Contribution of dust storms to PM10 levels in an urban arid environment

Quantitative information on the contribution of dust storms to atmospheric PM₁₀ (particulate matter with an aerodynamic diameter ≤10 µm) levels is still lacking, especially in urban environments with close proximity to dust sources. The main objective of this study was to quantify the contribution of dust storms to PM₁₀ concentrations in a desert urban center, the city of Beer-Sheva, Negev, Israel, during the period of 2001–2012. Toward this end, a background value based on the “dust-free” season was used as a threshold value to identify potentially “dust days.” Subsequently, the net contribution of dust storms to PM₁₀ was assessed. During the study period, daily PM₁₀ concentrations ranged from 6 to over 2000 µg/m³. In each year, over 10% of the daily concentrations exceeded the calculated threshold (BV_t) of 71 µg/m³. An average daily net contribution of dust to PM₁₀ of 122 µg/m³ was calculated for the entire study period based on this background value. Furthermore, a dust storm intensity parameter (Ai) was used to analyze several storms with very high PM₁₀ contributions (hourly averages of 1000–5197 μg/m³). This analysis revealed that the strongest storms occurred mainly in the last 3 yr of the study. Finally, these findings indicate that this arid urban environment experiences high PM₁₀ levels whose origin lies in both local and regional dust events.

Implications:The findings indicate that over time, the urban arid environment experiences high PM₁₀ levels whose origin lies in local and regional dust events. It was noticed that the strongest storms have occurred mainly in the last 3 yr. It is believed that environmental changes such as global warming and desertification may lead to an increased air pollution and risk exposure to human health.     

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.     

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.     

Windblown Dust Contributes to High PM25 Concentrations

ABSTRACT

The revised National Ambient Air Quality Standards for PM include fine particulate standards based upon mass measurements of PM₂₅. It is possible in arid and semi-arid regions to observe significant coarse mode intrusion in the PM_2.5 measurement. In this work, continuous PM₁₀, PM_2.5, and PM_1.0 were measured during several windblown dust events in Spokane, WA. PM_{2 5} constituted ~30% of the PM₁₀ during the dust event days, compared with ~48% on the non-dusty days preceding the dust events. Both PM₁₀ and PM_2.5 were enhanced during the dust events. However, PM_1.0 was not enhanced during dust storms that originated within the state of Washington. During a dust storm that originated in Asia and impacted Spokane, PM_1.0 was also enhanced, although the Asian dust reached Washington during a period of stagnation and poor dispersion, so that local sources were also contributing to high particulate levels. The “intermodal” region of PM, defined as particles ranging in aerodynamic size from 1.0 to 2.5 um, was found to represent a significant fraction of PM₂₅ (~51%) during windblown dust events, compared with 28% during the non-dusty days before the dust events.     

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.     

Implementation of a windblown dust parameterization into MODELS-3/CMAQ: Application to episodic PM events in the US/Mexico border

Windblown dust is known to impede visibility, deteriorate air quality and modify the radiation budget. Arid and semiarid areas with unpaved and unvegetated land cover are particularly prone to windblown dust, which is often attributed to high particulate matter (PM) pollution in such areas. Yet, windblown dust is poorly represented in existing regulatory air quality models. In a study by the authors on modeling episodic high PM events along the US/Mexico border using the state-of-the-art CMAQ/MM5/SMOKE air quality modeling system [Choi, Y.-J., Hyde, P., Fernando, H.J.S., 2006. Modeling of episodic particulate matter events using a 3D air quality model with fine grid: applications to a pair of cities in the US/Mexico border. Atmospheric Environment 40, 5181–5201], some of the observed PM₁₀ NAAQS exceedances were inferred as due to windblown dust, but the modeling system was incapable of dealing with time-dependent episodic dust entrainment during high wind periods. In this paper, a time-dependent entrainment parameterization for windblown dust is implemented in the CMAQ/MM5/SMOKE modeling system with the hope of improving PM predictions. An approach for realizing windblown dust emission flux for each grid cell over the study domain on an hourly basis, which accounts for the influence of factors such as soil moisture content, atmospheric stability and wind speed, is presented in detail. Comparison of model predictions with observational data taken at a pair of US/Mexico border towns shows a clear improvement of model performance upon implementation of the dust emission flux parameterization.     

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.     

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial,California, USA

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R² for converted hourly averaged Dylos mass measurements versus a PM_2.5 BAM was 0.79 and that versus a PM₁₀ BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM_2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R² = 0.35–0.81).

Implications: The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.     

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.     

Composition and secondary formation of fine particulate matter in the Salt Lake Valley: Winter 2009

Under the National Ambient Air Quality Standards (NAAQS), put in place as a result of the Clean Air Amendments of 1990, three regions in the state of Utah are in violation of the NAAQS for PM₁₀ and PM_2.5 (Salt Lake County, Ogden City, and Utah County). These regions are susceptible to strong inversions that can persist for days to weeks. This meteorology, coupled with the metropolitan nature of these regions, contributes to its violation of the NAAQS for PM during the winter. During January–February 2009, 1-hr averaged concentrations of PM_10-2.5, PM_2.5, NO_x, NO₂, NO, O₃, CO, and NH₃ were measured. Particulate-phase nitrate, nitrite, and sulfate and gas-phase HONO, HNO₃, and SO₂ were also measured on a 1-hr average basis. The results indicate that ammonium nitrate averages 40% of the total PM_2.5 mass in the absence of inversions and up to 69% during strong inversions. Also, the formation of ammonium nitrate is nitric acid limited. Overall, the lower boundary layer in the Salt Lake Valley appears to be oxidant and volatile organic carbon (VOC) limited with respect to ozone formation. The most effective way to reduce ammonium nitrate secondary particle formation during the inversions period is to reduce NO_x emissions. However, a decrease in NO_x will increase ozone concentrations. A better definition of the complete ozone isopleths would better inform this decision.

Implications: Monitoring of air pollution constituents in Salt Lake City, UT, during periods in which PM_2.5 concentrations exceeded the NAAQS, reveals that secondary aerosol formation for this region is NO_x limited. Therefore, NO_x emissions should be targeted in order to reduce secondary particle formation and PM_2.5. Data also indicate that the highest concentrations of sulfur dioxide are associated with winds from the north-northwest, the location of several small refineries.     

Characterization of summertime coarse particulate matter in the Desert Southwest—Arizona,USA

A year-long study was conducted in Pinal County, AZ, to characterize coarse (2.5 – 10 μm aerodynamic diameter, AD) and fine (< 2.5 μm AD) particulate matter (PMc and PMf, respectively) to further understand spatial and temporal variations in ambient PM concentrations and composition in rural, arid environments. Measurements of PMc and PMf mass, ions, elements, and carbon concentrations at one-in-six day resolution were obtained at three sites within the region. Results from the summer of 2009 and specifically the local monsoon period are presented.

The summer monsoon season (July – September) and associated rain and/or high wind events, has historically had the largest number of PM₁₀ NAAQS exceedances within a year. Rain events served to clean the atmosphere, decreasing PMc concentrations resulting in a more uniform spatial gradient among the sites. The monsoon period also is characterized by high wind events, increasing PMc mass concentrations, possibly due to increased local wind-driven soil erosion or transport. Two PM₁₀ NAAQS exceedances at the urban monitoring site were explained by high wind events and can likely be excluded from PM₁₀ compliance calculations as exceptional events. At the more rural Cowtown site, PM₁₀ NAAQS exceedances were more frequent, likely due to the impact from local dust sources.

PM mass concentrations at the Cowtown site were typically higher than at the Pinal County Housing and Casa Grande sites. Crustal material was equal to 52-63% of the PMc mass concentration on average. High concentrations of phosphate and organic carbon found at the rural Cowtown were associated with local cattle feeding operations. A relatively high correlation between PMc and PMf (R²?=?0.63) indicated that the lower tail of the coarse particle fraction often impacts the fine particle fraction, increasing the PMf concentrations. Therefore, reductions in PMc sources will likely also reduce PMf concentrations, which also are near the value of the 24-hr PM_2.5 NAAQS.

Implications: In the desert southwest, summer monsoons are often associated with above average PM₁₀ (<10 μm AD) mass concentrations. Competing influences of monsoon rain and wind events showed that rain suppresses ambient concentrations while high wind increase them. In this region, the PMc fraction dominates PM₁₀ and crustal sources contribute 52-63% to local PMc mass concentrations on average. Cattle feedlot emissions are also an important source and a unique chemical signature was identified for this source. Observations suggest monsoon wind events alone cannot explain PM₁₀ NAAQS exceedances, thus requiring these values to remain in compliance calculations rather than being removed as exceptional wind events.     

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.     

Air quality modeling for effective environmental management in the mining region

Air quality in the mining sector is a serious environmental concern and associated with many health issues. Air quality management in mining regions has been facing many challenges due to lack of understanding of atmospheric factors and physical removal mechanisms. A modeling approach called the mining air dispersion model (MADM) is developed to predict air pollutants concentration in the mining region while considering the deposition effect. The model takes into account the planet’s boundary conditions and assumes that the eddy diffusivity depends on the downwind distance. The developed MADM is applied to a mining site in Canada. The model provides values for the predicted concentrations of PM₁₀, PM_2.5, TSP, NO₂, and six heavy metals (As, Pb, Hg, Cd, Zn, Cr) at various receptor locations. The model shows that neutral stability conditions are dominant for the study site. The maximum mixing height is achieved (1280 m) during the evening in summer, and the minimum mixing height (380 m) is attained during the evening in winter. The dust fall (PM coarse) deposition flux is maximum during February and March with a deposition velocity of 4.67 cm/sec. The results are evaluated with the monitoring field values, revealing a good agreement for the target air pollutants with R-squared ranging from 0.72 to 0.96 for PM_2.5, from 0.71 to 0.82 for PM₁₀, and from 0.71 to 0.89 for NO₂. The analyses illustrate that the presented algorithm in this model can be used to assess air quality for the mining site in a systematic way. Comparisons of MADM and CALPUFF modeling values are made for four different pollutants (PM_2.5, PM₁₀, TSP, and NO₂) under three different atmospheric stability classes (stable, neutral, and unstable). Further, MADM results are statistically tested against CALPUFF for the air pollutants and model performance is found satisfactory.

Implications: The mathematical model (MADM) is developed by extending the Gaussian equation particularly when examining the settling process of important pollutants for the industrial region. Physical removal effects of air pollutants with field data have been considerred for the MADM development and for an extensive field case study. The model is well validated in the field of an open pit mine to assess the regional air quality. The MADA model helps to facilitate the management of the mining industry in doing estimation of emission rate around mining activities and predicting the resulted concentration of air pollutants together in one integrated approach.     

Experimental investigation of vegetative environment buffers in reducing particulate matters emitted from ventilated poultry house

Scientists have effectively proved that vegetative environment buffers (VEBs) can be used for reducing dust emissions from livestock buildings, but they have seen fewer tests in poultry farms. A field research was conducted to assess the effectiveness of VEBs on reducing downwind transport of particulate matter (PM) from a ventilated poultry house in Changchun. Five plant species transferred from local area were used to establish five diverse VEBs and separately installed outside of the ventilation fans in summer 2017. The five plant species were Winged Euonymus (WE), Malus Spectabilis (MS), Padus Maackii (PAA), Acer Saccharum Marsh (ASM), and Padus Virginiana “Red Select Shrub” (PV_RSS). The mass concentrations of PM_2.5 and PM₁₀ (particulate matter with an aerodynamic diameter of 2.5 μm and 10 μm or less, respectively) were monitored at downwind and upwind sampling locations around the VEB. The results showed that with the presenting of VEBs, the particle concentrations at the downwind sampling point were significantly reduced compared with that at the upwind sampling point (p < 0.05). Specifically, compared to the control test without VEB, the VEB with PV_RSS had the best PM concentration reduction rate (CRR) of 47.24%±4.33% and 41.13%±5.83% for PM_2.5 and PM₁₀, respectively. The rough surface of plant leaves may help intercept more PM, though it was also affected by other factors (such as the blade angle, the interaction with wind) needed to be further investigated. The VEB with PV_RSS, which presented the best capacity of CRR, selectively intercepted PM, mainly related to the elements of N, Na, Mg, P, S, and Cl.

Implications: Five plant species, including WE, PAA, MS, ASM, and PV_RSS, were evaluated as VEBs to mitigate particulate emissions from outside of a ventilated poultry house in Changchun. They all significantly reduced particulate matter emissions. However, the PV_RSS presented the best capability of trapping fine and coarse particles: PM_2.5 and PM₁₀, respectively, while the PAA was the worst one. The microstructure of leaves affected particle deposition and remaining on the leaves, and PV_RSS selectively intercepted particulate matter mainly related to certain elements.     

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.     

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.     

Purification characteristics of fine particulate matter treated by a self-flushing wet electrostatic precipitator equipped with a flexible electrode

A self-flushing wet electrostatic precipitator was developed to investigate the removal performance for fine particles. Flexible material (polypropylene, 840A) and carbon steel in the form of a spiked band were adopted as the collection plate and discharge electrode, respectively. The particle concentration, morphology, and trace-element content were measured by electric low-pressure impactor, scanning electron microscope, and energy-dispersive x-ray spectroscopy, respectively, before and after the electrostatic precipitator. With increasing gas velocity, the collection efficiency of fine particles (up to 0.8 μm in diameter) increased, while it decreased for particles with diameters larger than 0.8 μm. Increasing the dust inlet concentration increased the collection efficiency up to a point, from which it then declined gradually with further increases in the inlet concentration. The particulate matter after the wet electrostatic precipitator showed different degrees of agglomeration. The collection efficiency of trace elements within PM₁₀ was less than that of the PM₁₀ itself. Notably, the water consumption in the current setup was significantly lower than for other treatment processes of comparable collection efficiencies.

Implications: Wet electrostatic precipitators, as fine filtration equipment, were generally applicable to coal-fired plants to reduce PM_2.5 emissions in China. However, high energy consumption and unstable operation, such as water usage and spray washing directly in the electric field, seriously restricted the further development. The utilization of self-flushing wet electrostatic precipitator can solve these problems to some extent.     

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.     

Investigation and modeling of the residential infiltration of fine particulate matter in Beijing,China

The objective of this study was to estimate the residential infiltration factor (Finf) of fine particulate matter (PM_2.5) and to develop models to predict PM_2.5 Finf in Beijing. Eighty-eight paired indoor–outdoor PM_2.5 samples were collected by Teflon filters for seven consecutive days during both non-heating and heating seasons (from a total of 55 families between August, 2013 and February, 2014). The mass concentrations of PM_2.5 were measured by gravimetric method, and elemental concentrations of sulfur in filter deposits were determined by energy-dispersive x-ray fluorescence (ED-XRF) spectrometry. PM_2.5 Finf was estimated as the indoor/outdoor sulfur ratio. Multiple linear regression was used to construct Finf predicting models. The residential PM_2.5 Finf in non-heating season (0.70 ± 0.21, median = 0.78, n = 43) was significantly greater than in heating season (0.54 ± 0.18, median = 0.52, n = 45, p < 0.001). Outdoor temperature, window width, frequency of window opening, and air conditioner use were the most important predictors during non-heating season, which could explain 57% variations across residences, while the outdoor temperature was the only predictor identified in heating season, which could explain 18% variations across residences. The substantial variations of PM_2.5 Finf between seasons and among residences found in this study highlight the importance of incorporating Finf into exposure assessment in epidemiological studies of air pollution and human health in Beijing. The Finf predicting models developed in this study hold promise for incorporating PM_2.5 Finf into large epidemiology studies, thereby reducing exposure misclassification.

Implications: Failure to consider the differences between indoor and outdoor PM_2.5 may contribute to exposure misclassification in epidemiological studies estimating exposure from a central site measurement. This study was conducted in Beijing to investigate residential PM_2.5 infiltration factor and to develop a localized predictive model in both nonheating and heating seasons. High variations of PM_2.5 infiltration factor between the two seasons and across homes within each season were found, highlighting the importance of including infiltration factor in the assessment of exposure to PM_2.5 of outdoor origin in epidemiological studies. Localized predictive models for PM_2.5 infiltration factor were also developed.     

Projected changes in particulate matter concentrations in the South Coast Air Basin due to basin-wide reductions in nitrogen oxides,volatile organic compounds,and ammonia emissions

An ozone abatement strategy for the South Coast Air Basin (SoCAB) has been proposed by the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (ARB). The proposed emissions reduction strategy is focused on the reduction of nitrogen oxide (NO_x) emissions by the year 2030. Two high PM_2.5 concentration episodes with high ammonium nitrate compositions occurring during September and November 2008 were simulated with the Community Multi-scale Air Quality model (CMAQ). All simulations were made with same meteorological files provided by the SCAQMD to allow them to be more directly compared with their previous modeling studies. Although there was an overall under-prediction bias, the CMAQ simulations were within an overall normalized mean error of 50%; a range that is considered acceptable performance for PM modeling. A range of simulations of these episodes were made to evaluate sensitivity to NO_x and ammonia emissions inputs for the future year 2030. It was found that the current ozone control strategy will reduce daily average PM_2.5 concentrations. However, the targeted NO_x reductions for ozone were not found to be optimal for reducing PM_2.5 concentrations. Ammonia emission reductions reduced PM_2.5 and this might be considered as part of a PM_2.5 control strategy.

Implications: The SCAQMD and the ARB have proposed an ozone abatement strategy for the SoCAB that focuses on NO_x emission reductions. Their strategy will affect both ozone and PM_2.5. Two episodes that occurred during September and November 2008 with high PM_2.5 concentrations and high ammonium nitrate composition were selected for simulation with different levels of nitrogen oxide and ammonia emissions for the future year 2030. It was found that the ozone control strategy will reduce maximum daily average PM_2.5 concentrations but its effect on PM_2.5 concentrations is not optimal.