Urban Background Concentrations Research Articles

Impact of vehicles at the roadside of expressway in urban area: Simultaneous measurement of particle size distribution and positive matrix factorization

This study conducted real-time monitoring of size-resolved particle concentrations ranging from 9 nm to 10 μm simultaneously at four sites on the park ground and the roof of a five-story apartment buildings in the upwind and downwind areas of the Olympic Expressway next to apartment complex areas of Seoul, Korea. Using a positive matrix factorization model for source apportionment, eight factors were resolved at each monitoring site: four exhaust emissions of vehicles, one non-exhaust emission of vehicle, two regional sources, and one unknown source. After categorizing monitoring data into three cases by wind conditions, impact and contribution of each vehicle-related source on the local road to the roadside pollution was quantified and characterized by subtracting the urban background concentrations. Throughout the measurement period, the contribution of vehicle-related sources to the particle number concentration at each monitoring site ranged from 61 % to 69 %, while that to the particle mass concentration ranged from 39 % to 87 %. During periods of steady traffic flow and wind blowing from the road to three downwind sites at speeds exceeding >0.5 m/s during working hours, the particle number concentrations at the downwind sites were 2.2–2.5 times higher than the average levels. Among vehicle-related sources, gasoline vehicles with multiple injections or high-emitting diesel vehicles showed the highest contribution to particle number concentrations at all sites. As wind speed increased, the number concentrations of particles from vehicle exhaust and non-exhaust emissions decreased and increased, respectively, probably due to enhanced dilution and transport, respectively. In addition, particle number concentrations showed a parabolic curve-like trend with traffic volumes increasing to approximately 10,000 vehicles/h, and then decreasing for both vehicle exhaust and non-exhaust emissions. These results can be utilized in numerical modeling studies and in establishing traffic-related environmental policies to reduce seasonal and temporal particle exposure near the roadsides.

What can we learn from nested IoT low‐cost sensor networks for air quality? A case study of PM2.5 in Birmingham, UK

AbstractLow‐cost sensing and the Internet of Things (IoT), present new possibilities for unconventional monitoring of environmental parameters. This paper describes a series of intersecting networks of particulate matter sensors that were deployed across the Birmingham conurbation for a 12‐month period. The networks consisted of a combination of commercially available sensors and University developed sensors. Data from these networks were assimilated with data from a third‐party Zephyr deployment, along with the DEFRA AURN network, which was hosted on an open‐source online platform. This nesting of sensor networks allowed for new insights into sensor performance, including the accuracy of a large network to detect regional concentrations and the number of sensors needed for effective monitoring beyond indicative measurements. After comprehensive data validation steps, the sensors were shown to perform well during co‐location with reference instrumentation (exhibiting slopes of 0.74–1.3). The sensors demonstrated good capability of detecting temporal patterns of regional PM2.5 with the mean of the entire sensor network recording an annual mean PM2.5 concentration within 0.2 μgm−3 of the regulatory network annual mean observation. Network‐derived statistics for estimating urban background concentrations compared to a reference site increase in‐line with the number of sensors available, however when assessing this for near‐source concentrations the importance of sensor location rather than the number of sensors is highlighted. Overall, the network provided novel insights into local concentrations, detecting similar hotspots to those identified by a high‐resolution model. The increased spatial coverage afforded by the sensor network has the potential to support higher resolution evaluation of models and provide unprecedented spatial evidence for air pollution management interventions.

Calibrating low-cost sensors to measure vertical and horizontal gradients of NO2 and O3 pollution in three street canyons in Berlin

Despite improvements in air quality over the last several decades, air pollution will continue to be a leading cause of harmful health effects in European cities as urban populations continue to grow. In recent years, the technology of low-cost sensors (LCS) has been adapted for use in expanding air pollution measurements at higher spatial resolution in cities across the globe. In a novel application, this exploratory study deploys metal oxide (MOS) and electrochemical (EC) low-cost sensors housed in EarthSense Zephyr sensor systems to measure nitrogen dioxide (NO2) and ozone (O3) concentrations in three street canyons in Berlin in winter, spring, and summer from 2017 to 2020. After calibration with reference instrumentation using the seven-step methodology outlined by Schmitz et al. (2021), we compare the measured concentrations with reference and urban background concentrations and investigate relationships with meteorology. We find that, following proper calibration, LCS capture expected patterns of urban pollution in association with diurnal chemistry and meteorology well. Additionally, EC sensors outperform MOS and allow for greater insights into local patterns of pollution. Furthermore, we measure concentrations of NO2 and O3 in street canyons that match expectations from modelling studies, indicating that high spatial resolution deployment of LCS could successfully yield new insights in urban microenvironments and inform model development. While LCS have a wider range of uncertainty than reference instruments, these results suggest that they can be reliably used for several new applications, such as validating urban street canyon models or measuring air pollution alongside changes to urban infrastructure.

Assessing the Spatial Distribution of NO2 and Influencing Factors in Urban Areas—Passive Sampling in a Citizen Science Project in Berlin, Germany

Nitrogen dioxide (NO2) is a major air pollutant with diverse impacts on human health and the environment. In urban areas, road traffic is the main emission source for NO2. In Berlin, Germany, a network of measurement stations is operated by the state, fulfilling the monitoring requirements set by the European Union. To get a more detailed overview of the spatial distribution of NO2 concentrations in Berlin, a citizen science project allowed for collection of additional data and an increase in the number of sampling sites. Passive samplers (modified Palmes tubes) were distributed to participants to collect NO2 at a site of their choice. When returned, the samplers were analyzed based on the Griess–Ilosvay reaction and spectrophotometric detection. The results confirmed a seasonal trend of higher NO2 concentrations in winter and lower concentrations during the summer period. Furthermore, the spatially and monthly averaged NO2 concentrations observed in the study period from March 2019 to October 2020 were in good agreement with the average urban background concentration. At small spatial scales, a tendency of decreasing NO2 concentrations with increasing distance from roads was observed. Overall, this study shows the added benefit of extensive low-cost measurements of NO2 concentrations across urban environments in a citizen science project to complement stationary air pollution monitoring networks.

Background concentration of atmospheric PM2.5 in the Beijing–Tianjin–Hebei urban agglomeration: Levels, variation trends, and influences of meteorology and emission

The determination of background PM2.5 and the separation of the meteorology-related and emission-related influences on background concentration in urban areas are important to evaluate the effectiveness of local anthropogenic emission control measures. In this study, the baseline separation technique was used to estimate the urban background concentration of PM2.5 in the Beijing–Tianjin–Hebei Urban agglomeration (JJJUA) by comparing its results with the background level monitored at the Shangdianzi regional background site. The Kolmogorov–Zurbenko (KZ) filter and stepwise regression model were further used to isolate the impacts of meteorology and emission on background levels. The results showed that the annual average background levels of PM2.5 in JJJUA were 27.18, 24.77, and 22.20 μg/m3 in 2018, 2019, and 2020, respectively. The background concentration showed significant differences in the seasonal and spatial distributions, with the highest levels obtained during winter in the southern inland plains. Boundary layer height, surface net solar radiation, total precipitation, temperature, and wind direction were negatively correlated with the background level, whereas surface pressure was positively correlated with the background level. A significant contribution of anthropogenic emissions (89%, −5.71 μg/m3•yr) on the decrease in trend of long-term background concentration was observed in JJJUA, indicating the strong influence of long-range transport of PM2.5 from surrounding areas. The results emphasize the strong influence of regional air pollution levels on background PM2.5, and coordinated control of regional air pollution is suggested to potentially reduce the regional background level of PM2.5.

Children’s exposure to BC and PM pollution, and respiratory tract deposits during commuting trips to school

Although children have been identified as a vulnerable group highly susceptible to traffic-related air pollution, their exposure during school commutes to traffic-related pollutants and the relevant health impact is rarely studied. In this study, we measured black carbon (BC) and particulate matter (PM: PM1, PM2.5, and PM10) concentrations that children are exposed to during their multi-modal (walking, private cars, and e-bikes) commuting trips to schools in Xi'an, China. A multi-parameter inhalation rate assessment model was developed in combination with the Multi-Path Particle Dosimetry (MPPD) model to quantify the deposition dose in different parts of children’s respiratory system (head, tracheobronchial (TB), pulmonary (PUL)). Results show that walking to school exposed children to the lowest PM1, PM2.5, and BC concentrations, whereas riding an e-bike led to significantly elevated exposure to PM1 and BC than the other two modes. This is due to children’s closer proximity to vehicle tail pipe emissions when they bike to school on road or roadside. The PM and BC concentrations showed remarkable increases in comparison to background concentrations during children’s school commutes. Urban background (UB) concentration, traffic volume (TV), time of day, and meteorological parameters could influence a child’s personal exposure, and the impact of each factor vary across different transportation modes. Particle size of the pollutant affects its deposition site in the respiratory system. Deposition fractions (DFs) and deposition doses in the head region (DF > 50%) were the highest for PM and BC, for which fine particles (BC, PM1, and PM2.5) were then most easily deposited in the PUL region while coarse particles rarely reach PUL. Children inhaled higher doses of polluted air during active commuting (walking) than passive commuting (private cars, e-bikes), due to longer times of exposure coupled with more active breathing.

City Scale Modeling of Ultrafine Particles in Urban Areas with Special Focus on Passenger Ferryboat Emission Impact.

Air pollution by aerosol particles is mainly monitored as mass concentrations of particulate matter, such as PM10 and PM2.5. However, mass-based measurements are hardly representative for ultrafine particles (UFP), which can only be monitored adequately by particle number (PN) concentrations and are considered particularly harmful to human health. This study examines the dispersion of UFP in Hamburg city center and, in particular, the impact of passenger ferryboats by modeling PN concentrations and compares concentrations to measured values. To this end, emissions inventories and emission size spectra for different emission sectors influencing concentrations in the city center were created, explicitly considering passenger ferryboat traffic as an additional emission source. The city-scale chemical transport model EPISODE-CityChem is applied for the first time to simulate PN concentrations and additionally, observations of total particle number counts are taken at four different sampling sites in the city. Modeled UFP concentrations are in the range of 1.5–3 × 104 cm−3 at ferryboat piers and at the road traffic locations with particle sizes predominantly below 50 nm. Urban background concentrations are at 0.4–1.2 × 104 cm−3 with a predominant particle size in the range 50–100 nm. Ferryboat traffic is a significant source of emissions near the shore along the regular ferry routes. Modeled concentrations show slight differences to measured data, but the model is capable of reproducing the observed spatial variation of UFP concentrations. UFP show strong variations in both space and time, with day-to-day variations mainly controlled by differences in air temperature, wind speed and wind direction. Further model simulations should focus on longer periods of time to better understand the influence of meteorological conditions on UFP dynamics.

Black carbon modeling in urban areas: investigating the influence of resuspension and non-exhaust emissions in streets using the Street-in-Grid model for inert particles (SinG-inert)

Abstract. Black carbon (BC) is a primary and inert pollutant often used as a traffic tracer. Even though its concentrations are generally low at the regional scale, BC presents very high concentrations in streets (at the local scale), potentially with important effects on human health and the environment. Modeling studies of BC concentrations usually underestimate BC concentrations due to uncertainties in both emissions and modeling. Both exhaust and non-exhaust traffic emissions present uncertainties, but the uncertainties with respect to non-exhaust emissions, such as tire, brake, and road wear as well as particle resuspension, are particularly high. In terms of modeling, street models do not always consider the two-way interactions between the local and regional scales. Using a two-way modeling approach, a street with high BC concentrations may influence urban background concentrations above the street, which can subsequently enhance the BC concentrations in the same street. This study uses the multiscale Street-in-Grid model (SinG) to simulate BC concentrations in a suburban street network in Paris, taking the two-way coupling between local and regional scales into account. The BC concentrations in streets proved to have an important influence on urban background concentrations. The two-way dynamic coupling leads to an increase in BC concentrations in large streets with high traffic emissions (with a maximal increase of about 48 %) as well as a decrease in narrow streets with low traffic emissions and low BC concentrations (with a maximal decrease of about 50 %). A new approach to estimate particle resuspension in streets is implemented, strictly respecting the mass balance on the street surface. The resuspension rate is calculated from the available deposited mass on the street surface, which is estimated based on particle deposition and wash-off parameterizations adapted to street-canyon geometries. The simulations show that particle resuspension presents a low contribution to BC concentrations, as the deposited mass is not significant enough to justify high resuspension rates. Non-exhaust emissions, such as brake, tire, and road wear, may largely contribute to BC emissions, with a contribution that is equivalent to exhaust emissions. Here, a sensitivity analysis of BC concentrations is performed by comparing simulations with different emission factors of tire, brake, and road wear. The different emission factors considered are estimated based on the literature. We found a satisfying model–measurement comparison using high tire wear emission factors, which may indicate that the tire emission factors usually used in Europe are probably underestimated. These results have important policy implications: public policies replacing internal combustion engines with electric vehicles may not eliminate BC air pollution but only reduce it by half.

An integrated assessment of the impacts of PM2.5 and black carbon particles on the air quality of a large Brazilian city

Data on airborne fine particle (PM2.5) emissions and concentrations in cities are valuable for traffic and air quality managers, urban planners, health practitioners, researchers, and ultimately for legislators and decision makers. Emissions and ambient concentrations of PM2.5 and black carbon (BC) were assessed in the city of Curitiba, southern Brazil. The methodology combined a month-long monitoring campaign with both fixed and mobile instruments, development of emission inventories, and dispersion model simulations on different scales. The mean urban background PM2.5 concentrations during the campaign were 7.3 μg m−3 in Curitiba city center, but three- to fourfold higher (25.3 μg m-3) in a residential area on the city’s outskirts, indicating the presence of local sources, possibly linked to biomass combustion. BC concentrations seemed to be more uniformly distributed over the city, with mean urban background concentrations around 2 μg m−3, half of which due to local traffic emissions. Higher mean BC concentrations (3–5 μg m-3) were found along busy roads. The dispersion modeling also showed high PM2.5 and BC concentrations along the heavily transited ring road. However, the lack of in situ data over these peripheral areas prevented the verification of the model output. The vehicular emission factors for PM2.5 and BC from the literature were found not to be suitable for Curitiba’s fleet and needed to be adjusted. The integrated approach of this study can be implemented in other cities, as long as an open data policy and a close cooperation among regional, municipal authorities and academia can be achieved.

A comparison of long-term trends in observations and emission inventories of NO<sub><i>x</i></sub>

Abstract. Air pollution is a pressing issue that is associated with adverse effects on human health, ecosystems, and climate. Despite many years of effort to improve air quality, nitrogen dioxide (NO2) limit values are still regularly exceeded in Europe, particularly in cities and along streets. This study explores how concentrations of nitrogen oxides (NOx = NO + NO2) in European urban areas have changed over the last decades and how this relates to changes in emissions. To do so, the incremental approach was used, comparing urban increments (i.e. urban background minus rural concentrations) to total emissions, and roadside increments (i.e. urban roadside concentrations minus urban background concentrations) to traffic emissions. In total, nine European cities were assessed. The study revealed that potentially confounding factors like the impact of urban pollution at rural monitoring sites through atmospheric transport are generally negligible for NOx. The approach proves therefore particularly useful for this pollutant. The estimated urban increments all showed downward trends, and for the majority of the cities the trends aligned well with the total emissions. However, it was found that factors like a very densely populated surrounding or local emission sources in the rural area such as shipping traffic on inland waterways restrict the application of the approach for some cities. The roadside increments showed an overall very diverse picture in their absolute values and trends and also in their relation to traffic emissions. This variability and the discrepancies between roadside increments and emissions could be attributed to a combination of local influencing factors at the street level and different aspects introducing inaccuracies to the trends of the emission inventories used, including deficient emission factors. Applying the incremental approach was evaluated as useful for long-term pan-European studies, but at the same time it was found to be restricted to certain regions and cities due to data availability issues. The results also highlight that using emission inventories for the prediction of future health impacts and compliance with limit values needs to consider the distinct variability in the concentrations not only across but also within cities.

Evaluation of OSPM against air quality measurements in Brazil – the case study of Fortaleza, Ceará

ABSTRACT The contribution of vehicle emissions to air pollution is considered a large environmental and health problem in big Brazilian cities caused, among other factors, by slow renewal of the old vehicle fleet. Brazilian studies usually only consider traffic-related issues in transportation analysis, with minor assessments of emissions and close to non-existent assessment of air quality. On this background, this research aimed to calibrate and evaluate the Operational Street Pollution Model (OSPM®) to Brazilian conditions by implementing Brazilian emission factors. The urban background concentrations were modeled with the Urban Background Model (UBM) as part of the air quality system (THOR–AirPAS). In this case, we used meteorological data from a ground meteorological station outside Fortaleza processed by meteorological pre-processor and regional background concentrations from the Integrated Forecast System (IFS) as input to UBM. New air quality measurements were collected in busy streets of the city of Fortaleza during the year of 2017. The study collected samples of daily NO2 and PM10 concentrations to evaluate OSPM daily estimations. In addition, a transportation travel demand model (TRANUS) has been calibrated to the case study area with observed traffic data collected, in order to provide Annual Average Daily Traffic (AADT) as inputs to OSPM®. Two sets of emission factors were evaluated. Official Brazilian emission factors were applied to OSPM®, as well as adjusted emission factors derived in the project based on calibration that were higher than the official emission factors. Data showed that concentrations are significantly influenced by meteorological factors (such as temperature, wind speeds, wind directions), and especially precipitation for PM10 concentrations. OSPM® simulated results showed concentration levels and patterns close to air quality measurements with default emission factors and calibrated emission for UBM but large underestimations if official emissions were used for both UBM and OSPM. Implications: Busy urban streets in Brazilian cities with intense flow of diesel vehicles (such as buses and trucks) can significantly increase air pollution, especially for NO2 and PM10. With OSPM calibrated and evaluated to Brazilian conditions, the model system can be used by authorities to assess the impact of policy measures, such as vehicle access restrictions in Low Emission Zones, in order to consider not only traffic related issues, but also air pollution due to mobile sources with outdated emission technologies.

Engagement in outdoor physical activity under ambient fine particulate matter pollution: A risk-benefit analysis

BackgroundOutdoor physical activity (PA) brings important health benefits, but exposure to polluted air increases health risks. This study aimed to quantify the tradeoff of PA under fine particulate matter (PM2.5) air pollution by estimating the optimal PA duration under various pollution levels. MethodsA risk-benefit analysis was performed to estimate the optimal outdoor moderate-intensity PA (MPA) duration under varying PM2.5 concentrations. ResultsAn inverse nonlinear relationship was identified between optimal MPA duration and background PM2.5 concentration levels. When background PM2.5 concentration increased to 186 µg/m3, the optimal outdoor MPA duration decreased to 2.5 h/week, the minimum level recommended by current PA guidelines. When background PM2.5 concentration further increased to 235 µg/m3, the optimal outdoor MPA duration decreased to 1 h/week. The relationship between optimal MPA duration and background PM2.5 concentration levels was stronger when exercising at a location closer to a source of air pollution. Compared to the general adult population, adults aged 60 years and older had substantially steeper curves—the optimal outdoor MPA duration decreased to 2.5 h/week when background PM2.5 concentration reached 45 µg/m3. ConclusionThe health benefit of outdoor MPA by far outweighs the health risk of PM2.5 pollution for the global average urban background concentration (22 μg/m3). This modeling study examined a single type of air pollutant and suffered from measurement errors and estimation uncertainties. Future research should examine other air pollutants and indoor PA, incorporate short- and mid-term health effects of MPA and air pollution into the risk-benefit analysis, and provide estimates specific for high-risk subgroups.

Monitoring road traffic participants' exposure to PM10 using a low-cost system

The paper presents the application of a low-cost system for monitoring the current level of road traffic participants' exposure to PM10 air pollution. The research was carried out from the end of August 2017 to the beginning of October 2017 on the central section of one of the main roads in Bielsko-Biała, Poland. In the analysed period, significant changes in the daily distribution of road traffic both into and out of the city centre were observed. The average travel time depended on the direction of traffic, and the difference between directions being almost 50%. The PM10 urban background concentration was also subject to daily changes, and in the fifth week of observation, it reached a value more than twice as high as in the first week of observation. The maximum level of road traffic participants' exposure was observed at a relatively low urban background PM10 concentration. It was observed that a significant slowdown in traffic in conditions of acceptable urban air quality led to a comparable level of exposure to that of standard traffic conditions and poor urban air quality. It was also found that the slowdown in traffic increased the exposure time of traffic participants travelling towards the city centre by an average of 24% and, for those travelling in the opposite direction, by as much as 50%. In an extreme case of traffic delay, exposure to PM10 concentration in the vicinity of the road was two and a half times as long.

Ethylene Oxide Exposure Attribution and Emissions Quantification Based on Ambient Air Measurements near a Sterilization Facility.

Ethylene oxide (EtO) is a known carcinogen and mutagen associated with increased incidence of breast and blood cancers. The largest medical sterilization facility in Michigan had been assessed by the U.S. Environmental Protection Agency as imposing an additional cancer risk greater than one in one thousand in nearby neighborhoods. This prompted the Michigan Department of Environmental Quality (now referred to as the Department of Environment, Great Lakes, and Energy) to conduct an air quality modeling study of the ambient EtO impacts of the sterilization facility, followed by 24 h Summa canister sampling and TO-15 analysis in two phases. Inverse modeling of the measured 24 h EtO concentrations during the second phase yielded estimates of 594 lbs/year for the facility’s total emissions of EtO and 0.247 µg/m3 for the urban background concentration. The inverse-modeled emissions are similar to reported emissions by the facility operator based on indoor air measurements and simple mass balance assumptions, while the inferred background concentration agrees with estimates from other field investigations. The estimated peak 24 h exposure to EtO caused by the sterilization facility in nearby neighborhoods was 1.83 μg/m3 above the background level, corresponding to an additional cancer risk of approximately one in one hundred, if assumed to represent annual mean exposure.

The use of low-cost sensors for air quality analysis in road intersections

The paper discusses the results of air quality tests recorded by a low-cost system. It included PM concentration sensors and a system to estimate traffic conditions. The research was carried out from 8 October 2017 to 3 November 2017 at three intersections in city-centre Bielsko-Biała. Hourly atmospheric air quality variability and its relation to the recorded road traffic volume were analysed. The hourly PM1/PM10 and PM2.5/PM10 ratio averages showed a moderate correlation with the traffic volume estimator. The quantitative contribution of traffic to total PM2.5 pollution was estimated using the Kolmogorov-Zurbenko filter applied on 1-min average PM2.5 concentrations. On most of the days the estimated hourly average share of traffic-related emissions in PM2.5 pollution was identified as clearly correlated with the traffic volume. The calculated daily average contribution ranged from 6 to 27% on various days, and at a low urban background concentration it reached approximately 22%.

A Multi-Pollutant Air Quality Health Index (AQHI) Based on Short-Term Respiratory Effects in Stockholm

TPS 681: Short-term health effects of air pollutants 1, Exhibition Hall, Ground floor, August 26, 2019, 3:00 PM - 4:30 PM Background/Aim: In this study, an Air Quality Health Index (AQHI) is introduced to capture the health risks associated with multi-pollutant exposure. The index is intended for public information regarding the expected health risks associated with current or forecasted concentrations of pollutants and pollen. Methods: The AQHI is based on an epidemiological study of daily emergency department visits for asthma (AEDV) and urban background concentrations of NOx, O3, PM10 and birch pollen in Stockholm. The index is calculated as: AQHI = ∑(i=1…p) [100 (e^βiXi-1)] where the beta-coefficient (βi) represents the increase in AEDV per 1 µg m-3 increase of each individual air pollutant (Xi). For birch pollen it is the increase per one pollen per cubic meter. The beta-coefficients are based on all age groups, and the exposure window is lag01 (mean of same day and yesterday). Results: The epidemiological analysis showed per 10 µg m-3 increase an increase in AEDV of 0.5%, 0.3% and 2.5% for NOx, O3 and PM10, respectively. For birch pollen, the increase was 0.26% per 10 pollen m-3. The AQHI increase associated with NOx exhibits an even distribution throughout the year, except for a decrease during the summer due to less traffic. O3 contributes to an increase in AQHI during the spring. PM10 reaches a peak during early spring due to road dust suspension and pollen also peak during the late spring/early summer. Total monthly mean AQHI during 2015–2017 varied between 4 and 9%, with a peak value of 16%. Based on daily mean values, the most important risk contribution during the study period is from PM10 with 2.9%, followed by O3 with 2.0%. Conclusion: An AQHI based on asthma emergency department visits can provide the overall daily adverse risks of exposure to air pollutants and pollen especially for people suffering from respiratory diseases.

Modelling the impacts of EU countries\u2019 electric car deployment plans on atmospheric emissions and concentrations

The purpose of this work is to quantify key environmental impacts of electric vehicles deployment in the European Union. This is achieved by soft-linking three models (PRIMES-TREMOVE, DIONE and SHERPA) to explore a base and an alternative scenario. The alternative scenario draws on the assessment of the national policy frameworks for alternative fuels infrastructure requested by the Directive (2014/94/EU). Five environmental indicators are examined: tailpipe CO2, NOx and PM2.5 emissions as well as NO2 and PM2.5 urban background concentrations. By 2030, car travel activity is simulated to generate ca. 425 MtCO2/year in the EU28 under the alternative scenario. Compared to the base scenario, electric vehicles contribute to a 3% reduction in tailpipe CO2 emissions. Only two countries attain CO2 emission reductions greater than 10% in the model. The need for a higher level of policy ambition towards the deployment of less polluting vehicles in Europe is highlighted as a conclusion.

Vertical and horizontal fall-off of black carbon and NO2 within urban blocks

While exposure to traffic pollutants significantly decreases with distance from the curb, very dense urban architectures hamper such dispersion. Moreover, the building height reduces significantly the dispersion of pollutants. We have investigated the horizontal variability of Black Carbon (BC) and the vertical variability of NO2 and BC within the urban blocks. Increasing the distance from road BC concentrations decreased following an exponential curve reaching halving distances at 25 m (median), although with a wide variability among sites. Street canyons showed sharper fall-offs than open roads or roads next to a park. Urban background concentrations were achieved at 67 m distance on average, with higher distances found for more trafficked roads. Vertical fall-off of BC was less pronounced than the horizontal one since pollutants homogenize quickly vertically after rush traffic hours. Even shallower vertical fall-offs were found for NO2. For both pollutants, background concentrations were never reached within the building height. A street canyon effect was also found exacerbating concentrations at the lowest floors of the leeward side of the road. These inputs can be useful for assessing population exposure, air quality policies, urban planning and for models validation.

Exposure assessment of cyclists to UFP and PM on urban routes in Xi'an, China

With the promotion of bicycle sharing, cycling as an active transportation mode is a matter of public interest. However, cyclists' recurrent exposure to traffic-related air pollution is associated with the potential health risks. Quantification of the health risks associated with daily exposure of commuting cyclists to atmospheric pollutants is vital, but barely reported. In this study, real-time mobile measurement campaigns were performed with high time-resolution portable instruments, along two commuting routes in Xi'an, China. We investigated personal exposure and inhaled dose of particulate matter and ultrafine particle (UFP) for cyclists. The results showed cyclists' exposure to average pollutants concentrations: fine particulate matter (PM2.5, 38.6 ± 17.1 μg m−3) and UFP (18,172 ± 11,282 particles cm−3). The exposure “hotspots” of cyclists were identified: intersections, diesel engines, etc. Cyclists' exposure to the highest PM2.5 (46.9 μg m−3) concentrations were observed in morning periods; these were ∼36%/42% higher compared to the afternoon or evening, while the latter periods corresponded to higher UFP concentrations (18,342/18,502 particles cm−3). The measurements of PM2.5 and UFP were clearly higher during autumn months, when compared to summer months. In multivariate models, wind speed was not significant, temperature and local urban background concentrations explained 70.9% the variation of PM2.5, the 67.8% of UFP was explained by temperature, traffic and relative humidity, and each 100 increase in on-road vehicles were associated with increase of 1328 particles cm−3 for UFP exposure in cyclists. Cycling in bike boulevards decreased exposure concentrations by 31.5% for PM and 36.6% for UFP compared to traffic roadsides, moving vehicles were identified as key contributors to PM0.25-0.3 and PM2.0-10 of cyclists' exposure. The potential health risks deserve attention under the mobility and air pollution challenges faced by many metropolitan areas in emerging economies. Our findings could serve to promote better design for low-exposure network of separated bike boulevards.

Evaluating the impact of “Sustainable Urban Mobility Plans” on urban background air quality

Air quality in European cities is still a challenge, with various urban areas frequently exceeding the PM2.5 and NO2 concentration levels allowed by the European Union Air Quality Standards. This is a problem both in terms of legislation compliance, but also in terms of health of citizens, as it has been recently estimated that 400 to 450 thousand people die prematurely every year due to poor air quality. Air quality in cities can be improved with a number of interventions, at different sectoral (industry, traffic, residential, etc …) and geographical (international, European, national, local, etc.) levels. In this paper we explore the potential of city level plans to improve mobility and air quality (excluding electro-mobility options, not considered in this study). We applied the “Sustainable Urban Mobility Plans” (SUMPs) framework to 642 cities in Europe and modelled how the measures they include may impact at first on mobility and emissions at urban level, and then on urban background concentrations of PM2.5 and NO2. Results show that annual averages moderately improve for both pollutants, with reductions of urban background concentrations up to 2% for PM2.5 and close to 4% for NO2. The impact on NO2 at street level (that will be higher than on urban background) is not evaluated in this work. The air quality improvement of the simulated SUMP would only partially alleviate air quality problems in urban areas, but such a reduction in the emissions of air pollutants should still be considered as a positive result of SUMPs, given that they correspond to a set of low-cost measures that can be implemented at local level. Furthermore, the introduction of electro-mobility options (not considered here) would increase the impact on air quality. Other types of benefits, such as reduced fuel consumption, greenhouse gas emissions, higher impact at street level or accident rates reduction further add to the overall positive impact.