Traffic-related Nitrogen Oxides Research Articles

Estimating NOx removal capacity of urban trees using stable isotope method: A case study of Beijing, China

It is widely recognized that green infrastructures in urban ecosystems provides important ecosystem services, including air purification. The potential absorption of nitrogen oxides (NOx) by urban trees has not been fully quantified, although it is important for air pollution mitigation and the well-being of urban residents. In this study, four common tree species (Sophora japonica L., Fraxinus chinensis Roxb., Populus tomentosa Carrière, Sabina chinensis (L.)) in Beijing, China, were studied. The dual stable isotopes (15N and 18O) and a Bayesian isotope mixing model were applied to estimate the sources contributions of potential nitrogen sources to the roadside trees based on leaf and soil sampling in urban regions. The following order of sources contributions was determined: soil > dry deposition > traffic-related NOx. The capacity of urban trees for NOx removal in the city was estimated using a remote sensing and GIS approach, and the removal capacity was found to range from 0.79 to 1.11 g m−2 a−1 across administrative regions, indicating that 1304 tons of NOx could be potentially removed by urban trees in 2019. Our finding qualified the potential NOx removal by urban trees in terms of atmospheric pollution mitigation, highlighting the role of green infrastructure in air purification, which should be taken into account by stakeholders to manage green infrastructure as the basis of a nature-based approach.

Childhood traffic-related air pollution and adverse changes in subclinical atherosclerosis measures from childhood to adulthood

BackgroundChronic exposure to air pollutants is associated with increased risk of cardiovascular disease (CVD) among adults. However, little is known about how air pollution may affect the development of subclinical atherosclerosis in younger populations. Carotid artery intima-media thickness (CIMT) is a measure of subclinical atherosclerosis that provides insight into early CVD pathogenesis.MethodsIn a pilot study of 70 participants from the Southern California Children’s Health Study, we investigated CIMT progression from childhood to adulthood. Using carotid artery ultrasound images obtained at age 10 and follow-up images at age 21–22, we examined associations between childhood ambient and traffic-related air pollutants with changes in CIMT over time and attained adult CIMT using linear mixed-effects models adjusted for potential confounders.Average residential childhood exposures (i.e., birth to time of measurement at 10–11 years) were assigned for regional, ambient pollutants (ozone, nitrogen dioxide, particulate matter, interpolated from regulatory air monitoring data) and traffic-related nitrogen oxides (NOx) by road class (modeled using the CALINE4 line source dispersion model). Traffic density was calculated within a 300-m residential buffer.ResultsFor each 1 standard deviation (SD) increase in childhood traffic-related total NOx exposure, we observed greater yearly rate of change in CIMT from childhood to adulthood (β: 2.17 μm/yr, 95% CI: 0.78–3.56). Increases in annual rate of CIMT change from childhood to adulthood also were observed with freeway NOx exposure (β: 2.24 μm/yr, 95% CI: 0.84–3.63) and traffic density (β: 2.11 μm/yr, 95% CI: 0.79–3.43). Traffic exposures were also related to increases in attained CIMT in early adulthood. No associations of CIMT change or attained level were observed with ambient pollutants.ConclusionsOverall, we observed adverse changes in CIMT over time in relation to childhood traffic-related NOx exposure and traffic density in our study population. While these results must be cautiously interpreted given the limited sample size, the observed associations of traffic measures with CIMT suggest a need for future studies to more fully explore this relationship.

Traffic-related Air Pollution and Incident Obesity during Ages 10-18 years in the Southern California Children’s Health Study

Childhood obesity is a global public health crisis, often continuing into adulthood and contributing to increased morbidity and mortality. A growing literature suggests traffic pollution may contribute to increased BMI in childhood, but few studies have examined whether this translates to an increased risk of obesity. In this study we evaluated how traffic-related air pollution relates to incident obesity in a prospective study of schoolchildren from ages 10 to 18 years.The study population comprised 3430 children from eight Southern California communities who were not obese at study entry, recruited over three waves in 1992-93, 1995-96, and 2002-03. Children were followed until age 18 or high school graduation, and height and weight measurements were collected longitudinally. Residential traffic pollution exposure at baseline was estimated as nitrogen oxides (NOx) using the California line-source dispersion model. Multilevel Poisson regression models were fitted to estimate incidence rate ratios (IRR) for obesity associated with traffic-related NOx exposure, adjusting for a set of confounding variables selected a priori using a directed acyclic graph.Participants were primarily non-Hispanic White (44%) or Hispanic (40%). At study entry the median age was 9.7 (IQR: 9.3-10.1) and most children were of normal weight (78%). Traffic-related NOx was associated with increased risk of childhood obesity: IRR=1.10 (1.01-1.19) per average standard deviation within community. Further adjustment for baseline body mass index category increased the risk: IRR=1.14 (1.05-1.24).Exposure to traffic was associated with higher obesity risk in childhood. These findings strengthen the scientific evidence linking childhood obesity and air pollution from near-roadway sources, a modifiable risk factor which could be targeted through vehicular emissions reductions and exposure policies.

Influence of TiO2-based photocatalytic coating road on traffic-related NOx pollutants in urban street canyon by CFD modeling

The use of titanium dioxide (TiO2) photocatalytic nanoparticles as road coating to trap and decompose air pollutants provides a promising technology to mitigate the harmful effects of vehicle emissions. However, there are few studies on computational fluid dynamics (CFD) simulations of the effect of NOx photocatalytic oxidation in street canyon with TiO2 nanoparticles as pavement coating. This study develop a CFD model with photocatalytic oxidation (PCO) reaction implemented for numerical simulation of NOx abatement in an urban street canyon with TiO2 coating, considering the effects of relative humidity (RH) (10–90%), and irradiance (10–40W ⋅ m−2). Results show that TiO2 coating road can effectively reduce nitrogen oxide (NOx) concentration in the street canyon. The average nitric oxide (NO) and nitrogen dioxide (NO2) concentrations in street canyon with TiO2 coating road were reduced by 3.70% and 4.31%, respectively, comparing with street canyon without TiO2 coating. The irradiance and relative humidity had great effect on PCO reaction in street canyon with TiO2 coating road. When the irradiance increased from 10W ⋅ m−2 to 40W ⋅ m−2, average NO conversion rose from 1.35% to 3.70%, and average NO2 conversion rose from 2.43% to 4.31%. The average conversion of NO and NO2 decreased from 5.11% to 2.54% and from 5.60% to 3.25%, respectively, when the relative humidity is varied from 10% to 90%. Results are useful to transport planners and road engineers who need to reduce NOx concentrations in urban streets travelled by fossil fuel-powered vehicles. Method of the study can be considered by future research faced with different pavement construction and traffic environment.

Air pollution, noise exposure, and metabolic syndrome – A cohort study in elderly Mexican-Americans in Sacramento area

BackgroundPrevious studies suggested that air pollutants may increase the incidence of metabolic syndrome, but the potential impact from traffic sources is not well-understood. This study aimed to investigate associations between traffic-related nitrogen oxides (NOx) or noise pollution and risk of incident metabolic syndrome and its components in an elderly Mexican-American population. MethodsA total of 1,554 Mexican-American participants of the Sacramento Area Latino Study on Aging (SALSA) cohort were followed from 1998 to 2007. We used anthropometric measures and biomarkers to define metabolic syndrome according to the recommendations of the Third Adult Treatment Panel of the National Cholesterol Education Program (NCEP ATP III). Based on participants’ residential addresses at baseline, estimates of local traffic-related NOx were generated using the California Line Source Dispersion Model version 4 (CALINE4), and of noise employing the SoundPLAN software package. We used Cox regression models with calendar time as the underlying time scale to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations of air pollution or noise with metabolic syndrome or its components. ResultsEach per unit increase of traffic-related NOx (2.29 parts per billion (ppb)) was associated with a 15% (HR = 1.15, 95% CI: 1.04–1.28) lower level of high-density lipoprotein cholesterol (HDL-cholesterol), and each 11.6 decibels (dB) increase in noise increased the risk of developing metabolic syndrome by 17% (HR = 1.17, 95% CI: 1.01–1.35). ConclusionPolicies aiming to reduce traffic-related air pollution and noise might mitigate the risk of metabolic syndrome and its components in vulnerable populations.

Influence of different complexity levels of road traffic models on air quality modelling at street scale

Urban mobility accounts for 38 and 19% of nitrogen oxide (NOx) and particulate matter (PM) emissions at European urban areas, respectively. Despite of all the technological development around automobile industry, urban areas are still facing problems related to exposure to high levels of air pollutants. Increasing the accuracy of both emissions and air quality modelling from road traffic is a key-issue for the management of air pollution in road transport sector. This study assessed the influence of using different road traffic emission models on the accuracy of air quality modelling with street-level resolution, having as a case study an urban area located on the centre region of Portugal. Two emission models, with different complexity levels regarding the ability to characterise the traffic dynamics were analysed, namely, transport emission model for line sources (TREM) and vehicle-specific power (VSP), based on data obtained in an experimental campaign. To perform the air quality simulations, the pollutant dispersion in the atmosphere under variable wind conditions (VADIS) model was used and two pollutants were analysed: NOx and PM10. The results showed that the magnitude of PM10 and NOx concentrations were result of a conjoint influence of traffic dynamics and meteorological conditions. Comparison between measured and modelled data showed that the VADIS model could track the evolution of NOx levels, for both emission models considered, displaying a high correlation (> 0.8) between traffic-related NOx emissions and NOx concentrations. For PM10, VADIS model is more sensitive to the differences in the emissions calculation; however, it was observed that the traffic-related PM10 emissions accounts 1.3–8.4% to the PM10 concentration levels at the study area.

Traffic-Related Air Pollution and the Local Chronic Burden of Childhood Asthma in Bradford, UK

Background It is important to move beyond traditional Health Impact Assessment (HIA) focused on mortality, by including morbidity outcomes that pose a significant burden on healthcare systems and quality of life. Childhood asthma, the most common chronic illness in children, is one such outcome with 1 in 11 children in the UK suffering from this condition. Air pollution, particularly traffic-related air pollution, is thought to contribute to the childhood asthma burden. We aimed to estimate the burden of childhood asthma (from birth-18 years old) attributable to traffic-related air pollution in Bradford, UK, by calculating the number of asthma cases attributable to traffic-related Nitrogen Oxides (NO x ), Nitrogen Dioxide (NO 2 ), Particulate Matter 2.5 and 10 and Black Carbon. We further explored whether differences in the exposure assessment methods translate into differences in the estimated health burden. Methods We estimated the childhood population exposure to traffic-related NOx and NO 2 at the super output area level in Bradford using two full-chain models linking transport, emissions and air quality models. These were namely 1) a dispersion model with standard vehicle emission factors; 2) a dispersion model with novel vehicle emission factor developed in previous work (Khreis, 2016). A Land-Use Regression (LUR) model developed in previous work as part of the ESCAPE consortium (Beelen et al., 2013) was also used to estimate exposure. We extracted the incidence rate for childhood asthma and the exposure-response functions from previous published surveys and meta-analyses (Punekar and Sheikh 2009; Khreis et al., 2017). We calculated the relative risk and population attributable fraction of childhood asthma due to estimated air pollutant levels. We estimated the number of asthma cases attributable to these exposure levels in each output area in Bradford and summed the results across all output areas. Results To our knowledge, this study represents one of the very few studies undertaking full-chain burden of disease assessment that considers the full-chain from exposure source (e.g. vehicle emissions), through pathways (e.g. air pollution levels and exposure assignment) to health outcomes (e.g. childhood asthma). It also adds to the scarce literature exploring uncertainties associated with methodological issues related to the exposure assessments. The attributable cases of asthma as estimated using LUR exposures were 433 due to NO2, 685 due to NOx, 485 due to PM2.5, 608 due to PM10 and 276 due to Black Carbon. The remainder of the analysis is ongoing.

Characterizing spatial variability of air pollution from vehicle traffic around the Houston Ship Channel area

Mobile emissions are a major source of urban air pollution and have been associated with a variety of adverse health outcomes. The Houston Ship Channel area is the home of a large number of diesel-powered vehicles emitting fine particulate matter (PM2.5; ≤2.5 μm in aerodynamic diameter) and nitrogen oxides (NOx). However, the spatial variability of traffic-related air pollutants in the Houston Ship Channel area has rarely been investigated. The objective of this study is to characterize spatial variability of PM2.5 and NOx concentrations attributable to on-road traffic in the Houston Ship Channel area in the year of 2011. We extracted the road network from the Texas Department of Transportation Road Inventory, and calculated emission rates using the Motor Vehicle Emission Simulator version 2014a (MOVES2014a). These parameters and preprocessed meteorological parameters were entered into a Research LINE-source Dispersion Model (RLINE) to conduct a simulation. Receptors were placed at 50 m resolution within 300 m to major roads and at 150 m resolution in the rest of the area. Our findings include that traffic-related PM2.5 were mainly emitted from trucks, while traffic-related NOx were emitted from both trucks and cars. The traffic contributed 0.90 μg/m3 PM2.5 and 29.23 μg/m3 NOx to the annual average mass concentrations of on-road air pollution, and the concentrations of the two pollutants decreased by nearly 40% within 500 m distance to major roads. The pollution level of traffic-related PM2.5 and NOx was higher in winter than those in the other three seasons. The Houston Ship Channel has earlier morning peak hours and relative late afternoon hours, which indicates the influence of goods movement from port activity. The varied near-road gradients illustrate that proximities to major roads are not an accurate surrogate of traffic-related air pollution.

Forecasting traffic-related nitrogen oxides within a street canyon by combining a genetic algorithm-back propagation artificial neural network and parametric models

A human-built urban street canyon is typically characterized by the presence of buildings on both sides of a road in which the air pollutants, especially those resulting from road traffic, may pose a potential threat to human health. Artificial Neural Network (ANN) differs from parametric model in that it is trained to learn a solution rather than being programmed to model a specific problem with a normal way. Therefore, they would be able to offer better practical skill to predict pollutant. Because pollutant distribution is often greatly influenced by the terrain and meteorological factors, establishing ANN has to consider effective parameters as the input neurons. In this study, traffic-related nitrogen oxides was predicted by combining a genetic algorithm-back propagation ANN and two parametric models (STREET model and OSPM model). This study took those independent parameters or components in the two parametric models into account as the input neurons. These input neurons are likely to enable ANN to reach desire simulation accuracy. Results indicated that ANN had better performance than the parametric models. Further study illustrated that the simulation had higher squared Pearson correlation coefficient (R2) up to 0.73 for validation, less simulation error, and better trend description in measured data than measured mean. Overall, this study allowed the use of ANN as a viable option for forecasting the traffic-related air pollutants within a street canyon.

High NO2/NOx emissions downstream of the catalytic diesel particulate filter: An influencing factor study

Diesel vehicles are responsible for most of the traffic-related nitrogen oxide (NOx) emissions, including nitric oxide (NO) and nitrogen dioxide (NO2). The use of after-treatment devices increases the risk of high NO2/NOx emissions from diesel engines. In order to investigate the factors influencing NO2/NOx emissions, an emission experiment was carried out on a high pressure common-rail, turbocharged diesel engine with a catalytic diesel particulate filter (CDPF). NO2 was measured by a non-dispersive ultraviolet analyzer with raw exhaust sampling. The experimental results show that the NO2/NOx ratios downstream of the CDPF range around 20%–83%, which are significantly higher than those upstream of the CDPF. The exhaust temperature is a decisive factor influencing the NO2/NOx emissions. The maximum NO2/NOx emission appears at the exhaust temperature of 350°C. The space velocity, engine-out PM/NOx ratio (mass based) and CO conversion ratio are secondary factors. At a constant exhaust temperature, the NO2/NOx emissions decreased with increasing space velocity and engine-out PM/NOx ratio. When the CO conversion ratios range from 80% to 90%, the NO2/NOx emissions remain at a high level.

Contribution of ozone to airborne aldehyde formation in Paris homes

Indoor aldehydes may result from ozone-initiated chemistry, mainly documented by experimental studies. As part of an environmental investigation included in the PARIS birth cohort, the aim of this study was to examine ozone contribution to airborne aldehyde formation in Paris homes. Formaldehyde, acetaldehyde and hexaldehyde levels, as well as styrene, nitrogen dioxide and nicotine concentrations, comfort parameters and carbon dioxide levels, were measured twice during the first year of life of the babies. Ambient ozone concentrations were collected from the closest background station of the regional air monitoring network. Traffic-related nitrogen oxide concentrations in front of the dwellings were estimated by an air pollution dispersion model. Home characteristics and families' way of life were described by questionnaires. Stepwise multiple linear regression models were used to link aldehyde levels with ambient ozone concentrations and a few aldehyde precursors involved in oxidation reactions, adjusting for other indoor aldehyde sources, comfort parameters and traffic-related nitrogen oxides. A 4 and 11% increase in formaldehyde and hexaldehyde levels was pointed out when 8-hour ozone concentrations increased by 20 μg/m 3. The influence of potential precursors such as indoor styrene level and frequent use of air fresheners, containing unsaturated volatile organic compounds as terpenes, was also found. Thus, our results suggest that ambient ozone can significantly impact indoor air quality, especially with regard to formaldehyde and hexaldehyde levels.

Prediction of traffic-related nitrogen oxides concentrations using Structural Time-Series models

Ambient air quality monitoring, modeling and compliance to the standards set by European Union (EU) directives and World Health Organization (WHO) guidelines are required to ensure the protection of human and environmental health. Congested urban areas are most susceptible to traffic-related air pollution which is the most problematic source of air pollution in Ireland. Long-term continuous real-time monitoring of ambient air quality at such urban centers is essential but often not realistic due to financial and operational constraints. Hence, the development of a resource-conservative ambient air quality monitoring technique is essential to ensure compliance with the threshold values set by the standards. As an intelligent and advanced statistical methodology, a Structural Time Series (STS) based approach has been introduced in this paper to develop a parsimonious and computationally simple air quality model. In STS methodology, the different components of a time-series dataset such as the trend, seasonal, cyclical and calendar variations can be modeled separately. To test the effectiveness of the proposed modeling strategy, average hourly concentrations of nitrogen dioxide and nitrogen oxides from a congested urban arterial in Dublin city center were modeled using STS methodology. The prediction error estimates from the developed air quality model indicate that the STS model can be a useful tool in predicting nitrogen dioxide and nitrogen oxides concentrations in urban areas and will be particularly useful in situations where the information on external variables such as meteorology or traffic volume is not available.

Traffic-related Air Pollution and Personal Exposure to Nitrogen Oxides in School Children in Beijing

O-31A6-1 Background/Aims: Several studies have shown association between traffic-related nitrogen oxides (NOx) pollution and adverse health effects in children. Most of these studies, however, used ambient or indoor NOx concentrations as surrogate of personal exposure. The studies on personal exposure to NOx in children are still limited. In this study, we evaluated personal exposure to NOx, nitrogen dioxide (NO2), and nitric oxide (NO) in children from 2 primary schools located in 2 areas in Beijing with different levels of traffic-related air pollution. Methods: A study of personal exposure to NOx, NO2, and NO was conducted in 30 children from a school near a main road with high traffic density (School 1) 4 times from 2007 to 2008, and in 40 children from a school (School 2) located far from the main road in 2008, respectively. Personal exposure to NOx, NO2, and NO were measured with passive samplers. Repeated Measures Test in General Linear model was used to analyze the differences of exposures among the 4 periods in children from School 1. And the differences between 2 schools were analyzed by Mann-Whitney U Rank test. Results: In children from School 1, the highest exposure to NO2 was observed in January 2008, whereas there was no significant difference among the other 3 periods. The lowest and highest exposures to NO and NOx were seen in October and April 2008, respectively. There was no significant difference between the other 2 periods. At the same period of investigation, personal exposure to NO2, NO, and NOx in children from School 1 were 99%, 145%, and 129% higher than those in children from School 2, respectively. Conclusion: Our results suggested that traffic-related air pollution significantly contributed to the personal exposure to NOx, NO2, and NO in school children in Beijing.

Biomonitoring of traffic-related nitrogen oxides in the Maurienne valley (Savoie, France), using purple moor grass growth parameters and leaf 15N/ 14N ratio

Effects of traffic-related nitrogenous emissions on purple moor grass ( Molinia caerulea (L.) Moench) transplants, used here as a new biomonitoring species, were assessed along 500 m long transects orthogonal to roads located in two open areas in the Maurienne valley (French Alps). Leaves were sampled during summer 2004 and 2005 for total N-content and 15N-abundance determination while nitrogen oxides (NO and NO 2) concentrations were determined using passive diffusion samplers. A significant and negative correlation was observed between plant total N-content, and 15N-abundance and the logarithm of the distance to the road axis. The strongest decreases in plant N parameters were observed between 15 and 100 m from road axis. They were equivalent to background levels at a distance of about 800 m from the roads. In addition, motor vehicle pollution significantly affected vegetation at road edge, as was established from the relationship between leaf 15N-abundance, total N-content and road traffic densities.

Climate, traffic-related air pollutants and allergic rhinitis prevalence in middle-school children in Taiwan.

The prevalence of allergic rhinitis, a common respiratory disorder, may be rapidly increasing. Epidemiological studies, however, indicate little about its association with climatic factors and air pollution. The relationship between traffic-related air pollutants and allergic rhinitis in middle-school students was therefore investigated. In a nationwide survey of middle-school students in Taiwan conducted in 1995/1996, the lifetime prevalence of physician-diagnosed allergic rhinitis and typical symptoms of allergic rhinitis were compared with air-monitoring station data on temperature, relative humidity, sulphur dioxide (SO2), nitrogen oxides (NOx), ozone (O3), carbon monoxide (CO) and particulate matter with a 50% cut-off aerodynamic diameter of 10 microm (PM10). A total of 331,686 nonsmoking children attended schools located within 2 km of 55 stations. Mean (range) annual exposures were: CO 853 (381-1,610) parts per billion (ppb), NOx 35.1 (10.2-72.4) ppb, SO2 7.57 (0.88-21.2) ppb, PM10 69.2 (40.1-116.2) microg x m(-3), O3 21.3 (12.4-34.1) ppb, temperature 22.9 (19.6-25.1) degrees C, and relative humidity 76.2 (64.8-86.2)%. The prevalence of physician-diagnosed allergic rhinitis was 28.6 and 19.5% in males and females, respectively, with prevalence of questionnaire-determined allergic rhinitis 42.4 and 34.0%. After adjustment for age, parental education and history of atopic eczema, physician-diagnosed allergic rhinitis was found to be associated with higher nonsummer (September-May) warmth and traffic-related air pollutants, including CO, NOx and O3. Questionnaire-determined allergic rhinitis correlated only with traffic-related air pollutants. Nonsummer warmth and traffic-related air pollution, probably mediated through exposure to common allergens such as dust mites, are possible risk factors for allergic rhinitis in middle-school-aged children.