Estimations of global no, emissions and their uncertainties

Pergamon

Atmospheric Environment Vol. 31, No. 12, pp. 1735 1749, 1997 PIh

S1352-2310(96)00327-5

~;" 1997 Published by Elsevier Science Ltd All rights reserved, Printed in Great Britain 1352 2310/97 $17.00 + 0.00

ESTIMATIONS OF GLOBAL NOx EMISSIONS A N D THEIR UNCERTAINTIES D. S. L E E , * I. K O H L E R , t E. G R O B L E R , $ F. R O H R E R , ~ R. S A U S E N , t L. G A L L A R D O - K L E N N E R , § J. G. J. O L I V I E R , ¶ F. J. D E N T E N E R t J a n d A. F. B O U W M A N ¶ *AEA Technology plc, National Environmental Technology Centre, Culham Laboratory, Oxfordshire OX14 3DB, U.K.; tDeutsche Forschungsanstalt ffir Luft- und Raumfahrt e.V., Institut fiJr Physik der Atmosph~ire, Oberpfaffenhofen, D-82234 Wel31ing, Germany; :~KFA-ICG3, Postfaeh 1913 D-52425, Germany; §Department of Meteorology, Stockholm University, S-t06 91, Sweden; ~National Institute of Public Health and the Environment (RIVM), PO Box 1, NL720 BA Bilthoven, The Netherlands; and IIInstitute for Marine and Atmospheric Research, Utrecht University, Princetonplein 5, NL-3584 CC Utrecht. The Netherlands (First received 7 February 1996 and in final form 11 October 1996. Published March 1997) Abstract--The AERONOX programme investigated the impact of NO~ emissions from aircraft on the atmosphere and included an extensive modelling programme. In the model comparisons undertaken within the AERONOX programme, a "standard" set of emissions of NOx from both aviation and non-aviation sources was required so that differences between the models could be examined. This paper describes the data sets used in the study. These were: fossil fuel combustion from stationary and mobile sources at Earth's surface (22TgNyr-t), tropical biomass burning (5TgNyr-t), soil microbial production of NO (4 Tg N yr - t), lightning (5 Tg N yr - 1) and the stratospheric decomposition of nitrous oxide (0.6 Tg N yr - 1). However, global emission inventories of trace gases are developing rapidly: this paper also presents some emission estimates updated since the AERONOX study and also attempts to quantify uncertainties. The lightning source was constructed using convective cloud-top height from a GCM and differential rates of NO production calculated for cloud-to-cloud, and cloud-to-ground strikes. A revised biomass inventory including deforestation, savanna burning, agricultural waste burning and biofuel combustion results in approximately 8 T g N y r - t . This estimate includes sources beyond the tropics. Both extrapolation of measurements of soil NO fluxes by biome type, and a further refinement of the AERONOX soils emission model resulted in an emission of approximately 7 Tg N yr- 1. Ammonia oxidation as a source of NOx is calculated to be 0.9 NTgyr -1 with a range of 0-1.6TgNyr -1, which shows that this is a relatively unimportant source of NO~ in the troposphere. Uncertainty estimates for all sources have been given and discussed. The global source term for NOx for all sources (including the revisions) is estimated to be 44 Tg N yr 1 with an uncertainty range of 23-81 Tg N yr- 1. A future scenario for fossil fuel combustion is given for 2025 resulting in an emission term of 46.5 TgN for this source, showing a pronounced shift in distribution to Asia and the Far-East. © 1997 Published by Elsevier Science Ltd. All rights reserved. Key word index: NOx, biomass burning, soils, lightning, troposphere, ammonia oxidation, fossil fuels, global emissions, inventories, modelling, AERONOX.

l. INTRODUCTION Emissions of N O and NO2 (collectively referred to as NOx) arise as a result of both man's activities and natural processes. On the global scale, the major sources of NOx are the combustion of fossil fuel, biomass burning, lightning and microbiological emissions from soils. Other sources include aircraft, input from the stratosphere and a m m o n i a oxidation (Logan, 1983). The rate of increase of the burden of NO:, in the atmosphere on the global scale over the past century is neither well understood nor quantified (IPCC, 1995), but there is clear evidence of increasing nitrate concentrations in Greenland ice core samples which

show some correspondence with estimated increases in NO~ emissions since preindustrial times (Neflel et al., 1985). Nitrate in aerosol has also shown a steady increase at a rural site in England since 1954 (Lee et al., 1996). It has been estimated that the global NOx emission from fossil fuel combustion has increased by an order of magnitude over this century (Dignon and Hameed, 1989). It is of vital importance to quantify emissions and tropospheric concentrations of NOx as, although it is not a greenhouse gas itself, it results in the generation of ozone (03) in the troposphere, which is an important greenhouse gas (IPCC, 1995), and is also of concern because of its effect upon human health, vegetation and materials (Tillon, 1989; Guderian et al.,

1735

1736

D.S. LEE et al.

1984; Chameides et al., 1994; Lee et al., 1996). Furthermore, concern has been expressed over the consequences of high rates of atmospheric deposition of N, globally (Galloway et al, 1994). It is believed that tropospheric 03 is increasing, particularly in the northern hemisphere (Wege and Vandersee, 1991; Logan, 1994), although some of the data are insufficient in quantity and quality to be unequivocal about the significance of trends in many regions, particularly the southern hemisphere. Concern over the contribution of aircraft emissions of NOx to 03 in the upper troposphere resulted in a large European research programme, AERONOX, which included studies of engine emissions, the physics and chemistry of aircraft wakes and global modelling (Schumann, 1995). Other major sources of NOx required quantification for input to the two- and three-dimensional models utilised in the AERONOX project, so that the effects of aircraft emissions on 03 could be determined. The global aircraft inventory developed for this programme is described elsewhere (ANCAT/EC, 1995; Gardner et al., 1997) and aircraft emissions are not considered further here. Several reviews of global NOx sources and their magnitudes have been undertaken in recent years and a selection are summarised in Table 1. The sources that were considered of most importance for model input, other than aircraft, were fossil fuel combustion at the earth's surface, biomass burning, soils, lightning and decomposition of nitrous oxide (N20) in the stratosphere. The stratospheric input of NOx remained individual to some models by parameterisation of their upper boundary conditions. In this paper, we describe the emissions data sets utilised in model comparisons in the AERONOX project, which were either compiled from other sources or specially created. Since the AERONOX study was undertaken, revised inventories for some source sectors have been published. Included in this assessment are new estimations of the source of NO~ from ammonia oxidation, an improved biomass inventory and a 2025 scenario for fossil-fuel NO~. The distribution of sources is given and the uncertainties discussed.

2. C O M P I L A T I O N O F T H E A E R O N O X INVENTORIES

2.l. Fossil fuels Emissions from surface fossil fuel combustion were taken from Dignon (1992) for a base year of 1980, estimated to be of the order of 22 TgN yr ~, which is in good agreement with other estimates which range between approximately 20 and 2 4 T g N y r 1 (Table 1). This emission estimate was made from data on fuel consumption and global population distributions according to the statistical methodology of Dignon and Hameed (1985). The individual countries emitting the largest amounts of NOx were found to be the U.S.A., the former U.S.S.R., China, Japan and the former West Germany (6.4, 4.4, 1.7, 0.8 and 0 . 6 6 T g N y r -1, respectively) and 95% of the global source is emitted in the northern hemisphere. 2.2. Biomass burniny Biomass burning represents a significant global source of many trace gases including CO, H2, N20, NO, CH3C1, COS, NH3 and VOCs (Crutzen et al., 1979; Levine, 1991). An inventory of tropical biomass burning has been compiled by I-Iao et al. (1990) which covers South America, Africa and the Far East, and results in an annual consumption of 4480Tg dry matter. A selection of emission factors for NOx from biomass burning was reviewed from the literature (Andreae, 1991; Akerdolu and Isichei, 1991; Radke et aL, 1991; Griffith et al., 1991; Lobert et al., 1991; Logan, 1983; Laursen et al., 1992) and an emission factor of ~ 4 g (NO2) kg 1 dry matter was chosen for the derivation of the global emissions of NOx from biomass burning in the AERONOX study. The resultant emission of 5.3 T g N yr- ~ compares favourably with other estimates of potential global emissions (see Table 1). 2.3. Microbial soil sources The production of NO from soils is the result of microbial denitrification and nitrification and chemodenitrification (Bouwman, 1990). However, the principal process by which NO emissions arise is

Table 1. A comparison of global sources and budgets of NOx (Tg N yr -t) Sources Fossil fuel Biomass burning Soils Lightning Stratospheric Aircraft Oxidation of NH 3 Others Range Specified total

Logan (1983) 21 (14-28) 12 (4-24) 8 (4-16) 8 (2-20) 0.5 . . 1-10 < 1 (oceanic) 25-99 50

IPCC Hough (1990) (1991) 21 2 5 20 2-8 1 .

21 8 5 5 .

Penner et al. (1991)

Miiller (1992)

22.4 5.8 10 3 1

21.9 5 4.7

.

IPCC IPCC (1992) (1995) 24 2.5 13 5-20 2-20 1 0.6

-

24 8 12 5 0.6 0.4 3

-

Olivier et al. (1995)

21.8 7.3 0.6 1.5 (industrial)

16-55

35.1 78.6 42

42.2

21.6

52.5

31.2

Estimations of global NOx emissions thought to be nitrification. Nitrous oxide and ammonia are also emitted from soil microbial processes (Granli and Bockman, 1994; Bouwman et al., 1997), but are not considered here. Many studies have been made of the emissions of nitric oxide from soil surfaces in various environments. Some of the flux measurements are summarised in Table 2. These data show clearly variable but significant fluxes from various soil and ecosystem types. In order to produce a global distribution of emission fluxes for the AERONOX study the methodology of Williams et al. (1992) was utilised. Using data on measured fluxes of NO from various soil and ecosystem types in the United States, Williams et al. (1992) developed an algorithm based upon a regression equation using emission fluxes, fertilisation rates and estimated soil temperatures. Using a global data set on ecosystem types (Matthews, 1983) and 5-day mean surface temperatures from the GISS global climate model (Hansen et al., 1983), this algorithm was utilised to produce monthly global estimates of emissions on a 1~ x 1° grid. This estimation procedure resulted in a global emission of approximately 12 Tg N yr-1, which is relatively high when compared to other estimates of this source (see Table 1). In areas where 03 is available, the interconversion between NO and NO2 is rapid and defined by the well-known photostationary state. The principal terrestrial sink for NO2 is thought to be stomatal (Hargreaves et al., 1992) although some cuticular deposition cannot be excluded. Thus, some of the emissions from soil sources may not escape the canopy, especially within forested areas. Thus, the emission of NO from this source was scaled down in order to compensate for deposition of NOz within the canopy, and conform approximately with the calculated emission of Miiller (1992) for this source. Some attempts have been made to estimate fluxes from forest canopies (Bakwin et al., 1990; Jacob and Wofsy, 1990) but a simple approach of a division of the global total by 3 was made for the data used in the AERONOX study. This represents a significant uncertainty, and therefore, weakness in the global emissions estimate from this source, especially in areas more remote from industrialisation, where soil and biomass sources are more important.

1737

The range estimated by Logan (1983) was 2-20 Tg N y r - 1, with a best estimate of 8 Tg N y r - 1. However, estimates of the order of 80-100 Tg N y r - 1 have also been suggested (Franzblau and Popp, 1989; Liaw et al., 1990). In this study, an assumed source strength of 5 Tg y r - 1 was used (see Discussion). Emissions of NO from lightning discharges occur throughout the troposphere wherever strong convective systems are found. Therefore, these emissions have to be treated as three-dimensional fields in space and time. In order to distribute spatially and temporally the source of lightning, cloud-top height statistics from an annual cycle integration of the ECHAM3 G C M model (Roeckner et al., 1992) were used. Twelve two-dimensional fields of monthly averaged flash rates, F = F(2, q~, t) (where 2 and q) denote the geographical longitude and latitude, respectively and t is the time) were obtained by application of the parameterisation of Price and Rind (1992). This parameterisation makes use of a semi-empirical relationship between convective cloud-top heights and lightning flash frequency, with different formulations for continental and marine thunderstorms. The flash rate F is the sum of Fc¢, the cloud-to-cloud flash rate, and F eg, the cloud-to-ground flash rate: F = F cc + Fcg.

(1)

The partitioning between F ¢c and Fcg is only poorly known. We adopted the observed ratio of Prentice and Mackerras (1977): F cc

= f(cp) = 4.16 + 2.16cos(qg).

(2)

The NOx production per discharge by cloud-to-cloud flashes is often assumed to be smaller than that of cloud-to-ground discharges (e.g. Penner et al., 1991; Dentener and Crutzen, 1994; Kasibhatla et al., 1993). In the following, ~ denotes the ratio of production rate of one cloud-to-cloud flash to the production rate of one cloud-to-ground flash, and is assumed to be 0.1 (Kowalczyk and Bauer, 1982). Then, the NO~ production E i by flashes (cloud-to-cloud and cloud-toground) is parameterised as E¢~(2, ~p, t) = ~bFC¢(2, ¢p, t) = c¢' ~ ~ f(cP)

F(~o, ¢p, t) ~3)

2.4. Lightning Lightning heats the air around the discharge to temperatures of approximately 30,000 K, forming NO when the column of air cools to 2000 K or so. This is followed by NO oxidation to NO2 by 03. Lightning is potentially an important source of NO~ in the free troposphere and remote marine areas, where no other tropospheric NO~ sources are known to exist. However, our understanding of the mechanisms of NO~ formation from electrical discharges and knowledge of the actual distribution of this natural source of NO~ is poor. Current estimates of the strength of the global lightning source of NO~ are very uncertain.

E¢'()o, qL t) = ~bFCg(2,q~, t) = q~~

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F(2, ~o, t) (4)

where ~b is a normalisation factor determined by 12

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(5)

G P = ~b 1 + c~f(~o) t=1~=-./2 o 1 + f ( 2 ) × F(2, q~, t))COS(q~)d2 dq~

(6)

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and G P denotes the global N production per year (5 Tg) by lightning. In the last step, the NOx produced is distributed vertically. Since little is known about the actual vertical distribution, and convective mixing is strong in regions with lightning, a simple approach was taken whereby the NOx produced at certain geographical locations and times was equally distributed between the surface and the monthly-mean deep convective cloud-top height as simulated by ECHAM3, i.e. the same amount per altitude unit enters the atmosphere within convective regions. The geographical distribution on a 5" x 5 grid of NOx production by lightning integrated over all altitudes for a year is shown in Fig. 1.

to give the zonal mean source for four seasons (January, April, July and October) according to Kasibhatla et al. (1991). The fluxes were then interpolated to obtain the annual cycle and in most models involved in AERONOX treated as boundary conditions at the uppermost levels. The calculated production rate of Kasibhatla et al. (1991) was 0.64 T g N yr-1. This is consistent with other recent estimates: e.g. 0 . 4 - 0 . 7 T g N y r -1 (Crutzen and Schmailzl, 1983), 0 . 7 T g N y r 1 (Legrand et al., 1989), 1 T g N y r 1 (Jackman et al., 1980), 0.5 Tg N y r - ~ (Levy et al., 1980) and 1 T g N y r -1 (Johnston et al., 1979).

3. DISCUSSION OF UNCERTAINTIES

3.1. General source strengths and their distributions 2.5. T h e stratosphere In the stratosphere, NO production is controlled largely by the availability of NzO and OI(D) through the reactions 03 + hv ~ 0 1 ( D ) + 0 2

(13)

N 2 0 + OI(D) --" 2NO.

(14)

The above reactions are thought to contribute approximately 90% of the NOy in the stratosphere above 20 km. However, galactic cosmic rays may also produce NO in the lower stratosphere and upper troposphere (Nicolet, 1975; Jackman et al., 1980). Downwards fluxes of NO r from the thermosphere and mesosphere from solar proton events and relativistic electron precipitation may also be important at latitudes greater than 50 ° (Jackman et al., 1980; Legrand et al., 1989). However, these sources are not well quantified, and thought to be much smaller than fluxes arising from the decomposition of N 2 0 in the stratosphere. In order to represent fluxes of NO from stratospheric decomposition of N20, production rates in the altitude range 2-20 hPa were vertically integrated

A direct comparison of the relative strengths of the various sources of NOx presents difficulties because of their spatial and altitudinal distributions. Table 3 presents an overview of the total emission rate of various sources, uncertainty ranges and the regions in which they dominate. Some sources are injected into the atmosphere at different altitudes which may have a disproportionate effect on 03 generation, for example, aircraft emissions (Johnson et al., 1992; K6hler et al., 1997; Sausen et al., 1995), The physical and chemical nature of the atmosphere also plays a role. For example, lightning occurs throughout the height of the troposphere (Kowalczyk and Bauer, 1982) into the stratosphere (Boeck et al., 1995), mostly in the tropics. Biomass burning in the tropics will result in faster distribution in the troposphere over other surface sources as vertical mixing is very strong in this region and the plumes have a thermal b u o y ancy of their own. Thus, although NOx from lightning, aircraft and stratospheric oxidation of N 2 0 represent much smaller emissions per se, they may exert powerful effects upon the oxidising capacity of the atmosphere because of their injection height and subsequent atmospheric lifetimes.

Table 3. Summary of "best" source estimates, uncertainties, and emission locations Source Fossil fuel combustion

Emission (Tg N yr- 1) 22

Uncertainty range (Tg N yr- 1) 13 31

Biomass burning Soil microbial production Lightning

7.9 7.0 5.0

3 15 4 -12 2 20

Stratospheric decomposition of N20 Ammonia oxidation Aircraft (ANCAT/EC data")

0.64 0.9 0.85

0.4 1 0.6

Total "Gardner et al. (1997).

44

23 81

Principal location of emissions Northern hemisphere mid Latitude continental surface Tropical continental surface Non-polar continental surface Tropical continent, Troposphere Stratosphere Tropical continental surface Northern hemisphere, Latitudes 30 60N, 10-10kin Altitude

Estimations of global NO~ emissions 3.2. The fossil fuels combustion estimate The uncertainties of this estimate (22 Tg N y r - ~) were briefly discussed by Dignon (1992) but no overall quantitative uncertainty was given. Dignon's (1992) inventory was for a base year of 1980 and significant changes in emissions may have occurred over the last 15 yr or so although IPCC (1995) give a best estimate of 24 Tg N y r - ~ as "typical of the last decade", which is in agreement with the calculations of Olivier et al. (1995) for a base year of 1990. Recently, a revised global inventory of NO~ has been developed (Benkovitz et al., 1997) for a base year of 1985, resulting in an emission of 21 T g N y r - L The approach taken was very similar to that of Dignon (1992), except that regional gridded emissions from Europe, North America, southeast Asia and South Africa, were utilised and converted to a l ° × l ° g r i d . Elsewhere in the world, Dignon's (1992) inventory method is used as the default. If data are compared from a selection of countries within the United Nations Economic Commission for Europe (UNECE) Convention on Long-Range Transboundary Air Pollution (LRTAP) for 1980 and 1990, both positive and negative changes are observed (Fig. 2), but large changes in emissions have occurred in countries such as the U.K., Italy and the European part of the Russian Federation. This demonstrates that significant changes may have occurred over the last decade and a more up-to-date estimation, i.e. 1990s, is required. The International Global Atmospheric Chemistry's (IGAC) Global Emissions Inventory Activity (GEIA) is providing a successful focus for this, and other such activities (Graedel et al., 1995). Logan (1983) speculated that the uncertainty for NO~ emissions from fossil fuel combustion may be of

3500 3000

1741

the order of + 30%, IPCC (1995) also giving the same uncertainty estimate. The proportion of NOx arising from North America and Europe is approximately 50% of the global fossil fuel emission (Benkovitz et al., 1996) and the uncertainty of the estimates for these regions has been estimated at + 2 5 % (Saeger et al., 1989; Tuovinen et al., 1994). The uncertainty in emissions from NO~ in the U.K. and The Netherlands has been estimated to be +_30% and +__20%,respectively (Gillham et al., 1994; Anonymous, 1994). In these two example countries, considerable effort is devoted to compiling information, such that an uncertainty estimate of + 2 5 % for Europe as a whole seems rather optimistic. The uncertainties inherent in a global estimate are almost certainly going to be greater and we speculate that other regions may have an uncertainty of the order of _ 50%, which would result in a global uncertainty range of 13-31 Tg N y r - ~, Thus, estimates of global emissions of approximately 2 0 - 2 5 T g N yr-1 are well within this range. The distribution of fossil fuel combustion, which represents the largest surface source of NO~, reflects generally the distribution of highly populated and industrialised regions. Thus, for large areas of the northern hemisphere and small areas of the southern hemisphere, fossil fuel combustion represents more than 80% of the sources of NO~ emissions. It is likely that China and southeast Asia will become a much more important source region in the future, if industrial development in this region is assumed to continue at the current rapid rate. Regulatory controls will tend to keep NO~ emissions level in Europe and North America. The Intergovernmental Panel on Climate Change (IPCC) has developed a number of emissions scenarios for direct and indirect greenhouse gases, referred to as IS92 a - f

~onnes NOx(as NO2)yr-1

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1742

D.S. LEE et al.

(Pepper et al., 1992). In these scenarios, global total NOx emissions from fossil fuel combustion are projected to increase over the period 1990-2025 from 25 to 3 3 - 3 9 T g y r -1 in 2025, i.e. an increase of between 30% (IS92c) and 100% (IS92e). Regionally, the calculated growth of NO~ emissions may be as high as 180% for the China region (IS92e) to 300% for the "Rest of the World" region (IS92a, b), the latter region being dominated by southeast Asia. Thus, this shows clearly that a substantial growth of emissions can be expected in the Asian region as a whole over the next two decades. Although these scenarios are not meant as forecasts, they provide a crude estimation of future emission levels both globally and regionally and show that Asia will become as important a source region as North America and Europe by 2025. Gridded emissions scenarios can be created by combining regional emission scenario results with gridded emission maps for anthropogenic sources, thus using the present regional distribution pattern on a grid, per source category, to distribute future emissions within each region. This has been accomplished recently by linking regional emission results of the climate model I M A G E 2.0 (Alcamo et al., 1994), which are defined for fossil fuel combustion per main sector and fuel type, with gridded NOx emission maps for 1990 for each of these sector and fuel-type combinations which were generated using the so-called EDGAR database (Olivier et al., 1995). Figure 3 shows one example of this integration of regional emission scenarios and data on current gridded emission patterns for a scenario, which resembles key assumptions made in the IPCC IS92 scenarios with respect to development of G D P and population. 3.3. T h e biomass c o m b u s t i o n estimate The uncertainties of this estimate are large. A single emission factor is a major weakness in the methodology as combustion conditions will control the overall emission of NOx and, indeed, the balance of NOx to other N gas emissions. Furthermore, the N emission also depends upon the N content of the fuel, which in savannas is of the order of 0.3-1.1% by weight (Andreae et al., 1996). However, such information on burning conditions is not available so that a single emission factor represents a best estimate. Dignon and Penner (1991) attempted to use different emission factors for different vegetation types based upon a review of measurements, but these measurements did not exhibit any clear differences between biomes. The inventory of biomass combustion from Hao et al. (1990) covers only tropical burning of savannah and deforestation and the estimate of emissions of 5.3 T g N yr-~ used in the AERONOX program may, therefore, represent an underestimate. The emission factor used in the AERONOX study may also represent an upper limit as a global average, based upon more recent data, which gives a best estimate factor of 3 g N O x k g -~ dm (Andreae et al., 1996).

In recognition of the under-representation of the spatial extent of the Hao et al. (1990) inventory, Bouwman et al. (1997) have constructed an inventory for deforestation, savanna burning, agricultural waste burning and biofuel burning for the calculation of NH3 emissions. This is probably the best-available biomass inventory available, as it uses more recent data on rates of deforestation (1981-1990) than presented by Hao et al. (1990) and Hao and Liu (1994), The global loss of biomass from this source amounts to 2117 Tg dm yr 1. Tropical savanna burning results in a consumption of 2671 Tg dm yr 1, which includes Australia. Agricultural waste burning includes both energy generation and burning of crop residues in the field and was estimated on the basis of FAO (1991). The global total of waste burnt was 706 Tg dm yr-1, distributed by arable land as defined by Olsen et al. (1983). For biofuels, the consumption data are based upon Hall et al. (1994) and distributed according to population density (Logan, personal communication), except for vegetal fuel use, for which a gridded map of arable land was used to distribute the country total emissions (Bouwman et al., 1995), since most vegetal fuel use occurs near the location where the agricultural residues are generated. Using a revised emission factor based upon the recommendation of Andreae et al. (1996), the annual N emissions from deforestation, savanna burning, agricultural waste burning and biofuel combustion are: 1.9, 2.4, 0.7, and 2.9 Tg, respectively. The annual emission of 7.9 Tg N is approximately 50% greater than that used in the AERONOX study, and as mentioned, extends beyond the tropics (see Fig. 4). If we use the emissions of NOx (N) calculated above, some estimates of uncertainty can be made from uncertainties in the mass combusted. Hao et al. (1990) gave an overall uncertainty in their inventory ofbiomass combustion of +_50%. In order to account for uncertainties in the emission factor, that previously used (3.9 g NO 2 k g - i dm), is assumed to be an upper limit, and the factor given by Logan (1983) of 2 g NO2 k g - 1 dm assumed to be a lower limit. If it is assumed that the uncertainties in the above biomass inventory are at least the same as those of Hao et al. (1990), then an upper estimate for the total biomass combustion source term is 15 T g N y r -1 from NOx, and the lower is 2.6 Tg N yr 1. However, with respect to the assumed range of uncertainties in the emission factor, a factor of 3.9 gNO2 k g - 1 dm represented the overall average of many North American fires (Nance et al., 1993). This large range of uncertainty requires resolution and a suitable refinement would require a much more detailed knowledge of the N/C ratios of the biomass combusted and respective emission factors. 3.4. T h e soils emission estimate Soils may be a significant source of NO~ globally, but there is much uncertainty attached to the AERONOX estimate for a number of reasons. The

Estimations of global NO~ emissions procedure by which the fluxes were derived was from an algorithm which represented a variety of soil types found in the United States, and may not be applicable to the wider variety of soils and conditions found elsewhere in the world, although the approach has been utilised elsewhere (Miiller, 1992; Yienger and Levy, 1995; Stohl et al., 1996). Furthermore, the assumption of a global scaling factor of ×0.33 to compensate for in-canopy deposition is crude and was performed in order to conform approximately with M filler's (1992) estimation of NO emissions from soil. In order to check this estimation, a selection of flux data derived from field measurements (Table 2) were reviewed and emission factors estimated. These were multiplied by areas of a simple land classification system given by Matthews (1983) and the results presented in Table 4. The global total of approximately 11 T g N y r -1 may be compared with the total ( 1 2 T g N y r -1) derived from the application of the methodology of Williams et al. (1992). Such agreement should be regarded with caution, as whilst the increased availability of measurements facilitates such an extrapolation, an earlier extrapolation on the same basis resulted in a global estimate of 20 T g N y r - i (Davidson, 199l). Davidson (1991) urged caution in interpreting the global total, pointing out that the global estimate was heavily biased by two measurements with large flux rates. Alternative methods for global extrapolation have been utilised using modelling approaches. Yienger and Levy (1995), using a similar approach of applying the Williams et al. (1992) algorithm, modelled global soil emissions of NO including a scheme to simulate pulsing of emissions after rainfall (Williams et al., 1987; Williams and Fehsenfeld, 1991), nitrogen fertiliser stimulation of emissions (Shepherd et al., 1991) and a canopy reduction factor to account for the amount of NO transformed to NO2 which is subsequently deposited within the canopy. The global annual emission, with no effect of in-canopy deposition, was estimated to be 10.2 TgN. Once in-canopy

1743

deposition was accounted for, the annual emission was reduced to 5.5 TgN. More recently, Potter et al. (1996) estimated global emissions of NO to be of the order of 10 T g N yr- 1, based upon a model of N mineralisation rates and soil inundation. This estimate did not account for in-canopy deposition. It would seem that estimations of the global source term for soil NO emissions are becoming constrained to approximately 10 Tg N yr-1, or less, and that the earlier larger estimates of 20 Tg N yr- 1 (see Table 11 are unlikely. As an alternative to the application of a single canopy reduction factor of 66%, emissions were calculated by summarising flux measurements and relating them to biome areas and utilising "canopy reduction factors" (CRFs) to account for in canopy deposition. The CRFs are not well physically based. The CRF for tropical rain-forest was taken from Jacob and Wofsy (1990). Ventilation rates of tropical forest canopies are not well known, but Trumbore et al. (1990) estimated the daytime residence time of radon-222 to be of the order of < 1 h in a 40 m high canopy. Given that a tropical rain-forest canopy has a high leaf area index, it is unsurprising that little NO from the forest floor escapes the canopy (Jakob and Bakwin, 1991). Based upon this information, we rather subjectively assign broad CRFs of 0.5 for other woodland and 0.2 for grasslands, cultivated surfaces and tundra. However, Yienger and Levy (1995) were also cautious about their more mathematically-based model of in-canopy deposition. The global inventory of soil NO of Potter et al. (1996) and the European inventory of Stohl et al. (1996) do not attempt to account for in-canopy deposition. This is a subject which requires far more work. The total emission of NO from soil based upon the "extrapolation" method, accounting for in-canopy deposition results in a global emission of approximately 7 T g N y r - 1 (Table 4). This extrapolation does not compare badly with Yienger and Levy's (1995) estimation of 5 . 5 T g N y r -1 from their model. Using the

Table 4. Estimations of biome area and emissions of NO from soils, emissions scaled by canopy reduction factors and potential post-burning emissions

Biome~ Tropical rainforest Other forest Woodland Shrubland Grassland Tundra Cultivated Total (Tg N yr-1)

Area (I06 km2)

Emission factor (ngNm-2s -1 )

Emission (TgN yr -l )

Canopy reduction factor

Areaburntb (109m2)

Enhanced postburning emissionsc (TgN yr- 11

12.3 27.0 13.1 l 2.1 27.4 7.3 17.6

7 1 1 1 1 1 10

2.71 0.85 0.41 0.38 0.86 0.23 5.55

0.8 0.5 0.5 0.2 0.2 0.2 0.2

71 131 146 9 7012 38 2724

0.0234 0.006 0.007 0.0004 0.331 0.0018 1.288

10.99

6.9

"From Matthews (1983). bFrom Dignon and Penner (1991). ~This assumes an enhancement of 3 times the normal emission rate for half the year.

1.66

1744

D.S. LEE et al.

same CRFs as given in Table 4 rather than the uniform reduction, the original model of soil N O production used in the AERONOX study, based upon the Williams et al. (1992) equations, results in an emission of 6.5 Tg N y r - 1 (see Fig. 5). A further potential emission not accounted for from soils is enhanced emissions after biomass burning. Anderson et al. (1988) measured biogenic soil emissions of NO (and N20) enhanced by a factor of approximately three, under both wet and dry conditions, following a biomass burn and found that these fluxes persisted for at least 6 months. The cause of this was thought to be increased levels of exchangeable ammonium in the soil which were available for nitrification both at the time of the burn and after. However, results are quite variable. Using the area of various ecosystem types burnt annually (Dignon and Penner, 1991) in combination with the Anderson et al. (1988) observations results in an estimated emission of approximately 2 T g N y r 1. The calculated magnitude can only be considered speculative. The impact of burning on soil emissions is not well understood or quantified. It is therefore suggested that the estimate of 3.7 Tg N yr ~ represents a lower bound and an upper bound may be of the order of 11 Tg N y r - ~ and that the source term used in the AERONOX study was probably too small. The spatial distribution of this source requires more work. 3.5. T h e lightning emissions estimate The actual magnitude of lightning as a source of NO~ in the troposphere is difficult to estimate. The formulation of a model of the distribution in space and time of lightning requires many assumptions. The assumed amount of NOx generated by an individual stroke of lightning has a poor basis and has been mostly determined from a small number of field measurements and laboratory studies, the results of which are difficult to extrapolate to global totals with any certainty. In addition to the uncertainties in the geographical extent of lightning, there is the problem of estimating the relative frequencies of cloud-toground and cloud-to-cloud strikes and their NOx production rates. Cloud-to-cloud strikes occur high into the troposphere, and furthermore, the more recently studied stratospheric strikes whereby single strokes may extend 300 km from cloud tops into the stratosphere (Boeck et al., 1995), need to be considered. The relative NOx production strength of cloud-to-cloud strikes in this study was assumed to be 0.1, in accordance with Kowalczyk and Bauer (1982). We adopted an observed latitudinal variation of the ratio between the number of cloud-to-cloud and cloud-to-ground flashes according to Prentice and Mackerras (1977). Later work by Price and Rind (1993) and Mackerras and Darveniza (1994) have indicated a less pronounced variation of this ratio. This does not result in severe changes in the lightning source of NO~ at mid-latitudes where aircraft emis-

sions are important. A larger uncertainty is associated to the relative efficiency of cloud-to-cloud and cloudto-ground discharges in terms of NO~ production per discharge. Gallardo and Cooray (1996) have argued that cloud-to-cloud discharges may dissipate as much energy as cloud-to-ground discharges, and therefore may generate similar quantities of NOx. Thus, lightning represents potentially an important natural source of NOx in the upper troposphere in addition to aircraft emissions. The geographical distribution of lightning events can be quantified from satellite observations (e.g. Goodman and Christian, 1993). Some of the earlier estimates of global lightning emissions indicated large magnitudes and ranges of between 30 and 1 0 0 T g N y r -~ has been given (Chameides et al., 1977; Chameides, 1979). Based upon field observations of NO~ production during storms, Franzblau and Popp (1989) suggested 100 T g N y r - 1 as an order of magnitude estimate. Liaw et al. (1990) more recently reviewed and standardised all the available estimates of field and laboratory measurements and calculated emissions of between 9.1 and 211.9 Tg N y r - 2, with a best estimate of 81 T g N y r -1, pointing out that this was an order of magnitude larger than many estimates. If such a magnitude of NOx emissions from lightning is correct, then this represents the largest uncertainty in global NO~ emissions. Kumar et al. (1995) have estimated the global source strength to be 2 T g N yr-1 based upon satellite observations of lightning frequency and the conversion rates of Borucki and Chameides (1984). Lawrence et al. (1995) presented a review of the estimates of the global fixation of nitrogen by lightning and according to their estimate, the amount of NO produced by a lightning discharge ranges from 1 to 7 x 1025 molecules of NO per discharge. Much of the uncertainty involved in the estimate of the NO yield per discharge is due to the poor knowledge of energy dissipation in lightning flashes. Lawrence et al. (1995) also recommended that more data on flash frequency from observational systems were required. In this context, some uncertainty exists resulting from the spatial and temporal resolution of the observing systems. A validation and a parameterisation with help of surface lightning positions and tracking systems are required, as is currently done by several groups for different locations (e.g. Finke and Hauf, 1996). Evaluation of the source strength of lightning, particularly in remote areas where other sources are likely to make only small contributions to observed NO~ and NO r concentrations, are generally constrained by verification of global models against measurements. Using a 3D global model of the oxidised nitrogen cycle, Gallardo and Rodhe (1995) found that values of greater than 20 Tg N yr- ~ were difficult to reconcile with observed nitrate wet deposition data. In a similar modelling approach, but using measurements of NOx in the remote mid- and uppertroposphere to validate the model, Levy et al. (1996)

Estimations of global NO., emissions bracketed the annual global emission to be in the range of 2-6 Tg N yr-1. On the basis of these studies, a range of 2-20 Tg N yr-1 is proposed, and our prescribed emission term of 5 T g N y r - X and its associated range are not well-founded. The effectiveness of a such a modelling approach to validate the 91obal source-term, however, should not be overstated. Three-dimensional lightning inventories are usually modelled, as in the approach presented here, and are used as input to 2 and 3D global transport/chemistry models. Thus, evaluations of the global source-term from lightning are sensitive to parameterisations in both the lightning inventory and the chemistry/transport models. Furthermore, any such approach usually requires verification of measurement data against model results in locations remote from other sources, which usually implies oceanic regions. In such regions, high-quality measurement data are sparse and the modelled source-term of lightning is generally smaller, and more uncertain, than over land masses. Assumptions in the vertical distribution of NOx production from lightning discharges remains important because this is the only other significant source, other than aircraft, in the upper troposphere and it can exert a large effect on 03 production in the upper troposphere (Lee and Hayman, 1996). 3.6. Ammonia oxidation The significance of ammonia oxidation has been the subject of some speculation: estimates ranging from 1~-10(Logan, 1983) to 1.2-4.9 Tg N yr- 1 (B6ttger et al., 1978). Ammonia emissions arise principally as the result of microbial decomposition and other biological processes. Thus, the sources may include animal wastes and natural emissions from soil and vegetation, but also direct emissions from oceans, biomass combustion, fertilisers and, to a much lesser extent, industry. The most recent global inventory of NH3 emissions published is that of Dentener and Crutzen (19941, which indicates a global source term of 4 5 T g N y r 1 Ammonia may undergo gas-phase oxidation with OH according to the following reactions; NHs + OH --+ NH2 + HzO

(7)

NH2 + NO2 --+ N 2 0 + H 2 0

(8)

NH2 + HO2 ~ NH3 + 02

(9)

NH2 + NO--+ N2 + H20, other products

/

(10)

/ NH2 + 0 2 --+ N O + H 2 0 , /

HNO + OH, other products

(11)

NH2 + O3 --+ N H 2 0 + 02, other products.

(12)

The contribution of NH3 oxidation to NO~ production was estimated using a global 3D model of the

1745

ammonia cycle (Dentener and Crutzen, 1994). Reaction rates and their uncertainties were taken from the evaluation of DeMore et al. (1994). Reactions (8) and (10) represent a net loss of NOx, whereas reactions (11) and (12) are a net source of NOx. The experimental evidence for reaction (11) is, however, weak. The fate of NH2 is governed, to a large extent, by reactions with NOz and 03; unfortunately uncertainties of a factor of 3 are associated with the rates of the reactions. In addition, the fate of the N H : O radical in reaction (12) is unknown. Reaction of this radical with 03 or NO may regenerate the NH2 radical, but these reactions may be slow in comparison with reaction with molecular oxygen (Tyndall et al., 1991 ), the latter reaction ultimately resulting in NOx production. Calculations from this model indicate a source term of 0.9 T g N y r 1 95% of which is found between the latitudes 30°N and 30°S. Applying an uncertainty range of a factor of 3 for reactions (8) and (12) gives a range of 0.4-1.4 Tg N y r - 1 NOx production. If it is assumed that NHzO is completely recycled to N H : , the production is considerably less at 0.1 T g N y r 1 Additional uncertainties are associated with the emissions and calculated concentrations of NH3 and NO.,. Following Dentener and Crutzen (1994), an uncertainty range of 0.4 1.2 T g N yr-1 is attributed to uncertainties in emissions. Combining the uncertainties in emissions and reaction rates gives an uncertainty range of 0 - 1 . 6 T g N y r -1 with a best estimate of 0.9 Tg N y r - 1

4. CONCLUSIONS

• A standard set of data for emissions of NO~ from fossil fuels, biomass burning, soils and lightning was used in the model comparisons of the AERONOX project so that differences between the models were highlighted, rather than the input data. Spatially disaggregated NOx emissions from biomass burning ( 5 . 3 T g N y r ~), soils (3.9 Tg N yr-1), fossil fuel combustion at Earth's surface ( 2 2 T N y r - 1 ) , lightning ( 5 T g N y r 1), and the stratospheric decomposition of N 2 0 (0.64 T g N y r L) were used. • Where better inventories are now available, these are compared and discussed. Presented here is a new estimate of NOx emissions from biomass burning of approximately 8 Tg N yr 1, which is 50% greater than that used in the AERONOX modelling. This is based upon an inventory of biomass-burning which includes deforestation, savannas, biofuels and agricultural waste burning, and extends beyond the tropics, giving a more realistic representation • An attempt was made to quantify uncertainties. The range of emissions from biomass burning (all sources) was 3 - 1 5 T g N y r 1. The calculated emissions from soils was approximately 12 T g N yr k 1, which represents an upper

1746

D.S. LEE et al.

estimate. A simple scaling factor (0.33) to compensate for canopy interactions was adopted for the soils source in the A E R O N O X modelling, which was a major weakness in the spatial disaggregation. Using an alternative method of scaling emission factors by land-use and biome-specific canopy reduction factors, an estimate of approximately 7 Tg N yr-~ was made. Using the same canopy reduction factors, a down-scaling of the soil flux model resulted in an annual emission of approximately 7 Tg N y r - 1. A potential range of emissions from this source was estimated to be 4 - 1 2 T g N y r - 1. Our estimate of lightning was a prescribed 5 Tg N y r - 1, with a possible range of 20 Tg N yr-1, which is in good agreement with some recent estimates, but this source represents one of the major uncertainties in global NOx emissions, as some other recent estimates are an order of magnitude higher than this. The poor progress made in understanding emissions of NOx from lightning is in stark contrast to the progress made in quantifying emissions of N O from soils over the past ten years or so, and a consensus position on the potential global source term for lightning has not yet been reached. This is clearly an area which needs far more work. Fossil fuel combustion was estimated to have an uncertainty range of 13-31 Tg N y r - 1 • A new estimate of the contribution from ammonia oxidation to NOx production was found to be 0.9 T g N y r - 1. Previous estimates of a m m o n i a oxidation contributing as much as 10 Tg N y r are considered very unlikely. • The global source term for NOx for all sources was estimated to be 44 Tg N y r - 1 with an uncertainty range of 23-81 Tg N y r - 1. • An emission scenario for fossil fuel combustion is presented based upon key assumptions made in the IPCC's IS92 scenarios for the year 2025. This indicates an emission of 46.5 Tg N y r - 1 from this source with a shift in the geographical distribution of sources to Asia and the Far-East. Fossil fuel combustion at the earth's surface is presently the largest best quantified source, and should this scenario prove to be correct, further generation of photochemical oxidants and the risk of consequent environmental degradation seems inevitable. Acknowledgements--The compilation of these emissions would not have been possible without the generous provision of data from others. In particular, we would like to thank Dr Wei-Min Hao of the Canadian Forestry Service and Dr Jane Dignon of Lawrence Livermore Laboratory. We also gratefully acknowledge the support of this work by the Commission of the European Communities, under the AERONOX programme, the U.K. Department of Trade and Industry (Aerospace Division), the U.K. Department of Transport (Civil Aviation Division) and the U.K. Department of the Environment (Global Atmospheres Division). DLR was also supported by the German Bundesministerium fiir Forschung und Technologic (Verbundprogramme,

"Schadstoffe in der Luftfahrt"). We would also like to thank Dr H. Feichter, Max-Plank lnstit flit Meteorologic, Hamburg, for providing the annual cycle of monthly mean flash rates of lightning and F.J.D. thanks Geoff Tyndall for his comments on the oxidation chemistry of NH3.

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