Spatial and temporal variability of outdoor coarse particulate matter mass concentrations measured with a new coarse particle sampler during the Detroit Exposure and Aerosol Research Study

The Detroit Exposure and Aerosol Research Study (DEARS) provided data to compare outdoor residential coarse particulate matter (PM_10–2.5) concentrations in six different areas of Detroit with data from a central monitoring site. Daily and seasonal influences on the spatial distribution of PM_10–2.5 during Summer 2006 and Winter 2007 were investigated using data collected with the newly developed coarse particle exposure monitor (CPEM). These data allowed the representativeness of the community monitoring site to be assessed for the greater Detroit metro area. Multiple CPEMs collocated with a dichotomous sampler determined the precision and accuracy of the CPEM PM_10–2.5 and PM_2.5 data.CPEM PM_2.5 concentrations agreed well with the dichotomous sampler data. The slope was 0.97 and the R² was 0.91. CPEM concentrations had an average 23% negative bias and R² of 0.81. The directional nature of the CPEM sampling efficiency due to bluff body effects probably caused the negative CPEM concentration bias.PM_10–2.5 was observed to vary spatially and temporally across Detroit, reflecting the seasonal impact of local sources. Summer PM_10–2.5 was 5 μg m^?3 higher in the two industrial areas near downtown than the average concentrations in other areas of Detroit. An area impacted by vehicular traffic had concentrations 8 μg m^?3 higher than the average concentrations in other parts of Detroit in the winter due to the suspected suspension of road salt. PM_10–2.5 Pearson Correlation Coefficients between monitoring locations varied from 0.03 to 0.76. All summer PM_10–2.5 correlations were greater than 0.28 and statistically significant (p-value < 0.05). Winter PM_10–2.5 correlations greater than 0.33 were statistically significant (p-value < 0.05). The PM_10–2.5 correlations found to be insignificant were associated with the area impacted by mobile sources during the winter. The suspected suspension of road salt from the Southfield Freeway, combined with a very stable atmosphere, caused concentrations to be greater in this area compared to other areas of Detroit. These findings indicated that PM_10–2.5, although correlated in some instances, varies sufficiently across a complex urban airshed that that a central monitoring site may not adequately represent the population's exposure to PM_10–2.5.     

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).     

The use of receptor modelling and emission inventory data to explain the downward trend in UK PM10 concentrations

Statistically significant downward trends in measured UK annual mean PM₁₀ concentrations have been observed at eight out of the nine urban background monitoring sites between the start of monitoring in 1992 or 1993 and 2000.Site-specific projections of the individual components of measured PM₁₀ concentrations have been derived for the period 1992–2000 at three monitoring sites from receptor modelling results for 1999 monitoring data. Measured annual average PM₁₀ concentrations declined to between 71% and 66% of the 1992 values during this period at the sites studied. The largest contributions to the decline in total PM₁₀ are from secondary particles at London Bloomsbury (40%, 3.4 μg m⁻³, tapered element oscillating microbalance (TEOM)), stationary sources at Belfast Centre (53%, 4.6 μg m⁻³, TEOM) and roadside traffic emissions at Bury Roadside (49%, 5.0 μg m⁻³, TEOM). The good agreement between the projected total PM₁₀ concentrations and measured values for the years 1992–2000 indicate that the combination of the receptor model and the site-specific projections provide a suitably robust method for predicting future PM₁₀ concentrations and the quantification of the impact of possible future policy measures to reduce PM₁₀ concentrations. The good agreement between the projections and measured concentration also provides a useful verification of the trends in emissions inventory estimates for the 1990s.Projections of estimated PM₁₀ concentrations have also been calculated for the London Bloomsbury site for the period from 1970 to 1991. Annual mean concentrations are predicted to have been in the range from 30 to 35 μg m⁻³, TEOM from 1977 to 1991 but much higher at values between 39 and 46 μg m⁻³, TEOM in the early 1970s.     

Effect modification of ambient particle mortality by radon: A time series analysis in 108 U.S. cities

Numerous studies have reported a positive association between ambient fine particles and daily mortality, but little is known about the particle properties or environmental factors that may contribute to these effects. This study assessed potential modification of radon on PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm)-associated daily mortality in 108 U.S. cities using a two-stage statistical approach. First, city- and season-specific PM_2.5 mortality risks were estimated using over-dispersed Poisson regression models. These PM_2.5 effect estimates were then regressed against mean city-level residential radon concentrations to estimate overall PM_2.5 effects and potential modification by radon. Radon exposure estimates based on measured short-term basement concentrations and modeled long-term living-area concentrations were both assessed. Exposure to PM_2.5 was associated with total, cardiovascular, and respiratory mortality in both the spring and the fall. In addition, higher mean city-level radon concentrations increased PM_2.5-associated mortality in the spring and fall. For example, a 10 µg/m³ increase in PM_2.5 in the spring at the 10th percentile of city-averaged short-term radon concentrations (21.1 Bq/m³) was associated with a 1.92% increase in total mortality (95% CI: 1.29, 2.55), whereas the same PM_2.5 exposure at the 90th radon percentile (234.2 Bq/m³) was associated with a 3.73% increase in total mortality (95% CI: 2.87, 4.59). Results were robust to adjustment for spatial confounders, including average planetary boundary height, population age, percent poverty and tobacco use. While additional research is necessary, this study suggests that radon enhances PM_2.5 mortality. This is of significant regulatory importance, as effective regulation should consider the increased risk for particle mortality in cities with higher radon levels.

Implications: In this large national study, city-averaged indoor radon concentration was a significant effect modifier of PM_2.5-associated total, cardiovascular, and respiratory mortality risk in the spring and fall. These results suggest that radon may enhance PM_2.5-associated mortality. In addition, local radon concentrations partially explain the significant variability in PM_2.5 effect estimates across U.S. cities, noted in this and previous studies. Although the concept of PM as a vector for radon progeny is feasible, additional research is needed on the noncancer health effects of radon and its potential interaction with PM. Future air quality regulations may need to consider the increased risk for particle mortality in cities with higher radon levels.     

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.     

Particulate matter and manganese exposures in Toronto,Canada

Methylcyclopentadienyl manganese tricarbonyl (MMT) is a manganese-based gasoline additive used to enhance automobile performance. MMT has been used in Canadian gasoline for about 20 yr. Because of the potential for increased levels of Mn in particulate matter resulting from automotive exhausts, a large-scale population-based exposure study (∼1000 participant periods) was conducted in Toronto, Canada, to estimate the distribution of 3-day average personal exposures to particulate matter (PM_2.5 and PM₁₀) and Mn. A stratified, three-stage, two-phase probability, longitudinal sample design of the metropolitan population was employed. Residential indoor and outdoor, and ambient levels (at a fixed site and on a roof) of PM_2.5, PM₁₀, and Mn were also measured. Supplementary data on traffic counts, meteorology, MMT levels in gasoline, personal occupations, and activities (e.g. amount of vehicular usage) were collected. Overall precision (%RSD) for analysis of duplicate co-located samples ranged from 2.5 to 5.0% for particulate matter and 3.1 to 5.5% for Mn. The detection limits were 1.47 and 3.45 μg m^-3 for the PM₁₀ and PM_2.5 fractions, respectively, and 5.50 and 1.83 ng m^-3 for Mn in PM₁₀ and PM_2.5, respectively. These low detection limits permitted the reporting of concentrations for >98% of the samples. For PM₁₀, the personal particulate matter levels (median 48.5 μg m^-3) were much higher than either indoor (23.1 μg m^-3) or outdoor levels (23.6 μg m^-3). The median levels for PM_2.5 for personal, indoor, and outdoor were 28.4, 15.4 and 13.2 μg m^-3, respectively. The correlation between PM_2.5 personal exposures and indoor concentrations was high (0.79), while correlations between personal and the outdoor, fixed site and roof site were low (0.16–0.27). Indoor Mn concentration distributions (in PM_2.5 and PM₁₀), unlike particulate matter, exhibited much lower and less variable levels that the corresponding outdoor data. The median personal exposure was 8.0 ng m^-3, compared with 4.7 and 8.6 ng m^-3, respectively, for the indoor and outdoor distributions. The highest correlations occurred for personal vs indoor data (0.56) and for outdoor vs roof site data (0.66), and vs fixed site data (0.56). The concentration of Mn in particulate matter, expressed in ppm (w/w), revealed that the fixed site was the highest, followed by the roof site, outdoor, indoor, and personal. The personal and indoor data showed a statistically significant correlation (0.68) while all other correlations between personal or indoor data and outdoor or fixed-site data were quite small. The low correlations of personal and indoor levels with outdoor levels suggest that different sources in the indoor and outdoor microenvironments produce particle matter with dissimilar composition. The correlation results indicate that neither the roof- nor fixed-site concentrations can adequately predict personal particulate matter or Mn exposures.     

PM2.5 and PM10: The influence of sugarcane burning on potential cancer risk

In Brazil, sugarcane fields are often burned to facilitate manual harvesting, and this burning causes environmental pollution from the large amounts of soot released into the atmosphere. This material contains numerous organic compounds such as PAHs. In this study, the concentrations of PAHs in two particulate-matter fractions (PM_2.5 and PM₁₀) in the city of Araraquara (SE Brazil, with around 200,000 inhabitants and surrounded by sugarcane plantations) were determined during the sugarcane harvest (HV) and non-harvest (NHV) seasons in 2008 and 2009. The sampling strategy included four campaigns, with 60 samples in the NHV season and 220 samples in the HV season. The PM_2.5 and PM₁₀ fractions were collected using a dichotomous sampler (10 L min^?1, 24 h) with Teflon? filters. The filter sets were extracted (ultrasonic bath with hexane/acetone (1:1 v/v)) and analyzed by HPLC/Fluorescence. The median concentration for total PAHs (PM_2.5 in 2009) was 0.99 ng m^?3 (NHV) and 3.3 ng m^?3 (HV). In the HV season, the total concentration of carcinogenic PAHs (benz(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, and benzo(a)pyrene) was 5 times higher than in the NHV season. B(a)P median concentrations were 0.017 ng m^?3 and 0.12 ng m^?3 for the NHV and HV seasons, respectively. The potential cancer risk associated with exposure through inhalation of these compounds was estimated based on the benzo[a]pyrene toxic equivalence (BaP_eq), where the overall toxicity of a PAH mixture is defined by the concentration of each compound multiplied by its relative toxic equivalence factor (TEF). BaP_eq median (2008 and 2009 years) ranged between 0.65 and 1.0 ng m^?3 and 1.2–1.4 ng m^?3 for the NHV and HV seasons, respectively. Considering that the maximum permissible BaP_eq in ambient air is 1 ng m^?3, related to the increased carcinogenic risk, our data suggest that the level of human exposure to PAHs in cities surrounded by sugarcane crops where the burning process is used is cause for concern.     

Estimation of Ambient PM2.5 Concentrations in Maryland and Verification by Measured Values

Abstract

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 μm in aerodynamic diameter (PM_2.5), but did have annual ambient data for PM smaller than 10 μm (PM₁₀) at 24 sites. The PM₁₀ data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM_2.5 data from four nearby monitors in the IMPROVE network (located in the national parks, wildlife refuges, and wilderness areas) in an effort to estimate annual average and seasonal high PM_2.5 concentrations at the 24 PM₁₀ monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM_2.5 National Ambient Air Quality Standards (NAAQS) at the sites operating in Maryland between 1992 and 1996. The estimates also indicated that 12 monitor sites might exceed the 3-year annual average PM_2.5 NAAQS of 15 ug/m³, but Maryland’s air quality shows signs that it has been improving since 1992. The estimates also were compared with actual measurements after the PM_2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM_2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM_2.5 across central Maryland.     

A four-year size-segregated characterization study of particles PM10, PM2.5 and PM1 depending on air mass origin at Melpitz

PM₁₀ measurements were started in November 1992 at Melpitz site. The mean PM₁₀ concentration in 1993 was 38 μg m^?3 in the summer season (May until October) and about 44 μg m^?3 in the winter season (November until April). The mean PM₁₀ level decreased until 1999 and varies now in ranges from 20–34 μg m^?3 to 17–24 μg m^?3 (minimum and maximum mean values for 1999–2008) in winter and summer seasons, respectively. High volume filter samples of particles PM₁₀, PM_2.5 and PM₁ were characterized for mass, water-soluble ions, organic and elemental carbon from 2004 until 2008. The percentage of PM_2.5 in PM₁₀ varies between summer (71.6%) and winter seasons (81.9%). Mean concentrations of PM₁₀, PM_2.5 and PM₁ in Melpitz were 20, 15, and 13 μg m^?3 in 2004, 22, 18, and 13 μg m^?3 in 2005, 24, 19, and 12 μg m^?3 in 2006 and 22, 17, and 12 μg m^?3 in 2007, respectively. In the four winters the rural background concentration PM₁₀ at Melpitz exceeded the daily 50 μg m^?3 limit for Europe on 8, 8, 7 and 6 days, respectively.Findings for a simple two-sector-classification of the samples (May 2004 until April 2008) using 96-h backward trajectories for the identification of source regions are: Air masses were transported most of time (60%) from the western sector and secondly (17%) from the eastern sector. The lowest daily mean mass concentration PM₁₀ were found during western inflow in summer (17 μg m^?3) containing low amounts of sulphate (2.4 μg m^?3), nitrate (1.7 μg m^?3), ammonium (1.1 μg m^?3) and TC (3.7 μg m^?3). In opposite the highest mean mass concentration PM₁₀ was found during eastern inflow in winter (35 μg m^?3) with high amounts of sulphate (6.1 μg m^?3), nitrate (5.4 μg m^?3), ammonium (3.8 μg m^?3) and TC (9.4 μg m^?3). An estimation of secondary formed OC (SOA) shows 0.8–0.9 μg m^?3 for air masses from West and 2.1–2.2 μg m^?3 from East. The seasonal difference can be neglected.The half-hourly measurements of the particle mass concentration PM₁₀ evaluated as mean daily courses using a TEOM^® show low values (14–21 μg m^?3) in summer and winter for air masses transported from West and the highest concentrations (31–38 μg m^?3) in winter for air masses from East.The results demonstrate the influence of meteorological parameters on long-range transport, secondary particle mass formation and re-emission which modify mass concentration and composition of PM₁₀, PM_2.5 and PM₁. Melpitz site is located in the East of Germany faraway from strong local anthropogenic emissions (rural background). Therefore, this site is suitable for investigation of the influence of long-range transport of air pollution in continental air masses from the East with source regions inside and outside of the European Union.     

Exposure of PM2.5 and EC from diesel and gasoline vehicles in communities near the Ports of Los Angeles and Long Beach,California

The Ports of Los Angeles and Long Beach are the entry point for almost half of all cargo containers entering the United States. The use of diesel trucks to move Port-related goods has raised significant public health concerns associated with black carbon and other air pollutants. It is difficult to reliably estimate people's exposure to vehicle-related pollutants due to the narrow impact zone of traffic, usually within 200–300 m downwind of major roadways. Previous studies suffer from the lack of traffic count data on surface streets and the lack of neighborhood-level population data. We examined seasonal and annual average exposures of particulate matter less than 2.5 μm (PM_2.5) and elemental carbon (EC) at a neighborhood scale for communities heavily impacted by diesel trucks near these ports. We assembled a traffic-activity database that distinguishes gasoline and diesel vehicles on both freeways and surface streets, by consolidating information from several sources, including our own field measurements. The CALINE4 model was used to estimate residential exposure of the study population to PM_2.5 and EC. Parcel property data were used to allocate Census block group (BG) population to increase spatial resolution. The annual average PM_2.5 and EC exposure due to local traffic was 3.8 and 0.4 μg m^?3, respectively. On average, surface streets contributed a little more than freeways (55% vs. 45% for EC and 57% and 43% for PM_2.5). Light-duty vehicles contributed significantly more than heavy-duty trucks for PM_2.5 (61% vs. 39%), but slightly less than heavy-duty trucks for EC (49% vs. 51%). Community mean population exposure was similar using parcel, census block, and BG population data, but extreme values and standard deviations varied significantly at different spatial resolutions. The intake fraction for the study population was in the range of 1.0–2.2 × 10^?5 by vehicle type, roadway type, and season.     

Air quality at Santiago,Chile: a box modeling approach II. PM2.5, coarse and PM10 particulate matter fractions

Ambient monitored data at Santiago, Chile, are analyzed using box models with the goal of assessing contributions of different economic activities to air pollution levels. The box modeling approach was applied to PM₁₀, PM_2.5 and coarse (PM₁₀–PM_2.5) particulate matter (PM) fractions; the period analyzed is 1989–1999. A linear model for each PM fraction was obtained, having as independent variables CO and SO₂ concentrations, plus a term proportional to (wind speed)⁻¹ that lumps together non-combustion emissions and secondary generation terms; wet scavenging is included as another independent variable. Model identification results show good agreement for the different parameters across monitoring stations. The washout ratios and scavenging coefficients agree with data published in the literature, being higher for the coarse PM fraction. The CO and SO₂ coefficients fitted for 1989–1995 agree with a priori estimates for the same period. Background estimates for the PM fractions are in agreement with measurement campaigns in upwind sites. Results show that transportation sources have become the dominant contributors to ambient PM levels, while stationary sources have decreased their contributions in the last years. The relative importance of mobile sources to PM_2.5 ambient concentrations has doubled in the last 10 years, whereas stationary sources have reduced their relative contributions to half the value in the early 1990s. Model estimates of regional background of PM_2.5 and PM₁₀ have decreased 50% and 22% in the last decade, respectively; coarse background has shown no significant change. The final conclusion is that there is room and need for a more intensive emission reduction strategy for Santiago, focusing on mobile sources. The approach pursued in this work is feasible for cities or regions where comprehensive, transport and chemistry models are not available yet, but estimates of air quality contributions are needed for policy purposes. The methodology requires data on ambient air quality measurements and surface meteorology.     

Quantifying the effect of urban tree planting on concentrations and depositions of PM10 in two UK conurbations

Trees are efficient scavengers of particulate matter and are characterised by higher rates of dry deposition than other land types. To estimate the potential of urban tree planting for the mitigation of urban PM₁₀ concentrations, an atmospheric transport model was used to simulate the transport and deposition of PM₁₀ across two UK conurbations (the West Midlands and Glasgow). Tree planting was simulated by modifying the land cover database, using GIS techniques and field surveys to estimate reasonable planting potentials. The model predicts that increasing total tree cover in West Midlands from 3.7% to 16.5% reduces average primary PM₁₀ concentrations by 10% from 2.3 to 2.1 μg m⁻³ removing 110 ton per year of primary PM₁₀ from the atmosphere. Increasing tree cover of the West Midlands to a theoretical maximum of 54% by planting all available green space would reduce the average PM₁₀ concentration by 26%, removing 200 ton of primary PM₁₀ per year. Similarly, for Glasgow, increasing tree cover from 3.6% to 8% reduces primary PM₁₀ concentrations by 2%, removing 4 ton of primary PM₁₀ per year. Increasing tree cover to 21% would reduce primary PM₁₀ air concentrations by 7%, removing 13 ton of primary PM₁₀ per year.     

Estimating distributions of long-term particulate matter and manganese exposures for residents of Toronto,Canada

Methylcyclopentadienyl manganese tricarbonyl (MMT), a manganese-based gasoline additive, has been used in Canadian gasoline for about 20 yr. Because MMT potentially increases manganese levels in particulate matter resulting from automotive exhausts, a population-based study conducted in Toronto, Canada assessed the levels of personal manganese exposures. Integrated 3-day particulate matter (PM_2.5) exposure measurements, obtained for 922 participant periods over the course of a year (September 1995–August 1996), were analyzed for several constituent elements, including Mn. The 922 measurements included 542 participants who provided a single 3-day observation plus 190 participants who provided two observations (in two different months). In addition to characterizing the distributions of 3-day average exposures, which can be estimated directly from the data, including the second observation for some participants enabled us to use a model-based approach to estimate the long-term (i.e. annual) exposure distributions for PM_2.5 mass and Mn. The model assumes that individuals’ 3-day average exposure measurements within a given month are lognormally distributed and that the correlation between 3-day log-scale measurements k months apart (after seasonal adjustment) depends only on the lag time, k, and not on the time of year. The approach produces a set of simulated annual exposures from which an annual distribution can be inferred using estimated correlations and monthly means and variances (log scale) as model inputs. The model appeared to perform reasonably well for the overall population distribution of PM_2.5 exposures (mean=28 μg m^-3). For example, the model predicted the 95th percentile of the annual distribution to be 62.9 μg m^-3 while the corresponding percentile estimated for the 3-day data was 86.6 μg m^-3. The assumptions of the model did not appear to hold for the overall population of Mn exposures (mean=13.1 ng m^-3). Since the population included persons who were potentially occupationally exposed to Mn (in non-vehicle-related jobs), we used responses to questionnaire items to form a subgroup consisting of non-occupationally exposed participants (671 participant periods), for which the model assumptions did appear to hold. For that subpopulation (mean=9.2 ng m^-3), the model-predicted 95th percentile of the annual Mn distribution was 16.3-ng m^-3, compared with 21.1 ng m^-3 estimated for the 3-day data.     

PM2.5 particles and size-segregated ionic species measured during fall season in three urban sites in Korea

Twelve hours integrated fine particles (PM_2.5) and 24-h average size-segregated particles were collected to investigate the chemical characteristics and to determine the size distribution of ionic species during October–December 1999 in three cities of different urban scale; Chongju, Kwangju, and Seoul, Korea. Concentrations of 5-min PM_2.5 black carbon (BC) and hourly criteria air pollutants (PM₁₀, CO, NO_x, SO₂, and O₃) were also measured using the Aethalometer and ambient air monitoring system, respectively.Highest PM_2.5 mass concentrations at Chongju, Kwangju, and Seoul sites were 63.0, 77.9, and 143.7 μg m⁻³, respectively. For the time period when highest PM_2.5 mass occurred, BC level out of PM_2.5 chemical species was highest at both Chongju and Kwangju, and highest NO₃⁻ (23.6 μg m⁻³) followed by BC (23.1 μg m⁻³) were observed at Seoul site, indicating that highest PM_2.5 pollution is closely associated with the traffic emissions. Strong relationships of Fe with BC and Zn at both Kwangju and Seoul sites support that the Fe and Zn measured there are originated partly from same source as BC, i.e. diesel traffics. However, it is suggested that the Fe measured at Chongju is most likely derived from dispersion of soil dust.The size distributions of SO₄²⁻, NO₃⁻, and NH₄⁺ ionic species indicated similar unimodal distributions at all sampling sites. However, different unimodal patterns in the accumulation mode size range with a peak in the smaller size (0.28–0.53 μm, condensation mode) in both Kwangju and Seoul, and in the relatively larger size (0.53–1.0 μm, droplet mode) in Chongju, were found. The potassium ion under the study sites dominates in the fine mode, and its size distribution showed unimodal character with a maximum in the size range 0.56–1.0 μm.     

Estimation and characterization of children’s ambient generated exposure to PM2.5 using sulphate and elemental carbon as tracers

Children’s exposures to ambient and non-ambient fine particulate matter (PM_2.5) were determined using the sulphate and elemental carbon components of the PM_2.5 mixture as tracers of the ambient contribution during a 6-week winter period in Prince George, British Columbia, Canada. Personal exposures to PM_2.5 were measured in children at 5 elementary schools located throughout the city and ambient samples were collected on school rooftops. Average ambient levels and personal exposures during this time period were 13.8 μg m^?3 and 16.4 μg m^?3 respectively. From the data pooled across individuals, use of the two different tracers indicated identical estimates of median exposure to ambient PM_2.5 (7.5 μg m^?3) and similar estimates of non-ambient generated exposure (6.4 and 5.0 μg m^?3) and infiltration (0.49 and 0.52) for the sulphate and elemental carbon approach, respectively. The median fraction of the ambient concentration resulting in exposure or exposure factors were 0.54 and 0.55 respectively, however lower values of 0.46 and 0.42 were determined from regression analysis. A strong association was found between exposure to ambient PM_2.5 and measured ambient concentrations at both the closest school monitor (median r = 0.92) and a central site (median r = 0.88) demonstrating that the central site monitor was suitable for assessing longitudinal ambient generated exposure throughout the city. These results support the use of elemental carbon as a tracer of ambient generated exposure and the use of ambient data as estimates of longitudinal changes in children’s exposure in this setting. The importance of both ambient and non-ambient sources of PM_2.5 is emphasized by their almost equal contribution to total personal exposures. Comparison with other studies suggests a limited influence of climate and the cold season in Prince George on exposure levels and found similar mean non-ambient generated exposures despite large variability across and within subjects in any given location.     

Source apportionment of ambient PM2.5 at five spanish centres of the european community respiratory health survey (ECRHS II)

Fine particulate matter (PM_2.5) was sampled at 5 Spanish locations during the European Community Respiratory Health Survey II (ECRHS II). In an attempt to identify and quantify PM_2.5 sources, source contribution analysis by principal component analysis (PCA) was performed on five datasets containing elemental composition of PM_2.5 analysed by ED-XRF. A total of 4–5 factors were identified at each site, three of them being common to all sites (interpreted as traffic, mineral and secondary aerosols) whereas industrial sources were site-specific. Sea-salt was identified as independent source at all coastal locations except for Barcelona (where it was clustered with secondary aerosols). Despite their typically dominant coarse grain-size distribution, mineral and marine aerosols were clearly observed in PM_2.5. Multi-linear regression analysis (MLRA) was applied to the data, showing that traffic was the main source of PM_2.5 at the five sites (39–53% of PM_2.5, 5.1–12.0 μg m⁻³), while regional-scale secondary aerosols accounted for 14–34% of PM_2.5 (2.6–4.5 μg m⁻³), mineral matter for 13–31% (2.4–4.6 μg m⁻³) and sea-salt made up 3–7% of the PM_2.5 mass (0.4–1.3 μg m⁻³). Consequently, despite regional and climatic variability throughout Spain, the same four main PM_2.5 emission sources were identified at all the study sites and the differences between the relative contributions of each of these sources varied at most 20%. This would corroborate PM_2.5 as a useful parameter for health studies and environmental policy-making, owing to the fact that it is not as subject to the influence of micro-sitting as other parameters such as PM₁₀. African dust inputs were observed in the mineral source, adding on average 4–11 μg m⁻³ to the PM_2.5 daily mean during dust outbreaks. On average, levels of Al, Si, Ti and Fe during African episodes were higher by a factor of 2–8 with respect to non-African days, whereas levels of local pollutants (absorption coefficient, S, Pb, Cl) showed smaller variations (factor of 0.5–2).     

Evaluation of PM10 forecasting based on the artificial neural network model and intake fraction in an urban area: A case study in Taiyuan City,China

Primary fine particulate matters with a diameter of less than 10 µm (PM₁₀) are important air emissions causing human health damage. PM₁₀ concentration forecast is important and necessary to perform in order to assess the impact of air on the health of living beings. To better understand the PM₁₀ pollution health risk in Taiyuan City, China, this paper forecasted the temporal and spatial distribution of PM₁₀ yearly average concentration, using Back Propagation Artificial Neural Network (BPANN) model with various air quality parameters. The predicted results of the models were consistent with the observations with a correlation coefficient of 0.72. The PM₁₀ yearly average concentrations combined with the population data from 2002 to 2008 were given into the Intake Fraction (IF) model to calculate the IFs, which are defined as the integrated incremental intake of a pollutant released from a source category or a region over all exposed individuals. The results in this study are only for main stationary sources of the research area, and the traffic sources have not been included. The computed IFs results are therefore under-estimations. The IFs of PM₁₀ from Taiyuan with a mean of 8.5 per million were relatively high compared with other IFs of the United States, Northern Europe and other cities in China. The results of this study indicate that the artificial neural network is an effective method for PM₁₀ pollution modeling, and the Intake Fraction model provides a rapid population risk estimate for pollutant emission reduction strategies and policies.

Implications The PM₁₀ (particulate matter with an aerodynamic diameter ≤10 μm) yearly average concentration of Taiyuan, with a mean of 0.176 mg/m³, was higher than the 65 μg/m³ recommended by the U.S. Environmental Protection Agency (EPA). The spatial distribution of PM₁₀ yearly average concentrations showed that wind direction and wind speed played an important role, whereas temperature and humidity had a lower effect than expected. Intake fraction estimates of Taiyuan were relatively high compared with those observed in other cities. Population density was the major factor influencing PM₁₀ spatial distribution. The results indicated that the artificial neural network was an effective method for PM₁₀ pollution modeling.     

Association between particulate matter air pollution and cardiovascular disease mortality in Lanzhou,China

Ambient particulate matter (PM) pollution has been linked to elevated mortality, especially from cardiovascular diseases. However, evidence on the effects of particulate matter pollution on cardiovascular mortality is still limited in Lanzhou, China. This research aimed to examine the associations of daily mean concentrations of ambient air pollutants (PM_2.5, PM_C, and PM₁₀) and cardiovascular mortality due to overall and cause-specific diseases in Lanzhou. Data representing daily cardiovascular mortality rates, meteorological factors (daily average temperature, daily average humidity, and atmospheric pressure), and air pollutants (PM_2.5, PM₁₀, SO₂, NO₂) were collected from January 1, 2014, to December 31, 2017, in Lanzhou. A quasi-Poisson regression model combined with a distributed lag non-linear model (DLNM) was used to estimate the associations. Stratified analyses were also performed by different cause-specific diseases, including cerebrovascular disease (CD), ischemic heart disease (IHD), heart rhythm disturbances (HRD), and heart failure (HF). The results showed that elevated concentration of PM_2.5, PM_C, and PM₁₀ had different effects on mortality of different cardiovascular diseases. Only cerebrovascular disease showed a significant positive association with elevated PM_2.5. Positive associations were identified between PM_C and daily mortality rates from total cardiovascular diseases, cerebrovascular diseases, and ischemic heart diseases. Besides, increased concentration of PM₁₀ was correlated with increased death of cerebrovascular diseases and ischemic heart diseases. For cerebrovascular disease, each 10 μg/m³ increase in PM_2.5 at lag4 was associated with increments of 1.22% (95% CI 0.11–2.35%). The largest significant effects for PM_C on cardiovascular diseases and ischemic heart diseases were both observed at lag0, and a 10 μg/m³ increment in concentration of PM_C was associated with 0.47% (95% CI 0.06–0.88%) and 0.85% (95% CI 0.18–1.52%) increases in cardiovascular mortality and ischemic heart diseases. In addition, it exhibited a lag effect on cerebrovascular mortality as well, which was most significant at lag6d, and an increase of 10 μg/m³ in PM_C was associated with a 0.76% (95% CI 0.16–1.37%) increase in cerebrovascular mortality. The estimates of percentage change in daily mortality rates per 10 μg/m³ increase in PM₁₀ were 0.52% (95% CI 0.05–1.02%) for cerebrovascular disease at lag6 and 0.53% (95% CI 0.01–1.05%) for ischemic heart disease at lag0, respectively. Our study suggests that elevated concentration of atmospheric PM (PM_2.5, PM_C, and PM₁₀) in Lanzhou is associated with increased mortality of cardiovascular diseases and that the health effect of elevated concentration of PM_2.5 is more significant than that of PM_C and PM₁₀.

     

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.     

Modelling long-range transport of primary particulate material over Europe

This paper uses a simple model of atmospheric transport and an emissions inventory prepared by TNO to estimate the contribution of primary particulate material to PM₁₀ and PM_2.5 concentration across Europe. The resulting population exposure is compared with that of secondary particulates, and it is noted that both primary and secondary contributions will be significantly reduced with the implementation of new protocols under the Convention on Long-Range Transboundary Air Pollution (CLRTAP). Since concentrations of primary PM₁₀ can become elevated in episodic situations, when long-range transport of particulate could, on its own, exceed 24 h average targets of 50 μg m⁻³ over large areas of Europe, such reduction is important for achievement of current air quality standards to control exposure to atmospheric particulate PM₁₀.