Local Traffic Emissions Research Articles

Source apportionment of PM2.5 and PM10 pollutants near an urban roadside site using positive matrix factorization

This paper presents results from a comprehensive study of source apportionment of particulate matter (PM) of size PM2.5 and PM10 near a busy highway in Sharjah, United Arab Emirates. Source apportionment was carried out using US Environmental Protection Agency (EPA) Positive Matrix Factorization model. Furthermore, backward trajectory analysis and Potential Source Contribution Function were used to assess air mass transport pathways and identify potential source regions, respectively. The results revealed six major sources for PM2.5, including traffic, sea salt, fugitive dust, secondary aerosols, heavy oil combustion and mineral dust. For PM10, four major sources were identified, including secondary aerosols, traffic, sea salt and mineral dust. Traffic emissions were found to be significant contributors to both PM2.5 and PM10 pollution, along with natural sources like sea salt and mineral dust. Backward trajectory analysis indicated the influence of different wind regimes on air mass transport, with contributions from regions like Arabian Gulf, Arabian Sea, Oman and Iran. The Conditional Bivariate Probability Function analysis further explained the impact of local traffic emissions and other sources on PM pollution under varying wind conditions.

Mobile measurement background quantification methods for determining local traffic emissions and background source contributions to ammonia

On-road ammonia (NH3) could be critical for public health in high-population areas due to its contribution to fine particulate matter (PM2.5) formation. Therefore, quantifying the impact of vehicular NH3 emissions on pollution levels is vital from both policy and exposure perspectives. In this study, we conducted night- and daytime mobile measurements during a pollution episode in March 2021, explored common data processing strategies for background concentration estimation and calculated the vehicle contribution in urban Beijing. Percentile and time–frequency methods were evaluated and applied to separate local vehicle and background concentrations. The spatial distributions differed between the night- and daytime periods. However, vehicular emissions were an important source of NH3 both at night and during the day. In the pollution accumulation process, the vehicle contribution increased to 27.4%. Even though local traffic emissions notably impacted NH3 levels, the background concentration, including regional transport, was the largest contributor to NH3 at the city scale. This study has implications for local and regional NH3 control strategies aimed at reducing pollution in densely populated urban areas.

Impact of single and combined local air pollution mitigation measures in an urban environment

Urban air pollution is one of the most important environmental problems for human health and several strategies have been developed for its mitigation. The objective of this study is to assess the impact of single and combined mitigation measures on concentrations of air pollutants emitted by traffic at pedestrian level in the same urban environment. The effectiveness of different scenarios of green infrastructure (GI), the implementation of photocatalytic materials and traffic low emission zones (LEZ) are investigated, as well as several combinations of LEZ and GI. A wide set of scenarios is simulated through Computational Fluid Dynamics (CFD) modelling for two different wind directions (perpendicular (0°) and 45° wind directions). Wind flow for the BASE scenario without any measure implemented was previously evaluated using wind-tunnel measurements. Air pollutant concentrations for this scenario are compared with the results obtained from the different mitigation scenarios. Reduction of traffic emissions through LEZ is found to be the most effective single measure to improve local air quality. However, GI enhances the effects of LEZ, which makes the combination of LEZ + GI a very effective measure. The effectiveness of this combination depends on the GI layout, the intensity of emission reduction in the LEZ and the traffic diversion in streets surrounding the LEZ. These findings, in line with previous literature, suggest that the implementation of GI may increase air pollutant concentrations at pedestrian level for some cases. However, this study highlights that this negative effect on air quality can turn into positive when used in combination with reductions of local traffic emissions.

Improving 3-day deterministic air pollution forecasts using machine learning algorithms

Abstract. As air pollution is regarded as the single largest environmental health risk in Europe it is important that communication to the public is up to date and accurate and provides means to avoid exposure to high air pollution levels. Long- and short-term exposure to outdoor air pollution is associated with increased risks of mortality and morbidity. Up-to-date information on present and coming days' air quality helps people avoid exposure during episodes with high levels of air pollution. Air quality forecasts can be based on deterministic dispersion modelling, but to be accurate this requires detailed information on future emissions, meteorological conditions and process-oriented dispersion modelling. In this paper, we apply different machine learning (ML) algorithms – random forest (RF), extreme gradient boosting (XGB), and long short-term memory (LSTM) – to improve 1, 2, and 3 d deterministic forecasts of PM10, NOx, and O3 at different sites in Greater Stockholm, Sweden. It is shown that the deterministic forecasts can be significantly improved using the ML models but that the degree of improvement of the deterministic forecasts depends more on pollutant and site than on what ML algorithm is applied. Also, four feature importance methods, namely the mean decrease in impurity (MDI) method, permutation method, gradient-based method, and Shapley additive explanations (SHAP) method, are utilized to identify significant features that are common and robust across all models and methods for a pollutant. Deterministic forecasts of PM10 are improved by the ML models through the input of lagged measurements and Julian day partly reflecting seasonal variations not properly parameterized in the deterministic forecasts. A systematic discrepancy by the deterministic forecasts in the diurnal cycle of NOx is removed by the ML models considering lagged measurements and calendar data like hour and weekday, reflecting the influence of local traffic emissions. For O3 at the urban background site, the local photochemistry is not properly accounted for by the relatively coarse Copernicus Atmosphere Monitoring Service ensemble model (CAMS) used here for forecasting O3 but is compensated for using the ML models by taking lagged measurements into account. Through multiple repetitions of the training process, the resulting ML models achieved improvements for all sites and pollutants. For NOx at street canyon sites, mean squared error (MSE) decreased by up to 60 %, and seven metrics, such as R2 and mean absolute percentage error (MAPE), exhibited consistent results. The prediction of PM10 is improved significantly at the urban background site, whereas the ML models at street sites have difficulty capturing more information. The prediction accuracy of O3 also modestly increased, with differences between metrics. Further work is needed to reduce deviations between model results and measurements for short periods with relatively high concentrations (peaks) at the street canyon sites. Such peaks can be due to a combination of non-typical emissions and unfavourable meteorological conditions, which are rather difficult to forecast. Furthermore, we show that general models trained using data from selected street sites can improve the deterministic forecasts of NOx at the station not involved in model training. For PM10 this was only possible using more complex LSTM models. An important aspect to consider when choosing ML algorithms is the computational requirements for training the models in the deployment of the system. Tree-based models (RF and XGB) require fewer computational resources and yield comparable performance in comparison to LSTM. Therefore, tree-based models are now implemented operationally in the forecasts of air pollution and health risks in Stockholm. Nevertheless, there is big potential to develop generic models using advanced ML to take into account not only local temporal variation but also spatial variation at different stations.

A two-way coupled regional urban–street network air quality model system for Beijing, China

Abstract. Owing to the substantial traffic emissions in urban areas, especially near road areas, the concentrations of pollutants, such as ozone (O3) and its precursors, have a large difference compared to regional averages, and their distributions cannot be captured accurately by traditional single-scale air quality models. In this study, a new version of a regional urban–street network model (an Integrated Air Quality Modeling System coupling regional urban–street: IAQMS-street v2.0) is presented. An upscaling module is implemented in IAQMS-street v2.0 to calculate the impact of mass transfer to regional scale from street network. The influence of pollutants in the street network is considered in the concentration calculation on the regional scale, which is not considered in a previous version (IAQMS-street v1.0). In this study, the simulated results in Beijing during August 2021, using IAQMS-street v2.0, IAQMS-street v1.0, and the regional model (Nested Air Quality Prediction Modeling System, NAQPMS), are compared. On-road traffic emissions in Beijing, as the key model input data, were established using intelligent image-recognition technology and real-time traffic big data from navigation applications. The simulated results showed that the O3 and nitrogen oxide (NOx) concentrations in Beijing were reproduced by using IAQMS-street v2.0 on both the regional scale and street scale. The prediction fractions within a factor of 2 (FAC2s) between simulations and observations of NO and NO2 increased from 0.11 and 0.34 in NAQPMS to 0.78 and 1.00 in IAQMS-street v2.0, respectively. The normalized mean biases (NMBs) of NO and NO2 decreased from 2.67 and 1.33 to −0.25 and 0.08. In the coupled model, the concentration of NOx at the street scale is higher than that at the regional scale, and the simulated distribution of pollutants on a regional scale was improved in IAQMS-street v2.0 when compared with that in IAQMS-street v1.0. We further used IAQMS-street v2.0 to quantify the contribution of local on-road traffic emissions to the O3 and NOx emissions and analyze the effect of traffic regulation policies in Beijing. Results showed that heavy-duty trucks are the major source of on-road traffic emissions of NOx. The relative contributions of local traffic emissions to NO2, NO, and O3 concentrations were 53.41 %, 57.45 %, and 8.49 %, respectively. We found that traffic regulation policies in Beijing largely decreased the concentrations of NOx and hydrocarbons (HC); however, the O3 concentration near the road increased due to the decrease consumption of O3 by NO. To decrease the O3 concentration in urban areas, controlling the local emissions of HC and NOx from other sources requires consideration.

Measurement report: Black carbon properties and concentrations in southern Sweden urban and rural air – the importance of long-range transport

Abstract. Soot, or black carbon (BC), aerosol is a major climate forcer with severe health effects. The impacts depend strongly on particle number concentration, size and mixing state. This work reports on two field campaigns at nearby urban and rural sites, 65 km apart, in southern Sweden during late summer 2018. BC was measured using a single-particle soot photometer (SP2) and Aethalometers (AE33). Differences in BC concentrations between the sites are driven primarily by local traffic emissions. Equivalent and refractory BC mass concentrations at the urban site were on average a factor 2.2 and 2.5, with peaks during rush hour up to a factor ∼4, higher than the rural background levels. The number fraction of particles containing a soot core was significantly higher in the city. BC particles at the urban site were on average smaller by mass and had less coating owing to fresh traffic emissions. The organic components of the fresh traffic plumes were similar in mass spectral signature to hydrocarbon-like organic aerosol (HOA), commonly associated with traffic. Despite the intense local traffic (∼ 30 000 vehicles passing per day), PM1, including organic aerosol, was dominated by aged continental air masses even at the curbside site. The fraction of thickly coated particles at the urban site was highly correlated with the mass concentrations of all measured chemical species of PM1, consistent with aged, internally mixed aerosol. Trajectory analysis for the whole year showed that air masses arriving at the rural site from eastern Europe contained approximately double the amount of BC compared to air masses from western Europe. Furthermore, the largest regional emissions of BC transported to the rural site, from the Malmö–Copenhagen urban area, are discernible above background levels only when precipitation events are excluded. We show that continental Europe and not the Malmö–Copenhagen region is the major contributor to the background BC mass concentrations in southern Sweden.

Continuous Measurements and Source Apportionment of Ambient PM2.5-Bound Elements in Windsor, Canada

Ambient fine particulate matter (PM2.5) levels in Windsor, Ontario, Canada, are impacted by local emissions and regional/transboundary transport input and also attributable to secondary formation. PM2.5-bound elements were monitored hourly in Windsor from April to October 2021. Observed concentrations of the elements were generally comparable to historical measurements at urban sites in Ontario. A clear diurnal pattern was observed for most of the elements, i.e., high in the morning and low in the afternoon, mostly related to evolution of atmospheric mixing heights and local anthropogenic activities. Conversely, sulfur showed elevated levels in the afternoon, suggesting conversion of gaseous sulfur dioxide to particulate sulphate was enhanced by increased ambient temperatures. Five source factors were resolved using the US EPA positive matrix factorization model, including three traffic-related sources (i.e., vehicular exhaust, crustal dust, and vehicle tire and brake wear factors) and two industrial sources (i.e., coal/heavy oil burning and metal processing factors). Overall, the three traffic-related sources were mostly local and contributed to 47% of the total elemental concentrations, while the two industrial sources may originate from regional/transboundary sources and contributed to 53%. Measures to control both local traffic emissions and regional/transboundary industrial sources would help reduce levels of PM2.5-bound elements in Windsor.

Variations in PM2.5 Composition and Sources During 2020-2021 COVID-19 Epidemic Periods in Nanjing

To understand the changes in chemical composition and sources of PM2.5 under the extreme reduction background during the COVID-19 epidemic periods in Nanjing, hourly observation results of PM2.5 components (water-soluble inorganic ions, carbonaceous components, and inorganic elements) of two epidemic events from January to March 2020 and June to August 2021 were analyzed. In comparison to that during pre-epidemic periods, the concentration of NO3- during the two epidemic control periods decreased by 52.9% and 43.0%, respectively, which was larger than the decreases in NH4+(46.4% and 31.6%) and SO42-(33.8% and 16.5%). Since the observation site was located close to a main road, the decrease in elemental carbon (EC, 35.4% and 20.6%) was higher than that in organic carbon (OC, 11.1% and 16.2%). In reference to the variations in the characteristic ratios of the bulk components mentioned above, the epidemic control showed a more substantial influence on traffic emissions than industrial activities. The concentration time series of PM2.5 major components over the epidemic periods indicated that NOx from local traffic emissions had substantial contributions to the formation of NO3-, which led to local short-term PM2.5 pollution. In addition, the positive matrix factorization (PMF) model was used to analyze the hourly observation data of PM2.5 components. The seven identified factors were linked with metallurgy, firework and firecracker combustions, road traffic emissions, coal combustion, dust resuspension, secondary sulfate, and secondary nitrate. Because the nitrate was unstable under high temperature, the contribution of secondary nitrate to PM2.5 during the epidemic control period of 2021 (summer, 21.2%) was much lower than that during the epidemic control period of 2020 (winter, 60.6%); however, the formation of secondary components always dominated the contribution of PM2.5 sources. Therefore, emissions of NOx and SO2 should be further controlled to continuously reduce ambient PM2.5 concentrations in Chinese cities.

Elemental composition of the topsoil fine fraction at and around the Tibetan plateau

The <20 μm fractions of crusted topsoils on and around the Tibetan Plateau (TP) were analyzed to take a broad view of the composition of major elements (MEs, Al, Fe, and Mn) and twelve trace elements (TEs, As, Ba, Cd, Co, Cr, Cu, Ni, Pb, Sr, U, V, and Zn) and provide a crustal reference for environmental quality evaluation. The concentrations of most elements were generally higher in the Yarlung Zangbo River watershed (YZRW) and Pamirs but lower in the central Tibetan Plateau (CTP), Qaidam Basin (QB), and Tarim Basin (TB) due to the natural geochemical process. The concentrations of most elements in the five regions were higher than those of the upper continental crust (UCC), which was mainly affected by two natural factors. One was that the wide distribution of shale, schist, and phyllite on the TP led to the high concentrations of As and Cr. The other was that the concentrations of most elements in the <20 μm fractions of crusted topsoils were affected by particle sorting. Cu, Cd, As, and Pb in a few sites of the YZRW were influenced by local traffic emissions, mining operations, and increasing fossil fuel combustion over the past three decades (i.e., the 1980s–2010s). Furthermore, the values of crust‒referenced enrichment factor (EFucc) of most TEs (except Ba and Sr) in different environmental media with a high proportion of fine particles, such as aerosols, snow and ice cores, and river and lake sediments were generally 1.2–24.2 times greater than the values of fine fraction (<20 μm)‒referenced enrichment factor (EF < 20 μm), suggesting that the degree of anthropogenic effects on the TP environment should be overestimated in previous assessments using the UCC as the reference.

Assessment of carbonaceous aerosols at Mukteshwar: A high-altitude (~2200 m amsl) background site in the foothills of the Central Himalayas

The present study examined the equivalent black carbon (eBC) mass concentrations measured over 10.5 years (September 2005–March 2016) using a 7-wavelength Aethalometer (AE-31) at Mukteshwar, a high-altitude and regional background site in the foothills of Indian central Himalayas. The total spectral absorption coefficient (babs) was divided into three categories: black carbon (BC) and brown carbon (BrC); fossil fuels (FF) and wood/biomass burning (WB/BB); and primary and secondary sources. At the wavelength of 370 nm, a significant BrC contribution (25 %) to the total babs is identified, characterized by a pronounced seasonal variation with winter (December–January-February) maxima (31 %) and post-monsoon (October and November) minima (20 %); whereas, at 660 nm, the contribution of BrC is dramatically less (9 %). Climatologically, the estimated BCFF at 880 nm ranges from 0.25 ± 0.19 μg m−3 in July to 1.17 ± 0.80 μg m−3 in May with the annual average of 0.67 ± 0.63 μg m−3, accounting for 79 % of the BC mass. The maximum BCFF/BC fraction reaches its peak value during the monsoon (July and August, 85 %), indicating the dominance of local traffic emissions due to tourism activities. Further, the highest BCWB concentration observed during pre-monsoon (March–May) suggests the influence of local forest fires along with long-range transported aerosols from the low-altitude plains. The increased contribution of BrC (26 % at 370 nm) and WB absorption (61 % at 370 nm) to the total absorption at the shorter wavelengths suggests that wood burning is one of the major sources of BrC emissions. Secondary BrC absorption accounts for 24 % [91 %] of the total absorption [BrC absorption] at 370 nm, implying the dominance of secondary sources in BrC formation. A trend analysis for the measured BC concentration shows a statistically significant increasing trend with a slope of 0.02 μgm−3/year with a total increase of about 22 % over the study period. A back trajectory-based receptor model, potential source contribution function (PSCF), was used to identify the potential regional source region of BC. The main source regions of BC are the northwest states of India in the IGP region and the northeast Pakistan region.

Effect of COVID-19 pandemic restrictions on air pollution at a local scale in urban areas affected by high-intensity vehicle traffic in Poland

The lockdown in 2020 implemented due to the SARS-CoV-2 pandemic has resulted in a significant improvement in air quality at a global scale. Nationwide lockdown also considerably improved air quality at a local scale, especially in cities which were almost completely shut down during the first coronavirus wave, with nearly no activity. We tested the hypothesis that a reduction in the intensity of vehicle traffic causes a drastic decrease in urban air pollution at a local scale. We focused on two urban agglomerations, Warsaw and Cracow, in Poland. Data of the concentrations of traffic-related sources, namely NOx, PM10, and PM2.5, obtained from two air pollution monitoring stations were analyzed for the years 2020 and 2021, during which lockdown and pandemic restrictions were in effect, and for 2019, as a reference. In the years 2020–2021, the average annual concentration of NOx was decreased by ~ 19%, PM2.5 by ~ 19%, and PM10 by ~ 18% in Warsaw, while in Cracow the average annual concentration of NOx was decreased by ~ 16%, PM2.5 by ~ 22%, and PM10 by ~ 2%, compared to 2019. The contribution from traffic-related sources to the overall level of air pollution was estimated. The results indicated that ~ 30 µg/m3 of PM10, ~ 15 µg/m3 of PM2.5, and ~ 120 µg/m3 of NOx in Cracow, and ~ 20 µg/m3 of PM2.5 in Warsaw originate from moving vehicles. The nationwide lockdown allowed us to conduct this study to understand how a reduction in local traffic emissions can decrease ambient air pollution levels.

An evaluation of the impact of traffic on the distribution of PAHs and oxygenated PAHs in the soils and moss of the southeast Tibetan Plateau

Contaminants in high-altitude mountains such as the Tibetan Plateau (TP) have attracted extensive attention due to their potential impact on fragile ecosystems. Rapid development of the economy and society has promoted pollution caused by local traffic emissions in the TP. Among the pollutants emitted by traffic, polycyclic aromatic hydrocarbons (PAHs) and oxygenated PAHs (OPAHs) are of particular concern due to their high toxicity. The TP provides an environment to explore the degree and range of contribution for traffic-induced PAHs and OPAHs. In this study, soils and moss were collected at different altitudes and distances from the G318 highway in the southeast TP. The total concentrations of PAHs (∑16PAHs) and OPAHs (∑6OPAHs) in soils were in the range of 3.29–119 ng/g dry weight (dw) and 0.54–9.65 ng/g dw, respectively. ∑16PAH and ∑6OPAH concentrations decreased logarithmically with increasing distance from traffic. A significantly positive correlation between ∑16PAHs and altitude was found at sampling points closest to traffic. Dominant PAHs constituents in soil and moss included chrysene (CHR), benzo[g,h,i]perylene (BghiP), and benzo[b]fluoranthene (BbF); prevalent OPAH compounds were 9-fluorenone (9-FO) and 9,10-anthraquinone (ATQ). These compounds were related to characteristics of traffic emissions. The multiple diagnosis ratio and correlation analysis showed that exhaust emissions were the main source of the PAHs and OPAHs in the studied environment. PMF modeling quantification of the relative contribution of traffic emissions to PAHs in roadside soils was 45 % on average. The present study characterized the extent and range of traffic-induced PAH and OPAH emissions, providing valuable information for understanding the environmental behaviors and potential risks of traffic-related contaminants in high-altitude areas.

Ice-nucleating particles from multiple aerosol sources in the urban environment of Beijing under mixed-phase cloud conditions

Abstract. Ice crystals occurring in mixed-phase clouds play a vital role in global precipitation and energy balance because of the unstable equilibrium between coexistent liquid droplets and ice crystals, which affects cloud lifetime and radiative properties, as well as precipitation formation. Satellite observations proved that immersion freezing, i.e., ice formation on particles immersed within aqueous droplets, is the dominant ice nucleation (IN) pathway in mixed-phase clouds. However, the impact of anthropogenic emissions on atmospheric IN in the urban environment remains ambiguous. In this study, we present in situ observations of ambient ice-nucleating particle number concentration (NINP) measured at mixed-phase cloud conditions (−30 ∘C, relative humidity with respect to liquid water RHw= 104 %) and the physicochemical properties of ambient aerosol, including chemical composition and size distribution, at an urban site in Beijing during the traditional Chinese Spring Festival. The impact of multiple aerosol sources such as firework emissions, local traffic emissions, mineral dust, and urban secondary aerosols on NINP is investigated. The results show that NINP during the dust event reaches up to 160 # L−1 (where “#” represents number of particles), with an activation fraction (AF) of 0.0036 % ± 0.0011 %. During the rest of the observation, NINP is on the order of 10−1 to 10 # L−1, with an average AF between 0.0001 % and 0.0002 %. No obvious dependence of NINP on the number concentration of particles larger than 500 nm (N500) or black carbon (BC) mass concentration (mBC) is found throughout the field observation. The results indicate a substantial NINP increase during the dust event, although the observation took place at an urban site with high background aerosol concentration. Meanwhile, the presence of atmospheric BC from firework and traffic emissions, along with urban aerosols formed via secondary transformation during heavily polluted periods, does not influence the observed INP concentration. Our study corroborates previous laboratory and field findings that anthropogenic BC emission has a negligible effect on NINP and that NINP is unaffected by heavy pollution in the urban environment under mixed-phase cloud conditions.

Chemical characteristics and oxidative potential of indoor and outdoor PM2.5 in densely populated urban slums

A significant proportion of population in metropolitan cities in India live in slums which are highly dense and crowded informal housing settlements with poor environmental conditions including high exposure to air pollution. Recent studies report that toxicity is induced by oxidative processes, mediated by the water-soluble PM chemical components leading to reactive oxygen species production thereby causing inflammatory disorders. Hence, for the first time, this study assessed the chemical characteristics and oxidative potential (OP) of indoor and outdoor PM2.5 in two slums in Mumbai, India. Daily gravimetric PM2.5 was measured in ∼40 homes each in a low- and a high-traffic slum and analysed for 18 water-soluble elements and organic carbon (WSOC). Subsequently, OP was assessed through the Dithiothreitol (DTT) assay. Average WSOC was similar in indoor and outdoor environments while the water-soluble concentrations of total elements ranged 4.5–6.5 μg/m3 indoors and 6.4–19.2 μg/m3 outdoors, with S, Ca, K, Na and Zn being the most abundant elements. Spatial distributions of indoor concentrations were influenced by outdoor sources such as local traffic emissions for Cd, Fe, Al and Zn. The influence of outdoor-origin particles was enhanced in homes reporting high air exchange rates. OP was higher outdoors than indoors in both low-traffic slum (0.04–0.51 nmol min−1m−3 outdoors and 0.02–0.38 nmol min−1m−3 indoors) and high-traffic slum (0.03–1.06 nmol min−1m−3 outdoors and 0.04–0.77 nmol min−1m−3 indoors). Outdoor and indoor OP was also more influenced by outdoor road dust showing significant correlation with tracer elements Cu and Al (r ≥ 0.45; p < 0.05). Similar to OP, the non-carcinogenic health risk associated with indoor PM2.5 were also higher in high-traffic slum (Hazard Index, HI = 1.60) than in low-traffic slum (HI = 0.43). Overall, this study shows that the indoor PM2.5 and its chemical constituents in Mumbai slums are primarily of outdoor origin with higher toxicity and non-carcinogenic health risk in high-traffic slums.

Characterizing spatiotemporal variability in airborne heavy metal concentration: Changes after 18 Years in Baltimore, MD

IntroductionThis study investigates the impact of changes in local industry, urban development, and proximity to suspected emission sources on airborne metal concentration in Baltimore, Maryland between 2001 and 2019 with particular focus on the urban industrial community of Curtis Bay in South Baltimore. MethodsIntegrated PM2.5 and PM10 Harvard Impactors were set up at six locations in the Baltimore City metropolitan area in weeklong sampling sessions from January–July 2019 to assess variation in airborne metal concentration by proximity to suspected metal emission sources. PM2.5 and PM10 were collected on Teflo filters and analyzed for a panel of 12 metals and metalloids (As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sb, and Zn) using inductively coupled plasma mass spectrometry. The findings were compared against airborne metal concentrations reported by the Baltimore Supersite in 2001 and 2003 to assess changes over the 18-year period. ResultsPM2.5 concentrations reported from this study ranged from 3.27 μg/m3 to 36.0 μg/m3 and PM10 concentrations ranged from 9.00 μg/m3 to 30.1 μg/m3 across all sampling sites. Metal concentrations ranged from 1.4 times (Cd) to 4.8 times (Cr) higher in PM10 compared to PM2.5. Compared to the study reference site, median PM2.5 concentrations of Co and Fe were roughly 1.8 times and 2.1 times higher, respectively, at near-road sampling sites indicating significant variability in airborne metal concentration by proximity to local traffic emissions. PM2.5 and PM10 Sb concentrations were 3.4 times and 6.7 times higher at a near incinerator site compared to the reference, consistent with existing evidence of Sb sourcing from municipal incinerators in Baltimore City. Decreases in Cr (−40%), Ni (−73%), Pb (−55%), and Zn (−36%) concentrations were observed over the 18-year period while concentrations of Cu, Fe, and Mn were not statistically significantly different. ConclusionDeclines in airborne Cr, Ni, Pb, and Zn concentration since 2001 appear to coincide with industrial decline highlighting the success of remediation and redevelopment efforts. Remaining spatial variability is related to vehicular traffic and proximity to a municipal incinerator which should be focal areas for future intervention to reduce metal exposure disparities in Baltimore City.

Determination of local traffic emission and non-local background source contribution to on-road air pollution using fixed-route mobile air sensor network

Traffic-related air pollutants are major contributors to deteriorating urban air quality and pose a serious threat to pedestrians. From both a scientific and a regulatory standpoint, it is important and challenging to understand the contributions of local and non-local sources to accurately apportion specific sources such as traffic emissions contribution to on-road and near-road microenvironment air quality. In this study, we deployed mobile sensors on-board buses to monitor NO, NO2, CO and PM2.5 along ten important routes in Hong Kong. The measurements include two seasons: April 2017 and July 2017. Two types of baseline extraction methods were evaluated and applied to separate local and background concentrations. The results show NO and NO2 are locally dominated air pollutants in spring, constituting 72%–84% and 58%–71%, respectively, with large inter-road variation. PM2.5 and CO largely arise from background sources, which contribute 55%–65% and 73%–79% respectively. PM2.5 displays a homogeneous spatial pattern, and the contributions show seasonal change, decreasing during summer. Regional transport pollution is the primary contributor during high pollution episodes. Isolated vehicle plumes show highly skewed concentration distributions. There are characteristic polluted segments on routes and they are most evident at rush hours. The most polluted road segments (top 10%) cluster at tunnel entrances and congested points. Some of these polluted locations were observed in Hong Kong's Low Emission Zones and suggest limitations to the existing control strategies, which only address larger buses. Our work gives new insights in the importance of regional cooperation to improve background air pollution combined with local control strategies to improve roadside air quality in Hong Kong.

Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

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.

Specific sources of health risks induced by metallic elements in PM2.5 during the wintertime in Beijing, China

Haze pollution occurs frequently over northern China Plain (NCP) during winter, resulting in great threats to human health. So far, limited studies have linked between emission sources and health risks from ambient field measurements. In this work, PM2.5 samples were collected in Beijing in the 2018 winter; 23 metallic elements were determined to assess the health risks induced by PM-bound metals. During the sampling period, metallic elements constituted a minor fraction (5%) in PM2.5, but exhibited significant threats to human health. The cancer risk (CR) value induced by PM-bound metals was 1.41 × 10−4 for adults and 2.59 × 10−4 for children while non-cancer risk (NCR) was 2.59 for adults and 3.37 for children. Nickel (Ni), As and Cr(IV) were the major contributing elements to carcinogenic risk. Arsenic (As) contributed a major (57%) of NCR for children, and Mn (30%), Ni (27%) and As (24%) were the major contributing species to NCR for adults. Using positive matrix factorization (PMF) model, traffic-related emission (25% for children and 30% for adults) and heavy oil combustion (39% for children and 28% for adults) were the dominant sources of CR values. Moreover, the CR value induced by local emissions was higher than that by long-range transported air pollution. Local traffic emission and long-range transported heavy oil combustion enhanced CR values, threatening the human health. As results, we highlighted that control of traffic emissions and heavy oil combustion on local and regional scales should be seriously considered by the Chinese government in reduction of health risk in Beijing.

Source-Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown.

The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles but coincided with Beijing experiencing “pandemic haze,” raising the public concerns about the effectiveness of imposed traffic policies to improve the air quality. This paper explores the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown based on an integrated analysis framework, which combines a real-time on-road emission inventory, in situ air quality observations, and a localized numerical modeling system. We found that traffic emissions decreased substantially during the COVID-19 pandemic, but its imbalanced emission abatement of NOx (76%, 125.3 Mg/day) and volatile organic compounds (VOCs, 53%, 52.9 Mg/day) led to a significant rise of atmospheric oxidants in urban areas, resulting in a modest increase in secondary aerosols due to inadequate precursors, which still offset reduced primary emissions. Moreover, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which was transported into Beijing and mainly responsible for the aggravated haze pollution. We recommend that mitigation policies should focus on accelerating VOC emission reduction and synchronously controlling regional sources to release the benefits of local traffic emission control.