Estimating trace gas and aerosol emissions over South America: Relationship between fire radiative energy released and aerosol optical depth observations

Contemporary human activities such as tropical deforestation, land clearing for agriculture, pest control and grassland management lead to biomass burning, which in turn leads to land-cover changes. However, biomass burning emissions are not correctly measured and the methods to assess these emissions form a part of current research area. The traditional methods for estimating aerosols and trace gases released into the atmosphere generally use emission factors associated with fuel loading and moisture characteristics and other parameters that are hard to estimate in near real-time applications. In this paper, fire radiative power (FRP) products were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) and from the Geostationary Operational Environmental Satellites (GOES) fire products and new South America generic biomes FRE-based smoke aerosol emission coefficients were derived and applied in 2002 South America fire season. The inventory estimated by MODIS and GOES FRP measurements were included in Coupled Aerosol-Tracer Transport model coupled to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) and evaluated with ground truth collected in Large Scale Biosphere–Atmosphere Smoke, Aerosols, Clouds, rainfall, and Climate (SMOCC) and Radiation, Cloud, and Climate Interactions (RaCCI). Although the linear regression showed that GOES FRP overestimates MODIS FRP observations, the use of a common external parameter such as MODIS aerosol optical depth product could minimize the difference between sensors. The relationship between the PM_2.5μm (Particulate Matter with diameter less than 2.5 μm) and CO (Carbon Monoxide) model shows a good agreement with SMOCC/RaCCI data in the general pattern of temporal evolution. The results showed high correlations, with values between 0.80 and 0.95 (significant at 0.5 level by student t test), for the CATT-BRAMS simulations with PM_2.5μm and CO.     

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.     

Estimation of NH3 bi-directional flux from managed agricultural soils

The Community Multi-Scale Air Quality model (CMAQ) is used to assess regional air quality conditions for a wide range of chemical species throughout the United States (U.S.). CMAQ representation of the regional nitrogen budget is limited by its treatment of ammonia (NH₃) soil emission from, and deposition to underlying surfaces as independent rather than tightly coupled processes, and by its reliance on soil emission estimates that do not respond to variable meteorology and ambient chemical conditions. The present study identifies an approach that addresses these limitations, lends itself to regional application, and will better position CMAQ to meet future assessment challenges. These goals were met through the integration of the resistance-based flux model of Nemitz et al. (2001) with elements of the United States Department of Agriculture EPIC (Environmental Policy Integrated Climate) model. Model integration centers on the estimation of ammonium and hydrogen ion concentrations in the soil required to estimate soil NH₃ flux. The EPIC model was calibrated using data collected during an intensive 2007 field study in Lillington, North Carolina. A simplified process model based on the nitrification portion of EPIC was developed and evaluated. It was then combined with the Nemitz et al. (2001) model and measurements of near-surface NH₃ concentrations to simulate soil NH₃ flux at the field site. Finally, the integrated flux (emission) results were scaled upward and compared to recent national ammonia emission inventory estimates. The integrated model results are shown to be more temporally resolved (daily), while maintaining good agreement with established soil emission estimates at longer time-scales (monthly). Although results are presented for a single field study, the process-based nature of this approach and NEI comparison suggest that inclusion of this flux model in a regional application should produce useful assessment results if nationally consistent sources of driving soil and agricultural management information are identified.     

Dynamic evaluation of a regional air quality model: Assessing the emissions-induced weekly ozone cycle

Air quality models are used to predict changes in pollutant concentrations resulting from envisioned emission control policies. Recognizing the need to assess the credibility of air quality models in a policy-relevant context, we perform a dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system for the “weekend ozone effect” to determine if observed changes in ozone due to weekday-to-weekend (WDWE) reductions in precursor emissions can be accurately simulated. The weekend ozone effect offers a unique opportunity for dynamic evaluation, as it is a widely documented phenomenon that has persisted since the 1970s. In many urban areas of the Unites States, higher ozone has been observed on weekends than weekdays, despite dramatically reduced emissions of ozone precursors (nitrogen oxides [NO_x] and volatile organic compounds [VOCs]) on weekends. More recent measurements, however, suggest shifts in the spatial extent or reductions in WDWE ozone differences. Using 18 years (1988–2005) of observed and modeled ozone and temperature data across the northeastern United States, we re-examine the long-term trends in the weekend effect and confounding factors that may be complicating the interpretation of this trend and explore whether CMAQ can replicate the temporal features of the observed weekend effect. The amplitudes of the weekly ozone cycle have decreased during the 18-year period in our study domain, but the year-to-year variability in weekend minus weekday (WEWD) ozone amplitudes is quite large. Inter-annual variability in meteorology appears to influence WEWD differences in ozone, as well as WEWD differences in VOC and NO_x emissions. Because of the large inter-annual variability, modeling strategies using a single episode lasting a few days or a few episodes in a given year may not capture the WEWD signal that exists over longer time periods. The CMAQ model showed skill in predicting the absolute values of ozone concentrations during the daytime. However, early morning NO_x concentrations were underestimated and ozone levels were overestimated. Also, the modeled response of ozone to WEWD differences in emissions was somewhat less than that observed. This study reveals that model performance may be improved by (1) properly estimating mobile source NO_x emissions and their temporal distributions, especially for diesel vehicles; (2) reducing the grid cell size in the lowest layer of CMAQ; and, (3) using time-dependent and more realistic boundary conditions for the CMAQ simulations.     

Multimedia emissions inventory of polychlorinated biphenyls for the U.S. Great Lakes states

Polychlorinated biphenyls (PCBs) were banned in the United States in 1979, and since then a significant decline in their release to the environment has been observed. This decline has now reached a plateau. Several new regulatory programs have been put in place to further reduce PCB emissions/releases. However, our ability to measure the effectiveness of these regulatory/voluntary programs and to support regional fate/transport and source/receptor modeling efforts depend on reliable emission information. In this study, we attempt to improve the emission inventory for PCBs by compiling and analyzing the multimedia total PCB emission/release data reported for the U.S Great Lakes states for each year from 1990 to 2000. Although Toxic Release Inventory (TRI), National Emissions Inventory (NEI), Great Lakes Regional Air Toxic Emissions Inventory (GLRATEI), and Integrated Atmospheric Deposition Network (IADN) data formed the basis of estimating air emissions, we used the TRI, National Response Center (NRC), and PCB transformer inventory data to estimate PCB releases to land. We used the Permit Compliance System and NRC data to obtain estimates of PCB discharges to water systems in the Great Lakes states. The Remedial Action Plans for each area of concern were the primary source for estimating PCB loads of dredged sediments. On the basis of the NEI, IADN, and GLRATEI data, the total air emissions within the decade were approximately 126 t. The regionwide discharges to water systems and releases to land in the form of landfills and accidental spills in 1990-2000 were estimated as approximately 170 and 3225 t, respectively. We estimated that approximately 1.3 million t of PCB-contaminated sediment were removed or targeted for removal in five lakes of the U.S. portion of the Great Lakes basin. We stress that these estimates were based on reported amounts and the unreported PCB releases/emissions could result in significantly higher estimates.     

Trace gases and particulate matter emissions from wildfires and agricultural burning in Northeastern Mexico during the 2000 fire season

An inventory of air pollutants emitted from forest and agricultural fires in Northeastern Mexico for the period of January to August of 2000 is presented. The emissions estimates were calculated using an emissions factor methodology. The inventory accounts for the emission of carbon monoxide (CO), methane, nonmethane hydrocarbons, ammonia, nitrogen oxides, and particulate matter (PM). Particulate matter emissions include estimates for fine PM and coarse PM. A total of 2479 wildfires were identified in the domain for the period of interest, which represented approximately 810,000 acres burned and 621,130 short tons emitted (81% being CO). The main source of information used to locate and estimate the extent of the fires came from satellite imagery. A geographic information system was used to determine the type of vegetation burned by each fire. More than 54% of the total area burned during the period of study was land on the State of Tamaulipas. However, >58% of the estimated emissions came from the State of Coahuila. This was because of the mix of vegetation types burned in each state. With respect to the temporal distribution, 76.9% of the fires occurred during the months of April and May consuming almost 78% of the total area burned during the period of study. Analysis of wind forward trajectories of air masses passing through the burned areas and 850-mb wind reanalyses indicate possible transboundary transport of the emissions from Mexico to the United States during the occurrence of the major wildfires identified.     

Modeling analyses of the effects of changes in nitrogen oxides emissions from the electric power sector on ozone levels in the eastern United States

In this paper, we examine the changes in ambient ozone concentrations simulated by the Community Multiscale Air Quality (CMAQ) model for summer 2002 under three different nitrogen oxides (NOx) emission scenarios. Two emission scenarios represent best estimates of 2002 and 2004 emissions; they allow assessment of the impact of the NOx emissions reductions imposed on the utility sector by the NOx State Implementation Plan (SIP) Call. The third scenario represents a hypothetical rendering of what NOx emissions would have been in 2002 if no emission controls had been imposed on the utility sector. Examination of the modeled median and 95th percentile daily maximum 8-hr average ozone concentrations reveals that median ozone levels estimated for the 2004 emission scenario were less than those modeled for 2002 in the region most affected by the NOx SIP Call. Comparison of the "no-control" with the "2002" scenario revealed that ozone concentrations would have been much higher in much of the eastern United States if the utility sector had not implemented NOx emission controls; exceptions occurred in the immediate vicinity of major point sources where increased NO titration tends to lower ozone levels.     

Evaluation of air quality models for the simulation of a high ozone episode in the Houston metropolitan area

A high ozone event in the Houston–Galveston–Brazoria area was utilized to study the shortcomings of the current air quality models. To improve the baseline simulations with the Comprehensive Air quality Model with Extensions (CAMx) for developing the state implementation plan, the Texas Commission on Environmental Quality (TCEQ) imputed emissions of highly reactive volatile organic compounds (HRVOCs) by scaling the amount of fugitive emissions of olefins to co-emitted NO_x from selected point sources, effectively multiplying by 3–12 times over the regular inventory values. In this paper, CAMx and the Community Multiscale Air Quality (CMAQ) model were used to determine if the imputed HRVOC emissions were consistent with the observed atmospheric conditions. With the base emissions, CMAQ and CAMx both with the Carbon-Bond 4 (CB-4) mechanism simulated similar ozone concentrations. But with the imputed HRVOC emissions, CMAQ predicted lower ozone peaks than CAMx in the vicinity and downwind of the Ship Channel and other highly HRVOC-rich areas. Based on analyses of sensitivity simulations of CMAQ with different emission inputs and vertical diffusion algorithms in the model, we found that the modeled atmosphere lacked reactivity to produce the observed high ozone event. Although the imputed HRVOC emissions improved ozone prediction at the surface sites, but the ethylene concentrations were not consistent with the measurements at the super sites (La Porte and Clinton) and by NOAA aircraft. Several sensitivity tests designed to provide additional radicals into the system and other research results suggested that the lack of reactivity may need to be corrected by targeted, and probably of episodic, increase of HRVOC emissions, from the sources in the Houston Ship Channel. Additional investigation of the ozone production efficiency for different chemical mechanisms is necessary to pinpoint the emissions uncertainty issues.     

A socio-economic method for estimating future air pollutant emissions—Chicago case study

This paper presents the development of an econometric-emission model to formulate future anthropogenic emission inventories for different societal and climate change scenarios. Our approach is to formulate the emission projections for a given scenario into growth factors that can be used to project forward the 1999 National Emission Inventory (NEI99). The process involves (1) mapping NEI99 source classification code (SCC)-based emissions into the sector or standard industrial classification (SIC)-based representation used by the econometric model, (2) developing a sectoral emission intensity (EMI) defined as the sector emissions per unit of sector economic output and the mechanism to consider EMI variations over time, (3) using the resulting EMI with econometric models and future emission activities to project future emissions, (4) and then mapping the emissions back to the original NEI99 format. As a case study, we apply the model to project emissions in the Chicago metropolitan area. The results show that the model is a fast, flexible, yet reasonable tool to produce a wide range of emission scenarios that are specific to regions, and would prove valuable for future air quality and other impact studies.     

Emissions of gases and particles from biomass burning during the 20th century using satellite data and an historical reconstruction

A new dataset of emissions of trace gases and particles resulting from biomass burning has been developed for the historical and the recent period (1900–2005). The purpose of this work is to provide a consistent gridded emissions dataset of atmospheric chemical species from 1900 to 2005 for chemistry-climate simulations. The inventory is built in two steps. First, fire emissions are estimated for the recent period (1997–2005) using satellite products (GBA2000 burnt areas and ATSR fire hotspots); the temporal and spatial distribution of the CO₂ emissions for the 1997–2005 period is estimated through a calibration of ATSR fire hotspots. The historical inventory, covering the 1900–2000 period on a decadal basis, is derived from the historical reconstruction of burned areas from Mouillot and Field (2005). The historical emissions estimates are forced, for each main ecosystem, to agree with the recent inventory estimates, ensuring consistency between past and recent emissions.The methodology used for estimating the fire emissions is discussed, together with the time evolution of biomass burning emissions during the 20th century, first at the global scale and then for specific regions. The results are compared with the distributions provided by other inventories and results of inverse modeling studies.     

Development and application of a three-dimensional aerosol chemical transport model,PMCAMx

A three-dimensional chemical transport model (PMCAMx) is used to simulate PM mass and composition in the eastern United States for a July 2001 pollution episode. The performance of the model in this region is evaluated, taking advantage of the highly time and size-resolved PM and gas-phase data collected during the Pittsburgh Air Quality Study (PAQS). PMCAMx uses the framework of CAMx and detailed aerosol modules to simulate inorganic aerosol growth, aqueous-phase chemistry, secondary organic aerosol formation, nucleation, and coagulation. The model predictions are compared to hourly measurements of PM_2.5 mass and composition at Pittsburgh, as well as to measurements from the AIRS and IMPROVE networks. The performance of the model for the major PM_2.5 components (sulfate, ammonium, and organic carbon) is encouraging (fractional errors are in general smaller than 50%). Additional improvements are possible if the rainfall measurements are used instead of the meteorological model predictions. The modest errors in ammonium predictions and the lack of bias for the total (gas and particulate) ammonium suggest that the improved ammonia inventory used is reasonable. The significant errors in aerosol nitrate predictions are mainly due to difficulties in simulating the nighttime formation of nitric acid. The concentrations of elemental carbon (EC) in the urban areas are significantly overpredicted. This is a problem related to both the emission inventory but also the different EC measurement methods that have been used in the two measurement networks (AIRS and IMPROVE) and the actual development of the inventory. While the ability of the model to reproduce OC levels is encouraging, additional work is necessary to confirm that that this is due to the right reasons and not offsetting errors in the primary emissions and the secondary formation. The model performance against the semi-continuous measurements in Pittsburgh appears to be quite similar to its performance against daily average measurements in a wide range of stations across the Eastern US. This suggests that the skill of the model to reproduce the diurnal variability of PM_2.5 and its major components is as good as its ability to reproduce the daily average values and also the significant value of high temporal resolution measurements for model evaluation.     

Air pollutant source characterization using the revised regional haze tracking metric and a photochemical grid model and implications for regional haze planning

The 2017 revisions to the Regional Haze Rule clarify that visibility progress at Class I national parks and wilderness areas should be tracked on days with the highest anthropogenic contributions to haze (impairment). We compare the natural and anthropogenic contributions to haze in the western United States in 2011 estimated using the Environmental Protection Agency (EPA) recommended method and using model projections from the Comprehensive Air Quality Model with Extensions (CAMx) and the Particulate Source Apportionment Tool (PSAT). We do so because these two methods will be used by states to demonstrate visibility progress by 2028. If the two methods assume different natural and anthropogenic contributions, the projected benefits of reducing U.S. anthropogenic emissions will differ. The EPA method assumes that episodic elevated carbonaceous aerosols greater than an annual 95th percentile threshold are natural events. For western U.S. IMPROVE monitoring sites reviewed in this paper, CAMx-PSAT confirms these episodes are impacted by carbon from wildfire or prescribed fire events. The EPA method assumes that most of the ammonium sulfate is anthropogenic in origin. At most western sites CAMx-PSAT apportions more of the ammonium sulfate on the most impaired days to global boundary conditions and anthropogenic Canadian, Mexican, and offshore shipping emissions than to U.S. anthropogenic sources. For ammonium nitrate and coarse mass, CAMx-PSAT apportions greater contributions to U.S. anthropogenic sources than the EPA method assigns to total anthropogenic contributions. We conclude that for western IMPROVE sites, the EPA method is effective in selecting days that are likely to be impacted by anthropogenic emissions and that CAMx-PSAT is an effective approach to estimate U.S. source contributions. Improved inventories, particularly international and natural emissions, and further evaluation of global and regional model performance and PSAT attribution methods are recommended to increase confidence in modeled source characterization.

Implications: The western states intend to use the CAMx model to project visibility progress by 2028. Modeled visibility response to changes in U.S. anthropogenic emissions may be less than estimated using the EPA assumptions based on total U.S. and international anthropogenic contributions to visibility impairment. Additional model improvements are needed to better account for contributions to haze from natural and international emissions in current and future modeling years. These improvements will allow more direct comparison of model and EPA estimates of natural and anthropogenic contributions to haze and future visibility progress.     

The sensitivity of modeled ozone to the temporal distribution of point, area, and mobile source emissions in the eastern United States

Ozone remains one of the most recalcitrant air pollution problems in the US. Hourly emissions fields used in air quality models (AQMs) generally show less temporal variability than corresponding measurements from continuous emissions monitors (CEM) and field campaigns would imply. If emissions control scenarios to reduce emissions at peak ozone forming hours are to be assessed with AQMs, the effect of emissions' daily variability on modeled ozone must be understood. We analyzed the effects of altering all anthropogenic emissions' temporal distributions by source group on 2002 summer-long simulations of ozone using the Community Multiscale Air Quality Model (CMAQ) v4.5 and the Carbon Bond IV (CBIV) chemical mechanism with 12 km resolution. We find that when mobile source emissions were made constant over the course of a day, 8-h maximum ozone predictions changed by ±7 parts per billion by volume (ppbv) in many urban areas on days when ozone concentrations greater than 80 ppbv were simulated in the base case. Increasing the temporal variation of point sources resulted in ozone changes of +6 and −6 ppbv, but only for small areas near sources. Changing the daily cycle of mobile source emissions produces substantial changes in simulated ozone, especially in urban areas at night; results suggest that shifting the emissions of NO_x from day to night, for example in electric powered vehicles recharged at night, could have beneficial impacts on air quality.     

Air pollutant emissions associated with forest,grassland, and agricultural burning in Texas

Outdoor fires, such as wildfires and prescribed burns, can emit substantial amounts of particulate matter and other pollutants into the atmosphere. In Texas, an inventory of forest, grassland and agricultural burning activities revealed that fires consumed vegetation on 1.6 and 1.7 million acres of land, in 1996 and 1997, respectively. Emissions from the fires were estimated based on survey and field data on acres burned and land cover and literature data on fuel consumption and emission factors. Fire data were allocated spatially by county and temporally by month. While fire events can cause high transient air pollutant concentrations, for most criteria pollutants, the fire emissions were a relatively small fraction of the annual emission inventory for the State. For fine particulate matter, however, the annual emission estimates were 40,000 tons/yr, which is likely to represent a significant fraction of the State's emission inventory, especially in the counties where the emissions are concentrated.     

Lagrangian sampling of 3-D air quality model results for regional transport contributions to sulfate aerosol concentrations at Baltimore,MD, in summer 2004

We use ensemble-mean Lagrangian sampling of a 3-D Eulerian air quality model, CMAQ, together with ground-based ambient monitors data from several air monitoring networks and satellite (MODIS) observations to provide source apportionment and regional transport vs. local contributions to sulfate aerosol and PM_2.5 concentrations at Baltimore, MD, for summer 2004. The Lagrangian method provides estimates of the chemical and physical evolution of air arriving in the daytime boundary layer at Baltimore. Study results indicate a dominant role for regional transport contributions on those days when sulfate air pollution is highest in Baltimore, with a principal transport pathway from the Ohio River Valley (ORV) through southern Pennsylvania and Maryland, consistent with earlier studies. Thus, reductions in sulfur emissions from the ORV under the EPA's Clean Air Interstate Rule may be expected to improve particulate air quality in Baltimore during summer. The Lagrangian sampling of CMAQ offers an inexpensive and complimentary approach to traditional methods of source apportionment based on multivariate observational data analysis, and air quality model emissions separation. This study serves as a prototype for the method applied to Baltimore. EPA is establishing a system to allow air quality planners to readily produce and access equivalent results for locations of their choice.     

Comparison of regional and global land cover products and the implications for biogenic emission modeling

Accurate estimates of biogenic emissions are required for air quality models that support the development of air quality management plans and attainment demonstrations. Land cover characterization is an essential driving input for most biogenic emissions models. This work contrasted the global Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product against a regional land cover product developed for the Texas Commissions on Environmental Quality (TCEQ) over four climate regions in eastern Texas, where biogenic emissions comprise a large fraction of the total inventory of volatile organic compounds (VOCs) and land cover is highly diverse. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) was utilized to investigate the influences of land cover characterization on modeled isoprene and monoterpene emissions through changes in the standard emission potential and emission activity factor, both separately and simultaneously. In Central Texas, forest coverage was significantly lower in the MODIS land cover product relative to the TCEQ data, which resulted in substantially lower estimates of isoprene and monoterpene emissions by as much as 90%. Differences in predicted isoprene and monoterpene emissions associated with variability in land cover characterization were primarily caused by differences in the standard emission potential, which is dependent on plant functional type. Photochemical modeling was conducted to investigate the effects of differences in estimated biogenic emissions associated with land cover characterization on predicted ozone concentrations using the Comprehensive Air Quality Model with Extensions (CAMx). Mean differences in maximum daily average 8-hour (MDA8) ozone concentrations were 2 to 6 ppb with maximum differences exceeding 20 ppb. Continued focus should be on reducing uncertainties in the representation of land cover through field validation.

Implications: Uncertainties in the estimation of biogenic emissions associated with the characterization of land cover in global and regional data products were examined in eastern Texas. Misclassification between trees and low-growing vegetation in central Texas resulted in substantial differences in isoprene and monoterpene emission estimates and predicted ground-level ozone concentrations. Results from this study indicate the importance of land cover validation at regional scales.     

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.     

Evaluation of model simulated atmospheric constituents with observations in the factor projected space: CMAQ simulations of SEARCH measurements

Two-year CMAQ simulations of gases and aerosols over the southeast are evaluated using SEARCH observations for 2000 and 2001, both by direct comparison to observations and by projecting both datasets to the factor space using the Positive Matrix Factorization (PMF) model. Model performance for secondary species (sulfate, ozone) is generally better than for primary species (EC, CO). Nitrate concentrations are overestimated, mainly due to wintertime over-partitioning to the particulate phase. Projecting both observed and simulated constituents to the factor space using PMF, four common factors are resolved for each surface site (two urban sites and two rural sites). The resolved factors include (1) secondary sulfate, (2) secondary nitrate, (3) a fresh motor vehicle factor characterized by EC, OC, CO, NO and NO_y, and (4) a mixed factor characterized by EC, OC, and CO. Performance for the sulfate and nitrate factors follow that of the corresponding driving species, while the motor vehicle and “mixed” factors exhibit performance corresponding to that of primary species. Comparing observations and CMAQ simulations in the projected space allow for an evaluation of the co-variability between species, an indicator of source impacts. The fact that similar factors were resolved by PMF from both the observations and the CMAQ simulations suggests that temporal processes related to emissions from specific source categories, as well as the subsequent dispersion and reactivity, are well captured by the CMAQ model. The ability to identify additional factors can be enhanced by adding tracer species in CMAQ simulations.     

Impacts of prescribed fires and benefits from their reduction for air quality,health, and visibility in the Pacific Northwest of the United States

Using a WRF-SMOKE-CMAQ modeling framework, we investigate the impacts of smoke from prescribed fires on model performance, regional and loc al air quality, health impacts, and visibility in protected natural environments using three different prescribed fire emission scenarios: 100% fire, no fire, and 30% fire. The 30% fire case reflects a 70% reduction in fire activities due to harvesting of logging residues for use as a feedstock for a potential aviation biofuel supply chain. Overall model performance improves for several performance metrics when fire emissions are included, especially for organic carbon, irrespective of the model goals and criteria used. This effect on model performance is more pronounced for the rural and remote IMPROVE sites for organic carbon and total PM_2.5. A reduction in prescribed fire emissions (30% fire case) results in significant improvement in air quality in areas in western Oregon, northern Idaho, and western Montana, where most prescribed fires occur. Prescribed burning contributes to visibility impairment, and a relatively large portion of protected class I areas will benefit from a reduced emission scenario. For the haziest 20% days, prescribed burning is an important source of visibility impairment, and approximately 50% of IMPROVE sites in the model domain show a significant improvement in visibility for the reduced fire case. Using BenMAP, a health impact assessment tool, we show that several hundred additional deaths, several thousand upper and lower respiratory symptom cases, several hundred bronchitis cases, and more than 35,000 workday losses can be attributed to prescribed fires, and these health impacts decrease by 25–30% when a 30% fire emission scenario is considered.

Implications: This study assesses the potential regional and local air quality, public health, and visibility impacts from prescribed burning activities, as well as benefits that can be achieved by a potential reduction in emissions for a scenario where biomass is harvested for conversion to biofuel. As prescribed burning activities become more frequent, they can be more detrimental for air quality and health. Forest residue-based biofuel industry can be source of cleaner fuel with co-benefits of improved air quality, reduction in health impacts, and improved visibility.     

Estimating historical anthropogenic global sulfur emission patterns for the period 1850–1990

It is important to establish a reliable regional emission inventory of sulfur as a function of time when assessing the possible effects of global change and acid rain. This study developed a database of annual estimates of national sulfur emissions from 1850 to 1990. A common methodology was applied across all years and countries allowing for global totals to be produced by adding estimates from all countries. The consistent approach facilitates the modification of the database and the observation of changes at national, regional, or global levels. The emission estimates were based on net production (i.e., production plus imports minus exports), sulfur content, and sulfur retention for each country's production activities. Because the emission estimates were based on the above considerations, our database offers an opportunity to independently compare our results with those estimates based on individual country estimates. Fine temporal resolution clearly shows emission changes associated with specific historical events (e.g., wars, depressions, etc.) on a regional, national, or global basis. The spatial pattern of emissions shows that the US, the USSR, and China were the main sulfur emitters (i.e., approximately 50% of the total) in the world in 1990. The USSR and the US appear to have stabilized their sulfur emissions over the past 20 yr, and the recent increases in global sulfur emissions are linked to the rapid increases in emissions from China. Sulfur emissions have been reduced in some cases by switching from high- to low-sulfur coals. Flue gas desulfurization (FGD) has apparently made important contributions to emission reductions in only a few countries, such as Germany.