A European-wide inventory of soil NO emissions using the biogeochemical models DNDC/Forest-DNDC

Soils are a significant source for atmospheric NO. However, due to the limited number of measurements and in view of the high temporal and spatial variability of NO emissions, as originating from dependencies from a series of environmental constraints such as soil properties, meteorology or N fertilization, inventories of soil NO emissions are still highly uncertain. In this work, the agricultural DNDC model was modified and applied on site scale in order to evaluate its capability to simulate soil NO emissions. DNDC captured differences in the magnitude of NO emissions between sites, but was less successful when simulating observed day-by-day variations. However, major peak emission events, e.g. due to fertilizer application or following rainfall events, were mostly simulated. DNDC as well as its forest version Forest-DNDC were finally linked to a GIS to calculate NO emissions from agricultural and forest soils across Europe. Using the same databases for agricultural soils, we also compared our estimate with other commonly used methodologies (Skiba-EMEP/CORINAIR, Yienger and Levy, Stehfest and Bouwman). A canopy reduction factor was not applied in this study. Estimates for NO emissions for agricultural soils for EU15 states varied in a range of 48.9–189.8 kt NO-N for the year 2000 depending on the approach used (Yienger and Levy > DNDC > Stehfest and Bouwman > Skiba-EMEP/CORINAIR). For forests, using the model Forest-DNDC as the only approach, we calculated soil NO emissions to be 75.1 kt NO-N yr^?1. The results show that soils in EU15 states are significant sources of atmospheric NO, though the share of soil NO emissions on total NO_x emissions (incl. NO_x emissions by combustion processes) in EU15 was only 4–6%. Given that soil NO emissions are largely driven by the availability of inorganic nitrogen (fertilization) and temperature, emissions are larger during the vegetation period. Especially during early summer when fertilizer-induced NO emissions from agricultural soils are peaking, the contribution of soil emissions to total NO_x emissions may most likely be well above 10%.     

An estimation of the spatial and temporal distribution of biogenic non-methane hydrocarbon emissions in Greece

The present study presents the first detailed inventory for non-methane hydrocarbon emissions from vegetation over Greece. The emission inventory, based on a Geographic Information System (GIS), has a spatial resolution of 5×5 km² and a time resolution of 1 h. For the area under study, the calculated yearly monoterpene emissions are higher than the corresponding isoprene ones. In addition to the methodology presented here, the CORINAIR methodology was also applied for the calculation of emission rates. This resulted in orders of magnitude differences in the calculated emission rates. The CORINAIR methodology is judged to lead to unrealistically high values of biogenic NMHC emission rates. The temperature dependence of the CORINAIR correction factors seems to affect most the emissions, together with grazing land emission factors.     

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.     

Spatial surrogate for domestic combustion’s air emissions: A case study from Silesian Metropolis,Poland

The aim of this study is improving currently applied methodology for spatial disaggregation, as well as mapping air emission inventories by taking into account the auxiliary spatial data on population density. District heating infrastructure occurring in more populated areas changes distinctly the spatial distribution of estimated air emission; however, it does not change the initial estimate. That means the total, disaggregated value is constant. Considered sources of domestic combustion are located in the central part of the Silesian Metropolis, in the southern part of Poland. A large part of this area is strongly urbanized and supplied with heat (hot water) from the district heating system. Data on population density help to determine the area within which the dwellers use heat energy and hot water supplied by the heating infrastructure, apart from heating with small domestic boilers and stoves. This causes the domestic combustion’s emission impact within the distinguished area to be significantly lower in comparison to the official guidelines on air emission inventories. The important differences in spatial air emissions distributions calculated using a top-down approach are found for strongly urbanized areas supplied partly with heat and hot water from the district heating network. This fact should be taken into account when preparing detailed, high-resolution emission inventories for air regional and local quality modeling.

Implications: The spatial issues connected with elaboration of the high-resolution emission inventories are presented for the example of the populated area of the Silesian Metropolis (Poland). Spatial distribution of the population density is used to determine the area supplied with heat and hot water from the district heating system. It changes distinctly the spatial distribution of the air emission from small residential combustion sources.     

A revised estimate of copper emissions from road transport in UNECE-Europe and its impact on predicted copper concentrations

Comparisons of measured and model-predicted atmospheric copper concentrations show a severe underestimation of the observed concentrations by the models. This underestimation may be (partly) due to underestimated emissions of copper to air. Since the phase out of asbestos brake lining material, the composition of brake lining material has changed and may contain up to ∼15% copper. This makes brake wear from vehicles potentially an important source of atmospheric (particulate) copper concentrations. In this paper, we reassess the copper emissions due to exhaust emissions and brake wear from road transport. Overall, our reassessments result in an estimate of total copper emission to air in UNECE-Europe of 4.0–5.5 ktonnes yr⁻¹, which is substantially higher than the previous estimate of 2.8 ktonnes yr⁻¹. Copper concentrations over Europe are calculated with the LOTOS-EUROS model using the revised emission data as model input. The results show that the revised emission estimates are a major step towards gap closure of predicted versus observed copper concentrations in ambient air. Brake wear emissions may be responsible for 50–75% of the total copper emissions to air for most of Western Europe. The hypothesis that road transport is an important source of copper emissions is tested and confirmed by (1) reviewing available literature data of chemically speciated PM data from road tunnel studies and (2) the gradient observed in copper concentrations from ambient PM monitoring going from rural sites to street stations. The literature review and observational data suggest that the majority of the emitted PM10 brake wear particles is in the PM2.5–10 size range. The results of this study indicate that modification of brake lining composition is an important mitigation option to reduce copper exposure of the population in Western Europe.     

Modeling emissions for three-dimensional atmospheric chemistry transport models

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scales and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed, and new methods to improve the spatiotemporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions such as national totals on appropriate grids. The wide area of natural emissions is also summarized, and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example, by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date.

Implications: Emission data are probably the most important input for chemistry transport model (CTM) systems. They need to be provided in high spatial and temporal resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g., for ammonia emissions, provide grid cell–dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.     

The effect of variability in industrial emissions on ozone formation in Houston, Texas

Ambient observations have indicated that high concentrations of ozone observed in the Houston/Galveston area are associated with plumes of highly reactive hydrocarbons, mixed with NO_x, from industrial facilities. Ambient observations and industrial process data, such as mass flow rates for industrial flares, indicate that the VOCs associated with these industrial emissions can have significant temporal variability. To characterize the effect of this variability in emissions on ozone formation in Houston, data were collected on the temporal variability of industrial emissions or emission surrogates (e.g., mass flow rates to flares). The observed emissions variability was then used to construct regionwide emission inventories with variable industrial emissions, and the impacts of the variability on ozone formation were examined for two types of meteorological conditions, both of which lead to high ozone concentrations in Houston. The air quality simulations indicate that variability in industrial emissions has the potential to cause increases and decreases of 10–52 ppb (13–316%), or more, in ozone concentration. The largest of these differences are restricted to regions of 10–20 km², but the variability also has the potential to increase regionwide maxima in ozone concentrations by up to 12 ppb.     

Evaluation of the European population intake fractions for European and Finnish anthropogenic primary fine particulate matter emissions

The intake fraction (iF) has been defined as the integrated incremental intake of a pollutant released from a source category or region summed over all exposed individuals. In this study we evaluated the iFs in the population of Europe for emissions of anthropogenic primary fine particulate matter (PM_2.5) from sources in Europe, with a more detailed analysis of the iF from Finnish sources. Parameters for calculating the iFs include the emission strengths, the predicted atmospheric concentrations, European population data, and the average breathing rate per person. Emissions for the whole of Europe and Finland were based on the inventories of the European Monitoring and Evaluation Programme (EMEP) and the Finnish Regional Emission Scenario (FRES) model, respectively. The atmospheric dispersion of primary PM_2.5 was computed using the regional-scale dispersion model SILAM. The iFs from Finnish sources were also computed separately for six emission source categories. The iFs corresponding to the primary PM_2.5 emissions from the European countries for the whole population of Europe were generally highest for the densely populated Western European countries, second highest for the Eastern and Southern European countries, and lowest for the Northern European and Baltic countries. For the entire European population, the iF values varied from the lowest value of 0.31 per million for emissions from Cyprus, to the highest value of 4.42 per million for emissions from Belgium. These results depend on the regional distribution of the population and the prevailing long-term meteorological conditions. Regarding Finnish primary PM_2.5 emissions, the iF was highest for traffic emissions (0.68 per million) and lowest for major power plant emissions (0.50 per million). The results provide new information that can be used to find the most cost-efficient emission abatement strategies and policies.     

Evaluation of a simplified top-down model for the spatial assessment of hot traffic emissions in mid-sized cities

Traffic emission estimation in developing countries is a key-issue for air pollution management. In most cases, comprehensive bottom-up methodologies cannot be applied in mid-sized cities because of the resource cost related to their application. In this paper, a simplified emission estimation model (SEEM) is evaluated. The model is based on a top-down approach and gives annual global hot emission. Particular attention is paid to the quality of the input traffic data. The quality of results is assessed by application of the SEEM model in the Chilean Gran Concepción urban area and by comparison with a bottom-up approach that has been led for the year 2000. The SEEM model estimates emissions with an accuracy of about $20\%$ and is related to important resource savings. The results of the SEEM model are then distributed in space with a disaggregation approach and using GIS techniques. The relevancy of the disaggregation approach is evaluated among several possibilities through statistical methods. A spatial disaggregation using principal roads density gives the best results in terms of emissions repartition and gives a globally accurate image of the distribution of hot emissions in a mid-sized city.     

A methodology for the estimation of road transport air emissions in urban areas of Italy

This paper focuses on the top–down approach for estimating road transport emissions at a local level. A bottom–up approach is preferable where the data and information required by estimation methodologies are available at regional territorial level. In the absence of this regional data, emissions are adapted from national to smaller levels by means of proxy variables. This study highlights the importance of an improvement of the top–down methodology and identifies a corrective index to better characterise road transport emissions at a local level. A set of indicators related to transport activities is selected in order to identify homogeneous areas in the Italian territory. For each area, COPERT (Computer Programme to estimate Emissions from Road Traffic) methodology is applied to estimate the atmospheric emissions of different pollutants; the same methodology is used to calculate road transport emissions at a national level. The results, calculated according to vehicle category and driving mode, are compared with those deriving from a spatial disaggregation of national data by means of simple surrogate variables.     

Revised estimates of construction activity and emissions: Effects on ozone and elemental carbon concentrations in southern California

Emissions from diesel-powered construction equipment are an important source of nitrogen oxides (NO_x) and particulate matter (PM). A new emission inventory for construction equipment emissions is developed based on surveys of diesel fuel use; the revised inventory is compared to current emission inventories. California's OFFROAD model estimates are 4.5 and 3.1 times greater, for NO_x and PM respectively, than the fuel-based estimates developed here. The most relevant uncertainties are the overall amount of construction activity/diesel fuel use, exhaust emission factors for PM and NO_x, and the spatial allocation of emissions to county level and finer spatial scales. Construction permit data were used in this study to estimate spatial distributions of emissions; the resulting distribution is well correlated with population growth. An air quality model was used to assess the impacts of revised emission estimates. Increases of up to 15 ppb in predicted peak ozone concentrations were found in southern California. Elemental carbon and fine particle mass concentrations were in better agreement with observations using revised emission estimates, whereas negative bias in predictions of ambient NO_x concentrations increased.     

Identification of brake wear particles and derivation of a quantitative tracer for brake dust at a major road

Traffic-generated air pollutant emissions can be classified into exhaust and non-exhaust emissions. Increased attention is focussing on non-exhaust emissions as exhaust emissions are progressively limited by regulations. To characterise metal-rich emission from abrasion processes, size-segregated analysis of atmospheric aerosol particles sampled with micro-orifice uniform deposit impactors (MOUDI) in March 2007 in London was performed. The samples were collected at a roadside and a background site and were analysed for Al, Ba, Cu, Fe, Sb, Ti, V, Zn, Ca²⁺, K⁺, Mg²⁺, Na⁺, and NH₄⁺. Most components showed a clear roadside increment, which was evident as a higher mass concentration and a change in the size distribution. In particular, Fe, Cu, Ba, and Sb correlated highly, indicative of a common traffic-related source. Using complementary information on the fleet composition, vehicle number and average speed, the brake wear emission was calculated using the EMEP/CORINAIR emission database. The total PM₁₀ and barium emission of the traffic was determined by ratio to NO_x whose source strength was estimated from published emission factors. Barium was found to comprise 1.1% of brake wear (PM₁₀) particles from the traffic fleet as a whole, allowing its use as a quantitative tracer of brake wear emissions at other traffic-influenced sites.     

Methodologies for estimating disaggregated anthropogenic emissions--application to a coastal Mediterranean region of Spain

Regional estimates of both anthropogenic and biogenic emissions are important inputs for models of atmospheric chemistry. A disaggregated emissions inventory of all relevant pollutants for an area of 100 x 100 km2 centered in Burriana (Castellon, Spain) has been worked out. Time and spatial resolutions were hourly and 1 x 1 km2, respectively. Estimates were made for all relevant sources of anthropogenic emissions. The pollutants considered were SO2, NOx, NMVOCs (nonmethane volatile organic compounds), CH4, CO, CO2, N2O, and NH3. Thus, the emissions inventory includes up to 18 different NMVOCs. Emissions were computed for a typical sunny workday in June when strong photochemical activity could be expected. A "top-down" methodology was applied, taking as a starting point official annual and provincial estimates based on CORINAIR emission factors. This procedure is a very useful tool, particularly for those cases where a lack of sufficient local detailed information about the main emission-generating activities, such as road traffic, makes the use of a "bottom-up" approximation inadvisable. Moreover, updating these emission inventories is easier and they could be used to evaluate the impact of possible abatement strategies.     

Compilation of a database on the composition of anthropogenic VOC emissions for atmospheric modeling in Europe

To analyse and generate air pollution control strategies and policies, e.g. efficient abatement strategies or action plans that lead to a fulfilment of air quality aims, atmospheric dispersion models (CTMs) have to be used. These models include a chemical model, where the numerous volatile organic compounds (VOCs) species are lumped together in classes. On the other hand, emission inventories usually report only total non-methane VOC (NMVOC), but not a subdivision into these classes. Thus, VOC species profiles are needed that resolve total NMVOC emission data. The objective of this publication is to present the results of a compilation of VOC species profiles that dissolve total VOC into single-species profiles for all relevant anthropogenic emission source categories and the European situation. As in atmospheric dispersion models usually modules for generating biogenic emissions are directly included, only anthropogenic emissions are addressed. VOC species profiles for 87 emission source categories have been developed. The underlying data base can be used to generate the data for all chemical mechanisms. The species profiles have been generated using recent measurements and studies on VOC species resolution and thus represent the current state of knowledge in this area. The results can be used to create input data for atmospheric dispersion models in Europe.The profiles, especially those for solvent use, still show large uncertainties. There is still an enormous need for further measurements to achieve an improved species resolution. In addition, the solvent use directive and the DECOPAINT directive of the European Commission will result in a change of the composition of paints; more water-based and high-solid paints will be used; thus the species resolution will change drastically in the next years. Of course, the species resolution for combustion and production processes also requires further improvement.     

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.     

Spatiotemporal analysis of traffic emissions in over 5000 municipal districts in Brazil

Exposure to traffic emission is harmful to human health. Emission inventories are essential to public health policies aiming at protecting human health, especially in areas with incomplete or nonexistent air pollution monitoring networks. In Brazil, for example, only 1.7% of municipal districts have a monitoring network, and only a few studies have reported data on vehicle emission inventories. No studies have presented emission inventories by municipality. In this study, we predicted vehicular emissions for 5570 municipal districts in Brazil during the period 2001–2012. We used a top-down method to estimate emissions. Carbon dioxide (CO₂) is the pollutant with the highest emissions, with approximately 190 million tons per year during the period 2001–2012). For the other traffic-related pollutants, we predicted annual emissions of 1.5 million tons for carbon monoxide (CO), 1.2 million tons of nitrogen oxides (NO_x), 209,000 tons of nonmethane hydrocarbons (NMHC), 58,000 tons of particulate matter (PM), and 42,000 tons for methane (CH₄). From 2001 to 2012, CO, NMHC, and PM emissions decreased by 41, 33, and 47%, respectively, whereas those CH₄, NO_x, and CO₂ increased by 2, 4, and 84%, respectively. We estimated uncertainties in our study and found that NO_x was the pollutant with the lowest percentage difference, 8%, and NMHC with the highest one, 30%. For CO, CH₄, CO₂, and PM, the values were 22, 14, 21, and 20%, respectively. Finally, we found that during 2001 and 2012 emissions increased in the Northwest and Northeast. In contrast, pollutant emissions, except for CO₂, decreased in the Southeast, South, and part of Midwest. Our predictions can be critical to efforts developing cost-effective public policies tailored to individual municipal districts in Brazil.

Implications: Emission inventories may be an alternative approach to provide data for air quality forecasting in areas where air quality data are not available. This approach can be an effective tool in developing spatially resolved emission inventories.     

Air Emission Inventories in North America: A Critical Assessment

Abstract

Although emission inventories are the foundation of air quality management and have supported substantial improvements in North American air quality, they have a number of shortcomings that can potentially lead to ineffective air quality management strategies. Major reductions in the largest emissions sources have made accurate inventories of previously minor sources much more important to the understanding and improvement of local air quality. Changes in manufacturing processes, industry types, vehicle technologies, and metropolitan infrastructure are occurring at an increasingly rapid pace, emphasizing the importance of inventories that reflect current conditions. New technologies for measuring source emissions and ambient pollutant concentrations, both at the point of emissions and from remote platforms, are providing novel approaches to collecting data for inventory developers. Advances in information technologies are allowing data to be shared more quickly, more easily, and processed and compared in novel ways that can speed the development of emission inventories. Approaches to improving quantitative measures of inventory uncertainty allow air quality management decisions to take into account the uncertainties associated with emissions estimates, providing more accurate projections of how well alternative strategies may work. This paper discusses applications of these technologies and techniques to improve the accuracy, timeliness, and completeness of emission inventories across North America and outlines a series of eight recommendations aimed at inventory developers and air quality management decision-makers to improve emission inventories and enable them to support effective air quality management decisions for the foreseeable future.     

Quality considerations of European PM emission inventories

This paper reviews information on emission inventories of particulate matter (PM) in Europe. A large body of scientific literature is available to cover many different aspects. Studies focus on specific sources or source sectors (road transport as well as off-road machinery, domestic heating, industry, agriculture, and natural sources), among which especially road transport emissions are clearly best established. Emission inventories comprising all sources are available for specific European regions, often pointing out regional differences, but also for the entire continent. Still these inventories often are not able to satisfy the needs. Due to PM specific circumstances such as the large number of sources, very different release pathways and differences of the individual particles in terms of chemical composition or size, it is very difficult to appropriately handle measurement conditions to arrive at adequate emission factors, especially when emission points cannot be defined clearly. Information on fugitive emissions (caused by wind shear, material transfer processes or other mechanical forces from non-point sources) is sparse, except for road traffic emissions where recent data seems to converge. The problem of data gaps concerns activities in industry (quarries), agriculture, but also natural particles like sea salt and wind-blown dust. Comparing complete inventories to independent efforts in assessing emissions, e.g. atmospheric measurements combined with source apportionment, allows to better understand and quantify the reliability of inventory data. Methodological improvements and harmonization currently under way in Europe will focus efforts and allow for more reliable PM inventories in the near future.     

CAREAIR: A Computer Aided Modeling Toolbox to Generate and Analyze Emission Data in High Temporal and Spatial Resolution

ABSTRACT

For the evaluation of air quality improvement strategies, emission data in high temporal and spatial resolution is necessary, including all emission sources and all relevant pollutant species. Computer aided models are usually used to generate this emission data because it is not possible to obtain measurements from all sources, and, furthermore, a large amount of data has to be handled. For the development of emission modeling systems, a software tool called CAREAIR has been created. The intention of this paper is to introduce CAREAIR to the international community dealing with emission inventories and air quality improvement strategies.

CAREAIR is not just a single emission model but a flexible modeling toolbox. The database contains data and formulas for data manipulation, which is performed by using a set of flexible operators with different specifications. The emission calculation is carried out by combining several data manipulation operators. The CAREAIR modeling toolbox allows model implementation for the calculation of emissions from different pollutants in a high spatial and temporal resolution. The application of CAREAIR within various investigation projects in Germany, Europe, and Nigeria shows that CAREAIR is an appropriate instrument for the development of flexible emission models by meeting the various demands of these projects. The function and the data structures of this modeling toolbox are described and, towards the end of the paper, an example of an emission calculation with CAREAIR is given.     

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

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