Aerodynamic Equivalent Diameter Research Articles

Chemical Composition of Fine Particulate Matter from Peat Forest Fires at Palangka Raya and Its Dispersion using HYSPLIT

An air quality monitoring was conducted to investigate the chemical characteristics of particulate emissions in peat forest fires at Palangka Raya, Indonesia during 2012 where a peat forest fire episode occurred. Aerosol samples were collected at Palangka Raya where represents a sub urban site downwind of the peat forest fires. The samples were collected using Gent stacked filter unit sampler. The sampler provides two size fractions: coarse (2.5-10 μm equivalent aerodynamic diameters EAD) and fine (<2.5 μm EAD). Black carbon (BC) was measured using Smoke Stain Reflectometer, and elemental compositions were analyzed using X-ray Fluorescence (XRF). The concentrations of PM2.5 during a haze episode were significantly different about seven to eight times higher when compared to the concentrations in non-haze conditions. The major components of PM2.5 in peat smoke haze consist of sulphur, biomass burning component (BC, K), and crustal components (Al, Fe, Si). The sulphur mainly comes from the peat as it is the earliest stage of transition from compressed plant growth to the formation of coal. The dispersion pattern to show the effect of wind direction using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) simulation was also applied.

Airborne particulate matter emissions from vehicle brakes in micro- and nano-scales: Morphology and chemistry by electron microscopy

Brake wear particles constitute a significant part of the non-exhaust related particulate matter (PM) associated to traffic. These particles derive from various components of the vehicles’ brake system and were recognized as an important pollution source only recently. In the present study, electron microscopy was applied to elucidate brake wear particle morphology and associated chemical composition. Sampling was carried out on a brake test bench. Particles were collected on 13 successive polycarbonate foil bags and a backup filter by means of a Dekati Low Pressure Impactor (DLPI), based on the equivalent aerodynamic particle diameter. The results revealed a broad size range from the micro-to the nano-scale, as measured on electron microscope images, including coarse (2.5–10 μm), fine (0.1–2.5 μm) and ultrafine ones (<0.1 μm), down to a few nanometers. It cannot be implied with certainty to what extent the particle size spectrum identified under the experimental conditions of the present study strictly applies to real-world conditions. The particles occur typically in form of aggregates, also in the ultrafine scale; single, i.e. non-agglomerated particles are more common in the ultrafine fraction than at larger sizes. Imaged particles have commonly rounded outlines probably due to friction and associated abrasion during braking; melting/evaporation at high temperature braking phases, associated with the rate of the generated frictional energy of braking, and subsequent rapid solidification can be invoked to interpret the nearly spherical shape of nanometer size particles. The individual constituents of the aggregates have various sizes and chemical composition. Energy dispersive X-ray analysis of the imaged aggregates and of their constituents showed that Fe is prevalent in all size fractions but is less pronounced in the smaller sizes, where Ca, occasionally in combination with S and/or P becomes more frequent. Other frequently analysed elements are Al, Sn, Mg, Si, Cr, Ti, K and W; less frequent are Ni, Zn, Zr, Ba, S, C, P, F, Mn and rarely Bi and Sb.

Evidence for regional heterogeneous atmospheric particulate matter distribution in China: implications for air pollution control

China has suffered from severe nationwide air quality degradation for decades. PM2.5, the atmospheric particulate matter with an aerodynamic equivalent diameter of less than 2.5 μm, is the most concerning atmospheric pollutant for heath. Pollution control policies are commonly applied nationwide, but atmospheric pollution may vary from one area to another, thus suggesting the need for different, adapted policies. However, there is little knowledge on pollution distribution in China. Therefore, here we used recurrent neural network and random forest models to analyze the wintertime regional PM2.5 patterns in four most polluted cities of China, which are Beijing, Shanghai, Guangzhou and Chengdu, from December 2014 to February 2019. We find that different megacities in China have completely different PM2.5 patterns, which remained unchanged during the past 6 years. CO plays a predominant role in shaping PM2.5 nationwide, and the importance of CO varies from region to region. Therefore, different regional PM2.5 control policies should be carried out for better regulation. Furthermore, we demonstrate that PM2.5 is not strongly linked with time series, inferring that PM2.5 concentrations at a given date are not linked with previous PM2.5 concentrations. This finding suggests that the chemical reaction equilibrium may get reversed and that the rate of chemical reactions of PM2.5 is faster than we normally think.

The impact of meteorological changes from 2013 to 2017 on PM2.5 mass reduction in key regions in China

In 2013, China issued the “Action Plan for the Prevention and Control of Air Pollution” (“Ten Statements of Atmosphere”) and implemented a series of pollution reduction measures from 2013 to 2017. In key regions of China, the mass concentrations of particulate matter with aerodynamic equivalent diameters less than 2.5 μm (PM2.5) have dropped significantly. However, the contributions of meteorological changes to PM2.5 reduction are largely uncertain, which has attracted particular concern from the government and the public. Here, we investigated the impact of large-scale and boundary layer (BL) meteorological conditions on aerosol pollution and estimated the contributions of meteorological changes to PM2.5 reduction based on in-depth analysis and diagnosis of various observed meteorological elements and an integrated pollution-linked meteorological index (PLAM, which is approximately and linearly related to PM mass concentration). In this study, we found that the meteorological conditions worsened in 2014 and 2015 and improved in 2016 and 2017 relative to those in 2013 in key regions in China. In 2017 relative to 2013, only ~5% (approximately 13% of the total PM2.5 decline) of the 39.6% reduction in PM2.5 mass concentrations can be attributed to meteorological changes in the Beijing-Tianjin-Hebei (BTH) region, and only ~7% (approximately 20% of the total PM2.5 decline) of the 34.3% reduction can be attributable to meteorological changes in the Yangtze River Delta (YRD) region. Overall, the PM2.5 reduction due to meteorological improvement is much lower than the observed PM2.5 reduction in these areas, which indicates that emission reduction during the five-year implementation of the “Ten Statements of Atmosphere” is the dominant factor in the improvement in air quality. The changes in meteorology and climate are conducive to PM2.5 reduction but do not dominate the substantial improvement in air quality. Similar to the above regions, in the Pearl River Delta (PRD) region, the impact of meteorological changes on the annual averaged PM2.5 concentration from 2013 to 2017 was relatively weak, and the PM2.5 reduction was mainly due to emission reductions. During winter 2017 (January, February, and December of this year), the meteorological conditions improved ~20% in the BTH region (observed total PM2.5 reduction: 40.2%) and ~30% in the YRD region (observed total PM2.5 reduction: 38.2%) relative to those in 2013, showing the meteorological factors played more important role in the decrease of PM2.5 in winter of these years in the two regions, respectively. The meteorological conditions in winter 2016 were 14% better than those in winter 2017, but the PM2.5 reduction in winter 2016 was still less than that in winter 2017, reinforcing the significant contributions of the increasing efforts to reduce PM2.5 emissions in 2017. The substantial progress of strict emission measures was also confirmed by a comparison of several persistent heavy aerosol pollution episodes (HPEs) with similar meteorological conditions. It is found that the decrease of PM2.5 mass caused by emission reduction increases year by year, especially the decrease of PM2.5 concentration in 2016 and 2017. In China, HPEs mainly occur in winter, when meteorological conditions are approximately 40--100% worse than in other seasons. This worsening is partly due to the harbor effect of high topography, including downdrafts and the weak wind zone, and partly due to the increasingly stable regional BL structure caused by climate warming. For the formation of HPEs, it occurred under regional stagnant and stable conditions associated with upper-level circulation patterns, including the zonal westerly winds type and high-pressure ridges. After pollution formation, PM2.5 with mass accumulated to a certain degree can further worsen the BL meteorological conditions. The feedback effect associated with worsening conditions dominates PM2.5 mass explosive growth. In the context of high air pollutant emissions in China, unfavorable meteorological conditions are the necessary external conditions for the formation and accumulation of HPEs. Therefore, reducing aerosol pollution significantly during the earlier transport stage is critical in reducing persistent HPEs. Currently, even under favorable meteorological conditions, allowing emissions without restriction is also not advisable because aerosol pollution allowed to accumulate to a certain extent will significantly worsen the BL meteorological conditions and close the “meteorological channels” available for pollution dispersion.

Experiments on filtering nano-aerosols from vehicular and atmospheric pollutants under dominant diffusion using nanofiber filter

Nano-aerosols of size 100 nm and below are manifested everywhere in various urban micro-environments. In outdoor, the vehicular emission during traffic jam can release nano-aerosols with concentration above 200 million/m3 (200/cm3). Superimposed on vehicular emission are smog particles, around 10–50 nm, generated from the photochemical reaction of hydrocarbon and NOx in the presence of sunlight. These nano-aerosols, by virtue of their small sizes, can be inhaled readily into our bodies leading possibly to various chronic diseases. Air-borne viruses from influenza to epidemic viruses, which can lead to acute sickness and even death, are also in the same size range of 100 nm.Despite microfibers are being commonly used today in filters, there has been limited studies on filtration of real aerosols using microfiber filters, let alone nanofibrous filters, as most studies used simulated aerosols (e.g. sodium chloride) or test dust. Also, in standard sodium chloride test, only monodispersed aerosol size is allowed to challenge the filter. On the other hand, in reality aerosols of all sizes challenge simultaneously the filter. In this study, for the first time we have used nanofiber filter in a portable test filter set-up to filter polydispersed aerosols from the micro-environment near busy traffic area where aerosols comprise of both vehicular and atmospheric pollutants with size range between 10 and 400 nm. Real-time measurements are carried out with the portable test filter. The test results are compared to the theoretical correlation from Payet with diffusion correction at small Peclet number (Pe). We have found good comparison between test results with theoretical correlations using equivalent aerodynamic diameter for the aerosols with face velocity from 1 to 11 cm/s. A new dimensionless parameter, specific filter resistance (also established independently by Buckingham-π approach), is defined for the first time. It measures the flow drag on fibers to the amount of fibers present in the filter, the lower is the specific filter resistance the better is the filter. For our test condition, it is approximately 1.0–1.2. We have also improved the filtration efficiency of the filter by increasing the fiber basis weight by stacking up two layers of nanofibers. We have demonstrated that the efficiency increases while both the quality factor and specific filter resistance remain constant. We have also investigated the single fiber efficiency due to diffusion and found that at low velocity and low Peclet number (Pe < 10), the test results agree well with the theoretical prediction. On the other hand, at higher face velocity (>0.07 m/s) and large Peclet number (>10), there is small deviation from the theory, which is probably due to the smaller aerosols collecting by the larger aerosols upstream of the filter with an airstream consisting of polydispersed aerosol distribution challenging the filter. This has not been realized previously as tests conducted were mostly using monodispersed aerosol size distribution for which aerosol-aerosol interaction was absent.

Dry Deposition of Particulate Matter and Ions in Forest at Different Heights

Dry deposition of particulate matter (PM) indicates the capacity of atmosphere self-depuration. To investigate seasonal dry deposition of PM in an urban forest, the concentration and ionic composition of PM2.5 (particulate matter with aerodynamic equivalent diameters less than 2.5 μm) and the deposition of PM and ions in PM at different layer were measured at three canopy heights in the Beijing Olympic Forest Park. Results showed that diurnal trends in PM concentration varied with height and that concentrations tended to be highest in the understory. During winter, when the absorption ability of plants, which withered, was reduced, and anthropogenic emissions, primarily from coal combustion, ion concentrations tended to be highest in the forest canopy. The anions SO42−, NO3−, and Cl− were the dominant ionic species, accounting for 82% of the total mass of water-soluble ions in PM2.5. Results showed a lower mass ratio of NO3−/SO42− (mean = 0.29, SD = 0.24), relative to previous studies, implying that vehicle emissions may have reduced in Beijing. The chemical forms of sulfate and nitrate were likely NH4NO3 and (NH4)2SO4; however, Ca(NO3)2 was the only chemical form detected based on the correlation coefficient between Ca2+ and NO3−. Concentrations of PM were negatively related to temperature and wind speed, and positively related to relative humidity. Within the forest canopy, the deposition velocity was low (high) during summer (winter). Furthermore, ion deposition fluxes were higher in the forest understory (1.5–6 m) during summer and in the canopy (6–10 m) during winter. This was attributed to seasonal trends in PM concentration.

Deposition of water-soluble inorganic ions in PM2.5 in a typical forestry system in Beijing, China

BackgroundRapid economic development in China has resulted in an increase in severe air pollution in city groups such as the Beijing–Tianjin–Hebei Metropolitan Region. PM2.5 (fine particles with an aerodynamic equivalent diameter of 2.5 μm or less) is one of the most important pollutants. The deposition process is an important way of removing particles from the air. To evaluate the effect of an urban forest on atmospheric particle removal, a concentration gradient method was used to measure the deposition velocities of water-soluble inorganics in PM2.5 in two national forest parks in Beijing, China. The following eight water-soluble inorganic ions in PM2.5 were investigated: sodium, ammonium, potassium, magnesium, calcium, chloride, nitrate, and sulfate.MethodsSamples were taken from two sites in Beijing from the 7th to the 15th May, 2013. The concentrations of water-soluble inorganic ions were analyzed with ion chromatography. We used the concentration gradient technique to estimate the deposition flux and velocity. To determine the relationships between leaf traits and particle accumulation, typical leaf samples from each selected species were studied using scanning electron microscopy.ResultsThe total deposition flux and total deposition velocity during the daytime were higher than those at night. Sulfate showed the biggest deposition flux and velocity at both study sites, whereas the other ions showed different trends at each site. Result from higher proportion of coniferous to broadleaved trees, the total deposition flux of the eight ions measured in Jiufeng National Forest Park was greater than that in Olympic Forest Park.ConclusionsThe deposition velocity was affected by meteorological conditions such as wind speed, temperature, and humidity. The deposition velocity was also influenced by tree species. The surface of plants is an important factor influencing particle deposition. The results of this study may help in assessing the effects of forestry systems on particle removal and provide evidence for urban air pollution control and afforestation of urban areas.

Measurements of Atmospheric Proteinaceous Aerosol in the Arctic Using a Selective UHPLC/ESI-MS/MS Strategy

In this article, an analytical methodology to investigate the proteinaceous content in atmospheric size-resolved aerosols collected at the Zeppelin observatory (79 °N, 12 °E) at Ny Ålesund, Svalbard, from September to December 2015, is proposed. Quantitative determination was performed after acidic hydrolysis using ultrahigh-performance liquid chromatography in reversed-phase mode coupled to electrospray ionization tandem mass spectrometry. Chromatographic separation, as well as specificity in the identification, was achieved by derivatization of the amino acids with N-butyl nicotinic acid N-hydroxysuccinimide ester prior to the analysis. The chromatographic run was performed within 11 min and instrumental levels of detection (LODs) were between 0.2 and 8.1 pg injected on the column, except for arginine which exhibited an LOD of 37 pg. Corresponding method LODs were between 0.01 and 1.9 fmol/m3, based on the average air sampling volume of 57 m3. The sum of free amino acids and hydrolyzed polyamino acids was shown to vary within 6–2914 and 0.02–1417 pmol/m3 for particles in sizes < 2 and 2–10 μm in equivalent aerodynamic diameter, respectively. Leucine, alanine, and valine were the most abundant among the amino acids in both aerosol size fractions. In an attempt to elucidate source areas of the collected aerosols, 5- to 10-day 3D backward trajectories reaching the sampling station were calculated. Overall, the method described here provides a first time estimate of the proteinaceous content, that is, the sum of free and polyamino acids, in size-resolved aerosols collected in the Arctic.Graphical ᅟ

Inhalation exposure and potential health risk estimation of lanthanides elements in PM2.5 associated with rare earth mining areas: a case of Baotou city, northern China.

Particulate pollution, especially PM2.5 (particles with an aerodynamic equivalent diameter of 2.5μm or less), has received increased attention in China recently. In this study, PM2.5 samples were collected in August 2013 and April 2014 from different regions of Baotou, the largest rare earth elements (REEs) processing city in northern China. The concentrations and distribution patterns of REEs in PM2.5 were analyzed, and the inhalation exposure to REEs associated with PM2.5 was assessed. The results showed that the REEs levels were 56.9 and 15.3ngm-3 in August 2013 and April 2014, respectively. These values are much higher than those in non-REEs mining areas. The distribution patterns of REEs exhibited LREE enrichment. The Eu and Ce anomalies displayed slightly positive and negative values, respectively, which were in accordance with the background soil and ore. The average daily intake amounts of REEs for population through inhalation exposure of PM2.5 in Baotou were in the range of 5.09 × 10-7 to 2.25 × 10-5 mgkg-1 day-1.

Novel Hollow Fiber Air Filters for the Removal of Ultrafine Particles in PM2.5 with Repetitive Usage Capability.

Severe air pollution has become a global concern, and there is a pressing need to develop effective and efficient air filters for removing airborne particulate matters (PMs). In this work, a highly permeable poly(ether sulfone) (PES) based hollow fiber membrane was developed via a one-step dry-jet wet spinning. For the first time, a hollow fiber membrane was used in removing the ultrafine particles (PMs with aerodynamic equivalent diameters of less than 100 nm) in PM2.5. The novel air filter was designed to possess the synergistic advantages of porous filters and fibrous filters with a sievelike outer surface and a fibrouslike porous substrate. A filtration efficiency of higher than 99.995% could be easily achieved when the self-support hollow fiber was challenged with less than 300 nm particulates. Without losses of the structural advantages, we have demonstrated that the permeation properties of the hollow fiber membrane can be facilely tailored via manipulation of the dope and bore fluid formulations. Various cleaning strategies were explored to regenerate the membrane performance after fouling. Both water rinse and backwash showed effectiveness to restore the membrane permeance for repetitive usage.

Insights Into the Morphology of the East Asia PM2.5 Annual Cycle Provided by Machine Learning.

The abundance of airborne particulate matter with an aerodynamic equivalent diameter of 2.5 µm or less (PM2.5) is a significant environmental and health issue. Many tools have been used to examine the relationship between PM2.5 abundance and meteorological variables, but some of the relationships are nonlinear, non-Gaussian, and even unknown. Machine learning provides a broad range of practical algorithms to help examine this issue. In this study, we use machine learning to classify the morphology of PM2.5 seasonal cycles in East Asia. Machine learning is able to objectively classify the seasonal cycles and, without a priori assumption, is able to clearly distinguish between urban and rural areas. We show an example of this in the Sichuan Basin of China. Furthermore, machine learning is also able to provide physical insights by identifying the key factors associated with each distinct shape of the seasonal cycle, such as highlighting the key role played by the topography and the built environment.

A comparative study on physicochemical characteristics of household dust from a metropolitan city and a remote village in China

The physicochemical characteristics of household dust in a typical metropolitan city (i.e., Beijing, the urban region) and a remote village in western of China (the rural region) were investigated and compared. The results show that the particles of household dust in both the regions could be classified as six types: micro-aggregates, biogenic, spherical, subrounded, subangular, and angular in morphology. Most dust particles were found to belong to the latter three types and belonged to mineral particles. The average particle size (aerodynamic equivalent diameter) of household dust was 16.1 and 14.9 μm in the rural and urban regions, respectively. Dust particles with diameters 10–20 μm were the highest by number in the both regions, while dust diameters from 30 to 40 μm and from 20 to 30 μm were the highest by volume in the urban and rural regions, respectively. The minerals in household dust particles in both the rural and urban regions were primarily quartz, albite, calcite, and dolomite. The average percentages of macro-element species (Si, Al, Ca, Fe, K, Mg, Na, P, and Ti) in household dust in the rural and urban regions were lower than those in the corresponding outdoor dust and their background values, except for Ca. Silicon, Al, Ca, Fe, and K were the predominant elements distributed in household dust in both the rural and urban regions. The concentrations of the studied macro-elements in the rural household dust were lower than those in the urban household dust, being in agreement with the relationship of the reference crust element content in the rural and urban regions. The average percentages of the ions in the rural and urban household dust were generally higher than those in the corresponding outdoor dust. The levels of SO42−, NO3−, Cl−, and Ca2+ in the urban household dust were higher than those in the rural, owing to human activities. The deposition rate of household dust in the rural region (i.e., 15.3 ± 2.6 g m−2 year−1) was approximately 10 times greater than that observed in the urban region due to worse tightness of the houses. Dust at homes was one of the significant sources of PM10 in the residential environment through resuspension, and the studied properties of household dust are closely related to human health. Household dust in both the rural and urban regions of China should not be ignored.

Urban increments of gaseous and aerosol pollutants and their sources using mobile aerosol mass spectrometry measurements

Abstract. Air pollution is one of the main environmental concerns in urban areas, where anthropogenic emissions strongly affect air quality. This work presents the first spatially resolved detailed characterization of PM2.5 (particulate matter with aerodynamic equivalent diameter daero ≤ 2.5 µm) in two major Estonian cities, Tallinn and Tartu. The measurements were performed in March 2014 using a mobile platform. In both cities, the non-refractory (NR)-PM2.5 was characterized by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) using a recently developed lens which increases the transmission of super-micron particles. Equivalent black carbon (eBC) and several trace gases including carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) were also measured. The chemical composition of PM2.5 was found to be very similar in the two cities. Organic aerosol (OA) constituted the largest fraction, explaining on average about 52 to 60 % of the PM2.5 mass. Four sources of OA were identified using positive matrix factorization (PMF): hydrocarbon-like OA (HOA, from traffic emissions), biomass burning OA (BBOA, from biomass combustion), residential influenced OA (RIOA, probably mostly from cooking processes with possible contributions from waste and coal burning), and oxygenated OA (OOA, related to secondary aerosol formation). OOA was the major OA source during nighttime, explaining on average half of the OA mass, while during daytime mobile measurements the OA was affected by point sources and dominated by the primary fraction. A strong increase in the secondary organic and inorganic components was observed during periods with transport of air masses from northern Germany, while the primary local emissions accumulated during periods with temperature inversions. Mobile measurements offered the identification of different source regions within the urban areas and the assessment of the extent to which pollutants concentrations exceeded regional background levels (urban increments). HOA, eBC, CO2, and CO showed stronger enhancements on busy roads during the morning and evening traffic rush hours; BBOA had its maximum enhancement in the residential areas during the evening hours and RIOA was enhanced in both the city center (emissions from restaurants) and in the residential areas (emissions from residential cooking). In contrast, secondary components (OOA, sulfate (SO4), nitrate (NO3), ammonium (NH4), and chloride (Cl)) had very homogeneous distributions in time and space. We were able to determine a total PM2.5 urban increment in Tartu of 6.0 µg m−3 over a regional background concentration of 4.0 µg m−3 (i.e., a factor of 2.5 increase). Traffic exhaust emissions were identified as the most important source of this increase, with eBC and HOA explaining on average 53.3 and 20.5 % of the total increment, respectively.

PM2.5 source apportionment in a French urban coastal site under steelworks emission influences using constrained non-negative matrix factorization receptor model

The constrained weighted-non-negative matrix factorization (CW-NMF) hybrid receptor model was applied to study the influence of steelmaking activities on PM2.5 (particulate matter with equivalent aerodynamic diameter less than 2.5μm) composition in Dunkerque, Northern France. Semi-diurnal PM2.5 samples were collected using a high volume sampler in winter 2010 and spring 2011 and were analyzed for trace metals, water-soluble ions, and total carbon using inductively coupled plasma – atomic emission spectrometry (ICP-AES), ICP - mass spectrometry (ICP-MS), ionic chromatography and micro elemental carbon analyzer. The elemental composition shows that NO3−, SO42−, NH4+ and total carbon are the main PM2.5 constituents. Trace metals data were interpreted using concentration roses and both influences of integrated steelworks and electric steel plant were evidenced. The distinction between the two sources is made possible by the use Zn/Fe and Zn/Mn diagnostic ratios. Moreover Rb/Cr, Pb/Cr and Cu/Cd combination ratio are proposed to distinguish the ISW-sintering stack from the ISW-fugitive emissions. The a priori knowledge on the influencing source was introduced in the CW-NMF to guide the calculation. Eleven source profiles with various contributions were identified: 8 are characteristics of coastal urban background site profiles and 3 are related to the steelmaking activities. Between them, secondary nitrates, secondary sulfates and combustion profiles give the highest contributions and account for 93% of the PM2.5 concentration. The steelwork facilities contribute in about 2% of the total PM2.5 concentration and appear to be the main source of Cr, Cu, Fe, Mn, Zn.

RELATIONSHIP BETWEEN AEROSOL OPTICAL DEPTH AND PARTICULATE MATTER OVER SINGAPORE: EFFECTS OF AEROSOL VERTICAL DISTRIBUTIONS.

As part of the Seven Southeast Asian Studies (7SEAS) program, an Aerosol Robotic Network (AERONET) sun photometer and a Micro-Pulse Lidar Network (MPLNET) instrument have been deployed at Singapore to study the regional aerosol environment of the Maritime Continent (MC). In addition, the Navy Aerosol Analysis and Prediction System (NAAPS) is used to model aerosol transport over the region. From 24 September 2009 to 31 March 2011, the relationships between ground-, satellite- and model-based aerosol optical depth (AOD) and particulate matter with aerodynamic equivalent diameters less than 2.5 μm (PM2.5) for air quality applications are investigated. When MPLNET-derived aerosol scale heights are applied to normalize AOD for comparison with surface PM2.5 data, the empirical relationships are shown to improve with an increased 11 %, 10 % and 5 % in explained variances, for AERONET, MODIS and NAAPS respectively. The ratios of root mean square errors to standard deviations for the relationships also show corresponding improvements of 8 %, 6 % and 2 %. Aerosol scale heights are observed to be bimodal with a mode below and another above the strongly-capped/deep near-surface layer (SCD; 0 - 1.35 km). Aerosol extinctions within SCD are well-correlated with surface PM2.5 concentrations, possibly due to strong vertical mixing in the region.

Mote Trash System Particulate Emission Factors for Cotton Gins: Particle Size Distribution Characteristics

This report is part of a project to characterize cotton gin emissions from the standpoint of total particulate stack sampling and particle size analyses. In 2006 and again in 2013, the United States (U.S.) Environmental Protection Agency (EPA) published a more stringent National Ambient Air Quality Standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent need to collect additional cotton gin emissions data to address current regulatory issues, because EPA AP-42 cotton gin PM2.5 emission factors were limited. In addition, current EPA AP-42 emission factor quality ratings for cotton gin PM10 (particulate matter with nominal diameter less than or equal to 10 µm) data are questionable, being extremely low. The objective of this study was to characterize particulate emissions for mote trash systems from cotton gins across the cotton belt based on particle size distribution analysis of total particulate samples from EPA-approved stack sampling methods. Average measured of PM2.5, PM6, and PM10 emission factors based on the mass and particle size analyses of EPA Method 17 total particulate filter and wash samples from two gins (6 total test runs) were 0.00031 kg/227-kg bale (0.00068 lb/500-lb bale), 0.0023 kg/bale (0.0051 lb/bale), and 0.0042 kg/bale (0.0093 lb/bale), respectively. The mote trash system particle size distributions were characterized by an average mass median diameter of 23.9 µm (aerodynamic equivalent diameter). Based on system average emission factors, the ratio of PM2.5 to total particulate was 1.75%, PM6 to total particulate was 13.3%, and PM10 to total particulate was 24.2%.

First Stage Mote System Particulate Emission Factors for Cotton Gins: Particle Size Distribution Characteristics

This report is part of a project to characterize cotton gin emissions from the standpoint of total particulate stack sampling and particle size analyses. In 2006 and again in 2013, the United States (U.S.) Environmental Protection Agency (EPA) published a more stringent National Ambient Air Quality Standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent need to collect additional cotton gin emissions data to address current regulatory issues, because EPA AP-42 cotton gin PM2.5 emission factors were limited. In addition, current EPA AP-42 included combined mote cleaner PM10 (particulate matter with nominal diameter less than or equal to 10 µm) and total particulate emission factors and not individual mote system emission factors. The objective of this study was to characterize particulate emissions for 1st stage mote systems from cotton gins across the cotton belt based on particle size distribution analysis of total particulate samples from EPA-approved stack sampling methods. Average measured PM2.5, PM6, and PM10 emission factors based on the mass and particle size analyses of EPA Method 17 total particulate filter and wash samples from five gins (14 total test runs) were 0.00063 kg/227-kg bale (0.0014 lb/500-lb bale), 0.0054 kg/bale (0.012 lb/bale), and 0.0091 kg/bale (0.020 lb/bale), respectively. The 1st stage mote system particle size distributions were characterized by an average mass median diameter of 16.4 µm (aerodynamic equivalent diameter). Based on system average emission factors, the ratio of PM2.5 to total particulate was 2.49%, PM6 to total was 21.6%, and PM10 to total was 36.0%.

Battery Condenser System Particulate Emission Factors for Cotton Gins: Particle Size Distribution Characteristics

This report is part of a project to characterize cotton gin emissions from the standpoint of total particulate stack sampling and particle size analyses. In 2006 and again in 2013, the United States (U.S.) Environmental Protection Agency (EPA) published a more stringent National Ambient Air Quality Standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent need to collect additional cotton gin emissions data to address current regulatory issues, because EPA AP-42 cotton gin PM2.5 emission factors were limited. In addition, current EPA AP-42 emission factor quality ratings for cotton gin PM10 (particulate matter with nominal diameter less than or equal to 10 µm) data are questionable, being extremely low. The objective of this study was to characterize particulate emissions for battery condenser systems from cotton gins across the cotton belt based on particle size distribution analysis of total particulate samples from EPA-approved stack sampling methods. Average measured PM2.5, PM6, and PM10 emission factors based on the mass and particle size analyses of EPA Method 17 total particulate filter and wash samples from six gins (17 total test runs) were 0.00036 kg/227-kg bale (0.00078 lb/500-lb bale), 0.0042 kg/bale (0.0093 lb/bale), and 0.0078 kg/bale (0.017 lb/bale), respectively. The battery condenser system particle size distributions were characterized by an average mass median diameter of 24.5 µm (aerodynamic equivalent diameter). Based on system average emission factors, the ratio of PM2.5 to total particulate was 1.11%, PM6 to total particulate was 13.2%, and PM10 to total particulate was 24.3%.

Third Stage Seed-Cotton Cleaning System Particulate Emission Factors for Cotton Gins: Particle Size Distribution Characteristics

This report is part of a project to characterize cotton gin emissions from the standpoint of total particulate stack sampling and particle size analyses. In 2006 and again in 2013, the United States (U.S.) Environmental Protection Agency (EPA) published a more stringent National Ambient Air Quality Standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent need to collect additional cotton gin emissions data to address current regulatory issues, because EPA AP-42 cotton gin PM2.5 emission factors were limited. In addition, current EPA AP-42 emission factor quality ratings for cotton gin PM10 (particulate matter with nominal diameter less than or equal to 10 µm) data are questionable, being extremely low. The objective of this study was to characterize particulate emissions for 3rd stage seed-cotton cleaning systems from cotton gins across the cotton belt based on particle size distribution analysis of total particulate samples from EPA-approved stack sampling methods. Average measured PM2.5, PM6, and PM10 emission factors based on the mass and particle size analyses of EPA Method 17 total particulate filter and wash samples from two gins (5 total test runs) were 0.00090 kg/227-kg bale (0.0020 lb/500-lb bale), 0.0075 kg/bale (0.017 lb/bale), and 0.012 kg/bale (0.027 lb/bale), respectively. The 3rd stage seed-cotton cleaning system particle size distributions were characterized by an average mass median diameter of 9.6 µm (aerodynamic equivalent diameter). Based on system average emission factors, the ratio of PM2.5 to total particulate was 3.84%, PM6 to total particulate was 32.2%, and PM10 to total particulate was 51.5%.

Second Stage Seed-Cotton Cleaning System Particulate Emission Factors for Cotton Gins: Particle Size Distribution Characteristics

This report is part of a project to characterize cotton gin emissions from the standpoint of total particulate stack sampling and particle size analyses. In 2006 and again in 2013, the United States (U.S.) Environmental Protection Agency (EPA) published a more stringent National Ambient Air Quality Standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent need to collect additional cotton gin emissions data to address current regulatory issues, because EPA AP-42 cotton gin PM2.5 emission factors were limited. In addition, current EPA AP-42 emission factor quality ratings for cotton gin PM10 (particulate matter with nominal diameter less than or equal to 10 µm) data are questionable, being extremely low. The objective of this study was to characterize particulate emissions for 2nd stage seed-cotton cleaning systems from cotton gins across the cotton belt based on particle size distribution analysis of total particulate samples from EPA-approved stack sampling methods. Average measured PM2.5, PM6, and PM10 emission factors based on the mass and particle size analyses of EPA Method 17 total particulate filter and wash samples from five gins (14 total test runs) were 0.0014 kg/227-kg bale (0.0031 lb/500-lb bale), 0.015 kg/bale (0.032 lb/bale), and 0.025 kg/bale (0.056 lb/bale), respectively. The 2nd stage seed-cotton cleaning system particle size distributions were characterized by an average mass median diameter of 12.2 µm (aerodynamic equivalent diameter). Based on system average emission factors, the ratio of PM2.5 to total particulate was 2.42%, PM6 to total particulate was 25.1%, and PM10 to total particulate was 43.2%.