This study investigates PM2.5-bound PAHs for rural sites (Dacheng and Fangyuan) positioned close to heavy air-polluting industries in Changhua County, central Taiwan. A total of 113 PM2.5 samples with 22 PAHs collected from 2014 to 2015 were analyzed, and Positive Matrix Factorization (PMF) and diagnostic ratios of PAHs were applied to quantify potential PAH sources. The influences of local and regional sources were also explored using the conditional probability function (CPF) and potential source contribution function (PSCF) with PMF-modeled results, respectively. Annual mean concentrations of total PAHs were 2.91 ± 1.34 and 3.04 ± 1.40 ng/m3 for Dacheng and Fangyuan, respectively, and their corresponding BaPeq were measured at 0.534 ± 0.255 and 0.563 ± 0.273 ng/m3 in concentration. Seasonal variations with higher PAHs found for the winter than for the spring and summer were observed for both sites. The lifetime excess cancer risk (ECR) from inhalation exposure to PAHs was recorded as 4.7 × 10−5 overall. Potential sources of PM2.5-bound PAHs include unburned petroleum and traffic emissions (42%), steel industry and coal combustion (31%), and petroleum and oil burning (27%), and unburned petroleum and traffic emission could contribute the highest ECR (2.4 × 10−5). The CPF results show that directional apportionment patterns were consistent with the actual locations of local PAH sources. The PSCF results indicate that mainly northeastern regions of China have contributed elevated PM2.5-bound PAHs from long-range transports.

Polycyclic aromatic hydrocarbons (PAHs) were studied in 230 daily fine particulate matter (PM2.5) samples collected in four seasons at urban and suburban sites of Shanghai, China. This study focused on the emission sources of PAHs and its dynamic results under different weather conditions and pollution levels and also emphasized on the spatial sources of PM2.5 and PAHs at a regional level. Annual concentrations of PM2.5 and 16 EPA priority PAHs were 53 μg/m3 and 6.9 ng/m3, respectively, with highest levels in winter. Positive matrix factorization (PMF) modeling identified four sources of PAHs: coal combustion, traffic, volatilization and biomass combustion, and coking, with contributions of 34.9%, 27.5%, 21.1% and 16.5%, respectively. The contribution of traffic, a local-indicative source, increased from 17.4% to 28.7% when wind speed changed from >2m/s to <2m/s, and increased from 18.3% to 31.3% when daily PAH concentrations changed from below to above the annual mean values. This indicated that local sources may have larger contributions under stagnant weather when poorer dispersion conditions and lower wind speed led to the accumulation of local-emitted pollutants. The trajectory clustering and potential source contribution function (PSCF) and concentration weighted trajectory (CWT) models showed clearly that air parcels moved from west had highest concentrations of PM2.5, total PAHs and high molecular weight (HMW) PAHs. While small differences were found among all five clusters in low molecular weight (LMW) PAHs. Sector analyses determined that regional transport source contributed 39.8% to annual PM2.5 and 52.5% to PAHs, mainly from western regions and varying with seasons. This work may make contribution to a better understanding and control of the increasingly severe air pollution in China as well as other developing Asian countries.

To investigate the size distributions of chemical compositions and sources of particulate matter (PM) at ground level and from the urban canopy, a study was conducted on a 255 m meteorological tower in Tianjin from December 2013 to January 2014. Thirteen sets of 8 size-segregated particles were collected with cascade impactor at 10 m and 220 m. Twelve components of particles, including water-soluble inorganic ions and carbonaceous species, were analyzed and used to apportion the sources of PM with positive matrix factorization. Our results indicated that the concentrations, size distributions of chemical compositions and sources of PM at the urban canopy were affected by regional transport due to a stable layer approximately 200 m and higher wind speed at 220 m. The concentrations of PM, Cl− and elemental carbon (EC) in fine particles at 10 m were higher than that at 220 m, while the reverse was true for NO3− and SO42−. The concentrations of Na+, Ca2+, Mg2+, Cl− and EC in coarse particles at 10 m were higher than that at 220 m. The size distributions of major primary species, such as Cl−, Na+, Ca2+, Mg2+ and EC, were similar at two different heights, indicating that there were common and dominant sources. The peaks of SO42−, NH4+, NO3− and organic carbon (OC), which were partly secondary generated species, shifted slightly to the smaller particles at 220 m, indicating that there was a different formation mechanism. Industrial pollution and coal combustion, re-suspended dust and marine salt, traffic emissions and transport, and secondary inorganic aerosols were the major sources of PM at both heights. With the increase in vertical height, the influence of traffic emissions, re-suspended dust and biomass burning on PM weakened, but the characteristics of regional transport from Hebei Province and Beijing gradually become obvious.

Air pollutants emitted from vehicles in street canyons may be reactive, undergoing mixing and chemical processing before escaping into the overlying atmosphere. The deterioration of air quality in street canyons occurs due to combined effects of proximate emission sources, dynamical processes (reduced dispersion) and chemical processes (evolution of reactive primary and formation of secondary pollutants). The coupling between dynamics and chemistry plays a major role in determining street canyon air quality, and numerical model approaches to represent this coupling are reviewed in this article. Dynamical processes can be represented by Computational Fluid Dynamics (CFD) techniques. The choice of CFD approach (mainly the Reynolds-Averaged Navier-Stokes (RANS) and Large-Eddy Simulation (LES) models) depends on the computational cost, the accuracy required and hence the application. Simplified parameterisations of the overall integrated effect of dynamics in street canyons provide capability to handle relatively complex chemistry in practical applications. Chemical processes are represented by a chemical mechanism, which describes mathematically the chemical removal and formation of primary and secondary species. Coupling between these aspects needs to accommodate transport, dispersion and chemical reactions for reactive pollutants, especially fast chemical reactions with time scales comparable to or shorter than those of typical turbulent eddies inside the street canyon. Different approaches to dynamical and chemical coupling have varying strengths, costs and levels of accuracy, which must be considered in their use for provision of reference information concerning urban canopy air pollution to stakeholders considering traffic and urban planning policies.

The Paranaguá Estuarine Complex (PEC) is an important socioeconomic estuary of the Brazilian coast that is influenced by the input of pollutants like polycyclic aromatic hydrocarbons (PAHs). Because of the apparent lack of comparative studies involving PAHs in different estuarine compartments, the aim of this study was to determine and compare PAH concentrations in surface sediment and suspended particulate material (SPM) in the PEC to evaluate their behaviour, compositions, sources and spatial distributions. The total PAH concentrations in the sediment ranged from 0.6 to 63.8 ng g−1 (dry weight), whereas in the SPM these concentrations ranged from 391 to 4164 ng g−1. Diagnostic ratios suggest distinct sources of PAHs to sediments (i.e., pyrolytic sources) and SPM (i.e., petrogenic sources such as vessel traffic). Thus, the recent introduction of PAHs is more clearly indicated in the SPM since oil related-compounds (e.g., alkyl-PAHs) remain present in similar concentrations. Further, this matrix may better reflect the current state of the environment at the time of sampling because of the absence of significant degradation.

Among urban stormwater pollutants, hydrocarbons are a significant environmental concern due to their toxicity and relatively stable chemical structure. This study focused on the identification of hydrocarbon contributing sources to urban road dust and approaches for the quantification of pollutant loads to enhance the design of source control measures. The study confirmed the validity of the use of mathematical techniques of principal component analysis (PCA) and hierarchical cluster analysis (HCA) for source identification and principal component analysis/absolute principal component scores (PCA/APCS) receptor model for pollutant load quantification. Study outcomes identified non-combusted lubrication oils, non-combusted diesel fuels and tyre and asphalt wear as the three most critical urban hydrocarbon sources. The site specific variabilities of contributions from sources were replicated using three mathematical models. The models employed predictor variables of daily traffic volume (DTV), road surface texture depth (TD), slope of the road section (SLP), effective population (EPOP) and effective impervious fraction (EIF), which can be considered as the five governing parameters of pollutant generation, deposition and redistribution. Models were developed such that they can be applicable in determining hydrocarbon contributions from urban sites enabling effective design of source control measures.

Three instrumented bicycles were used to measure black carbon (BC) and PM2.5 concentrations in a midsized city in southern Brazil. The objective of this study was to map the spatial distribution of BC and PM2.5, to identify air pollution hotspots and to assess factors that may affect the concentrations of these pollutants, e.g. traffic volume, number of heavy-duty diesel vehicles (HDDV), position of traffic signals and street incline. The cyclists collected data in the city centre along streets of different traffic density during nine sampling sessions in the weekday morning and afternoon rush hours, between March 13 and April 28, 2015. The sampling by bicycle covered an area of 2.70 km2, over variable elevation, and travelled a total distance of 215 km. BC and PM2.5 exhibited a large spatial variability on a scale of tens of metres and the concentrations were positively correlated with traffic counts, but exhibited a stronger relationship with the number of HDDV. These results imply that older buses and diesel-powered trucks may be the main driver behind the high pollution levels in the city's inner core. We observed a strong relationship between BC concentrations at junctions managed by traffic signals and the quantity of HDDV. The mean BC concentration was found to be 8.10 μg m−3 near traffic signals located on an inclined street (HDDV > 100 vehicles h−1) compared to traffic signals on flat terrain (6.00 μg m−3), which can be attributed to the higher acceleration required at the start of motion. This pattern was less evident for PM2.5 concentrations.

China has been embracing rapid motorization since the 1990s, and vehicles have become one of the major sources of air pollution problems. Since the late 1990s, thanks to the international experience, China has adopted comprehensive control measures to mitigate vehicle emissions. This study employs a local emission model (EMBEV) to assess China's first fifteen-year (1998–2013) efforts in controlling vehicles emissions. Our results show that China's total annual vehicle emissions in 2013 were 4.16 million tons (Mt) of HC, 27.4 Mt of CO, 7.72 Mt of NOX, and 0.37 Mt of PM2.5, respectively. Although vehicle emissions are substantially reduced relative to the without control scenarios, we still observe significantly higher emission density in East China than in developed countries with longer histories of vehicle emission control. This study further informs China's policy-makers of the prominent challenges to control vehicle emissions in the future. First, unlike other major air pollutants, total NOX emissions have rapidly increased due to a surge of diesel trucks and the postponed China IV standard nationwide. Simultaneous implementation of fuel quality improvements and vehicle-engine emission standards will be of great importance to alleviate NOX emissions for diesel fleets. Second, the enforcement of increasingly stringent standards should include strict oversight of type-approval conformity, in-use complacence and durability, which would help reduce gross emitters of PM2.5 that are considerable among in-use diesel fleets at the present. Third, this study reveals higher HC emissions than previous results and indicates evaporative emissions may have been underestimated. Considering that China's overall vehicle ownership is far from saturation, persistent efforts are required through economic tools, traffic management and emissions regulations to lower vehicle-use intensity and limit both exhaust and evaporative emissions. Furthermore, in light of the complex technology for emerging new energy vehicles, their real-world emissions need to be adequately evaluated before massive promotion.

CicLAvia in Los Angeles, CA is the open streets program that closes streets to motorized vehicles and invites people to walk, run, play or ride their bicycles on these streets, allowing them to experience the city in a new way and get exercise at the same time. Since the events reduce the motorized traffic flow, which is a significant source of air pollution, on the streets, it is reasonable to hypothesize that the CicLAvia events can reduce the concentrations of traffic-emitted air pollutants during the road closure. This study is the first experiment to test this hypothesis. The on-road and community-wide ultrafine particle (UFP) and PM2.5 were measured on the Event-Sunday (October 5th, 2014) and the Pre- and Post- Sundays (September 28ᵗʰ and October 12ᵗʰ, 2014). Data analysis results showed the on-road UFP and PM2.5 reduction was 21% and 49%, respectively, and the community-wide PM2.5 reduction was 12%.

The unintended influence of exhaust plumes emitted from a vehicle ahead to on-road air quality surveying data measured with a mobile laboratory (ML) at 20–40 km h−1 in dense traffic areas was investigated by experiment and life-sized computational fluidic dynamics (CFD) simulation. The ML equipped with variable sampling inlets of five columns by four rows was used to measure the spatial distribution of CO2 and NOx concentrations when following 5–20 m behind a sport utility vehicle (SUV) as an emitter vehicle equipped with a portable emission monitoring system (PEMS). The PEMS measured exhaust gases at the tailpipe for input data of the CFD simulations. After the CFD method was verified with experimental results of the SUV, dispersion of exhaust plumes emitted from a bus and a sedan was numerically analyzed.More dilution of the exhaust plume was observed at higher vehicle speeds, probably because of eddy diffusion that was proportional to turbulent kinetic energy and vehicle speed. The CO2 and NOx concentrations behind the emitter vehicle showed less overestimation as both the distance between the two vehicles and their background concentrations increased. If the height of the ML inlet is lower than 2 m and the ML travels within 20 m behind a SUV and a sedan ahead at 20 km h−1, the overestimation should be considered by as much as 200 ppb in NOx and 80 ppm in CO2. Following a bus should be avoided if possible, because effect of exhaust plumes from a bus ahead could not be negligible even when the distance between the bus and the ML with the inlet height of 2 m, was more than 40 m. Recommendations are provided to avoid the unintended influence of exhaust plumes from vehicles ahead of the ML during on-road measurement in urban dense traffic conditions.