Influence of anthropogenic activities on metals, sugars and PAHs in PM10 in the city of Fez, Morocco: Implications on air quality

Particulate matter (PM) is an important component in the atmosphere, affecting air quality, health, radiation balance, and global climate. To assess regional air quality in the city of Fez, an intensive field campaign was carried out in the autumn of 2019 in the Middle Atlas region of Morocco. Aerosol sampling was performed simultaneously at two urban sites in the city of Fez: (1) Fez University (FU), a sub-urban site, and (2) Fez Parc (FP), an urban site located in the city center of Fez, using PM10 collectors. Various laboratory analyses were carried out, including PM mass, trace metals, inorganic ions, OC/EC, sugar compounds, and PAHs. The results indicate that the PM10 mass (61 ng m-3) was comparable at both sites, with a 37-107 ng m-3 range. Most of the 19 investigated PAHs at the FU site (10.2 ± 6.2 ng m-3) were low-molecular-weight PAHs, while the most abundant PAHs at the FP site (6.9 ± 3.8 ng m-3) were mainly higher-molecular-weight PAHs. A diagnostic ratio analysis at both sites indicated that PAHs originated from fossil fuel combustion and traffic emissions from diesel engines, with Ant/(Ant + Phe) and Flu/(Flu + Pyr) ratios averaging 0.22 and 0.84, respectively. PMF analysis identified traffic emissions as a major source (30%), with secondary inorganic aerosols (20%) and biomass burning (14%). Polar plots highlight the dominance of local anthropogenic activities in PM pollution, with vehicular emissions, industrial activities, and biomass burning. This study shows that local sources and combustion processes significantly contribute to PM10 sources in Morocco, providing insights into air pollution mitigation in North Africa.

Air pollution prediction and backcasting through a combination of mobile monitoring and historical on-road traffic emission inventories

An important challenge for studies of air pollution and health effects is the derivation of historical exposures. These generally entail some form of backcasting, which refers to a range of approaches that aim to project a current surface into the past. Accurate backcasting is conditional upon the availability of historical data for predictor variables and the ability to capture spatial and temporal trends in these variables. This study proposes a method to backcast traffic-related air pollution surfaces developed using land-use regression models by including temporal variability of traffic and emissions and trends in concentrations measured at reference stations. Nitrogen dioxide (NO2) concentrations collected in the City of Toronto using the Urban Scanner mobile platform were adjusted for historical trends captured at reference stations. The Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST), a powerful tool for time series decomposition, was employed to isolate seasonal variations, annual trends, and abrupt changes in NO2 at reference stations, hence decomposing the signal. Exposure surfaces were generated for a period extending from 2006 to 2020, exhibiting decreases ranging from 10 to 50 % depending on the neighborhood, with an average of 20.46 % across the city. Yearly surfaces were intersected with mobility patterns of Torontonians extracted from travel survey data for 2006 and 2016, illustrating strong spatial gradients in the evolution of NO2 over time, with larger decreases along major roads and highways and in the central core. These findings demonstrate that air pollution improvements throughout the 14 years are inhomogeneous across space.

A new portable open-path instrument for ambient NH3 and on-road emission measurements

Increased attentions to vehicle emission of NH3 have been paid since it is generally regarded as an important source in urban areas. Here, we developed a movable instrument based on Differential Optical Absorption Spectroscopy (DOAS) principle for detecting on-road NH3, which can avoid the losses in the sampling process attributed to the non-sampling methods. For this mobile DOAS, the temporal resolution, detection limit and relative error for NH3 were 1 min, 2.29 ppbv and 4.57% ± 2.44%, respectively. By employed to the on-road measurements along the arterial highway in Shanghai, the spatial distributions of NH3 and NO were obtained, and their dependence of traffic and road conditions were studied. The slopes of linear regression between NH3 and NO were 0.40, 0.02 and 0.07 on the Middle Ring Road, Outer Ring Road and Chongming Island Ring Road. It indicates that light gasoline vehicles (LGVs) were found to be the main contributor to NH3 emissions, while heavy-duty diesel vehicles (HDVs) mainly emitted NO. Based on the measured NH3 in the tunnel, the mileage-based NH3 emission factor per vehicle was estimated to be 17.9 ± 6.3 mg/km. The reported open-path instrument can be broadly used in on-road pollutant monitoring or vehicle emissions, and the measurements can reveal the real situation of emission characteristics, even find the abnormal operations of vehicle catalyst system.

Air pollution mortality benefits of sustained COVID-19 mobility restrictions in Australian cities

OBJECTIVES

Emissions from road traffic, power generation and industry were substantially reduced during pandemic lockdown periods globally. Thus, we analysed reductions in traffic-related air pollution in Australian capital cities during March-April 2020 and then modelled the mortality benefits that could be realised if similar reductions were sustained by structural policy interventions.

STUDY DESIGN

Satellite, air pollution monitor and land use observations were used to estimate ground-level nitrogen dioxide (NO2) concentrations in all Australian capital cities during: (a) a typical year with no prolonged air pollution events; (b) a hypothetical sustained reduction in NO2 equivalent to the COVID-19 lockdowns.

METHODS

We use the WHO recommended NO2 exposure-response coefficient for mortality (1.023, 95 % CI: 1.008-1.037, per 10 μg/m3 annual average) to assess gains in life expectancy and population-wide years of life from reduced exposure to traffic-related air pollution.

RESULTS

We attribute 1.1 % of deaths to anthropogenic NO2 exposures in Australian cities, corresponding to a total of 13,340 years of life lost annually. Although COVID-19-related reductions in NO2 varied widely between Australian cities during April 2020, equivalent and sustained reductions in NO2 emissions could reduce NO2-attributable deaths by 27 %, resulting in 3348 years of life gained annually.

CONCLUSIONS

COVID-19 mobility restrictions reduced NO2 emissions and population-wide exposures in Australian cities. When sustained to the same extent by policy interventions that reduce fossil fuel consumption by favouring the uptake of electric vehicles, active travel and public transport, the health, mortality and economic benefits will be measurable in Australian cities.

Emissions from modern engines induce distinct effects in human olfactory mucosa cells, depending on fuel and aftertreatment

Ultrafine particles (UFP) with a diameter of ≤0.1 μm, are contributors to ambient air pollution and derived mainly from traffic emissions, yet their health effects remain poorly characterized. The olfactory mucosa (OM) is located at the rooftop of the nasal cavity and directly exposed to both the environment and the brain. Mounting evidence suggests that pollutant particles affect the brain through the olfactory tract, however, the exact cellular mechanisms of how the OM responds to air pollutants remain poorly known. Here we show that the responses of primary human OM cells are altered upon exposure to UFPs and that different fuels and engines elicit different adverse effects. We used UFPs collected from exhausts of a heavy-duty-engine run with renewable diesel (A0) and fossil diesel (A20), and from a modern diesel vehicle run with renewable diesel (Euro6) and compared their health effects on the OM cells by assessing cellular processes on the functional and transcriptomic levels. Quantification revealed all samples as UFPs with the majority of particles being ≤0.1 μm by an aerodynamic diameter. Exposure to A0 and A20 induced substantial alterations in processes associated with inflammatory response, xenobiotic metabolism, olfactory signaling, and epithelial integrity. Euro6 caused only negligible changes, demonstrating the efficacy of aftertreatment devices. Furthermore, when compared to A20, A0 elicited less pronounced effects on OM cells, suggesting renewable diesel induces less adverse effects in OM cells. Prior studies and these results suggest that PAHs may disturb the inflammatory process and xenobiotic metabolism in the OM and that UFPs might mediate harmful effects on the brain through the olfactory route. This study provides important information on the adverse effects of UFPs in a human-based in vitro model, therefore providing new insight to form the basis for mitigation and preventive actions against the possible toxicological impairments caused by UFP exposure.

Ambient air particulate total lung deposited surface area (LDSA) levels in urban Europe

This study aims to picture the phenomenology of urban ambient total lung deposited surface area (LDSA) (including head/throat (HA), tracheobronchial (TB), and alveolar (ALV) regions) based on multiple path particle dosimetry (MPPD) model during 2017-2019 period collected from urban background (UB, n = 15), traffic (TR, n = 6), suburban background (SUB, n = 4), and regional background (RB, n = 1) monitoring sites in Europe (25) and USA (1). Briefly, the spatial-temporal distribution characteristics of the deposition of LDSA, including diel, weekly, and seasonal patterns, were analyzed. Then, the relationship between LDSA and other air quality metrics at each monitoring site was investigated. The result showed that the peak concentrations of LDSA at UB and TR sites are commonly observed in the morning (06:00-8:00 UTC) and late evening (19:00-22:00 UTC), coinciding with traffic rush hours, biomass burning, and atmospheric stagnation periods. The only LDSA night-time peaks are observed on weekends. Due to the variability of emission sources and meteorology, the seasonal variability of the LDSA concentration revealed significant differences (p = 0.01) between the four seasons at all monitoring sites. Meanwhile, the correlations of LDSA with other pollutant metrics suggested that Aitken and accumulation mode particles play a significant role in the total LDSA concentration. The results also indicated that the main proportion of total LDSA is attributed to the ALV fraction (50 %), followed by the TB (34 %) and HA (16 %). Overall, this study provides valuable information of LDSA as a predictor in epidemiological studies and for the first time presenting total LDSA in a variety of European urban environments.

Characterizing emission factors and oxidative potential of motorcycle emissions in a real-world tunnel environment

Transportation emissions significantly affect human health, air quality, and climate in urban areas. This study conducted experiments in an urban tunnel in Taipei, Taiwan, to characterize vehicle emissions under real driving conditions, providing emission factors of PM2.5, eBC, CO, and CO2. By applying multiple linear regression, it derives individual emission factors for heavy-duty vehicles (HDVs), light-duty vehicles (LDVs), and motorcycles (MCs). Additionally, the oxidative potential using dithiothreitol assay (OPDTT) was established to understand PM2.5 toxicity. Results showed HDVs dominated PM2.5 and eBC concentrations, while LDVs and MCs influenced CO and CO2 levels. The CO emission factor for transportation inside the tunnel was found to be higher than those in previous studies, likely owing to the increased fraction of MCs, which generally emit higher CO levels. Among the three vehicle types, HDVs exhibited the highest PM2.5 and eBC emission factors, while CO and CO2 levels were relatively higher for LDVs and MCs. The OPDTTm demonstrated that fresh traffic emissions were less toxic than aged aerosols, but higher OPDTTv indicated the impact on human health cannot be ignored. This study updates emission factors for various vehicle types, aiding in accurate assessment of transportation emissions' effects on air quality and human health, and providing a guideline for formulating mitigation strategies.

Health and economic benefits of heavy-duty diesel truck emission control policies in Beijing

PM2.5 emissions from heavy-duty diesel trucks (HDDTs) have a significant impact on air quality, human health, and climate change, and seriously threaten the UN Sustainable Development Goals. Globally, a series of emission control measures have been implemented to reduce pollution emissions from HDDTs. Current studies assessing the impact of these measures on air quality and human health have mainly used coarse-grained emission data as input to dispersion model, resulting in the inability to capture the spatiotemporal variability of pollutant concentrations and tending to increase the uncertainty of health impact assessment results. In this study, we quantified the impact of pollution control policies for HDDTs in Beijing on PM2.5 concentrations, human health, and economic losses by integrating policy scenario analysis, pollution dispersion simulation, public health impact and economic benefit assessment models, supported by high spatiotemporal resolution emission data from HDDTs. The results show that PM2.5 concentrations from HDDTs exhibit significant spatial aggregation characteristics, with the intensity of aggregation at night being about twice as high as that during the day. The emission hotspots are mainly concentrated in the sixth, fifth and fourth rings and major highways. Compared to the "business as usual" scenario in 2018, the current policy of updating the fuel standard to China VI and the emission standard to China 6 can reduce PM2.5 concentrations by 96.72%, thereby avoiding 612 premature deaths, which is equivalent to obtaining economic benefits of 1.65 billion CNY. This study further emphasizes the importance of high spatiotemporal resolution emission data during traffic dispersion modeling. The results can help improve the understanding of the effectiveness of emission reduction measures for HDDTs from a health benefit perspective.

Emissions of multiple metals from vehicular brake linings wear in China, 1980-2020

Metals emitted from brake linings wear have adverse effects on air quality and human health due to their toxicity and reactivity. However, complexities of factors affecting brake like conditions of vehicles and roads hinder the accurate quantification. Here, we established a comprehensive emission inventory for multi-metals from brake linings wear in China during 1980-2020, based on metals contents in well-representative samples, the wear of brake linings before replacement, vehicle populations, fleet composition, and vehicle-kilometers travelled (VKT). We show that with the boom of vehicle population, the total emissions of studied metals have surged from 3.7 × 10⁶ g in 1980 to 4.9 × 10¹⁰ g in 2020, which mainly concentrated in coastal and eastern urban areas while grown significantly in the central and western urban areas in recent years. Therein, Ca, Fe, Mg, Al, Cu, and Ba were the top six metals emitted, together responsible for >94 % of the mass total. Jointly determined by brake linings especially metals contents thereof, VKTs, and vehicle populations, heavy-duty trucks, light-duty passenger vehicles, and heavy-duty passenger vehicles were the top three contributors in metals emissions, together accounting about 90 % of the total. Moreover, more precise description on real-world metals emissions from brake linings wear are still urgently needed, considering the increasingly significant role it has been playing on worsening air quality and public health.

Deciphering urban traffic impacts on air quality by deep learning and emission inventory

Air pollution is a major obstacle to future sustainability, and traffic pollution has become a large drag on the sustainable developments of future metropolises. Here, combined with the large volume of real-time monitoring data, we propose a deep learning model, iDeepAir, to predict surface-level PM_2.5 concentration in Shanghai megacity and link with MEIC emission inventory creatively to decipher urban traffic impacts on air quality. Our model exhibits high-fidelity in reproducing pollutant concentrations and reduces the MAE from 25.355 µg/m³ to 12.283 µg/m³ compared with other models. And identifies the ranking of major factors, local meteorological conditions have become a nonnegligible factor. Layer-wise relevance propagation (LRP) is used here to enhance the interpretability of the model and we visualize and analyze the reasons for the different correlation between traffic density and PM_2.5 concentration in various regions of Shanghai. Meanwhile, As the strict and effective industrial emission reduction measurements implementing in China, the contribution of urban traffic to PM_2.5 formation calculated by combining MEIC emission inventory and LRP is gradually increasing from 18.03% in 2011 to 24.37% in 2017 in Shanghai, and the impact of traffic emissions would be ever-prominent in 2030 according to our prediction. We also infer that the promotion of vehicular electrification would achieve further alleviation of PM_2.5 about 8.45% by 2030 gradually. These insights are of great significance to provide the decision-making basis for accurate and high-efficient traffic management and urban pollution control, and eventually benefit people's lives and high-quality sustainable developments of cities.

Long-term residential exposure to source-specific particulate matter and incidence of diabetes mellitus - A cohort study in northern Sweden

Diabetes mellitus (DM) incidence have been assessed in connection with air pollution exposure in several studies; however, few have investigated associations with source-specific local emissions. This study aims to estimate the risk of DM incidence associated with source-specific air pollution in a Swedish cohort with relatively low exposure. Individuals in the Västerbotten intervention programme cohort were followed until either a DM diagnosis or initiation of treatment with glucose-lowering medication occurred. Dispersion models with high spatial resolution were used to estimate annual mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10 μm (PM₁₀) and ≤2.5 μm (PM_2.5) at individual addresses. Hazard ratios were estimated using Cox regression models in relation to moving averages 1-5 years preceding the outcome. During the study period, 1479 incident cases of DM were observed during 261,703 person-years of follow-up. Increased incidence of DM was observed in association with PM₁₀ (4% [95% CI: -54-137%] per 10 μg/m³), PM₁₀-traffic (2% [95% CI: -6-11%] per 1 μg/m³) and PM_2.5-exhaust (11% [95% CI: -39-103%] per 1 μg/m³). A negative association was found for both PM_2.5 (-18% [95% CI: -99-66%] per 5 μg/m³), but only in the 2nd exposure tertile (-10% [95% CI: -25-9%] compared to the first tertile), and PM_2.5-woodburning (-30% [95% CI: -49-4%] per 1 μg/m³). In two-pollutant models including PM_2.5-woodburning, there was an 11% [95% CI: -11-38%], 6% [95% CI: -16-34%], 13% [95% CI: -7-36%] and 17% [95% CI: 4-41%] higher risk in the 3rd tertile of PM₁₀, PM_2.5, PM₁₀-traffic and PM_2.5-exhaust, respectively, compared to the 1st. Although the results lacked in precision they are generally in line with the current evidence detailing particulate matter air pollution from traffic as an environmental risk factor for DM.

Multiscale spatiotemporal variations of NOx emissions from heavy duty diesel trucks in the Beijing-Tianjin-Hebei region

Heavy-duty diesel trucks (HDDTs) cause serious pollution to urban and regional environment. Understanding the spatiotemporal pattern of pollution emissions and its impact factors is the basis for implementing emission reduction measures. However, since the multiscale emission inventory of HDDTs is not currently established, multiscale analysis of these issues is still lacking. Therefore, this study uses massive trajectory data, detailed vehicle specification information and road network information, combined with localized emission factors, to construct a multiscale NOx emission inventory of HDDTs with high spatiotemporal resolution in the Beijing-Tianjin-Hebei region. Then the multiscale spatiotemporal variations of NOx emissions are analyzed by using spatial statistical indicators and multiscale geographical weighted regression model. The results show that the NOx emissions of HDDTs show different spatiotemporal distribution and aggregation characteristics at different scales. Specifically, link-scale emissions are concentrated to a few highways and are dominated by Low-Low cluster. While county-scale and city-scale emissions are concentrated in the eastern plains, mainly in High-High and Low-Low clusters. There are spatial heterogeneity and multiscale effects of socioeconomic and road attribute characteristics on the NOx emissions from HDDTs. Population density, urbanization rate, proportion of second industry, and proportion of highway affect the NOx emissions of HDDTs globally, while per capita GDP and road density have local effects. Our results extend the scientific understanding of the multiscale spatiotemporal variations of HDDTs and may provide a scientific basis for the development of targeted emission control measures for HDDTs.

The comparison between in-situ monitored data and modelled results of nitrogen dioxide (NO2): case-study, road networks of Kigali city, Rwanda

The incomplete combustion of fossil fuels from petrol, natural gas, and fuel oil in the engine of vehicles contributes to air quality degradation through traffic-related air pollutant emissions. The Real-time affordable multi-pollutant (RAMPs) monitors were installed in Kigali, the capital of Rwanda, to fill the gap in air quality datasets. Using RAMPs, this is the first air quality modelling research in Rwanda aiming to report the concentration of NO₂ by comparing In-situ monitored data and modelled results. We targeted NO₂ emissions from 27 road networks of Kigali to address the impacts of traffic emissions on air quality over 2021. The American Meteorological Society and Environmental Protection Agency regulatory models (AERMOD and ISCST3) were used for simulation. Statistical indexes include fractional bias (FB), the fraction of the prediction within the factor of two of the observations (FAC2), normalized mean square error (NMSE), geometric mean bias (MG), and geometric variance (VG) used to assess models' reliability. Monitoring shows the annual mean of 16.07 μg/m³, 20.35 μg/m³, and 15.46 μg/m³ at Mont-Kigali, Gacuriro, and Gikondo-Mburabuturo stations, respectively. Modelling shows the daily mean of 111.77 μg/m³ and annually mean of 50.42 μg/m³ with AERMOD and daily mean of 200.26 μg/m³ and annually mean of 72.26 μg/m³ with ISCST3. The FB, NMSE, and FAC2 showed good agreement, while MG and VG showed moderate agreement with AERMOD. The FB, NMSE, and MG showed moderate agreement, while FAC2 and VG disagreed with ISCST3. Traffic and urban residential emissions were identified as potential sources of NO₂. Results indicated that Kigali residents are exposed to a significant level of NO₂ exceeding World Health Organisation limits. Findings will help track the effectiveness of Rwanda's recently executed pollution-control policy, suggest evidence based on the recommendations to reduce NO₂, and use further dispersion models to support ground-based observations to improve public health.

Use of historical mapping to understand sources of soil-lead contamination: Case study of Santa Ana, CA

This paper investigates the historical sources of soil-lead contamination in Santa Ana, California. Even though dangerous levels of soil-lead have been found in a wide variety of communities across the United States, public health institutions lack clarity on the historical origins of these crises. This study uses geo-spatial data collected through archival research to estimate the impact of two potential sources of lead contamination in the past -- lead-paint and leaded gasoline. It examines, through a combination of statistical and historical methods, the association between lead concentrations in contemporary soil samples and patterns in the evolution of the city's physical features, such as the growth of urbanized areas and the historical flow of traffic. We emphasize the value of historical data collected through archival research for understanding the sources of environmental lead, particularly leaded gasoline, which our study found to be the most likely and most prominent contributor to soil-lead in Santa Ana's environment. This research contributes to environmental-justice advocacy efforts to reframe lead poisoning as a systemic environmental issue and outlines the path forward to community-level remediation strategies.

Long-term characterization of roadside air pollutants in urban Beijing and associated public health implications

Road traffic constitutes a major source of air pollutants in urban Beijing, which are responsible for substantial premature mortality. A series of policies and regulations has led to appreciable traffic emission reductions in recent decades. To shed light on long-term (2014-2020) roadside air pollution and assess the efficacy of traffic control measures and their effects on public health, this study quantitatively evaluated changes in the concentrations of six key air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, CO and O₃) measured at 5 roadside and 12 urban background monitoring stations in Beijing. We found that the annual mean concentrations of these air pollutants were remarkably reduced by 47%-71% from 2014 to 2020, while the concurrent ozone concentration increased by 17.4%. In addition, we observed reductions in the roadside increments in PM_2.5, NO₂, SO₂ and CO of 54.8%, 29.8%, 20.6%, and 59.1%, respectively, indicating the high effectiveness of new vehicle standard (China V and VI) implementation in Beijing. The premature deaths due to traffic emissions were estimated to be 8379 and 1908 cases in 2014 and 2020, respectively. The impact of NO₂ from road traffic relative to PM_2.5 on premature mortality was comparable to that of traffic-related PM_2.5 emissions. The public health effect of SO₂ originating from traffic was markedly lower than that of PM_2.5. The results indicated that a reduction in traffic-related NO₂ could likely yield the greatest benefits for public health.

Evaluating the applicability of the ratio of PM2.5 and carbon monoxide as source signatures

Air pollution is among the top risk faced by people around the world, and therefore combating it is among the top priorities. It begins with identifying the sources that contribute the most to local air pollution to prioritize their control. There are advanced methods for source identification and apportionment, but such methods are not available in many low-income countries and not everywhere in all high-income countries. We propose a simplified method by using source the signatures to help obtain information about the local source contribution if no other methods are available. Using low-cost monitors, particle mass (PM_2.5) and carbon monoxide (CO) concentrations were measured and the ratio of CO/PM_2.5 was determined. We investigated outdoor and indoor sources, including vehicular exhaust, combustion of biomass, incense and mosquito coil burning, and cigarette smoking. The results show that the ratios differed significantly between certain pollutant sources. Compressed natural gas (CNG) engines have a high ratio (mean value of 972 ± 419), which is attributed to relatively low PM_2.5 emissions, while ship emissions and cigarette smoke recorded a relatively low ratio. Most traffic emissions recorded higher ratios than those of bushfire emissions, and ratios of most outdoor pollutant sources were much higher than those of indoor pollutant sources. There is a clear trend for ratios to decrease from high to low for CNG, petrol, diesel for buses, and fuel for ships. Our results suggest that the ratio of CO/PM_2.5 can be used as an effective method to identify pollution sources.

1H NMR structural signatures of source and atmospheric organic aerosols in India

Organic aerosols (OA) play significant roles in several atmospheric processes and adversely impact human health. This study examines the key structural units present in water- and methanol-soluble organic carbon (WSOC, MSOC) fraction of OA from emission sources (traffic and biomass cooking) and an urban background location in India. Proton nuclear magnetic resonance (¹H NMR) spectroscopy was employed to assess the distribution of non-exchangeable proton structural groups of the OAs. Organic carbon, elemental carbon, black carbon, and water-soluble organic carbon (WSOC) analyses were also conducted. The ¹H NMR analysis corroborated that the WSOC and MSOC fractions hold similar ¹H structural groups; however, they differ in their relative distribution and absolute concentrations across the ambient locations and source emissions. The relative contribution of the proton structural groups to OA was in the order C-H > H-C-C=> H-C-O > Ar-H. The aliphatic concentration was lower in the morning tunnel entry aerosols when compared to other tunnel aerosols, whereas the unsaturated structures (H-C-C= ) were present in all the tunnel aerosols within a range of 47.2-62.3 μmol/m³. The aromatic groups were the maximum in the firewood aerosols, about 1.4 and 3.7 times higher than the crop residue and the mixed fuel aerosols, respectively. The total functional groups, i.e., the sum of all the observed groups, significantly correlated with C-H (r = 0.96) and WSOC (r = 0.7), suggesting the higher contribution of aliphatic groups in the WSOC fraction. WSOC examined in this study fits well in the established ¹H NMR source identification fingerprints of urban aerosols. However, biomass cooking aerosols do not fit the established biomass burning organic aerosols (BBOAs) boundaries, exhibiting a smaller relative contribution of carbon-oxygen double bonds and a less oxidised character than open-field burning. Our results provide essential insights into the nature of urban atmospheric, near-traffic and biomass cooking OAs in India.

Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts

The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO₂ emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO₂, we analysed district level CO₂ fluxes measured by the eddy-covariance technique from 13 stations in 11 European cities. The data span several years before the pandemic until October 2020 (six months after the pandemic began in Europe). All sites showed a reduction in CO₂ emissions during the national lockdowns. The magnitude of these reductions varies in time and space, from city to city as well as between different areas of the same city. We found that, during the first lockdowns, urban CO₂ emissions were cut with respect to the same period in previous years by 5% to 87% across the analysed districts, mainly as a result of limitations on mobility. However, as the restrictions were lifted in the following months, emissions quickly rebounded to their pre-COVID levels in the majority of sites.

A decade of CO2 flux measured by the eddy covariance method including the COVID-19 pandemic period in an urban center in Sakai, Japan

Cities constitute an important source of greenhouse gases, but few results originating from long-term, direct CO₂ emission monitoring efforts have been reported. In this study, CO₂ emissions were quasi-continuously measured in an urban center in Sakai, Osaka, Japan by the eddy covariance method from 2010 to 2021. Long-term CO₂ emissions reached 22.2 ± 2.0 kg CO₂ m^-2 yr^-1 from 2010 to 2019 (± denotes the standard deviation) in the western sector from the tower representing the densely built-up area. Throughout the decade, the annual CO₂ emissions remained stable. According to an emission inventory, traffic emissions represented the major source of CO₂ emissions within the flux footprint. The interannual variations in the annual CO₂ flux were positively correlated with the mean annual traffic counts at two highway entrances and exits. The CO₂ emissions decreased suddenly, by 32% ± 3.1%, in April and May 2020 during the period in which the first state of emergency associated with COVID-19 was declared. The annual CO₂ emissions also decreased by 25% ± 3.1% in 2020. Direct long-term observations of CO₂ emissions comprise a useful tool to monitor future emission reductions and sudden disruptions in emissions, such as those beginning in 2020 during the COVID-19 pandemic.

Traffic restrictions during COVID-19 lockdown improve air quality and reduce metal biodeposition in tree leaves

The coronavirus disease (COVID-19) has had a great global impact on human health, the life of people, and economies all over the world. However, in general, COVID-19´s effect on air quality has been positive due to the restrictions on social and economic activity. This study aimed to assess the impact on air quality and metal deposition of actions taken to reduce mobility in 2020 in two different urban locations. For this purpose, we analysed air pollution (NO₂, NO, NO_x, SO_2, CO, PM_10, O₃) and metal accumulation in leaves of Tilia cordata collected from April to September 2020 in two cities in northern Spain (Pamplona-PA and San Sebastián-SS). We compared their values with data from the previous year (2019) (in which there were no mobility restrictions) obtained under an identical experimental design. We found that metal accumulation was mostly lower during 2020 (compared with 2019), and lockdown caused significant reductions in urban air pollution. Nitrogen oxides decreased by 33%-44%, CO by 24%-38%, and PM₁₀ by 16%-24%. The contents of traffic-related metals were significantly reduced in both studied cities. More specifically, significant decreases in metals related to tyre and brake wear (Zn, Fe, and Cu) and road dust resuspension (Al, Ti, Fe, Mn, and Ca) were observed. With these results, we conclude that the main reason for the improvement in urban air pollutants and metals was the reduction in the use of cars due to COVID-19 lockdown. In addition, we offer some evidence indicating the suitability of T. cordata leaves as a tool for biomonitoring metal accumulation. This information is relevant for future use by the scientific community and policy makers to implement measures to reduce traffic air pollution in urban areas and to improve environmental and human health.

Long-term evaluation of a low-cost air sensor network for monitoring indoor and outdoor air quality at the community scale

Given the growing interest in community air quality monitoring using low-cost sensors, 30 PurpleAir II sensors (12 outdoor and 18 indoor) were deployed in partnership with community members living adjacent to a major interstate freeway from December 2017- June 2019. Established quality assurance/quality control techniques for data processing were used and sensor data quality was evaluated by calculating data completeness and summarizing PM_2.5 measurements. To evaluate outdoor sensor performance, correlation coefficients (r) and coefficients of divergence (CoD) were used to assess temporal and spatial variability of PM_2.5 between sensors. PM_2.5 concentrations were also compared to traffic levels to assess the sensors' ability to detect traffic pollution. To evaluate indoor sensors, indoor/outdoor (I/O) ratios during resident-reported activities were calculated and compared, and a linear mixed-effects regression model was developed to quantify the impacts of ambient air quality, microclimatic factors, and indoor human activities on indoor PM_2.5. In general, indoor sensors performed more reliably than outdoor sensors (completeness: 73% versus 54%). All outdoor sensors were highly temporally correlated (r > 0.98) and spatially homogeneous (CoD<0.06). The observed I/O ratios were consistent with existing literature, and the mixed-effects model explains >85% of the variation in indoor PM_2.5 levels, indicating that indoor sensors detected PM_2.5 from various sources. Overall, this study finds that community-maintained sensors can effectively monitor PM_2.5, with main data quality concerns resulting from outdoor sensor data incompleteness.

Elemental composition of fine and coarse particles across the greater Los Angeles area: Spatial variation and contributing sources

The inorganic components of particulate matter (PM), especially transition metals, have been shown to contribute to PM toxicity. In this study, the spatial distribution of PM elements and their potential sources in the Greater Los Angeles area were studied. The mass concentration and detailed elemental composition of fine (PM_2.5) and coarse (PM_2.5-10) particles were assessed at 46 locations, including urban traffic, urban community, urban background, and desert locations. Crustal enrichment factors (EFs), roadside enrichments (REs), and bivariate correlation analysis revealed that Ba, Cr, Cu, Mo, Pd, Sb, Zn, and Zr were associated with traffic emissions in both PM_2.5 and PM_2.5-10, while Fe, Li, Mn, and Ti were affected by traffic emissions mostly in PM_2.5. The concentrations of Ba, Cu, Mo, Sb, Zr (brake wear tracers), Pd (tailpipe tracer), and Zn (associated with tire wear) were higher at urban traffic sites than urban background locations by factors of 2.6-4.6. Both PM_2.5 and PM_2.5-10 elements showed large spatial variations, indicating the presence of diverse emission sources across sampling locations. Principal component analysis extracted four source factors that explained 88% of the variance in the PM_2.5 elemental concentrations, and three sources that explained 86% of the variance in the PM_2.5-10 elemental concentrations. Based on multiple linear regression analysis, the contribution of traffic emissions (27%) to PM_2.5 was found to be higher than mineral dust (23%), marine aerosol (18%), and industrial emissions (8%). On the other hand, mineral dust was the dominant source of PM_2.5-10 with 45% contribution, followed by marine aerosol (22%), and traffic emissions (19%). This study provides novel insight into the spatial variation of traffic-related elements in a large metropolitan area.

The impact of coal combustion, nitrous oxide emissions, and traffic emissions on COVID-19 cases: a Markov-switching approach

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread to more than 200 countries with a current case fatality ratio (CFR) of more than 2% globally. The concentration of air pollutants is considered a critical factor responsible for transmitting coronavirus disease among the masses. The photochemical process and coal combustions create respiratory disorders that lead to coronavirus disease. Based on the crucial fact, the study evaluated the impact of nitrous oxide (N₂O) emissions, coal combustion, and traffic emissions on COVID-19 cases in a panel of 39 most affected countries of the world. These three air pollution factors are considered to form a lethal smog that negatively affects the patient's respiratory system, leading to increased susceptibility to coronavirus worldwide. The study used the Markov two-step switching regime regression model for obtaining parameter estimates. In contrast, an innovation accounting matrix is used to assess smog factors' intensity on possibly increasing coronavirus cases over time. The results show that N₂O emissions, coal combustion, and traffic emissions increase COVID-19 cases in regime-1. On the other hand, N2O emissions significantly increase coronavirus cases in regime-2. The innovation accounting matrix shows that N2O emissions would likely have a more significant share of increasing coronavirus cases with a variance of 33.902%, followed by coal combustion (i.e., 6.643%) and traffic emissions (i.e., 2.008%) over the time horizon. The study concludes that air quality levels should be maintained through stringent environmental policies, such as carbon pricing, sustainable urban planning, green technology advancement, renewable fuels, and pollution less accessible vehicles. All these measures would likely decrease coronavirus cases worldwide.

Traffic exposure, air pollution and children's physical activity at early childhood education and care

BACKGROUND

A significant number of children attend Early Childhood Education and Care (ECEC). ECEC is an important environment and behaviour setting for young children. Time spent outdoors is positively associated with children's physical activity levels, yet increased time spent physically active outdoors may expose young children to traffic-related air pollution, particularly in ECEC centres located in high traffic areas.

METHODS

This study was part of the Play Spaces and Environments for Children's Physical Activity (PLAYCE) study, Perth, Western Australia. Data from 22 ECEC centres and 478 children were collected. Continuous measures of indoor and outdoor fine particulate matter (PM_2.5) were conducted for 48-72 h in each ECEC. Children wore ActiGraph GT3X + accelerometers to measure their physical activity at ECEC. The total length of high traffic roads within a 300m road network service area buffer around each ECEC was used to identify high and low traffic centres.

RESULTS

Outdoor PM_2.5 concentrations peaked in the afternoon (1pm, 2pm and 6pm) at ECEC centres. Outdoor and indoor PM_2.5 concentrations were significantly higher for centres located in high compared with low traffic areas (both p < 0.05). There was no significant association between a centre being located in a high or low traffic area and the time preschoolers spent outdoors or their physical activity levels.

DISCUSSION

Time periods when air pollution concentrations in ECECs are highest correspond with times when preschoolers are likely to be physically active outdoors. Children's potential exposure to traffic-related air pollutants is occurring during a period of rapid lung development. Given there is no evidence of a safe level of exposure to PM_2.5 or a threshold below which no adverse health effects occur, careful planning should be a consideration to avoid locating ECEC centres in high traffic areas.

Proximity of schools to roads and students' academic performance: A cross-sectional study in the Federal District, Brazil

Investigations of the educational implications of children's exposure to air pollutants at school are crucial to enhance our understanding of the hazards for children. Most of the existing literature is based on studies performed in North America and Europe. Further investigation is required in low- and middle-income countries, where there are important challenges related to public health, transportation, environment, and education sector. In response, in this present study, we studied the association between proximity of schools to roads and the academic achievement of the students in the Federal District, Brazil. We accessed academic achievement data at the student level. The data consist of 256 schools (all the public schools in the FD) and a total of 344,175 students (all the students enrolled in the public schools in the FD in 2017-2020). We analyzed the association between the length of all roads within buffers around schools and student-level academic performance using mixed-effects regression models. After adjustments for several covariates, the results of the primary analysis indicate that the presence of roads surrounding schools is negatively associated with student-level academic performance in the FD. This association varies significantly depending on the buffer size surrounding schools. We found that the highest effects occur in the first buffer, with 250 m. While in the first buffer we estimated that an increase of 1 km of length of roads around schools was associated with a statistically significant decrease of 0.011 (95%CI: 0.008; 0.013) points in students' grades (students' academic performance varies from 0 to 10), in the buffer of 1 km we found a decrease of 0.002 (95%CI: 0.002; 0.002) points in the student-level academic performance. Findings from our investigation provide support for the creation of effective health, educational and urban planning policies for local intervention in the FD. This is essential to improve the environmental quality surrounding schools to protect children from exposure to environmental hazards.

Molecular characterization of atmospheric particulate organosulfates in a port environment using ultrahigh resolution mass spectrometry: Identification of traffic emissions

Organosulfates (OSs) are an important component of atmospheric organic aerosol (OA) and are widespread in various environments. However, the OSs generated from anthropogenic emissions are poorly understood. In this study, the molecular compositions of OSs from atmospheric PM_2.5 samples collected during a winter measurement campaign (SEISO-Bohai) at Jingtang Harbor were characterized via ultrahigh resolution mass spectrometry (UHRMS). The changes of port OS compositions were observed in episodes of complete haze pollution. As the pollution aggravated, the relative abundances of OSs were apparently increased, and the molecule compositions became more complex, primarily driven by the oxidation and fragmentation processes. Potential OS precursors from traffic emissions were identified based on an optimized "OS precursor map" developed in the previous study. OSs characterized by high molecular weights and low degrees of both unsaturation and oxidization were suggested to mainly derive from secondary reactions of intermediate volatile organic compounds (IVOCs) emitted by traffic sources. These OSs were primarily detected in clean-day samples, followed by decreasing with the pollution process. In addition, our study also finds that ship emissions may further facilitated OS productions under haze pollution conditions.

Organic compound source profiles of PM2.5 from traffic emissions, coal combustion, industrial processes and dust

Eighteen polycyclic aromatic hydrocarbons (PAHs), 24 n-alkanes, 7 hopanes, 2 cholestanes, inorganic ions, elements and carbon fractions were analyzed in real-world source samples of PM_2.5 (fine particulate matter) from traffic emissions (gasoline vehicles-TGV, diesel vehicles-TDV, diesel ship-TDS, and heavy oil ships-THOS), coal combustion (coal-fired industrial boilers-CIB, power plants-CPP, and residential stoves-CRS), industrial process emissions (cement industry-IPCI, and steel industry-IPSI), and dust (soil dust-DSD, road dust-DRD, and construction dust-DCD). High molecular weight (sum of five to seven rings) PAHs accounted for higher fractions for TGV (80%) and THS (61%) than for TDV, TDS and coal combustion sources (31%-47%). Hopane ratios (C29αβ/C30αβ) in coal related sources were mostly higher than 1, whereas that of traffic emissions was lower than 1. The homohopane index [S/(S + R)], which is a useful index for identifying the maturity of fuels, ranked as TGV > THS > TDV and TDS > coal combustion. For n-alkane profiles, coal related sources showed peaks at C16-C19, TDV, TDS and THS showed similar peaks at C17-C25, but peaks for DSD (C30-C32), DRD (C17-C20, C24-25 and C30-C31), CRS (C16-C18 and C28-C29) and TGV (C24-C26) are different. Organic markers were selected which can best differentiate the subtypes within source categories by considering the component levels and variations. Through a comprehensive review, we showed that it is inadvisable to directly use diagnostic ratios for source attribution, although their trends can assist in identifying influential sources.

Characterization and exposure assessment to urban air toxics across Middle Eastern and North African countries: a review

Middle East and North African (MENA) countries over the decades are experiencing rapid industrial and infrastructural growth combined with being the global hub of oil and gas industries. These economic transformations are associated with release of air pollutants including urban air toxics (UAT) through industrial, traffic, and constructional activities into ambient urban environments. UAT concentrations levels may exacerbate in most MENA countries considering high number of vehicular traffic populations and petrochemical industries which are one of the main sources of this pollutant. Therefore, the main objective of the study is to review major findings of UAT levels in urban areas across thirteen (13) MENA countries. The study characterizes various measured UAT, assesses their concentrations in ambient environment, and identifies their major sources of emissions by reviewing more than 100 relevant UAT papers across the selected MENA countries. It was found that benzene, heavy metals, formaldehyde, and dioxin-like compounds are the most reported UAT. The study concluded that road traffic, fuel stations, and petrochemical industries were identified as the main sources of ambient UAT levels. It was further reported that most of the studies were based on short-term ambient environment with limited studies in indoor environments. Therefore, it is highly recommended that future research should focus on innovative health impact assessment and epidemiological studies from exposure to UAT levels. Also embarking on sustainable mitigation approaches through urban greenery, eco-industrial estates infrastructural developments, and renewable energy shares will reduce UAT levels and improve human health.

Analysis of lockdown for CoViD-19 impact on NO2 in London, Milan and Paris: What lesson can be learnt?

Nitrogen dioxide (NO₂) can have harmful effects on human health and can act as a precursor for the formation of other air pollutants in urban environment such as secondary PM_2.5 and ozone. The lockdown measures for CoViD-19 allowed to simulate on a large scale the massive and prolonged reduction of road traffic (the main source for NO₂ in urban environment). This work aims to selectively assess the maximum impact that total traffic blocking measures can have on NO₂. For this reason, three megacities (London, Milan and Paris) were chosen which had similar characteristics in terms of climatic conditions, population, policies of urban traffic management and lockdown measures. 52 air quality control units have been used to compare data measured in lockdown and in the same periods of previous years, highlighting a significant decrease in NO₂ concentration due to traffic (London: 71.1 % - 80.8 %; Milan: 8.6 % - 42.4 %; Paris: 65.7 % - 79.8 %). In 2020 the contribution of traffic in London, Milan and Paris dropped to 3.3 ± 1.3 μg m^-3, 6.1 ± 0.8 μg m^-3, and 13.4 ± 1.5 μg m^-3, respectively. Despite the significant reduction in the NO₂ concentration, in UT stations average NO₂ concentrations higher than 40 μg m^-3 were registered for several days. In order to reduce the pollution, the limitation of road traffic could be not enough, but a vision also aimed at rethink the vehicles and their polluting effects should be developed.

Assessment of mesoscale and microscale simulations of a NO2 episode supported by traffic modelling at microscopic level

The aim of this work is to simulate with high accuracy an episode of high NO2 pollution during December 2016 in the city of Madrid (Spain). For this purpose, a multiscale modelling system has been implemented that includes a mesoscale model (WRF/Chem) up to a horizontal resolution of 1 km and a computational fluid dynamics model (CFD; MICROSYS) with a resolution of 5 m. For the calculation of traffic emissions, a traffic simulation has been previously conducted with the SUMO microscopic model, calibrated from data measured with traffic counters. We show a substantial improvement in the results obtained with 5 m resolution with respect to those of 1 km, reproducing very closely the daily peaks of NO₂ concentrations since a very detailed traffic emission source is being used and the CFD reproduces the interactions between the air flow and the buildings. The modelling system presented can be used as a tool to evaluate different emission reduction strategies at street level, as it would allow to have an orientation on their effectiveness without having to implement them.

Competing PM2.5 and NO2 holiday effects in the Beijing area vary locally due to differences in residential coal burning and traffic patterns

The holiday effect is a useful tool to estimate the impact on air pollution due to changes in human activities. In this study, we assessed the variations in concentrations of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) during the holidays in the heating season from 2014 to 2018 based on daily surface air quality monitoring measurements in Beijing. A Generalized Additive Model (GAM) is used to analyze pollutant concentrations for 34 sites by comprehensively accounting for annual, monthly, and weekly cycles as well as the nonlinear impacts of meteorological factors. A Saturday effect was found in the downtown area, with about 4% decrease in PM_2.5 and 3% decrease in NO₂ relative to weekdays. On Sundays, the PM_2.5 concentrations increased by about 5% whereas there were no clear changes for NO₂. In contrast to the small effect of the weekend, there was a strong holiday effect throughout the region with average increases of about 22% in PM_2.5 and average reductions of about 11% in NO₂ concentrations. There was a clear geographical pattern in the strength of the holiday effect. In rural areas the increase in PM_2.5 is related to the proportion of coal and biomass consumption for household heating. In the suburban areas between the Fifth Ring Road and Sixth Ring Road there were larger reductions in NO₂ than downtown which might be due to decreased traffic as many people return to their hometown for the holidays. This study provides insights into the pattern of changes in air pollution due to human activities. By quantifying the changes, it also provides insights for improvements in air quality due to control policies implemented in Beijing during the heating season.

Geochemical characteristics of solid particles deposited on experimental plots established for traffic pollution monitoring in different countries

The main aim of this research was to identify the mineralogical, morphological, and chemical characteristics of solid particles emitted by vehicular traffic and deposited on special monitoring plots located on the roadside of five countries with different climatic conditions and traffic structure. Within 24 months of exposure, the composition of the matrix used at the monitoring plots changed. Percentage quartz content decreased in all locations, and due to the input from local sources, the share of other mineral phases increased. In some locations, an increase in the share of mineral phases associated with local parent rock and soil erosion was noted (e.g. Helsinki, Böblingen). In other places, material associated with abrasion of the road surface was characteristic (e.g. Gliwice, Opole). The composition of pollutants accumulated at all the monitoring plots was varied, however the common feature was the presence of technogenic magnetic particles in the matrix after exposure. Analyses showed that numerous irregular, angular particles of iron oxides with porous surface, which are carriers for a number of metals and metalloids were present in the samples. Angular iron oxides containing zinc, chromium, and copper are usually considered as non-exhaust traffic emissions. Another type of iron oxides particles found in the samples were magnetic spherules related to exhaust emissions (smaller spherules, < 20 μm). Study of results confirmed the effectiveness of the testing method for roadside pollution monitoring related to currently emitted solid particles accumulated on matrix of known mineral composition.

Air Pollution and Asthma: Critical Targets for Effective Action

Evidence to advocate for cleaner air for people with asthma is not in short supply. We know that air pollution is associated with the development and worsening of the condition and that mitigating interventions can improve respiratory outcomes. We have clear targets, particularly traffic emissions, especially in urban areas, and plenty of potentially effective actions. Road traffic must be reduced, and what remains should be cleaner and greener. Urban green spaces, safe cycle networks and wider pavements will promote active travel and leisure time exercise. Healthcare professionals must ensure people are aware of their air quality, its impact on asthma and the appropriate behaviour to safeguard health. What remains are realistic policies and effective measures, based on the correct scientific evidence, to be taken forth with political courage and investment so that air pollution no longer contributes to the development or worsening of respiratory ill health.

Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India

Lockdown measures to contain COVID-19 pandemic has resulted in a considerable change in air pollution worldwide. We estimate the temporal and diurnal changes of the six criteria air pollutants, including particulate matter (PM2.5 and PM10) and gaseous pollutants (NO2, O3, CO, and SO2) during lockdown (25th March - 3rd May 2020) across regions of India using the observations from 134 real-time monitoring sites of Central Pollution Control Board (CPCB). Significant reduction in PM2.5, PM10, NO2, and CO has been found in all the regions during the lockdown. SO2 showed mixed behavior, with a slight increase at some sites but a comparatively significant decrease at other locations. O3 also showed a mixed variation with a mild increase in IGP and a decrease in the South. The absolute decrease in PM2.5, PM10, and NO2 was observed during peak morning traffic hours (08-10 Hrs) and late evening (20-24 Hrs), but the percentage reduction is almost constant throughout the day. A significant decrease in day-time O3 has been found over Indo Gangetic plain (IGP) and central India, whereas night-time O3 has increased over IGP due to less O3 loss. The most significant reduction (∼40-60%) was found in PM2.5 and PM10. The highest decrease in PM was found for the north-west and IGP followed by South and central regions. A considerable reduction (∼30-70%) in NO2 was found except for a few sites in the central region. A similar pattern was observed for CO having a ∼20-40% reduction. The reduction observed for PM2.5, PM10, NO2, and enhancement in O3 was proportional to the population density. Delhi's air quality has improved with a significant reduction in primary pollutants, however, an increase in O3 was observed. The changes reported during the lockdown are combined effect of changes in the emissions, meteorology, and atmospheric chemistry that requires detailed investigations.

Changes in air quality related to the control of coronavirus in China: Implications for traffic and industrial emissions

Measures taken to control the disease (Covid-19) caused by the novel coronavirus dramatically reduced the number of vehicles on the road and diminished factory production. For this study, changes in the air quality index (AQI) and the concentrations of six air pollutants (PM_2.5, PM₁₀, CO, SO₂, NO₂, and O₃) were evaluated during the Covid-19 control period in northern China. Overall, the air quality improved, most likely due to reduced emissions from the transportation and secondary industrial sectors. Specifically, the transportation sector was linked to the NO₂ emission reductions, while lower emissions from secondary industries were the major cause for the reductions of PM_2.5 and CO. The reduction in SO₂ concentrations was only linked to the industrial sector. However, the reductions in emissions did not fully eliminate air pollution, and O₃ actually increased, possibly because lower fine particle loadings led to less scavenging of HO₂ and as a result greater O₃ production. These results also highlight need to control emissions from the residential sector.

The impact of diesel vehicles on NOx and PM10 emissions from road transport in urban morphological zones: A case study in North Rhine-Westphalia, Germany

Harmful emissions like nitrogen oxide and particulate matter are one of the big challenges facing modern society. These emissions are especially apparent in agglomerations. Possible solutions to overcome this challenge within the framework of the transformation of the transport sector are the change of the transport vehicles of freight and passenger transport or changing the fuel of the vehicles. Determining the viability of both approaches requires analyses to determine which vehicles are the main polluters in urban areas. This study outlines a bottom-up approach for the calculation of road transport emissions on street level in the representative model region of North Rhine-Westphalia in Germany, considering eight different vehicle classes as well as diesel and gasoline as fuel. Part of the approach is the development of a street-section traffic volume map considering all streets in the model region using a developed multivariate linear regression model for Germany and existing traffic counts. Using the approach developed here, the urban areas of Herne, Oberhausen and Bochum were identified as hotspots with the highest specific nitrogen oxide emissions, while the urban areas of Herne, Oberhausen and Gelsenkirchen were identified as hotspots with the highest specific particulate matter emissions. A detailed investigation of Oberhausen as a representative emission hotspot showed that 91% of road transport nitrogen oxide emissions are produced by vehicles that use diesel fuel and 9% from vehicles with gasoline fuel, while gasoline vehicles account for 43% of the total distance driven and diesel vehicles for 57%. With respect to particulate matter emissions in the urban area of Oberhausen, 29% are produced by gasoline vehicles and 71% by diesel vehicles. However, only 22% of particulate matter emissions are exhaust emissions, while 78% are produced due to the abrasion of tires, brakes and the road.

Relative contributions of a major international airport activities and other urban sources to the particle number concentrations (PNCs) at a nearby monitoring site

In this study, the positive matrix factorization (PMF) source apportionment model was employed to quantify the contributions of airport activities to particle number concentrations (PNCs) at Amsterdam Schiphol. Time-resolved particle number size distributions in parallel with the concentrations of auxiliary variables, including gaseous pollutants (NO_x and CO), black carbon, PM_2.5 mass, and number of arrivals/departures were measured for 32 sampling days over a 6-month period near Schiphol airport to be used in the model. PMF results revealed that airport activities, cumulatively, accounted for around 79.3% of PNCs and our model segregated them into three major groups: (i) aircraft departures, (ii) aircraft arrivals, and (iii) ground service equipment (GSE) (with some contributions of local road traffic, mostly from airport parking lots). Aircraft departures and aircraft arrivals showed mode diameters <20 nm and contributed, respectively, to 46.1% and 26.7% of PNCs. The factor GSE/local road traffic, with a mode diameter of around 60-80 nm, accounted for 6.5% of the PNCs. Road traffic related mainly to the surrounding freeways was characterized with a mode diameter of 30-40 nm; this factor contributed to 18.0% of PNCs although its absolute PNCs was comparable with that of areas heavily impacted by traffic emissions. Lastly, urban background with a mode diameter at 150-225 nm, had a minimal contribution (2.7%) to PNCs while dominating the particle volume/mass concentrations with a contribution of 58.2%. These findings illustrate the dominant role of the airport activities in ambient PNCs in the surrounding areas. More importantly, the quantification of the contributions of different airport activities to PNCs is a useful tool to better control and limit the increased PNCs near the airports that could adversely impact the health of the adjacent urban communities.

Surfactant assisted extraction of incidental nanoparticles from road runoff sediment and their characterization by single particle-ICP-MS

A surfactant assisted extraction (SAE) method was developed to extract incidental nanoparticles (INPs) in the <300 nm particle size fraction from road runoff sediments and applied to a road runoff sediment. The method was evaluated by spiking experiments of road runoff sediment with engineered nanoparticle (ENP) suspensions of gold (Au-ENPs) between 30 nm and 200 nm and platinum (Pt-ENPs) between 30 nm and 70 nm with content ranging from 40 to 800 ng/g. Suspensions were analyzed by single particle (sp-)ICP-MS. In the presence of a road runoff matrix, an increase in ENP sizes by a maximum of 8% for Au-ENPs and 9% for Pt-ENPs was observed. ENPs mass recovery was >50% for all Au-ENPs with content higher than 200 ng/g and for 30 and 50 nm Pt-ENPs at content of 160 ng/g while for lower content the recovery was 0%. For 70 nm Pt-ENPs, recovery was always >80% and increased with increasing Pt content up to 100% in the presence of road runoff matrix. Metal content of INPs in the road runoff sediment in the fraction <300 nm decreased from copper (Cu; μg/g)> zinc (Zn)> zirconium (Zr)> cerium (Ce)> lead (Pb)> cadmium (Cd) > platinum (Pt; μg/g). Over 90% of Pt-, Zn-, Cd-, Pb- and Ce-INPs are composed of particles with less than 20 fg, while Zr- and Cu-INPs are dominated by masses higher than 20 fg. The tested SAE may be applicable to determine environmental contents of INPs in sediments and possibly in soils.

The atmospheric impacts of initiatives advancing shifts towards low-emission mobility: A scoping review

In an urban environment, people's daily traffic choices are reflected in emissions and the resulting local air composition, or air quality. Traffic contributes to the emissions of both carbon dioxide (CO₂), affecting climate, and particulate matter (PM), affecting atmospheric chemistry and human health. While the development of city infrastructure is not in the hands of individuals, it is their transport mode choices that constitute traffic. In this scoping review we analyse 108 initiatives from around the world potentially influencing individual travel behaviour and producing changes in the shares of different transport modes (modal shifts). The targets, types and techniques of initiatives are identified. Examples of economic, regulative, structural and persuasive initiatives are included. Special focus is on whether the impacts on CO₂ emissions, PM emissions and/or PM concentrations have been quantitatively evaluated, and on the quality and results of the evaluations. We observe that a variety of targets can motivate actions that lead to modal shifts and emission reductions. The results indicate that the level of atmospheric evaluations is low: absolute or relative changes in emissions and/or concentrations had been evaluated for only 31% (N = 34) of the reviewed initiatives, with substantial heterogeneity in quality. Sanctions, such as congestion charge and restrictions, have more likely been evaluated in peer reviewed analyses than incentives. Scientific evaluations of impacts on ambient PM concentrations are especially scarce (N = 4), although Air Quality is the primary target of 13% of actions and secondary target for at least 12%. We discuss the determinants of success and failure, when it comes to different types of initiatives, emission reductions and evaluations. A high-quality evaluation of atmospheric impacts captures the following: correct data about the modal shift (rate and direction), exclusion of external factors affecting the shift and emissions, and possible indirect impacts of the shift.

Monitoring and assessment of cadmium, lead, zinc and copper concentrations in arable roadside soils in terms of different traffic conditions

Quantification of the contributions from traffic source to arable roadside soil heavy metal loadings is a challenge. The contribution depends on: traffic intensity, road type and distance from the road. At a field scale (3.9 ha), 720 topsoil samples were taken. The aim of the study was to monitor and assess the impact of regional/local roads with various conditions of traffic and period of use on the distribution of Cd, Zn, Pb and Cu in the arable roadside topsoil in their vicinity. PCA indicated the occurrence of two main gradients of 11 environmental elements influencing the distribution of heavy metals in the soils of the neighbouring land. The first gradient was associated mainly with the distance from the edge of the road. The second gradient was associated with the degree of contamination of the soils and with the road type, defined by the traffic volume and period of being use. Anova reviled lack of influence of the factors for Cu contents. Unlike Cu, for Cd, Pb and Zn, the significant impact was observed for both factors and interactions between them. The concentrations of Cd, Pb and Zn, regardless of the distance from the road were 0.21-0.58 mg Cd kg^-1 d.m., 13.60-41.96 mg Pb kg^-1 d.m. and 40.31-63.97 mg Zn kg^-1 d.m. In case of increasing distance from the road, generally the contents of Pb, Zn and Cd contents were decreasing. However, only in the case the oldest and carrying the highest traffic road was a clear, statistically significant differences noted for following distances from the road on the content of Cd, Pb and Zn. Analysis of spread gave trend curves, for Pb, Cd and Zn they were parabolas. The curves let reduce sapling distances to 65 m, 45 and 47 m for Cd, Pb and Zn, respectively.

Source apportionment of particle number size distribution in urban background and traffic stations in four European cities

Ultrafine particles (UFP) are suspected of having significant impacts on health. However, there have only been a limited number of studies on sources of UFP compared to larger particles. In this work, we identified and quantified the sources and processes contributing to particle number size distributions (PNSD) using Positive Matrix Factorization (PMF) at six monitoring stations (four urban background and two street canyon) from four European cities: Barcelona, Helsinki, London, and Zurich. These cities are characterised by different meteorological conditions and emissions. The common sources across all stations were Photonucleation, traffic emissions (3 sources, from fresh to aged emissions: Traffic nucleation, Fresh traffic - mode diameter between 13 and 37 nm, and Urban - mode diameter between 44 and 81 nm, mainly traffic but influenced by other sources in some cities), and Secondary particles. The Photonucleation factor was only directly identified by PMF for Barcelona, while an additional split of the Nucleation factor (into Photonucleation and Traffic nucleation) by using NO_x concentrations as a proxy for traffic emissions was performed for all other stations. The sum of all traffic sources resulted in a maximum relative contributions ranging from 71 to 94% (annual average) thereby being the main contributor at all stations. In London and Zurich, the relative contribution of the sources did not vary significantly between seasons. In contrast, the high levels of solar radiation in Barcelona led to an important contribution of Photonucleation particles (ranging from 14% during the winter period to 35% during summer). Biogenic emissions were a source identified only in Helsinki (both in the urban background and street canyon stations), that contributed importantly during summer (23% in urban background). Airport emissions contributed to Nucleation particles at urban background sites, as the highest concentrations of this source took place when the wind was blowing from the airport direction in all cities.

Determination of antimony and barium in UK air quality samples as indicators of non-exhaust traffic emissions

The aim of this study was to determine concentrations of antimony and barium in air quality samples and assess the potential suitability of these metals as tracer elements for non-exhaust traffic emissions sources. Air quality filters sampled at monitoring sites around the UK for the purposes of the UK Heavy Metals Monitoring Network were subjected to microwave digestion in hydrogen peroxide and nitric acid, then analysed by ICP-MS for a suite of metals including antimony and barium. The average antimony concentration found across all the network sites was 1.84 ng m^-3; the average barium concentration was 6.33 ng m^-3. The range of antimony concentrations observed was 0.13-8.02 ng m^-3; barium concentrations ranged from levels below the detection limit of 0.18 to 39.9 ng m^-3. There are no legislative limits for antimony and barium in ambient air, but the maximum concentrations found are well below the Workplace Exposure Limits specified by the UK Health and Safety Executive. The highest concentrations were found at roadside sites situated to monitor traffic environments, supporting the suitability of antimony and barium to be considered tracer elements for traffic emissions sources. Strong correlations were observed between antimony, barium and copper, indicating they share a common traffic-related source. Based on the strong correlation with copper at urban and traffic locations, indicative annual UK atmospheric emission estimates for antimony and barium in brake and tyre wear were calculated as 6 and 19 tonnes respectively.

Triggering of cardiovascular hospital admissions by source specific fine particle concentrations in urban centers of New York State

BACKGROUND

Previous work reported increased rates of acute cardiovascular hospitalizations associated with increased PM2.5 concentrations in the previous few days across urban centers in New York State from 2005 to 2016. These relative rates were higher after air quality policies and economic changes resulted in decreased PM2.5 concentrations and changes in PM composition (e.g. increased secondary organic carbon), compared to before and during these changes. Changes in PM composition and sources may explain this difference.

OBJECTIVES

To estimate the rate of acute cardiovascular hospitalizations associated with increases in source specific PM2.5 concentrations.

METHODS

Using source apportioned PM2.5 concentrations at the same NYS urban sites, a time-stratified case-crossover design, and conditional logistic regression models adjusting for ambient temperature and relative humidity, we estimated the rate of these acute cardiovascular hospitalizations associated with increases in mean source specific PM2.5 concentrations in the previous 1, 4, and 7 days.

RESULTS

Interquartile range (IQR) increases in spark-ignition emissions (GAS) concentrations were associated with increased excess rates of cardiac arrhythmia hospitalizations (2.3%; 95% CI = 0.4%, 4.2%; IQR = 2.56 μg/m3) and ischemic stroke hospitalizations (3.7%; 95% CI = 1.1%, 6.4%; 2. 73 μg/m3) over the next day. IQR increases in diesel (DIE) concentrations were associated with increased rates of congestive heart failure hospitalizations (0.7%; 95% CI = 0.2% 1.3%; 0.51 μg/m3) and ischemic heart disease hospitalizations (0.8%; 95% CI = 0.3%, 1.3%; 0.60 μg/m3) over the next day, as hypothesized. However, secondary sulfate PM2.5 (SS) was not. Increased acute cardiovascular hospitalization rates were also associated with IQR increases in concentrations of road dust (RD), residual oil (RO), and secondary nitrate (SN) over the previous 1, 4, and 7 days, but not other sources.

CONCLUSIONS

These findings suggest a role of several sources of PM2.5 in New York State (i.e. traffic emissions, non-traffic emissions such as brake and tire wear, residual oil, and nitrate that may also reflect traffic emissions) in the triggering of acute cardiovascular events.

Impact of emissions from the Ports of Los Angeles and Long Beach on the oxidative potential of ambient PM0.25 measured across the Los Angeles County

In this study, weekly samples of ambient PM_0.25 (particulate matter with an aerodynamic diameter <0.25 μm) were collected in three contrasting locations, including central Los Angeles (USC), north Long Beach (NLB), and the Port of Long Beach (PRT), during June and July of 2017 to evaluate the chemical composition of ambient PM_0.25 and identify the sources that contribute to the oxidative potential of ambient PM_0.25 in these locations. Special focus was given in exploring the impact of emissions from the Ports of Los Angeles and Long Beach on the oxidative potential of ambient PM_0.25 measured across these sites. The oxidative potential of the collected samples was quantified by means of an in vitro cell-based alveolar macrophage (AM) assay. We used multiple linear regression (MLR) analysis to link individual measured species, used as source markers, to the oxidative potential of the ambient PM_0.25 across the monitoring sites. Results from the MLR analysis indicated that vehicular emissions and secondary organic aerosols (SOA) were the major contributors to the oxidative potential of ambient PM_0.25 across the three sites, with corresponding contributions of 40 ± 2% and 39 ± 3%, respectively. Emissions of PM_0.25 related to port activities, including emissions from ships, locomotives, and heavy-duty vehicles (HDVs) operating at the port, accounted for 16 ± 3% of the overall oxidative potential of the ambient PM_0.25 samples. The concentrations of the marker species at the three different sites suggested that the contributions of port-related emissions to the oxidative potential of PM_0.25 decreased from the port area to central Los Angeles, underscoring the greater impact of these emissions on the PM_0.25 toxicity in the communities near the Ports of Los Angeles and Long Beach, whereas we observed larger impact of SOA formation and vehicular emissions on the oxidative potential of ambient PM_0.25 in the receptor sites located further inland.

Exploratory assessment of indoor and outdoor particle number concentrations in Hanoi households

No studies have been conducted in Vietnam to understand the levels of atmospheric ultrafine particles, despite having adverse health effects. Information about indoor air quality in Vietnam is also limited. Hence we aimed to conduct the first assessment of ultrafine particle concentrations in terms of particle number (PN) in Hanoi, by simultaneously measuring indoor and outdoor PN concentrations from six households at different locations across the city in January 2016. We also acquired PM_2.5 data for this monitoring period from an air quality monitoring station located at the US Embassy in Hanoi, to compare the general trends between PN and PM_2.5 concentrations. The mean daily indoor and outdoor PN concentrations for the monitoring period were 1.9×10⁴p/cm³ and 3.3×10⁴p/cm³, respectively, with an increase during rush hour traffic. It was concluded that traffic was the main contributor to outdoor PN concentrations, with agricultural burning having a small influence at one study location. The mean ratio of indoor to outdoor PN concentrations for all six sites was 0.66±0.26, which points to outdoor air as the main driver of indoor PN concentrations, rather than indoor sources. These PN concentrations and I/O ratios are similar to those reported for a number of cities in developed countries. However, in contrast to PN, ambient mean PM_2.5 concentrations in Hanoi (60-70μg/m³) were significantly higher than those typically recorded in developed countries. These findings demonstrate that urban particle mass (PM_2.5) concentrations are not indicative of the PN concentrations, which can be explained by different sources contributing to PN and PM, and that direct measurements of PN are necessary to provide information about population exposure to ultrafine particles and for management of air quality.

The influence of odd-even car trial on fine and coarse particles in Delhi

The odd-even car trial scheme, which reduced car traffic between 08.00 and 20.00 h daily, was applied from 1 to 15 January 2016 (winter scheme, WS) and 15-30 April 2016 (summer scheme, SS). The daily average PM_2.5 and PM₁₀ exceeded national standards, with highest concentrations (313 μg m^-3 and 639 μg m^-3, respectively) during winter and lowest (53 μg m^-3 and 130 μg m^-3) during the monsoon (June-August). PM concentrations during the trials can be interpreted either as reduced or increased, depending on the periods used for comparison purposes. For example, hourly average net PM_2.5 and PM₁₀ (after subtracting the baseline concentrations) reduced by up to 74% during the majority (after 1100 h) of trial hours compared with the corresponding hours during the previous year. Conversely, daily average PM_2.5 and PM₁₀ were higher by up to 3-times during the trial periods when compared with the pre-trial days. A careful analysis of the data shows that the trials generated cleaner air for certain hours of the day but the persistence of overnight emissions from heavy goods vehicles into the morning odd-even hours (0800-1100 h) made them probably ineffective at this time. Any further trial will need to be planned very carefully if an effect due to traffic alone is to be differentiated from the larger effect caused by changes in meteorology and especially wind direction.

Trace elements and nitrogen content in naturally growing moss Hypnum cupressiforme in urban and peri-urban forests of the Municipality of Ljubljana (Slovenia)

We monitored trace metals and nitrogen using naturally growing moss Hypnum cupressiforme Hedw. in urban and peri-urban forests of the City Municipality of Ljubljana. The aim of this study was to explore the differences in atmospheric deposition of trace metals and nitrogen between urban and peri-urban forests. Samples were collected at a total of 44 sites in urban forests (forests within the motorway ring road) and peri-urban forests (forests outside the motorway ring road). Mosses collected in urban forests showed increased trace metal concentrations compared to samples collected from peri-urban forests. Higher values were significant for As, Cr, Cu, Hg, Mo, Ni, Pb, Sb, Tl and V. Within the motorway ring road, the notable differences in element concentrations between the two urban forests were significant for Cr, Ni and Mo. Factor analysis showed three groups of elements, highlighting the contribution of traffic emissions, individual heating appliances and the resuspension of contaminated soils and dust as the main sources of trace elements in urban forests.

Real-driving emissions of circulating Spanish car fleet in 2015 using RSD Technology

In this paper we present the results corresponding to on-road traffic emissions measurements obtained during two field campaigns developed in the Madrid region (Spain) during 2014 and 2015 in the framework of the CORETRA project. The experimental strategy was based on the use of a RSD 4600 remote sensor in interurban roads. These measurements have produced a global database of >190,000 vehicles with their associated emission data (NO/CO₂, HC/CO₂ and CO/CO₂), which can be considered representative of the current Spanish circulating fleet. The results of M1 vehicles were analysed according to their distribution by Euro Standard and engine model. One of the relevant findings is that, despite the progressive introduction of increasingly stringent standards, no NO emission reduction is observed for diesel vehicles with time, although this behavior shows significative differences among brands and engine models. We have also investigated the presence of "high emitter" (HE) vehicles in the Spanish M1 circulating fleet and most of the HE detected corresponded to diesel vehicles with very high NO/CO₂ values. With these results at hand, we strongly propose the future incorporation of the "high emitter vehicle" definition into the European environmental legislation, as well as the establishment of specific strategies in each country/region in order to identify these anomalous vehicles. Identification and repair of HE vehicles within the European circulating fleets, although are not easy tasks, should be considered very important for the improvement of air quality in the EU. The use of non-intrusive optical technologies (i.e. RSD) is an excellent option to provide instantaneous real emission data of each individual vehicle without disturbing traffic and for on-road fleet monitoring. In summary, it is a good strategy to obtain valuable information about the long term surveillance of real vehicle emission trends, specially after the introduction of new standard.

Levels, sources, and health risk assessment of polycyclic aromatic hydrocarbons in Brno, Czech Republic: a 5-year study

This work aimed to determine the seasonal variations of polycyclic aromatic hydrocarbons (PAHs) in airborne PM₁₀ at two background sites (Masná-MS, Líšeň-LN) in Brno over a 5-year period (2009-2013). Samples were collected on quartz filters using a low-volume sampler by continual filtration. Concentrations of PAHs in collected PM₁₀ samples were determined using a gas chromatography with a mass spectrometer as a detector. A different number of PAHs were determined to be at each site, i.e., 11 PAHs at the MS site and six PAHs at the LN site, and similarities between them were identified using non-parametric analysis of variance. Potential sources were identified using principal component analysis (PCA) and PAHs diagnostic ratios. The work also focused on health risk assessment. This was estimated using toxic equivalent factors to calculate individual lifetime cancer risk, which quantifies risk of exposure to PAHs for specific age groups. The average 11-PAH concentrations in M|S site annually ranged from 19.28 ± 19.02 ng m^-3 (2011) to 40.37 ± 21.35 ng m^-3 (2013). With regard to the LN site, the average six-PAH concentrations annually ranged from 3.64 ± 3.87 ng m^-3 (2009) and 5.27 ± 6.19 ng m^-3 (2012). PCA and diagnostic ratios indicate the main sources to be traffic emissions and coal combustion. Health risk assessment showed carcinogenic risk under limit value in all cases.

Association of long-term exposure to local industry- and traffic-specific particulate matter with arterial blood pressure and incident hypertension

BACKGROUND

Long-term exposure to fine particulate matter (PM2.5) may lead to increased blood pressure (BP). The role of industry- and traffic-specific PM2.5 remains unclear.

OBJECTIVE

We investigated the associations of residential long-term source-specific PM2.5 exposure with arterial BP and incident hypertension in the population-based Heinz Nixdorf Recall cohort study.

METHODS

We defined hypertension as systolic BP≥140mmHg, or diastolic BP≥90mmHg, or current use of BP lowering medication. Long-term concentrations of PM2.5 from all local sources (PM2.5ALL), local industry (PM2.5IND) and traffic (PM2.5TRA) were modeled with a dispersion and chemistry transport model (EURAD-CTM) with a 1km(2) resolution. We performed a cross-sectional analysis with BP and prevalent hypertension at baseline, using linear and logistic regression, respectively, and a longitudinal analysis with incident hypertension at 5-year follow-up, using Poisson regression with robust variance estimation. We adjusted for age, sex, body mass index, lifestyle, education, and major road proximity. Change in BP (mmHg), odds ratio (OR) and relative risk (RR) for hypertension were calculated per 1μg/m(3) of exposure concentration.

RESULTS

PM2.5ALL was highly correlated with PM2.5IND (Spearman's ρ=0.92) and moderately with PM2.5TRA (ρ=0.42). In adjusted cross-sectional analysis with 4539 participants, we found positive associations of PM2.5ALL with systolic (0.42 [95%-CI: 0.03, 0.80]) and diastolic (0.25 [0.04, 0.46]) BP. Higher, but less precise estimates were found for PM2.5IND (systolic: 0.55 [-0.05, 1.14]; diastolic: 0.35 [0.03, 0.67]) and PM2.5TRA (systolic: 0.88 [-1.55, 3.31]; diastolic: 0.41 [-0.91, 1.73]). We found crude positive association of PM2.5TRA with prevalence (OR 1.41 [1.10, 1.80]) and incidence of hypertension (RR 1.38 [1.03, 1.85]), attenuating after adjustment (OR 1.19 [0.90, 1.58] and RR 1.28 [0.94, 1.72]). We found no association of PM2.5ALL and PM2.5IND with hypertension.

CONCLUSIONS

Long-term exposures to all-source and industry-specific PM2.5 were positively related to BP. We could not separate the effects of industry-specific PM2.5 from all-source PM2.5. Estimates with traffic-specific PM2.5 were generally higher but inconclusive.