A land use database and examples of biogenic isoprene emission estimates for the state of Texas, USA

Using data from a variety of sources, land use and vegetation in Texas were mapped with a spatial resolution of approximately 1 km. Over 600 classifications were used to characterize the land use and land cover throughout the state and field surveys were performed to assign leaf biomass densities, by species, to the land cover classifications. The total leaf biomass densities associated with these land use classifications ranged from 0 to 556 g/m², with the highest assigned total and oak leaf biomass densities located in central and eastern Texas. The land cover data were used as input to a biogenic emissions model, GLOBEIS2. Estimates of biogenic emissions of isoprene based on GLOBEIS2 and the new land cover data showed significant differences when compared to biogenic isoprene emissions estimated using previous land cover data and emission estimation procedures. For example, for one typical domain in eastern Texas, total daily isoprene emissions increased by 38% with the new modeling tools. These results may ultimately affect the way in which ozone and other photochemical pollutants are modeled and evaluated in the state of Texas.     

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.     

Effects of temperature and land use on predictions of biogenic emissions in Eastern Texas,USA

Accurate estimates of biogenic volatile organic compound emissions are critical for air quality planning in areas such as Eastern Texas where biogenic emissions comprise a significant fraction of the total volatile organic compound inventory. Uncertainties in biogenic volatile organic chemical emission estimates associated with different land use databases, surface temperature databases, and temperature interpolation methods were quantified and compared. The sensitivity of isoprene emissions to land use classification was investigated by comparing predictions based on land use data recently compiled for Eastern Texas to those based on the Biogenic Emissions Landcover Database version 3.1 (BELD3). Previous studies have only made these comparisons with the previous BELD version 2 database. Isoprene emission increased throughout much of Eastern Texas because areas classified as agricultural or savannah in BELD3 were more accurately classified as Post Oak, Live Oak, mesquite, and juniper in the new database. These results indicate the need for land use studies in areas poorly characterized in the BELD3. The sensitivity of isoprene emission estimates to uncertainties in surface temperatures were investigated by comparing predictions based on two different temperature databases and three different interpolation techniques. Spatial interpolations of surface temperatures collected at available Automated Surface Observing System (ASOS) stations in Houston, Austin, and Dallas were similar to the spatial interpolations of surface temperatures obtained from the ETA Data Assimilation System (EDAS). As a result, substantial variations in isoprene emissions were not observed over the majority of the modeling domain; however, differences of 4 F over localized regions produced a 35% difference in isoprene emissions. Comparisons between the isoprene emissions of the three interpolation methods sometimes revealed large variations, with maximum temperature differences of 4 F resulting in 60% differences in isoprene emissions in areas with the highest isoprene emissions. It was noted that the ASOS stations were clustered in urban areas and not in areas with the highest biogenic emissions. More ambient temperature monitors need to be located in rural locations to provide robust estimates of biogenic emissions and facilitate validation of interpolated temperature fields.     

Future land use and land cover influences on regional biogenic emissions and air quality in the United States

A regional modeling system was applied with inputs from global climate and chemistry models to quantify the effects of global change on future biogenic emissions and their impacts on ozone and biogenic secondary organic aerosols (BSOA) in the US. Biogenic emissions in the future are influenced by projected changes in global and regional climates and by variations in future land use and land cover (LULC). The modeling system was applied for five summer months for the present-day case (1990–1999, Case 1) and three future cases covering 2045–2054. Individual future cases were: present-day LULC (Case 2); projected-future LULC (Case 3); and future LULC with designated regions of tree planting for carbon sequestration (Case 4). Results showed changing future meteorology with present-day LULC (Case 2) increased average isoprene and monoterpene emission rates by 26% and 20% due to higher temperature and solar insolation. However when LULC was changed together with climate (Case 3), predicted isoprene and monoterpene emissions decreased by 52% and 31%, respectively, due primarily to projected cropland expansion. The reduction was less, at 31% and 14% respectively, when future LULC changes were accompanied by regions of tree planting (Case 4). Despite the large decrease in biogenic emission, future average daily maximum 8-h (DM8H) ozone was found to increase between +8 ppbv and +10 ppbv due to high future anthropogenic emissions and global chemistry conditions. Among the future cases, changing LULC resulted in spatially varying future ozone differences of ?5 ppbv to +5 ppbv when compared with present-day case. Future BSOA changed directly with the estimated monoterpene emissions. BSOA increased by 8% with current LULC (Case 2) but decreased by 45%–28% due to future LULC changes. Overall, the results demonstrated that on a regional basis, changes in LULC can offset temperature driven increases in biogenic emissions, and, thus, LULC projection is an important factor to consider in the study of future regional air quality.     

Improved land cover and emission factors for modeling biogenic volatile organic compounds emissions from Hong Kong

This paper describes a study of local biogenic volatile organic compounds (BVOC) emissions from the Hong Kong Special Administrative Region (HKSAR). An improved land cover and emission factor database was developed to estimate Hong Kong emissions using MEGAN, a BVOC emission model developed by Guenther et al. (2006). Field surveys of plant species composition and laboratory measurements of emission factors were combined with other data to improve existing land cover and emission factor data. The BVOC emissions from Hong Kong were calculated for 12 consecutive years from 1995 to 2006. For the year 2006, the total annual BVOC emissions were determined to be 12,400 metric tons or 9.82 × 10⁹ g C (BVOC carbon). Isoprene emission accounts for 72%, monoterpene emissions account for 8%, and other VOCs emissions account for the remaining 20%. As expected, seasonal variation results in a higher emission in the summer and a lower emission in the winter, with emission predominantly in day time. A high emission of isoprene occurs for regions, such as Lowest Forest-NT North, dominated by broadleaf trees. The spatial variation of total BVOC is similar to the isoprene spatial variation due to its high contribution. The year to year variability in emissions due to weather was small over the twelve-year period (?1.4%, 2006 to 1995 trendline), but an increasing trend in the annual variation due to an increase in forest land cover can be observed (+7%, 2006 to 1995 trendline). The results of this study demonstrate the importance of accurate land cover inputs for biogenic emission models and indicate that land cover change should be considered for these models.     

Effects of land use data on dry deposition in a regional photochemical model for eastern Texas

Land use data are among the inputs used to determine dry deposition velocities for photochemical grid models such as the Comprehensive Air Quality Model with extensions (CAMx) that is currently used for attainment demonstrations and air quality planning by the state of Texas. The sensitivity of dry deposition and O3 mixing ratios to land use classification was investigated by comparing predictions based on default U.S. Geological Survey (USGS) land use data to predictions based on recently compiled land use data that were collected to improve biogenic emissions estimates. Dry deposition of O3 decreased throughout much of eastern Texas, especially in urban areas, with the new land use data. Predicted 1-hr averaged O3 mixing ratios with the new land use data were as much as 11 ppbv greater and 6 ppbv less than predictions based on USGS land use data during the late afternoon. In addition, the area with peak O3 mixing ratios in excess of 100 ppbv increased significantly in urban areas when deposition velocities were calculated based on the new land use data. Finally, more detailed data on land use within urban areas resulted in peak changes in O3 mixing ratios of approximately 2 ppbv. These results indicate the importance of establishing accurate, internally consistent land use data for photochemical modeling in urban areas in Texas. They also indicate the need for field validation of deposition rates in areas experiencing changing land use patterns, such as during urban reforestation programs or residential and commercial development.     

Effects of Land Use Data on Dry Deposition in a Regional Photochemical Model for Eastern Texas

ABSTRACT

Land use data are among the inputs used to determine dry deposition velocities for photochemical grid models such as the Comprehensive Air Quality Model with extensions (CAMx) that is currently used for attainment demonstrations and air quality planning by the state of Texas. The sensitivity of dry deposition and O₃ mixing ratios to land use classification was investigated by comparing predictions based on default U.S. Geological Survey (USGS) land use data to predictions based on recently compiled land use data that were collected to improve biogenic emissions estimates. Dry deposition of O₃ decreased throughout much of eastern Texas, especially in urban areas, with the new land use data. Predicted 1-hr averaged O₃ mixing ratios with the new land use data were as much as 11 ppbv greater and 6 ppbv less than predictions based on USGS land use data during the late afternoon. In addition, the area with peak O₃ mixing ratios in excess of 100 ppbv increased significantly in urban areas when deposition velocities were calculated based on the new land use data. Finally, more detailed data on land use within urban areas resulted in peak changes in O₃ mixing ratios of ~2 ppbv. These results indicate the importance of establishing accurate, internally consistent land use data for photochemical modeling in urban areas in Texas. They also indicate the need for field validation of deposition rates in areas experiencing changing land use patterns, such as during urban reforestation programs or residential and commercial development.     

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.     

An Estimate of Biogenic Emissions of Volatile Organic Compounds during Summertime in China (7 pp)

Background and Aim An accurate estimation of biogenic emissions of VOC (volatile organic compounds) is necessary for better understanding a series of current environmental problems such as summertime smong and global climate change. However, very limited studies have been reported on such emissions in China. The aim of this paper is to present an estimate of biogenic VOC emissions during summertime in China, and discuss its uncertainties and potential areas for further investigations. Materials and Methods This study was mainly based on field data and related research available so far in China and abroad, including distributions of land use and vegetations, biomass densities and emission potentials. VOC were grouped into isoprene, monoterpenes and other VOC (OVOC). Emission potentials of forests were determined for 22 genera or species, and then assigned to 33 forest ecosystems. The NCEP/NCAR reanalysis database was used as standard environmental conditions. A typical summertime of July 1999 was chosen for detailed calculations. Results and Discussion The biogenic VOC emissions in China in July were estimated to be 2.3×10¹²gC, with 42% as isoprene, 19% as monoterpenes and 39% as OVOC. About 77.3% of the emissions are generated-from forests and woodlands. The averaged emission intensity was 4.11 mgC m⁻² hr⁻¹ for forests and 1.12 mgC m⁻² hr⁻¹ for all types of vegetations in China during the summertime. The uncertainty in the results arose from both the data and the assumptions used in the extrapolations. Generally, uncertainty in the field measurements is relatively small. A large part of the uncertainty mainly comes from the taxonomic method to assign emission potentials to unmeasured species, while the ARGR method serves to estimate leaf biomass and the emission algorithms to describe light and temperature dependence. Conclusions This study describes a picture of the biogenic VOC emissions during summertime in China. Due to the uneven spatial and temporal distributions, biogenic VOC emissions may play an important role in the tropospheric chemistry during summertime. Recommendations and Perspectives Further investigations are needed to reduce uncertainties involved in the related factors such as emission potentials, leaf biomass, species distribution as well as the mechanisms of the emission activities. Besides ground measurements, attention should also be placed on other techniques such as remotesensing and dynamic modeling. These new approaches, combined with ground measurements as basic database for calibration and evaluation, can hopefully provide more comprehensive information in the research of this field. Submission Editor: Prof. Dr. Gerhard Lammel (lammel@recetox.muni.cz)     

Modeling speciated terpenoid emissions from the European boreal forest

We present the first estimates of speciated monoterpene emissions from the North European coniferous forests. Measured emission factors and emission profiles of boreal tree species (Picea abies, Pinus sylvestris, Betula pendula, Salix phylicifolia, Populus tremula, and Alnus incana) were used together with detailed satellite land cover information and meteorological data in an emission model based on the Guenther emission algorithms. The variation of the coniferous biomass within the boreal region (60°N to 70°N) was obtained from forest inventory data, and the seasonal variability of the deciduous biomass was taken into account through simple boreal climatology parameterisation. The annual biogenic emissions in the boreal zone are dominated by coniferous species, but in the summer months, the deciduous contribution to the monoterpene and isoprene emissions is considerable. Norway spruce (Picea abies) is the most important isoprene emitter in the north European boreal forests. The biogenic emission fluxes in the South boreal zone are approximately twice as high as fluxes in the North boreal zone. α- and β-pinene, carene, and cineole are the most abundant emitted terpenes, with a strong contribution of isoprene and linalool during the summer months.     

Temporal,spatial characteristics and uncertainty of biogenic VOC emissions in the Pearl River Delta region,China

Using the Global Biosphere Emissions and Interactions System model (GloBEIS), 3 × 3 km gridded and hourly biogenic volatile organic compound (BVOC) emissions in the Pearl River Delta (PRD) were estimated for the year 2006. The study used newly available land cover database, observed meteorological data, and recent measurements of emission rates for tree species in China. The results show that the total BVOC emission in the PRD region in 2006 was 296 kt (2.2 × 10¹¹ gC), of which isoprene contributes about 25% (73 kt, 6.4 × 10¹⁰ gC), monoterpenes about 34% (102 kt, 8.9 × 10¹⁰ gC), and other VOCs (OVOC) about 41% (121 kt, 6.8 × 10¹⁰ gC). BVOC emissions in the PRD region exhibit a marked seasonal pattern with the peak emission in July and the lowest emission in January, and are mainly distributed over the outlying areas of the PRD region, where the economy and land use are less developed. The uncertainties in BVOC emission estimates were quantified using Monte Carlo simulation; the results indicate high uncertainties in isoprene emission estimates, with a relative error of ?82 to +177%, ranging from 12.4 to 186.4 kt; ?41 to +58% uncertainty for monoterpenes emissions, ranging from 67.7 to 181.9 kt; and ?26 to +30% uncertainty in OVOC emissions, ranging from 88.8 to 156.2 kt on the 95% confidence intervals. The key uncertainty sources include emission factors and the model empirical coefficients α, C_T1, C_L, and E_opt for estimating isoprene emission, and emission factors and foliar density for estimating monoterpenes and OVOC emissions. This implies that determining these empirical coefficient values properly and conducting more field measurements of emission rates of tree species are key approaches for reducing uncertainties in BVOC emission estimates. Improving future BVOC emission inventory work in the PRD region requires giving priority to research on shrub land, coniferous forests, and irrigated cropland and pasture.     

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.     

Measurement and analysis of atmospheric concentrations of isoprene and its reaction products in central Texas

A field experiment was conducted in August 1998 to investigate the concentrations of isoprene and isoprene reaction products in the surface and mixed layers of the atmosphere in Central Texas. Measured near ground-level concentrations of isoprene ranged from 0.3 (lower limit of detection – LLD) to 10.2 ppbv in rural regions and from 0.3 to 6.0 ppbv in the Austin urban area. Rural ambient formaldehyde levels ranged from 0.4 ppbv (LLD) to 20.0 ppbv for 160 rural samples collected, while the observed range was smaller at Austin (0.4–3.4 ppbv) for a smaller set of samples (37 urban samples collected). Methacrolein levels did not vary as widely, with rural measurements from 0.1 ppbv (LLD) to 3.7 ppbv and urban concentrations varying between 0.2 and 5.7 ppbv. Isoprene flux measurements, calculated using a simple box model and measured mixed-layer isoprene concentrations, were in reasonable agreement with emission estimates based on local ground cover data. Ozone formation attributable to biogenic hydrocarbon oxidation was also calculated. The calculations indicated that if the ozone formation occurred at low VOC/NO_x ratios, up to 20 ppbv of ozone formed could be attributable to biogenic photooxidation. In contrast, if the biogenic hydrocarbon reaction products were formed under low NO_x conditions, ozone production attributable to biogenics oxidation would be as low as 1 ppbv. This variability in ozone formation potentials implies that biogenic emissions in rural areas will not lead to peak ozone levels in the absence of transport of NO_x from urban centers or large rural NO_x sources.     

Sensitivity of urban ozone formation to chlorine emission estimates

Recent evidence has demonstrated that chlorine radical chemistry can enhance tropospheric volatile organic compound oxidation and has the potential to enhance ozone formation in urban areas. In order to investigate the regional impacts of chlorine chemistry in southeastern Texas, preliminary estimates of atmospheric releases of atomic chlorine precursors from industrial point sources, cooling towers, water and wastewater treatment, swimming pools, tap water, reactions of chlorides in sea salt aerosols, and reactions of chlorinated organics were developed. To assess the potential implications of these estimated emissions on urban ozone formation, a series of photochemical modeling studies was conducted to examine the spatial and temporal sensitivity of ozone and a unique marker species for chlorine chemistry, 1-Chloro-3-methyl-3-butene-2-one (CMBO), to molecular chlorine emissions estimates. Based on current estimates of molecular chlorine emissions in southeastern Texas, chlorine chemistry has the potential to enhance ozone mixing ratios by up to 11–16 ppbv. Impacts varied temporally, with emissions from cooling towers primarily responsible for a morning enhancement in ozone mixing ratios and emissions from residential swimming pools for an afternoon enhancement. Maximum enhancement in CMBO mixing ratios ranged from 59 to 69 pptv.     

Intra- and inter-annual variability of VOC emissions from natural and semi-natural vegetation in Europe and neighbouring countries

Biogenic VOC emission estimates from the earth's surface are crucial input parameters in air quality models. Knowledge accumulated in the last years about BVOC source distributions and chemical compound species emission profiles in Europe as well as the demand of air quality modellers for a finer resolution in space and time of BVOC estimates have led to the set-up of new emission modelling systems. An updated fast BVOC emission modelling platform explicitly considering the seasonality of emission potentials and leaf temperature gradients in forest canopies by the semi-empirical emission module (seBVOC) will be proposed and used for estimating hourly values of chemical compound-specific emissions in Europe (33–68° north; 10° west to 40° east) in the years 1997, 2000, 2001, and 2003. Spatial resolution will be 10 km by 10 km. The database used contains latest land and forest distributions, updated foliar biomass densities, leaf area indices (LAI), and plant as well as chemical compound-specific emission potentials, if available. Meteorological input parameters for the respective years will be generated using the non-hydrostatic meteorological model MM5. Highest BVOC emissions occur in daytime hours around noon from the end of May to mid-August in the Mediterranean area and from the mid of June to the end of July in the boreal forests. Comparison of 3 BVOC model approaches will reveal that for July 2003, the European isoprene and monoterpene totals range from 1124 Gg to 1446 Gg and from 338 Gg to 1112 Gg, respectively. Small-scale deviations may be as high as ±0.6 Mg km^?2 for July 2003, reflecting the current uncertainty range for BVOC estimates. Key sources of errors in inventories are still insufficiently detailed land use data for some areas and lacking chemically speciated plant-specific emission potentials in particular in boreal, south-eastern, and northern African landscapes. The hourly emissions of isoprene, speciated terpenes, and oxyVOC have been made available by the NatAir database.     

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.     

Spatial surrogates for the disaggregation of CORINAIR emission inventories

CORINAIR atmospheric emission inventories are frequently used input data for air quality models with a domain situated in Europe. In CORINAIR emission inventories, sources are broken down over 11 major source categories. This paper presents spatial surrogates for the disaggregation of CORINAIR atmospheric emission inventories for input of air pollutants and particulate matter to grid or polygon based air quality model domains inside Europe. The basis for the disaggregation model was the CLC2000 land cover data to which statistical weights were added. Weights were population census data for residential emissions, employment statistics for agricultural and industrial area emissions, livestock statistics for ammonia emissions and annual aircraft movements for emissions realized by air transport. Additional road and off-road network information was used to disaggregate emissions realized by traffic. A comparison of top down produced emission estimates with spatially resolved national emission data for The Netherlands and the United Kingdom gave confidence in the present spatial surrogates as a tool for the top down production of atmospheric emission maps. Explained variance at a spatial resolution of 5 km was >70% for CO, NMVOC and NO_x, >60% for PM10 and almost 50% for SO₂.     

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.     

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.     

Fine particulate matter emissions inventories: comparisons of emissions estimates with observations from recent field programs

Emissions inventories of fine particulate matter (PM2.5) 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 PM2.5 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 PM2.5 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 PM2.s are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.