Traffic-related Pollution Research Articles

Phytoremediation as an urban paradigm in promoting the health-potential of small green areas.

This paper aims to present a methodical design of a small-scale urban green area with increased phytoremediation potential. The applied compilation-based method with a view to intensifying the regenerative potential of the shaped green area, determining both the quantitative potential of improving air quality and simultaneously identifying qualitative aesthetic features, comes out of recognition of the psychophysical nature of air pollution impacts on human health.A multifaceted evaluation of the designed solutions carried out using the Micrometeorological Computational Fluid Dynamics model (ENVI-met software) allows us to explore various properties of the plant layout and its influence on the PM2.5 concentration. The result of the CFD simulation indicated that the proper sequence in the plant layout may reduce the level of pollution concentration behind the green barrier by about 7-8%, on average. Simultaneously, we demonstrate that the assembly of plants, organised according to phytoremediation requirements, acts as passive protection from traffic-related pollution, and may offer high visual value ensuring the environment of positive cognitive stimuli. The correlation of these aspects maximises the benefits of nature-human relation, extending the scope of the 'restorative' as a concept and revealing the multifaceted potential of phytoremediation as a comprehensive method of urban green area design.

Deep learning-based multi-target regression for traffic-related air pollution forecasting

Traffic-related air pollution (TRAP) remains one of the main contributors to urban pollution and its impact on climate change cannot be overemphasised. Experts in developed countries strive to make optimal use of traffic and air quality data to gain valuable insights into its effect on public health. Over the years, the research community has developed advanced methods of forecasting traffic-related pollution using several machine learning methods albeit with persistent accuracy and insufficient data challenges. Despite the potentials of emerging techniques such as multi-target deep neural network to achieve optimal solutions, they are yet to be fully exploited in the air quality space due to their complexity and unavailability of the right training data. It is to this end that this study investigates the impact of integrating an updated data set including road elevation, vehicle emissions factor and background maps with traffic flow, weather and pollution data on TRAP forecasting. To explore the robustness and adaptability of our methodology, the study was carried out in one major city (London), one smaller city (Newport) and one large town (Chepstow) in the United Kingdom. The forecasting task was modelled as a multi-target regression problem and experiments were carried out to predict NO2,PM2.5 and PM10 concentrations over multiple timesteps. Fastai’s tabular model was used alongside prophet’s time-series model and scikit-learn’s multioutputregressor for experimentation with fastai recording the overall best performance. Statistical tests run using Friedman and Wilcoxon test also revealed the significance of the fastai model with a p-values < 0.05. Finally, a model explanation tool was then used to reveal the most and least influential features from the newly curated data set. Results showed traffic count and speed were part of the most contributing features. This result demonstrates the impact of these and other introduced features on TRAP forecasting and will serve as a foundation for related studies.

Estimating vehicular emission factors and vehicle-induced turbulence: Application of an air quality sensor array for continuous multipoint monitoring in a tunnel

In this study, air quality monitoring nodes (equipped with pollutants (NO, NO2, CO, and PM2.5), temperature, and humidity sensors) were deployed at seven locations inside a road tunnel for continuous multipoint monitoring of traffic emissions. At the same time, in-tunnel turbulence was measured with a 3D-sonic anemometer in the middle of the tunnel to estimate vehicle-induced turbulence (VIT). The emission factors (EFs) of all pollutants estimated from conventional two-point measurements varied significantly among arbitrarily chosen pairs of measurement locations (with a range of 53–193% compared to the mean value). These findings suggest the need for multipoint monitoring for more generalizable EF estimates. Our results indicate that installing a sensor array in a tunnel could enable long-term continuous multipoint monitoring of traffic-related pollutants with limited resources. The EF estimates obtained in this study were higher (∼7 times) than those calculated from an emission inventory based on actual traffic data, particularly for CO and wintertime NOX. One possible explanation for this inconsistency is an underestimation of high emitters in the emission inventory. We also estimated VIT as a function of the total traffic flow rate and the fraction of heavy-duty diesel vehicles in a fleet. We expect our results to be used as input data for local and regional air quality models, which can improve the model's performance. We also expect that long-term continuous monitoring of air pollutants in tunnels with multiple sensor nodes will aid evaluations of the effectiveness of air pollution reduction policies by tracking changes in traffic emissions.

Physicochemical Assessment of the Road Vehicle Traffic Pollution Impact on the Urban Environment

Vehicle traffic pollution requires complex physicochemical analysis besides emission level measuring. The current study is focused on two campaigns of emissions measurements held in May and September 2019 in Alba Iulia City, Romania. There was found a significant excess of PM2.5 for all measuring points and PM10 for the most circulated points during May, along with significant VOC and CO2 emissions. September measurements reveal threshold excess for all PM along with increased values for VOC and CO2 emissions. These are the consequences of the complex environmental interaction of the traffic. Street dust and air-suspended particle samples were collected and analyzed to evidence the PM2.5 and PM10 sources. Physicochemical investigation reveals highly mineralized particulate matter: PM2.5 fractions within air-suspended particle samples predominantly contain Muscovite, Kaolinite, and traces of Quartz and Calcite, while PM10 fractions within air-suspended particle samples predominantly contain Quartz and Calcite. These mineral fractions originate in street dust and are suspended in the atmosphere due to the vehicles’ circulation. A significant amount of soot was found as small micro-sized clusters in PM2.5 and fine micro-spots attached over PM10 particles, as observed by Mineralogical Optical Microscopy (MOM) and Fourier Transformed Infrared Spectroscopy (FTIR). GC-MS analysis found over 53 volatile compounds on the investigated floating particles that are related to the combustion gases, such as saturated alkanes, cycloalkanes, esters, and aromatic hydrocarbons. It proves a VOC contamination of the measured particulate matters that make them more hazardous for the health. Viable strategies for vehicle traffic-related pollutants mitigation would be reducing the street dust occurrence and usage of modern catalyst filters of the combustion gas exhausting system.

Nature-based solution for urban traffic heat mitigation facing carbon neutrality: sustainable design of roadside green belts

Urban heat islands (UHI) and heat waves related to climate change can increase urban carbon emissions and endanger human health. Transportation accounts for a large part of UHI and greenhouse gas emissions, which can effectively be mitigated by nature-based solutions (NBS). Roadside green belt is an important element of urban NBS targeting to blck traffic-related pollutants; however, less attention was paid to its impact on mitigating traffic heat emissions. Therefore, the design of roadside green belts was quantitatively investigated considering traffic heat in this work. A new method to rapidly model moving traffic source was proposed, namely urban traffic coupling source (UTCS) method, to deal with the dynamic and complex diffusion of traffic-generated heat. The impact of roadside green belts' locations and types on the thermal environment of cities' motorized and non-motorized area was investigated. The design parameters (tree spacing and shrub length) were evaluated for the optimum co-benefits between cooling efficiency and nurture management costs. Results showed that placing trees and shrubs near non-motorized lanes and sidewalks provided a favorable cooling effect, with the non-motorized areas' temperature decreased by up to 1.05 °C. When the range of tree spacing and shrub length were 0–0.375 W and 0.17–0.63 L (W and L are the width and length of the road, respectively), a maximum co-benefit improvement of 45.7% could be achieved. Moreover, this work provides a guideline for sustainable design of roadside green belts to improve the urban climate and achieve carbon neutrality target.

Acute Effects of Ambient Air Pollution on Asthma Emergency Department Visits in Ten U.S. States.

Previous studies of short-term ambient air pollution exposure and asthma morbidity in the United States have been limited to a small number of cities and/or pollutants and with limited consideration of effects across ages. To estimate acute age group-specific effects of fine and coarse particulate matter (PM), major PM components, and gaseous pollutants on emergency department (ED) visits for asthma during 2005-2014 across the United States. We acquired ED visit and air quality data in regions surrounding 53 speciation sites in 10 states. We used quasi-Poisson log-linear time-series models with unconstrained distributed exposure lags to estimate site-specific acute effects of air pollution on asthma ED visits overall and by age group (1-4, 5-17, 18-49, 50-64, and y), controlling for meteorology, time trends, and influenza activity. We then used a Bayesian hierarchical model to estimate pooled associations from site-specific associations. Our analysis included asthma ED visits. We observed positive associations for multiday cumulative exposure to all air pollutants examined [e.g., 8-d exposure to : rate ratio of 1.016 with 95% credible interval (CI) of (1.008, 1.025) per increase, : 1.014 (95% CI: 1.007, 1.020) per increase, organic carbon: 1.016 (95% CI: 1.009, 1.024) per increase, and ozone: 1.008 (95% CI: 0.995, 1.022) per increase]. and ozone showed stronger effects at shorter lags, whereas associations of traffic-related pollutants (e.g., elemental carbon and oxides of nitrogen) were generally stronger at longer lags. Most pollutants had more pronounced effects on children ( y old) than adults; had strong effects on both children and the elderly ( y old); and ozone had stronger effects on adults than children. We reported positive associations between short-term air pollution exposure and increased rates of asthma ED visits. We found that air pollution exposure posed a higher risk for children and older populations. https://doi.org/10.1289/EHP11661.

Association between exposure to multiple air pollutants, transportation noise and cause-specific mortality in adults in Switzerland

BackgroundLong-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for a range of air pollutants and transportation noise.MethodsOver 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM2.5, PM2.5 components (Cu, Fe, S and Zn), NO2, black carbon (BC) and ozone (O3) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges.ResultsDuring follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m3 PM2.5, 1.050 (1.041, 1.059) per 10 µg/m3 NO2, 1.057 (1.048, 1.067) per 0.5 × 10–5/m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO2, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM2.5 was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m3 for PM2.5 and NO2, < 1.5 10–5/m BC and < 53 dB Lden total transportation noise. The O3 association was inverse for all outcomes. Including noise attenuated all outcome associations, though many remained significant. Across outcomes, noise was robust to adjustment to air pollutants (e.g. natural mortality 1.037 (1.033, 1.042) per 10 dB Lden total transportation noise, after including BC).ConclusionLong-term exposure to air pollution and transportation noise in Switzerland contribute to premature mortality. Considering co-exposures revealed the importance of local traffic-related pollutants such as NO2, BC and transportation noise.

Ethnic disparities in ambient air and traffic-related pollution exposure and ethnic-specific impacts on clinical biomarker levels

BackgroundAlthough characterizing the inequality in pollution exposure burden across ethnic groups and the ethnic-specific exposure associations is of great social and public health importance, it has not been systematically investigated in large population studies. MethodsThe UK Biobank data (N = 485, 806) of individual-level air ambient and traffic-related pollution exposure, biomarkers routinely used in clinical practice, genotype, life-style factors, and socioeconomic status were analyzed. Air pollution exposure estimates were compared among six genetically inferred ethnic groups. We also quantified the association between exposure and biomarkers within and across ethnicities. ResultsNon-European participants (defined by genetics) disproportionately bear a higher burden of exposure than their European counterparts even after adjusting for covariables including socioeconomic status. For example, exposure to NO2 in people with African ancestry was 30.7 % higher (p = 1.5E-786) than European subjects. Within the genetically defined African group, larger African genetic ancestry proportion (AGAP) was linked to higher ambient air pollutant exposure. Trans-Ethnic analysis identified 32 clinical biomarkers associated with environmental exposure. For 13 biomarkers, the association with exposure was significantly different or even in opposing directions across ethnic groups. ConclusionsSubstantial disparities in air pollution exposure was observed among genetically-defined ethnic groups. Most importantly, we show that the impact of exposure on biomarkers varies by ethnicity. Reducing the disproportionally high exposure burden on non-European populations and alleviating the adverse consequences in an ethnic-specific manner are of great urgency and significance.

Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data

Abstract. This paper presents a bottom-up methodology to estimate multi-pollutant hourly gridded on-road traffic emission using advanced traffic flow and speed data for Delhi. We have used the globally adopted COPERT (Computer Programme to Calculate Emissions from Road Transport) emission functions to calculate the emission as a function of speed for 127 vehicle categories. At first, the traffic volume and congestion (travel time delay) relation is applied to model the 24 h traffic speed and flow for all the major road links of Delhi. The modelled traffic flow and speed shows an anti-correlation behaviour having peak traffic and emissions in morning–evening rush hours. We estimated an annual emission of 1.82 Gg for PM (particulate matter), 0.94 Gg for BC (black carbon), 0.75 Gg for OM (organic matter), 221 Gg for CO (carbon monoxide), 56 Gg for NOx (oxides of nitrogen), 64 Gg for VOC (volatile organic compound), 0.28 Gg for NH3 (ammonia), 0.26 Gg for N2O (nitrous oxide) and 11.38 Gg for CH4 (methane) for 2018 with an uncertainty of 60 %–68 %. The hourly emission variation shows bimodal peaks corresponding to morning and evening rush hours and congestion. The minimum emission rates are estimated in the early morning hours whereas the maximum emissions occurred during the evening hours. Inner Delhi is found to have higher emission flux because of higher road density and relatively lower average speed. Petrol vehicles dominate emission share (&gt;50 %) across all pollutants except PM, BC and NOx, and within them the 2W (two-wheeler motorcycles) are the major contributors. Diesel-fuelled vehicles contribute most of the PM emission. Diesel and CNG (compressed natural gas) vehicles have a substantial contribution in NOx emission. This study provides very detailed spatiotemporal emission maps for megacity Delhi, which can be used in air quality models for developing suitable strategies to reduce the traffic-related pollution. Moreover, the developed methodology is a step forward in developing real-time emission with the growing availability of real-time traffic data. The complete dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.6553770 (Singh et al., 2022).

Do objective and subjective traffic-related pollution, physical activity and nature exposure affect mental wellbeing? Evidence from Shenzhen, China

Urban environment (e.g. greenspaces, air pollution and traffic noise) and individuals' behaviours (e.g. physical activity) have all been associated with mental wellbeing. The large majority of studies on the influence of nature exposure on mental wellbeing assumed that multiple pathways act independently, ignoring the interactions among potential correlated pathways that engage simultaneously. The parallel mediation approach fails to explore the complex associations of combined exposure to air pollution, traffic noise and nature exposure with physical activity, which in turn affect mental wellbeing. Hence, the interest of understanding the sophisticated interactions among different pathways is warranted. We utilized structural equation modelling to simultaneously evaluate whether actual and perceived traffic-related pollution and physical activity mediate the associations between mental wellbeing and nature exposure, which was assessed by Normalized Difference Vegetation Index (NDVI), green view index (GVI), green space density and park accessibility. In summer 2022, we conducted questionnaires from 1772 adults residing in 117 neighbourhoods in Shenzhen, China. Nature exposure was positively and directly associated with mental wellbeing in the single mediator model that considered physical activity only. The indirect effects of nature exposure on mental wellbeing were observed through all pathways in all models, except through the perceived acoustic quality pathway in the serial mediation model. In addition, the percentage mediated by perceived air quality was higher than that of perceived acoustic quality. The influence of nature exposure on mental wellbeing was only for a small proportion mediated by the physical activity pathway. The associations between nature exposure and mental wellbeing were modified by individual characteristics, such as gender, age, income level and alcohol usage, but not employment status and smoking behaviour. These findings point out the importance of both objective and subjective environmental features and human behaviours on mental wellbeing, as well as the necessity of considering multiple pathways simultaneously.

Using hybrid methodologies to characterize temporal behavior and source of ambient ammonia

For the areas with much less agricultural activities, it is hotly debatable whether the atmospheric ammonia (NH3) mainly comes from agricultural or non-agriculture sources. This paper chooses the city of Taichung, the second most populated city in Taiwan, to resolve this debate by analyzing the data of NH3, PM2.5-bound water-soluble ions, SO2 and NOx monitored from 2016 to 2018 through online measurement instruments. We conclude that a significant amount of NH3 came from agricultural sources in light of (1) the strong correlations between NH3 concentrations and temperature, (2) the weak correlations between NH3 concentrations and the traffic related pollutants (NOx) and industrial pollutants (SO2)), (3) the high conversion ratio of ammonium (NHR), and (4) high background source contribution to NH3 in multiple linear regression models. As to other sources of NH3, while less impactful than the agriculture sources, the coal combustion, iron ore and steel industry, and oil combustion are three majors local NH3 emissions to form PM2.5. The results of this study can help control and regulate PM2.5 in NH3-rich regions such as Taichung.

Traffic-Related Air Pollution and Ground-Level Ozone Associated Global DNA Hypomethylation and Bulky DNA Adduct Formation.

Studies have indicated that air pollution, including surface-level ozone (O3), can significantly influence the risk of chronic diseases. To better understand the carcinogenic mechanisms of air pollutants and identify predictive disease biomarkers, we examined the association between traffic-related pollutants with DNA methylation alterations and bulky DNA adducts, two biomarkers of carcinogen exposure and cancer risk, in the peripheral blood of 140 volunteers-95 traffic police officers, and 45 unexposed subjects. The DNA methylation and adduct measurements were performed by bisulfite-PCR and pyrosequencing and 32P-postlabeling assay. Airborne levels of benzo(a)pyrene [B(a)P], carbon monoxide, and tropospheric O3 were determined by personal exposure biomonitoring or by fixed monitoring stations. Overall, air pollution exposure was associated with a significant reduction (1.41 units) in global DNA methylation (95% C.I. -2.65-0.04, p = 0.026). The decrement in ALU repetitive elements was greatest in the policemen working downtown (95% C.I. -3.23--0.49, p = 0.008). The DNA adducts were found to be significantly increased (0.45 units) in the municipal officers with respect to unexposed subjects (95% C.I. 0.02-0.88, p = 0.039), mainly in those who were controlling traffic in downtown areas (95% C.I. 0.39-1.29, p < 0.001). Regression models indicated an increment of ALU methylation at higher B(a)P concentrations (95% C.I. 0.03-0.60, p = 0.032). Moreover, statistical models showed a decrement in ALU methylation and an increment of DNA damage only above the cut-off value of 30 µg/m3 O3. A significant increment of 0.73 units of IL-6 gene methylation was also found in smokers with respect to non-smokers. Our results highlighted the role of air pollution on epigenetic alterations and genotoxic effects, especially above the target value of 30 µg/m3 surface-level O3, supporting the necessity for developing public health strategies aimed to reduce traffic-related air pollution molecular alterations.

Association of walkability and NO2 with metabolic syndrome: A cohort study in China

BackgroundEpidemiological studies have reported an association between traffic-related pollution with risk of metabolic syndrome (MetS). However, evidence from prospective studies on the association of walkability and nitrogen dioxide (NO2) with MetS is still scarce. We, therefore, aimed to evaluate the association of long-term exposure to NO2 and walkability with hazards of incident MetS. MethodsA total of 17,965 participants without MetS diagnosed within one year at baseline were included in our study from a population-based prospective cohort in Yinzhou District, Ningbo, Zhejiang Province, China. Participants were followed up by the regional Health Information System (HIS) until December 15, 2021. MetS was defined based on the criteria of Chinese Diabetes Society (CDS2004). We used walkscore tools, calculating with amenity categories and decay functions, and spatial–temporal land-use regression (LUR) models to estimate walkability and NO2 concentrations. We used Cox proportional hazards regression models to examine the association of walkability and NO2 with hazards of MetS incidence reporting with hazard ratios (HRs) and 95% confidence intervals (CIs). ResultsOverall, we followed up 77,303 person-years and identified 4040 incident cases of MetS in the entire cohort. Higher walkability was inversely associated with incident MetS (HR = 0.94, 95 % CI: 0.91–0.99), whereas NO2 was positively associated with MetS incidence (HR = 1.07, 95 %CI: 1.00–1.15) per interquartile range increment in two-exposure models. Furthermore, we found a significant multiplicative interaction between walkability and NO2. Stronger associations were observed for NO2 and incident MetS among men, smokers, drinkers and participants who aged < 60 years and had higher levels of income. ConclusionIn summary, we found living in areas with lower walkability and higher concentrations of NO2 were associated with increased incidence of MetS. The beneficial effect of higher walkability may be attenuated by exposure to NO2.

Cardiac Autonomic Impacts of Bushfire Smoke - A Prospective Panel Study.

Air pollution is associated with cardiovascular disease and mortality. Most studies have focussed on urban or traffic-related pollution, and less is known about the impacts from bushfire smoke on cardiovascular autonomic function, although it is associated with increased sudden cardiac death and mortality. We sought to investigate its instantaneous and short-term impacts on heart rate variability (HRV). Twenty-four (24)-hour Holter electrocardiography (ECG) was repeated twice (during bushfire [Phase 1] and then clean air [Phase 2]) in 32 participants from two Australian towns (Warburton and Traralgon, Victoria) surrounding planned burning areas. This was compared with 10 control participants in another town (Maffra, Victoria) with two clean air assessments during the same periods. The primary HRV parameters assessed were those assessing overall HRV (Standard Deviation of Normal-to-Normal intervals [SDNN]), long-term HRV (Standard Deviation of the Average of Normal Sinus-to-Normal Sinus intervals for each 5-minutes [SDANN]), low frequency [LF]) and short-term HRV (Root Mean Square of Successive Differences between N-N intervals [RMSSD], High Frequency [HF], LF:HF ratio). Average concentrations of particulate matter <2.5 μm in diameter (PM2.5) were measured at fixed site monitors in each location. Mean PM2.5 levels were significantly elevated during bushfire exposure in Warburton (96.5±57.7 μg/m3 vs 4.0±1.9 μg/m3, p<0.001) and Traralgon (12.6±4.9 μg/m3 vs 3.4±3.1 μg/m3, p<0.001), while it remained low in the control town, Maffra, in each phase (4.3±3.2 μg/m3 and 3.9±3.6 μg/m3, p=0.70). Although SDANN remained stable in controls, the exposed cohort showed significant worsening in SDANN during bushfire smoke exposure by 9.6±25.7ms (p=0.039). In univariable analysis, smoke exposure was significantly associated with higher ΔSDNN and ΔSDANN (p=0.03, p=0.01 exposed vs control). The association remained significant in ΔSDANN after adjusting for age, sex and cigarette smoking (p=0.02) and of borderline significance in ΔSDNN (p=0.06). Exposure to the bushfire smoke was independently associated with reduced overall and long-term HRV. Our findings suggest that imbalance in cardiac autonomic function is a key mechanism of adverse cardiovascular effects of bushfire smoke.

A Statistical Analysis of Traffic-Related Pollution and City Center Dynamics in Ankara: The Cases of Ulus and Kızılay

A Statistical Analysis of Traffic-Related Pollution and City Center Dynamics in Ankara: The Cases of Ulus and Kızılay

Design and Development of Terrain Globetrotter Bot

Autonomous vehicles (AV) increase safety while consuming less energy, fuel, and reducing traffic-related pollution. We'll create a Terrain Globetrotter Bot from scratch. An RP Lidar is interfaced with an RP Lidar in the front top portion of a Terrain Globetrotter bot, which has a straightforward construction and uses the ROS (Robotic Operating System) software library of version ROS Kinetic / Melodic. This low-cost mapping bot has capabilities like SLAM (Simultaneous Localization and Mapping), which can not only create a map of the environment using Lidar scans and Matlab's Robotic Operating System Software package to communicate with ROS in the Raspberry Pi via ROS Network Configurations, but also other features like asking the user to select the destination, path planning to safely reach the destination, and then gathering the necessary small resources. The objective of the project is to build a completely autonomous robot that can map its environment and avoid impediments. A chassis with tracks, two motors, a lidar, a compass, and a Raspberry Pi can be used to achieve this. The work given here is a mini-project that is taken up as a part of the curriculum completed by electronics and communication engineering students in the second year of the electronics &amp; communication engineering department at Dayananda Sagar College of Engineering in Bangalore.

Serum Lead Level and Academic Performance of Elementary School Children in Makassar City

Lead exposure to children results in a negative effect on behaviour and cognitive performance. Air lead concentration might be influenced by traffic density on the road. Schools are the locations affected by traffic-related pollution. This study aims to explore the correlation between Serum Lead Levels (SLL) and academic achievement of elementary school students, comparing the distance of the school from the road. This cross-sectional study included 54 5th and 6th-grade students from two schools that differed in the distance from the main road. We observed the students' SLL with laboratory analysis and academic performance from the final score of five subjects. The mean difference of SLL and academic achievement between the two schools were performed using the Mann-Whitney U test, and the correlation between lead concentration and academic performance using the Spearman-Rho test. This study observed that all students were exposed to lead with the SLL range of 0.39-5.97 µg/dL in the school which is located road side, and 0.42-6.44 µg/dL in the school far from main road. The insignificant difference in the students' SLL (p=0.43) between the two schools but significant in students-level of academic performance (p=0.03) were discovered. Serum lead level correlated negatively with academic performance. (r=-0.234, p=0.044). It is suggested to give more attention to preventing lead exposure in children through the implementation of some prevention programmes and policies.

Are floating treatment wetlands more suitable for retrofitting highway runoff basins than vertical-flow treatment wetlands?

Highway runoffs introduce numerous traffic-related pollutants – such as heavy metals, suspended solids and different kinds of hydrocarbons – into surface waters, thus endangering environmental health. In Germany, sedimentation basins with oil retention baffles are mandatory for the treatment of highway runoff in water protection areas. If the distance to the groundwater table is too low, further treatment with event-loaded vertical-flow treatment wetlands (VFWs) is required. In this study, we evaluated if retrofitting of stormwater retention basins to floating treatment wetlands (FTWs) can serve as an alternative to post-treatment VFWs and if native plant species could adapt to the oxygen-deprived salt-enriched environment. Two such basins with two hydraulically separated parallel chambers each near the municipality of Cologne were equipped with floating mats on one chamber, while the other one served as control. One location additionally had hydraulically separated post-treatment VFWs, allowing for a comparison with the treatment efficiency of the FTW. The removal of chloride, sulfate, suspended solids (total and < 63 μm), nutrients, metals, petroleum derived hydrocarbons and polycyclic aromatic hydrocarbons (PDH and PAH) was examined in 54 events over a period of two years. As a result, it was found that plants can create an intense root network despite hostile conditions in the basins. For the target parameters (TSS63, PAH and PDH), the removal efficiency of the stormwater retention basin was already sufficient. For metals and ammonium nitrogen, the VFWs proved to be more efficient, whereas for nitrate nitrogen, this was the case for FTWs. None of the treatment systems proved effective against reducing chloride concentration from deicing salts.

Excess deaths associated with long-term exposure to ambient NO2 in China

World Health Organization updated the target of annual mean NO2 from 40 μg m−3 to 10 μg m−3 in 2021 based on new evidences that showed statistically independent effects of long-term exposure to ambient NO2 and mortality. We estimate the excess deaths associated with long-term exposure to ambient NO2 (DAAN) from non-accidental disease (NAD), cardiovascular disease (CVD) and respiratory disease (RD) in China in 2013–2020 using a counterfactual analytic framework adopted by Global Burden Disease. We use relative risk (RR) values based on a meta-analysis, and assume a linear concentration-response (C-R) function and a threshold value of 10 μg m−3. DAAN from NAD vary in 279 (95% Cl: 189–366) to 339 (95% Cl: 231–442) thousand in 2013–2020, comparable to excess deaths attributed to long-term exposure to ambient O3 in China. DAAN from NAD changes by −43%–+220% using different RR values, C-R function shapes, and threshold values. DAAN from RD reduces while those from CVD increases significantly in 2013–2020. DAAN from RD account for ∼10% of total DAAN. We found that the reduction of NO2 concentration and baseline mortality of NAD offsets the adverse effects of population growth and aging in 2013–2017. In 2017–2020, the contribution from air pollution reduction surpasses the adverse effects of population growth and aging in most regions. We suggest that continuing the reduction rate of NO2 emissions in 2013–2020 would offset the effects of population growth and aging in 2020–2030. Faster reduction of NO2 sources is required to reduce DAAN in Liaoning, Shanxi, Shanghai, and Anhui, where DAAN from NAD, CVD and RD increased in 2013–2020. Our results should be interpreted with caution because the causality support of long-term exposure to ambient NO2 on mortality from toxicological studies is not firm yet, and NO2 is possibly just a marker of traffic-related pollutants.

Traffic-related PM2.5 and its specific constituents on circulatory mortality: A nationwide modelling study in China

BackgroundShort-term fine particulate matter (PM2.5) exposure and increased circulatory mortality have been well documented. However, there are inconsistent findings on mortality effects of traffic-related pollutants from the perspective of sources or constituents. Few studies have examined such associations using source and constituents simultaneously, and even less are based on large-scale, nationally representative data. We aimed to conduct a comprehensive analysis to investigate source- and constituent-specific mortality effects due to traffic-related PM2.5 pollution in China. MethodsWe extracted daily mortality data in 280 counties from the China Disease Surveillance Points system (DSPs) from January 2013 to December 2018. Daily concentrations of traffic-related PM2.5 and specific constituents were simulated using the Community Multiscale Air Quality (CMAQ) model. The downscaling and adjustment methods were carried out to generate a refined exposure assessment. We estimated the circulatory mortality risk using a standard two-stage approach, combining generalized linear model (GLM) with a quasi-Poisson distribution and random-effects meta-analysis. ResultsWe observed that traffic-related PM2.5 and specific constituents were significantly associated with increased circulatory mortality. An increase of interquartile range of traffic-related PM2.5, elemental carbon (EC), organic carbon (OC), and nitrate (NO3−) were associated with elevated circulatory mortality risks of 1.80 % (95 % confidence interval, CI: 1.27, 2.33), 1.85 % (1.33, 2.37), 1.42 % (0.90, 1.94), and 1.10 % (0.55, 1.66) at 3-day moving average (lag 0-2 days), respectively. We also found relatively high associations between traffic-related PM2.5 and EC exposures and cardiovascular mortality, and OC exposure and cerebrovascular mortality. Moreover, our stratified analysis demonstrated such mortality risks tended to be stronger in males, individuals age 65 years or older, and during the cold season. ConclusionOur findings provided robust evidence on significant associations of traffic-related PM2.5 and specific constituents with circulatory mortality. Further emissions abatement from the transportation sector and corresponding pollutants should merit a particular focus in China.