Moss (as a reference material) and camphor (Cinnamomum Camphora) leaf, branch bark and bark samples were systematically collected across an urban-rural gradient in Guiyang (SW China) to determine the efficacy of using these bio-indicators to evaluate nitrogen (N) pollution. The tissue N concentrations (0.13%–2.70%) and δ¹⁵N values (−7.5‰ to +9.3‰) of all of these bio-indicators exhibited large spatial variations, as they recorded higher values in urban areas that quickly decreased with distance from the city center; moreover, both soil N concentrations and soil δ¹⁵N values were found no significant differences within each 6 km from the urban to the rural area. This not only suggests that the different N uptake strategies and variety of N responses of these bio-indicators can be reflected by their different susceptibilities to variations in N deposition but also reveals that they are able to indicate that urban N deposition is mostly from traffic and industry (NOₓ-N), whereas rural N deposition is mainly from agriculture (NHₓ-N). Compared to previously collected urban moss and camphor leaf samples, the significantly increased δ¹⁵N values in current urban moss and camphor leaf samples further indicate a greater contribution of NOₓ-N than NHₓ-N to urban N deposition. The feasibility of using the N concentrations and δ¹⁵N values of branch bark and bark as biomarkers of N deposition thus was further confirmed through the comparative use of these bio-indicators. It can be concluded that vascular plant leaves, branch bark and bark can be used as useful biomonitoring tools for evaluating atmospheric N pollution. For further study, quantitative criteria for the practical use of these bio-indicators in response to N deposition should be developed and the differences in the δ¹⁵N values of different plant parts should also be considered, particularly in urban environments that are severely disrupted by atmospheric pollution.

Although several air pollution studies have examined the relationship between people living close to roadways and human health, we are unaware of studies that have examined the distance-decay of this effect based on a snapshot of congestion and focused on a micro-level traffic emission inventory. In this paper we estimate the distance-decay of premature mortality risk related to PM₂.₅ emitted by traffic congestion in Hamilton, Canada, in 2011 We employ the Stochastic User Equilibrium (SUE) traffic assignment algorithm to estimate congested travel times for each road link in our study area. Next, we used EPA's MOVES model to estimate mass of PM₂.₅, and then R-line dispersion model to predict concentration of PM₂.₅. Finally, we apply Integrated Exposure Response Function (IERF) to estimate PM₂.₅-related premature mortality at 100 m × 100 m grid resolution. We estimated total premature mortality over Hamilton to be 73.10 (95%CI: 39.05; 82.11) deaths per year. We observed that the proximity to a roadway increases the risk of premature mortality and the strength of this risk decreases as buffer sizes are increased. For example, we estimated that the premature mortality risk within buffer 0–100 m is 29.5% higher than for the buffer 101–200 m, 179.3% higher than for the buffer 201–300 m, and 566% higher than for the buffer 301–400 m. Our study provides a new perspective on exposure increments from traffic congestion. In particular, our findings show health effects gradients across neighborhoods, capturing microscale near-road exposure up to 2000 m of the roadway. Results from this research can be useful for policymakers to develop new strategies for the challenges of regulating transportation, land use, and air pollution.

The structure and organization of acoustic signals arise through evolutionary processes and adaptive pressures on each species. During learning, natural or anthropogenic factors, such as high noise levels in urban areas, pose challenges to acoustic communication in birds. Many species adjust their acoustic signals to higher noise levels by increasing the frequency of vocalizations. The objectives of this study were to compare the dominant frequency of songs among birds dwelling in forest fragments distant from and near to urban areas, establish correlations between the dominant frequency of song and noise levels in these environments and verified the difference of response between oscines, suboscines and non-passerines. We recorded vocalizations of birds between July/2013 and November/2014 in four forest fragments, two of them near and two distant from urban areas. We used Audacity software to measure the dominant frequency. We measured the ambient noise by a calibrated sound pressure level meter in decibels (dBA) in each of the forest fragments. We analyzed 3740 vocalizations of nine tropical bird species. Forest fragments near to urban areas have higher noise levels than more distant forest fragments. Eight of nine studied species presented higher dominant frequencies of songs in forest fragments near to urban areas. Only one species, Myiothlypis flaveola, did not change the dominant frequency of song between the four analyzed forest fragments. The difference in dominant frequency between the forest fragments distant and closer to the urban areas did not vary between oscines, suboscines and non-passerines. Eight tropical birds exhibited higher dominant frequencies of song in forest fragments near urban areas with high level of ambient noise. Oscine, suboscine and non-passerine showed song variations. Bird species that have differences in the vocalization dominant frequency can be used in environmental monitoring and in ethological studies, as they are sensitive to high noise levels.Noise pollution caused by the vehicular traffic and urbanization are correlates with changes in the vocalization of tropical birds in forest fragments.

A series of field samples including ambient air (gaseous and particulate phases), dust fall, surface soil, rhizosphere soil and cabbage tissues (leaf, root and core), were collected in vegetable bases near a large coking manufacturer in Shanxi Province, Northern China, during a harvest season. A factor analysis was employed to apportion the emission sources of polycyclic aromatic hydrocarbons (PAHs), and the statistical results indicated coal combustion was the dominant emission source that accounted for different environmental media and cabbage tissues, while road traffic, biomass burning and the coking industry contributed to a lesser extent. A structural equation model was first developed to quantitatively explore the transport pathways of PAHs from surrounding media to cabbage tissues. The modeling results showed that PAHs in ambient air were positively associated with those in dust fall, and a close relationship was also true for PAHs in dust fall and in surface soil due to air-soil exchange process. Furthermore, PAHs in surface soil were correlated with those in rhizosphere soil and in the cabbage leaf with the path coefficients of 0.83 and 0.39, respectively. PAHs in the cabbage leaf may dominantly contribute to the accumulation of PAHs in the edible part of cabbages.

The relative impact of non-exhaust sources (i.e. road dust, tire wear, road wear and brake wear particles) on urban air quality is increasing. Among them, road dust resuspension has generally the highest impact on PM concentrations but its spatio-temporal variability has been rarely studied and modeled. Some recent studies attempted to observe and describe the time-variability but, as it is driven by traffic and meteorology, uncertainty remains on the seasonality of emissions. The knowledge gap on spatial variability is much wider, as several factors have been pointed out as responsible for road dust build-up: pavement characteristics, traffic intensity and speed, fleet composition, proximity to traffic lights, but also the presence of external sources. However, no parameterization is available as a function of these variables.We investigated mobile road dust smaller than 10 μm (MF10) in two cities with different climatic and traffic conditions (Barcelona and Turin), to explore MF10 seasonal variability and the relationship between MF10 and site characteristics (pavement macrotexture, traffic intensity and proximity to braking zone). Moreover, we provide the first estimates of emission factors in the Po Valley both in summer and winter conditions. Our results showed a good inverse relationship between MF10 and macro-texture, traffic intensity and distance from the nearest braking zone. We also found a clear seasonal effect of road dust emissions, with higher emission in summer, likely due to the lower pavement moisture. These results allowed building a simple empirical mode, predicting maximal dust loadings and, consequently, emission potential, based on the aforementioned data. This model will need to be scaled for meteorological effect, using methods accounting for weather and pavement moisture. This can significantly improve bottom-up emission inventory for spatial allocation of emissions and air quality management, to select those roads with higher emissions for mitigation measures.

Adult coho salmon (Oncorhynchus kisutch) prematurely die when they return from the ocean to spawn in urban watersheds throughout northwestern North America. The available evidence suggests the annual mortality events are caused by toxic stormwater runoff. The underlying pathophysiology of the urban spawner mortality syndrome is not known, and it is unclear whether closely related species of Pacific salmon are similarly at risk. The present study co-exposed adult coho and chum (O. keta) salmon to runoff from a high traffic volume urban arterial roadway. The spawners were monitored for the familiar symptoms of the mortality syndrome, including surface swimming, loss of orientation, and loss of equilibrium. Moreover, the hematology of both species was profiled by measuring arterial pH, blood gases, lactate, plasma electrolytes, hematocrit, and glucose. Adult coho developed behavioral symptoms within a few hours of exposure to stormwater. Various measured hematological parameters were significantly altered compared to coho controls, indicating a blood acidosis and ionoregulatory disturbance. By contrast, runoff-exposed chum spawners showed essentially no indications of the mortality syndrome, and measured blood hematological parameters were similar to unexposed chum controls. We conclude that contaminant(s) in urban runoff are the likely cause of the disruption of ion balance and pH in coho but not chum salmon. Among the thousands of chemicals in stormwater, future forensic analyses should focus on the gill or cardiovascular system of coho salmon. Because of their distinctive sensitivity to urban runoff, adult coho remain an important vertebrate indicator species for degraded water quality in freshwater habitats under pressure from human population growth and urbanization.

Bogota registers frequent episodes of poor air quality from high PM₁₀ concentrations. It is one of the main Latin American megacities, located at 2600 m in the tropical Andes, but there is insufficient data on PM₁₀ source contribution. A characterization of the chemical composition and the source apportionment of PM₁₀ at an urban background site in Bogota was carried out in this study. Daily samples were collected from June 2015 to May 2016 (a total of 311 samples). Organic carbon (OC), elemental carbon (EC), water soluble compounds (SO₄²⁻, Cl⁻, NO₃⁻, NH₄⁺), major elements (Al, Fe, Mg, Ca, Na, K, P) and trace metals (V, Cd, Pb, Sr, Ba, among others) were analyzed. The results were interpreted in terms of their variability during the rainy season (RS) and the dry season (DS). The data obtained revealed that the carbonaceous fraction (∼51%) and mineral dust (23%) were the main PM₁₀ components, followed by others (15%), Secondary Inorganic Compounds (SIC) (11%) and sea salt (0.4%). The average concentrations of soil, SIC and OC were higher during RS than DS. However, peak values were observed during the DS due to photochemical activity and forest fires. Although trace metals represented <1% of PM₁₀, high concentrations of toxic elements such as Pb and Sb on RS, and Cu on DS, were obtained. By using a PMF model, six factors were identified (∼96% PM₁₀) including fugitive dust, road dust, metal processing, secondary PM, vehicles exhaust and industrial emissions. Traffic (exhaust emissions + road dust) was the major PM₁₀ source, accounting for ∼50% of the PM₁₀. The results provided novel data about PM₁₀ chemical composition, its sources and its seasonal variability during the year, which can help the local government to define control strategies for the main emission sources during the most critical periods.

Multiple cross-sectional studies indicated an association between hypertension and road traffic noise and they were recently synthetized in a WHO systematic evidence review. However, recent years have seen a growing body of high-quality, large-scale research, which is missing from the WHO review. Therefore, we aimed to close that gap by conducting an updated systematic review and meta-analysis on the exposure-response relationship between residential road traffic noise and the risk of hypertension in adults. Studies were identified by searching MEDLINE, EMBASE, the Internet, conference proceedings, reference lists, and expert archives in English, Russian, and Spanish through August 5, 2017. The risk of bias for each extracted estimate and the overall quality of evidence were evaluated using a list of predefined safeguards against bias related to different study characteristics and the Grading of Recommendations Assessment, Development and Evaluation system, respectively. The inverse variance heterogeneity (IVhet) model was used for meta-analysis. The possibility of publication bias was evaluated by funnel and Doi plots, and asymmetry in these was tested with Egger's test and the Luis Furuya-Kanamori index, respectively. Sensitivity analyses included leave-one-out meta-analysis, subgroup meta-analysis with meta-regressions, and non-linear exposure-response meta-analysis. Based on seven cohort and two case-control studies (n = 5 514 555; 14 estimates; Lden range ≈ 25–90 dB(A)), we found “low” evidence of RR per 10 dB(A) = 1.018 (95% CI: 0.984, 1.053), moderate heterogeneity (I2 = 46%), and no publication bias. In the subgroup of cohort studies, we found “moderate” evidence of RR per 10 dB(A) = 1.018 (95% CI: 0.987, 1.049), I2 = 31%, and no publication bias. In conclusion, residential road traffic noise was associated with higher risk of hypertension in adults, but the risk was lower than previously reported in the systematic review literature.

Faced with the unavoidable reality of the emission of pollutant gases by vessels both while sailing and when performing in-port manoeuvres, the international community has devised an extensive set of rules to limit greenhouse gas emissions and the emission of other pollutants which are bad for our health. In order to make these reductions in the emissions, the areas addressed are the engine regime or speed control, the quality of the fuel used, the state of conservation of the vessel and its hull or the time taken to perform the manoeuvres of mooring and unmooring. One factor which is having a strong influence on this last aspect is the installation in commercial ports of Automatic Mooring Systems using suction cups (AMS). These devices, which help to reduce considerably the time required to perform the mooring and unmooring manoeuvres, allow the times taken in operations for making steady a vessel to land and of releasing it to sail away to be reduced from some tens of minutes to a few seconds. The aim of this work is to verify the effect of the AMS on the emission of pollutant gases in the surroundings of the installations devoted to Ro-Ro/Pax vessel traffic. In particular, will focus on the CO2 emissions produced by vessels during mooring operations using two different calculation methodologies (EPA and ENTEC), first when using traditional mooring methods as a means of securing the vessel to the dock and second when using only the AMS, to finally carry out a comparison of the results. Will conclude with a discussion on the values of the reduction in emissions obtained and the advantages of installing AMS in commercial ports. In the RoRo/Pax terminals in which the AMS is installed and operating, a reduction in CO2 emissions of 97% has been estimated.

The state of practice for noise assessment utilizes established standards for emission and propagation modelling of linear and point sources. Recently, land use regression (LUR) modelling has emerged as an alternative method due to relatively low data and computing resource demands. However, a limitation of LUR modelling is that is does not account for noise attenuation and reflections by features of the built environment. This study demonstrates and validates a method that combines the two modelling frameworks to exploit their respective strengths: Emission and propagation based prediction of traffic noise, the predominant source of noise at the level of streetscapes, and a LUR-based correction for noise sources that vary on spatial scales beyond the streetscape.Multi-criteria analysis, location-allocation modelling and stakeholder consultation identified 220 monitoring sites with optimal coverage for a 1-week sampling period. A subset of sites was used to validate a road traffic noise emission and propagation model and to specify a LUR model that predicted the contribution of other sources. The equivalent 24-h sound pressure level (LAeq) for all sites was 62.9 dBA (SD 6.4). This varied by time of day, weekday, types of roads and land uses. The traffic noise emission model demonstrated a high level of covariance with observed noise levels, with R² values of 0.58, 0.60 and 0.59 for daytime, nighttime and 24-h periods, respectively. Combined with LUR models to correct for other noise sources, the hybrid models R² values were 0.64, 0.71 and 0.67 for the respective time periods.The study showed that road traffic noise emissions account for most of the variability of total environmental noise in Toronto. The combined approach to predict fine resolution noise exposures with emission and receptor-based models presents an effective alternative to noise modelling approaches based on emission and propagation or LUR modelling.