Pilot study on road traffic emissions (PAHs,heavy metals) measured by using mosses in a tunnel experiment in Vienna,Austria

BACKGROUND, AIMS AND SCOPE: Over the last few years there has been extensive research for new indicators providing information about deposition resulting from road traffic and tunnel experiments received special attention in emission research. Mosses have been used for the estimation of atmospheric heavy metal and PAH depositions for more than three decades, although they were used only a few times for estimating ambient air pollution caused by traffic. In the current study, the suitability of using a moss species for monitoring road traffic emissions inside a tunnel was evaluated. This was a first-time ever attempt to use plants (mosses) as bioindicators in a tunnel experiment. Specifically, two relevant questions were examined: 1) Do mosses accumulate toxic substances derived from road traffic emissions under the extremely adverse conditions which can be found in a tunnel, and 2) Which substances can mainly be attributed to road traffic emissions and therefore be taken as efficient and reliable indicators for motor vehicles? METHODS: For the first time a biomonitor (the moss species Hylocomium splendens (Hedwig) B.S.G.) was used in a road tunnel experiment to analyse emissions from road traffic. Moss samples were exposed for four weeks in wooden frames (size 10 cm x 10 cm), covered by a thin plastic net with a mesh size of 1 cm x 1 cm. 17 elements, mainly heavy metals, and the 16 EPA-PAHs together with coronene were analysed by ICP-AES, AAS and GC-MSD. RESULTS: Enrichment factors, calculated by comparing post-experiment concentrations to those of a background site, were high for most PAHs, especially benzo(g,h,i)perylene (150.7), coronene (134.7), benzo(a)anthracene (125.0), indeno(1,2,3-c,d)pyrene (79.8), chrysene (78.1), pyrene (69.6) and benzo(b)-fluoranthene (67.4), and among the other elements for Sb (73.1), Mo (59.6), Cr (33.9), As (24.1), Cu (19.6), and Zn (17.1). All these substances can thus be taken as indicators for road traffic pollution. Concentrations were also significantly higher in the tunnel mosses for all investigated substances than along busy roads outside tunnels. Cluster analysis revealed groups of substances which could sensibly be attributed to various sources (abrasion processes, Diesel combustion) and enrichment in the various particle size classes. DISCUSSION: The extreme high concentrations in the analysed moss samples from inside the tunnel were due to higher concentrations in the ambient tunnel air, and the fact that already deposited chemical substances are not lost by rain, as well as efficient uptake capacities even under the extremely adverse conditions in a tunnel. In accordance with previous studies our results suggest that PAHs are better indicators for emissions from the burning process than heavy metals. CONCLUSIONS: As in open fields, mosses are suitable indicators for monitoring traffic emissions in tunnels. In addition to biomonitoring in open fields, in tunnel experiments mosses are even better indicators, because the confounding effects of other sources of pollution and the 'noise' in the accumulation process (e.g. washout through wet deposition) are minimised. The results of our study demonstrate the usefulness of mosses for surveying heavy metals and PAH emissions and deposition arising from road traffic sources, even under the extremely adverse conditions of the tunnel environment. RECOMMENDATION: It can be considered that biomonitors like mosses are a suitable alternative to technical particle filters inside tunnels. They are easy to handle, low in costs and valuable information regarding traffic emissions can be obtained. PERSPECTIVE: The results of this pilot-study proved the feasibility of the method, however, should be corroborated by further investigations based on a sample set that allows for generalization of the findings and might even include other moss species. A comparison of technical measurements with the biomonitoring method could lead to a more general acceptance of the results.     

Tracer-based source apportionment of polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China, using positive matrix factorization (PMF)

From 28 November to 23 December 2009, 24-h?PM_2.5 samples were collected simultaneously at six sites in Guangzhou. Concentrations of 18 polycyclic aromatic hydrocarbons (PAHs) together with certain molecular tracers for vehicular emissions (i.e., hopanes and elemental carbon), coal combustion (i.e., picene), and biomass burning (i.e., levoglucosan) were determined. Positive matrix factorization (PMF) receptor model combined with tracer data was applied to explore the source contributions to PAHs. Three sources were identified by both inspecting the dominant tracer(s) in each factor and comparing source profiles derived from PMF with determined profiles in Guangzhou or in the Pearl River Delta region. The three sources identified were vehicular emissions (VE), biomass burning (BB), and coal combustion (CC), accounting for 11?±?2 %, 31?±?4 %, and 58?±?4 % of the total PAHs, respectively. CC replaced VE to become the most important source of PAHs in Guangzhou, reflecting the effective control of VE in recent years. The three sources had different contributions to PAHs with different ring sizes, with higher BB contributions (75?±?3 %) to four-ring PAHs such as pyrene and higher CC contributions (57?±?4 %) to six-ring PAHs such as benzo[ghi]perylene. Temporal variations of VE and CC contributions were probably caused by the change of weather conditions, while temporal variations of BB contributions were additionally influenced by the fluctuation of BB emissions. Source contributions also showed some spatial variations, probably due to the source emission variations near the sampling sites.     

Airborne pollutants along a roadside: assessment using snow analyses and moss bags

Vertical snow sampling and moss bag transplants were used to estimate the local inorganic and organic pollutant load deposited from traffic along a major highway in Finland. The pH and concentrations of Cl(-), NO(3)(-), SO(4)(2-), Ca(2+), Na(+) and polyaromatic hydrocarbons (PAHs) were determined from snow samples collected in winter at different sites along the highway. In summer, moss bags containing 20 g of fresh red-stemmed feather moss (Pleurozium schreberi) were transplanted at the same sites. The moss bag transplants remained exposed to roadside traffic for a period of one month following which the samples were collected and the PAH profiles and concentrations were analysed. The deposition of inorganic and organic pollutants from road traffic was observed up to 60 m from the road. The prevailing winds had a significant effect on the dispersion of pollutants. Snow appears to be a good collector of inorganic pollutants from the atmosphere and can be used to monitor local airborne pollution from road traffic. Snow packs can also be used as passive collectors of organic pollutant loads from road traffic on a local scale. To monitor organic PAH deposition from the road traffic, moss bags appeared to be better indicators compared to snow sampling. The efficiency of moss bags in accumulating PAH compounds indicate that vegetation may be an important sink for traffic pollution.     

Sources and seasonal variation of atmospheric polycyclic aromatic hydrocarbons in Dalian,China: Factor analysis with non-negative constraints combined with local source fingerprints

Vapor- and particulate-phase polycyclic aromatic hydrocarbon (PAH) samples were continuously collected at an urban site in Dalian, China, during the heating and non-heating period. There is strong temperature dependence and obvious seasonal trend for atmospheric PAHs, and significant positive correlations of atmospheric PAHs with SO₂ and CO concentrations were observed. Factor analysis model with non-negative constraints (FA–NNC) combined with local and literature PAH source fingerprints was successful in source identification of particulate PAHs in the atmospheric samples. The results suggested that, in heating period, the main pollution sources were identified as coal-fired boiler emission (56%), residential coal combustion (33%) and traffic emissions (11%). As for non-heating period, the main sources were gasoline engine emission, traffic tunnel emission and coal-fired power plant, and the overall source contributions of traffic emission (gasoline engine + traffic tunnel) were 79% and coal-fired power plant 21%. The current results support our previous study and provide new insights. This can be the first attempt to quantitatively apportion air organic pollutants using receptor models combined with local source fingerprints. The source fingerprints can be used as reference data for source apportionment of atmospheric PAHs of China.     

Use of the terrestrial moss Pseudoscleropodium purum to detect sources of small scale contamination by PAHs

Here we present a simple, economic method of identifying sources of small scale contamination by polycyclic aromatic hydrocarbons (PAHs). The method involves determining the concentrations of the contaminants in the terrestrial moss Pseudoscleropodium purum and consists of the following steps: i) testing for the existence of gradients of decreasing concentrations of PAHs in the moss in relation to distance from different emission sources; ii) measurement of the concentration of PAHs at 35 pairs of sampling sites, each separated by a distance of 1 km; iii) study of the distribution of the differences in concentration between these pairs of sampling sites and elimination of extreme values (affected by small scale sources of contamination); iv) characterization of normal distributions to determine the probability of the data being thus distributed; and v) testing the method in the surroundings of possible sources of small scale contamination by PAHs. The decrease in concentration of all of the compounds followed a steep gradient with increasing distance from the emission source; after elimination of the outliers, the distribution of the differences in concentration between the 35 pairs of sampling sites was normal for all compounds, except benzo(a)pyrene. Application of the method to 15 different types of industries provided satisfactory results and the method proved to be a very useful tool for monitoring and evaluating air quality.     

Characterization of atmospheric particulates, particle-bound transition metals and polycyclic aromatic hydrocarbons of urban air in the centre of Athens (Greece)

The concentrations of trace metals and polycyclic aromatic hydrocarbons (PAHs) adsorbed to total suspended particulate (TSP) and finer fractions of airborne particulate matter (PM) were determined from a site in the centre of Athens (Greece), which is characterized by heavy local traffic and is densely populated, during the winter and summer periods in 2003-2004. Also, we collected and analyzed samples of diesel and gasoline exhaust particles from local vehicles (buses, taxis and private cars) and from chimney exhaust of residential central heating appliances. A seasonal effect was observed for the size distribution of aerosol mass, with a shift to larger fine fractions in winter. The most commonly detected trace metals in the TSP and PM fractions were Fe, Pb, Zn, Cu, Cr, V, Ni and Cd and their concentrations were similar to levels observed in heavily polluted urban areas from local traffic and other anthropogenic emissions. Analysis of 16 PAHs bound to PM showed that they are mostly traffic related. In general, the fine particulate PAHs concentrations were higher than coarse particles. The most common PAHs in PM(10.2) and PM(2.1) were pyrene, phenanthrene, acenapthylene and fluoranthene, which are associated with diesel and gasoline exhaust particles. The results of this study underlined the importance of local emission sources, especially vehicular traffic, central heating and other local anthropogenic emissions. Compared with other big cities, Athens has much higher levels of airborne particles, especially of the finer fractions PM(10) and PM(2.5), correlated with traffic-related air pollution.     

Spider webs as environmental indicators

Analysis of spider webs from limestone arches in New South Wales, Australia showed levels of lead and zinc to be several times higher at Jenolan Caves than reference sites at Abercrombie and Wombeyan Caves. The high concentrations at Jenolan were attributed to emissions from motor vehicles that travel through the arch. Analysis of water-soluble ions in webs from Jenolan and Abercrombie Caves showed large differences between the sites, which could be explained by differences in the geology and biology of the cave environments. Spider webs proved useful indicators of environmental chemistry and undoubtedly have applications beyond the cave environments studied here.     

PM10 source apportionment in a Swiss Alpine valley impacted by highway traffic

Although trans-Alpine highway traffic exhaust is one of the major sources of air pollution along the highway valleys of the Alpine regions, little is known about its contribution to residential exposure and impact on respiratory health. In this paper, source-specific contributions to particulate matter with an aerodynamic diameter?<?10 μm (PM₁₀) and their spatio-temporal distribution were determined for later use in a pediatric asthma panel study in an Alpine village. PM₁₀ sources were identified by positive matrix factorization using chemical trace elements, elemental, and organic carbon from daily PM₁₀ filters collected between November 2007 and June 2009 at seven locations within the village. Of the nine sources identified, four were directly road traffic-related: traffic exhaust, road dust, tire and brake wear, and road salt contributing 16 %, 8 %, 1 %, and 2 % to annual PM₁₀ concentrations, respectively. They showed a clear dependence with distance to highway. Additional contributions were identified from secondary particles (27 %), biomass burning (18 %), railway (11 %), and mineral dust including a local construction site (13 %). Comparing these source contributions with known source-specific biomarkers (e.g., levoglucosan, nitro-polycyclic aromatic hydrocarbons) showed high agreement with biomass burning, moderate with secondary particles (in winter), and lowest agreement with traffic exhaust.     

Deposition of motor vehicle emissions and winter maintenance along roadside assessed by snow analyses

A vertical snow-sampling method, where a sample was taken throughout the snowpack, was used to estimate the pollutant load on a roadside where average daily traffic density was about 9100 motor vehicles. The snow samples were collected at two sites, forest and open field, at two distances of 10 and 30 m from the road. The concentrations of inorganic anions (Cl(-), NO(-)(3), SO(2-)(4)), total N, polycyclic aromatic hydrocarbons (PAHs) and polychlorinated phenols (PCPhs) were analysed. The results suggest that on roadsides there is a deposition caused by road traffic emissions and winter maintenance which exceeds normal background deposition. Inorganic anions mainly in particle form, originating from winter maintenance, are deposited near the road. PAHs with low molecular weight (相似文献   

PAHs in the bulk atmospheric deposition of the Seine river basin: source identification and apportionment by ratios, multivariate statistical techniques and scanning electron microscopy

The origin of polycyclic aromatic hydrocarbons (PAH) contamination in bulk atmospheric deposition at two sites of the Seine estuary, one urban and one industrial, has been investigated. The PAH profiles indicate that PAHs mainly have a pyrolytic origin, both in urban and industrial areas. PAH sources vary during the year with an increase of high molecular weight PAH proportions (especially for carcinogenic PAHs) in winter, that means an increase of combustion processes such as domestic heating. Ratios of indicator PAHs (FTH/FTH+PYR and IcdP/IcdP+BghiP) confirm the pyrolytic origin of PAHs. In summer, ratios show the presence of industrial sources. In addition to these two methods, a factor analysis/multiple linear regression model was applied and gave an approximation of PAH source apportionment. PAH were found to be associated predominantly with emissions from road traffic (gasoline and diesel), that accounts for 17-34%. Domestic heating is a very important PAH source in urban areas and accounts for up to 85% of PAHs in winter. Industrial emissions (refineries...) account for 25% in the industrial area in summer. Each is an identified source category for the region and these results are consistent with fly-ashes identified by scanning electron microscopy. This study demonstrates that a combination of source identification methods is a far more efficient than one method alone.     

Anthropogenic magnetic particles and heavy metals in the road dust: Magnetic identification and its implications

Magnetic properties of road dusts in the East Lake area in Wuhan, China, were measured and compared with the results of heavy metal analyses in order to delineate the sources of pollutants. A total of ninety-seven dust samples were collected spatially from four segments with different traffic density and field settings from the roads encircling the lake. Thermomagnetic and hysteresis measurements revealed that the dominant magnetic carrier is coarse-grained magnetite. Correlations between magnetic parameters and element concentrations with traffic density and distances to the industrial region revealed that elements Cu, Ni and Fe mainly originate from vehicle traffic, which is also the major source of coarser magnetic particles (e.g., pseudo-single-domain/multi-domain (PSD/MD) grains), while element Pb and the smaller grains such as single-domain (SD) magnetic particles mainly originate from industrial emissions. The ratio between anhysteretic remanent magnetization and low-field magnetic susceptibility (ARM/χ_lf) can be employed as an indirect indicator for Cu, Fe and Ni emissions resulting from vehicle traffic. Due to the intermixture of elements from different sources, the element concentrations are not conclusive about the pollution source. A linear correlation between magnetic concentration-related parameters (e.g., ARM and saturation isothermal remanent magnetization, SIRM) and the concentrations of major elements (e.g., Cu, Co, Fe, Mn, Ni and V) suggests that they can be used as a proxy for heavy metal pollution. Road dusts in four segments show different magnetic characteristics, indicating various influxes of anthropogenic magnetic materials from vehicle traffic and industrial plants due to the different traffic loads and field settings. These results suggest that magnetic measurements can serve as an efficient complementary tool for the routinely employed geochemical methods to map the heavy metal pollution and trace the sources of pollutants in the road dust.     

Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2

Atmospheric PM pollution from traffic comprises not only direct emissions but also non-exhaust emissions because resuspension of road dust that can produce high human exposure to heavy metals, metalloids, and mineral matter. A key task for establishing mitigation or preventive measures is estimating the contribution of road dust resuspension to the atmospheric PM mixture. Several source apportionment studies, applying receptor modeling at urban background sites, have shown the difficulty in identifying a road dust source separately from other mineral sources or vehicular exhausts. The Multilinear Engine (ME-2) is a computer program that can solve the Positive Matrix Factorization (PMF) problem. ME-2 uses a programming language permitting the solution to be guided toward some possible targets that can be derived from a priori knowledge of sources (chemical profile, ratios, etc.). This feature makes it especially suitable for source apportionment studies where partial knowledge of the sources is available.In the present study ME-2 was applied to data from an urban background site of Barcelona (Spain) to quantify the contribution of road dust resuspension to PM₁₀ and PM_2.5 concentrations. Given that recently the emission profile of local resuspended road dust was obtained (Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., Moreno, T., 2009. Spatial and chemical patterns of PM₁₀ in road dust deposited in urban environment. Atmospheric Environment 43 (9), 1650–1659), such a priori information was introduced in the model as auxiliary terms of the object function to be minimized by the implementation of the so-called “pulling equations”.ME-2 permitted to enhance the basic PMF solution (obtained by PMF2) identifying, beside the seven sources of PMF2, the road dust source which accounted for 6.9 μg m^?3 (17%) in PM₁₀, 2.2 μg m^?3 (8%) of PM_2.5 and 0.3 μg m^?3 (2%) of PM₁. This reveals that resuspension was responsible of the 37%, 15% and 3% of total traffic emissions respectively in PM₁₀, PM_2.5 and PM₁. Therefore the overall traffic contribution resulted in 18 μg m^?3 (46%) in PM₁₀, 14 μg m^?3 (51%) in PM_2.5 and 8 μg m^?3 (48%) in PM₁. In PMF2 this mass explained by road dust resuspension was redistributed among the rest of sources, increasing mostly the mineral, secondary nitrate and aged sea salt contributions.     

Development and preliminary evaluation of a particulate matter emission factor model for European motor vehicles

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 microns, either from published data or from user-defined size distributions. A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM10, PM5, PM2.5, and PM1] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway). A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM10 was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Environmental Progress and Problems: A Chemical Industry Perspective

From 1995 to 2004, in Genoa, Italy, daily concentrations of twelve polycyclic aromatic hydrocarbons (PAHs) were measured in particulate phase (PM10), around a coke oven plant in operation from the 1950s and closed in 2002. The study permitted to identify the coke oven as the main PAH source in Genoa, causing constant exceeding of benzo(a)pyrene (BaP) air quality target (1.0 ng/m3) in the urban area till 1,900 meters distance downwind the plant. For this reason the plant was closed. Distance and daily hours downwind the coke plant were the main sources of variability of toxic BaP equivalent (BaPeq) concentrations and equations that best fitted these variables were experimentally obtained. During full plant activity, annual average BaPeq concentrations, measured in the three sampling sites aligned downwind to the summer prevalent winds, were: 85 ng/m3 at 40 m (site 2, industrial area), 13.2 ng/m3 at 300 m (site 3, residential area) and 5.6 ng/m3 at 575 m (site 4, residential area).

Soon after the coke oven's closure (February 2002) BaPeq concentrations (annual average) measured in residential area, decreased drastically: 0.2 ng/m3 at site 3, 0.4 ng/m3 at site 4. Comparing 1998 and 2003 data, BaPeq concentrations decreased 97.6% in site 3 and 92.8% in site 4.

Samples collected at site 3, during the longest downwind conditions, provided a reliable PAH profile of fugitive coke oven emissions. This profile was significantly different from the PAH profile, contemporary found at site 5, near the traffic flow.

This study demonstrates that risk assessment based only on distance of residences from a coke plant can be heavily inaccurate and confirmed that seasonal variability of BaPeq concentrations and high variability of fugitive emissions of PAHs during coke oven activities require at least one year of frequent and constant monitoring (10-15 samples each month).

Implications: Around a coking plant, polycyclic aromatic hydrocarbons (PAHs), concentrations depend mainly on downwind hours and distance. Equations that best fit these variables were experimentally calculated. Fugitive emissions of an old coke oven did not comply with the threshold BAP air concentration proposed by the World Health Organization (WHO), up to 1,900 m distance. The study identified the PAH profile of fugitive emissions of a coke oven, statistically different from the profile of traffic emissions. During its activity, in the Genoa residential area, 575 m away from the plant, 92.8% of found PAHs was due to coke oven emission only.     

Distribution and spatial trends of PAHs and PCBs in soils in the Seine River basin, France

Persistent organic pollutants (PAHs and PCBs) in soil samples from seven sites across the Seine basin were analysed. Samples were taken from industrialized, urban, suburban and remote sites. Results showed spatial differences, in terms of concentrations and congener profiles. PAH (Sigma14 PAHs) and PCB (Sigma 7 PCBs) concentrations ranged from 450 to 5650 microg kg(-1) and 0.09 to 150 microg kg(-1), respectively. A clear gradient from industrial to remote sites was highlighted, with a ratio of up to one order of magnitude for PAHs and two orders of magnitude for PCBs. Fluoranthene and pyrene were predominant, while the carcinogenic PAHs represented 15-46% of the total PAH content. Using hierarchical cluster analysis, soil samples profiles were compared and the influence of site location and potential sources were identified: automobile traffic, domestic heating, and industrial emissions were the prevalent PAHs sources in the Seine basin. PCB profiles suggested different transport patterns among congeners. For remote sites, the congener fingerprint showed a relatively higher proportion of the most volatile congeners, which were attributed to increased atmospheric residence times. Thus, PAH and PCB distributions in soils provided information on sources and evidence for short-range transport, and profiles of compounds reflected differences between regional and local emissions. This study demonstrates that soil sampling can be used to investigate spatial differences in atmospheric inputs of persistent organic pollutants based on differences in the mixtures of compounds, reflecting differences in regional and local atmospheric emissions.     

Molecular signatures of organic particulates as tracers of emission sources

Chemical signature of airborne particulates and deposition dusts is subject of study since decades. Usually, three complementary composition markers are investigated, namely, (i) specific organic compounds; (ii) concentration ratios between congeners, and (iii) percent distributions of homologs. Due to its intrinsic limits (e.g., variability depending on decomposition and gas/particle equilibrium), the identification of pollution sources based on molecular signatures results overall restricted to qualitative purposes. Nevertheless, chemical fingerprints allow drawing preliminary information, suitable for successfully approaching multivariate analysis and valuing the relative importance of sources. Here, the state-of-the-art is presented about the molecular fingerprints of non-polar aliphatic, polyaromatic (PAHs, nitro-PAHs), and polar (fatty acids, organic halides, polysaccharides) compounds in emissions. Special concern was addressed to alkenes and alkanes with carbon numbers ranging from 12 to 23 and?≥?24, which displayed distinct relative abundances in petrol-derived spills and exhausts, emissions from microorganisms, high vegetation, and sediments. Long-chain alkanes associated with tobacco smoke were characterized by a peculiar iso/anteiso/normal homolog fingerprint and by n-hentriacontane percentages higher than elsewhere. Several concentration ratios of PAHs were identified as diagnostic of the type of emission, and the sources of uncertainty were elucidated. Despite extensive investigations conducted so far, the origin of uncommon molecular fingerprints, e.g., alkane/alkene relationships in deposition dusts and airborne particles, remains quite unclear. Polar organics resulted scarcely investigated for pollution apportioning purposes, though they looked as indicative of the nature of sources. Finally, the role of humans and living organisms as actual emitters of chemicals seems to need concern in the future.

     

Source diagnostics of polycyclic aromatic hydrocarbons in urban road runoff, dust, rain and canopy throughfall

Diagnostic ratios and multivariate analysis were utilized to apportion polycyclic aromatic hydrocarbon (PAH) sources for road runoff, road dust, rain and canopy throughfall based on samples collected in an urban area of Beijing, China. Three sampling sites representing vehicle lane, bicycle lane and branch road were selected. For road runoff and road dust, vehicular emission and coal combustion were identified as major sources, and the source contributions varied among the sampling sites. For rain, three principal components were apportioned representing coal/oil combustion (54%), vehicular emission (34%) and coking (12%). For canopy throughfall, vehicular emission (56%), coal combustion (30%) and oil combustion (14%) were identified as major sources. Overall, the PAH's source for road runoff mainly reflected that for road dust. Despite site-specific sources, the findings at the study area provided a general picture of PAHs sources for the road runoff system in urban area of Beijing.     

Air pollution reduction via use of green energy sources for electricity and hydrogen production

The implementation of renewable wind and solar energy sources instead of fossil fuels to produce such energy carriers as electricity and hydrogen facilitates reductions in air pollution emissions. Unlike from traditional fossil fuel technologies, air pollution emissions from renewable technologies are associated mainly with the construction of facilities. With present costs of wind and solar electricity, it is shown that, when electricity from renewable sources replaces electricity from natural gas, the cost of air pollution emission abatement is more than ten times less than the cost if hydrogen from renewable sources replaces hydrogen produced from natural gas. When renewable-based hydrogen is used instead of gasoline in a fuel cell vehicle, the cost of air pollution emissions reduction approaches the same value as for renewable-based electricity only if the fuel cell vehicle efficiency exceeds significantly (i.e., by about two times) that of an internal combustion vehicle. The results provide the basis for a useful approach to an optimal strategy for air pollution mitigation.     

Can transportation infrastructure reduce haze pollution in China?

Traffic emission is one of the main sources of haze pollution, but few studies have evaluated the dynamic impact and mechanism of transportation infrastructure on haze pollution based on a spatial perspective. This study selects the annual data of 30 provinces in China from 2000 to 2017 and uses a dynamic spatial Durbin model to study the dynamic impact of transportation infrastructure on haze pollution. The results show that transportation infrastructure has a significant spatial spillover effect on haze pollution, and the spatial spillover effect has regional heterogeneity. Specifically, whether long term or short term, highway traffic has a boosting effect on haze pollution, while railway traffic has an inhibitory effect on haze pollution. In addition, transportation infrastructure can affect haze pollution through three paths: expanding economic scale, promoting transformation of industrial structure, and promoting technological progress. At the regional level, the improvement of highway traffic density in eastern, central, and western regions will significantly increase haze pollution. The enhancement of railway traffic density has a significant inhibitory and boosting effect on haze pollution in central and western regions, respectively. For the eastern region, railway traffic construction can only restrain local haze pollution, but cannot exert the spatial spillover effect of railway traffic to reduce haze. The conclusions of this paper provide policy inspirations for giving full play to the haze reduction effect of transportation infrastructure and the development of green transportation.

     

Application of positive matrix factorization to identify potential sources of PAHs in soil of Dalian, China

Soil derived sources of polycyclic aromatic hydrocarbons (PAHs) in the region of Dalian, China were investigated using positive matrix factorization (PMF). Three factors were separated based on PMF for the statistical investigation of the datasets both in summer and winter. These factors were dominated by the pattern of single sources or groups of similar sources, showing seasonal and regional variations. The main sources of PAHs in Dalian soil in summer were the emissions from coal combustion average (46%), diesel engine (30%), and gasoline engine (24%). In winter, the main sources were the emissions from coal-fired boiler (72%), traffic average (20%), and gasoline engine (8%). These factors with strong seasonality indicated that coal combustion in winter and traffic exhaust in summer dominated the sources of PAHs in soil. These results suggested that PMF model was a proper approach to identify the sources of PAHs in soil.