Simulating the meteorology and PM10 concentrations in Arizona dust storms using the Weather Research and Forecasting model with Chemistry (Wrf-Chem)

Nine dust storms in south-central Arizona were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2 km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM₁₀ observations, the model unevenly reproduces the dust-storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 µm and smaller ([PM₁₀]).Furthermore, the model underestimated [PM₁₀] in highly agricultural Pinal County because it underestimated surface wind speeds and because the model’s erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model overestimated [PM₁₀] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) for which the surface-layer speeds were too strong. In Phoenix, AZ, the model’s performance depended on the event, with both under- and overestimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM₁₀] highly relies on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM₁₀] in that region. Both 24-hr and 1-hr measured [PM₁₀] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as 10-fold and the latter exceeding health-based guidelines by as much as 70-fold. Monsoonal thunderstorms not only produce elevated [PM₁₀], but also cause urban flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and observations, additional research in both the windblown dust emissions model and the weather research/physicochemical model is called for.

Implications: While many dust storms can be considered to be natural, in semi-arid climates such storms often have an anthropogenic component in their sources of dust. Applying the natural, exceptional events policy to these storms with strong signatures of anthropogenic sources would appear not only to be misguided but also to stifle genuine regulatory efforts at remediation. Those dust storms that have resulted, in part, from passage over abandoned farm land should no longer be considered “natural”; policymakers and lawmakers need to compel the owners of such land to reduce its potential for windblown dust.     

Feasibility of using low-cost portable particle monitors for measurement of fine and coarse particulate matter in urban ambient air

Exposure to ambient particulate matter (PM) is known as a significant risk factor for mortality and morbidity due to cardiorespiratory causes. Owing to increased interest in assessing personal and community exposures to PM, we evaluated the feasibility of employing a low-cost portable direct-reading instrument for measurement of ambient air PM exposure. A Dylos DC 1700 PM sensor was collocated with a Grimm 11-R in an urban residential area of Houston Texas. The 1-min averages of particle number concentrations for sizes between 0.5 and 2.5 µm (small size) and sizes larger than 2.5 µm (large size) from a DC 1700 were compared with the 1-min averages of PM_2.5 (aerodynamic size less than 2.5 µm) and coarse PM (aerodynamic size between 2.5 and 10 µm) concentrations from a Grimm 11-R. We used a linear regression equation to convert DC 1700 number concentrations to mass concentrations, utilizing measurements from the Grimm 11-R. The estimated average DC 1700 PM_2.5 concentration (13.2 ± 13.7 µg/m³) was similar to the average measured Grimm 11-R PM_2.5 concentration (11.3 ± 15.1 µg/m³). The overall correlation (r²) for PM_2.5 between the DC 1700 and Grimm 11-R was 0.778. The estimated average coarse PM concentration from the DC 1700 (5.6 ± 12.1 µg/m³) was also similar to that measured with the Grimm 11-R (4.8 ± 16.5 µg/m³) with an r² of 0.481. The effects of relative humidity and particle size on the association between the DC 1700 and the Grimm 11-R results were also examined. The calculated PM mass concentrations from the DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.

Implications: The performance of a low-cost particulate matter (PM) sensor was evaluated in an urban residential area. Both PM_2.5 and coarse PM (PM_10-2.5) mass concentrations were estimated using a DC1700 PM sensor. The calculated PM mass concentrations from the number concentrations of DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.     

PM10 concentration levels at an urban and background site in Cyprus: The impact of urban sources and dust storms

Air quality in Cyprus is influenced by both local and transported pollution, including desert dust storms. We examined PM₁₀ concentration data collected in Nicosia (urban representative) from April 1, 1993, through December 11, 2008, and in Ayia Marina (rural background representative) from January 1, 1999, through December 31, 2008. Measurements were conducted using a Tapered Element Oscillating Micro-balance (TEOM). PM₁₀ concentrations, meteorological records, and satellite data were used to identify dust storm days. We investigated long-term trends using a Generalized Additive Model (GAM) after controlling for day of week, month, temperature, wind speed, and relative humidity. In Nicosia, annual PM₁₀ concentrations ranged from 50.4 to 63.8 μg/m³ and exceeded the EU annual standard limit enacted in 2005 of 40 μg/m³ every year. A large, statistically significant impact of urban sources (defined as the difference between urban and background levels) was seen in Nicosia over the period 2000–2008, and was highest during traffic hours, weekdays, cold months, and low wind conditions. Our estimate of the mean (standard error) contribution of urban sources to the daily ambient PM₁₀ was 24.0 (0.4) μg/m³. The study of yearly trends showed that PM₁₀ levels in Nicosia decreased from 59.4 μg/m³ in 1993 to 49.0 μg/m³ in 2008, probably in part as a result of traffic emission control policies in Cyprus. In Ayia Marina, annual concentrations ranged from 27.3 to 35.6 μg/m³, and no obvious time trends were observed. The levels measured at the Cyprus background site are comparable to background concentrations reported in other Eastern Mediterranean countries. Average daily PM₁₀ concentrations during desert dust storms were around 100 μg/m³ since 2000 and much higher in earlier years. Despite the large impact of dust storms and their increasing frequency over time, dust storms were responsible for a small fraction of the exceedances of the daily PM₁₀ limit.

ImplicationsThis paper examines PM₁₀ concentrations in Nicosia, Cyprus, from 1993 to 2008. The decrease in PM₁₀ levels in Nicosia suggests that the implementation of traffic emission control policies in Cyprus has been effective. However, particle levels still exceeded the European Union annual standard, and dust storms were responsible for a small fraction of the daily PM₁₀ limit exceedances. Other natural particles that are not assessed in this study, such as resuspended soil and sea salt, may be responsible in part for the high particle levels.     

Temporal variations of fine and coarse particulate matter sources in Jeddah,Saudi Arabia

This study provides the first comprehensive analysis of the seasonal variations and weekday/weekend differences in fine (aerodynamic diameter <2.5 μm; PM_2.5) and coarse (aerodynamic diameter 2.5–10 μm; PM_2.5–10) particulate matter mass concentrations, elemental constituents, and potential source origins in Jeddah, Saudi Arabia. Air quality samples were collected over 1 yr, from June 2011 to May 2012 at a frequency of three times per week, and analyzed. The average mass concentrations of PM_2.5 (21.9 μg/m³) and PM₁₀ (107.8 μg/m³) during the sampling period exceeded the recommended annual average levels by the World Health Organization (WHO) for PM_2.5 (10 μg/m³) and PM₁₀ (20 μg/m³), respectively. Similar to other Middle Eastern locales, PM_2.5–10 is the prevailing mass component of atmospheric particulate matter at Jeddah, accounting for approximately 80% of the PM₁₀ mass. Considerations of enrichment factors, absolute principal component analysis (APCA), concentration roses, and backward trajectories identified the following source categories for both PM_2.5 and PM_2.5–10: (1) soil/road dust, (2) incineration, and (3) traffic; and for PM_2.5 only, (4) residual oil burning. Soil/road dust accounted for a major portion of both the PM_2.5 (27%) and PM_2.5–10 (77%) mass, and the largest source contributor for PM_2.5 was from residual oil burning (63%). Temporal variations of PM_2.5–10 and PM_2.5 were observed, with the elevated concentration levels observed for mass during the spring (due to increased dust storm frequency) and on weekdays (due to increased traffic). The predominant role of windblown soil and road dust in both the PM_2.5 and PM_2.5–10 masses in this city may have implications regarding the toxicity of these particles versus those in the Western world where most PM health assessments have been made in the past. These results support the need for region-specific epidemiological investigations to be conducted and considered in future PM standard setting.

Implications: Temporal variations of fine and coarse PM mass, elemental constituents, and sources were examined in Jeddah, Saudi Arabia, for the first time. The main source of PM_2.5–10 is natural windblown soil and road dust, whereas the predominant source of PM_2.5 is residual oil burning, generated from the port and oil refinery located west of the air sampler, suggesting that targeted emission controls could significantly improve the air quality in the city. The compositional differences point to a need for health effect studies to be conducted in this region, so as to directly assess the applicability of the existing guidelines to the Middle East air pollution.     

Overview of surface measurements and spatial characterization of submicrometer particulate matter during the DISCOVER-AQ 2013 campaign in Houston,TX

The sources of submicrometer particulate matter (PM₁) remain poorly characterized in the industrialized city of Houston, TX. A mobile sampling approach was used to characterize PM₁ composition and concentration across Houston based on high-time-resolution measurements of nonrefractory PM₁ and trace gases during the DISCOVER-AQ Texas 2013 campaign. Two pollution zones with marked differences in PM₁ levels, character, and dynamics were established based on cluster analysis of organic aerosol mass loadings sampled at 16 sites. The highest PM₁ mass concentrations (average 11.6 ± 5.7 µg/m³) were observed to the northwest of Houston (zone 1), dominated by secondary organic aerosol (SOA) mass likely driven by nighttime biogenic organonitrate formation. Zone 2, an industrial/urban area south/east of Houston, exhibited lower concentrations of PM₁ (average 4.4 ± 3.3 µg/m³), significant organic aerosol (OA) aging, and evidence of primary sulfate emissions. Diurnal patterns and backward-trajectory analyses enable the classification of airmass clusters characterized by distinct PM sources: biogenic SOA, photochemical aged SOA, and primary sulfate emissions from the Houston Ship Channel. Principal component analysis (PCA) indicates that secondary biogenic organonitrates primarily related with monoterpenes are predominant in zone 1 (accounting for 34% of the variability in the data set). The relevance of photochemical processes and industrial and traffic emission sources in zone 2 also is highlighted by PCA, which identifies three factors related with these processes/sources (~50% of the aerosol/trace gas concentration variability). PCA reveals a relatively minor contribution of isoprene to SOA formation in zone 1 and the absence of isoprene-derived aerosol in zone 2. The relevance of industrial amine emissions and the likely contribution of chloride-displaced sea salt aerosol to the observed variability in pollution levels in zone 2 also are captured by PCA.

Implications: This article describes an urban-scale mobile study to characterize spatial variations in submicrometer particulate matter (PM₁) in greater Houston. The data set indicates substantial spatial variations in PM₁ sources/chemistry and elucidates the importance of photochemistry and nighttime oxidant chemistry in producing secondary PM₁. These results emphasize the potential benefits of effective control strategies throughout the region, not only to reduce primary emissions of PM₁ from automobiles and industry but also to reduce the emissions of important secondary PM₁ precursors, including sulfur oxides, nitrogen oxides, ammonia, and volatile organic compounds. Such efforts also could aid in efforts to reduce mixing ratios of ozone.     

The impact of airborne particulate matter on pediatric hospital admissions for pneumonia among children in Jinan,China: A case-crossover study

This study aims to examine the effect of short-term changes in the concentration of particulate matter of diameter ≤2.5 µm (PM_2.5) and ≤10 µm (PM₁₀) on pediatric hospital admissions for pneumonia in Jinan, China. It explores confoundings factors of weather, season, and chemical pollutants. Information on pediatric hospital admissions for pneumonia in 2014 was extracted from the database of Jinan Qilu Hospital. The relative risk of pediatric hospital admissions for pneumonia was assessed using a case-crossover approach, controlling weather variables, day of the week, and seasonality. The single-pollutant model demonstrated that increased risk of pediatric hospital admissions for pneumonia was significantly associated with elevated PM_2.5 concentrations the day before hospital admission and elevated PM₁₀ concentrations 2 days before hospital admission. An increment of 10 μg/m³ in PM_2.5 and PM₁₀ was correlated with a 6% (95% CI 1.02–-1.10) and 4% (95% CI 1.00–1.08) rise in number of admissions for pneumonia, respectively. In two pollutant models, PM_2.5 and PM₁₀ remained significant after inclusion of sulfur dioxide or nitrogen dioxide but not carbon monoxide. This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China.

Implications: This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China, and suggested the relevance of pollutant exposure levels and their effects. As a specific group, children are sensitive to airborne particulate matter. This study estimated the short-term effects attribute to other air pollutants to provide references for relevant studies.     

Seasonal ambient particulate matter and population health outcomes among communities impacted by road dust in British Columbia,Canada

In recent years, many air quality monitoring programs have favored measurement of particles less than 2.5 µm (PM_2.5) over particles less than 10 µm (PM₁₀) in light of evidence that health impacts are mostly from the fine fraction. However, the coarse fraction (PM_10-2.5) may have independent health impacts that support continued measurement of PM₁₀ in some areas, such as those affected by road dust. The objective of this study was to evaluate the associations between different measures of daily PM exposure and two daily indicators of population health in seven communities in British Columbia, Canada, where road dust is an ongoing concern. The measures of exposure were PM₁₀, PM_2.5, PM_10-2.5, PM_2.5 adjusted for PM_10-2.5, and PM_10-2.5 adjusted for PM_2.5. The indicators of population health were dispensations of the respiratory reliever medication salbutamol sulfate and nonaccidental mortality. This study followed a time-series design using Poisson regression over a 2003–2015 study period, with analyses stratified by three seasons: residential woodsmoke in winter; road dust in spring; and wildfire smoke in summer. A random-effects meta-analysis was conducted to establish a pooled estimate. Overall, an interquartile range increase in daily PM_10-2.5 was associated with a 3.6% [1.6, 5.6] increase in nonaccidental mortality during the road dust season, which was reduced to 3.1% [0.8, 5.4] after adjustment for PM_2.5. The adjusted coarse fraction had no effect on salbutamol dispensations in any season. However, an interquartile range increase in PM_2.5 was associated with a 2.7% [2.0, 3.4] increase in dispensations during the wildfire season. These analyses suggest different impacts of different PM fractions by season, with a robust association between the coarse fraction and nonaccidental mortality in communities and periods affected by road dust. We recommend that PM₁₀ monitoring networks be maintained in these communities to provide feedback for future dust mitigation programs.

Implications: There was a significant association between daily concentrations of the coarse fraction and nonaccidental mortality during the road dust season, even after adjustment for the fine fraction. The acute and chronic health effects associated with exposure to the coarse fraction remain unclear, which supports the maintenance of PM₁₀ monitoring networks to allow for further research in communities affected by sources such as road dust.     

Outdoor fine and ultrafine particle measurements at six bus stops with smoking on two California arterial highways—Results of a pilot study

As indoor smoking bans have become widely adopted, some U.S. communities are considering restricting smoking outdoors, creating a need for measurements of air pollution near smokers outdoors. Personal exposure experiments were conducted with four to five participants at six sidewalk bus stops located 1.5–3.3 m from the curb of two heavily traveled California arterial highways with 3300–5100 vehicles per hour. At each bus stop, a smoker in the group smoked a cigarette. Gravimetrically calibrated continuous monitors were used to measure fine particle concentrations (aerodynamic diameter ≤2.5 µm; PM_2.5) in the breathing zones (within 0.2 m from the nose and mouth) of each participant. At each bus stop, ultrafine particles (UFP), wind speed, temperature, relative humidity, and traffic counts were also measured. For 13 cigarette experiments, the mean PM_2.5 personal exposure of the nonsmoker seated 0.5 m from the smoker during a 5-min cigarette ranged from 15 to 153 µg/m³. Of four persons seated on the bench, the smoker received the highest PM_2.5 breathing-zone exposure of 192 µg/m³. There was a strong proximity effect: nonsmokers at distances 0.5, 1.0, and 1.5 m from the smoker received mean PM_2.5 personal exposures of 59, 40, and 28 µg/m³, respectively, compared with a background level of 1.7 µg/m³. Like the PM_2.5 concentrations, UFP concentrations measured 0.5 m from the smoker increased abruptly when a cigarette started and decreased when the cigarette ended, averaging 44,500 particles/cm³ compared with the background level of 7200 particles/cm³. During nonsmoking periods, the UFP background concentrations showed occasional peaks due to traffic, whereas PM_2.5 background concentrations were extremely low. The results indicate that a single cigarette smoked outdoors at a bus stop can cause PM_2.5 and UFP concentrations near the smoker that are 16–35 and 6.2 times, respectively, higher than the background concentrations due to cars and trucks on an adjacent arterial highway.

Implications: Rules banning smoking indoors have been widely adopted in the United States and in many countries. Some communities are considering smoking bans that would apply to outdoor locations. Although many measurements are available of pollutant concentrations from secondhand smoke at indoor locations, few measurements are available of exposure to secondhand smoke outdoors. This study provides new data on exposure to fine and ultrafine particles from secondhand smoke near a smoker outdoors. The levels are compared with the exposure measured next to a highway. The findings are important for policies that might be developed for reducing exposure to secondhand smoke outdoors.     

Recent spatial gradients and time trends in Dhaka,Bangladesh, air pollution and their human health implications

Dhaka, the capital of Bangladesh, is among the most polluted cities in the world. This research evaluates seasonal patterns, day-of-week patterns, spatial gradients, and trends in PM_2.5 (<2.5 µm in aerodynamic diameter), PM₁₀ (<10 µm in aerodynamic diameter), and gaseous pollutants concentrations (SO₂, NO₂, CO, and O₃) monitored in Dhaka from 2013 to 2017. It expands on past work by considering multiple monitoring sites and air pollutants. Except for ozone, the average concentrations of these pollutants showed strong seasonal variation, with maximum during winter and minimum during monsoon, with the pollution concentration of PM_2.5 and PM₁₀ being roughly five- to sixfold higher during winter versus monsoon. Our comparisons of the pollutant concentrations with Bangladesh NAAQS and U.S. NAAQS limits analysis indicate particulate matter (PM_2.5 and PM₁₀) as the air pollutants of greatest concern, as they frequently exceeded the Bangladesh NAAQS and U.S. NAAQS, especially during nonmonsoon time. In contrast, gaseous pollutants reported far fewer exceedances throughout the study period. During the study period, the highest number of exceedances of NAAQS limits in Dhaka City (Darus-Salam site) were found for PM_2.5 (72% of total study days), followed by PM₁₀ (40% of total study days), O₃ (1.7% of total study days), SO₂ (0.38% of total study days), and CO (0.25% of total study days). The trend analyses results showed statistically significant positive slopes over time for SO₂ (5.6 ppb yr^?1, 95% confidence interval [CI]: 0.7, 10.5) and CO (0.32 ppm yr^?1, 95% CI: 0.01, 0.56), which suggest increase in brick kilns operation and high-sulfur diesel use. Though statistically nonsignificant annual decreasing slopes for PM_2.5 (?4.6 µg/m³ yr^?1, 95% CI: ?12.7, 3.6) and PM₁₀ (?2.7 µg/m³ yr^?1, 95% CI: ?7.9, 2.5) were observed during this study period, the PM_2.5 concentration is still too high (~ 82.0 µg/m³) and can cause severe impact on human health.

Implications: This study revealed key insights into air quality challenges across Dhaka, Bangladesh, indicating particulate matter (PM) as Dhaka’s most serious air pollutant threat to human health. The results of these analyses indicate that there is a need for immediate further investigations, and action based on those investigations, including the conduct local epidemiological PM exposure-human health effects studies for this city, in order to determine the most public health effective interventions.     

Particulate matter pollution in the coal-producing regions of the Appalachian Mountains: Integrated ground-based measurements and satellite analysis

This study integrates the relationship between measured surface concentrations of particulate matter 10 μm or less in diameter (PM₁₀), satellite-derived aerosol optical depth (AOD), and meteorology in Roda, Virginia, during 2008. A multiple regression model was developed to predict the concentrations of particles 2.5 μm or less in diameter (PM_2.5) at an additional location in the Appalachia region, Bristol, TN. The model was developed by combining AOD retrievals from Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor on board the EOS Terra and Aqua Satellites with the surface meteorological observations. The multiple regression model predicted PM_2.5 (r² = 0.62), and the two-variable (AOD-PM_2.5) model predicted PM_2.5 (r² = 0.4). The developed model was validated using particulate matter recordings and meteorology observations from another location in the Appalachia region, Hazard, Kentucky. The model was extrapolated to the Roda, VA, sampling site to predict PM_2.5 mass concentrations. We used 10 km x 10 km resolution MODIS 550 nm AOD to predict ground level PM_2.5. For the relevant period in 2008, in Roda, VA, the predicted PM_2.5 mass concentration is 9.11 ± 5.16 μg m^-3 (mean ± 1SD).

Implications: This is the first study that couples ground-based Particulate Matter measurements with satellite retrievals to predict surface air pollution at Roda, Virginia. Roda is representative of the Appalachian communities that are commonly located in narrow valleys, or “hollows,” where homes are placed directly along the roads in a region of active mountaintop mining operations. Our study suggests that proximity to heavy coal truck traffic subjects these communities to chronic exposure to coal dust and leads us to conclude that there is an urgent need for new regulations to address the primary sources of this particulate matter.     

Comparison of current Federal Reference Methods for ambient lead measurements adjacent to a secondary lead smelter

The United States Environmental Protection Agency (EPA) reduced their National Ambient Air Quality Standard (NAAQS) for lead (Pb) an order of magnitude to a concentration level of 0.15 micrograms per cubic meter (µg/m³) when the new rule was promulgated in 2008. At that time, the possibility of revising the Pb sampling method from total suspended particulate (TSP) to particulate matter less than or equal to 10 µm in diameter (PM₁₀) was considered due to potential measurement bias of the Pb-TSP monitoring technique. The New York State Department of Environmental Conservation (NYSDEC) has been operating source-orientated colocated TSP and PM₁₀ monitors documenting ambient air lead (Pb) concentrations since 2011 at a site adjacent to a secondary Pb smelter in Wallkill, New York. The colocated Wallkill data show a very strong correlation between the readings recorded by these two sampling techniques. After the range of the variability in the individual Pb-PM₁₀/Pb-TSP ratios was reduced by using a 0.005 µg/m³ concentration cut point, because of the concerns about the measurements at low concentrations, an adjustment factor (AF) of 1.49 was calculated using the remaining data set. This AF can be used to estimate Pb-TSP concentrations from Pb-PM₁₀ readings at this Wallkill source-orientated location. It was stated by the EPA that there is only a limited data set in situations where Pb-TSP and Pb-PM₁₀ are colocated, especially for those sites considered to be source-oriented, so the analyses performed and summarized herein for the Wallkill colocated airborne Pb concentration data add to that limited data set.

Implications: These data analyses add to the limited data set in situations where Pb-TSP and Pb-PM₁₀ are colocated to help refine the derivation of a site-specific adjustment factor for estimating TSP Pb concentrations from measured PM₁₀ Pb concentrations. This could assist the EPA in transitioning away from the use of the Pb-TSP monitoring technique, with its indicated measurement bias, for the Pb NAAQS to the use of Pb-PM₁₀ instead. An adjustment factor of 1.49 was calculated that could be used to estimate Pb-TSP concentrations from Pb-PM₁₀ values collected around this source-orientated location.     

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.     

Assessment of personal integrated exposure to fine particulate matter of urban residents in Hong Kong

Metropolitan residents are concerned about their exposure to airborne pollutants. But establishing these exposures is challenging. A compact personal exposure kit (PEK) was developed to evaluate personal integrated exposure (PIE) from time-resolved data to particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5) in five microenvironments, including office, home, commuting, other indoor activities (other than home and office), and outdoor activities experienced both on weekdays and weekends. The study was conducted in Hong Kong. The PEK measured PM_2.5, reported location and several other factors, stored collected data, as well as reported the data back to the investigators using global system for mobile communication (GSM) telemetry. Generally, PM_2.5 concentrations in office microenvironment were found to be the smallest (13.0 μg/m³), whereas the largest PM_2.5 concentration microenvironments were experienced during outdoor activities (54.4 μg/m³). Participants spent more than 85% of their time indoors, including in offices, homes, and other public indoor venues. On average, 42% and 81% of the time were spent in homes, which contributed 52% and 79% of PIE (during weekdays and weekends, respectively), suggesting that improvement of air quality in homes may reduce overall exposures and indicating the need for actions to mitigate possible public health burdens in Hong Kong. This study also found that various indoor/outdoor microenvironments experienced by urban office workers cannot be accurately represented by general urban air quality data reported from the regulatory monitoring. Such personalized air quality information, especially while in transit or in offices and homes, may provide improved information on population exposures to air pollution.

Implications: A newly developed personal exposure kit (PEK) was used to monitor PM_2.5 exposure of metropolitan citizens in their daily life. Different microenvironments and time durations caused various personal integrated exposure (PIE). The stationary monitoring method for PIE was also compared and evaluated with PEK. Positive protection actions can be taken after understanding the major contribution to PM_2.5 exposure.     

Design and characterization of human exposure to generated sulfate and soot particles in a pilot chamber study

A number of literatures have documented adverse health effects of exposure to fine particulate matter (PM_2.5), and secondary sulfate aerosol and black carbon may contribute to health impacts of PM_2.5 exposure. We designed an exposure system to generate sulfate and traffic soot particles, and assessed the feasibility of using it for human exposure assessment in a pilot human exposure study. In the designed exposure system, average mass concentrations of generated sulfate and soot particles were 74.19μg/m³ and 11.54μg/m³ in the chamber and did not vary significantly during two-hour human exposure sessions. The size ranges of generated sulfate were largely between 20 to 200 nm, whereas those of generated soot particles were in the size ranges of 50 to 200nm. Following two-hour exposure to generated sulfate and soot particles, we observed significant increases in fractional exhaled NO (FeNO) in young and health subjects. Building on established human exposure system and health response follow-up methods, future full-scale studies focusing on the effects of mixed particulates and individual PM_2.5 components would provide data in understanding the underpinning cardio-respiratory outcomes in relation to air pollution mixture exposure.

Implications: Controlled exposure is a useful design to measure the biological responses repeatedly following particulate exposures of target components and set exposure at target levels of health concerns. Our study provides rational and establishes method for future full-scale studies to focus on examining the effects of mixed particulates and individual PM_2.5 components.     

Public health and components of particulate matter: The changing assessment of black carbon

In 2012, the WHO classified diesel emissions as carcinogenic, and its European branch suggested creating a public health standard for airborne black carbon (BC). In 2011, EU researchers found that life expectancy could be extended four to nine times by reducing a unit of BC, vs reducing a unit of PM_2.5. Only recently could such determinations be made. Steady improvements in research methodologies now enable such judgments.

In this Critical Review, we survey epidemiological and toxicological literature regarding carbonaceous combustion emissions, as research methodologies improved over time. Initially, we focus on studies of BC, diesel, and traffic emissions in the Western countries (where daily urban BC emissions are mainly from diesels). We examine effects of other carbonaceous emissions, e.g., residential burning of biomass and coal without controls, mainly in developing countries.

Throughout the 1990s, air pollution epidemiology studies rarely included species not routinely monitored. As additional PM_2.5. chemical species, including carbonaceous species, became more widely available after 1999, they were gradually included in epidemiological studies. Pollutant species concentrations which more accurately reflected subject exposure also improved models.

Natural “interventions” - reductions in emissions concurrent with fuel changes or increased combustion efficiency; introduction of ventilation in highway tunnels; implementation of electronic toll payment systems – demonstrated health benefits of reducing specific carbon emissions. Toxicology studies provided plausible biological mechanisms by which different PM species, e.g., carbonaceous species, may cause harm, aiding interpretation of epidemiological studies.

Our review finds that BC from various sources appears to be causally involved in all-cause, lung cancer, and cardiovascular mortality, morbidity, and perhaps adverse birth and nervous system effects. We recommend that the U.S. EPA rubric for judging possible causality of PM_2.5. mass concentrations, be used to assess which PM_2.5. species are most harmful to public health.

Implications: Black carbon (BC) and correlated co-emissions appear causally related with all-cause, cardiovascular, and lung cancer mortality, and perhaps with adverse birth outcomes and central nervous system effects. Such findings are recent, since widespread monitoring for BC is also recent. Helpful epidemiological advances (using many health relevant PM_2.5 species in models; using better measurements of subject exposure) have also occurred. “Natural intervention” studies also demonstrate harm from partly combusted carbonaceous emissions. Toxicology studies consistently find biological mechanisms explaining how such emissions can cause these adverse outcomes. A consistent mechanism for judging causality for different PM_2.5 species is suggested.

A list of acronyms will be found at the end of the article.     

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.     

Spatial differences in ambient coarse and fine particles in the Monterrey metropolitan area,Mexico: Implications for source contribution

The ambient air of the Monterrey Metropolitan Area (MMA) in Mexico frequently exhibits high levels of PM₁₀ and PM_2.5. However, no information exists on the chemical composition of coarse particles (PM_c = PM₁₀ – PM_2.5). A monitoring campaign was conducted during the summer of 2015, during which 24-hr average PM₁₀ and PM_2.5 samples were collected using high-volume filter-based instruments to chemically characterize the fine and coarse fractions of the PM. The collected samples were analyzed for anions (Cl^–, NO₃^–, SO₄^2–), cations (Na⁺, NH₄⁺, K⁺), organic carbon (OC), elemental carbon (EC), and 35 trace elements (Al to Pb). During the campaign, the average PM_2.5 concentrations did not showed significance differences among sampling sites, whereas the average PM_c concentrations did. In addition, the PM_c accounted for 75% to 90% of the PM₁₀ across the MMA. The average contribution of the main chemical species to the total mass indicated that geological material including Ca, Fe, Si, and Al (45%) and sulfates (11%) were the principal components of PM_c, whereas sulfates (54%) and organic matter (30%) were the principal components of PM_2.5. The OC-to-EC ratio for PM_c ranged from 4.4 to 13, whereas that for PM_2.5 ranged from 3.97 to 6.08. The estimated contribution of Secondary Organic Aerosol (SOA) to the total mass of organic aerosol in PM_2.5 was estimated to be around 70–80%; for PM_c, the contribution was lower (20–50%). The enrichment factors (EF) for most of the trace elements exhibited high values for PM_2.5 (EF: 10–1000) and low values for PM_c (EF: 1–10). Given the high contribution of crustal elements and the high values of EFs, PM_c is heavily influenced by soil resuspension and PM_2.5 by anthropogenic sources. Finally, the airborne particles found in the eastern region of the MMA were chemically distinguishable from those in its western region.

Implications: Concentration and chemical composition patterns of fine and coarse particles can vary significantly across the MMA. Public policy solutions have to be built based on these observations. There is clear evidence that the spatial variations in the MMA’s coarse fractions are influenced by clearly recognizable primary emission sources, while fine particles exhibit a homogeneous concentration field and a clear spatial pattern of increasing secondary contributions. Important reductions in the coarse fraction can come from primary particles’ emission controls; for fine particles, control of gaseous precursors—particularly sulfur-containing species and organic compounds—should be considered.     

Concentrations of aliphatic and polycyclic aromatic hydrocarbons in ambient PM2.5 and PM10 particulates in Doha,Qatar

Organic carbon (OC), elemental carbon (EC), and 90 organic compounds (36 polycyclic aromatic hydrocarbons [PAHs], 25 n-alkane homologues, 17 hopanes, and 12 steranes) were concurrently quantified in atmospheric particulate matter of PM_2.5 and PM₁₀. The 24-hr PM samples were collected using Harvard Impactors at a suburban site in Doha, Qatar, from May to December 2015. The mass concentrations (mean ± standard deviation) of PM_2.5 and PM₁₀ were 40 ± 15 and 145 ± 70 µg m^?3, respectively, exceeding the World Health Organization (WHO) air quality guidelines. Coarse particles comprised 70% of PM₁₀. Total carbonaceous contents accounted for 14% of PM_2.5 and 10% of PM₁₀ particulate mass. The major fraction (90%) of EC was associated with the PM_2.5. In contrast, 70% of OC content was found in the PM_2.5–10 fraction. The secondary OC accounted for 60–68% of the total OC in both PM fractions, indicating photochemical conversions of organics are much active in the area due to higher air temperatures and solar radiations. Among the studied compounds, n-alkanes were the most abundant group, followed by PAHs, hopanes, and steranes. n-Alkanes from C₂₅ to C₃₅ prevailed with a predominance of odd carbon numbered congeners (C₂₇–C₃₁). High-molecular-weight PAHs (5–6 rings) also prevailed, within their class, with benzo[b + j]fluoranthene (Bb + jF) being the dominant member. PAHs were mainly (80%) associated with the PM_2.5 fraction. Local vehicular and fugitive emissions were predominant during low-speed southeasterly winds from urban areas, while remote petrogenic/biogenic emissions were particularly significant under prevailing northwesterly wind conditions.

Implications: An unprecedented study in Qatar established concentration profiles of EC, OC, and 90 organic compounds in PM_2.5 and PM₁₀. Multiple tracer organic compounds for each source can be used for convincing source apportionment. Particle concentrations exceeded WHO air quality guidelines for 82–96% of the time, revealing a severe problem of atmospheric PM in Doha. Dominance of EC and PAHs in fine particles signifies contributions from combustion sources. Dependence of pollutants concentrations on wind speed and direction suggests their significant temporal and spatial variability, indicating opportunities for improving the air quality by identifying sources of airborne contaminants.     

Fugitive Dust Emission Source Profiles and Assessment of Selected Control Strategies for Particulate Matter at Gravel Processing Sites in Taiwan

Abstract

Particles emitted from gravel processing sites are one contributor to worsening air quality in Taiwan. Major pollution sources at gravel processing sites include gravel and sand piles, unpaved roads, material crushers, and bare ground. This study analyzed fugitive dust emission characteristics at each pollution source using several types of particle samplers, including total suspended particulates (TSP), suspended particulate (PM₁₀), fine suspended particulate (PM_2.5), particulate sizer, and dust-fall collectors. Furthermore, silt content and moisture in the gravel were measured to develop particulate emission factors. The results showed that TSP (<100 µm) concentrations at the boundary of gravel sites ranged from 280 to 1290 µg/m³, which clearly exceeds the Taiwan hourly air quality standard of 500 µg/m³. Moreover, PM₁₀ concentrations, ranging from 135 to 550 µg/m³, were also above the daily air quality standard of 125 µg/m³ and approximately 1.2 and 1.5 times the PM_2.5 concentrations, ranging from 105 to 470 µg/m³. The size distribution analysis reveals that mass mean diameter and geometric standard deviation ranged from 3.2 to 5.7 µm and from 2.82 to 5.51, respectively. In this study, spraying surfactant was the most effective control strategy to abate windblown dust from unpaved roads, having a control efficiency of approximately 93%, which is significantly higher than using paved road strategies with a control efficiency of approximately 45%. For paved roads, wet suppression provided the best dust control efficiencies ranging from 50 to 83%. Re-vegetation of disturbed ground had dust control efficiencies ranging from 48 to 64%.     

Forecasting of particulate matter time series using wavelet analysis and wavelet-ARMA/ARIMA model in Taiyuan,China

Particulate matter with aerodynamic diameter below 10 μm (PM₁₀) forecasting is difficult because of the uncertainties in describing the emission and meteorological fields. This paper proposed a wavelet-ARMA/ARIMA model to forecast the short-term series of the PM₁₀ concentrations. It was evaluated by experiments using a 10-year data set of daily PM₁₀ concentrations from 4 stations located in Taiyuan, China. The results indicated the following: (1) PM₁₀ concentrations of Taiyuan had a decreasing trend during 2005 to 2012 but increased in 2013. PM₁₀ concentrations had an obvious seasonal fluctuation related to coal-fired heating in winter and early spring. (2) Spatial differences among the four stations showed that the PM₁₀ concentrations in industrial and heavily trafficked areas were higher than those in residential and suburb areas. (3) Wavelet analysis revealed that the trend variation and the changes of the PM₁₀ concentration of Taiyuan were complicated. (4) The proposed wavelet-ARIMA model could be efficiently and successfully applied to the PM₁₀ forecasting field. Compared with the traditional ARMA/ARIMA methods, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction.

Implications: Wavelet analysis can filter noisy signals and identify the variation trend and the fluctuation of the PM₁₀ time-series data. Wavelet decomposition and reconstruction reduce the nonstationarity of the PM₁₀ time-series data, and thus improve the accuracy of the prediction. This paper proposed a wavelet-ARMA/ARIMA model to forecast the PM₁₀ time series. Compared with the traditional ARMA/ARIMA method, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. The proposed model could be efficiently and successfully applied to the PM₁₀ forecasting field.