Trends,temporal and spatial characteristics,and uncertainties in biomass burning emissions in the Pearl River Delta,China

Multi-year inventories of biomass burning emissions were established in the Pearl River Delta (PRD) region for the period 2003–2007 based on the collected activity data and emission factors. The results indicated that emissions of sulfur dioxide (SO₂), nitrogen oxide (NO_x), ammonia (NH₃), methane (CH₄), organic carbon (OC), non-methane volatile organic compounds (NMVOC), carbon monoxide (CO), and fine particulate matter (PM_2.5) presented clear declining trends. Domestic biofuel burning was the major contributor, accounting for more than 60% of the total emissions. The preliminary temporal profiles were established with MODIS fire count information, showing that higher emissions were observed in winter (from November to March) than other seasons. The emissions were spatially allocated into grid cells with a resolution of 3 km × 3  km, using GIS-based land use data as spatial surrogates. Large amount of emissions were observed mostly in the less developed areas in the PRD region. The uncertainties in biomass burning emission estimates were quantified using Monte Carlo simulation; the results showed that there were higher uncertainties in organic carbon (OC) and elemental carbon (EC) emission estimates, ranging from ?71% to 133% and ?70% to 128%, and relatively lower uncertainties in SO₂, NO_x and CO emission estimates. The key uncertainty sources of the developed inventory included emission factors and parameters used for estimating biomass burning amounts.     

Chemical composition of aerosols during a major biomass burning episode over northern Europe in spring 2006: Experimental and modelling assessments

The long-range transported smokes emitted by biomass burning had a strong impact on the PM_2.5 mass concentrations in Helsinki over the 12 days period in April and May 2006. To characterize aerosols during this period, the real-time measurements were done for PM_2.5, PM_2.5–10, common ions and black carbon. Moreover, the 24-h PM₁ filter samples were analysed for organic and elemental carbon (OC and EC), water-soluble organic carbon (WSOC), ions and levoglucosan. The Finnish emergency and air quality modelling system SILAM was used for the forecast of the PM_2.5 concentration generated by biomass burning. According to the real-time PM_2.5 data, the investigated period was divided into four types of PM situations: episode 1 (EPI-1; 25–29 April), episode 2 (EPI-2; 1–5 May), episode 3 (EPI-3; 5–6 May) and a reference period (REF; 24 March–24 April). EPI-3 included a local warehouse fire and therefore it is discussed separately. The PM₁ mass concentrations of biomass burning tracers—levoglucosan, potassium and oxalate—increased during the two long-range transport episodes (EPI-1 and EPI-2). The most substantial difference between the episodes was exhibited by the sulphate concentration, which was 4.9 (±1.4) μg m⁻³ in EPI-2 but only 2.4 (±0.31) μg m⁻³ in EPI-1 being close to that of REF (1.8±0.54 μg m⁻³). The concentration of particulate organic matter in PM₁ was clearly higher during EPI-1 (11±3.3 μg m⁻³) and EPI-2 (9.7±4.0 μg m⁻³) than REF (1.3±0.45 μg m⁻³). The long-range transported smoke had only a minor impact on the WSOC-to-OC ratio. According to the model simulations, MODIS detected the fires that caused the first set of concentration peaks (EPI-1) and the local warehouse fire (EPI-3), but missed the second one (EPI-2) probably due to dense frontal clouds.     

Aerosol transport model evaluation of an extreme smoke episode in Southeast Asia

Biomass burning is one of many sources of particulate pollution in Southeast Asia, but its irregular spatial and temporal patterns mean that large episodes can cause acute air quality problems in urban areas. Fires in Sumatra and Borneo during September and October 2006 contributed to 24-h mean PM₁₀ concentrations above 150 μg m^?3 at multiple locations in Singapore and Malaysia over several days. We use the FLAMBE model of biomass burning emissions and the NAAPS model of aerosol transport and evolution to simulate these events, and compare our simulation results to 24-h average PM₁₀ measurements from 54 stations in Singapore and Malaysia. The model simulation, including the FLAMBE smoke source as well as dust, sulfate, and sea salt aerosol species, was able to explain 50% or more of the variance in 24-h PM₁₀ observations at 29 of 54 sites. Simulation results indicated that biomass burning smoke contributed to nearly all of the extreme PM₁₀ observations during September–November 2006, but the exact contribution of smoke was unclear because the model severely underestimated total smoke emissions. Using regression analysis at each site, the bias in the smoke aerosol flux was determined to be a factor of between 2.5 and 10, and an overall factor of 3.5 was estimated. After application of this factor, the simulated smoke aerosol concentration averaged 20% of observed PM₁₀, and 40% of PM₁₀ for days with 24-h average concentrations above 150 μg m^?3. These results suggest that aerosol transport models can aid analysis of severe pollution events in Southeast Asia, but that improvements are needed in models of biomass burning smoke emissions.     

Organic and elemental carbon associated to PM10 and PM2.5 at urban sites of northern Greece

Organic carbon (OC) and elemental carbon (EC) concentrations, associated to PM₁₀ and PM_2.5 particle fractions, were concurrently determined during the warm and the cold months of the year (July–September 2011 and February–April 2012, respectively) at two urban sites in the city of Thessaloniki, northern Greece, an urban-traffic site (UT) and an urban-background site (UB). Concentrations at the UT site (11.3?±?5.0 and 8.44?±?4.08 14 μg m^?3 for OC₁₀ and OC_2.5 vs. 6.56?±?2.14 and 5.29?±?1.54 μg m^?3 for EC₁₀ and EC_2.5) were among the highest values reported for urban sites in European cities. Significantly lower concentrations were found at the UB site for both carbonaceous species, particularly for EC (6.62?±?4.59 and 5.72?±?4.36 μg m^?3 for OC₁₀ and OC_2.5 vs. 0.93?±?0.61 and 0.69?±?0.39 μg m^?3 for EC₁₀ and EC_2.5). Despite that, a negative UT-UB increment was frequently evidenced for OC_2.5 and PM_2.5 in the cold months possibly indicative of emissions from residential wood burning at the urban-background site. At both sites, cconcentrations of OC fractions were significantly higher in the cold months; on the contrary, EC fractions at the UT site were prominent in the warm season suggesting some influence from maritime emissions in the nearby harbor area. Secondary organic carbon, being estimated using the EC tracer method and seasonally minimum OC/EC ratios, was found to be an appreciable component of particle mass particularly in the cold season. The calculated secondary contributions to OC ranged between 35 and 59 % in the PM₁₀ fraction, with relatively higher values in the PM_2.5 fraction (39–61 %). The source origin of carbonaceous species was investigated by means of air parcel back trajectories, satellite fire maps, and concentration roses. A local origin was mainly concluded for OC and EC with limited possibility for long range transport of biomass (agricultural waste) burning aerosol.     

Comparison of summer and winter California central valley aerosol distributions from lidar and MODIS measurements

Aerosol distributions from two aircraft lidar campaigns conducted in the California Central Valley are compared in order to identify seasonal variations. Aircraft lidar flights were conducted in June 2003 and February 2007. While the ground PM_2.5 (particulate matter with diameter ≤ 2.5 μm) concentration was highest in the winter, the aerosol optical depth (AOD) measured from the MODIS and lidar instruments was highest in the summer. A multiyear seasonal comparison shows that PM_2.5 in the winter can exceed summer PM_2.5 by 68%, while summer AOD from MODIS exceeds winter AOD by 29%. Warmer temperatures and wildfires in the summer produce elevated aerosol layers that are detected by satellite measurements, but not necessarily by surface particulate matter monitors. Temperature inversions, especially during the winter, contribute to higher PM_2.5 measurements at the surface. Measurements of the mixing layer height from lidar instruments provide valuable information needed to understand the correlation between satellite measurements of AOD and in situ measurements of PM_2.5. Lidar measurements also reflect the ammonium nitrate chemistry observed in the San Joaquin Valley, which may explain the discrepancy between the MODIS AOD and PM_2.5 measurements.     

Long-range transport episodes of fine particles in southern Finland during 1999–2007

The frequency, strength and sources of long-range transport (LRT) episodes of fine particles (PM_2.5) were studied in southern Finland using air quality monitoring results, backward air mass trajectories, remote sensing of fire hot spots, transport and dispersion modelling of smoke and chemical analysis of particle samples (black carbon, monosaccharide anhydrides, oxalate, succinate, malonate, SO₄^2?, NO₃^?, K⁺ and NH₄⁺). At an urban background site in Helsinki, the daily WHO guideline value (24-h PM_2.5 mean 25 μg m^?3) was exceeded during 1–7 LRT episodes per year in 1999–2007. The 24-h mean maximum concentrations varied between 25 and 49 μg m^?3 during the episodes, which was 3–6 times higher than the local mean concentration (8.7 μg m^?3) in 1999–2007. The highest particle concentrations (max. 1-h mean 163 μg m^?3) and the longest episodes (max. 9 days) were mainly caused by the emissions from open biomass burning, especially during springs and late-summers in 2002 and 2006. During the period 2001–2007, the satellite remote sensing of active fire hot spots and transport and dispersion modelling of smoke indicated that approximately half of the episodes were caused partly by the emissions from wildfires and/or agricultural waste burning in fields in Eastern Europe, especially in Russia, Belarus and Ukraine. Other episodes were mainly caused by the LRT of ordinary anthropogenic pollutants, e.g. from energy production, traffic, industry and wood combustion. During those ‘other episodes’, air masses also arrived from Eastern Europe, including Poland. The highest concentrations of biomass-burning tracers, such as monosaccharide anhydrides (levoglucosan + mannosan + galactosan) and K⁺, were observed during open biomass-burning episodes, but quite high values were also measured during some winter episodes due to wood combustion emissions. Our results indicate that open biomass burning in Eastern Europe causes high fine particle concentration peaks in large areas of Europe almost every year.     

Sources and characteristics of carbonaceous aerosol in two largest cities in Pearl River Delta Region,China

PM_2.5 samples were collected at five sites in Guangzhou and Hong Kong, Pearl River Delta Region (PRDR), China in both summer and winter during 2004–2005. Elemental carbon (EC) and organic carbon (OC) in these samples were measured. The OC and EC concentrations ranked in the order of urban Guangzhou > urban Hong Kong > background Hong Kong. Total carbonaceous aerosol (TCA) contributed less to PM_2.5 in urban Guangzhou (32–35%) than that in urban Hong Kong (43–57%). The reason may be that, as an major industrial city in South China, Guangzhou would receive large amount of inorganic aerosol from all kinds of industries, however, as a trade center and seaport, urban Hong Kong would mainly receive organic aerosol and EC from container vessels and heavy-duty diesel trucks. At Hong Kong background site Hok Tsui, relatively lower contribution of TCA to PM_2.5 may result from contributions of marine inorganic aerosol and inland China pollutant. Strong correlation (R²=0.76–0.83) between OC and EC indicates minor fluctuation of emission and the secondary organic aerosol (SOA) formation in urban Guangzhou. Weak correlation between OC and EC in Hong Kong can be related to the impact of the long-range transported aerosol from inland China. Averagely, secondary OC (SOC) concentrations were 3.8–5.9 and 10.2–12.8 μg m⁻³, respectively, accounting for 21–32% and 36–42% of OC in summer and winter in Guangzhou. The average values of 4.2–6.8% for SOA/ PM_2.5 indicate that SOA was minor component in PM_2.5 in Guangzhou.     

Seasonal and spatial trends in the sources of fine particle organic carbon in Israel,Jordan, and Palestine

A study of carbonaceous particulate matter (PM) was conducted in the Middle East at sites in Israel, Jordan, and Palestine. The sources and seasonal variation of organic carbon, as well as the contribution to fine aerosol (PM_2.5) mass, were determined. Of the 11 sites studied, Nablus had the highest contribution of organic carbon (OC), 29%, and elemental carbon (EC), 19%, to total PM_2.5 mass. The lowest concentrations of PM_2.5 mass, OC, and EC were measured at southern desert sites, located in Aqaba, Eilat, and Rachma. The OC contribution to PM_2.5 mass at these sites ranged between 9.4% and 16%, with mean annual PM_2.5 mass concentrations ranging from 21 to 25 ug m^?3. These sites were also observed to have the highest OC to EC ratios (4.1–5.0), indicative of smaller contributions from primary combustion sources and/or a higher contribution of secondary organic aerosol. Biomass burning and vehicular emissions were found to be important sources of carbonaceous PM in this region at the non-southern desert sites, which together accounted for 30%–55% of the fine particle organic carbon at these sites. The fraction of measured OC unapportioned to primary sources (1.4 μgC m^?3 to 4.9 μgC m^?3; 30%–74%), which has been shown to be largely from secondary organic aerosol, is relatively constant at the sites examined in this study. This suggests that secondary organic aerosol is important in the Middle East during all seasons of the year.     

Chemical characterization and source apportionment of fine and coarse particulate matter in Lahore,Pakistan

Lahore, Pakistan is an emerging megacity that is heavily polluted with high levels of particle air pollution. In this study, respirable particulate matter (PM_2.5 and PM₁₀) were collected every sixth day in Lahore from 12 January 2007 to 19 January 2008. Ambient aerosol was characterized using well-established chemical methods for mass, organic carbon (OC), elemental carbon (EC), ionic species (sulfate, nitrate, chloride, ammonium, sodium, calcium, and potassium), and organic species. The annual average concentration (±one standard deviation) of PM_2.5 was 194 ± 94 μg m^?3 and PM₁₀ was 336 ± 135 μg m^?3. Coarse aerosol (PM_10?2.5) was dominated by crustal sources like dust (74 ± 16%, annual average ± one standard deviation), whereas fine particles were dominated by carbonaceous aerosol (organic matter and elemental carbon, 61 ± 17%). Organic tracer species were used to identify sources of PM_2.5 OC and chemical mass balance (CMB) modeling was used to estimate relative source contributions. On an annual basis, non-catalyzed motor vehicles accounted for more than half of primary OC (53 ± 19%). Lesser sources included biomass burning (10 ± 5%) and the combined source of diesel engines and residual fuel oil combustion (6 ± 2%). Secondary organic aerosol (SOA) was an important contributor to ambient OC, particularly during the winter when secondary processing of aerosol species during fog episodes was expected. Coal combustion alone contributed a small percentage of organic aerosol (1.9 ± 0.3%), but showed strong linear correlation with unidentified sources of OC that contributed more significantly (27 ± 16%). Brick kilns, where coal and other low quality fuels are burned together, are suggested as the most probable origins of unapportioned OC. The chemical profiling of emissions from brick kilns and other sources unique to Lahore would contribute to a better understanding of OC sources in this megacity.     

Chemical speciation,transport and contribution of biomass burning smoke to ambient aerosol in Guangzhou,a mega city of China

Intensive measurements of aerosol (PM₁₀) and associated water-soluble ionic and carbonaceous species were conducted in Guangzhou, a mega city of China, during summer 2006. Elevated levels of most chemical species were observed especially at nighttime during two episodes, characterized by dramatic build-up of the biomass burning tracers levoglucosan and non-sea-salt potassium, when the prevailing wind direction had changed due to two approaching tropical cyclones. High-resolution air mass back trajectories based on the MM5 model revealed that air masses with high concentrations of levoglucosan (43–473 ng m^?3) and non-sea-salt potassium (0.83–3.2 μg m^?3) had passed over rural regions of the Pearl River Delta and Guangdong Province, where agricultural activities and field burning of crop residues are common practices. The relative contributions of biomass burning smoke to organic carbon in PM₁₀ were estimated from levoglucosan data to be on average 7.0 and 14% at daytime and nighttime, respectively, with maxima of 9.7 and 32% during the episodic transport events, indicating that biomass and biofuel burning activities in the rural parts of the Pearl River Delta and neighboring regions could have a significant impact on ambient urban aerosol levels.     

Source apportionment of PM2.5 and PM10 aerosols in Brisbane (Australia) by receptor modelling

Aerosol samples for PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters less than 2.5 and 10 μm, respectively) were collected from 1993 to 1995 at five sites in Brisbane, a subtropical coastal city in Australia. This paper investigates the contributions of emission sources to PM_2.5 and PM₁₀ aerosol mass in Brisbane. Source apportionment results derived from the chemical mass balance (CMB), target transformation factor analysis (TTFA) and multiple linear regression (MLR) methods agree well with each other. The contributions from emission sources exhibit large variations in particle size with temporal and spatial differences. On average, the major contributors of PM₁₀ aerosol mass in Brisbane include: soil/road side dusts (25% by mass), motor vehicle exhausts (13%, not including the secondary products), sea salt (12%), Ca-rich and Ti-rich compounds (11%, from cement works and mineral processing industries), biomass burning (7%), and elemental carbon and secondary products contribute to around 15% of the aerosol mass on average. The major sources of PM_2.5 aerosols at the Griffith University (GU) site (a suburban site surrounded by forest area) are: elemental carbon (24% by mass), secondary organics (21%), biomass burning (15%) and secondary sulphate (14%). Most of the secondary products are related to motor vehicle exhausts, so, although motor vehicle exhausts contribute directly to only 6% of the PM_2.5 aerosol mass, their total contribution (including their secondary products) could be substantial. This pattern of source contribution is similar to the results for Rozelle (Sydney) among the major Australian studies, and is less in contributions from industrial and motor vehicular exhausts than the other cities. An attempt was made to estimate the contribution of rural dust and road side dust. The results show that road side dusts could contribute more than half of the crustal matter. More than 80% of the contribution of vehicle exhausts arises from diesel-fuelled trucks/buses. Biomass burning, large contributions of crustal matter, and/or local contributing sources under calm weather conditions, are often the cause of the high PM₁₀ episodes at the GU site in Brisbane.     

Oxidation of ketone groups in transported biomass burning aerosol from the 2008 Northern California Lightning Series fires

Submicron particles were collected from June to September 2008 in La Jolla, California to investigate the composition and sources of atmospheric aerosol in an anthropogenically-influenced coastal site. Factor analysis of aerosol mass spectrometry (AMS) and Fourier transform infrared (FTIR) spectroscopy measurements revealed that the two largest sources of submicron organic mass (OM) at the sampling site were (1) fossil fuel combustion associated with ship and diesel truck emissions near the ports of Los Angeles and Long Beach and (2) aged smoke from large wildfires burning in central and northern California. During non-fire periods, fossil fuel combustion contributed up to 95% of FTIR OM, correlated to sulfur, and consisted mostly of alkane (86%) and carboxylic acid groups (9%). During fire periods, biomass burning contributed up to 74% of FTIR OM, consisted mostly of alkane (48%), ketone (25%), and carboxylic acid groups (17%), and correlated to AMS-derived factors resembling brush fire smoke, wood smoldering and flaming particles, and biogenic secondary organic aerosol. The two AMS-derived biomass burning factors were identified as oxygenated and hydrocarbon biomass burning aerosol on the basis of spectral similarities to smoldering and flaming smoke particles, respectively. In addition, the ratio of oxygenated to hydrocarbon biomass burning OM shows a clear diurnal trend with an afternoon peak, consistent with photochemical oxidation. Back trajectory analysis indicates that 2–4-day old forest fire emissions include substantial ketone groups, which have both lower O/C and lower m/z 44/OM fraction than carboxylic acid groups. Air masses with more than 4-day old emissions have higher carboxylic acid/ketone group ratios, showing that atmospheric processing of these ketone-containing organic aerosol particles results in increased m/z 44 and O/C. These observations may provide functionally-specific evidence for the type of chemical processing that is responsible for biomass burning particle composition in the atmosphere.     

Estimating PM2.5 over southern Sweden using space-borne optical measurements

In the present study Bremen aerosol retrieval (BAER) columnar aerosol optical thickness (AOT) data, according to moderate resolution imaging spectroradiometer (MODIS) and medium resolution imaging sensor (MERIS) level 1 calibrated satellite data, have been compared with AOT data obtained with the MODIS and MERIS retrieval algorithms (NASA and ESA, respectively) and by AErosol RObotic NETwork (AERONET). Relatively good agreement is found between these different instruments and algorithms. The R² and relative RMSD were 0.86 and 31% for MODIS when comparing with AERONET and 0.92 and 21% for MERIS. The aerosols investigated were influenced by low relative humidity. During this period, a relatively large range of aerosol loadings were detected; from continental background aerosol to particles emitted from agricultural fires. In this study, empirical relationships between BAER columnar AOT and ground-measured PM_2.5 have been estimated. Linear relationships, with R² values of 0.58 and 0.59, were obtained according to MERIS and MODIS data, respectively. The slopes of the regression of AOT versus PM_2.5 are lower than previous studies, but this could easily be explained by considering the effect of hygroscopic growth. The present AOT–PM_2.5 relationship has been applied on MERIS full resolution data over the urban area of Stockholm and the results have been compared with particle mass concentrations from dispersion model calculations. It seems that the satellite data with the 300 m resolution can resolve the expected increased concentrations due to emissions along the main highways close to the city. Significant uncertainties in the spatial distribution of PM_2.5 across land/ocean boundaries were particularly evident when analyzing the high resolution satellite data.     

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.     

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.     

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.     

Year-long continuous personal exposure to PM2.5 recorded by a fast responding portable nephelometer

Personal exposure to particulate matter of aerodynamic diameter under 2.5 μm (PM_2.5) was monitored using a DustTrak nephelometer. The battery-operated unit, worn by an adult individual for a period of approximately one year, logged integrated average PM_2.5 concentrations over 5 min intervals. A detailed time-activity diary was used to record the experimental subject’s movement and the microenvironments visited. Altogether 239 days covering all the months (except April) were available for the analysis. In total, 60 463 acceptable 5-min averages were obtained. The dataset was divided into 7 indoor and 4 outdoor microenvironments. Of the total time, 84% was spent indoors, 10.9% outdoors and 5.1% in transport. The indoor 5-min PM_2.5 average was higher (55.7 μg m^?3) than the outdoor value (49.8 μg m^?3). The highest 5-min PM_2.5 average concentration was detected in restaurant microenvironments (1103 μg m^?3), the second highest 5-min average concentration was recorded in indoor spaces heated by stoves burning solid fuels (420 μg m^?3). The lowest 5-min mean aerosol concentrations were detected outdoors in rural/natural environments (25 μg m^?3) and indoors at the monitored person’s home (36 μg m^?3). Outdoor and indoor concentrations of PM_2.5 measured by the nephelometer at home and during movement in the vicinity of the experimental subject’s home were compared with those of the nearest fixed-site monitor of the national air quality monitoring network. The high correlation coefficient (0.78) between the personal and fixed-site monitor aerosol concentrations suggested that fixed-site monitor data can be used as proxies for personal exposure in residential and some other microenvironments. Collocated measurements with a reference method (β-attenuation) showed a non-linear systematic bias of the light-scattering method, limiting the use of direct concentration readings for exact exposure analysis.     

Analysis of atmospheric aerosol (PM2.5) in Recife city,Brazil

Several studies indicate that mortality and morbidity can be well correlated to atmospheric aerosol concentrations with aerodynamic diameter less than 2.5 µm (PM_2.5). In this work the PM_2.5 at Recife city was analyzed as part of a main research project (INAIRA) to evaluate the air pollution impact on human health in six Brazilian metropolitan areas. The average concentration, for 309 samples (24-hr), from June 2007 to July 2008, was 7.3 µg/m³, with an average of 1.1 µg/m³ of black carbon. The elemental concentrations of samples were obtained by x-ray fluorescence. The concentrations were then used for characterizing the aerosol, and also were employed for receptor modelling to identify the major local sources of PM_2.5. Positive matrix factorization analysis indicated six main factors, with four being associated to soil dust, vehicles and sea spray, metallurgical activities, and biomass burning, while for a chlorine factor, and others related to S, Ca, Br, and Na, we could make no specific source association. Principal component analysis also indicated six dominant factors, with some specific characteristics. Four factors were associated to soil dust, vehicles, biomass burning, and sea spray, while for the two others, a chlorine- and copper-related factor and a nickel-related factor, it was not possible to do a specific source association. The association of the factors to the likely sources was possible thanks to meteorological analysis and sources information. Each model, although giving similar results, showed factors’ peculiarities, especially for source apportionment. The observed PM_2.5 concentration levels were acceptable, notwithstanding the high urbanization of the metropolitan area, probably due to favorable conditions for air pollution dispersion. More than a valuable historical register, these results should be very important for the next analysis, which will correlate health data, PM_2.5 levels, and sources contributions in the context of the six studied Brazilian metropolises.

Implications: The analysis of fine particulate matter (PM_2.5) in Recife city, Brazil, gave a significant picture of the local concentration and composition of this pollutant, which exhibits robust associations to adverse human health effects. Data from 1 year of sampling evaluated the seasonal variability and its connections with weather patterns. Source apportionment in this metropolitan area was obtained based in a combination of receptor models: principal component analysis (PCA)/chemical mass balance (CMB) and positive matrix factorization (PMF). These results give guidelines for local air pollution control actions, providing significant information for a health study in the context of establishing a new national air pollution protocol based on Brazilian cities data.     

Characterization of organic aerosol in Big Bend National Park,Texas

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study was conducted in Big Bend National Park, Texas, July through October 1999. Daily PM_2.5 organic aerosol samples were collected on pre-fired quartz fiber filters. Daily concentrations were too low for detailed organic analysis by gas chromatography-mass spectrometry (GC-MS) and were grouped based on their air mass trajectories. A total of 12 composites, each containing 3–10 daily samples, were analyzed. Alkane carbon preference indices suggest primary biogenic emissions were small contributors to primary PM_2.5 organic matter (OM) during the first 3 months, while in October air masses advecting from the north and south were more strongly influenced by biogenic sources. A series of trace organic compounds previously shown to serve as particle phase tracers for various carbonaceous aerosol source types were examined. Molecular tracer species were generally at or below detection limits, except for the wood smoke tracer levoglucosan in one composite, so maximum possible source influences were calculated using the detection limit as an upper bound to the tracer concentration. Wood smoke was found not to contribute significantly to PM_2.5 OM, with contributions for most samples at <1% of the total organic particulate matter. Vehicular exhaust also appeared to make only minor contributions, with maximum possible influences calculated to be 1–4% of PM_2.5 OM. Several factors indicate that secondary organic aerosol formation was important throughout the study, and may have significantly altered the molecular composition of the aerosol during transport.     

MODIS derived fire characteristics and aerosol optical depth variations during the agricultural residue burning season, north India

Agricultural residue burning is one of the major causes of greenhouse gas emissions and aerosols in the Indo-Ganges region. In this study, we characterize the fire intensity, seasonality, variability, fire radiative energy (FRE) and aerosol optical depth (AOD) variations during the agricultural residue burning season using MODIS data. Fire counts exhibited significant bi-modal activity, with peak occurrences during April-May and October-November corresponding to wheat and rice residue burning episodes. The FRE variations coincided with the amount of residues burnt. The mean AOD (2003-2008) was 0.60 with 0.87 (+1σ) and 0.32 (−1σ). The increased AOD during the winter coincided well with the fire counts during rice residue burning season. In contrast, the AOD-fire signal was weak during the summer wheat residue burning and attributed to dust and fossil fuel combustion. Our results highlight the need for ‘full accounting of GHG’s and aerosols’, for addressing the air quality in the study area.