Traffic Sites Research Articles

Innovative Individual Vehicle Record Traffic Data Quality Analysis Methods

Most traffic data collection sites have individual vehicle record (IVR) data of each vehicle passing the sensor area but have traditionally only stored binned and summary data because of previous hardware data storage limitations. Most recently, agencies and traffic equipment vendors are trending more toward IVR data-capable sites. Detailed IVR traffic data (including weigh-in-motion) are being collected, processed, and provided as an output product to agencies. Agencies process and store this very detailed IVR data from both portable and/or permanent traffic counting locations and could benefit from enhanced tools and methods that best leverage this rich information. This research paper details an extensive IVR literature review and 10 unique IVR innovative quality control and processing methods that would not be possible with traditional binned or summary speed, classification, and/or weight data. By employing these innovative methods, agencies are now better able to troubleshoot and check their data. These methods also offer improved monitoring of IVR sites to better assist the field staff who perform site visits, troubleshoot sensors, and fix equipment issues. The more detailed IVR data are best suited to meeting several customer needs and provide the same data streams that already exist from binned data sources. IVR data also provide additional value to every data collection site through more detailed traffic data that better explain travel characteristics.

Urban air quality changes resulting from the lockdown period due to the COVID-19 pandemic.

This work aims to quantify potential pollution level changes in an urban environment (Madrid city, Spain) located in South Europe due to the lockdown measures for preventing the SARS-CoV-2 transmission. Polluting 11 species commonly monitored in urban zones were attended. Except for O3, a prompt target pollutant levels abatement was reached, intensely when implanted stricter measures and moderately along those measures' relaxing period. In the case of TH and CH4, it is evidenced a progressive diminution over the lockdown period. While the highest decreasing average changes relapsed on NOx (NO2: − 40.0% and NO: − 33.3%) and VOCs (C7H8: − 36.3% and C6H6: − 32.8%), followed by SO2 (− 27.0%), PM10 (− 19.7%), CO (− 16.6%), CH4 (− 14.7%), TH (− 11.6%) and PM2.5 (− 10.1%), the O3 level slightly raised 0.4%. These changes were consistently dependent on the measurement station location, emphasizing urban background zones for SO2, CO, C6H6, C7H8, TH and CH4, suburban zones for PM2.5 and O3, urban traffic sites for NO and PM10, and keeping variations reasonably similar at all the stations in the case of NO2. Those pollution changes were not translated in variations on geospatial pattern, except for NO, O3 and SO2. Although the researched urban atmosphere improvement was not attributable to meteorological conditions' variations, it was in line with the decline in traffic intensity. The evidenced outcomes might offer valuable clues to air quality managers in urban environments regarding decision-making in favor of applying punctual severe measures for quickly and considerably relieving polluting high load occurred in urban environments.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13762-022-04464-6.

Impacts of the COVID-19 lockdown measures on coarse and fine atmospheric aerosol particles (PM) in the city of Rome (Italy): compositional data analysis approach.

In the year 2020, Italy faced a pandemic due to the virus SARS-CoV-2 for short COVID-19. Following this pandemic, a national lockdown period was imposed and throughout the year 2020 various measures were taken by the government to limit the mobility of people and contain the mortality associated with COVID-19. In Italy, pandemic measures led to a reduction in anthropogenic activities and provided an unprecedented opportunity to evaluate the possible effects that restrictions on anthropogenic activities may have on the air quality. Two background site (i.e., Cipro and Cinecittà) and a traffic sites (i.e., Corso Francia) were studied in the city of Rome. PM10 and PM2.5 were considered for the years 2019 and 2020. Moreover, the vehicular mobility, the emission classes of the vehicles, and the people mobility were taken into consideration along with meteorological variables. A compositional data analysis was used to evaluate the effect of pandemic measures on the fine- and coarse-size fractions of PM in the three considered sites. The results showed that in the traffic site (i.e., Corso Francia site) in 2020, there was a reduction of fine-size fraction of PM of about 10% when compared to the data of 2019, whereas in the background site (i.e., Cinecittà site) in 2020 there was an increase of fine-size fraction of PM of about 14% when compared to the data of 2019. No variation in the coarse- and fine-size fractions of PM were observed at the background site Cipro. This study showed how, in an urban context, PM can be influenced by strong changes in people’s habits and in vehicular mobility such as those recorded during the investigated period and due to pandemic lockdown measures.

Spatiotemporal Distributions and Source Apportionment of PM2.5‐Bound Antimony in Beijing, China

AbstractAntimony (Sb) is a toxic heavy metal, and PM2.5‐bound Sb (SbPM2.5) in the air impacts human health via inhalation pathways. In this study, we analyzed multiyear measurements of ambient SbPM2.5 in Beijing to characterize its spatiotemporal distributions, identify main sources, and predict future trends. The results show that ambient SbPM2.5 has been decreasing with fluctuations from 2005 to 2012 and decreased rapidly after 2013, which was likely a result of the government's enhanced air pollution control plan that targeted main sources of industrial Sb. Across the city, average SbPM2.5 concentrations were relatively higher at nonemission locomotive traffic sampling sites and in densely populated areas (9.45–19.45 ng/m3) and lower in background areas (0.6–0.9 ng/m3). Regional‐scale emissions and local human activities both affected the spatial distributions of SbPM2.5. Notably, SbPM2.5 concentration increased by 58.3% from 2006 to 2013 in one suburban background area, indicating the changing emission distributions and intensities over the study period. A neural network model was developed and tested to predict future SbPM2.5 levels, results from which showed that with simulated massive reductions in coal supplies and a rapid boom in the waste incineration industry, SbPM2.5 concentration would vary in a smaller range (from 4.08 to 4.38 ng/m3) over the next decade as compared to the observed range during 2011–2018 (19.0–5.44 ng/m3). The impact of the continued expansion of the waste incineration industry on SbPM2.5 pollution needs to be considered in future emission control policies.

BENZENE AND TOLUENE CONCENTRATION AT DIFFERENT TRAFFIC INTERSECTION DURING PRE-MID-POST WINTER SEASON, IN AMBIENT AIR OF ALIGARH AND ITS IMPACT ON HUMAN HEALTH

In current scenario, pollution in environment, is a big problem for all living species at around the world.We know that, Volatile Organic Compounds (VOCs) in presence of sunlight and oxides of nitrogen in atmosphere are considered as precursors for ozone production at the layer of Troposphere.Concentration of Benzene and Toluene (BT) in ambient air was measured near three major traffic sites in the city of Aligarh,India.All air samples were collected using for two times (in a month) during eight hours of normal working period time for in October – December 2020, and January - March 2021.The three selected sites used in this study represent traffic sites ( at Etah Chungi Chauraha, Quarsi Chauraha and Sootmil Chauraha, Aligarh ). In this study, real-time measurements of Benzene and Toluene concentration were performed the programmable compound specific PID detector designed to provide instantaneous exposure monitoring of a specific organic gas.It monitors a specific gas by utilizing a gas separation tube and the photo-ionization detector (PID) with a 9.8 eV gas discharge lamp (range- 50 ppb to 200 ppb) and whole data analyzed by SPSS software. The study the higher concentration 25.32 µg/m3 of Benzene in the evening shows at site 3 and lower concentration 10.22 µg/m3 of Benzene shows at site 2 in the morning.The higher concentration 22.22 µg/m3 in the evening of Toluene shows at site 1 and lower concentration 07.10 µg/m3 in the evening of Toluene shows at site 2, were observed respectively. Benzene and Toluene were widely used as a solvent in different products and petroleum. Exposure to a mixture of toluene and benzene in air led to an increase in the cytotoxic effect and DNA damage without any further repair and also its chronic effect on human health.The higher concentration of benzene and toluene co-exposure of benzene or toluene in this study.The relevance of these data on interactions for humans exposed at low benzene concentrations can be best assessed only when the mechanism of interaction is understood at a quantitative level and incorporated within a biologically based modelling framework for human health.

Quantifying changes in ambient NOx, O3 and PM10 concentrations in Austria during the COVID-19 related lockdown in spring 2020

During spring 2020, unprecedented changes in local and regional emissions have occurred around the globe due to governmental restrictions associated with COVID-19. Many European countries including Austria issued partial curfews or stay-at-home order policies, which have impacted ambient air quality through reductions in non-essential transportation and energy consumption of industrial sites and work places. Here, we analyse the effect of these measures on ambient concentrations of nitrogen oxides (NOx), ozone (O3) and particulate matter (PM10) during the first nationwide lockdown in Austria (16.03.2020 to 14.04.2020). To ensure a robust analysis, the Austrian domain is divided into four individual subsectors contingent on regional climate. For air quality analysis a novel method is applied for filtering days with comparable weather conditions during the 2020 lockdown and spring 2017 to 2019. In general, our analysis shows decreasing pollutant concentrations, although in magnitude dependent on pollutant and regional subdomain. Largest reductions are found for NOx reaching up to −68% at traffic sites reflecting the substantial decrease in non-essential transport. Changes in the O3 concentrations at background sites show a rather weak response to NOx declines varying between roughly −18 to +8% for both the median and the upper tail of the distribution. Occasional site level increases in O3 concentrations can be attributed to comparably weak titration during night-time. PM10 concentrations show the smallest response among air pollutants, attributable to manifold precursor sources not affected by the lockdown measures. However, our analysis indicates also a shift of PM10 distributions at traffic sites closer to distributions observed at background sites.

Size-segregated particulate matter characteristics in indoor and outdoor environments of urban traffic and residential sites

This study aims to assess the spatial and temporal variations of size-segregated particulate matter (PM) concentration in indoor and outdoor environments located in Vellore city, India. Size-segregated PM was measured using an eight-stage cascade impactor in traffic and residential sites during monsoon, winter, and summer seasons. Results showed that bimodal and trimodal distribution were common in indoor and outdoor environments of residential and traffic sites. Average outdoor (indoor) size-segregated mass concentration in all stages varied from 5 to 38 (7 to 42) and 4 to 32 (2 to 37) μg m−3 in traffic and residential sites, respectively. The maximum and minimum contribution to total PM mass was observed in 9 to 10 and < 0.4 μm fractions, respectively. Indoor concentration in traffic and residential sites was highest during summer and monsoon seasons. However, outdoor concentration was observed to be maximum during summer in both sampling sites. Correlation analysis of size-segregated PM mass with wind speed and wind direction indicated the non-regional source for coarse fraction concentrations and local source for fine fraction concentrations. Further, study results showed the dominance of coarse size fractions across all seasons in both sites.

Identification and Ranking of Accident Black Spots in Jordan

In any country, identifying high-intensity accident hotspots is essential in establishing effective techniques to minimize high-intensity accident sites. Because of Jordan's continual population growth in recent years, vehicle ownership has grown, leading to an increase in accident rates. According to many researches, Jordan suffers from damages caused by traffic accidents. As a result, the current study focuses on finding the black spots in selected Jordanian localities as a first step toward identifying the strategies to minimize traffic accidents in Jordan. To achieve this objective, the researcher started their investigation by collecting the accidents that occurred in Jordan during three years in 30 departments in Amman. The study area includes 30 segments in seven intersections in Amman city. Based on the collected data, the case study traffic sites were ranked based on their safety performance using several methods: accident rates, accident frequency, and accident severity index. The study's findings revealed that the high safety segment in the study area is from al-zamakhshre to interchange al-shfaa. In contrast, the high black spots are found from Jordan University to major streets. Results confirmed that identifying the high black spots segments contributes to reducing expected traffic accidents.

Mass, composition, and sources of particulate matter in residential and traffic sites of an urban environment.

Present study aims to assess the mass, composition, and sources of PM10 and PM2.5 (particulate matter having aerodynamic diameter less than or equal to 10 and 2.5µm aerodynamic diameter, respectively) in Vellore city. Seasonal samples collected in traffic and residential sites were analyzed for ions, elements, organic carbon (OC), and elemental carbon (EC). Source apportionment of PM10 and PM2.5 is carried out using Chemical Mass Balance, Unmix, Positive Matrix Factorization and Principal Component Analysis receptor models. Results showed that traffic site had higher annual concentration (PM2.5 = 62 ± 32 and PM10 = 112 ± 23µgm-3) when compared to residential site (PM2.5 = 54 ± 22 and PM10 = 98 ± 20µgm-3). Al, Ca, Fe, K, and Mg known to have crustal origin dominated the element composition irrespective of PM size and sampling site. Among ions, SO42- accounted highest in both sites with an average of 70 and 60% to PM2.5 and PM10 ionic mass. Elemental carbon contribution to PM mass was found highest in traffic site (PM2.5 = 17 to 23% and PM10 = 8 to 10%) than residential site (PM2.5 = 9 to 17% and PM10 = 4 to 8%). Elements, ions, OC, and EC accounted 12, 28, 34, and 16% of PM2.5 mass and 12, 21, 20, and 8% of PM10 mass, respectively. Different sources identified by the receptor models are resuspended road dust, crustal material, secondary aerosol, traffic, non-exhaust vehicular emissions, secondary nitrate, construction, cooking, and biomass burning. Since Vellore is aspiring to be a smart city, this study can help the policymakers in effectively curbing PM.

Improving the current air quality index with new particulate indicators using a robust statistical approach

To convey the severity of ambient air pollution level to the public, air quality index (AQI) is used as a communication tool to reflect the concentrations of individual pollutants on a common scale. However, due to the enhanced air pollution control in recent years, air quality has improved, and the roles of some air pollutant species included in the existing AQI as urban air pollutants have diminished. In this study, we suggest the current AQI should be revised in a way that new air pollution indicators would be considered so that it would better represent the health effects caused by local combustion processes from traffic and residential burning. Based on the air quality data of 2017–2019 in three different sites in Helsinki metropolitan area, we assumed the statistical distributions of the current indicators (NO2 and PM2.5) and the proposed particulate indicators (BC, LDSA and PNC) were related as they have similar sources in urban regions despite the varying correlations between the current and proposed indicators (NO2: r = 0.5–0.85, PM2.5: r = 0.28–0.72). By fitting the data to an optimal distribution function, together with expert opinions, we improved the current Finnish AQI and determined the AQI breakpoints for the proposed indicators where this robust statistical approach is transferrable to other cities. The addition of the three proposed indicators to the current AQI would decrease the number of good air quality hours in all three environments (largest decrease in urban traffic site, ~22 %). The deterioration of air quality class appeared more severe during peak hours in the urban traffic site due to vehicular emission and evenings in the detached housing site where domestic wood combustion often takes place. The introduction of the AQI breakpoints of the three new indicators serve as a first step of improving the current AQI before further air quality guideline levels are updated.

Road Traffic and Its Influence on Urban Ammonia Concentrations (France)

Ammonia (NH3) is an unregulated atmospheric gaseous pollutant in ambient air, involved in the formation of fine particles. Ammonia is therefore a major precursor of particulate matter (PM), the health effects of which have been widely demonstrated. NH3 emissions are clearly dominated by the agricultural sector (livestock and fertilizers), but other sources may also be important and less studied, such as road traffic with the increased use of catalytic converters in vehicles. This study is based on a long-term real-time measurements campaign (December 2019–September 2021) on two urban sites: a background site and a roadside site in the same agglomeration in France. The study of historical measurements at the background site clearly demonstrated the dominance of agriculture on the ammonia concentrations. This influence was also observed at both sites during the measurement campaign. The annual and monthly averages obtained in the study were similar to previous ones, with concentrations between 1–10 µg/m3 at both sites, indicating lower levels than previous studies for the roadside site. The ammonia levels measured during the campaign at the traffic site were significantly higher than those measured at the background site, highlighting the road traffic influence on ammonia in urban area. The biomass burning influence also seemed to be observed during this long measurement campaign at the agglomeration scale. The influences of road traffic and biomass burning on ammonia concentration remain small compared to agriculture.

Long-term behavior and stability of calibration models for NO and NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; low-cost sensors

Abstract. Low-cost sensors are considered to exhibit great potential to complement classical air quality measurements in existing monitoring networks. However, the use of low-cost sensors poses some challenges. In this study, the behavior and performance of electrochemical sensors for NO and NO2 were determined over a longer operating period in a real-world deployment. After careful calibration of the sensors, based on co-location with reference instruments at a rural traffic site during 6 months and by using robust linear regression and random forest regression, the coefficient of determination of both types of sensors was high (R2 &gt; 0.9), and the root mean square error (RMSE) of NO and NO2 sensors was about 6.8 and 3.5 ppb, respectively, for 10 min mean concentrations. The RMSE of the NO2 sensors, however, more than doubled when the sensors were deployed without recalibration for a 1-year period at other site types (including urban background locations), where the range and the variability of air pollutant concentrations differed from the calibration site. This indicates a significant effect of relocation of the sensors on the quality of their data. During deployment, we found that the NO2 sensors are capable of distinguishing general pollution levels, but they proved unsuitable for accurate measurements, mainly due to significant biases. In order to investigate the long-term stability of the original calibration, the sensors were reinstalled at the calibration site after deployment. Surprisingly, the coefficient of determination and the RMSE of the NO sensor remained almost unchanged after more than 1 year of operation. In contrast, the performance of the NO2 sensors clearly deteriorated as indicated by a higher RMSE (about 7.5 ppb, 10 min mean concentrations) and a lower coefficient of determination (R2 = 0.59).

Correction: Sadiq et al. A Characterization and Cell Toxicity Assessment of Particulate Pollutants from Road Traffic Sites in Kano State, Nigeria. Atmosphere 2022, 13, 80

Emerging African countries are characterized by explosive population growth and urbanization, which threaten environmental sustainability. This study comparatively characterized ambient aerosols and assessed cytotoxicity to facilitate improving health and environmental policy. Twenty-four air samples were collected at high and low-density traffic sites in Kano State using polysulfone and stainless steel filters attached to an automated pump. The physico-chemical properties of particulate matter were determined using scanning electron microscopy and energy dispersive X-ray analysis (SEM-EDX). In vitro, their potential toxicity was assessed using macrophages and cell fixation with staining. Results showed 51.7% of particles as PM2.5, with the highest particle concentration in mixed sites (urban and industrial). Particle classification into four groups by elemental composition and structure showed: sand particles (Si, Al, Fe, Ca, Mg, K, Na, Mo, Sr, Zr) 30–51%; other fibers 0–3%; other particles (Si, Fe, S, Mo, Zn, and other metals) 22–40%; and silicone-based fibres 23–34%. The abundant elements are: Si, Al, Ca, Ce, Ti, Fe, Cl, Pb, and Mn. The lowest viability on cytotoxicity assessment was recorded in mixed site M2. The majority of households were located within 50 m of air sampling sites. Proximity to traffic sites worsens health, as evidenced in cytotoxicity findings. We recommend improved urban planning and intensification of emissions control.

Motorway Bottleneck Probability Estimation in Connected Vehicles Environment Using Speed Transition Matrices.

Increased development of the urban areas leads to intensive transport service demand, especially on urban motorways. To increase traffic flow and reduce congestion, motorway traffic bottlenecks caused by high traffic demand need to be efficiently resolved using Intelligent Transport Systems services. Communication technology development that supports Connected Vehicles (CVs), which act as an active mobile sensor for collecting traffic data, provides an opportunity to harness the large datasets to develop novel methods regarding traffic bottlenecks detection. This paper presents a speed transition matrix based model for bottleneck probability estimation on motorways. The method is based on the computation of the speed at the vehicle transition point between consecutive motorway segments, which forms a traffic pattern that is represented using transition matrices. The main feature extracted from the traffic patterns was the center of mass, whose position is used as an input to the fuzzy-based system for bottleneck probability estimation. The proposed method is evaluated on four different simulated motorway traffic scenarios: (i) traffic collision site, (ii) short recurring bottleneck, (iii) long recurring bottleneck, and (iv) moving bottleneck. The method achieves comparable bottleneck detection results on every scenario, with a total accuracy of 92% on the validation dataset. The results indicate possible implementation of the method in the motorway traffic environment with a high CVs penetration rate using them as the sensory input data for the control systems based on the machine learning algorithms.

Statistical modeling of complex health outcomes and air pollution data: Application of air quality health indexing for asthma risk assessment

&#x0D; Background: Statistical models for complex health outcome data analyses with; zero inflation, autocorrelation, confounding, seasonality and delayed exposures, play an important role in accurately assessing air pollution risk, especially in public health warning using national air quality health indices (NAQHI). NAQHI assessment generalizes model estimates across all geographies and seasons and neglects area and season specific variations. The aim is to develop complex statistical models, specific to the complex data structures and to demonstrate effectiveness of the model estimates in public health massage delivery.&#x0D; Methods: A time series model was fitted to asthma hospital admissions and ambient air pollution data from two sites, Halifax, an urban, traffic and industry polluted site and Sydney, a rural waste disposal polluted site, in the province of Nova Scotia, Canada. I fitted zero inflated, auto regressive, Poisson and Negative Binomial models with lagged effects for sparse asthma admissions and air pollution data and compared the model risk estimates with that of the NAQHI.&#x0D; Results: NAQHI used three pollutants, Nitrogen Dioxide, Ozone and particulate matter. I found Carbon monoxide in the urban site and lead in the waste disposal site as prominent pollutants and there were seasonal differences. The findings demonstrated severe under-assessment of asthma relative risk by NAQHI, when prominent pollutants are neglected and also when auto correlation and zero inflation are ignored. &#x0D; Conclusion: This study demonstrated the importance of complex statistical model use and the consequences of lack of such modelling that accounted for data structures in public health risk assessments.

Variability and sources of NMHCs at a coastal urban location in the Piraeus Port, Greece

Ambient concentrations and sources of non-Methane Hydrocarbons (NMHCs) with 6–9 carbon atoms were investigated at an industrialized coastal location within the Port of Piraeus in Greece. Measurements were performed for a yearlong period during 2019 by means of an automated gas chromatograph with flame ionization detector (GC-FID). N-Hexane registered the highest annual mean concentration, followed by toluene and benzene, whereas all compounds presented important day to day variability, with an enhancement in summer. The seasonal diurnal cycles were characterized by strong morning peaks, especially in summer. The night-time maxima were less pronounced during the warm period, by almost 50% relative to the morning ones. On the contrary, during winter night-time, the combined impact of emissions and the shallow boundary layer was reflected on the night-time peaks. The area seems to be affected mainly by local land emission sources, whereas temperature possibly triggers evaporation processes, as indicated by comparisons with nearby traffic and urban background sites. The enhanced NMHCs concentration, in spite of increased ventilation coefficients during the summer, indicated again the impact of local emission sources. This was also highlighted by means of Positive Matrix Factorization (PMF) modeling. Three PMF factors were identified, quantified and supported by supplementary seasonal runs during short-term campaigns. Fugitive emissions were recognized as the main source, contributing more than 70% of total NMHCs year-round, while the input of emissions associated with traffic and diesel combustion was almost equal (13% and 15%, respectively).

Perception of noise mitigation approaches along a major highway construction site

The aim of this study was to describe the perception and satisfaction of mitigation measures along the construction site of a major urban highway, and to quantify the relationship between mitigation measures and noise annoyance. A total of 1,409 participants were included in a first socio-acoustic survey in 2018, and 609 in a second survey in 2020. Residents were generally satisfied with most of mitigation measures, although a reduction in their perceived effectiveness was observed in the 2020 survey. The perception of mitigation measures explained between 2.9 and 6.5% of the variance in construction noise annoyance. Traffic management, site surveillance and temporary noise barriers were the most important variables in the statistical models. While some measures are used only by a small proportion of the target population, our results show that implementing comprehensive mitigation measures can help to reduce construction noise annoyance.

Distribution and sources of SVOCs in fine and coarse aerosols in the megacity of Istanbul

Approximately 15.4 million people are continuously exposed to various air pollutants in the megacity of Istanbul. Anthropogenic activities in Istanbul generate emissions from mobile sources (i.e., vehicles, aircraft, ships, etc.) and stationary sources such as industrial and residential heating emissions. Biogenic emissions and long-range transport such as desert dust from Sahara and pollutants from Balkan countries also contribute to the local air pollution in Istanbul. In this work, fine (Dp < 2.5 μm) and coarse (Dp > 2.5 μm) particles were collected with a high-volume sampler during four seasons of the period Jan 2017 - Jan 2018. A total of 15 PAHs and 28 n-alkanes were identified and quantified with a newly developed thermal desorption – gas chromatography with mass spectrometry method (TD-GC–MS). Source analysis was performed with PAH and n-alkane diagnostic ratios, and source apportionment was performed with principal component analysis. The yearly averages of PAHs and n-alkanes in the fine fraction were 21.6 ng m−3 and 103.8 ng m−3, with daily averages of 7.1–80.8 ng m−3 and 55.3–204.2 ng m−3, respectively. Approximately 90% of the PAHs and n-alkanes were found in the fine PM fraction in this traffic site. The BaP carcinogenic (BaP-TEQ) and mutagenic (BaP-MEQ) equivalents were on average 5.47 ± 0.64 and 4.72 ± 0.8 ng m−3 in the fine fraction, respectively, and were approximately 6–7 times lower in the coarse fraction. This has important implications due to the respirable nature of fine aerosols and their longer lifetimes in the atmosphere. Multivariate analysis coupled with principal component analysis led to an important result that the organic aerosol mainly originates from two local sources: road traffic (50.4%) and shipping emissions (26.6%). The results found in this work indicate the urgent need for the application of mitigation measures to control road traffic and minimize the emissions from ships passing through the İstanbul Bosphorus.

Size-dependent in vitro inhalation bioaccessibility of PAHs and O/N PAHs - Implications to inhalation risk assessment

Size segregated samples (<0.49, 0.49–0.95, 0.95–1.5, 1.5–3.0, 3.0–7.2 and > 7.2 μm) of atmospheric particulate matter (APM) were collected at a traffic site in the urban agglomeration of Thessaloniki, northern Greece, during the cold and the warm period of 2020. The solvent-extractable organic matter was analyzed for selected organic contaminants including polycyclic aromatic hydrocarbons (PAHs), and their nitro- and oxy-derivarives (NPAHs and OPAHs, respectively). Mean concentrations of ∑16PAHs, ∑6NPAHs and ∑10OPAHs associated to total suspended particles (TSP) were 18 ng m−3, 0.2 ng m−3 and 0.9 ng m−3, respectively, in the cold period exhibiting significant decrease (6.4, 0.2 and 0.09 ng m−3, respectively) in the warm period. The major amount of all compounds was found to be associated with the alveolar particle size fraction <0.49 μm. The inhalation bioaccessibility of PAHs and O/N PAHs was measured in vitro using two simulated lung fluids (SLFs), the Gamble's solution (GS) and the artificial lysosomal fluid (ALF). With both SLFs, the derived bioaccessible fractions (BAFs) followed the order PAHs > OPAHs > NPAHs. Although no clear dependence of bioaccessibility on particle size was obtained, increased bioaccessibility of PAHs and PAH derivatives in coarse particles (>7.2 μm) was evident. Bioaccessibility was found to be strongly related to the logKOW and the water solubility of individual compounds hindering limited mobilization of the most hydrophobic and less water-soluble compounds from APM to SLFs. The lifetime cancer risk due to inhalation exposure to bioaccessible PAHs, NPAHs and OPAHs was estimated and compared to those calculated from the particulate concentrations of organic contaminants.

Estimating changes in air pollutant levels due to COVID-19 lockdown measures based on a business-as-usual prediction scenario using data mining models: A case-study for urban traffic sites in Spain

In response to the COVID-19 pandemic, governments declared severe restrictions throughout 2020, presenting an unprecedented scenario of reduced anthropogenic emissions of air pollutants derived mainly from traffic sources. To analyze the effect of these restrictions derived from COVID-19 pandemic on air quality levels, relative changes in NO, NO2, O3, PM10 and PM2.5 concentrations were calculated at urban traffic sites in the most populated Spanish cities over different periods with distinct restrictions in 2020. In addition to the changes calculated with respect to the observed air pollutant levels of previous years (2013–2019), relative changes were also calculated using predicted pollutant levels for the different periods over 2020 on a business-as-usual scenario using Multiple Linear Regression (MLR) models with meteorological and seasonal predictors. MLR models were selected among different data mining techniques (MLR, Random Forest (RF), K-Nearest Neighbors (KNN)), based on their higher performance and accuracy obtained from a leave-one-year-out cross-validation scheme using 2013–2019 data. A q-q mapping post-correction was also applied in all cases in order to improve the reliability of the predictions to reproduce the observed distributions and extreme events. This approach allows us to estimate the relative changes in the studied air pollutants only due to COVID-19 restrictions. The results obtained from this approach show a decreasing pattern for NOx, with the largest reduction in the lockdown period above −50%, whereas the increase observed for O3 contrasts with the NOx patterns with a maximum increase of 23.9%. The slight reduction in PM10 (−4.1%) and PM2.5 levels (−2.3%) during lockdown indicates a lower relationship with traffic sources. The developed methodology represents a simple but robust framework for exploratory analysis and intervention detection in air quality studies.