The spatial relationship between traffic-related air pollution and noise in two Danish cities: Implications for health-related studies

Linking joint exposures to residential greenness and air pollution with adults' social health in dense Hong Kong

Despite the growing recognition of the impact of urban environments on social health, limited research explores the combined associations of multiple urban exposures, particularly in dense cities. This study examines the interplay between greenspace, air pollution, and social health as well as the underlying pathways and population heterogeneity in Hong Kong using cross-sectional survey data from 1977 adults and residential environmental data. Social health includes social contacts, relations, and support. Greenspace used street-view greenness (SVG), park density, and the normalized difference vegetation index (NDVI). 100-m daily ground NO2 and O3, indicative of air pollution, were derived using a spatiotemporal deep learning model. Mediators involved physical activity and negative emotions. Main analyses were performed in a 1000-m buffer with multivariate logistical regressions, stratification, interaction, and Partial Lease Square - Structural Equation Modelling (PLS-SEM). Multi-exposure models revealed positive associations between park density/SVG and social contacts, as well as between SVG and social relations, while O3 was negatively associated with social relations/support. Significant moderators included age, birthplace, employment, and education. PLS-SEM indicated direct positive associations between SVG and social contacts/relations and significant indirect negative associations between NO2/O3 and social health via negative emotions. This study adds to urban health research by exploring complex relationships between greenspace, air pollution, and social health, highlighting the role of the environment in fostering social restoration.

Long-term noise exposure and cause-specific mortality in chronic respiratory diseases, considering the modifying effect of air pollution

BACKGROUND

Chronic respiratory diseases (CRDs) are among the top three causes of human mortality. The relationship between modifiable environmental risk factor of noise and risk of mortality in CRDs is unclear. We investigated the longitudinal association between environmental noise exposure and cause-specific mortality in individuals with CRDs, considering the modifying effect of air pollution.

METHODS

Residential noise exposure was modelled using Common Noise Assessment Methods in Europe. Information on death causes were acquired from death registry data. Cox proportional-hazards models were used to estimate effect sizes.

RESULTS

Among 41,222 participants selected from UK Biobank with CRDs in baseline, a total of 3618 death cases occurred during an average follow-up of 12 years with mortality density of 7.16 per 1000 person years. Exposure with highest noise level (> percentile 90) were associated with 22 % (Hazard ratio [HR] = 1.22, 95 % confidence interval [CI]: 1.05, 1.42), 71 % (HR = 1.71, 95 % CI: 1.14, 2.56), and 84 % (HR = 1.84, 95 % CI: 1.10, 3.07) increased risks for all-cause, respiratory disease (RD)-cause, and COPD-cause mortalities, separately. Both multiplicative and additive interactions was found between air pollution and noise with the risk of RD-cause mortality. Participants with high air pollution and noise exposure were associated with a 101 % (HR = 2.01, 95 % CI: 1.10, 3.66) increased risk of RD-cause mortality.

CONCLUSION

It is imperative to mitigate noise exposure as a preventive measure against incident mortality in individuals with CRDs.

Exploring the Joint Association of Road Traffic Noise and Air Quality with Hypertension Using QGIS

There is growing evidence linking exposure to air pollution and traffic noise with hypertension. The aim of this study was to examine the associations of registered hypertension cases and hypertension rate with exposure to air pollution and road noise. In this cross-sectional study, we linked the information from the NHS Scotland database of 776,579 hypertension patients' registrations and rates per 13.80 people at the Scottish NHS Board, HSCP, Cluster, and GP practice levels. Based on the geospatial attributes, the data on residential areas were added by modelling annual average air pollutant concentrations, including particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), and road-traffic noise at different frequency components (Lden). The relationships between exposure to road noise, air pollution, and hypertension were examined using multiple regression and multivariate analysis. Traffic noise and air pollution at various frequency components positively and negatively predicted registered hypertension cases and hypertension rate. Based on the canonical loading technique, the variance explained by the canonical independent variable at a canonical correlation of 0.342 is 89%. There is a significant correlation between joint air pollution and noise at different frequency components and combined registered hypertension cases and hypertension rate. Exploring the combined effects of the two environmental exposures and the joint modelling of noise and air pollutants with hypertension in geospatial views provides an opportunity to integrate environmental and health data to support spatial assessment strategies in public and environmental health.

Exploring the Combined Association between Road Traffic Noise and Air Quality Using QGIS

There is mounting evidence that exposure to air pollution and noise from transportation are linked to the risk of hypertension. Most studies have only looked at relationships between single exposures. To examine links between combined exposure to road traffic, air pollution, and road noise. A Casella CEL-63x instrument was used to monitor traffic noise on a number of locations in residential streets in Glasgow, UK during peak traffic hours. The spatial numerical modelling capability of Quantum GIS (abbreviated QGIS) was used to analyse the combined association of noise and air pollution. Based on geospatial mapping, data on residential environmental exposure was added using annual average air pollutant concentrations from local air quality monitoring network, including particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), and road-traffic noise measurements at different component frequencies (Lden). The combined relationships between air pollution and traffic noise at different component frequencies were examined. Based on Moran I autocorrelation, geographically close values of a variable on a map typically have comparable values when there is a positive spatial autocorrelation. This means clustering on the map was influenced significantly by NO₂, PM₁₀ and PM_2.5, and Lden at the majority of monitoring locations. Studies that only consider one of these two related exposures may exaggerate the impact of the individual exposure while underestimating the combined impact of the two environmental exposures.

Exposure to a real traffic environment impairs brain cognition in aged mice

Traffic-related air pollution (TRAP) has been a common public health problem, which is associated with central nervous system dysfunction according to large-scale epidemiological studies. Current studies are mostly limited to artificial laboratory exposure environments and specific genetic mechanisms remain unclear. Therefore, we chose a real-world transportation environment to expose aged mice, transporting them from the laboratory to a 1-m-high dry platform inside the campus and tunnel, and the mice were exposed daily from 7 a.m. to 7 p.m. for 2, 4 and 12 weeks respectively. Compared with the control group (in campus), the memory function of mice in the experimental group (in tunnel) was significantly impaired in the Morris water maze test. TRAP exposure increased the number of activated microglia in the hippocampal DG, CA1, CA3 regions and dorsolateral prefrontal cortex (dPFC). And neuroinflammation and oxidative stress levels were up-regulated in both hippocampus and dPFC of aged mice. By screening the risk genes of Alzheimer's disease, we found the mRNA and protein levels of ABCA7 were down-regulated and those of PYK2 were up-regulated. The DNA methylation ratios increased in four CpG sites of abca7 promoter region and decreased in one CpG site of pyk2 promoter region, which were consistent with the altered expression of ABCA7 and PYK2. In conclusion, exposure to the real traffic environment impaired memory function and enhanced neuroinflammation and oxidative stress responses, which could be relevant to the altered expression and DNA methylation levels of ABCA7 and PYK2. Our work provides a new and promising understanding of the pathological mechanisms of cognitive impairment caused by traffic-related air pollution.

A comprehensive experimental study of the influence of temperature on urban road traffic noise under real-world conditions

The effect of road traffic noise in urban environments is an issue of social and scientific interest, due to its public health and economic impacts. Scientific literature showed a decrease in the level of tyre/road noise generated as temperature increases, but usually under standardised traffic conditions in non-urban environments. Based on a wide network for the hourly monitoring of road traffic flow, air temperature and noise levels across the city of Madrid (Spain), this work proposes and applies a new experimental methodology for studying the dependence of urban road traffic noise on temperature. This study was conducted under real-world traffic conditions involving a wide variability in urban configurations and in the type and state of preservation of vehicles, tires and pavements. From the analysis of data for a whole year, a time interval was identified (from Tuesday to Thursday and between 8 a.m. and 8 p.m.) in which the variability in road traffic flow for the whole city of Madrid was stable enough to allow for a linear regression study between temperature and noise levels from urban road traffic. The relationships found were highly significant (p ≤ 0.001) for data from all the noise monitoring stations, with values of higher than 20% and up to 42% for the explanation of the variability in the measured noise levels by temperature at most of the measurement points. The values of the slope coefficients at the noise monitoring stations ranged from -0.036 to -0.125 dB/°C, with an average value of -0.090 ± 0.011 dB/°C. These results are within the range of values reported in the scientific literature for experimental tests conducted under conditions of controlled or free-flowing traffic.

Toxicological effects of traffic-related air pollution on the lungs: Evidence, biomarkers and intervention

BACKGROUND

Numerous epidemiological studies have recently observed that exposure to traffic-related air pollution (TRAP) is associated with increased risk of various respiratory diseases. Major gaps in knowledge remain regarding the toxicological effects.

OBJECTIVES

We examined the toxicological effects of the gasoline exhaust particles (GEP), a paradigm of TRAP, in rats, with an objective to provide the evidence, obtain the biomarkers, and suggest effective intervention measure.

METHODS

We measured the airway hyperresponsiveness (AHR), inflammatory cells in the bronchoalveolar lavage (BAL) fluid, histological changes in the lung tissues, and the biomarkers so as to systematically examine the toxicological effects of GEPs at different dose levels (0.5, 2.5, 5 mg/kg BW). The intervention of vitamin E (VE), a natural antioxidant, on the toxicological effects was investigated.

RESULTS

The lung injury caused by GEP exposure was first indicated by the airway hyperresponsiveness (AHR). Compared with the control group, GEP exposure significantly increased the airway resistances and decreased the lung compliance; the higher the dose of GEP, the more serious the lung injury. Lung injury was also revealed by the increase of inflammatory cells, including the lymphocytes and neutrophils, in the BAL fluid. With the increase of GEP dose, histological changes in the lung tissues were further observed: inflammatory cell infiltration increased and alveolar wall thickened. The toxicology of GEP was demonstrated by the increase of the biomarkers of the oxidative stress, the pro-inflammatory cytokines and the apoptosis cytokine. However, administration of VE was found to be effective in restoring airway injury.

CONCLUSION

The toxicological effects of traffic-related air pollution (TRAP) on rat lungs are supported by evidence and biomarkers, and vitamin E intervention is feasible.

Noise and air pollution during Covid-19 lockdown easing around a school site

During the Covid-19 pandemic and resulting lockdowns, road traffic volumes reduced significantly leading to reduced pollutant concentrations and noise levels. Noise and the air pollution data during the lockdown period and loosening of restrictions through five phases in 2021 are examined for a school site in the United Kingdom. Hourly and daily average noise level as well as the average over each phase, correlations between noise and air pollutants, variations between pollutants, and underlying reasons explaining the temporal variations are explored. Some strong linear correlations were identified between a number of traffic-sourced air pollutants, especially between the differently sized particulates PM₁, PM_2.5, and PM₁₀ (0.70 < r <0.98) in all phases and an expected inverse correlation between nitrogen dioxide (NO₂) and ground-level ozone (O₃) (-0.68 < r < -0.78) as NO₂ is a precursor of O₃. Noise levels exhibit a weak correlation with the measured air pollutants and moderate correlation with meteorological factors, including wind direction, temperature, and relative humidity. There was a consistent and significant increase in noise levels (p < 0.01) of up to 3 dB with initial easing, and this was maintained through the remaining phases.

Characteristics analysis of near-field and far-field aerodynamic noise around high-speed railway bridge

The aerodynamic noise around the high-speed railway bridge is studied by the train-bridge-flow field numerical model and theory analysis. With the background of the Beijing-Shanghai high-speed railway line in China, based on the broadband noise sources method and acoustic analogy theory, both the intensity characteristics of near-field aerodynamic noise sources of the train and the spatial distribution characteristics of far-field aerodynamic noise around the bridge are analyzed. The results show that there is the largest sound source energy on the nose tip of the high-speed train; the fluctuating pressure between air and train surface contributes the most to aerodynamic noise; along the longitudinal direction of the bridge, the aerodynamic noise energy near the junction of train tail and body is the strongest; along the transverse direction of the bridge, the aerodynamic noise energy decreases gradually with the distance from the centerline of the railway; along the vertical direction, the aerodynamic noise energy is the strongest at a location of 1.2 m above the top surface of the rail; the train speed, train type, and the height variation of the bridge pier can affect the distribution of far-field aerodynamic noise.

Efficient Photocatalytic Degradation of Gaseous Benzene and Toluene over Novel Hybrid PIL@TiO2/m-GO Composites

In this work, the PIL (poly ionic liquid)@TiO2 composite was designed with two polymerized ionic liquid concentrations (low and high) and evaluated for pollutant degradation activity for benzene and toluene. The results showed that PIL (low)@TiO2 composite was more active than PIL (high)@TiO2 composites. The photodegradation rate of benzene and toluene pollutants by PIL (low)@TiO2 and PIL (high)@TiO2 composites was obtained as 86% and 74%, and 59% and 46%, respectively, under optimized conditions. The bandgap of TiO2 was markedly lowered (3.2 eV to 2.2 eV) due to the formation of PIL (low)@TiO2 composite. Besides, graphene oxide (GO) was used to grow the nano-photocatalysts’ specific surface area. The as-synthesized PIL (low)@TiO2@GO composite showed higher efficiency for benzene and toluene degradation which corresponds to 91% and 83%, respectively. The resultant novel hybrid photocatalyst (PIL@TiO2/m-GO) was prepared and appropriately characterized for their microstructural, morphology, and catalytic properties. Among the studied photocatalysts, the PIL (low)@TiO2@m-GO composite exhibits the highest activity in the degradation of benzene (97%) and toluene (97%). The ultimate bandgap of the composite reached 2.1 eV. Our results showed that the as-prepared composites hold an essential role for future considerations over organic pollutants.

Algorithm for Reducing Truck Noise on Via Baltica Transport Corridors in Lithuania

The section of Via Baltica going through the territory of the Republic of Lithuania is the most traffic intensive land logistics corridor in the country. The annual transportation volume has been increasing on this road; thus, the reduction of pollution caused by vehicles has become important. If gas emissions are regulated, and carriers have to pay pollution taxes, this does not apply to noise levels. The article presents the traffic intensity in this logistics corridor, measurements of the noise level at the characteristic points, its relation to the number of vehicles passing through it and an expert evaluation of proposed methods for noise energy reduction. Environmental noise is an unwanted or harmful sound that propagates in terms of both duration and geographical coverage. Noise is associated with many human activities, but road, rail and air traffic noises have the greatest impact. Due to irrationally arranged transport network, the transit flow of freight transport crosses residential areas of the city, places of rest and recreation of the population, causing high noise levels in adjacent areas. This is the biggest problem for the urban environment. Environmental noise affects many Europeans and is therefore considered by society to be one of the biggest environmental problems. This article presents an assessment of a new traffic noise algorithm. The presented expert survey on noise energy reduction allows choosing the most appropriate method for reducing noise energy in Via Baltica transport logistics corridor. Based on the expert survey, a hierarchical table for noise energy reduction was compiled. It will allow assessing the validity of individual noise energy reduction solutions. It has become relevant for improving infrastructure of other transport corridors and choosing the most appropriate solutions to reduce vehicle noise pollution. A further application of this model can be focused on economic evaluation, forecasting of expected benefits and so on.