Air Quality In Urban Environment Research Articles

Associations between Indoor and Outdoor Size-Resolved Particulate Matter in Urban Beijing: Chemical Compositions, Sources, and Health Risks

Ventilation may lead to a deterioration in indoor air quality in urban environments located close to roads. Understanding the differences in the chemical compositions of size-resolved particulate matter (PM) in indoor air and outdoor air could aid in assessing the health impacts of air in these settings and establishing relevant regulation policies. In this study, indoor and outdoor size-resolved PM was collected from an office in Beijing in summer (between 5 and 25 July 2020) and winter (between 5 and 31 January 2021). Its chemical components, including sulfate, nitrate, ammonium, chlorine, organic matter (OM), elemental carbon (EC), crustal materials (CM), and heavy metals (HM), were analyzed. The mean levels of indoor and outdoor PM2.1 and PM9 were found to be much higher than those in the guidelines for PM2.5 and PM10 outlined by the National Ambient Air Quality Standard. Moreover, the levels of PM2.1 and PM2.1–9 mass were higher outdoors than they were indoors. The size distributions of mass concentrations were shown to be bimodal, peaking at 0.43–0.65 μm and 4.7–5.8 μm, respectively. The most abundant chemicals were OM, nitrate, and sulfate for PM2.1 and OM, CM, and nitrate for PM2.1–9. We found higher percentages of sulfate, nitrate, ammonium, EC, and HM in smaller-size fractions of PM. Additionally, positive matrix factorization showed that biomass burning, secondary inorganic aerosol, coal combustion, dust, traffic, and industrial pollution were the main sources of PM during the study period. The greatest non-carcinogenic and carcinogenic hazards were found at 0.43–0.65 μm in summer and 2.1–3.3 μm in winter. Our results indicate that size-resolved PM of ambient origin may infiltrate buildings near roads to varying degrees, resulting in negative health effects.

ARIMA Analysis of PM Concentrations during the COVID-19 Isolation in a High-Altitude Latin American Megacity

The COVID-19 pandemic precipitated a unique period of social isolation, presenting an unprecedented opportunity to scrutinize the influence of human activities on urban air quality. This study employs ARIMA models to explore the impact of COVID-19 isolation measures on the PM10 and PM2.5 concentrations in a high-altitude Latin American megacity (Bogota, Colombia). Three isolation scenarios were examined: strict (5 months), sectorized (1 months), and flexible (2 months). Our findings indicate that strict isolation measures exert a more pronounced effect on the short-term simulated concentrations of PM10 and PM2.5 (PM10: −47.3%; PM2.5: −54%) compared to the long-term effects (PM10: −29.4%; PM2.5: −28.3%). The ARIMA models suggest that strict isolation measures tend to diminish the persistence of the PM10 and PM2.5 concentrations over time, both in the short and long term. In the short term, strict isolation measures appear to augment the variation in the PM10 and PM2.5 concentrations, with a more substantial increase observed for PM2.5. Conversely, in the long term, these measures seem to reduce the variations in the PM concentrations, indicating a more stable behavior that is less susceptible to abrupt peaks. The differences in the reduction in the PM10 and PM2.5 concentrations between the strict and flexible isolation scenarios were 23.8% and 12.8%, respectively. This research provides valuable insights into the potential for strategic isolation measures to improve the air quality in urban environments.

Examining the relationship between atmospheric pollutants and meteorological factors in Asansol city, West Bengal, India, using statistical modelling.

Meteorological conditions significantly impact ambient air quality in urban environments. This study focuses on Asansol, known as the "Coal City" and the "Industrial Heart of West Bengal," a notable hotspot for air pollution. Despite its significance, limited research has addressed the influence of meteorological factors on key air pollutants in this urban area. From January 2019 to December 2023, this investigation explores the relationships between meteorological parameters (including atmospheric temperature, relative humidity, rainfall, wind speed) and the concentrations of crucial air pollutants (PM2.5, PM10, NO2, SO2). Temporal trends in air pollutant concentrations are also analysed. The Spearman correlation method is used to establish associations between pollutant concentrations and meteorological variables, while multiple linear regression (MLR) models are employed to assess meteorological factors and potential impact on pollutant concentrations. The analysis reveals a decreasing trend in pollutant concentrations in Asansol. Temperature exhibits negative correlations with all pollutants in all seasons except for a positive correlation during the monsoon. Rainfall consistently displays significant negative correlations with pollutants in all seasons. Relative humidity is negatively correlated with pollutants in all seasons, and wind speed, except during the post-monsoon season, shows negative correlations with all pollutants. Linear models excel in predicting particulate matter concentrations but perform poorly in predicting gaseous contaminants. Accounting for seasonal fluctuations and meteorological parameters, this research enhances the accuracy of air pollution forecasting, contributing to a better understanding of air quality dynamics in Asansol and similar urban areas.

Integrasi Bioenergi dalam Desain Taman Kota

Bioenergy is a renewable energy source that can be renewed naturally and has a good environmental impact on air quality in urban environments. Urban parks have the potential to integrate bioenergy into an urban context. Design environmentally friendly city parks to be able to produce bioenergy, so that public spaces can double as both open recreation spaces and sources of green energy. The air condition in Lhokseumawe City experiences CO2 pollution and high air temperatures. The aim is to implement bioenergy in gardens through application to plants and trees. Climate change is characterized by extreme rainfall and temperatures. Apart from that, the depletion of the ozone layer is the impact of global warming which is indicated by high air temperatures a global issue. In essence, climate change occurs in all cities. Apart from that, rapid urban development is the influence of the activity and density of the city center which triggers an increase in global warnings and has an impact on thermal comfort. good air quality and thermal conditions in outdoor spaces in urban areas are difficult to find. The presence of public space plays a role as a green open space and a source of green energy and renewable energy and can increase absorption areas. However, the existence of environmentally friendly green open spaces that are capable of reducing global warming cannot be integrated with bioenergy, which is still less familiar and not yet optimal for application, so it is the basic fundamental phenomenon in this research. This research aims to identify thermal quality (CO2, temperature, and wind speed); identify softcape elements, namely plants in RTH, and contribute through integration with the bioenergy approach in RTH as a solution to reduce global warming, especially CO2. This type of research is descriptive using a quantitative approach. The research results show that CO2 levels have exceeded the threshold, resulting in air pollution with high air temperatures. This condition has a very negative impact on the survival of an urban environmental climate. The presence of plant elements as softcap elements has yet to be fulfilled, so certain plants are needed as a solution in producing bioenergy applications.

Air quality analysis and modeling in urban area: A review study

Urban areas across the world are experiencing significant challenges related to air quality, with adverse effects on public health, the environment, and overall quality of life. This thesis aims to investigate and model air quality in urban environments, focusing on the identification of pollution sources and the evaluation of potential mitigation strategies. The research begins by analyzing the complex interplay of factors influencing urban air quality, including emissions from vehicular traffic, industrial activities, and meteorological conditions. Various modeling techniques, such as numerical simulations, statistical analyses, and machine learning algorithms, are employed to assess the spatiotemporal distribution of air pollutants within urban areas. The overview is carried out to focus on various parameters such as emission sources, meteorological parameters, and topographical features to predict pollutant concentrations. The study also explores the effectiveness of different mitigation strategies to improve urban air quality. These strategies may include urban planning measures, such as the design of green spaces and pedestrian-friendly zones, as well as transportation-related interventions like the promotion of electric vehicles and the enhancement of public transportation systems. The impact of these strategies on reducing pollutant concentrations is quantitatively assessed using the developed air quality models. Furthermore, the study considers the implications of climate change on urban air quality, acknowledging that changing climate patterns can exacerbate air pollution issues. Potential adaptation strategies to address these challenges are discussed. In conclusion, this thesis offers a comprehensive analysis of air quality modeling in urban areas, providing insights into the sources of pollution and the effectiveness of mitigation measures. The research aims to inform policymakers, urban planners, and environmental stakeholders in their efforts to create healthier and more sustainable urban environments.

The influence of plant species, leaf morphology, height and season on PM capture efficiency in living wall systems

Green infrastructure (GI) is already known to be a suitable way to enhance air quality in urban environments. Living wall systems (LWS) can be implemented in locations where other forms of GI, such as trees or hedges, are not suitable. However, much debate remains about the variables that influence their particulate matter (PM) accumulation efficiency. This study attempts to clarify which plant species are relatively the most efficient in capturing PM and which traits are decisive when it comes to the implementation of a LWS. We investigated 11 plant species commonly used on living walls, located close to train tracks and roads. PM accumulation on leaves was quantified by magnetic analysis (Saturation Isothermal Remanent Magnetization (SIRM)). Several leaf morphological variables that could potentially influence PM capture were assessed, as well as the Wall Leaf Area Index. A wide range in SIRM values (2.74–417 μA) was found between all species. Differences in SIRM could be attributed to one of the morphological parameters, namely SLA (specific leaf area). This suggest that by just assessing SLA, one can estimate the PM capture efficiency of a plant species, which is extremely interesting for urban greeners. Regarding temporal variation, some species accumulated PM over the growing season, while others actually decreased in PM levels. This decrease can be attributed to rapid leaf expansion and variations in meteorology. Correct assessment of leaf age is important here; we suggest individual labeling of leaves for further studies. Highest SIRM values were found close to ground level. This suggests that, when traffic is the main pollution source, it is most effective when LWS are applied at ground level. We conclude that LWS can act as local sinks for PM, provided that species are selected correctly and systems are applied according to the state of the art.

How does particulate matter affect plant transcriptome and microbiome?

Phylloremediation for the reduction of air particulate matter (PM) is an interesting opportunity to significantly contribute to improve the air quality of urban environment. The aim of this study was to: 1) gain insight into the gene regulatory networks modulating leaf responses to polluted air, 2) identify possible changes in the leaf microbiome due to particulate matter in the real urban environment. The leaf transcriptome and microbiome were analyzed for Photinia x fraseri L. plants cultivated for three months in pots in two close-by areas under different levels of air PMs (low and high). PCA and heat map analysis showed that 28 differentially expressed genes in common between the three pairwise comparisons were able to clearly discriminate plants under higher PM levels. The pollutants were mainly sensed by plants through a restructuring modification of cell wall and membrane due to the main repression of lipid desaturases. In addition, high PMs showed a clear repression of genes belonging to primary metabolism pathways involved in C assimilation. Microbiome analysis showed no significant changes in taxonomic diversity indexes for the bacterial communities, whereas fungi belonging to the genera Epicoccum and Dioszegia were differently affected by the different exposure to PM levels. A model of transcriptional regulation to air PMs in plants has been proposed.

Impacts of COVID-19 Lockdown on Traffic Flow, Active Travel and Gaseous Pollutant Concentrations; Implications for Future Emissions Control Measures in Oxford, UK

The COVID-19 lockdown provided a unique opportunity to test the impacts of changes in travel patterns on air quality and the environment. Therefore, this study provides insights into the impacts of COVID-19 emergency public health “lockdown” measures upon traffic flow, active travel and gaseous pollutant concentrations (NO, NO2 and O3) in Oxford city centre during 2020 using time-series analysis and linear regression methods. Comparisons of traffic counts indicated pronounced changes in traffic volume associated with national lockdown periods. Car volume reduced by 77.5% (statistically significant) during the first national lockdown, with lesser changes in goods vehicles and public transport (bus) activity during the second lockdown. Cycle flow reduced substantively during the first lockdown only. These changes resulted in a reduction in nitric oxide (NO) and nitrogen dioxide (NO2) concentrations of 75.1% and 47.4%, respectively, at roadside, and 71.8% and 34.1% at urban background during the first lockdown period. In contrast ozone (O3) concentrations increased at the urban background site by 22.3% during the first lockdown period, with no significant changes in gaseous concentrations during the second lockdown at either roadside or urban background location. The diurnal pattern of peak mean NO and NO2 concentrations reduced in magnitude and was shifted approximately 2 h earlier in the morning and 2 h later in the evening (roadside) and 3 h earlier in the morning and 3 h later in the evening (urban background). Our findings provide an example of how gaseous air quality in urban environments could respond to future urban traffic restrictions, suggesting benefits from reductions in peak and daily NO2 exposures may be offset by health harms arising from increases in ground level O3 concentrations in the summer months.

PM10 variation, composition, and source analysis in Tuscany (Italy) following the COVID-19 lockdown restrictions

Abstract. To control the spread of COVID-19, exceptional restrictive measures were taken in March 2020 that imposed a radical change on the lifestyle of millions of citizens around the world, albeit for a short period. The national lockdown, which lasted from 10 March to 18 May 2020 in Italy, was a unique opportunity to observe the variation in air quality in urban environments under conditions comprising almost total traffic restriction and a strong reduction in work activities. In this paper, the data from 17 urban monitoring sites in Tuscany are presented, and the PM and NO2 concentrations in the 2 months before the start of the lockdown and the 2 months after lockdown are compared with the corresponding months of the previous 3 years. The results show that the total loads of PM2.5 and PM10 (particulate matter with an aerodynamic diameter smaller than 2.5 and 10 µm, respectively) decreased, but they did not exhibit significant changes compared to previous years, whereas NO2 underwent a drastic reduction. For three of these sites, the chemical composition of the collected samples was measured using thermal–optical techniques, ion chromatography, and particle-induced X-ray emission analysis, and the application of multivariate positive matrix factorization analysis also allowed for PM10 source identification and apportionment. Using these analyses, it was possible to explain the low sensitivity of PM10 to the lockdown effects as being due to different, sometimes inverse, behaviors of the different sources that contribute to PM. The results clearly indicate a decline in pollution levels related to urban traffic and an increase in the concentration of sulfate for all sites during the lockdown period.

Spatial characteristics of VOCs and their ozone and secondary organic aerosol formation potentials in autumn and winter in the Guanzhong Plain, China

As critical precursors of tropospheric ozone (O3) and secondary organic aerosol (SOA), volatile organic compounds (VOCs) largely influence air quality in urban environments. In this study, measurements of 102 VOCs at all five major cities in the Guanzhong Plain (GZP) were conducted during Sep.09-Oct. 13, 2017 (autumn) and Nov. 14, 2017–Jan. 19, 2018 (winter) to investigate the characteristics of VOCs and their roles in O3 and SOA formation. The average concentrations of total VOCs (TVOCs) at Xi'an (XA), Weinan (WN), Xianyang (XY), Tongchuan (TC), and Baoji (BJ) sites were in the range of 55.2–110.2 ppbv in autumn and 42.4–74.3 ppbv in winter. TVOCs concentrations were reduced by 22.4%–43.5% from autumn to winter at XA, WN and BJ. Comparatively low concentrations of TVOCs were observed in XY and TC, ranging from 53.5 to 62.7 ppbv across the sampling period. Alkanes were the major components at all sites, accounting for 26.4%–48.9% of the TVOCs during the sampling campaign, followed by aromatics (4.2%–26.4%). The average concentration of acetylene increased by a factor of up to 4.8 from autumn to winter, indicating the fuel combustion in winter heating period significantly impacted on VOCs composition in the GZP. The OH radical loss rate and maximum incremental reactivity method were employed to determine photochemical reactivities and ozone formation potentials (OFPs) of VOCs, respectively. The VOCs in XA and WN exhibited the highest reactivities in O3 formation, with the OFP of 168–273 ppbv and the OH loss rates of 19.3–40.8 s−1. Alkenes and aromatics primarily related to on-road and industrial emissions contributed 57.8%–76.3% to the total OFP. The contribution of aromatics to the SOA formation at all sites reached 94.1%–98.6%. Considering the potential source-area of VOCs, regional transport of VOCs occurred within the GZP cities.

A Novel Bike-Mounted Sensing Device with Cloud Connectivity for Dynamic Air-Quality Monitoring by Urban Cyclists.

We present a device based on low-cost electrochemical and optical sensors, designed to be attached to bicycle handlebars, with the aim of monitoring the air quality in urban environments. The system has three electrochemical sensors for measuring NO2 and O3 and an optical particle-matter (PM) sensor for PM2.5 and PM10 concentrations. The electronic instrumentation was home-developed for this application. To ensure a constant air flow, the input fan of the particle sensor is used as an air supply pump to the rest of the sensors. Eight identical devices were built; two were collocated in parallel with a reference urban-air-quality-monitoring station and calibrated using a neural network (R2 > 0.83). Several bicycle routes were carried out throughout the city of Badajoz (Spain) to allow the device to be tested in real field conditions. An air-quality index was calculated to facilitate the user’s understanding. The results show that this index provides data on the spatiotemporal variability of pollutants between the central and peripheral areas, including changes between weekdays and weekends and between different times of the day, thus providing valuable information for citizens through a dedicated cloud-based data platform.

The level of air quality at public transport stations: The Case of Torhailoch-Ayat main road in Addis Ababa

IntroductionThe increase of population and rapid spatial expansion of urban areas generate high travel demand and increase of motorization, which is directly related to air quality of urban environment. The continuous increase in traffic congestion and fuel consumption deteriorates air quality. Public transportation stations are places where people spend a considerable amount of time in the open and get exposed to transport-related emissions. The aim of this study is to investigate the level of air quality at public transport stations in Addis Ababa city along the major route from Torhailoch to Ayat focusing on the concentration of PM2.5, PM10, Air Quality Index (AQI) and CO2. Methods and materialsObservation, vehicle count and field measurements of air quality were used to collect the data. Primary data were collected via field surveying using IQAir AirVisual® pro model air quality measuring device from five public transport stations at peak and off-peak hours. ResultsThis study found that increase in peak hour traffic volume at stations contributes high concentration of PM2.5, PM10, AQI and CO2. High levels of air pollutants were found during peak hours compared to off peak hours. The maximum 30 min’ average concentrations of PM2.5 were found to be 89 μg/m3 during peak hours and 61 μg/m3 during off peak hours, which is far exceeding the WHO air quality standard (35.4 μg/m3). Regression model shows dependent variable (PM2.5) and independent variables is statistically significant. ConclusionThe temporal and spatial distributions of the air pollutants in this study demonstrated that rush hours were the most polluted, having high concentrations of PM2.5 and PM10 while an off-peak hour have low concentration of air pollutants. RecommendationIt is recommended that the city government should encourage zero emission vehicles, provision of efficient public transport and green development in order to reduce the current condition of transport-related air pollutants.

Development of urban air monitoring with high spatial resolution using mobile vehicle sensors.

Traditionally, the equipment used to measure air pollution is expensive and placed around cities or in mobile laboratories. It might only represent a certain area and not the entire city due to the locations and limited number of monitoring stations. Nowadays, a mobile sensing is becoming an alternative option to monitor air quality in urban environment due to its ease of use, high flexibility, and low price. This paper develops a vehicular-based mobile monitoring system for real time air quality sensing and visualization across large cities with high spatial resolution. The commercially available low-cost CO, NO[Formula: see text], NH[Formula: see text] O[Formula: see text], CH[Formula: see text], SO[Formula: see text], PM[Formula: see text], temperature and humidity sensors along with the microcontroller and GPS were integrated in a sensing device installed on the roof of taxi and sport utility vehicle (SUV). The developed device was calibrated through a reference monitoring station and validated through field measurement. We first split the entire city with a uniform grid discretization. We then propose a data processing methodology based on machine learning algorithms for generating 250 representative data set from 286 million data which is collected using the vehicular based mobile sensors. Next we present the representativeness of the data set by comparison of stationary data and mobile data. We also describe the analytical results and spatial distribution with high spatial resolution throughout the city. In addition, the collected mobile sensor data is also used to show that the significant differences and spatial variability in mean levels per street. Finally, we conclude that the proposed mobile monitoring system using high spatial resolution can effectively map the air quality in metropolitan environment and provide detail about the spatial variability that cannot be done with stationary monitoring systems.

Impact of synoptic meteorological conditions on air quality in three different case studies in Rome, Italy

This study analyses the influence of synoptic weather conditions on atmospheric particulate matter concentration and composition during an intensive measurement campaign, performed in the urban area of Rome (Italy) in winter 2017. To evaluate the effect of local particulate sources, data from several urban and rural ground-based air quality stations were considered. The analysis involved the following atmospheric parameters: wind speed and direction near the ground, air temperature, specific humidity, height and evolution of the mixing layer. Furthermore, the daily variability of aerosol optical depth, tropospheric and near-surface nitrogen dioxide amounts were investigated. Results show that the natural removal of particulate matter is favoured by intense, continental winds. Contrariwise, when persistent thermal inversion occurs, pollutant dispersion is very limited and high concentrations are recorded by urban stations. Finally, in the case of Saharan dust outbreaks, an increase in the particulate content in both urban and rural stations is notable. Consequently, specific measurements aimed at improving air quality in urban environments should be planned according to synoptic weather and aerosol forecasts. This keeps valid in specific conditions of long-range transport of desert dust particles when the natural contribution could exceed that of pollutants from anthropogenic emissions.

Air quality in urban areas: Comparing objective and subjective indicators in European countries

Urban areas are major consumers of environmental resources and thus often place unsustainable demands on natural resources. As half of the world’s population (55%) lives in urban areas, the environmental degradation produced by cities threatens the health and quality of life of a fair share of the world’s population. For these reasons, progress towards sustainable urban development must be monitored and measured through suitable indicators. With reference to the assessment of air quality as a specific dimension of environmental quality in urban areas, existing studies have introduced various methodologies that mostly focus on objective measures (typically, exposure to outdoor air pollutants) while neglecting measures based on individual perceptions. Our goal is to contribute to filling this gap. To this end, we explore the relationship between objective and subjective measures of urban air quality in European countries. While the objective indicator is based on concentrations of PM2.5, our subjective indicator is reconstructed from individual perceptions collected through the European Union Statistics on Income and Living Conditions (EU-SILC) sample survey. Finally, through a cluster analysis, we classify the countries into homogeneous groups based on the values of these indicators. Our analysis reveals several differences in the country rankings according to the two indicators. For one group of countries, both approaches converge, thus leading to more definitive conclusions. For other countries, the mismatch between the two indicators suggests that either approach alone is not able to capture the full picture on air quality in urban environments.

The Effect of the Covid-19 Lockdown on Air Quality in Three Italian Medium-Sized Cities

Despite the societal and economic impacts of the COVID-19 pandemic, the lockdown measures put in place by the Italian government provided an unprecedented opportunity to increase our knowledge of the effect transportation and industry-related emissions have on the air quality in our cities. This study assessed the effect of reduced emissions during the lockdown period, due to COVID-19, on air quality in three Italian cities, Florence, Pisa, and Lucca. For this study, we compared the concentration of particulate matter PM10, PM2.5, NO2, and O3 measured during the lockdown period, with values obtained in the same period of 2019. Our results show no evidence of a direct relationship between the lockdown measures implemented and PM reduction in urban centers, except in areas with heavy traffic. Consistent with recently published studies, we did, however, observe a significant decrease in NO2 concentrations among all the air-monitoring stations for each city in this study. Finally, O3 levels remained unchanged during the lockdown period. Of note, there were slight variations in the meteorological conditions for the same periods of different years. Our results suggest a need for further studies on the impact of vehicular traffic and industrial activities on PM air pollution, including adopting holistic source-control measures for improved air quality in urban environments.

Assessment of particulate matter levels and sources in a street canyon at Loures, Portugal – A case study of the REMEDIO project

Air quality in urban environments is directly related to structural aspects of streets and traffic variables, justifying the need for local assessments. This information is crucial as input to obtain accurate and reliable statistical modelling of the implementation of different mitigation scenarios aiming to improve the local air quality management. The present study intended to assess temporal trends of particulate matter levels in a street canyon of the urban area of Moscavide (Loures, Portugal) for one-month in autumn of 2016. Moreover, fine and coarse particles were characterised for their carbonaceous and elemental contents in order to identify the main pollution sources affecting the study area.Particle concentration peaks were observed during daytime and were associated with traffic intensity due to commuting. During the studied period, no exceedances of the limit values set by the European legislation were registered. The natural sources sea salt and mineral dust contributed, on average, to 6 and 8% of PM10 levels. The Fe/Cu ratios indicated the contribution of wear emissions from road traffic. Enrichment of anthropogenic elements in PM was found and several traffic markers were identified from specific correlations between elements (good: Cu–Mn, Cu–Pb; moderate: Cu–Zn, Mn–Zn, Pb–Zn), highlighting the contribution of local traffic to PM levels.This information is valuable to understand possible health effects of particulate matter levels on citizens due to their exposure and to establish a reference scenario with which the future implementation of mitigation measures targeting local traffic can be compared to assess improvements in air quality in the studied street canyon.

A transition of atmospheric emissions of particles and gases from on-road heavy-duty trucks

Abstract. The transition, in extent and characteristics, of atmospheric emissions caused by the modernization of the heavy-duty on-road fleet was studied utilizing roadside measurements. Emissions of particle number (PN), particle mass (PM), black carbon (BC), nitrogen oxides (NOx), carbon monoxide (CO), hydrocarbon (HC), particle size distributions, and particle volatility were measured from 556 individual heavy-duty trucks (HDTs). Substantial reductions in PM, BC, NOx, CO, and to a lesser extent PN were observed from Euro III to Euro VI HDTs by 99 %, 98 %, 93 %, and 57 % for the average emission factors of PM, BC, NOx, and CO, respectively. Despite significant total reductions in NOx emissions, the fraction of NO2 in the NOx emissions increased continuously from Euro IV to Euro VI HDTs. Larger data scattering was evident for PN emissions in comparison to solid particle number (SPN) for Euro VI HDTs, indicating a highly variable fraction of volatile particle components. Particle size distributions of Euro III to enhanced environmentally friendly vehicle (EEV) HDTs were bimodal, whereas those of Euro VI HDTs were nucleation mode dominated. High emitters disproportionately contributed to a large fraction of the total emissions with the highest-emitting 10 % of HDTs in each pollutant category being responsible for 65 % of total PM, 70 % of total PN, and 44 % of total NOx emissions. Euro VI HDTs, which accounted for 53 % of total kilometres driven by Swedish HDTs, were estimated to only contribute to 2 %, 6 %, 12 %, and 47 % of PM, BC, NOx, and PN emissions, respectively. A shift to a fleet dominated by Euro VI HDTs would promote a transition of atmospheric emissions towards low PM, BC, NOx, and CO levels. Nonetheless, reducing PN, SPN, and NO2 emissions from Euro VI HDTs is still important to improve air quality in urban environments.

A Secure and Portable Multi-Sensor Module for Distributed Air Pollution Monitoring.

Air quality in urban environments has become a central issue of our present society as it affects the health and lives of the population all over the world. The first step in mitigating negative effects is proper measurement of the pollution level. This work presents a portable air pollution measurement system, built from off-the-shelf devices, that is designed to assure user privacy and data authenticity. Data is collected from sensor modules that can be hand carried or installed on vehicles, possibly leading to a vehicular sensor network that may cover a larger area. The main challenge is to provide authenticity for the sensor data while also ensuring user privacy. The proposed system assures authenticity and non-repudiation for the collected data by using group signatures and a blockchain-like structure for secure storage. We use regular key-exchange protocols based on elliptic curve cryptography in order to securely bootstrap a session key, then we benefit from secure tunneling to export data from sensors to the remote server. Post-update tampering is prevented by the use of a blockchain-like structure on the data server. We carry experiments both to determine the computational requirements of the procedures, as well as to measure indicators of air quality on nearby areas.

Car Wake Flows and Ultrafine Particle Dispersion: From Experiments to Modelling

Improving air quality in urban environments and transportation systems is crucial. Concerns are related to health and environmental issues associated with huge costs. Car cabin is a microenvironment where pollutants can accumulate with possible risks for occupants. In automotive engineering, it has then become mandatory to study the path and dispersion of such pollutants emitted from the tailpipe of a car. In the present paper, the relation between the flow topology and the dispersion of ultrafine particles (UFP) in the wake of a vehicle is discussed. Experiments were undertaken at a reduced scale using simplified car models. Experimental conditions were defined to be representative of a vehicle in an urban environment. Based on experimental data, a simplified analytical model is developed, which aims at describing the concentration fields of UFP in the wake of a single vehicle for different rear slant angles. The strengths and limits of the present model are discussed and ways of improvements are suggested. Additional experiments are presented to assess the influence of the inter-vehicle distance on this recirculation region. Critical inter-vehicle distances were determined based on defined criteria for different rear slant angles of the leading vehicle and compared to safety clearances.