Differentiation of nitrous oxide emission factors for agricultural soils

Nitrous oxide (N₂O) direct soil emissions from agriculture are often estimated using the default IPCC emission factor (EF) of 1%. However, a large variation in EFs exists due to differences in environment, crops and management. We developed an approach to determine N₂O EFs that depend on N-input sources and environmental factors. The starting point of the method was a monitoring study in which an EF of 1% was found. The conditions of this experiment were set as the reference from which the effects of 16 sources of N input, three soil types, two land-use types and annual precipitation on the N₂O EF were estimated. The derived EF inference scheme performed on average better than the default IPCC EF. The use of differentiated EFs, including different regional conditions, allows accounting for the effects of more mitigation measures and offers European countries a possibility to use a Tier 2 approach.     

Greenhouse gas emissions from the waste sector in Argentina in business-as-usual and mitigation scenarios

The objective of this work was the application of 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines for the estimation of methane and nitrous oxide emissions from the waste sector in Argentina as a preliminary exercise for greenhouse gas (GHG) inventory development and to compare with previous inventories based on 1996 IPCC Guidelines. Emissions projections to 2030 were evaluated under two scenarios—business as usual (BAU), and mitigation—and the calculations were done by using the ad hoc developed IPCC software. According to local activity data, in the business-as-usual scenario, methane emissions from solid waste disposal will increase by 73% by 2030 with respect to the emissions of year 2000. In the mitigation scenario, based on the recorded trend of methane captured in landfills, a decrease of 50% from the BAU scenario should be achieved by 2030. In the BAU scenario, GHG emissions from domestic wastewater will increase 63% from 2000 to 2030. Methane emissions from industrial wastewater, calculated from activity data of dairy, swine, slaughterhouse, citric, sugar, and wine sectors, will increase by 58% from 2000 to 2030 while methane emissions from domestic will increase 74% in the same period. Results show that GHG emissions calculated from 2006 IPCC Guidelines resulted in lower levels than those reported in previous national inventories for solid waste disposal and domestic wastewater categories, while levels were 18% higher for industrial wastewater.

Implications: The implementation of the 2006 IPCC Guidelines for National Greenhouse Inventories is now considering by the UNFCCC for non-Annex I countries in order to enhance the compilation of inventories based on comparable good practice methods. This work constitutes the first GHG emissions estimation from the waste sector of Argentina applying the 2006 IPCC Guidelines and the ad doc developed software. It will contribute to identifying the main differences between the models applied in the estimation of methane emissions on the key categories of waste emission sources and to comparing results with previous inventories based on 1996 IPCC Guidelines.     

Developing spatially stratified N(2)O emission factors for Europe

We investigate the possibility to replace the – so-called – Tier 1 IPCC approach to estimate soil N₂O emissions with stratified emissions factors that take into account both N-input and the spatial variability of the environmental conditions within the countries of the European Union, using the DNDC-Europe model. Spatial variability in model simulations is high and corresponds to the variability reported in literature for field data. Our results indicate that (a) much of the observed variability in N₂O fluxes reflects the response of soils to external conditions, (b) it is likely that national inventories tend to overestimate the uncertainties in their estimated direct N₂O emissions from arable soils; (c) on average over Europe, the fertilizer-induced emissions (FIE) coincide with the IPCC factors, but they display large spatial variations. Therefore, at scales of individual countries or smaller, a stratified approach considering fertilizer type, soil characteristics and climatic parameters is preferable.     

Estimating and comparing greenhouse gas emissions with their uncertainties using different methods: A case study for an energy supply utility

Energy supply utilities release significant amounts of greenhouse gases (GHGs) into the atmosphere. It is essential to accurately estimate GHG emissions with their uncertainties, for reducing GHG emissions and mitigating climate change. GHG emissions can be calculated by an activity-based method (i.e., fuel consumption) and continuous emission measurement (CEM). In this study, GHG emissions such as CO₂, CH₄, and N₂O are estimated for a heat generation utility, which uses bituminous coal as fuel, by applying both the activity-based method and CEM. CO₂ emissions by the activity-based method are 12–19% less than that by the CEM, while N₂O and CH₄ emissions by the activity-based method are two orders of magnitude and 60% less than those by the CEM, respectively. Comparing GHG emissions (as CO₂ equivalent) from both methods, total GHG emissions by the activity-based methods are 12–27% lower than that by the CEM, as CO₂ and N₂O emissions are lower than those by the CEM. Results from uncertainty estimation show that uncertainties in the GHG emissions by the activity-based methods range from 3.4% to about 20%, from 67% to 900%, and from about 70% to about 200% for CO₂, N₂O, and CH₄, respectively, while uncertainties in the GHG emissions by the CEM range from 4% to 4.5%. For the activity-based methods, an uncertainty in the Intergovernmental Panel on Climate Change (IPCC) default net calorific value (NCV) is the major uncertainty contributor to CO₂ emissions, while an uncertainty in the IPCC default emission factor is the major uncertainty contributor to CH₄ and N₂O emissions. For the CEM, an uncertainty in volumetric flow measurement, especially for the distribution of the volumetric flow rate in a stack, is the major uncertainty contributor to all GHG emissions, while uncertainties in concentration measurements contribute a little to uncertainties in the GHG emissions.

Implications:Energy supply utilities contribute a significant portion of the global greenhouse gas (GHG) emissions. It is important to accurately estimate GHG emissions with their uncertainties for reducing GHG emissions and mitigating climate change. GHG emissions can be estimated by an activity-based method and by continuous emission measurement (CEM), yet little study has been done to calculate GHG emissions with uncertainty analysis. This study estimates GHG emissions and their uncertainties, and also identifies major uncertainty contributors for each method.     

Ammonia abatement and its impact on emissions of nitrous oxide and methane in Europe—Part 1: method

Agriculture is an important source of NH₃, which contributes to acidification and eutrophication, as well as emissions of the greenhouse gases CH₄ and N₂O. Because of their common sources, emission reduction measures for one of these gases may affect emissions of others. These interrelations are often ignored in policy making. This study presents an analysis of the effects of measures to reduce NH₃ emissions on emissions of N₂O and CH₄ from agriculture in Europe. The analysis combines information from the NH₃ module of the Regional Air pollution INformation and Simulation (RAINS) model for Europe with the IPCC method for national greenhouse gas inventories. The IPCC method for estimating agricultural emissions of N₂O and CH₄ is adjusted in order to use it in combination with the RAINS database for the European agricultural sector. As an example, we applied the adjusted method to the agricultural sector in the Netherlands and found that application of several NH₃ abatement options may result in a substantial increase in N₂O emissions while the effect on CH₄ emissions is relatively small. In Part 2 of this paper we focus on the resulting emissions for all European countries for 1990 and 2010.     

Ammonia abatement and its impact on emissions of nitrous oxide and methane—Part 2: application for Europe

Agriculture is an important source of NH₃, which contributes to acidification and eutrophication, as well as emissions of the greenhouse gases CH₄ and N₂O. Because of their common sources, emission reduction measures for one of these gases may affect emissions of others. These interrelations are often ignored in policy making. This study presents an analysis of the effects of measures to reduce NH₃ emissions on emissions of N₂O and CH₄ from agriculture in Europe. The analysis combines information from the NH₃ module of the Regional Air pollution INformation and Simulation (RAINS) model for Europe with the IPCC method for national greenhouse gas inventories. The IPCC method for estimating agricultural emissions of N₂O and CH₄ is adjusted in order to use it in combination with the RAINS database for the European agricultural sector. As an example, we applied the adjusted method to the agricultural sector in the Netherlands and found that application of several NH₃ abatement options may result in a substantial increase in N₂O emissions while the effect on CH₄ emissions is relatively small. In Part 2 of this paper we focus on the resulting emissions for all European countries for 1990 and 2010.     

Indirect nitrous oxide emission from a nitrogen saturated spruce forest and general accuracy of the IPCC methodology

The relevance of indirect N₂O emission is a controversial topic which is subject to much uncertainty. Only a small number of studies measure the indirect N₂O emission at the interface from soil to stream. In addition, the majority of studies undertaken only cover a short-term period (<1 year). Therefore, limited information is available regarding the influence of seasonal or event effects, nor is there much information as to whether indirect N₂O emissions are reflected by N₂O in soil solutions. The present study aimed at clarifying these two questions along with the general relevance of dissolved nitrous oxide. A wetness gradient involving soil solutions of different soil types and surface waters within an N-saturated forest catchment (3.2 ha) was monitored over a period of 1 year. N₂O concentrations in soil solutions (0.09–16.6 μg N l⁻¹) were affected by events such as dry–wet cycles but did not reflect to the actual, indirect N₂O emission at the soil-stream interface. It was assumed that N₂O emission was due to N transformation processes. The N₂O concentration at the spring was three times higher than the N₂O concentrations in the soil solutions. Nevertheless, indirect N₂O emission was still subordinate (<1%) to the direct emission of N₂O. The weekly amount of indirect N₂O emissions depended only on the stream flow rate (62% of the total annual amount). For this reason it was necessary to measure indirect N₂O emission at short intervals and at the interface between soil and stream over a longer time period. Our results and the results of the reviewed studies show that the default IPCC emission factor (EF5-g=1.5%) overestimates the indirect N₂O emission from ecosystems. The emission factor should therefore be lowered to about 0.1–0.3%. In addition, the results indicate that indirect N₂O emission is an insignificant pathway in the N cycle of most ecosystems. However, final judgement will depend on long-term studies.     

Development of a country-specific CO2 emission factor for domestic anthracite in Korea, 2007�C2009

Introduction

Korea has been making efforts to reduce greenhouse gas (GHG) emissions, including a voluntary commitment to the target of a 30% reduction, based on business-as-usual of the total GHG emission volume, by 2020; 2006 IPCC Guidelines provided default values, applying country-specific emission factors was recommended when estimating national greenhouse gas emissions.

Results and discussion

This study focused on anthracite produced in Korea in order to provide basic data for developing country-specific emission factor. This study has estimated CO₂ emission factors to use worksheet of which five steps consisted according to the fuel analysis method.

Conclusion

As a result, the average of net colorific value for 3 years (2007??2009) was 4,519 kcal/kg, and the CO₂ emission factor was calculated to be 111,446 kg/TJ, which is about 11.8% lower than the 2006 IPCC guidelines default value, and about 7.9% higher than the US EPA emission factor.     

A study on the evaluations of emission factors and uncertainty ranges for methane and nitrous oxide from combined-cycle power plant in Korea

In this research, in order to develop technology/country-specific emission factors of methane (CH₄) and nitrous oxide (N₂O), a total of 585 samples from eight gas-fired turbine combined cycle (GTCC) power plants were measured and analyzed. The research found that the emission factor for CH₄ stood at “0.82 kg/TJ”, which was an 18 % lower than the emission factor for liquefied natural gas (LNG) GTCC “1 kg/TJ” presented by Intergovernmental Panel on Climate Change (IPCC). The result was 8 % up when compared with the emission factor of Japan which stands at “0.75 kg/TJ”. The emission factor for N₂O was “0.65 kg/TJ”, which is significantly lower than “3 kg/TJ” of the emission factor for LNG GTCC presented by IPCC, but over six times higher than the default N₂O emission factor of LNG. The evaluation of uncertainty was conducted based on the estimated non-CO₂ emission factors, and the ranges of uncertainty for CH₄ and N₂O were between ?12.96 and +13.89 %, and ?11.43 and +12.86 %, respectively, which is significantly lower than uncertainties presented by IPCC. These differences proved that non-CO₂ emissions can change depending on combustion technologies; therefore, it is vital to establish country/technology-specific emission factors.     

Preliminary investigation of greenhouse gas emissions from the environmental sector in Taiwan

The United Nations Framework Conventions on Climate Change (UNFCCC) asks their Parties to submit a National Inventory Report (NIR) for greenhouse gas (GHG) emissions on an annual basis. However, when many countries are quickly growing their economy, resulting in substantial GHG emissions, their inventory reporting systems either have not been established or been able to be linked to planning of mitigation measures at national administration levels. The present research was aimed to quantify the GHG emissions from an environmental sector in Taiwan and also to establish a linkage between the developed inventories and development of mitigation plans. The "environmental sector" consists of public service under jurisdiction of the Taiwan Environmental Protection Administration: landfilling, composting, waste transportation, wastewater treatment, night soil treatment, and solid waste incineration. The preliminary results were compared with that of the United States, Germany, Japan, United Kingdom, and Korea, considering the gaps in the scopes of the sectors. The GHG emissions from the Taiwanese environmental sector were mostly estimated by following the default methodology in the Intergovernmental Panel on Climate Change guideline, except that of night soil treatment and waste transportation that were modified or newly developed. The GHG emissions from the environmental sectors in 2004 were 10,225 kilotons of CO2 equivalent (kt CO2 Eq.). Landfilling (48.86%), solid waste incineration (27%), and wastewater treatment (21.5%) were the major contributors. Methane was the most significant GHG (70.6%), followed by carbon dioxide (27.8%) and nitrous oxide (1.6%). In summary, the GHG emissions estimated for the environmental sector in Taiwan provided reasonable preliminary results that were consistent and comparable with the existing authorized data. On the basis of the inventory results and the comparisons with the other countries, recommendations of mitigation plans were made, including wastewater and solid waste recycling, methane recovery for energy, and waste reduction/sorting.     

Estimating national landfill methane emissions: an application of the 2006 Intergovernmental Panel on Climate Change Waste Model in Panama

This paper estimates national methane emissions from solid waste disposal sites in Panama over the time period 1990-2020 using both the 2006 Intergovernmental Panel on Climate Change (IPCC) Waste Model spreadsheet and the default emissions estimate approach presented in the 1996 IPCC Good Practice Guidelines. The IPCC Waste Model has the ability to calculate emissions from a variety of solid waste disposal site types, taking into account country- or region-specific waste composition and climate information, and can be used with a limited amount of data. Countries with detailed data can also run the model with country-specific values. The paper discusses methane emissions from solid waste disposal; explains the differences between the two methodologies in terms of data needs, assumptions, and results; describes solid waste disposal circumstances in Panama; and presents the results of this analysis. It also demonstrates the Waste Model's ability to incorporate landfill gas recovery data and to make projections. The former default method methane emissions estimates are 25 Gg in 1994, and range from 23.1 Gg in 1990 to a projected 37.5 Gg in 2020. The Waste Model estimates are 26.7 Gg in 1994, ranging from 24.6 Gg in 1990 to 41.6 Gg in 2020. Emissions estimates for Panama produced by the new model were, on average, 8% higher than estimates produced by the former default methodology. The increased estimate can be attributed to the inclusion of all solid waste disposal in Panama (as opposed to only disposal in managed landfills), but the increase was offset somewhat by the different default factors and regional waste values between the 1996 and 2006 IPCC guidelines, and the use of the first-order decay model with a time delay for waste degradation in the IPCC Waste Model.     

Seasonal and Spatial Variations of Ammonia Emissions from an Open-Lot Dairy Operation

Abstract

There is a need for a robust and accurate technique to measure ammonia (NH₃) emissions from animal feeding operations (AFOs) to obtain emission inventories and to develop abatement strategies. Two consecutive seasonal studies were conducted to measure NH₃ emissions from an open-lot dairy in central Texas in July and December of 2005. Data including NH₃ concentrations were collected and NH₃ emission fluxes (EFls), emission rates (ERs), and emission factors (EFs) were calculated for the open-lot dairy. A protocol using flux chambers (FCs) was used to determine these NH₃ emissions from the open-lot dairy. NH₃ concentration measurements were made using chemiluminescence-based analyzers. The ground-level area sources (GLAS) including open lots (cows on earthen corrals), separated solids, primary and secondary lagoons, and milking parlors were sampled to estimate NH₃ emissions. The seasonal NH₃ EFs were 11.6 ± 7.1 kg-NH₃ yr^-1head^-1 for the summer and 6.2 ± 3.7 kg-NH₃ yr^-1head^-1 for the winter season. The estimated annual NH₃ EF was 9.4 ± 5.7 kg-NH₃ yr^-1head^-1 for this open-lot dairy. The estimated NH₃ EF for winter was nearly 47% lower than summer EF. Primary and secondary lagoons (～37) and open-lot corrals (～63%) in summer, and open-lot corrals (～95%) in winter were the highest contributors to NH₃ emissions for the open-lot dairy. These EF estimates using the FC protocol and real-time analyzer were lower than many previously reported EFs estimated based on nitrogen mass balance and nitrogen content in manure. The difference between the overall emissions from each season was due to ambient temperature variations and loading rates of manure on GLAS. There was spatial variation of NH₃ emission from the open-lot earthen corrals due to variable animal density within feeding and shaded and dry divisions of the open lot. This spatial variability was attributed to dispirit manure loading within these areas.     

Sub-region (district) and sector level SO2 and NOx emissions for India: assessment of inventories and mitigation flexibility

Sub-regional and sector level distribution of SO₂ and NO_x emissions inventories for India have been estimated for all the 466 Indian districts using base data for years 1990 and 1995. Although, national level emissions provide general guidelines for assessing mitigation alternatives, but significant regional and sectoral variability exist in Indian emissions. Districts reasonably capture this variability to a fine grid as 80% of these districts are smaller than 1°×1° resolution with 60% being smaller than even 1/2°×1/2°. Moreover, districts in India have well-established administrative and institutional mechanisms that would be useful for implementing and monitoring measures. District level emission estimates thus offer a finer regional scale inventory covering the combined interests of the scientific community and policy makers. The inventory assessment methodology adopted is similar to that prescribed by the Intergovernmental Panel on Climate Change (IPCC) for greenhouse gas (GHG) emissions. The sectoral decomposition at district level includes emissions from fossil fuel combustion, non-energy emissions from industrial activities and agriculture. Total SO₂ and NO_x emissions from India were 3542 and 2636 Gg, respectively (1990) and 4638 and 3462 Gg (1995) growing at annual rate of around 5.5%. The sectoral composition of SO₂ emissions indicates a predominance of electric power generation sector (46%). Power and transport sector emissions equally dominate NO_x emissions contributing nearly 30% each. However, majority of power plants are situated in predominantly rural districts while the latter are concentrated in large urban centers. Mitigation efforts for transport sector NO_x emissions would therefore be higher. The district level analysis indicates diverse spatial distribution with the top 5% emitting districts contributing 46.5 and 33.3% of total national SO₂ and NO_x emissions, respectively. This skewed emission pattern, with a few districts, sectors and point sources emitting significant SO₂ and NO_x, offers mitigation flexibility to policy makers for cost-effective mitigation.     

Seasonal and spatial variations of ammonia emissions from an open-lot dairy operation

There is a need for a robust and accurate technique to measure ammonia (NH3) emissions from animal feeding operations (AFOs) to obtain emission inventories and to develop abatement strategies. Two consecutive seasonal studies were conducted to measure NH3 emissions from an open-lot dairy in central Texas in July and December of 2005. Data including NH3 concentrations were collected and NH3 emission fluxes (EFls), emission rates (ERs), and emission factors (EFs) were calculated for the open-lot dairy. A protocol using flux chambers (FCs) was used to determine these NH3 emissions from the open-lot dairy. NH3 concentration measurements were made using chemiluminescence-based analyzers. The ground-level area sources (GLAS) including open lots (cows on earthen corrals), separated solids, primary and secondary lagoons, and milking parlors were sampled to estimate NH3 emissions. The seasonal NH3 EFs were 11.6 +/- 7.1 kg-NH3 yr(-1)head(-1) for the summer and 6.2 +/- 3.7 kg-NH3 yr(-1)head(-1) for the winter season. The estimated annual NH3 EF was 9.4 +/- 5.7 kg-NH3 yr(-1)head(-1) for this open-lot dairy. The estimated NH3 EF for winter was nearly 47% lower than summer EF. Primary and secondary lagoons (approximately 37) and open-lot corrals (approximately 63%) in summer, and open-lot corrals (approximately 95%) in winter were the highest contributors to NH3 emissions for the open-lot dairy. These EF estimates using the FC protocol and real-time analyzer were lower than many previously reported EFs estimated based on nitrogen mass balance and nitrogen content in manure. The difference between the overall emissions from each season was due to ambient temperature variations and loading rates of manure on GLAS. There was spatial variation of NH3 emission from the open-lot earthen corrals due to variable animal density within feeding and shaded and dry divisions of the open lot. This spatial variability was attributed to dispirit manure loading within these areas.     

Power models and average ship parameter effects on marine emissions inventories

Maritime greenhouse gas emissions are projected to increase significantly by 2050, highlighting the need for reliable inventories as a first step in analyzing ship emission control policies. The impact of ship power models on marine emissions inventories has garnered little attention, with most inventories employing simple, load-factor-based models to estimate ship power consumption. The availability of more expansive ship activity data provides the opportunity to investigate the inventory impacts of adopting complex power models. Furthermore, ship parameter fields can be sparsely populated in ship registries, making gap-filling techniques and averaging processes necessary. Therefore, it is important to understand of the impact of averaged ship parameters on ship power and emission estimations. This paper examines power estimation differences between results from two complex, resistance-based and two simple, load-factor-based power models on a baseline inventory with unique ship parameters. These models are additionally analyzed according to their sensitivities toward average ship parameters. Automated Identification System (AIS) data from a fleet of commercial marine vessels operating over a 6-month period off the coast of the southwestern United States form the basis of the analysis. To assess the inventory impacts of using averaged ship parameters, fleet-level carbon dioxide (CO₂) emissions are calculated using ship parameter data averaged across ship types and their subtype size classes. Each of the four ship power models are used to generate four CO₂ emissions inventories, and results are compared with baseline estimates for the same sample fleet where no averaged values were used. The results suggest that a change in power model has a relatively high impact on emission estimates. They also indicate relatively little sensitivity, by all power models, to the use of ship characteristics averaged by ship and subtype.

Implications: Commercial marine vessel emissions inventories were calculated using four different models for ship engine power. The calculations used 6 months of Automated Identification System (AIS) data from a sample of 248 vessels as input data. The results show that more detailed, resistance-based models tend to estimate a lower propulsive power, and thus lower emissions, for ships than traditional load-factor-based models. Additionally, it was observed that emission calculations using averaged values for physical ship parameters had a minimal impact on the resulting emissions inventories.     

Comparison of the MOVES2010a,MOBILE6.2, and EMFAC2007 mobile source emission models with on-road traffic tunnel and remote sensing measurements

The Desert Research Institute conducted an on-road mobile source emission study at a traffic tunnel in Van Nuys, California, in August 2010 to measure fleet-averaged, fuel-based emission factors. The study also included remote sensing device (RSD) measurements by the University of Denver of 13,000 vehicles near the tunnel. The tunnel and RSD fleet-averaged emission factors were compared in blind fashion with the corresponding modeled factors calculated by ENVIRON International Corporation using U.S. Environmental Protection Agency's (EPA's) MOVES2010a (Motor Vehicle Emissions Simulator) and MOBILE6.2 mobile source emission models, and California Air Resources Board's (CARB's) EMFAC2007 (EMission FACtors) emission model. With some exceptions, the fleet-averaged tunnel, RSD, and modeled carbon monoxide (CO) and oxide of nitrogen (NO_x) emission factors were in reasonable agreement (±25%). The nonmethane hydrocarbon (NMHC) emission factors (specifically the running evaporative emissions) predicted by MOVES were insensitive to ambient temperature as compared with the tunnel measurements and the MOBILE- and EMFAC-predicted emission factors, resulting in underestimation of the measured NMHC/NO_x ratios at higher ambient temperatures. Although predicted NMHC/NO_x ratios are in good agreement with the measured ratios during cooler sampling periods, the measured NMHC/NO_x ratios are 3.1, 1.7, and 1.4 times higher than those predicted by the MOVES, MOBILE, and EMFAC models, respectively, during high-temperature periods. Although the MOVES NO_x emission factors were generally higher than the measured factors, most differences were not significant considering the variations in the modeled factors using alternative vehicle operating cycles to represent the driving conditions in the tunnel. The three models predicted large differences in NO_x and particle emissions and in the relative contributions of diesel and gasoline vehicles to total NO_x and particulate carbon (TC) emissions in the tunnel.

Implications: Although advances have been made to mobile source emission models over the past two decades, the evidence that mobile source emissions of carbon monoxide and hydrocarbons in urban areas were underestimated by as much as a factor of 2–3 in past inventories underscores the need for on-going verification of emission inventories. Results suggest that there is an overall increase in motor vehicle NMHC emissions on hot days that is not fully accounted for by the emission models. Hot temperatures and concomitant higher ratios of NMHC emissions relative to NO_x both contribute to more rapid and efficient formation of ozone. Also, the ability of EPA's MOVES model to simulate varying vehicle operating modes places increased importance on the choice of operating modes to evaluate project-level emissions.     

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%.     

Uncertainties in current estimates of emissions of ammonia in the United Kingdom

Estimates of the emissions of ammonia have previously concentrated on animal husbandry sources from agricultural systems. Animal husbandry sources still constitute the major fraction of emissions of ammonia, but we have also considered the potential magnitude of other 'minor' sources, which may include coal combustion, waste incineration, road vehicles, sewage treatment plants, fertiliser manufacture and application, vegetation senescence and crop emissions, domestic pets, and human sources. Where possible, a provisional estimate of UK emissions from each of these sources is given. It is concluded that the potential magnitude of emissions from these 'minor' sources may make a significant contribution to the total emissions of ammonia to the atmosphere. On the basis of the available data, and the application of a range of emission factors to the UK situation, an additional annual emission potential lying in the range of approximately 80-140 ktonne year(-1) over and above that from animal husbandry has been calculated. The uncertainties in the emission estimates and instances in which a better resolution of sources is required are discussed. The emission factors used for animals in various inventories are reviewed and applied to the main UK agricultural animal populations. By using this approach, estimates of emissions from these sources range between 113 and 647 ktonne year(-1), which illustrates the uncertainties involved. It is suggested that our knowledge of the sources of ammonia, and their distribution, is far from complete.     

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.     

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.