COVID-19 phases (before, during and after stay-at-home order), and the interactions between them. Density, represented in the model as Level of Service, was found to be associated with the odds of speeding, with better levels of service such as A, or B (low density) resulting in the higher odds that drivers would speed. We also found that narrower shoulder width could result in lower odds of speeding. Furthermore, we found that during the stay-at-home order, the odds of speeding by more than 10, 15, and 20 mph increased respectively by 54%, 71% and 85% in Connecticut, and by 15%, 36%, and 65% in Maine during evening peak hours. Additionally, one year after the onset of the pandemic, during evening peak hours, the odds of speeding greater than 10, 15, and 20 mph were still 35%, 29%, and 19% greater in Connecticut and 35% 35% and 20% greater in Maine compared to before pandemic.

The characteristics of dissolved organic matter (DOM) in road runoff under different traffic densities were compared using resin fractionation, molecular weight distribution analysis, three-dimensional excitation-emission matrix fluorescence spectroscopy, and UV-visible spectroscopy. Heavy traffic density strongly increased the concentration of DOM in road runoff, resulting in higher dissolved organic carbon. The distribution of molecular weights in DOM was not influenced by the traffic. DOM was dominated by colloidal organic matter with molecular weight in the 1 kDa to 0.45 μm size range. Hydrophobic fractions accounted for a large proportion than hydrophilic fractions in DOM, and hydrophobic acids increased with higher traffic density. Traffic density did not alter the fluorescent substances in DOM, including fulvic-like UV fluorescent substances and protein-like substances. However, more tryptophan-like protein substances were found in DOM from road runoff with heavy traffic. Moreover, the aromatization degree of DOM was not affected by heavy traffic, while the degree of humification decreased.

Background: Traffic-related pollution is associated with the onset of asthma and the development of different phenotypes of asthma. Few studies have investigated the association between traffic proximity and late-onset of asthma (LOA) and early-onset asthma (EOA). This study was conducted to investigate the associations of LOA phenotypes with a function of the distance between residence and heavy traffic roads (HTRs). Methods: The study group consisted of 280 patients who were (LOA: 78.4%) recruited consecutively from a pay-for-performance asthma program to clarify the patient characteristics and proximity to HTRs within 1,000 m from their residences between EOA and LOA in three urban centers in Taiwan. The subsequent analysis focused on patients with LOA (n = 210) linking phenotypes and distance to HTRs. Results: Subjects with LOA tended to be older than those with EOA and had shorter asthma duration, poorer lung function, lower atopy, and less exposure to fumes or dust at home. Patients with LOA were more likely than those with EOA to live within 900 m of two or more HTRs (14.3 vs. 3.4%, p = 0.02). Among patients with LOA, minimum distance to an HTR was negatively associated with numbers of specific IgE as well as positively associated with the age of onset and body weight significantly. A higher proportion of patients with atopy (26.3 vs. 20.6%, p = 0.001. odds ratio [OR]: 2.82) and anxiety/depression (21.0 vs. 18.1%, p = 0.047. OR: 1.81) and a trend of lower proportion of patients with obese (5.7 vs. 12.4%, p = 0.075) were found to be living within 900 m from HTRs. Conclusions: Late-onset of asthma (LOA) tended to live in areas of higher HTR density compared to EOAs. Among patients with LOA living close to HTRs, the interaction between traffic-related pollution, allergy sensitization, and mood status were the factors associated with asthma onset early. Obesity may be the factor for later onset who live far from HTRs.

Black carbon is one of the riskiest particle matter pollutants that is harmful to human health. Although it has been increasingly investigated, factors that depend on black carbon distribution and concentration are still insufficiently researched. Variables, such as traffic density, wind speeds, and ground levels can lead to substantial variations of black carbon concentrations and potential exposure, which is even riskier for people living in less-airy sites. Therefore, this paper \"fills the gaps\" by studying black carbon distribution variations, concentrations, and oscillations, with special emphasis on traffic density and road segments, at multiple locations, in a small city located in a basin, with frequent temperature inversions and infrequent low wind speeds. As wind speed has a significant impact on black carbon concentration trends, it is critical to present how low wind speeds influence black carbon dispersion in a basin city, and how black carbon is dependent on traffic density. Our results revealed that when the wind reached speeds of 1 ms-1, black carbon concentrations actually increased. In lengthy wind periods, when wind speeds reached 2 or 3 ms-1, black carbon concentrations decreased during rush hour and in the time of severe winter biomass burning. By observing the results, it could be concluded that black carbon persists longer in higher altitudes than near ground level. Black carbon concentration oscillations were also seen as more pronounced on main roads with higher traffic density. The more the traffic decreases and becomes steady, the more black carbon concentrations oscillate.

Air pollution is becoming increasingly dangerous which is quite a significant issue of today\'s world, especially air pollution from heavy metal, whose emission increases with industrial and traffic activities. This is of great importance in terms of environmental pollution and human health. Heavy metals do not deteriorate and disappear easily on earth. They are liable to bioaccumulate within cells in organisms. Most of them demonstrate harmful effects in addition as a result of advanced accumulation, and thus they emerge as toxic and carcinogenic. Therefore, it is of great importance to observe the changes in heavy metal concentrations in the air. One of the most effective techniques for monitoring the change of heavy metal concentrations in the atmosphere is the use of annual rings of trees as biomonitors. In this study, in the annual rings of the Cedrus atlantica Manetti tree cut at the Kastamonu province at the end of 2019, the variation of the concentrations of some of the heavy metals most associated with traffic density was tried to be determined. Within the scope of the study, Cr and Mn concentration in the outer bark and the inner bark was compared with the direction and wood for the variation of heavy metal concentrations. Also, variance analysis and Duncan test were applied and evaluated. As a result of the study, while the highest values in many heavy metals are generally obtained in the outer bark, the transfer of metals in the wood is limited, and some heavy metal concentrations change significantly depending on the direction, especially in the wood. This change is related to the traffic density, so Cedrus atlantica Manetti annual rings are very suitable as biomonitors for air pollution control.

Elevated noise level is an emerging global problem. Therefore, the present work is conducted that can improve, increase, and integrate the already known issue in literature with new information coming from an emerging country such as Pakistan. The objectives of this study were (i) to assess the urban noise levels and traffic density of Chiniot and Jhang and (ii) to determine nonauditory health effects of noise levels on the residents of both cities. Noise levels were examined from 181 locations (103 from Jhang and 78 from Chiniot) and categorized into hospitals, educational, religious and recreational, residential, industrial areas, and traffic intersections. A-weighted noise level measurements were taken using an integrated sound level meter which recorded short-term road traffic noise continuously for 15 min at each location (LAeq15). The urban noise data showed 82% of the sites in Jhang (LAmax = 103 dB) and 95% in Chiniot (LAmax = 120 dB) exceeded the noise limits set by the National Environment Quality Standard of Pakistan (NEQS-Pak) and World Health Organization (WHO). Moreover, higher intensity of noise levels (LAeq15 ≥ 100 dB) was recorded in Chiniot (17 sites) than in Jhang (1 site). Regression analysis showed a relatively strong relationship of traffic density with noise at Chiniot (R2 = 0.48) compared to Jhang (R2 = 0.31). However, spatial variability of noise with traffic density was observed in both cities. Survey study revealed that all the respondents in Jhang and Chiniot suffered from many noise-related health problems such as annoyance (53 and 51%), depression (45 and 47%), dizziness (61 and 65%), headache (67 and 64%), hypertension (71 and 56%), hearing loss (53 and 56%), physiological stress (65 and 65%), sleeplessness (81 and 84%), and tinnitus (70 and 62%) due to noise, respectively. We conclude that noise levels are higher in Chiniot primarily due to high road traffic and secondarily due to high population density. It is recommended that vehicle maintenance and family and urban planning could be effective measures to reduce urban noise levels.

Based on Global Navigation Satellite Systems (GNSS) and Internet of Vehicles (IoV), collision warning systems can provide drivers specific warning information such as the position of hazardous vehicles. However, positioning technologies vary in accuracy. Highly accurate positioning technologies are theoretically favorable for driving safety but are relatively difficult to use widely due to the high cost. While many researchers compared accuracies of different positioning technologies or explored methods to improve accuracy, few directly investigated the effect of different positioning accuracies for hazardous vehicles on driving safety. The present study conducted a laboratory experiment to explore the effect of four positioning accuracies of hazardous vehicles (i.e., highest: 1.5 m, high: 5 m, medium: 8.5 m, and low: 20 m, each value represented the radius of a circle and the estimated positions of hazardous vehicle were within this circle) and different traffic densities (high: one car per 150 m and low: one car per 1500 m) on driver behaviors. Thirty participants were distributed into high and low traffic density groups. Each participant received auditory warning information, which provided positions of hazardous vehicles relative to the ego vehicle concerning four accuracy levels. Driving safety (i.e., number of collisions and min TTC), driving performance (i.e., brake onset reaction time, steer onset reaction time, and mean deceleration), and subjective workload for warnings with different positioning accuracies of hazardous vehicles were recorded and analyzed. Results suggested the following: 1) Under low traffic density, four positioning accuracies showed no significant differences on driving safety and performance as well as subjective workload. 2) Under high traffic density, the medium positioning accuracy (8.5 m) exerted no significant differences on driving safety and performance compared with the highest positioning accuracy (1.5 m), which had the fastest brake onset reaction time, the least number of collisions, and the largest mean deceleration. Moreover, when traffic density was high, warnings with the highest (1.5 m), high (5 m), and medium (8.5 m) positioning accuracies generated a significantly lower workload than the warning with low (20 m) positioning accuracy. In conclusion, low positioning accuracy (20 m), which was a general accuracy of A-GNSS (no added cost) or GNSS (SPP) (relatively low cost) in dense urban area, was feasible for providing warnings under low traffic density. Medium positioning accuracy (8.5 m), which was the accuracy of A-GNSS (no added cost) in open-sky area, was acceptable for supporting warning systems under high traffic density. These findings have implications for promoting the application of positioning technologies to realize warnings in the near future.