Brominated flame retardants in dust from UK cars--within-vehicle spatial variability, evidence for degradation and exposure implications

Polybrominated diphenyl ethers (PBDEs), hexabromocyclododecanes (HBCDs), and tetrabromobiphenol-A (TBBP-A) were measured in a preliminary study of dust from passenger cabins and trunks of 14 UK cars. Concentrations in cabin dust of HBCDs, TBBP-A, and BDEs 47, 85, 99, 100, 153, 154, 183, 196, 197, 202, 203, 206, 207, 208, and 209 exceeded significantly (p < 0.05) those in trunk dust. Sampling cabin dust thus appears to provide a more accurate indicator of human exposure via car dust ingestion than trunk dust. Elevated cabin concentrations are consistent with greater in-cabin use of BFRs. In five cars, while no significant differences (p > 0.05) in concentrations of HBCDs and most PBDEs were detected in dust sampled from four different seating areas; concentrations of TBBP-A and of PBDEs 154, 206, 207, 208, and 209 were significantly higher (p < 0.05) in dust sampled in the front seats. Possible photodebromination of BDE-209 was indicated by significantly higher (p < 0.05) concentrations of BDE-202 in cabin dust. In-vehicle exposure via dust ingestion to PBDEs, HBCDs and TBBP-A exceeded that via inhalation. Comparison with overall exposure via diet, dust ingestion, and inhalation shows while in-vehicle exposure is a minor contributor to overall exposure to BDE-99, ΣHBCDs, and TBBP-A, it is a significant pathway for BDE-209.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.     

Polybrominated diphenyl ethers occurrence in major inflowing rivers of Lake Chaohu (China): Characteristics,potential sources and inputs to lake

Eight commonly occurring polybrominated diphenyl ethers (PBDEs), including BDE 28, 47, 99, 100, 153, 154, 183, 207, and 209, were investigated in water samples from seven major inflowing rivers of Lake Chaohu to determine the distribution characteristics, potential sources and inputs to the lake. The sum of 8 BDE congeners (Σ₈PBDEs) had a concentration varied from 0.31 to 84 ng L⁻¹, with those of BDE 209, BDE 47, BDE 99, and BDE 153 being 0.31–83, <0.012–0.36, <0.012–1.3, and <0.012–0.77 ng L⁻¹, respectively. These levels were in the high range of the global PBDEs concentrations in the water environments. The highest concentrations of Σ₈PBDEs were detected in the western rivers, of which the main pollution sources were strongly related to human activities in urban centers, such as automobile-derived wastes. A sewage treatment plant was likely an important source of the lower brominated BDEs input to one western river. The correlation analyses (all p < 0.05) between PBDEs and DOC, TN, TP, and EC, suggested that the distributions and sources of PBDEs in rivers might also be related with the soil erosion by heave floods. Σ₈PBDEs input to Lake Chaohu from the rivers outlets was estimated at 344 kg yr⁻¹ during the flood season. BDE 209 was the dominant contributor with an input of 340 kg yr⁻¹, followed by BDE 99 (1.3 kg yr⁻¹), BDE 47 (0.83 kg yr⁻¹) and BDE 153 (0.60 kg yr⁻¹).     

Development and validation of the volatile correction model for PM10 – An empirical method for adjusting TEOM measurements for their loss of volatile particulate matter

EU Directives stipulate that PM₁₀ should be measured using the gravimetric reference method as laid out in EN12341 [CEN, 1998. Air Quality – Determination of the PM₁₀ Fraction of Suspended Particulate Matter – Reference Method and Field Test Procedure to Demonstrate Reference Equivalence of Measurement Methods. European Committee for Standardisation], or an equivalent method as demonstrated using EC guidance [EC, 2005. Demonstration of Equivalence of Ambient Air Monitoring Methods. European Commission Working Group on Guidance for the Demonstration of Equivalence]. There is however a conflict between the requirement to measure PM₁₀ using the gravimetric reference method and the need for rapid public reporting, and many member states, including the UK, rely on non-gravimetric techniques to measure PM₁₀. In the UK the majority of PM₁₀ measurements are made using the Tapered Element Oscillating Microbalance (TEOM), which does not meet the equivalence criteria [Harrison, D., 2006. UK Equivalence Programme for Monitoring of Particulate Matter. Defra, London]. The implied need to upgrade or replace TEOMs with an equivalent automated measurement technique has significant cost implications. The model described in this paper was based on analysis of daily mean measurements of PM₁₀ by the Filter Dynamics Measurement System (FDMS) and the TEOM at UK sites. It uses the FDMS measurement of the volatile component of PM₁₀ (referred to here as FDMS purge) to correct for differences in the sensitivity to volatile PM₁₀ between the TEOM and the EU gravimetric reference method. The model equation for the correction of TEOM PM₁₀ measurements is: TEOM_VCM = TEOM ? 1.87 FDMS purge due to the regional homogeneity of volatile PM, the FDMS purge concentration may be measured at a site distant to the TEOM, allowing the possibility of using a single FDMS instrument to correct PM₁₀ measurements made by several TEOMs in a defined geographical area. The model was assessed against the criteria for the EC Working Group's Guidance for the Demonstration of Equivalence of Ambient Air Monitoring Methods [EC, 2005. Demonstration of Equivalence of Ambient Air Monitoring Methods. European Commission Working Group on Guidance for the Demonstration of Equivalence]. The model satisfies the equivalence criteria using remote FDMS purge measurements for distances up to 200 km (in 22 out of 23 data sets). These data provide strong evidence that the model is a viable tool for correcting measurements from TEOM instruments on the national and local government networks.     

Rates of particulate pollution deposition onto leaf surfaces: Temporal and inter-species magnetic analyses

Evaluation of health impacts arising from inhalation of pollutant particles <10 μm (PM₁₀) is an active research area. However, lack of exposure data at high spatial resolution impedes identification of causal associations between exposure and illness. Biomagnetic monitoring of PM₁₀ deposited on tree leaves may provide a means of obtaining exposure data at high spatial resolution. To calculate ambient PM₁₀ concentrations from leaf magnetic values, the relationship between the magnetic signal and total PM₁₀ mass must be quantified, and the exposure time (via magnetic deposition velocity (MV_d) calculations) known. Birches display higher MV_d (∼5 cm⁻¹) than lime trees (∼2 cm⁻¹). Leaf saturation remanence values reached ‘equilibrium’ with ambient PM₁₀ concentrations after ∼6 ‘dry’ days (<3 mm/day rainfall). Other co-located species displayed within-species consistency in MV_d; robust inter-calibration can thus be achieved, enabling magnetic PM₁₀ biomonitoring at unprecedented spatial resolution.     

Physicochemical variations in atmospheric aerosols recorded at sea onboard the Atlantic–Mediterranean 2008 Scholar Ship cruise (Part I): Particle mass concentrations,size ratios,and main chemical components

We report on ambient atmospheric aerosols present at sea during the Atlantic–Mediterranean voyage of Oceanic II (The Scholar Ship) in spring 2008. A record was obtained of hourly PM₁₀, PM_2.5, and PM₁ particle size fraction concentrations and 24-h filter samples for chemical analysis which allowed for comparison between levels of crustal particles, sea spray, total carbon, and secondary inorganic aerosols. On-board monitoring was continuous from the equatorial Atlantic to the Straits of Gibraltar, across the Mediterranean to Istanbul, and back via Lisbon to the English Channel. Initially clean air in the open Atlantic registered PM₁₀ levels <10 μg m^?3 but became progressively polluted by increasingly coarse PM as the ship approached land. Away from major port cities, the main sources of atmospheric contamination identified were dust intrusions from North Africa (NAF), smoke plumes from biomass burning in sub-Saharan Africa and Russia, industrial sulphate clouds and other regional pollution sources transported from Europe, sea spray during rough seas, and plumes emanating from islands. Under dry NAF intrusions PM₁₀ daily mean levels averaged 40–60 μg m^?3 (30–40 μg m^?3 PM_2.5; c. 20 μg m^?3 PM₁), peaking briefly to >120 μg m^?3 (hourly mean) when the ship passed through curtains of higher dust concentrations amassed at the frontal edge of the dust cloud. PM₁/PM₁₀ ratios ranged from very low during desert dust intrusions (0.3–0.4) to very high during anthropogenic pollution plume events (0.8–1).     

Fine Particulate Matter Emissions Inventories: Comparisons of Emissions Estimates with Observations from Recent Field Programs

Abstract

Emissions inventories of fine particulate matter (PM_2.5) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM_2.5 emissions were reviewed: on-road mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM_2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5–20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM_2.5 are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM_2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.     

Monitoring of dust emission on gravel roads: Development of a mobile methodology and examination of horizontal diffusion

Traffic-generated fugitive dust on gravel roads impairs visibility and deposits on the adjacent environment. Particulate matter smaller than 10 μm in diameter (PM₁₀) is also associated with human health problems. Dust emission strength depends on the composition of granular material, road moisture, relative humidity, local climate (precipitation, wind velocity, etc.), and vehicle characteristics.The objectives of this study were to develop a reliable and rapid mobile methodology to measure dust concentrations on gravel roads, evaluate the precision and repeatability of the methodology and correspondence with the currently used visual assessment technique. Downwind horizontal diffusion was studied to evaluate the risk of exceeding the maximum allowed particulate matter concentration in ambient air near gravel roads according to European Council Directive [European Council Directive 1999/30/EC of 22 April 1999 relating to limit values for sulphur dioxide, nitrogen dioxide and oxides of nitrogen, particulate matter and lead in ambient air. Official Journal of the European Communities. L163/41.].A TSI DustTrak Aerosol Monitor was mounted on an estate car travelling along test sections treated with various dust suppressants. Measured PM₁₀ concentrations were compared to visual assessments performed at the same time. Airborne particles were collected in filters mounted behind the vehicle to compare the whole dust fraction with the PM₁₀ concentration. For measuring the horizontal diffusion, DustTraks were placed at various distances downwind of a dusty road section.The mobile methodology was vehicle and speed dependent but not driver dependent with pre-specified driving behaviours. A high linear correlation between PM₁₀ of different vehicles makes relative measurements of dust concentrations possible. The methodology gives continuous data series, mobility, and easy handling and provides fast, reliable and inexpensive measurements for estimating road conditions to make road maintenance more efficient.Good correlations between measured PM₁₀-values, visually assessed dust generation and dust collected in filters were obtained. PM₁₀ seems to be correlated to the whole dust fraction that impairs visibility on gravel roads.A decay in PM₁₀ concentration as a function of distance from the road was observed. Measured particles principally did not travel further than 45 m from the road. The risk of exceeding the PM₁₀ concentration stated in the EC-directive seems small.     

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.     

The impacts of different kinds of dust events on PM10 pollution in northern China

In this study the frequencies of PM₁₀ (as key urban pollutant) in 14 key environmental protection cities in northern China were analyzed. It follows that the PM₁₀ concentration in the high-frequency period is higher with an extent 0.009–0.066 mg m⁻³ than in the low-frequency period of 2001–2002. Further the impacts of three kinds of dust events on the PM₁₀ concentration in four cities (Beijing, Hohhot, Xi’an and Lanzhou) were explored. The results showed that different kinds of dust events have different influences on variation of PM₁₀ concentration in these four cities. In Lanzhou and Hohhot, which are near the source areas of dust events, the contribution degree of these three dust events to the PM₁₀ is: floating dust>dust storm>blowing dust. Whereas, in Beijing and Xi’an situated in dust event passing areas, the mean value of PM₁₀ concentration is higher in blowing dust than in floating dust (no dust storm). In addition, the influences of dust events on PM₁₀ concentration are different in the cities on different dust event paths. In Beijing and Hohhot (on the northern path), the high PM₁₀ concentration is usually caused by blowing dust. But in both Lanzhou and Xi’an (on the western/northwestern path) the high PM₁₀ pollution concentration is usually caused by floating dust.     

Particulate matter emissions from on-road vehicles in a freeway tunnel study

Particulate matter, including coarse particles (PM_2.5–10, aerodynamic diameter of particle between 2.5 and 10 μm) and fine particles (PM_2.5, aerodynamic diameter of particle lower than 2.5 μm) and their compositions, including elemental carbon, organic carbon, and 11 water-soluble ionic species, and elements, were measured in a tunnel study. A comparison of the six-hour average of light-duty vehicle (LDV) flow of the two sampling periods showed that the peak hours over the weekend were higher than those on weekdays. However, the flow of heavy-duty vehicles (HDVs) on the weekdays was significant higher than that during the weekend in this study. EC and OC content were 49% for PM_2.5–10 and 47% for PM_2.5 in the tunnel center. EC content was higher than OC content in PM_2.5–10, but EC was about 2.3 times OC for PM_2.5. Sulfate, nitrate, ammonium were the main species for PM_2.5–10 and PM_2.5. The element contents of Na, Al, Ca, Fe and K were over 0.8 μg m^?3 in PM_2.5–10 and PM_2.5. In addition, the concentrations of S, Ba, Pb, and Zn were higher than 0.1 μg m^?3 for PM_2.5–10 and PM_2.5. The emission factors of PM_2.5–10 and PM_2.5 were 18 ± 6.5 and 39 ± 11 mg km^?1-vehicle, respectively. The emission factors of EC/OC were 3.6/2.7 mg km^?1-vehicle for PM_2.5–10 and 15/4.7 mg km^?1-vehicle for PM_2.5 Furthermore, the emission factors of water-soluble ions were 0.028(Mg²⁺)–0.81(SO₄^2?) and 0.027(NO₂^?)–0.97(SO₄^2?) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively. Elemental emission factors were 0.003(V)–1.6(Fe) and 0.001(Cd)–1.05(Na) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively.     

Distribution of polybrominated diphenyl ethers and dust particle size fractions adherent to skin in indoor dust,Pretoria, South Africa

In order to determine human exposure to the indoor toxicant, selection of dust fraction and understanding dust particle size distribution in settled indoor dust are very important. This study examined the influence of dust particle size on the concentration of polybrominated diphenyl ethers (PBDEs) congeners, assessed the distribution of dust particle size and characterized the main indoor emission sources of PBDEs. Accordingly, the concentrations of PBDE congeners determined in different indoor dust fractions were found to be relatively higher in the order of dust particle size: 45–106 μm?>?(<45 μm)?>?106–150 μm. The finding shows arbitrary selection of dust fractions for exposure determination may result in wrong conclusions. Statistically significant moderate correlation between the concentration of Σ₉PBDEs and organic matter content calculated with respect to the total dust mass was also observed (r?=?0.55, p?=?0.001). On average, of total dust particle size <250 μm, 93.4 % (m/m%) of dust fractions was associated with less than 150 μm. Furthermore, of skin adherent dust fractions considered (<150 μm), 86 % (v/v%) is in the range of particle size 9.25–104.7 μm. Electronic materials treated with PBDEs were found the main emission sources of PBDE congeners in indoor environment. Based on concentrations of PBDEs determined and mass of indoor dust observed, 150 μm metallic sieve is adequate for human exposure risk assessment. However, research in this area is very limited and more research is required to generalize the fact.     

Polyfluorinated compounds in ambient air from ship- and land-based measurements in northern Germany

Neutral volatile and semi-volatile polyfluorinated organic compounds (PFC) and ionic perfluorinated compounds were determined in air samples collected at two sites in the vicinity of Hamburg, Germany, and onboard the German research vessel Atair during a cruise in the German Bight, North Sea, in early November 2007. PUF/XAD-2/PUF cartridges and glass fiber filters as sampling media were applied to collect several fluorotelomer alcohols (FTOH), fluorotelomer acrylates (FTA), perfluoroalkyl sulfonamides (FASA), and perfluoroalkyl sulfonamido ethanols (FASE) in the gas- and particle-phase as well as a set of perfluorinated carboxylates (PFCA) and sulfonates (PFSA) in the particle-phase. This study presents the distribution of PFC in ambient air of the German North Sea and in the vicinity of Hamburg for the first time. Average total PFC concentrations in and around Hamburg (180 pg m^?3) were higher than those observed in the German Bight (80 pg m^?3). In the German Bight, minimum–maximum gas-phase concentrations of 17–82 pg m^?3 for ΣFTOH, 2.6–10 pg m^?3 for ΣFTA, 10–15 pg m^?3 for ΣFASA, and 2–4.4 pg m^?3 for ΣFASE were determined. In the vicinity of Hamburg, minimum–maximum gas-phase concentrations of 32–204 pg m^?3 for ΣFTOH, 3–26 pg m^?3 for ΣFTA, 3–18 pg m^?3 for ΣFASA, and 2–15 pg m^?3 for ΣFASE were detected. Concentrations of perfluorinated acids were in the range of 1–11 pg m^?3. FTOH clearly dominated the substance spectrum; 8:2 FTOH occurred in maximum proportions. Air mass back trajectories, cluster, and correlation analyses revealed that the air mass origin and thus medium to long range atmospheric transport was the governing parameter for the amount of PFC in ambient air. Southwesterly located source regions seemed to be responsible for elevated PFC concentrations, local sources appeared to be of minor importance.     

Estimation of wind blown dust emissions in Europe and its vicinity

The assessment of the wind blown dust emission for Europe and selected regions of North Africa and Southwest Asia was carried out using a mesoscale model. The mesoscale model was parameterized based on the current literature review. The model provides data on PM₁₀ emission from several dust reservoirs (anthropogenic, agriculture, semi- and natural) with spatial resolution of 10 × 10 km and temporal resolution of 1 h. The spatial variability of PM₁₀ emission depends on soil texture, land cover/land use as well as meteorological conditions. Lands covered with water or permanently wet were excluded from the model. The land covered with vegetation is treated as dust reservoir whose dust emission capacity depends on the type of vegetation and cover. The dust reservoirs are divided into reservoirs with stable and unstable surface. The changes of emission in time depend on meteorological parameters.The wind blown dust emission should be treated as a non-continuous spatio-temporal process. The emissions are estimated with high uncertainty. The estimated PM₁₀ yearly total load emitted by wind from the European territory is highly differentiated in space and time and is equal to 0.74 Tg. The total load of PM₁₀ emitted by wind from North African and Southwest Asian land surface located in the vicinity of European boundaries is assessed as nearly 50% (0.43 Tg) of the total load estimated for the whole Europe.The average yearly PM₁₀ emission factor for Europe was estimated at 0.139 Mg km^?2.The PM₁₀ emission from agricultural areas is estimated at 52% of the total wind blown emission from the domain of the European Union project “Improving and applying methods for the calculation of natural and biogenic emissions and assessment of impacts to the air quality” - NatAir.PM₁₀ emission factor for natural areas of Europe is estimated at 0.021 Mg km^?2. Appropriate factors for agricultural areas and anthropogenic areas are 0.157 Mg km^?2 and 0.118 Mg km^?2, respectively. The latter two factors are probably underestimated due to omitting in the model of other dust emission mechanisms than aeolian erosion.     

Quantification of Saharan dust contribution to PM10 concentrations over Italy during 2003–2005

Italy is frequently affected by Saharan dust intrusions, which result in high PM₁₀ concentrations in the atmosphere and can cause the exceedances of the PM₁₀ daily limits (50 μg m^?3) set by the European Union (EU/2008/50). The estimate of African dust contribution to PM₁₀ concentrations is therefore a key issue in air quality assessment and policy formulation. This study presents a first identification of Saharan dust outbreaks as well as an estimate of the African dust contribution to PM₁₀ concentrations during the period 2003–2005 over Italy. The identification of dust events has been carried out by looking at different sources of information such as monitoring network observations, satellite images, ground measurements of aerosol optical properties, dust model simulations and air mass backward trajectory analysis. The contribution of Saharan dust to PM₁₀ monthly concentrations has been estimated at seven Italian locations. The results are both spatially (with station) and temporally (with month and year) variable, as a consequence of the variability of the meteorological conditions. However, excluding the contribution of severe dust events (21st February 2004, 25th–28th September 2003, 23rd–27th March 2005), the monthly contribution of dust varies approximately between 1 μg m^?3 and 10 μg m^?3 throughout year 2005 and between 1 μg m^?3 and 8 μg m^?3 throughout year 2003. In 2004 the dust concentration is lower than 2003 and 2005 (<5 μg m^?3 at all sites). The reduction in the number of daily exceedances of the limit value (50 μg m^?3) after subtraction of the dust contribution is also calculated at each station: it varies with station between 20% and 50% in 2005 and between 5% and 25% in 2003 and 2004.     

Carbon content of common airborne fungal species and fungal contribution to aerosol organic carbon in a subtropical city

Interest in the role and contribution of fungi to atmospheric aerosols and processes grows in the past decade. Substantial data or information such as fungal mass or carbon loading to ambient aerosols is however still lacking. This study aimed to quantify the specific organic carbon content (OC per spore) of eleven fungal species commonly found airborne in the subtropics, and estimated their contribution to organic carbon in aerosols. The specific OC contents showed a size-dependent relationship (r = 0.64, p < 0.05) and ranged from 3.6 to 201.0 pg carbon per spore or yeast cell, giving an average of 6.0 pg carbon per spore (RSD 51%) for spore or cell size less than 10 μm. In accounting for natural variations in the composition and abundance of fungal population, weighted-average carbon content for field samples was adopted using the laboratory determined specific OC values. An average of 5.97 pg carbon per spore (RSD 3.8%) was enumerated from 28 field samples collected at the university campus. The mean fungal OC concentration was 3.7, 6.0 and 9.7 ng m^?3 in PM_2.5, PM_2.5–10 and PM₁₀, respectively. These corresponded to 0.1%, 1.2% and 0.2% of the total OC in PM_2.5, PM_2.5–10 and PM₁₀, respectively. In the study period, rain provided periods with low total OC but high fungal prevalence and fungi contributed 7–32% OC in PM_2.5–10 or 2.4–7.1% OC in PM₁₀. More extensive studies are deserved to better understand the spatial-, temporal- and episodic dependency on the fungal OC contribution to the atmospheric aerosols.     

Soil water and particle size distribution influence laboratory-generated PM10

Management of soils to reduce the amount of PM₁₀ emitted during agricultural tillage operations is important for attainment of air quality standards in California's San Joaquin Valley (SJV). The purpose of this study was to improve and expand upon earlier work of predicting tillage-generated dust emissions based on soil properties. We focus on gravimetric soil water content (GWC) and soil texture. A mechanical laboratory dust generator was used to test 23 soils collected for this study. Averaged results showed PM₁₀ concentrations (mg m^?3) increased logarithmically as GWC decreased below soil water potentials of ?1500 kPa. Soils with clay contents less than about 10% by weight began to emit PM₁₀ at GWCs 1.5–4 times their GWC at ?1500 kPa. Soils with clay contents greater than about 10% began to emit PM₁₀ at GWC values closer to ?1500 kPa. We found no correlation between maximum PM₁₀ concentrations, measured at low GWC values, and the %sand, %silt, or %clay in a soil. However, there was a significant correlation between the %silt to %clay ratio and PM₁₀ concentrations. This not only suggests the dependence of dust emission magnitudes on the supply of particles of PM₁₀ size, but also the importance of clay in stabilizing aggregates and maintaining higher amounts of capillary water at lower water potentials. Based on modeled results of pooled data, PM₁₀ concentrations increased linearly (slope = 564) for every unit increase in the %silt to %clay ratio. However, when soils were separated into groups based on clay content, the slopes for PM₁₀ concentrations vs. %silt to %clay ratio were texture dependent. The slope for soils with <10% clay (slope = 727) was 3.3 times greater than for soils with >20% clay (slope = 221). Improved PM₁₀ emission prediction based on soil properties should improve management decisions aimed at reducing tillage-generated PM₁₀.     

Halogenated organic contaminants (HOCs) in sediment from a highly eutrophicated lake, China: Occurrence, distribution and mass inventories

Halogenated organic contaminants (HOCs) including 16 polybrominated diphenyl ethers (PBDEs) and 37 polychlorinated biphenyls (PCBs) were determined in 49 surfacial sediments from Chaohu Lake, a highly eutrophicated lake, China. PBDEs were detected in almost samples with the range of the total concentration (defined as Σ₁₆PBDEs) from 0.84 to 86.6 ng g⁻¹. Compared with the occurrence of PBDEs in Pearl River Delta and Yangtze River Delta in China, lower percentage of BDE-209 over the concentration of Σ₁₆PBDEs was inferred by the high-volume application of penta-BDE mixture product for local domestic furniture purpose. The total concentration of 37 PCBs (Σ₃₇PCBs) ranged from 0.05 to 3.36 ng g⁻¹ with the most detection of PCB-1, -4, -52 and -71. Both the concentrations of Σ₁₆PBDE and Σ₃₇PCB poorly correlated with total organic carbon (TOC), suggesting the significant contribution of phytoplankton organic carbons to sediment TOC. The contamination by PBDEs and PCBs in western region of the lake was significantly more serious than in eastern lake. Our findings about the higher residues of PBDEs and PCBs in sediments at the estuary of Nanfei River compared to the other estuaries also supported the conclusion that urban area (Hefei city) was the main source of PBDEs and PCBs. The comparison with the concentration of HOC in the present study with those in other lacustrine sediments around the world suggested the contamination by PBDEs in Chaohu Lake is at middle of the global concentration range, whereas PCBs is at low end of the global range which could be elucidated by local economic development and historical usage of PBDEs and PCBs. The mass inventories of HOCs in the lake were estimated at 561 and 38 kg, which corresponds to only 0.000006% and 0.0001% of these global historical produce volumes, respectively.     

Source-to-receptor pathways of anthropogenic PM2.5 in Detroit,Michigan: Comparison of two inhalation exposure studies

Recent studies have attributed toxic effects of ambient fine particulate matter (aerodynamic diameter ≤ 2.5 μm; PM_2.5) to physical and/or chemical properties rather than total mass. However, identifying specific components or sources of a complex mixture of ambient PM_2.5 that are responsible for adverse health effects is still challenging. In order to improve our understanding of source-to-receptor pathways for ambient PM_2.5 (links between sources of ambient PM_2.5 and measures of biologically relevant dose), integrated inhalation toxicology studies using animal models and concentrated air particles (CAPs) were completed in southwest Detroit, a community where the pediatric asthma rate is more than twice the national average. Ambient PM_2.5 was concentrated with a Harvard fine particle concentrator housed in AirCARE1, a mobile air research laboratory which facilitates inhalation exposure studies in real-world settings. Detailed characterizations of ambient PM_2.5 and CAPs, identification of major emission sources of PM_2.5, and quantification of trace elements in the lung tissues of laboratory rats that were exposed to CAPs for two distinct 3-day exposure periods were completed.This paper describes the physical/chemical properties and sources of PM_2.5, pulmonary metal concentrations and meteorology from two different 3-day exposure periods—both conducted at the southwest Detroit location in July 2003—which resulted in disparate biological effects. More specifically, during one of the exposure periods, ambient PM_2.5-derived trace metals were recovered from lung tissues of CAPs-exposed animals, and these metals were linked to local combustion point sources in southwest Detroit via receptor modeling and meteorology; whereas in the other exposure period, no such trace metals were observed. By comparing these two disparate results, this investigation was able to define possible links between PM_2.5 emitted from refineries and incinerators and biologically relevant dose, which in turn may be associated with observed health effects.     

Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CPRAQS) using the UCD/CIT source-oriented air quality model – Part III. Regional source apportionment of secondary and total airborne particulate matter

A comprehensive air quality modeling project was carried out to simulate regional source contributions to secondary and total (=primary + secondary) airborne particle concentrations in California's Central Valley. A three-week stagnation episode lasting from December 15, 2000 to January 7, 2001, was chosen for study using the air quality and meteorological data collected during the California Regional PM₁₀/PM_2.5 Air Quality Study (CRPAQS). The UCD/CIT mechanistic air quality model was used with explicit decomposition of the gas phase reaction chemistry to track source contributions to secondary PM. Inert artificial tracers were used with an internal mixture representation to track source contributions to primary PM. Both primary and secondary source apportionment calculations were performed for 15 size fractions ranging from 0.01 to 10 μm particle diameters. Primary and secondary source contributions were resolved for fugitive dust, road dust, diesel engines, catalyst equipped gasoline engines, non-catalyst equipped gasoline engines, wood burning, food cooking, high sulfur fuel combustion, and other anthropogenic sources.Diesel engines were identified as the largest source of secondary nitrate in central California during the study episode, accounting for approximately 40% of the total PM_2.5 nitrate. Catalyst equipped gasoline engines were also significant, contributing approximately 20% of the total secondary PM_2.5 nitrate. Agricultural sources were the dominant source of secondary ammonium ion. Sharp gradients of PM concentrations were predicted around major urban areas. The relative source contributions to PM_2.5 from each source category in urban areas differ from those in rural areas, due to the dominance of primary OC in urban locations and secondary nitrate in the rural areas. The source contributions to ultra-fine particle mass PM_0.1 also show clear urban/rural differences. Wood smoke was found to be the major source of PM_0.1 in urban areas while motor vehicle sources were the major contributor of PM_0.1 in rural areas, reflecting the influence from two major highways that transect the Valley.