Estimation of wind blown dust emissions in Europe and its vicinity

The assessment of the wind blown dust emission for Europe and selected regions of North Africa and Southwest Asia was carried out using a mesoscale model. The mesoscale model was parameterized based on the current literature review. The model provides data on PM₁₀ emission from several dust reservoirs (anthropogenic, agriculture, semi- and natural) with spatial resolution of 10 × 10 km and temporal resolution of 1 h. The spatial variability of PM₁₀ emission depends on soil texture, land cover/land use as well as meteorological conditions. Lands covered with water or permanently wet were excluded from the model. The land covered with vegetation is treated as dust reservoir whose dust emission capacity depends on the type of vegetation and cover. The dust reservoirs are divided into reservoirs with stable and unstable surface. The changes of emission in time depend on meteorological parameters.The wind blown dust emission should be treated as a non-continuous spatio-temporal process. The emissions are estimated with high uncertainty. The estimated PM₁₀ yearly total load emitted by wind from the European territory is highly differentiated in space and time and is equal to 0.74 Tg. The total load of PM₁₀ emitted by wind from North African and Southwest Asian land surface located in the vicinity of European boundaries is assessed as nearly 50% (0.43 Tg) of the total load estimated for the whole Europe.The average yearly PM₁₀ emission factor for Europe was estimated at 0.139 Mg km^?2.The PM₁₀ emission from agricultural areas is estimated at 52% of the total wind blown emission from the domain of the European Union project “Improving and applying methods for the calculation of natural and biogenic emissions and assessment of impacts to the air quality” - NatAir.PM₁₀ emission factor for natural areas of Europe is estimated at 0.021 Mg km^?2. Appropriate factors for agricultural areas and anthropogenic areas are 0.157 Mg km^?2 and 0.118 Mg km^?2, respectively. The latter two factors are probably underestimated due to omitting in the model of other dust emission mechanisms than aeolian erosion.     

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.     

Transport of dusts from East Asian and non-East Asian sources to Hong Kong during dust storm related events 1996–2007

Over a twelve year period from 1996 to 2007, 76 dust storm related events (as days) in Hong Kong were selected for study, based on Aluminium and Calcium concentrations in PM₁₀. Four of the 76 events reach episodic levels with exceedances of the Hong Kong air quality standards. The purpose of the study is to identify and characterize dust sources impacting Hong Kong.Global distribution of aerosols in NASA’s daily aerosol index images from TOMS and OMI, are compared to plots generated by NRL(US)’s Navy Aerosol Analysis and Prediction System. Possible source areas are assigned by computing air parcel backward trajectories to Hong Kong using the NOAA HYSPLIT model. PM₁₀ and elemental data are analyzed for crustal mass concentrations and element mass ratios.Our analysis reveals that 73 out of the 76 dust events (96%) involve non-East Asian sources-the Thar, Central/West Asian, Arabian and Sahara deserts (Saharan influence is found in 63 events), which are previously not known to affect Hong Kong. The Gobi desert is the most frequent origin of dust, affecting 68 dust events while the Taklamakan desert impacts only 30 of the dust events. The impact of the Gobi desert in March and December is apparently associated with the northeast monsoon in East Asia.Our results also show a seasonal pattern in dust impact from both East Asian and more remote sources, with a maximum in March. Dust event occurrences are conspicuously absent from summer. Dust transport to Hong Kong is commonly associated with the passage of frontal low-pressure systems.The coarse size fraction of PM₁₀ concentrations were, as indicated by Al, Ca and Fe concentrations, about 4–8 times higher during dust events. The mean Ca/Al ratios of sources involving the Taklamakan desert are notably higher than those for non-East Asian sources owing to a higher Ca content of most of the East Asian deserts. The Fe/Al ratios follow a similar trend.Contributions from the desert sources are grossly estimated where possible, by using the average Al abundance of 8% in the upper continental crust to convert the Al mass in the PM₁₀ to dust concentrations. This is done for the six events identified with air mass purely of non-East Asian origin and the two events related only to the Thar/Arabian/Sahara deserts. Results reveal that the average contribution from the non-East Asian sources (including C/W Asia) is approximately 10% and, that from the Thar/Arabian/Sahara deserts is about 8%.     

Assessment of source apportionment by Positive Matrix Factorization analysis on fine and coarse urban aerosol size fractions

This study was conducted in order to investigate the differences observed in source profiles in the urban environment, when chemical composition parameters from different aerosol size fractions are subjected to factor analysis. Source apportionment was performed in an urban area where representative types of emission sources are present. PM₁₀ and PM₂ samples were collected within the Athens Metropolitan area and analysed for trace elements, inorganic ions and black carbon. Analysis by two-way and three-way Positive Matrix Factorization was performed, in order to resolve sources from data obtained for the fine and coarse aerosol fractions. A difference was observed: seven factors describe the best solution in PMF3 while six factors in PMF2. Six factors derived from PMF3 analysis correspond to those described by the PMF2 solution for the fine and coarse particles separately. These sources were attributed to road dust, marine aerosol, soil, motor vehicles, biomass burning, and oil combustion. The additional source resolved by PMF3 was attributed to a different type of road dust. Combustion sources (oil combustion and biomass burning) were correctly attributed by PMF3 solely to the fine fraction and the soil source to the coarse fraction. However, a motor vehicle's contribution to the coarse fraction was found only by three-way PMF. When PMF2 was employed in PM₁₀ concentrations the optimum solution included six factors. Four source profiles corresponded to the previously identified as vehicles, road dust, biomass burning and marine aerosol, while two could not be clearly identified. Source apportionment by PMF2 analysis based solely on PM₁₀ aerosol composition data, yielded unclear results, compared to results from PMF2 and PMF3 analyses on fine and coarse aerosol composition data.     

Source apportionment of PM10 in six cities of northern China

Ambient PM₁₀ was sampled in six northern China cities (Urumqi, Yinchuan, Taiyuan, Anyang, Tianjin and Jinan) from December 1999 to July 2002, and analyzed for 16 chemical elements, two water-soluble ions, total carbon, and organic carbon. In addition, chemical source profiles consisting of the same particulate components were obtained from a number of naturally occurring geological sources (soil dust from exposed lands) and sources of atmospheric particulates resulting from human activities (resuspended dust, cement, coal combustion fly ash, vehicle exhaust, and secondary particles). Ambient and source data were used in a chemical mass balance (CMB) receptor model to determine the major source of PM₁₀ in these six cities. Results of CMB modeling showed that the major source of ambient PM₁₀ in all the cities was resuspended dust. Significant contributions from coal fly ash were also found in all six cities.     

Characterization of African Dust (PM2.5) across the Atlantic Ocean during AEROSE 2004

An Aerosol and Oceanographic Science Expedition (AEROSE) on the NOAA Ship Ronald H. Brown collected PM_2.5 particles from a Saharan dust storm in March 2004. High levels of PM_2.5 (120 μg m^?3) were measured during this Saharan storm over the Atlantic Ocean. The particles were characterized for trace element content, with Al and Fe the most abundant metals. These metals were detected in high concentrations during the Saharan event and exhibited good correlations with PM_2.5, suggesting its soil origin. Other elements (Pb, Ni, Cd) did not correlate with Al and Fe, indicating their anthropogenic origin. Enrichment factor calculation conducted on these trace elements support our findings. Trace element analyses performed on particulate matter from a reference site on land in Puerto Rico (Fajardo), demonstrated similar results to those obtained in the AEROSE expedition, where high concentrations of PM_2.5 and Fe were present concomitantly with Saharan events at this station.     

Soil water and particle size distribution influence laboratory-generated PM10

Management of soils to reduce the amount of PM₁₀ emitted during agricultural tillage operations is important for attainment of air quality standards in California's San Joaquin Valley (SJV). The purpose of this study was to improve and expand upon earlier work of predicting tillage-generated dust emissions based on soil properties. We focus on gravimetric soil water content (GWC) and soil texture. A mechanical laboratory dust generator was used to test 23 soils collected for this study. Averaged results showed PM₁₀ concentrations (mg m^?3) increased logarithmically as GWC decreased below soil water potentials of ?1500 kPa. Soils with clay contents less than about 10% by weight began to emit PM₁₀ at GWCs 1.5–4 times their GWC at ?1500 kPa. Soils with clay contents greater than about 10% began to emit PM₁₀ at GWC values closer to ?1500 kPa. We found no correlation between maximum PM₁₀ concentrations, measured at low GWC values, and the %sand, %silt, or %clay in a soil. However, there was a significant correlation between the %silt to %clay ratio and PM₁₀ concentrations. This not only suggests the dependence of dust emission magnitudes on the supply of particles of PM₁₀ size, but also the importance of clay in stabilizing aggregates and maintaining higher amounts of capillary water at lower water potentials. Based on modeled results of pooled data, PM₁₀ concentrations increased linearly (slope = 564) for every unit increase in the %silt to %clay ratio. However, when soils were separated into groups based on clay content, the slopes for PM₁₀ concentrations vs. %silt to %clay ratio were texture dependent. The slope for soils with <10% clay (slope = 727) was 3.3 times greater than for soils with >20% clay (slope = 221). Improved PM₁₀ emission prediction based on soil properties should improve management decisions aimed at reducing tillage-generated PM₁₀.     

Sensitivity analysis of source regions to PM2.5 concentration at Fukue Island,Japan

The authors analyze the sensitivities of source regions in East Asia to PM_2.5 (particulate matter with an aerodynamic diameter of ≤2.5 µm) concentration at Fukue Island located in the western part of Japan by using a regional chemical transport model with emission sensitivity simulations for the year 2010. The temporal variations in PM_2.5 concentration are generally reproduced, but the absolute concentration is underestimated by the model. Chemical composition of PM_2.5 in the model is compared with filter sampling data in spring; simulated sulfate, ammonium, and elemental carbon are consistent with observations, but mass concentration of particulate organic matters is underestimated. The relative contribution from each source region shows the seasonal variation, especially in summer. The contribution from central north China (105°E–124°E, 34°N–42°N) accounts for 50–60% of PM_2.5 at Fukue Island except in summer; it significantly decreases in summer (18%). Central south China (105°E–123°E, 26°N–34°N) has the relative contribution of 15–30%. The contribution from the Korean Peninsula is estimated at about 10% except in summer. The domestic contribution accounts for about 7% in spring and autumn and increases to 19% in summer. We also estimate the relative contribution to daily average concentration in high PM_2.5 days (>35 μg m^?3). Central north China has a significant contribution of 60–70% except in summer. The relative contribution from central south China is estimated at 46% in summer and about 30% in the other seasons. The contributions from central north and south China on high PM_2.5 days are generally larger than those of their seasonal mean contributions. The domestic contribution is smaller than the seasonal mean value in every season; it is less than 10% even in summer. These model results suggest that foreign anthropogenic sources have a substantial impact on attainment of the atmospheric environmental standard of Japan at Fukue Island.

Implications: The contribution from several source regions in East Asia to PM_2.5 concentration at Fukue Island, a remote island located in the western part of Japan and close to the Asian continent, is estimated using a three-dimensional chemical transport model. The model results suggest that PM_2.5 that is attributed to foreign anthropogenic sources have a larger contribution than that of domestic pollution and have a substantial impact on attainment of the atmospheric environmental standard of Japan at Fukue Island.     

Chemical Composition and Source Apportionment of PM25 Particles in the Sihwa Area,Korea

ABSTRACT

To investigate the chemical characteristics of fine particles in the Sihwa area, Korea, atmospheric aerosol samples were collected using a dichotomous PM₁₀ sampler and two URG PM_2.5 cyclone samplers during five intensive sampling periods between February 1998 and February 1999. The Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS), ion chromatograph (IC), and thermal manganese dioxide oxidation (TMO) methods were used to analyze the trace elements, ionic species, and carbonaceous species, respectively. Backward trajectory analysis, factor analysis, and a chemical mass balance (CMB) model were used to estimate quantitatively source contributions to PM_{2 5} particles collected in the Sihwa area.

The results of PM_2.5 source apportionment using the CMB7 receptor model showed that (NH₄)₂SO₄ was, on average, the major contributor to PM_2.5 particles, followed by nontraffic organic carbon (OC) emission, NH₄NO₃, agricultural waste burning, motor vehicle emission, road dust, waste incineration, marine aerosol, and others. Here, the nontraffic OC sources include primary anthropogenic OC emitted from the industrial complex zone, secondary OC, and organic species from distant sources. The source impact of waste incineration emission became significant when the dominant wind directions were from southwest and west sectors during the sampling periods. It was found that PM_2.5 particles in the Sihwa area were influenced mainly by both anthropogenic local sources and long-range transport and transformation of air pollutants.     

Emission of respirable dust from stone quarrying,potential health effects,and its management

Mining of minerals exerts adverse pressure on different compartments of environment directly or indirectly. Air is the worst affected environmental matrix, and it can carry the harmful effect of pollutants generated from mining activity even to distant places. The present study was undertaken to estimate the emission of particulate matter (PM_2.5 and PM₁₀) from different activities undertaken in stone quarrying in Mahendragarh, Haryana. The results obtained from the present study indicated that drilling, blasting, crushing, and transport of mined material are chiefly responsible for the generation of dust. Whereas drilling, blasting, and loading were responsible for emission of higher fraction of PM₁₀, crushing and re-suspension of roadside dust from movement of vehicles resulted in generation of relatively higher fraction of finer dust (PM_2.5). Modelling the transport of dust over the Hybrid Single-Particle Lagrangian Integrated Trajectory model revealed that the emitted particle may move up to the distance of about 40 km within 4 h of emission under average meteorological conditions. Fourier transform infrared (FTIR) spectroscopy analysis of dust confirmed the presence of calcite and gypsum, thus confirming the source as mining. The study concluded that generation of PM_2.5-sized particles may impose serious respiratory health effects over the workers engaged in mining, crushing, and transportation of sandstone. Apart from it, population residing downwind of the mining area is particularly vulnerable to the pulmonary effects due to inhalation of dust.

     

Estimating fugitive dust emission rates using an environmental boundary layer wind tunnel

Emissions from fugitive dust due to erosion of “natural” wind-blown surfaces are an increasingly important part of PM₁₀ (particulate matter with sizes of 10 μm aerodynamic diameter) emission inventories. These inventories are particularly important to State Implementation Plans (SIP), the plan required for each state to file with the Federal government indicating how they will comply with the Federal Clean Air Act (FCAA). However, techniques for determining the fugitive dust contribution to over all PM₁₀ emissions are still in their developmental stages. In the past, the methods have included field monitoring stations, specialized field studies and field wind-tunnel studies. The measurements made in this paper allow for systematic determination of PM₁₀ emission rates through the use of an environmental boundary layer wind tunnel in the laboratory. Near surface steady-state concentration profiles and velocity profiles are obtained in order to use a control volume approach to estimate emission rates. This methodology is applied to soils retrieved from the nation's single largest PM₁₀ source, Owens (dry) Lake in California, to estimate emission rates during active storm periods. The estimated emission rates are comparable to those obtained from field studies and lend to the validity of this method for determining fugitive dust emission rates.     

Chemical characteristics and source apportionment of PM<Subscript>2.5</Subscript> using PCA/APCS,UNMIX, and PMF at an urban site of Delhi,India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^?3 (range 25.1–429.8 μg m^?3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ～17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.     

Differentiation of the contribution of local resuspension from that of regional and remote sources on trace elements content in the atmospheric aerosol in the Mediterranean area

For the determination of effects of contaminated crude soil on the content of trace elements in the atmospheric aerosol, trace elements in crude soil samples from within the area of influence of local resuspension were analysed. The obtained results were used for determining the contribution of local resuspension on contents of trace elements in the atmospheric aerosol using the enrichment factors (EF) method. The content of trace elements in a crude soil could arise from the geochemical background of the soil or from anthropogenic contributions. Analysis of the quantile showed that Cd, Se and Ni originate from local emission sources. PCA showed that four groups of sources contributed to the content of trace elements in PM in part of the receptor. Using EF, it was ascertained that local resuspension of crude soil particles had a dominant influence on the content of Fe, Mn and Ti in the atmospheric aerosol, and that local resuspension had no influence on the content of Se in the atmospheric aerosol. Dust originating from deserts of North Africa and Middle East, through long-range transport and through resuspension of settled dust particles, significantly contributes to the content of Fe, Mn and Ti in the atmospheric aerosol. Cd originated from contaminated crude soil. The other investigated elements originated partly from crude soil but also from some other emission sources in the region.     

Uncertainty requirements of the European Union’s Industrial Emissions Directive for monitoring sulfur dioxide emissions: Implications from a blind comparison of sulfate measurements by accredited laboratories

When annual average PM_2.5 (fine particulate matter sized 2.5 microns and less) data for 2005 became available in April 2006 and the 3-yr average PM_2.5 concentration in an area just north of the Houston Ship Channel reached 15.0 µg/m³, the Texas Commission on Environmental Quality (TCEQ) initiated daily collection of quartz fiber as well as Teflon PM_2.5 filter samples for chemical speciation analysis. The purpose of the chemical speciation analysis was to use the speciation data, together with meteorological data and hourly TEOM (tapered element oscillating microbalance) PM_2.5 mass data, to identify the causes of the high PM_2.5 concentrations affecting the monitoring site and the neighborhood. The ultimate purpose was to target emission reduction efforts to sources contributing to the high measured PM_2.5 concentrations. After a year of data collection, it was recognized that a specific source, unpaved driveways and loading areas along the Ship Channel and dirt tracked onto Clinton Drive, the main artery running east-west north of the Ship Channel, were the primary cause for the Clinton Drive site's measuring PM_2.5 concentrations significantly higher than other sites in Houston. The source characterization and remediation steps that have led to sustained reduced concentrations are described in this paper.

Implications: With PM_2.5 exceedances it can be essential to have or develop chemical speciation data as part of the process of identifying the source types causing exceedances of an annual standard. Positive matrix factorization (PMF) analysis proved to be a powerful tool that identified the two locally emitted species contributing to exceedances, which did not occur at other sites in the region. They were calcium sulfate (gypsum), an industrial by-product, and soil minerals. Other data analysis approaches were necessary to distinguish North African dust events, which PMF failed to identify.     

Mineral aerosols from western India: Temporal variability of coarse and fine atmospheric dust and elemental characteristics

Size-segregated aerosol samples (PM_2.5 and PM₁₀) were collected during Jan–Dec-2007 from a high-altitude site located in a semi-arid region (Mt. Abu, 24.6 °N, 72.7 °E, 1680 m asl) in order to asses the temporal variability in the abundance of atmospheric mineral dust and its elemental composition over western India. The mass concentrations of fine (PM_2.5) and coarse (PM_10–2.5) mode aerosols varied from 1.6 to 46.1 and 2.3 to 102 μg m^?3 respectively over the annual seasonal cycle; with dominant and uniform contribution of mineral dust (60–80%) in the coarse mode relative to large temporal variability (11–75%) observed in the fine mode. The coarse mass fraction shows a characteristic increase with the wind speed during summer months (Mar to Jun); whereas fine aerosol mass and its elemental composition exhibit conspicuous temporal pattern associated with north-easterlies during wintertime (Oct–Feb). The Fe/Al weight ratio in PM_2.5 ranges from 0.5 to 1.0 during winter months. The relative enrichment of Fe in fine mode, compared to the crustal ratio of 0.44, is attributed to the down-wind advective transport of combustion products derived from large-scale biomass burning, industrial and automobile emission sources located in the Indo-Gangetic Plain (northern India). In contrast, Ca/Al and Mg/Al weight ratios show relative enrichment of Ca and Mg in the coarse mode; indicating their dominant contribution from carbonate minerals. This has implication to efficient neutralization of atmospheric acidic species (SO₄^2? and NO₃^?) by mineral dust over western India.     

Fine Particulate Matter Emissions Inventories: Comparisons of Emissions Estimates with Observations from Recent Field Programs

Abstract

Emissions inventories of fine particulate matter (PM_2.5) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM_2.5 emissions were reviewed: on-road mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM_2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5–20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM_2.5 are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM_2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.     

Regional-specific emission inventory for NH3, N2O, and CH4 via animal farming in South, Southeast, and East Asia

Ammonia, nitrous oxide, and methane emission from animal farming of South, Southeast, and East Asia, in 2000, was estimated at about 4.7 Tg NH₃–N, 0.51 Tg N₂O–N, and 29.9 Tg CH₄, respectively, using the FAO database and countries’ statistic databases as activity data, and emission factors taking account of regional characteristics. Most of these atmospheric components, up to 60–80%, were produced in China and India. Pakistan, Bangladesh, and Indonesia, which were large source countries next to China and India, contributed more than a few percent of total emission of each atmospheric component. The largest emission livestock were cattle whose contribution was considerably high in South, Southeast, and East Asia; more than one-fourth of ammonia and nitrous oxide emissions: more than half of methane emission. The other major livestock for nitrous oxide and ammonia emissions were pigs. For methane emission, buffaloes were second source livestock. To provide spatial distributions of these gases, the emissions of county and district level were allocated into each 0.5° grid by means of the weighting by high-resolution land cover datasets. The regions with considerable high emissions of all components were able to be found at the Ganges delta and the Yellow River basin. The spatial distributions for ammonia and nitrous oxide emissions were similar but had a substantial difference from methane distribution.     

Estimating PM10 air concentrations from dust storms in Iraq,Kuwait and Saudi Arabia

A model for the emission of PM₁₀ dust has been constructed using the concept of a threshold friction velocity which is dependent on surface roughness. Surface roughness in turn was correlated with geomorphology or soil properties for Kuwait, Iraq, part of Syria, Saudi Arabia, the United Arab Emirates and Oman. The PM₁₀ emission algorithm was incorporated into a Lagrangian transport and dispersion model. PM₁₀ air concentrations were computed from August 1990 through August 1991. The model predicted about the right number of dust events over Kuwait (events occur 18% of the time). The model results agreed quantitatively with measurements at four locations in Saudi Arabia and one in Kuwait for one major dust event (>1000 μg/m³). However, for smaller scale dust events (200–1000 μg/m³), especially at the coastal sampling locations, the model substantially over-predicted the air concentrations. Part of the over-prediction was attributed to the entrainment of dust-free air by the sea breeze, a flow feature not represented by the large-scale gridded meteorological data fields used in the model computation. Another part of the over-prediction was the model's strong sensitivity to threshold friction velocity and the surface soil texture coefficient (the soil emission factor), and the difficulty in accurately representing these parameters in the model. A comparison of the model predicted PM₁₀ spatial pattern with the TOMS satellite aerosol index (AI) yielded a spatial pattern covering a major portion of Saudi Arabia that was quite similar to the observed AI pattern.     

An analysis of seasonal surface dust aerosol concentrations in the western US (2001–2004): Observations and model predictions

Long-term surface observations indicate that soil dust represents over 30% of the annual fine (particle diameter less than 2.5 μm) particulate mass in many areas of the western US; in spring and summer, it represents an even larger fraction. There are numerous dust-producing playas in the western US, but surface dust aerosol concentrations in this region are also influenced by dust of Asian origin. This study examines the seasonality of surface soil dust concentrations at 15 western US sites using observations from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network from 2001 to 2004. Average soil concentrations in particulate matter less than 10 μm in diameter (PM₁₀) were lowest in winter and peaked during the summer months at these sites; however, episodic higher-concentration events (>10 μg m⁻³) occurred in the spring, the time of maximum Asian dust transport to the western US. Simulated surface dust concentrations from the Navy Aerosol Analysis and Prediction System (NAAPS) suggested that long-range transport from Asia dominates surface dust concentrations in the western US in the spring, and that, although some long-range transport does occur throughout the year (1–2 μg m⁻³), locally generated dust plays a larger role in the region in summer and fall. However, NAAPS simulated some anomalously high concentrations (>50 μg m⁻³) of local dust in the fall and winter months over portions of the western US. Differences between modeled and observed dust concentrations were attributed to overestimation of total observed soil dust concentrations by the assumptions used to convert IMPROVE measurements into PM₁₀ soil concentrations, lack of inhibition of model dust production in snow-covered regions, and lack of seasonal agricultural sources in the model.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.