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 in California: Part 2—Spatial,Temporal, and Compositional Patterns of PM2.5, PM10–2.5, and PM10

Abstract

Geographic and temporal variations in the concentration and composition of particulate matter (PM) provide important insights into particle sources, atmospheric processes that influence particle formation, and PM management strategies. In the nonurban areas of California, annual-average PM_2.5 and PM₁₀ concentrations range from 3 to 10 [H9262]g/m³ and from 5 to 18 µg/m³, respectively. In the urban areas of California, annual-averages for PM_2.5 range from 7 to 30 [H9262]g/m³, with observed 24-hr peaks reaching levels as high as 160 [H9262]g/m³. Within each air basin, exceedances are a mixture of isolated events as well as periods of elevated PM_2.5 concentrations that are more prolonged and regional in nature. PM_2.5 concentrations are generally highest during the winter months. The exception is the South Coast Air Basin, where fairly high values occur throughout the year. Annual-average PM_2.5 mass, as well as the concentrations of major components, declined from 1988 to 2000. The declines are especially pronounced for the sulfate (SO₄ ^2?) and nitrate (NO₃ ^?) components of PM_2.5 and PM₁₀ and correlate with reductions in ambient levels of oxides of sulfur (SO_x) and oxides of nitrogen (NO_x). Annual averages for PM_10–2.5 and PM₁₀ exhibited similar downwind trends from 1994 to 1999, with a slightly less pronounced decrease in the coarse fraction.     

Particulate matter,nitrogen oxides,ozone, and select volatile organic compounds during a winter sampling period in Logan,Utah, USA

Particulate matter mass (PM), trace gaseous pollutants, and select volatile organic compounds (VOCs) with meteorological variables were measured in Logan, Utah (Cache Valley), for >4 weeks during winter 2017 as part of the Utah Winter Fine Particle Study (UWFPS). Higher PM levels for short time periods and lower ozone (O₃) levels were present due to meteorological and mountain valley conditions. Nitrogenous pollutants were relatively strongly correlated with PM variables. Diurnal cycles of NO_x, O₃, and fine PM(PM 2.5) (aerodynamic diameter <2.5 μm [PM_2.5]) suggested formation from NO_x. O₃ levels increased from early morning into midafternoon, and NO_x and PM_2.5 increased throughout the morning, followed by sharp decreases. Toluene/benzene and xylenes/benzene ratios and VOC correlations with nitrogenous and PM species were indicative of local traffic sources. Wind sector comparisons suggested that pollutant levels were lower when winds were from nearby mountains to the east versus winds from northerly or southerly origins.

Implications: The Cache Valley in Idaho and Utah has been designated a PM_2.5 nonattainment area that has been attributed to air pollution buildup during winter stagnation events. To inform state implementation plans for PM_2.5 in Cache Valley and other PM_2.5 nonattainment areas in Utah, a state and multiagency federal research effort known as the UWFPS was conducted in winter 2017. As part of the UWFPS, the U.S. Environmental Protection Agency (EPA) measured ground-based PM species and their precursors, VOCs, and meteorology in Logan, Utah. Results reported here from the EPA study in Logan provide additional understanding of wintertime air pollution conditions and possible sources of PM and gaseous pollutants as well as being useful for future PM control strategies in this area.     

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

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

Exposure to ultrafine particles and PM2.5 in four Sydney transport modes

Concentrations of ultrafine (<0.1 μm) particles (UFPs) and PM_2.5 (<2.5 μm) were measured whilst commuting along a similar route by train, bus, ferry and automobile in Sydney, Australia. One trip on each transport mode was undertaken during both morning and evening peak hours throughout a working week, for a total of 40 trips. Analyses comprised one-way ANOVA to compare overall (i.e. all trips combined) geometric mean concentrations of both particle fractions measured across transport modes, and assessment of both the correlation between wind speed and individual trip means of UFPs and PM_2.5, and the correlation between the two particle fractions. Overall geometric mean concentrations of UFPs and PM_2.5 ranged from 2.8 (train) to 8.4 (bus) × 10⁴ particles cm^?3 and 22.6 (automobile) to 29.6 (bus) μg m^?3, respectively, and a statistically significant difference (p < 0.001) between modes was found for both particle fractions. Individual trip geometric mean concentrations were between 9.7 × 10³ (train) and 2.2 × 10⁵ (bus) particles cm^?3 and 9.5 (train) to 78.7 (train) μg m^?3. Estimated commuter exposures were variable, and the highest return trip mean PM_2.5 exposure occurred in the ferry mode, whilst the highest UFP exposure occurred during bus trips. The correlation between fractions was generally poor, and in keeping with the duality of particle mass and number emissions in vehicle-dominated urban areas. Wind speed was negatively correlated with, and a generally poor determinant of, UFP and PM_2.5 concentrations, suggesting a more significant role for other factors in determining commuter exposure.     

Development of a PM2 5 Emissions Inventory for the South Coast Air Basin

ABSTRACT

With the promulgation of a national PM_2.5 ambient air quality standard, it is important that PM_2.5 emissions inventories be developed as a tool for understanding the magnitude of potential PM2.5 violations. Current PM₁₀ inventories include only emissions of primary particulate matter (1 ^ï PM), whereas, based on ambient measurements, both PM₁₀ and PM2.5 emissions inventories will need to include sources of both 1^ï PM and secondary particulate matter (2^ï PM). Furthermore, the U. S. Environmental Protection Agency’s (EPA) current edition of AP-42 includes size distribution data for 1o PM that overestimate the PM_2.5 fraction of fugitive dust sources by at least a factor of 2 based on recent studies.

This paper presents a PM_2.5 emissions inventory developed for the South Coast Air Basin (SCAB) that for the first time includes both 1^ï PM and 2^ï PM. The former is calculated by multiplying PM₁₀ emissions estimates by the PM_2.5/PM₁₀ ratios for different sources. The latter is calculated from estimated emission rates of gas-phase aerosol precursor and gas to aerosol conversion rates consistent with the measured chemical composition of ambient PM_2.5 concentrations observed in the SCAB. The major finding of this PM_2.5 emissions inventory is that the ^2ï aerosol component is more than twice the ^1ï aerosol component, which may result in widely different control strategies being required for fine PM and coarse PM.     

Concentration and characterization of airborne particles in Tehran’s subway system

Particulate matter is an important air pollutant, especially in closed environments like underground subway stations. In this study, a total of 13 elements were determined from PM₁₀ and PM_2.5 samples collected at two subway stations (Imam Khomeini and Sadeghiye) in Tehran’s subway system. Sampling was conducted in April to August 2011 to measure PM concentrations in platform and adjacent outdoor air of the stations. In the Imam Khomeini station, the average concentrations of PM₁₀ and PM_2.5 were 94.4?±?26.3 and 52.3?±?16.5 μg m^?3 in the platform and 81.8?±?22.2 and 35?±?17.6 μg m^?3 in the outdoor air, respectively. In the Sadeghiye station, mean concentrations of PM₁₀ and PM_2.5 were 87.6?±?23 and 41.3?±?20.4 μg m^?3 in the platform and 73.9?±?17.3 and 30?±?15 μg m^?3, in the outdoor air, respectively. The relative contribution of elemental components in each particle fraction were accounted for 43 % (PM₁₀) and 47.7 % (PM_2.5) in platform of Imam Khomeini station and 15.9 % (PM₁₀) and 18.5 % (PM_2.5) in the outdoor air of this station. Also, at the Sadeghiye station, each fraction accounted for 31.6 % (PM₁₀) and 39.8 % (PM_2.5) in platform and was 11.7 % (PM₁₀) and 14.3 % (PM_2.5) in the outdoor. At the Imam Khomeini station, Fe was the predominant element to represent 32.4 and 36 % of the total mass of PM₁₀ and PM_2.5 in the platform and 11.5 and 13.3 % in the outdoor, respectively. At the Sadeghiye station, this element represented 22.7 and 29.8 % of total mass of PM₁₀ and PM_2.5 in the platform and 8.7 and 10.5 % in the outdoor air, respectively. Other major crustal elements were 5.8 % (PM₁₀) and 5.3 % (PM_2.5) in the Imam Khomeini station platform and 2.3 and 2.4 % in the outdoor air, respectively. The proportion of other minor elements was significantly lower, actually less than 7 % in total samples, and V was the minor concentration in total mass of PM₁₀ and PM_2.5 in both platform stations.     

Particulate matter emissions of different brands of mentholated cigarettes

Inhaling particulate matter (PM) in environmental tobacco smoke (ETS) endangers the health of nonsmokers. Menthol, an additive in cigarettes, attenuates respiratory irritation of tobacco smoke. It reduces perceptibility of smoke and therefore passive smokers may inhale ETS unnoticed. To investigate a possible effect of menthol on PM concentrations (PM₁₀, PM_2.5, and PM₁), ETS of four mentholated cigarette brands (Elixyr Menthol, Winston Menthol, Reyno Classic, and Pall Mall Menthol Blast) with varying menthol content was analyzed. ETS was generated in a standardized way using an automatic environmental tobacco smoke emitter (AETSE), followed by laser aerosol spectrometry. This analysis shows that the tested cigarette brands, despite having different menthol concentrations, do not show differences with regard to PM emissions, with the exception of Reyno Classic, which shows an increased emission, although the menthol level ranged in the midfield. More than 90% of the emitted particles had a size smaller than or equal to 1 µm. Regardless of the menthol level, the count median diameter (CMD) and the mass median diameter (MMD) were found to be 0.3 µm and 0.5 µm, respectively. These results point out that there is no effect of menthol on PM emission and that other additives might influence the increased PM emission of Reyno Classic.

Implications: Particulate matter (PM) in ETS endangers the health of nonsmokers and smokers. This study considers the effect of menthol, an additive in cigarettes, on PM emissions. Does menthol increase the amount of PM? Due to the exposure to secondhand smoke nearly 900,000 people die each year worldwide. The aim of the study is to measure the particle concentration (L^?1), mass concentration (µg m^?3), and dust mass fractions shown as PM₁₀, PM_2.5, and PM₁ of five different cigarette brands, including four with different menthol concentrations and one menthol-free reference cigarette, in a well-established standardized system.     

Particulate Air Pollution in Mexico City: A Collaborative Research Project

ABSTRACT

PM₁₀, PM₂₅, precursor gas, and upper-air meteorological measurements were taken in Mexico City, Mexico, from February 23 to March 22, 1997, to understand concentrations and chemical compositions of the city's particulate matter (PM). Average 24-hr PM₁₀ concentrations over the period of study at the core sites in the city were 75 H g/m³. The 24-hr standard of 150 μ g/m³ was exceeded for seven samples taken during the study period; the maximum 24-hr concentration measured was 542 μ g/m³. Nearly half of the PM₁₀ was composed of fugitive dust from roadways, construction, and bare land. About 50% of the PM₁₀ consisted of PM_2.5, with higher percentages during the morning hours. Organic and black carbon constituted up to half of the PM_2.5. PM concentrations were highest during the early morning and after sunset, when the mixed layers were shallow. Meteorological measurements taken during the field campaign show that on most days air was transported out of the Mexico City basin during the afternoon with little day-to-day carryover.     

PM2.5, soot and NO2 indoor–outdoor relationships at homes,pre-schools and schools in Stockholm,Sweden

In developed nations people spend about 90% of their time indoors. The relationship between indoor and outdoor air pollution levels is important for the understanding of the health effects of outdoor air pollution. Although other studies describe both the outdoor and indoor atmospheric environment, few excluded a priori major indoor sources, measured the air exchange rate, included more than one micro-environment and included the presence of human activity. PM_2.5, soot, NO₂ and the air exchange rate were measured during winter and summer indoors and outdoors at 18 homes (mostly apartments) of 18 children (6–11-years-old) and also at the six schools and 10 pre-schools that the children attended. The three types of indoor environments were free of environmental tobacco smoke and gas appliances, as the aim was to asses to what extent PM_2.5, soot and NO₂ infiltrate from outdoors to indoors. The median indoor and outdoor PM_2.5 levels were 8.4 μg m^?3 and 9.3 μg m^?3, respectively. The median indoor levels for soot and NO₂ were 0.66 m^?1 × 10^?5 and 10.0 μg m^?3, respectively. The respective outdoor levels were 0.96 m^?1 × 10^?5 and 12.4 μg m^?3. The median indoor/outdoor (I/O) ratios were 0.93, 0.76 and 0.92 for PM_2.5, soot and NO₂, respectively. Their infiltration factors were influenced by the micro-environment, ventilation type and air exchange rate, with aggregated values of 0.25, 0.55 and 0.64, respectively. Indoor and outdoor NO₂ levels were strongly associated (R² = 0.71), followed by soot (R² = 0.50) and PM_2.5 (R² = 0.16). In Stockholm, the three major indoor environments occupied by children offer little protection against combustion-related particles and gases in the outdoor air. Outdoor PM_2.5 seems to infiltrate less, but indoor sources compensate.     

Major air pollutants in Bursa,Turkey: their levels,temporal changes,interactions, and sources

Bursa is one of the largest cities of Turkey and it hosts 17 organized industrial zones. Parallel to the increase in population, rapidly growing energy consumption, and increased numbers of transport vehicles have impacts on the air quality of the city. In this study, regularly calibrated automatic samplers were employed to get the levels of air pollution in Bursa. The concentrations of CH₄ and N-CH₄ as well as the major air pollutants including PM₁₀, PM_2.5, NO, NO₂, NO_x, SO₂, CO, and O₃, were determined for 2016 and 2017 calendar years. Their levels were 1641.62?±?718.25, 33.11?±?5.45, 42.10?±?10.09, 26.41?±?9.01, 19.47?±?16.51, 46.73?±?16.56, 66.23?±?32.265, 7.60?±?3.43, 659.397?±?192.73, and 51.92?±?25.63 µg/m³ for 2016, respectively. Except for O₃, seasonal concentrations were higher in winter and autumn for both years. O₃, CO, and SO₂ had never exceeded the limit values specified in the regulations yet PM₁₀, PM_2.5, and NO₂ had violated the limits in some days. The ratios of CO/NO_x, SO₂/NO_x, and PM_2.5/PM₁₀ were examined to characterize the emission sources. Generally, domestic and industrial emissions were dominated in the fall and winter seasons, yet traffic emissions were effective in spring and summer seasons. As a result of the correlation process between O_x and NO_x, it was concluded that the most important source of O_x concentrations in winter was NO_x and O₃ was in summer.     

Characterizing and predicting coarse and fine particulates in classrooms located close to an urban roadway

The PM₁₀, PM_2.5, and PM₁ (particulate matter with aerodynamic diameters <10, <2.5, and <1 μm, respectively) concentrations were monitored over a 90-day period in a naturally ventilated school building located at roadside in Chennai City. The 24-hr average PM₁₀, PM_2.5, and PM₁ concentrations at indoor and outdoor environments were found to be 136 ± 60, 36 ± 15, and 20 ± 12 and 76 ± 42, 33 ± 16, and 23 ± 14 μg/m³, respectively. The size distribution of PM in the classroom indicated that coarse mode was dominant during working hours (08:00 a.m. to 04:00 p.m.), whereas fine mode was dominant during nonworking hours (04:00 p.m. to 08:00 a.m.). The increase in coarser particles coincided with occupant activities in the classrooms and finer particles were correlated with outdoor traffic. Analysis of indoor PM₁₀, PM_2.5, and PM₁ concentrations monitored at another school, which is located at urban reserved forest area (background site) indicated 3–4 times lower PM₁₀ concentration than the school located at roadside. Also, the indoor PM₁ and PM_2.5 concentrations were 1.3–1.5 times lower at background site. Further, a mass balance indoor air quality (IAQ) model was modified to predict the indoor PM concentration in the classroom. Results indicated good agreement between the predicted and measured indoor PM_2.5 (R² = 0.72–0.81) and PM₁ (R² = 0.81–0.87) concentrations. But, the measured and predicted PM₁₀ concentrations showed poor correlation (R² = 0.17–0.23), which may be because the IAQ model could not take into account the sudden increase in PM₁₀ concentration (resuspension of large size particles) due to human activities.

Implications:The present study discusses characteristics of the indoor coarse and fine PM concentrations of a naturally ventilated school building located close to an urban roadway and at a background site in Chennai City, India. The study results will be useful to engineers and policymakers to prepare strategies for improving the IAQ inside classrooms. Further, this study may help in the development of IAQ standards and guidelines in India.     

Temporal variations of atmospheric aerosol in four European urban areas

Purpose

The concentrations of PM₁₀ mass, PM_2.5 mass and particle number were continuously measured for 18 months in urban background locations across Europe to determine the spatial and temporal variability of particulate matter.

Methods

Daily PM₁₀ and PM_2.5 samples were continuously collected from October 2002 to April 2004 in background areas in Helsinki, Athens, Amsterdam and Birmingham. Particle mass was determined using analytical microbalances with precision of 1 ??g. Pre- and post-reflectance measurements were taken using smoke-stain reflectometers. One-minute measurements of particle number were obtained using condensation particle counters.

Results

The 18-month mean PM₁₀ and PM_2.5 mass concentrations ranged from 15.4 ??g/m³ in Helsinki to 56.7 ??g/m³ in Athens and from 9.0 ??g/m³ in Helsinki to 25.0 ??g/m³ in Athens, respectively. Particle number concentrations ranged from 10,091 part/cm³ in Helsinki to 24,180 part/cm³ in Athens with highest levels being measured in winter. Fine particles accounted for more than 60% of PM₁₀ with the exception of Athens where PM_2.5 comprised 43% of PM₁₀. Higher PM mass and number concentrations were measured in winter as compared to summer in all urban areas at a significance level p?Conclusions Significant quantitative and qualitative differences for particle mass across the four urban areas in Europe were observed. These were due to strong local and regional characteristics of particulate pollution sources which contribute to the heterogeneity of health responses. In addition, these findings also bear on the ability of different countries to comply with existing directives and the effectiveness of mitigation policies.     

Fine particulate speciation profile and emission factor of municipal solid waste incinerator established by dilution sampling method

In this study, fine particulate matter (PM_2.5) emitted from a municipal solid waste incinerator (MSWI) was collected using dilution sampling method. Chemical compositions of the collected PM_2.5 samples, including carbon content, metal elements, and water-soluble ions, were analyzed. Traditional in-stack hot sampling was simultaneously conducted to compare the influences of dilution on PM_2.5 emissions and the characteristics of the bonded chemical species. The results, established by a dilution sampling method, show that PM_2.5 and total particulate matter (TPM) emission factors were 61.6 ± 4.52 and 66.1 ± 5.27 g ton-waste^?1, respectively. The average ratio of PM_2.5/TPM is 0.93, indicating that more than 90% of PM emission from the MSWI was fine particulate. The major chemical species in PM_2.5 included organic carbon (OC), Cl^?, NH₄⁺, elemental carbon (EC) and Si, which account for 69.7% of PM_2.5 mass. OC was from the unburned carbon in the exhaust, which adsorbed onto the particulate during the cooling process. High Cl^? emission is primarily attributable to wastes containing plastic bags made of polyvinyl chloride, salt in kitchen refuse and waste biomass, and so on. Minor species that account for 0.01–1% of PM_2.5 mass included SO₄^2-, K⁺, Na, K, NO₃^?, Al, Ca²⁺, Zn, Ca, Cu, Fe, Pb, and Mg. The mean ratio of dilution method/in-stack hot method was 0.454. The contents of water-soluble ions (Cl^?, SO₄^2-, NO₃^?) were significantly enriched in PM_2.5 via gas-to-particle conversion in the dilution process. Results indicate that in-stack hot sampling would underestimate levels of these species in PM_2.5.

Implications: PM_2.5 samples from a municipal solid waste incinerator (MSWI) were collected simultaneously by a dilution sampling technique and a traditional in-stack method. PM_2.5 emission factors and chemical speciation profiles were established. Dilution sampling provides more reliable data than in-stack hot sampling. The results can be applied to estimate the PM_2.5 emission inventories of MSWI, and the source profile can be used for contribution estimate of chemical mass balance modeling.     

Concentration,size, and density of total suspended particulates at the air exhaust of concentrated animal feeding operations

Total suspended particulate (TSP) samples were seasonally collected at the air exhaust of 15 commercial concentrated animal feeding operations (CAFOs; including swine finishing, swine farrowing, swine gestation, laying hen, and tom turkey) in the U.S. Midwest. The measured TSP concentrations ranged from 0.38 ± 0.04 mg m^?3 (swine gestation in summer) to 10.9 ± 3.9 mg m^?3 (tom turkey in winter) and were significantly affected by animal species, housing facility type, feeder type (dry or wet), and season. The average particle size of collected TSP samples in terms of mass median equivalent spherical diameter ranged from 14.8 ± 0.5 µm (swine finishing in winter) to 30.5 ± 2.0 µm (tom turkey in summer) and showed a significant seasonal effect. This finding affirmed that particulate matter (PM) released from CAFOs contains a significant portion of large particles. The measured particle size distribution (PSD) and the density of deposited particles (on average 1.65 ± 0.13 g cm^?3) were used to estimate the mass fractions of PM₁₀ and PM_2.5 (PM ≤10 and ≤2.5 μm, respectively) in the collected TSP. The results showed that the PM₁₀ fractions ranged from 12.7 ± 5.1% (tom turkey) to 21.1 ± 3.2% (swine finishing), whereas the PM_2.5 fractions ranged from 3.4 ± 1.9% (tom turkey) to 5.7 ± 3.2% (swine finishing) and were smaller than 9.0% at all visited CAFOs. This study applied a filter-based method for PSD measurement and deposited particles as a surrogate to estimate the TSP’s particle density. The limitations, along with the assumptions adopted during the calculation of PM mass fractions, must be recognized when comparing the findings to other studies.

Implications: The concentration, size, and density of TSP samples varied greatly with animal species, housing facility type, feeder type, and season, suggesting that PM emission data derived from limited measurements may not be readily applied to estimate the overall emission from concentrated animal feeding operations (CAFOs). This study also affirmed that particles released from CAFOs is of relatively high density (~1.65 g cm^?3) and with diameter mostly larger than 10 µm, indicating that regular PM abatement devices, such as cyclones, fabric filters, or even a simple downward-facing exhaust duct, may be employed to mitigate the TSP emission with acceptable efficiency.     

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

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

Optical and thermal characteristics of carbonaceous aerosols measured at an urban site in Gwangju,Korea, in the winter of 2011

Carbonaceous components (organic carbon [OC] and elemental carbon [EC]) and optical properties (light absorption and scattering) of fine particulate matter (aerodynamic diameter <2.5 μm; PM_2.5) were simultaneously measured at an urban site in Gwangju, Korea, during the winter of 2011. OC was further classified into OC1, OC2, OC3, and OC4, based on a temperature protocol using a Sunset OC/EC analyzer. The average OC and EC concentrations were 5.0 ± 2.5 and 1.7 ± 0.9 μg C m^?3, respectively. The average single-scattering albedo (SSA) at a wavelength of 550 nm was 0.58 ± 0.11, suggesting that the aerosols observed in the winter of 2011 had a local warming effect in this area. During the whole sampling period, “stagnant PM” and “long-range transport PM” events were identified. The light absorption coefficient (b_abs) was higher during the stagnant PM event than during the long-range transport PM event due to the existence of abundant light-absorbing OC during the stagnant PM event. In particular, the OC2 and OC3 concentrations were higher during the stagnant PM event than those during the long-range transport event, suggesting that OC2 and OC3 might be more related to the light-absorbing OC. The light scattering coefficient (b_scat) was similar between the events. On average, the mass absorption efficiency attributed to EC (σ_EC) was 9.6 m² g^?1, whereas the efficiency attributed to OC (σ_OC) was 1.8 m² g^?1 at λ = 550 nm. Furthermore, the σ_EC is comparable among the PM event days, but the σ_OC for the stagnant PM event was significantly higher than that for the long-range transport PM event (1.7 vs. 0.5).

Implications: Optical and thermal properties of carbonaceous aerosol were measured at Gwangju, and carbonaceous aerosol concentration and optical property varied between “stagnant PM” and “long-range transport PM” events. More abundant light absorbing OC was observed during the stagnant PM event.     

Comparisons of ambient air particulates concentrations (TSP,PM2.5) and dry depositions during smog and non-smog periods at Luliao,Shalu District sampling site

The concentrations of ambient total suspended particulates (TSP) and PM_2.5, and the dry depositions at a sample site at Luliao Junior High School (Luliao) in central Taiwan were measured during smog and non-smog days between December 2017 and July 2018. The results are compared to those obtained during non-smog periods in the years 2015–2017. The mean TSP and PM_2.5 concentrations and dry deposition flux were 72.41?±?26.40, 41.88?±?23.51?μg/m³, and 797.57?±?731.46?μg/m² min, respectively, on the smog days. The mean TSP and PM_2.5 concentrations and dry deposition flux on the non-smog days were 56.39?±?18.08, 34.81?±?12.59?μg/m³ and 468.93?±?600.57?μg/m² min, respectively. The mean TSP concentration in the smog period was 28% greater than that in the non-smog period, and the mean PM_2.5 concentration was 20% higher. The mean dry deposition flux in the smog period was 70% higher than that in the non-smog period at Luliao. The PM_2.5 concentrations exceeded the standards set by the Taiwan EPA (35?μg/m³ daily, and 15?μg/m³ annually). Therefore, the TSP and PM_2.5 concentrations and dry deposition must be reduced in central Taiwan on smog days. In addition, atmospheric TSP and PM_2.5 concentrations at various sampling sites were compared, and those herein were not higher than those measured in other countries. Finally, apart from the local traffic emissions, during smog periods, the other pollution source originated from the transportation process of traffic pollutants emitted in the northwest side of Taiwan.     

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.     

Human Exposure to Sulfates from Coal-Fired Power Plants

Abstract

Increased interest in the health effects of ambient par–ticulate mass (PM) has focused attention on the evaluation of existing mass measurement methodologies and the definition of PM in ambient air. The Rupprecht and Patashnick Tapered Element Oscillating MicroBalance (TEOM^®) method for PM is compared with time–integrated gravimetric (manual) PM methods in large urban areas during different seasons. Comparisons are conducted for both PM₁₀ and PM_2.5 concentrations.

In urban areas, a substantial fraction of ambient PM can be semi–volatile material. A larger fraction of this component of PM₁₀ may be lost from the TEOM–heated filter than the Federal Reference Method (FRM). The observed relationship between TEOM and FRM methods varied widely among sites and seasons. In East Coast urban areas during the summer, the methods were highly correlated with good agreement. In the winter, correlation was somewhat lower, with TEOM PM concentrations generally lower than the FRM. Rubidoux, CA, and two Mexican sites (Tlalnepantla and Merced) had the highest levels of PM₁₀ and the largest difference between TEOM and manual methods.

PM_2.5 data from collocation of 24–hour manual samples with the TEOM are also presented. As most of the semi–volatile PM is in the fine fraction, differences between these methods are larger for PM_2.5 than for PM₁₀.