The contemporary atmosphere was created as a result of biological activity some Gs years ago. To this day, its natural composition is supported, and modified, mostly through biological processes. The majority of green house gases are naturally produced as a result of decomposition processes, facilitated by microorganisms. It must be remembered that the source strength of most gaseous emissions in nature corresponds to the net balance between biological production and destruction processes, although physical and chemical processes are also involved in cases such as ozone. Over time, climatic conditions determine the relative importance of the biological processes of production and destruction as well as the strength of the photochemical source and/or sink, all of which vary regionally but are globally connected.
One of the best-documented and most important indicators of global change is the secular increase of a number of trace gases in the atmosphere, among them carbon dioxide, methane, nitrous oxide and ozone. There is considerable uncertainty, however, regarding the processes that determine the concentration and distribution of trace gases and aerosols in the atmosphere and the causes and consequences of atmospheric change (Andreae and Schimel, 1989). The goal of the International Global Atmospheric Chemistry (IGAC) Core Project of the IGBP has been to understand the factors that regulate composition and change in the atmosphere, including in situ chemical and physical processes as well as biogenic and abiotic sources and sinks in the biosphere (Hobbs and Huebert, 1996). In this chapter, we focus on what we have learned with respect to the exchange of trace gases and aerosols between terrestrial and marine biosphere in regulation of the atmosphere and their feedback on biological processes. We consider both natural exchanges of trace gases, as they vary spatially and temporally on the Earth s surface, and their alteration by anthropogenic activities, and the effects of the deposition of atmospheric materials on the surface. More is understood about the production of trace gases from soils, vegetation, freshwater and marine systems than the deposition of chemical species to the Earth s surface. Deposition provides a natural sink for atmospheric trace species that influence atmospheric chemistry, whilst also acting as a source of nutrients for biological systems. However, in regions where the biogeochemical cycles of many species are grossly perturbed by anthropogenic activities, atmospheric deposition can become an equally important source of toxic substances to the biosphere. Deposition of atmospheric dust acts as a fertilizer in certain oceanic and continental areas. In marine regions, where trace elements such as iron are limiting, we have observed increased uptake of atmospheric CO2 and release of other gases such as dimethyl sulfide. Furthermore, a significant change in community structure may result in these systems, currently a highly visible research topic among oceanographers. Similarly, wet deposition on temperate and boreal forests has been shown to increase certain gas emissions, similar to those resulting from the addition of artificial fertilizers.
In the past decade, our knowledge of trace gas exchange between terrestrial or aquatic systems and the atmosphere, and of the biological, physical, and chemical processes that control these fluxes, has increased dramatically. The increased attention and research effort in this area stems primarily from the fact that the atmospheric concentrations of a number of trace gases are increasing. The increases of some of the less reactive gases such as nitrous oxide (N2O) and methane (CH4) are documented in the 20 year or longer record of atmospheric measurements at sampling stations throughout the world (Prinn, 1994, Steele et al., 1992) and by the long-term record provided through the analysis of gases trapped in glacial ice (Barnola et al., 1987). The consequences of these atmospheric changes are felt at a variety of scales: some contribute to the radiative balance of Earth and hence climate change, and others have critical roles in regional and global atmospheric chemistry.
The understanding of sources and sinks of trace gases, and of the degree to which they are undergoing change, has benefited from the contributions of a number of disciplines, including atmospheric chemistry, ecology, biogeochemistry, microbiology, soil physics and chemistry, meteorology, hydrology, and oceanography. Exchanges of biogenic trace gases between surfaces and the atmosphere are controlled by the production and consumption of gases by plant, microbial, and chemical processes, the physical transport through soils, sediments, or water, and the flux across the air-surface boundary. These biological and physical processes in turn depend on other biotic and abiotic properties and processes within ecosystems. One of the hallmarks and great successes of IGAC research has been the integration of knowledge from a number of disciplines toward the understanding of trace gas sources and sinks.
It will not be possible in this document to recount all progress made over the past ten years towards understanding the magnitude and mechanisms of biosphere-atmosphere trace gas exchanges; much of the research can be found published in many peer-reviewed journals. This chapter is divided into two sections, one dealing with terrestrial highlights and the other with marine systems; whilst some of the processes have the same abiotic controlling factors, the rates of exchange between the two systems and the atmosphere vary markedly. The conclusion of the chapter attempts to bring the two sections together by discussing feedbacks and impacts. The terrestrial section will highlight what has been achieved in addressing the gaps in the knowledge which were identified at a Dahlem conference held in 1989. It is also not our intent to provide current assessments of the source and sink strength of all trace gases, as those budgets have been compiled and published (with considerable contributions by IGAC researchers) in recent IPCC documents. Instead, in the following sections, we will highlight what we have learned about the regulation of gas fluxes due to microbial and plant processes and to biomass burning in the terrestrial biosphere, and due to biogeochemical production, consumption and exchange processes in the marine environment. The Dahlem conference recommended three critical biological issues for terrestrial systems concerning process and methodological issues; first, factors controlling the partitioning of nitrogen gas production between N2O, N2 and NO are not well understood. Second, the control and importance of CH4 oxidation requires much more study since a less efficient sink could contribute to globally increasing concentrations. Finally, the controls over non-methane hydrocarbon exchange between plants and the atmosphere are a key new topic. Issues related to direct and indirect effects of biomass burning on the tropical biosphere were also raised. Recommendations were made as to where these measurements should be made, the sampling scale and which methodologies should be applied (Andreae and Schimel, 1989).
Ten years ago, at the beginning of IGAC, researchers sought to establish the source and sink strength of gases in different kinds of ecosystems, in different areas of the world. Earlier extrapolations of gas fluxes over space and time were often based on a single, or very small, set of measurements, and researchers searched for representative sites in which to make those crucial measurements. In contrast, IGAC research, in many ways, sought to understand and take advantage of variability among ecosystems and regions of the world, in order to better understand the factors controlling fluxes (Galbally, 1989). For example, studies of CH4 flux from wetlands and rice paddies, of N2O flux from natural and managed ecosystems, and of dimethylsulphide emissions from oceans, consciously spanned gradients of temperature, hydrological characteristics, soil types, marine systems, management regimes, and nitrogen deposition. One result of this strategy was the recognition that the same basic processes were responsible for gas fluxes, across regions, latitudinal zones, and environments. Consequently, the development of simulation or statistical models that included those processes together with their range of uncertainities, driven by the suite of environmental and edaphic factors important in their regulation, could be applied more broadly than once thought. Today, estimates of fluxes and global budgets rely on numerous measurements taken around the world, and a mechanistic understanding of biogenic gas fluxes has been formalized into conceptual and mathematical models.
Curently much of IGAC s work on biosphere-atmosphere exchange is addressing the consequences of change in land use, land management, atmospheric deposition, climate, tropospheric and stratospheric ozone, aerosols, carbon dioxide, and so on. And along with the rest of the IGBP, thefocus is increasingly on the effects of multiple and interacting changes. Moreover, IGAC researchers are addressing not just the causes of alterations in biosphere-atmosphere exchange, but what can be done to prevent, reduce, or mitigate those changes.
The Dahlem conference recommended that to best address knowledge gaps, manipulations to whole systems are required. In addition, integrated field and modeling experiments are necessary to develop the techniques for estimating regional exchange rates of gases and predictive models for gas exchange rates. These field experiments should include studies of production, micrometeorological measurements of flux, and stratified sampling to link landscape variability to variation in trace gas exchange. These approaches have been employed very successfully in Southern Africa (SAFARI 92 and 2000), West and Central Africa (DECAFE and EXPRESSO) over the last ten years. A similar experiment is currently being conducted in Brazil. The Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) is an international research project addressing these issues in an interdisciplinary and innovative way. Its main four integrated components: 1) Atmospheric chemistry and physics; 2) Physical climate; 3) Biogeochemical cycles; 4) Carbon storage and exchange, act together to understand how the Amazonian ecosystem functions as a regional entity.
A. Case study: SAFARI 92
The following example from the SAFARI 92 campaign highlights the scientific approaches used to test hypotheses and validate models related to biogenic emissions, biomass burning emissions and depositions. It is approaches like thesethat have allowed for an integrated understanding on the magnitude and controllers of sources, sinks and exchange processes. During SAFARI-92, experimental vegetation fires were conducted in the Kruger National Park, South Africa, and at some sites in Zambia and Swaziland. These experiments provided a broad set of data on trace gases and aerosol emissions, from which emission factors for fires in dry savannas and related biomes could be derived. The relationships between fuel characteristics, burning conditions, and fire behavior were elucidated. Regional studies on atmospheric chemistry and air mass transport showed that savanna fires in southern Africa account for a substantial amount of photochemical oxidants and haze over the subcontinent and that the export of smoke-laden air masses contributed strongly to the burden of ozone and other trace gases and aerosols over the tropical ocean surrounding Africa. Investigations on the relationships between fire, soil moisture status, and soil trace gas showed that moisture played a crucial role but that fire history also had an important influence on the emission of several trace gases. Figure 1a shows the relationship between daily NO emissions and NO3 concentrations plotted against water-filled pore space. Figure 1b describes the relationship between NO emission rate and nitrification rate in areas where fire has been excluded (Ex) and in areas where the vegetation has been burned every two years (Parsons et al., 1996). These relationships were later incorporated into a simulation model to predict NO emissions from semi-arid savannas thereby reducing the large uncertainty associated with the magnitude of previous savanna measurements (Otter, 1999). B. Exchange of trace gases and aerosols from vegetation, soil, invertebrates and vertebrates 13
This section reviews the progress made in the last decade in the quantification of the terrestrial sources and sinks of volatile organic carbons, nitrous and nitric oxides and methane, the advances in the understanding of the processes controlling the fluxes, the synthesis of existing knowledge and the capacity to develop predictive models of fluxes at landscape and ecosystem scales. The nature of the emissions are such that they occur in a more or less continuous way over the year with the magnitude of the exchange being controlled by a complex interaction of biotic and abiotic factors. In practice, the distinction between soil and vegetation is often not trivial and usually not solved simply by removing the plants. Plant processes and soil processes interact in various ways, which is particularly true when considering the oxides of nitrogen and methane. Absorption of nitric oxide by the plant canopy and the role of plants as conduits in the transport of methane from the soil to the atmosphere will be discussed in the section on soil processes. The production of volatile organic carbons will be discussed in greater detail due to the progress made in this field over the last decade. 1. Production of volatile organic carbons from vegetation
Aside from oxygen, hydrocarbons are the most abundant reactive chemicals that are produced and emitted by plants, although certain plants also emit oxygenated organic compounds (VOC). Organic sulphur compounds, NO, CO and organic particles may also be emitted. Plants emit 400-800 Tg C/yr as hydrocarbons, an amount equivalent to the sum of biogenic and anthropogenic methane emissions. Unlike methane, which is well mixed in the atmosphere because of its long atmospheric lifetime (8-11 years), plant- produced VOCs are extremely reactive in the troposphere, with life times ranging from 1-2 hrs for isoprene to greater than a day for other volatile organic compounds (Guenther et al., 1995). Many are emitted at very low rates, and in some cases are offset by plant uptake, and so have a negligible impact on atmospheric chemistry; others impact ozone production, methane oxidation and the global carbon monoxide budget. Modeling studies of a few compounds, such as isoprene, have shown that emissions from vegetation can significantly influence the chemical composition of the atmosphere. For example, isoprene can compete with ozone as a sink for NO and with CH4 as sink for OH. The major impact of some other compounds, including the monoterpene _-pinene, is the production of secondary aerosols. VOC emissions from plants also have a role in global carbon cycling representing about 2% of the carbon exchange between biota and the atmosphere.
Figure 1. (a) Mean daily NO emissions and NO3 concentrations in the fire exclusion plots, plotted against water-filled pore space simulated using the HotWet model. Solid lines represent fitted functions to the NO emissions and NO3 concentrations. (b) Mean NO emissions measured in both the exclusion plots and the plots burned every two years during both this study and that of Levine et al, 1996 plotted against mean nitrification rate measured in the corresponding plots (Parsons et al., 1996).
Remote sensing studies confirmed that AVHRR/LAC (1 km) imagery was a useful tool for fire monitoring in the region. In combination with biomass models, the remote sensing data could be used for the estimation of the seasonal and geographical distribution of pyrogenic emissions. The results from SAFARI 92 confirmed that it is justified to consider biomass burning as a significant contributor to the overall increase in greenhouse gases that has occurred over the last 150 years, accounting for some 10-25% of current estimates (Andreae, 1993). In order to establish accurately the global budgets of trace gases, reliable source strength and distribution estimates are needed. At present, the uncertainties associated with budget calculations are necessarily large, owing to the often inadequate quantification of individual sources and the problems associated with extrapolating from a number of poorly known sources to achieve a global estimate. The contribution of vegetation fires in the savanna regions of southern Africa has been such a poorly quantified source, despite the fact that savannas are recognized as one of the most significant biomes in terms of global biomass burning emissions (Andreae, 1993) and that a large portion of the savanna burns each year. It will now be possible to refine these estimates on the basis of results obtained from SAFARI 92. Modeling studies incorporating the emission data, meteorological information, and the chemical measurements made during these campaigns indicate that the fires on the African and South American continents are indeed a major source of the gaseous and particulate pollutants, particularly ozone, found in the troposphere over the study region (Jacob et al., 1996, Thompson, et al., 1996). Data from airborne observations (Figure 2a,b), aboard a DC-3 using a combination of spectrometers and chemiluminescence instruments, showed that episodic pyrogenic emissions were not adequate to account for the buildup of tropospheric ozone in the region but that the continuous production of biogenic NOx emissions and especially the amounts produced at the start of the rainy seasons have important consequences for regional scale ozone formation (Harris et al., 1996). The vertical distribution of NO2 and NO as well as that of CO2 showed markedly different characteristics. All three species have a strong gradient toward higher values near the ground, and the CO2 and NOx mixing ratios correlated linearly. The anticorrelation of the profiles of these species with that of CO rules out biomass burning as a source of the observed NOx and CO2 near the ground, supporting the field evidence of no active fires in the region. It was concluded that the source of the elevated NOx mixing ratios near the surface was biogenic emission from the soil (Harris et al., 1996).
Figure 2. (a) Vertical profiles of CO2 , NO2 and NO and the ratio NOx /NOy measured during SAF11. (b) Scatter plot of NOx and CO2 mixing ratios determined during the SAF11 profile (Harris et al., 1996).
SAFARI-92 was an innovative project in many ways. As well as being the largest international, interdisciplinary investigation of biomass burning and its emissions to the atmosphere ever undertaken, it also represented the first time that a large-scale fire emission measurement campaign included, as an integral component the characteristics of the biomass, the fire ecology, the fire dynamics in the area, the biogenic emissions and the long range transport of the aerosols and particulates. The integration constitutes recognition of the significant link between fire behaviour and emissions to the atmosphere. The success of the project is reflected in the issuing of a special issue of the Journal for Geophysical Research containing 21 papers on the campaign (Lindesay et al., 1996).
Recent improvements in our understanding of vegetation trace gas emissions are a result of advances in emission measurement methods and the initiation of collaborative efforts employing multi-scale and multi-disciplinary experiments. There are now a large number of enclosure methods available including whole-plant enclosures, controlled-environment enclosures, and inexpensive screening tools. Eddy covariance VOC flux systems are currently available only for isoprene although new methods (Lindinger et al., 1998) may soon extend the list of compounds that can be investigated with direct flux measurements. In the meantime, the use of indirect flux measurement methods (e.g., mixed layer mass balance, gradient, and relaxed eddy accumulation) are providing measurements suitable for investigating above canopy fluxes. Our improved understanding of the potentially important influence of vegetation VOC emissions on atmospheric chemistry has resulted in a substantial increase in the research activity in this area. This work is described in recent reviews of biogenic VOC published in journals of the biological (Sharkey 1996; Lerdau et al. 1997, Harley et al. 1999), chemical (Atkinson 1999) and atmospheric (Kesselmeier 1998, Guenther et al. 1999) science communities as well as in a book containing 12 articles (Helas et al. 1997) and several book chapters (e.g., Fall 1999; Guenther 1999; Steinbrecher and Ziegler 1997). The following text is a brief synthesis of these studies and the reader is referred to these review papers for more detailed descriptions.
|
|
|
| Tropical forests | Temperate forests | Boreal forests | |
| Seasonality Species number per 10000 km2 Species diversity Degree of uncertainty |
No (mostly evergreen) 5000 High Very Large |
Yes (mostly deciduous) 500-1500 Low (Aspen, Oak, Poplar) Small |
No (mostly evergreen) 200-500 Low (Pines, Aspen, Spruce) Medium |
| References | Isoprene | Mono-terpenes | ORVOC | OVOC | Total |
| Rasmussen and Went, 1965 Robinson and Robbins, 1968 Zimmerman, 1979 Isidorov, 1985 Rasmussen and Khalil, 1988 Dignon and Logan, 1990 Taylor et al, 1990 Turner et al, 1991 Mueller, 1992 Isidorov, 1994 Guenther et al, 1995 |
350 452 450 175 285 250 503 |
480 143 147 127 |
260 |
260 |
432 480 830 1550 452 450 318 285 397 1350- 1500 1150 |
1.5. Global change and the ecology of emissions
Three related aspects of global change have the potential to dramatically affect biogenic hydrocarbon emissions: increases in atmospheric levels of carbon dioxide; increases in greenhouse gases, which lead to higher surface temperatures and changes in precipitation patters; and landscape-scale alterations in vegetation type. Despite the taxonomic variability in VOC emissions, one constant is that no C4 species has been found to emit as much isoprene or monoterpene as some C3 species. Increased productivity in C3 species and changed biome distributions could markedly influence emissions. Due to the large differences in emission rates associated with different landscapes, there is a substantial potential for land-use change to influence biogenic emissions. Since woody plants tend to have much higher isoprene and monoterpene emissions rates, compared to crops and grasses, it might be presumed that deforestation would greatly reduce biogenic VOC emissions. However, there is a tendency for higher emissions from the woody plants (shrubs and sun tolerant trees) that replace a closed canopy forest (Klinger et al., 1988). Fire dominated systems in the more arid areas have kept emissions low but agricultural practices of grazing and fire suppression have allowed shrublands to spread with resultant increased emissions. The chestnut blight of the late nineteenth and early twentieth centuries on the USA East Coast lowland forests caused massive change in forest composition with oak replacing the chestnut. Unlike oak, chestnut does not emit isoprene. The chestnut blight has thus resulted in an approximate doubling of the biomass of isoprene-emitting species (Lerdau et al., 1997).
There is an equally great potential for changes in biogenic VOC emissions as a result of climate change. Biogenic VOC emissions are very sensitive to temperature and an increase of a few degrees could lead to increases in emissions of more than 20%. VOC emissions from the peat-lands and bog areas of Northern Europe, USA, Canada and Eurasia may be significantly increased under global warming.
| Trace gas | Mixing ratio (ppbv) | Life-time (days) | Total Budget (Tg yr-1 ) |
Annual increase (%) |
Contribution (%) of soils as: Source Sink |
Importance | |
| H2 CO CH4 OCS N2O NO DMS CH3 CCl3 CF2 C2 |
550 100 1700 0.5 310 <0.1 <0.1 0.14 0.48 |
1,000 100 4000 1500 60,000 1 <0.9 2200 44000 |
90 2600 540 2.3 3.23-10.7 17.0-25.0 38 0.2 0.45 |
0.6 1.0 <0.8 0 0.2-0.3 ? ? -3.4 <5 |
5 1 60 25 70 20 <0.1 0 0 |
95 15 5 ? ? ? 0 0 0 |
Insignificant Tropospheric chemistry Greenhouse effect and tropospheric and stratospheric chemistry Stratospheric aerosol Greenhouse effect, stratospheric chemistry Tropospheric chemistry Cloud formation Calibration of OH Stratospheric chemistry, greenhouse effect |
| Biome | Y&L1 no canopy |
D&K2 no canopy |
Y&L w/ canopy effect |
D&K w/ Y&L's canopy effect |
| Tundra Temperate Grassland Temperate Woodland Temperate Forest Temperate Agriculture Tropical Grassland Tropical Woodland Tropical Dry Forest Tropical Rainforest Tropical Agriculture Deserts and Semi-deserts Total |
0.02 0.52 0.09 0.07 1.82 2.50 0.39 0.11 3.4 1.16 - 1.02 |
0.1 1.1 4.7 4.0 1.8 7.4 5.0 2.0 1.1 3.6 5.0 21.0 |
0.02 0.34 0.05 0.04 1.33 1.60 0.22 0.06 0.85 0.92 - 5.45 |
0.0 0.7 2.9 0.2 1.0 4.3 0.3 1.0 0.3 2.9 0.5 13 |
 |
 |
| CASE STUDY: IMPACT OF NITROGEN FERTILIZER AND DEPOSITION ON NITROGEN TRACE GAS EMISSIONS. |
 |
 |
 |
 |
2.3. Methane emissions
Methane is the second most important greenhouse gas after CO2 and is expected to contribute 18% of the total expected global warming over the next 50 years, as opposed to 50% attributable to CO2. In addition to these direct effects, methane participates in tropospheric ozone formation. The major anthropogenic sources of methane are in developing countries with high population growth. China and India together account for over half the global area devoted to rice cultivation; large areas of ruminant livestock graze over vast areas of Asia, Africa, and Latin America; and biomass burning (forest clearance, savanna enhancement, field preparation, fuel wood consumption and charcoal production) is widespread . Anthropogenic sources of methane are thought to be nearly twice as high as emissions from natural sources. The concentration of methane in the atmosphere is of the order of 1.7 ppmv. This concentration had been increasing at about 20 ppbv per year in the 1970s; the rate declined to a virtual standstill by 1992/3, but then recovered somewhat, to 8 pppv per year in 1994 (Schimel et al., 1996). 2.3.1. Wetlands and rice fields
Global methane production is dominated by fluxes from a) natural wetlands and bog areas, where production rates may be related to water depth, and b) from agricultural wetlands, rice paddies in particular. Early studies came to conflicting conclusions about whether tropical wetlands were more or less important contributors than those in boreal regions. For example, Seiler and Conrad (1987) estimated that 38 Tg CH4 yr-1 out of a global total of 47 Tg were of tropical origin, whereas Matthews and Fung (1987) estimated that northern wetlands contributed 60% of a total of 111 Tg y-1 . More recently, a study of the Hudson Bay lowland, one of the two largest wetlands north of 40ºN, gave much lower fluxes (20 ± 16 mg CH4 m-2 d-1 ) than those expected on the basis of the earlier estimates for northern wetlands (Roulet et al., 1994). This work has pointed strongly to a lesser contribution from boreal regions, and is supported by process-based modeling work, e.g. that by Cao et al. (1996), which predicted a total emission of 92 Tg CH4 y-1 , of which 56% came from tropical wetlands. Most global estimates since that of Matthews and Fung (1987) agree well with their estimate of global wetland emissions (which corresponds to 22% of CH4 emissions from all sources), but the mean of the tropical component within these estimates is 53 ± 11% (Boeckx and van Cleemput, 1996). The most recent estimates indicate that 109Tg yr-1 of methane is released by wetlands globally. Tropical regions (20°N to 30°S) are calculated to release 66 Tg yr-1 (60.5% of the total), emissions from subtropical and temperate wetlands (20-45°N and 30-50ºS) are only 5 Tg yr-1 (4.5% of the total) but there have been relatively few measurements in the tropics and subtropics, and this figure is therefore currently uncertain. Northern wetlands (north of 45ºN) are calculated to release a total of 38 Tg yr-1 (35% of the total) with 34 Tg yr-1 from wet soils and 4 Tg yr-1 from relatively dry tundra (Milich, 1999). Current estimates of the total CH4 emission from rice paddies amount to 50 ± 20 Tg y-1 (Neue, 1997), or about half that from natural wetlands. 2.3.2. Enteric fermentation
Domestic animals, predominantly cattle, account for approximately 94% of the total global methane emissions by animals, including humans. Methane is emitted primarily form the enteric fermentation in the rumen and not from emissions from dung. Global estimates are hampered by two factors, firstly cattle numbers are difficult to obtain especially in developing countries where government records are incomplete. Secondly, cattle can emit from 7-42 g of methane animal-1 day-1 , a variation that has serious consequences for accurate estimates of methane emissions from ruminants, depending on the quality and quantity of the daily intake as well as on the cattle breed. In general, methane yields decrease as dietary intake increases, and the decreases are typically greater for highly digestible diets compared to less-digestible diets (Williams, 1993).
2.3.3. Termites
Tropical termites have a substantial effect on the recycling of organic matter and humus formation. Because of their numbers and diet, termites are important producers of methane but global estimates of production are extremely uncertain. The production of methane is related to the quality of the material eaten and the wood eating termites are acetogenic, not methanogenic, and thus these species are low methane producers. On the other hand, soil- feeding termites produce high quantities of methane and no acetate. Field estimates from the Congo range from 1.8 -13.1µg g termites-1 hr-1 (Rouland 11 et al., 1993). Values are highly variable because of the simultaneous process of production and consumption taking place, estimates will only improve with the development of more sophisticated technologies allowing for better spatial integration of data. The annual global methane source strength is currently estimated to be only Tg yr-1 down from the 40 Tg yr-1 estimated in 1992 (Milich, 1999, Aber, 1992).
2.3.4. Methane oxidation in soils
Methane oxidation in soils is perhaps best considered under two headings: the oxidation of atmospheric methane and the oxidation in aerobic soil layers of methane diffusing from nearby anaerobic environments, e.g. in natural wetlands, rice paddies and landfill cover soils. At the outset of the IGAC programme, there were few data available on the oxidation of atmospheric methane in soils. The size of this sink was estimated by the IPCC at 30 (range 15-45) Tg CH4 y-1 -- 6% of the estimated sink due to reaction with OH in the atmosphere (Watson et al., 1990) and this has been accepted as the best estimate until recently. There are now many more flux measurements available, including some from studies lasting one to several years, there is more information on the impact of land use change, and the relationships between oxidation rates and several soil parameters have been modeled. An analysis of the available flux values for different ecosystems has shown consistent median values of between 1 and 2 kg CH4 ha-1 y-1 , but with skewed (log-normal) distributions (Smith et al., 1999). One major reason for the similarities between different ecosystems is that the effect of temperature on oxidation rate is small, as the organisms responsible are substrate-limited due to diffusion resistance and low atmospheric concentration. This data analysis indicates a global terrestrial sink of the order of 29 Tg CH4 y-1 , and a ±1s range from a quarter to four times this value (Smith et al., 1999). Thus we are faced with more uncertainty than was the case before, and until there are at least a few data from large areas of the world that have not been studied at all, the situation is unlikely to be greatly altered. Global estimates from models range from 17 Tg CH4 y-1 (Potter et al., 1996) to 38 Tg CH4 y-1 (Ridgewell et al., 1999). 2.3.5 Global warming impact on methane fluxes
One possible outcome of global warming in wet tundra ecosystems will be increased temperatures and thaw depth, which should increase methane fluxes. On the other hand, increased evaporation at the soil surface may create an oxygenated zone, producing an environment conducive to methanotrophs and reducing methane fluxes. However, climate models indicate an increase in precipitation for northern latitudes (Vourlitis et al., 1993) and under this scenario, coastal wet tundra soils will continue to be waterlogged but will experience significantly elevated temperatures, substantially increasing methane emissions. Improved resolution of global climate models will enhance the biologists capacity to suggest appropriate mitigation strategies for different methane producing areas. Doubled ambient carbon dioxide concentrations increased rice yields but enhanced temperatures limited the potential increases. Rice production may expand northwards especially in Japan and China. Elevated carbon dioxide concentrations will enhance the production of rice yields with increased carbon exudation from the roots enhancing methane emissions, breeding of rice cultivars will be the most effective strategy for dealing with this issue (Milich, 1999).
2.4. Summary
The Dahlem conference posed five areas of research that needed to be addressed ranging from an improved mechanistic understanding of the soil processes involved, to the application of modeling techniques which would allow for regional and global estimates to be improved, to an appreciation of how these fluxes would change under global climate change. Though much was known about the mechanisms of production in 1989, the last ten years have contributed an increased sophistication in the methods of measurement, increased availability of supporting data and the incorporation of these data into a range of models. Matson et a., (1989) stated that empirical models that are based on correlation analysis involving easily measured soil variables (eg temperature, moisture, texture, and organic carbon) often predict trace gas fluxes quite well. As data sets became more available, this set of variables has been further reduced to moisture and temperature with some corrections needed to take account of texture differences. Empirical relationships have been established for a number of different ecosystems around the world for both NO and N2O emissions with water filled pore space values of approximately 35% being the switch from NO to N2O emissions. N2O emissions show stronger temperature dependence than do NO emissions. The magnitude of the emissions vary with substrate availability; the use of 15N labelling techniques to measure the turnover of the soil ammonium and nitrate pools has greatly enhanced our capacity to partition nitrogen gas production between NO, N2O and N2. Trace gases are produced and consumed by defined reactions in individual microorganisms and control must be exerted at this level initially. To date, empirical models based on various physical and chemical parameters are successful without considering the structure of the microbial community; even those models that differentiate between nitrification and denitrification neglect microbial community structure. The jury is still out as to whether microbial species diversity is an important factor especially if one considers changes associated with land use (Conrad, 1996). For many of the trace gases uptake and emissions may occur simultaneously and models using one-directional fluxes are no longer appropriate. The concept of compensation points has been successfully applied to a number of soils and vegetations; these compensation points vary with environmental factors such as light, temperature, precipitation and soil and vegetation characteristics. Theoretical models describing the fundamental processes governing compensation points are needed to permit extrapolation of the available measurements. It is suggested that major advances for the scaling of fluxes are to be made in applying compensation points (Conrad and Dentener, 1999). Many models are now available for predicting trace gas exchanges with reduced uncertainties at various local and regional scales. Recent data on N20 and NO emissions from N fertilized and N-saturated systems give indications as to how global change and changing land management practices may be enhancing emissions. Recent data on methane-oxidising bacteria associated with the roots of rice were shown to be stimulated by fertilization and not inhibited as was generally believed; these data will make a re-evaluation of the link between fertilizer use and methane emissions necessary. Sufficient studies have been conducted on methane budgets from rice paddies to allow for mitigation strategies to be proposed for different regions and land management practices.
C. Episodic emissions
Fire and its impact on the Earth's atmosphere must have been present ever since the evolution of land plants, some 350-400 million years ago. Before the advent of humans, fires were ignited naturally by lightning strikes, especially during dry periods in vegetated regions. Today, however, fire is almost exclusively the result of human activities, such as the burning of forested areas for land clearing, of natural grasslands and savannas to sustain nomadic agriculture, of agricultural residues, and of biomass as fuel for cooking and heating. Even wildfires are frequently caused by human activities, e.g. camp fires, cigarettes, or sparks from engines. Natural wildfires play a substantial role in the boreal and savanna regions of the world. Wildfires are of an episodic nature with the return frequency varying widely across the biomes of the world; for example, in savannas they return with a frequency of 3-5 years whereas in boreal areas this may take as long as 500 years. As a result of the increasing human impact on our planet, it is likely that the amount of biomass burned annually has strongly increased over the past century, especially because of increasing tropical deforestation and domestic biofuel use. However, associated with this is the capacity to better control and manage emissions from biomass burning. 1.2. Scientific approach
Since the early 1990s, BIBEX has designed and carried out a number of biomass burning experiments in various ecosystems throughout the world, often in collaboration with other international programs (e.g., other IGBP Core Projects, the International Boreal Forest Research Association, and the International Union of Forest Research Organizations). These experiments have been designed to provide local-scale data on vegetation fire characteristics and ecology, while simultaneous regional-scale measurements, using remote sensing and aircraft sampling platforms, have provided a capability to scale-up results. Typically these experiments would involve ground measurements on individual fires, airborne sampling and analysis of smoke plumes, and remote sensing of regional and global fire activity. Emphasis to date has been placed on tropical ecosystems, but an increasing number of experiments are now being organized in the boreal zone in response to climate change concerns. 1.3. Land-use fires, wildfires and domestic biomass burning: General trends, uncertainties and possible changes
In these activities and the preceding regional and global research on the fire ecology of the main vegetation types and on atmospheric chemistry, several key questions have been addressed: What is the current state of vegetation fires at the global scale? Are there quantitative and qualitative changes of vegetation fires compared to historic times? The baseload of natural fires and those anthropogenic fires that have been burning during evolutionary time scales has been determined by several factors: climate and vegetation changes, changes of land occupation, and cultural practices. The magnitude of historic and prehistoric vegetation burning, however, remains largely unknown despite the availability of fragmentary data obtained by case studies (summarized in Clark et al., 1997). BIBEX research and other observations reveal uncertainties, recent changes, and new insights of fire occurrence in the following main vegetation zones: Tropical evergreen forest: Deforestation statistics by the FAO and others have in many studies provided the baseline data for calculation of pyrogenic emissions due to land-use change. While these numbers are useful for estimating the net release of carbon to the atmosphere, they do not reflect the entire spectrum of fire activities. Recurrent fires following the initial deforestation burns not only present additional emission pulses but also lead to impoverishment of forest ecosystems resulting in reduced of above- and below-ground phytomass (Goldammer, 1999a; Nepstad et al., 1999). Extreme climate variability such as the ENSO-related droughts of 1982-83 and 1997-98 favor the application of fire for land-use change and maintenance of agricultural systems, and facilitate the spread of uncontrolled fires (wildfires) in humid tropical ecosystems that under average climate conditions are subjected to less fire. The area burned by wildfire in the Indonesian and Malaysian provinces on Borneo island in 1982-83 covered ca. 5x10 6 ha, and in 1997-98 land-use fires and wildfires combined burned ca. 8-9x106 ha in Indonesia alone.
Figure 8 shows the relative magnitude of annual anthropogenic and natural sources and sinks of methane, in which IGAC scientists contributed most to understanding the processes involved in rice paddies and biomass burning. Some discussion is included on the other aspects for completeness. An excellent review of this topic is presented by Milich, 1999. Natural wetlands, rice paddies and livestock farming are among the principal sources of CH4 entering the atmosphere with termites contributing smaller amounts from the cellulose-digesting bacteria in their guts. The quantitative contribution of each factor to the observed total methane increase is not well known and carries with it a wide range of uncertainity (Glantz and Krenz, 16 1992). Further uncertainties lie in the future, for example, in an area where large-scale land use changes continue to occur and where industrialization often increases ammonium wet and dry deposition. It is generally accepted that ammonium-based fertilizers enhance methane emission from rice agriculture; however, recent evidence using a combination of radioactive fingerprinting and molecular biology techniques show that bacteria in the root zone of rice plants are stimulated after fertilization and that inhibition of soil methane consumption may be much less than initially thought (Bodelier et al., 1999).
Figure 8. Estimated annual anthropogenic and natural sources and sinks of methane, in millions of tones. Black lines are uncertainty ranges. Adapted from Aber (1992).
Both natural wetland and paddy rice systems are characterized by high carbon availability under anaerobic conditions, in which the activity of methanogenic bacteria results in approximately equimolar production of CH4 and CO2. However, estimates of net rates of methane flux from wetland areas are complicated by the occurrence of methane consumption in overlying aerobic layers, such as aerobic soil layers or a less-anaerobic water layer. Emission rates are affected by soil water status, temperature, soil type, pH, Eh, nutrient inputs, and the presence of vascular plants. The impact of the first two factors is well illustrated by Figure 9. In boreal wetlands, it has been shown that the removal of vascular plants could reduce emissions by 30 to 85% (Waddington et al., 1996).
Figure 9. (a, b) Relationship between seasonal methane flux and mean water table position and temperature, for a site in Southern Hudson Bay wetland (Moore et al., 1994).
The emissions from tropical and sub-tropical wetlands are generally governed by precipitation and flood cycles, while those from high-latitude wetlands are controlled by temperature-water table interactions (Matthews, 1993; Boeckx and van Cleemput, 1996). Regional estimates of methane emissions are problematic in tropical and sub-tropical areas since variation in precipitation is the major source of seasonal changes in the tropics and the extent of land inundation also varies sometimes quite dramatically, as for example, the several-kilometer swath of seasonally flooded forest on either side of the river in the lower Amazon basin. An adaptation to seasonal flooding is the occurrence of floating grass mats, which have methane fluxes from 1.2 to 4.4 times greater than those of inundated seasonally flooded forests on a m2 basis and 18.5 times more than those of dry seasonally flooded forests in the Amazon basin. In general, well-drained rainforests appear to be a relatively insignificant source of methane, e.g., in Panama, the average flux is 18 0.26g m-2 yr-1 compared to 500 times greater (126g m-2 yr-1 ) for adjacent swamp forest. These Panamanian tropical forests are only slightly more methanogenic than the conifer forests of the Hudson Bay lowlands which have an annual methane flux of 0.2g m-2 yr-1 (Milich, 1999). In subtropical savanna areas, it has been found that savannas are not always sinks as had been previously thought. Seasonally inundated savannas showed CH4 emissions during the wet, summer season with fluxes in the range of -1.6 to 1.68 mg m-2 d-1 . The length of the dry season preceding the flood and the extent of the flooding did not appear to have a significant effect on the methane fluxes from the area. Southern African floodplains were estimated to produce between 0.2- 28 10 Tg CH4 yr-1 (excluding the effects of vegetation-mediated emissions) and therefore produce more CH4 than the savannas consume (Otter and Scholes, 1999).
CASE STUDY: SYNTHESIS OF METHANE EMISSION STUDIES FROM FLOODED RICE PADDIES AND MITIGATION STRATEGIES
CONTROLLING FACTORS OF METHANE FLUXES FROM RICE FIELDS
In rice fields, the emissions are influenced by many factors, of which the most important are the amount of decomposable organic matter (e.g. rice straw) that is incorporated into the soil, water management and the cultivar of rice grown (Neue, 1997). Methane fluxes in rice fields are the result of production, oxidation and transport processes. All these processes are controlled by factors such as temperature, carbon source, soil redox potential, soil pH, soil microbes, and the properties of the rice plant itself, all of which are affected by management and cultural practices.
SOILS
Substantial methane emissions occur only during those parts of the cultivation period when rice paddies are flooded. The International Rice Research Institute (IRRI) experiments showed that for tropical flooded rice soil with temperatures of 25-30º C, methane production in alkaline and calcerous soils commenced hours after flooding, was delayed 2-3 weeks in circumneutral soils, and lagged by 5 or more weeks post-flooding in acid soils (Neue, 1993). Recent evidence using anoxic rice slurries collected from fields with pHs ranging from 5.1-7.7 showed that methane started to increase exponentially right from the beginning of anoxic incubation at positive redox potentials. The second phase of the process was dominated by sulfate reduction or reduction of Fe(III) instead of methane production. Methane was then again vigorously produced and eventually accumulated at a constant rate. These data indicate that the main controller of methane production was the availability of degradable organic substrates rather than the amount of reducible sulfate and ferric iron (Yao and Conrad, 1999). Higher soil temperature speeds up the initiation of CH4 formation but total amounts may not differ when comparing weeks or months rather than days. Probably due to enlarging rooting systems and resulting increased oxygen release into the rhizosphere, CH4 oxidation increases as the season progresses and may account for as much as 81% of the CH4 produced (Sass and Fisher 1995). Initial claims that up to 90% of CH4 produced from paddy fields is oxidised have been refuted , the use of a novel gaseous inhibitor, difluoromethane, which is specific for methane oxidising bacteria in rice fields, showed that CH4 oxidation was important only during a rather short period of time at the beginning of the season, when ca. 40% of the CH4 produced was oxidised before it could enter the atmosphere. The ratio rapidly decreased and for most of the season the CH4 oxidation was only of minor importance. There is now evidence of systematic changes during the rice-growing season in the d 13 C value of emitted CH4 due to changes in production, transport and oxidation (Tyler et al., 1994; Bergamaschi, 1997). This can have a significant impact on the d13C signal of atmospheric CH4 and this has potential use in inverse modeling of methane sources.
Readily mineralizable carbon sources enhance the reductive capacity of soils and finally drive CH4 formation. Organic amendments of wetland soils increase production and emission. Changes are more pronounced when organic substrates are added to soils low in organic matter. Based on the content of readily mineralizable carbon, rice straw or green manures produce more CH4 per unit carbon than humified substrates like compost. CH4 emission was about four times greater throughout the growing season from plots fertilised with up to 20 t ha-1 of green manure than in urea-fertilised plots (Van der Gon and Neue, 1995).
RICE CULTIVARS
Up to 90% of the CH4 released from rice fields to the atmosphere is emitted through the rice plant. Well-developed intracellular air spaces (aerenchyma) in leaf blades, leaf sheaths, culm, and roots provide a transport system for the conduction of CH4 from the bulk soil into the atmosphere (Nouchi et al., 1990). Reported oxidation in rice fields, attributed to be associated with the rice plants, varies between 30 and 90% of total production (Denier van der Gon and Neue 1996). Plant associated oxidation has been reported from a wide range of wetland species and large differences exist between rice cultivars in root oxidation power and in emission rates. Modern cultivars emit generally less than traditional varieties when compared on a single plant basis because the improved harvest index often results in less unproductive tiller, root biomass and root exudates (Neue et al., 1997). Work in China (Lin, 1993) and the USA (Huang et al., 1997) has demonstrated a two-fold difference in emission rates between rice varieties grown under similar conditions. However, under field conditions, a comparison of cultivars is more complex because farmers adjust planting densities or seed rates to achieve an optimum canopy and tiller number per m2 . The large variability in traits of rice plants affecting emission provides the opportunity to breed cultivars with high yield but low emission potentials. A comprehensive program has started at IRRI to screen rice plants for lower methane emissions.
SOURCE STRENGTH
Existing model approaches are still crude, with low resolution, but provide good regional estimates within the range of observed and extrapolated fluxes. The best estimate of the global emission of CH4 from rice fields is likely to be in the range of 30 - 70 Tg ( Neue 1997). Recently Matthews et al. (1999) developed a simulation model describing the main processes involved in methane emission from flooded rice fields by linking an existing crop simulation model (CERES-Rice) to a model describing the steady-state concentrations of methane and oxygen in soils. Experimental field and laboratory data from five Asian countries, participating in the Interregional Research Program were used to develop, parameterize, and test the model. Field measurements of methane emissions were extrapolated to national levels for various crop management scenarios using spatial databases of required inputs on a province / district level. Geographic information on required inputs at appropriate scales limits fast application of this model in defining actual and predicting the future source strengths. Verification methods like downscaling by inverse modeling from regional atmospheric background levels should be a priority.
MITIGATION
The IPCC has determined that methane emissions need to be reduced by only 15-20% to stop the rise in its atmospheric concentration. Mitigation strategies need to be developed. In order to accomplish this successfully, the source strengths of rice fields need to be reliably identified and discriminated according to the various rice ecologies and production systems. They will only be accepted if such technologies are in accord with increased rice production and productivity at least at the farm level. Future improvements of rice production, will likely enhance emissions if not combined with mitigation technologies. Promising mitigation candidates, according to the factors and processes controlling emission, are water management, organic amendments, fertilisation, cultural practices and rice cultivars (Neue and Boonjawat, 1998).
While present knowledge of processes controlling fluxes allow the development of mitigation technologies, information is still lacking on trade- offs and socio-economic feasibilities. Methane emissions have the highest potential to be reduced in irrigated and favourable rainfed rice, where the source strength is highest. One defined drainage at midtillering and drying the fields before harvest is feasible in irrigated rice fields during dry seasons and may reduce emission up to 85%. The drainage at midtillering will not promote nitrous oxide (N2O) emissions nor reduce nitrogen efficiency and rice yields, if done at the time when soil-N becomes exhausted and before topdressing N-fertiliser. Changes in cultural practices because of labour shortage, like direct seeding, and the need to increase water use efficiency are fully compatible with those mitigation technologies. Flooding for land preparation and during most of the rice growing season will probably remain common practice. Wet tillage remains the preferred land-preparation method in tropical Asia where hand and animal power is still common and the principal form of mechanisation is a 10-15-hp hand tractor. The advantages of wet tillage are lower draught requirements, reduced water percolation, ease of transplanting, and improved weed control.
Developing rice cultivars with lower emission potentials, optimising residue recycling and organic amendments, and using sulphate containing fertilisers would effectively supplement modifications of water regimes. Adding fresh organic materials into flooded soils should be avoided in all wetland rice ecosystems. Incorporation into dry soils or composting should be practiced whenever possible. Crop diversification (i.e. sequential cropping of an upland crop in the dry season before or after one or two crops of rice in the wet season) is another feasible option to reduce emissions in line with economic benefits in rice growing areas with year-round irrigation and good access to markets. Common upland crops that are widely grown in rotation with wetland rice are wheat, mungbean, soya bean, maize, and vegetables.
The impact of land use change from natural grassland to pasture or arable land has a drastic effect on CH4 oxidation. The mean reduction in oxidation rate after conversion, calculated for 10 paired sites reported in the literature, was 71% the same outcome as that obtained from the distributions of all values for agricultural and natural sites, respectively (Smith et al., 1999), while the modeled estimate by Del Grosso et al (1999) was 46%. The latter authors attributed the difference between these estimates to differences in the gas diffusivities of the soils examined. Their model was derived from field data on grassland soils, but gives good predictions of oxidation in coniferous and tropical forest soils; however, a separate submodel, which assumes that the maximum rate is a function of bulk density, has proved necessary for deciduous forest soils.
The impact of disturbance on oxidation rate is long-lasting. It has been shown that in the temperate zone at least, recovery of soil oxidation rates to pre-disturbance values takes 100 years or more (Priemé et al., 1997; Fig 10), but nothing is known about the ecological reasons for this. There is evidence that the microorganisms principally responsible for atmospheric methane oxidation differ from those responsible for CH4 oxidation in such environments as landfill cover soils, wetland hummocks, termite mounds and oxidized zones within rice paddy soils, where much higher gas concentrations are the norm (Conrad, 1996).
Figure 10. Increase in rate of soil oxidation of atmosphericCH with time, after reversion of former agricultural land to forest/woodland or grassland. (a) European forest/woodland: Denmark (_), Scotland (O); (b) N. American grassland (_, _), forest (_). (Smith et al., 1999).
1. Biomass burning
1.1. Introduction and history
The first pioneering papers on the impact of biomass burning on the chemistry of the atmosphere were published in the late 1970s and early 1980s (e.g., Crutzen et al., 1979; Radke et al., 1978). Scientific interest in this topic grew when early estimates of pyrogenic emissions suggested that, for some atmospheric pollutants, biomass burning could rival fossil fuel use as a source of atmospheric pollution (Crutzen and Andreae, 1990). Further impetus to study biomass burning came from the discovery that pyrogenic emissions could affect large areas of the world as a consequence of long-range transport (Andreae, 1983; Fishman et al., 1990; Reichle et al., 1986). The investigation of the role of biomass burning in atmospheric chemistry was therefore seen as a high priority when the objectives of IGAC were formulated in 1988.
Since the Biomass Burning Experimental Programme (BIBEX) became active in 1990, research activity in this field has increased dramatically, and, over the last decade, fire has been widely recognized as a major source of important trace gases and aerosol particles to the world atmosphere. The rapid development of this field is reflected in the sharp increase in the rate of publications on biomass burning since that time (Figure 11).
Figure 11. Number of papers with Biomass burning in the title, abstract or keywords. (Embedded in text)
Following well-publicized large fire catastrophes in recent years and intensive scientific efforts over the last decade, the general public as well as the scientific community are now aware that emissions from biomass burning represent a large perturbation to global atmospheric chemistry, especially in the tropics. Satellite and airborne observations have shown elevated levels of O3, CO, and other trace gases over vast areas of Africa, South America, the tropical Atlantic, the Indian Ocean, and the Pacific. Smoke aerosols perturb regional, and probably global, radiation budgets by their light-scattering effects and by their influence on cloud microphysical processes.
We have also learned that the effects of burning reach well beyond the fires themselves, and that vegetation fires have both short- and long-term effects on trace gas emissions from plants and soils. In the case of CO2 and N2O, the effect of burning on post-fire emissions may be more significant than their immediate pyrogenic release. Fire also alters the long term dynamics of the cycling and storage of elements within terrestrial ecosystems, thereby changing their potential as sources or sinks of various trace gases. Finally, deposition of pyrogenic compounds onto pristine tropical ecosystems may affect their composition and dynamics. In the following sections, we will review some of the results and attempt to put them into the larger context of Global Change research.
STARE (Southern Tropical Atlantic Regional Experiment), with its two components SAFARI (Southern Africa Fire-Atmosphere Research Initiative), and TRACE-A (Transport and Chemistry near the Equator) was the first large experiment coordinated by BIBEX. Conducted in 1992, STARE brought together scientists from many countries to investigate the chemical composition, transport and fate of fire emissions originating from South America and southern Africa. The results of this unprecedented international and interdisciplinary experiment were published in a special edition of the Journal of Geophysical Research (Andreae et al., 1996). As a follow-up to SAFARI-92, a much smaller experiment (SA ARI-94) was organized by BIBEX to investigate the composition of trace gases in the troposphere over Africa outside the burning season, and results are being prepared for publication. EXPRESSO (Experiment for Regional Sources and Sinks of Oxidants), designed primarily to investigate the exchange fluxes of trace gases between the tropical biosphere and atmosphere, took place in the Central African Republic and the Republic of Congo in 1996-97. In 1997, AFARI-97 (African Fire-Atmosphere Research Initiative) was carried out in Kenya, investigating the atmospheric effects of fires occurring in the fertile savannas of East Africa. At the same time, an experiment designed to quantify aerosol and trace gas fluxes from the Miombo woodlands of southern Africa was initiated: ZIBBEE (The Zambian International Biomass Burning Emissions Experiment) began in 1997 and is ongoing. At the present time, BIBEX is heavily involved in the planning of two large tropical fire/atmosphere experiments: SAFARI-2000 will investigate the transport and climatic effect of biogenic, pyrogenic and anthropogenic emissions in southern Africa, while LBA (The Large Scale Biosphere-Atmosphere Experiment in Amazonia) is designed to investigate the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia, and the sustainability of development in this region.
In the boreal zone, BIBEX has been involved in the development of research programs addressing the role of fire in circumpolar boreal ecosystems and consequences for the global atmosphere and climate. FIRESCAN (Fire Research Campaign Asia-North) began by conducting of the first joint Russian/western experimental fire in central Siberia in 1993, and continues with the planning of further Siberian fire experiments under the auspices of the IGBP Northern Eurasia Study (FIRESCAN Science Team, 1996). In addition, BIBEX is active in ICFME (The International Crown Fire Modeling Experiment), a series of high-intensity experimental crown fires carried out by international fire scientists in the Canadian Northwest Territories during the 1997-99 period for the purpose of developing a physical model of crown fire initiation and propagation.
Tropical savannas and open seasonal forests: Assessments made in the early 1990s on the average annual amount of savanna phytomass burned were in the range of 3 to 4 Pg yr-1 (Andreae, 1993). Model predictions on the savanna area annually burned ranged between 750x10 6 ha yr-1 (Hao et al., 1990) and 1500x10 6 ha yr-1 (Goldammer, 1993). More detailed studies on fire regimes and fuel loads in Africa point towards lesser amounts of regional and global combustion of savanna phytomass (Menaut et al., 1991; Scholes et al., 1996). Recent and ongoing growth of rural populations and intensity of land use involves landscape fragmentation and competitive utilization of phytomass for grazing and domestic burning (biofuel use) and may represent a reason for a decrease of fire activities in tropical savannas and open forests; desertification in the Sub-Saharan Sahel zone of Africa and other regions leads to a reduction and discontinuity of fuel loads and wildfire occurrence.
Mediterranean and temperate vegetation: Mediterranean forest and shrub vegetation, including Californian chaparral and South African fynbos, are increasingly occupied by spreading sub-urban residential areas. The consequent suppression of natural and human-caused wildfires results in a build-up of fuels that often cannot be burned by prescribed fires. High- intensity wildfires are an inevitable consequence of fire suppression in these ecosystems. However, there is no indication of change in the average area burned in the recent decade. In the industrial countries of the temperate region the application of fire in non-forest land-use systems has been eliminated (e.g., in Europe) or is subject to legal restrictions due to air pollution and traffic risks (e.g. in North America). Natural and human-caused wildfires in temperate forests are usually suppressed. Prescribed burning in forestry has been receiving more attention in the U.S.A. where it is envisaged to expand the prescribed burned area under the jurisdiction of the USDA Forest Service to 1.2x10 6 ha by 2010 (Haines et al., 1998).
Temperate-boreal steppe-forest ecotones: A typical region representing the steppe-forest fire environment is central Asia. Recent remotely sensed data from Mongolia indicate that in the past years political and socio-economic changes in the country were responsible for a sharp increase in the area burned by wildfires. In 1996 and 1997 more than 10x106 ha and 12x106 ha burned in the grass steppes and adjoining coniferous forests (Goldammer, 1999b). Steppe fires so far have received limited attention by the IGAC community.
Boreal forest: More than 70 % of the global boreal forest area is located in Russia. Fire statistics published after the dissolution of the USSR indicate that more than 650,000 ha of forests were burned annually. This number most likely is still an underestimation. In the period 1990-96 burn areas totalling more than 1.12x106 ha yr-1 were recorded (Stocks et al., 1999a; Stocks et al., 1999b). NOAA AVHRR satellite imagery revealed that a large area was burning in central Siberia during the 1987 fire season totaling ca. 10x106 ha (Cahoon et al., 1994). The fire exclusion policy of the USSR certainly had effects on reducing the area burned by natural fires. In the same period, however, an increasing amount of human-caused fires must be noted. Current economic problems resulting in a weakening of the fire control system in Russia are responsible for an increase in area burned.
In Canada, detailed forest fire statistics have been archived since 1920 and, within limits, this extensive record permits a general analysis of trends in this country (Stocks et al., 1999b). Annual fire occurrence, without fluctuating greatly on a year-to-year basis, has increased rather steadily from approximately 6,000 fires annually in the 1930-1960 period, to almost 10,000 fires during the 1980s and 1990s. This reflects a growing population and increased forest use, but is also due to an expanded fire detection capability.
During the 1981-96 period an average of 9,246 fires annually burned over an average of 2.5x106 ha in Canada, with annual area burned fluctuating by an order of magnitude (0.76 million to 7.28 million hectares). Lightning accounts for 35% of Canada's fires, yet these fires result in 85% of the total area burned, due to the fact that lightning fires occur randomly and therefore present access problems usually not associated with human-caused fires, with the end result that lightning fires generally grow larger, as detection and subsequent initial attack is often delayed. A recent evaluation of Canadian fire statistics also identified some of the reasons why Canadian fire impact varies significantly. Sophisticated fire management programs are largely successful at controlling the vast majority of forest fires at an early stage, such that only ~2% of fires grow larger than 200 hectares in size, but these fires account for ~98% of the area burned across Canada. In addition, the practice of "modified" or "selective" protection in remote regions of Canada results in many large fires in low-priority areas being allowed to perform their natural function.
Domestic biofuel use. Plant biomass provides about 14% of the world's demand of primary energy. Half of the global population covers an average of 35% of its energy needs by domestic biomass burning. In Africa, for example, the biomass contribution to the total energy use typically ranges from 80-90% in poor, 55-65% in middle and 30-40% in high income groups. Unlike free-burning vegetation fires, which are usually restricted to a few months during the dry season, domestic biofuel combustion takes place during the whole year.
Summary assessment of trends in global vegetation fire occurrence: The trends of changing fire occurrence and fire regimes are not uniform. Qualitative and quantitative data on fire occurrence and fire effects are still insufficient to reliably determine the amount of phytomass combusted in all ecosystems and land-use systems worldwide. However, improved remote sensing capabilities and rigorous fire detection algorithms now provide regional fuel load estimates within a much narrower range of uncertainty. Fire in boreal and tropical forests and the resulting ecological effects play a potentially critical role in determining the rate of global climate change (Goldammer and Price, 1998; Stocks et al., 1999a; Nepstad et al., 1999). Changes in the carbon balance of these two forest biomes could strongly influence global warming through impacts on atmospheric CO2. The implications of regional circumpolar changes of climate and fire regimes on boreal ecosystem properties, permafrost changes, and the release of gas and carbon stored in organic terrain and ice must be further addressed by research.
| Species | Savanna | Tropical Forest |
Extratropical Forest |
Biofuel | Charcoal burning |
Agricultural Residues |
| CO2 | 1660±90 | 1580±90 | 1620±70 | 1579±80 | 2480±260 | 1570±210 |
| CO | 58±15 | 106±21 | 96±25 | 83±37 | 170±40 | 74±40 |
| CH4 | 2.0±0.6 | 6.9±2.1 | 4.4±1.4 | 4.8±4.0 | 2.4 | 2.7 |
| NMHC | 3.6±1.3 | 8.4±3.6 | 3.3±0.7 | 2.8 | 0.5 | --- |
| acetylene | 0.15±0.08 | 0.36±0.32 | 0.23±0.06 | --- | --- | --- |
| ethene | 0.43±0.27 | 0.63 | 0.30±0.04 | --- | --- | --- |
| ethane | 0.27±0.07 | 0.33 | 0.47±0.18 | --- | --- | --- |
| propyne | 0.015±0.013 | 0.01 | --- | --- | --- | --- |
| propene | 0.21±0.14 | 0.35 | 0.47±0.22 | --- | --- | --- |
| propane | 0.08±0.02 | 0.10 | 0.17±0.08 | --- | --- | --- |
| 1-butene | 0.09±0.06 | 0.08 | --- | --- | --- | --- |
| isobutenes | 0.04±0.01 | 0.13 | --- | --- | --- | --- |
| butadiene | 0.05 | --- | --- | --- | --- | --- |
| n-butane | 0.020±0.007 | 0.026 | 0.04±0.04 | --- | --- | --- |
| i-butane | 0.007±0.002 | 0.009 | 0.02 | --- | --- | --- |
| 1-pentene | 0.09±0.09 | 0.29 | --- | --- | --- | 0.043 |
| n-pentane | 0.01±0.01 | 0.009 | --- | --- | --- | --- |
| 2-methyl-butene | 0.06 | 0.38 | --- | --- | --- | 0.003 |
| 2-methyl-butane | 0.015±0.015 | 0.005 | --- | --- | --- | --- |
| isoprene | 0.006 | 0.01 | --- | --- | --- | --- |
| cyclopentene | 0.02 | --- | --- | --- | --- | --- |
| 4-methyl-1-pentene | 0.25 | 0.25 | --- | --- | --- | 0.09 |
| 1-hexene | 0.15±0.15 | 0.40 | --- | --- | --- | 0.081 |
| n-hexane | 0.02 | --- | --- | --- | --- | --- |
| octenes | 0.065 | 0.10 | --- | --- | --- | 0.30 |
| benzene | 0.46±0.46 | 1.4±1.4 | --- | --- | --- | 0.90 |
| toluene | 0.33±0.30 | 0.9±0.9 | --- | --- | --- | 0.19 |
| xylenes | 0.06±0.03 | 0.08±0.04 | --- | --- | --- | 0.03 |
| ethylbenzene | 0.04±0.04 | 0.07±0.06 | --- | --- | --- | 0.03 |
| 1-propanol | 0.03 | --- | --- | --- | --- | --- |
| butanols | 0.03 | 0.04 | --- | --- | --- | 0.05 |
| cyclopentanol | 0.16 | 0.16 | --- | --- | --- | 0.09 |
| phenol | 0.02 | 0.04 | --- | --- | --- | 0.01 |
| formaldehyde | 0.36±0.14 | --- | --- | --- | --- | --- |
| acetaldehyde | 0.59±0.43 | --- | --- | --- | --- | --- |
| butanals | 0.22 | 0.27 | --- | --- | --- | 0.09 |
| hexanals | 0.15 | 0.18 | --- | --- | --- | 0.07 |
| heptanals | 0.01 | 0.03 | --- | --- | --- | 0.006 |
| benzaldehyde | 0.18 | 0.17 | --- | --- | --- | 0.056 |
| acetone | 0.62 | --- | --- | --- | --- | --- |
| pentanones | 0.11 | 0.16 | --- | --- | --- | 0.04 |
| heptanones | 0.04 | 0.01 | --- | --- | --- | 0.02 |
| octanones | 0.12 | 0.16 | --- | --- | --- | 0.001 |
| furan | 0.56 | --- | --- | --- | --- | --- |
| 2-methyl - furan | 0.30±0.06 | 0.88 | --- | --- | --- | 0.06 |
| 3-methyl - furan | 0.06 | 0.15 | --- | --- | --- | 0.015 |
| 2-ethylfuran | 0.01 | 0.02 | --- | --- | --- | 0.003 |
| 2,4-dimethyl- furan | 0.05 | 0.14 | --- | --- | --- | 0.015 |
| tetrahydrofuran | 0.07 | 0.07 | --- | --- | --- | 0.024 |
| 2,3- dihydrofuran | 0.05 | 0.06 | --- | --- | --- | 0.021 |
| benzofuran | 0.11 | 0.13 | --- | --- | --- | 0.034 |
| acetonitrile | 0.07 | --- | --- | --- | --- | --- |
| H2 | 0.78±0.05 | 3.8±0.3 | 1.9±0.6 | --- | --- | --- |
| NOx (as NO) | 2.3±0.9 | 1.5±1.1 | 3.0±1.5 | 3.6±3.4 | 3.9 | 2.4±1.1 |
| N2O | 0.17±0.08 | --- | 0.27±0.09 | --- | --- | 0.07 |
| NH3 | 0.8±0.3 | --- | 1.0±0.5 | --- | --- | --- |
| HCN | 0.023±0.10 | --- | --- | --- | --- | --- |
| SO2 | 0.35±0.16 | 0.57±0.23 | --- | 0.1 | --- | --- |
| COS | --- | --- | 0.04 | --- | --- | 0.09±0.09 |
| CH3Cl | 0.066±0.027 | 0.05±0.05 | 0.05±0.04 | --- | --- | 0.12 |
| CH3Br | 0.019±0.005 | 0.005±0.003 | 0.003±0.002 | --- | --- | --- |
| CH3I | 0.001±0.001 | 0.004 | --- | --- | --- | --- |
| TPM | 6.9±0.7 | 8.5±2.9 | 18.0±6.8 | 10±8 | --- | --- |
| PM (<2.5µm) | 4.3±0.7 | 9.1±1.5 | 13.8±5.4 | --- | --- | --- |
| OC | 3.7±1.5 | 5.2±1.5 | 8.6 | 4.9 | --- | 3.3 |
| BC | 0.46±0.18 | 0.84±0.23 | 0.66±0.05 | 1.0±0.6 | --- | 0.7 |
| K | 0.33 | 0.11 | --- | --- | --- | 0.43 |
| Crutzen & Andreae, 1990 |
Andreae 1993 |
Hao & Liu 1994 |
Liousse et al., 1996 |
Lobert et al. 1999 | |
| Tropical forest Extratropical forest Savanna & grassland Domestic biomass fuel Agricultural waste TOTAL |
1560 - 3800 --- 670 - 3600 670 - 1300 1100 - 1800 4000 - 10400 |
1260 1150 3690 1960 850 8910 |
1820 --- 2670 620 280 5390 |
1260 --- 2680 1380 300 (5620) |
1330 640 3160 1950 1190 8260 |
1.7. Detection of fires and burned area by remote sensing
First order estimations of trace gas and particulate emissions from biomass burning involve multiplying the area burned by the amount of fuel consumed taking into account the emission factors for the gases and particulates (Crutzen et al., 1990). More detailed estimates take into account other controlling variables such as wind speed, fuel moisture content and fire intensity. Reporting of national estimates of anthropogenic trace gas emissions are a requirement of the Framework Convention on Climate Change and the IPCC provides guidelines for these emissions calculations (Callander, 1995). For many parts of the world however, national emissions estimates from biomass burning are based largely on expert opinion or summary statistics and the resulting accuracies are largely unknown. 1.8. Impacts of burning on trace gas exchange from soils
The process of biomass burning represents a vast reallocation of nutrients in cleared tropical forest and savanna systems. Large proportions of system carbon, nitrogen and sulfur are volatilized. Soils are affected by changes in nutrient levels, pH and temperature, with associated changes in microbial communities. Studies conducted during the SAFARI campaign showed that after burning the mean NO emissions from dry sites increased and ranged from 13.3 to 15.2 ng N m-2 s-1 and the wetted sites increased, exceeding 60 ng N m-2 s-1 ( Levine et al., 1996). The effect of excluding fire from a savanna is to increase the soil nitrogen content through increased litter inputs, which in turn increases nitrification rates and soil NO emissions (Parsons et al., 1996). Increases in soil emissions of CO2 and CO were increased by an order of magnitude after burning, whereas exchange of CH4 was not affected. In all cases the increases were short lived and dropped back to pre-burn levels within a few days (Zepp et al., 1996). Studies on the impact of burning on soil carbon pools showed that annual burning in a semi-arid savanna reduced the light fraction carbon markedly but did not impact the intermediate or passive carbon pools. This has implications for the amount of soil carbon, which can be readily metabolized by the soil microorganisms. Burning the savannas at longer time intervals in no way changed the pool size or the turnover rates of the various soil carbon pools (Otter, 1992).
1.9. Importance to atmospheric chemistry and climate
We have already pointed out that biomass burning is a significant source of several greenhouse gases, among them CO2, CH4, and N2O. It also makes important contributions to the budget of several gases of stratospheric importance, such as methyl chloride and methyl bromide, N2O, and COS. Of particular importance to the chemistry and radiative characteristics of the atmosphere are the emissions of ozone precursors, particularly NOx and NMHC. Because vegetation fires can occur only when the vegetation is dry enough to burn, fires are most abundant in the dry season, when the trade wind inversion with its large-scale subsidence prevails over the part of the tropics in question. Because this inversion prevents convection to heights of more than a few kilometers, it was initially thought that the linkage between dry conditions and subsidence more or less precluded the transport of pyrogenic ozone precursors to the middle and upper troposphere. Recent work has shown, however, that large amounts of smoke can get swept by low-level circulation, e.g. the trade winds, towards convergent regions over the continents or the ITCZ, and there become subject to deep convection (Andreae et al., 2000; Chatfield et al., 1996; Thompson et al., 1996). This transport pattern can explain the abundance of fire-related O3 and O3-precursors observed in the middle and upper troposphere by remote sensing and in-situ measurements (Browell et al., 1996; Connors et al., 1996; Olson et al., 1996). The exchange of inert and sparingly soluble gases including carbon dioxide, oxygen, methane, and DMS between the atmosphere and oceans is controlled by a thin 20 200 µm thick boundary layer at the top of the ocean. Laboratory and field measurements show that wind waves significantly increase the gas transfer rate and that it is significantly influenced in this way by surfactants. The mechanisms are still understood only marginally. Empirical gas transfer rate/wind speed relations imply an uncertainty of a least a factor of two. B. Measurements and intercomparisons: The examples of DMS and SO2
(Note: This section might be combined with an equivalent one in Terrestrial and/or go into the Technical Annex on Advances in measurement methods for atmospheric chemistry ) 1. Measurements of DMS and its oxidation products in remote marine environments.
DMS has been shown in the laboratory to oxidize via two separate chemical routes, both initiated by the OH free radical (Hynes et al. 1986). An abstraction channel is thought to proceed directly to SO2 while an addition channel leads to more complex products such as dimethyl sulfoxide (DMSO) and dimethyl sulfone (DMSO2). Each can lead to the formation of H2SO4 and aerosol formation and growth. The chemical sequences are complex and the major pathways cross one another (Berresheim et al. 1995). The abstraction rate increases with increasing temperature while addition decreases, so the overall temperature dependence is complex. 2. Comparisons of sulfur compound measurement methods
A meaningful test of the predictions of models of atmospheric chemistry can only be accomplished if field measurements operate at appropriately low limits of detection (LOD) and have quantitatively determined accuracy. In the remote troposphere, mixing ratios of sulfur compounds are very low, ranging from a few part-per-trillion by volume (pptv) to perhaps 100 pptv. For this, commercially available instrumentation is unavailable, so establishing LOD and accuracy is a major effort. This has been accomplished by instrument comparisons; in the case of sulfur compounds, these have been performed in a blind fashion. C. Global climatologies and modeling
(Note: May be joint with Terrestrial) D. Marine biogenic emissions: A few examples
Dimethylsulfide (DMS) was discovered in ocean waters some 30 years ago by Lovelock et al. (1972). However, it remained a compound of marginal scientific interest for about a decade, until it was established that DMS is the main volatile sulfur species emanating from the oceans and therefore plays a major role in the atmospheric sulfur cycle (Nguyen et al., 1978; Barnard et al., 1982; Andreae and Raemdonck, 1983; Bates and Cline, 1985). Interest in the biogeochemical cycle of DMS again increased sharply thirteen years ago, when Charlson et al. (1987) proposed a hypothesis linking biogenic DMS emission and global climate. In short, this hypothesis states that DMS released by marine phytoplankton enters the troposphere and is oxidized there to sulfate particles, which then act as cloud condensation nuclei (CCN) for marine clouds. Changes in CCN concentration affect the cloud droplet number concentration, which influences cloud albedo and consequently climate. Large-scale climate change, in turn, affects the phytoplankton number and speciation in the oceans and thereby closes a feedback loop. A recent assessment of the DMS-climate link can be found in Watson and Liss (1998). 1.2. Physiological and ecological controls of DMS production
Improved understanding of what controls DMS production in the euphotic zone of the ocean has come from field manipulations (i.e. Fe fertilization coupled with Lagrangian time series), ocean time series, and use of large scale mesocosms (REF). New methods, including use of 35 S tracers, improved inhibitors, and molecular genetics techniques have allowed ever more sensitive analyses of DMSP/DMS cycling rates and fates, and have permitted more detailed examination of the complex microbial communities involved (REF). Along these lines, more isolates of bacteria and other organisms are available with which to study biochemical pathways and physiology of DMSP and DMS metabolism (REF). The pathways of DMSP biosynthesis in phytoplankton have been studied in detail and have shed light on potential regulating mechanisms such as nitrogen nutrition (REF). Modeling efforts have expanded our understanding of DMS production, both for field situations (REF) and laboratory systems (REF). In addition, the potential role of marine viruses (REF) and photochemistry (REF) in the overall biogeochemistry of DMSP/DMS is now appreciated. 1.3. DMS and aerosols
(Note: this section may be removed pending comparison with Ch. 4 Aerosols) 2. The marine source of carbonyl sulfide (COS)
Carbonyl sulfide (COS) in the atmosphere originates predominantly from the outgassing of the upper ocean, atmospheric oxidation of carbon disulfide, and biomass burning (Chin and Davis, 1993). With the longest tropospheric lifetime of all atmospheric sulfur species, COS can reach the stratosphere where it is oxidized to sulfate particles, which may impact the radiation budget of the Earth's surface (Crutzen, 1976) and influence the stratospheric ozone cycle. The oceans represent approximately 30% of the total atmospheric source of COS, and much of the oceanographic work on COS over the last decade has focussed on assessing the spatial and temporal distributions of COS concentration and understanding the processes which control its temporal and spatial distribution. 3. Ammonia
Ammonia is the dominant gas phase basic species in the marine atmosphere and, as such, has a unique influence on marine multi-phase atmospheric chemistry. It can impact the formation of new particles by lowering the vapor concentration of other gases required for the initiation of particle nucleation (Weber et al., 1998). If the resulting particles grow to a large enough size, they will act as CCN and will contain sulfate neutralized to some extent by ammonia. The pH of the cloud droplets formed on these CCN determines the reaction rates of many aqueous phase reactions. In addition, the degree of neutralization of sulfate aerosol by NH3 (g) affects the growth response of particles to changes in relative humidity. Since light scattering by aerosol particles is determined in part by particle size, NH3 (g) will influence the scattering efficiency of the aerosol by adding particulate mass and by changing its hygroscopic properties (Charlson et al., 1999). Finally, long range transport of ammonium-containing aerosols followed by deposition in rainfall may redistribute marine ammonia (Zhuang and Huebert, 1996) and affect oceanic biological productivity. 4. Nitrous oxide
The world oceans represent a significant natural source of nitrous oxide (N2O) to the atmosphere. The surface waters of many oceanic regions are supersaturated in N2O with respect to solubility equilibrium with the atmosphere, giving rise to a net air-sea gas exchange flux of N2O to the atmosphere. N2O is produced in subsurface waters both as an intermediate of denitrification, the reduction of nitrate ion (NO3- ) to nitrogen (N2), and as a trace byproduct of nitrification, the oxidation of ammonium ion (NH4+ ) to NO3- . Denitrification occurs under suboxic to anoxic conditions, and is thought to take place mainly in restricted low-oxygen regions such as the eastern tropical Pacific and the Arabian Sea, and in the sediments of continental shelves. The distribution of nitrification is thought to be more widespread, since it occurs under aerobic conditions in association with the internal recycling of fixed nitrogen. 5. The ocean s role as source and sink of atmospheric methyl bromide and other methyl halides.
Methyl halides are produced and consumed biologically (CH3Br- Moore and Webb 1996, Baker et al. 1999; CH3I- Moore and Groszko 1999) and photochemically (CH3I- Happell and Wallace 1993(1996); CH3Cl- Moore et al. 1996) in surface ocean waters. Recent measurements have shown that the flux of CH3Cl is significantly less than early estimates (Moore et al. 1996) and that the open ocean is a net sink, rather than a source, for CH3Br (see below). 6. Non-methane hydrocarbons (NMHC)
NMHC are produced in surface seawater possibly by photochemical mechanisms, phytoplankton activity and/or microbial breakdown of organic matter (Plass-Dulmer et al. 1995, Ratte et al. 1995, Broadgate et al. 1997). Oceanic concentrations show a strong seasonal cycle (Broadgate et al. 1997). The ocean-atmosphere flux is dominated by alkenes and is small compared to terrestrial emission estimates (<1%). However, the emissions may be significant on local scales considering the short lifetimes of the unsaturated species (Donahue and Prinn 1993, Pszenny et al. 1999). Additional seasonal measurements of isoprene, ethane, and propene are needed in different oceanic regions.
7. Methane
The ocean is a small source of methane to the atmosphere. Open Pacific Ocean saturation ratios (ratio of seawater CH4 partial pressure to the overlying atmospheric CH4 partial pressure) range from 0.95 to 1.17. Large areas of the Pacific Ocean are undersaturated with respect to atmospheric CH4 partial pressures during the fall and winter. On a seasonal time scale, the driving force controlling saturation ratios outside the tropics appears to be the change in sea surface temperature. Saturation ratios in the equatorial region have always been positive and appear to be driven by the strength of the equatorial upwelling. Extrapolating the Pacific data globally and regionally into 10 zones, the calculated average flux of CH4 to the atmosphere is 25 Gmoles y-1 (13 to 38 Gmoles y-1 ) (Bates et al. 1996). This is approximately an order of magnitude less than previous estimates, which lacked fall and winter data. Thus the open ocean is a very minor source of methane to the atmosphere (<0.1%) compared with other sources (IPCC 1994). However, the coastal ocean and marginal seas appear to be a much larger source (Owens et al. 1991, Kvenvolden et al. 1993, Bange et al. 1994, Lammers et al. 1995) due to CH4 emissions from bottom sediments and definitively warrant further 9 investigation.
8. Carbon monoxide
The ocean is ubiquitously supersaturated with CO with respect to the atmosphere, resulting in a net flux to the atmosphere ranging seasonally and regionally from 0.25 to 13 ?moles/m2/d. However, the total annual emission to the atmosphere (13 Tg) is small compared to current estimates from both terrestrial natural and anthropogenic sources (2400 Tg CO/yr). Even in the Southern Hemisphere, which accounts for 2.3 of the oceanic emissions, the ocean source is relatively small (<1%), since both methane oxidation and biomass burning are large sources of CO (Bates et al. 1995).
E. Biological and chemical impacts of atmospheric deposition on marine and estuarine systems: Two case studies.
1. The input of atmospheric iron to the ocean and its role in marine biogeochemistry It is now recognised that a primary transport path for iron found in the ocean is through the atmosphere. Among the first papers to address the importance of atmospherically derived iron were those of Moore et al. (1984) and Duce (1986), who calculated that in many areas of the ocean the eolian transport of mineral matter into the ocean, with subsequent dissolution of some fraction of the iron from the mineral matter into sea water when the dust was deposited directly on the ocean surface. This topic was reviewed by Duce and Tindale (1991) and, more recently in a thorough analysis, by Jickells and Spokes (2000). 1.2. Sources and transport of mineral aerosol to the oceans
The primary sources of mineral aerosol are arid and semi-arid continental regions (e.g., Tegen and Fung 1994, Houghton et al. 1996, Duce 1995). A description of production and transport mechanisms can be found in Chapter 4. The atmospheric concentrations of dust and the deposition of dust to the ocean surface are both very episodic and are primarily associated with the transport of aerosol from dust storms or major dust outbreaks. For example, half of the annual deposition of dust to the ocean at Midway Island in the central Pacific occurred during only two weeks (Prospero et al. 1989). The typical duration of such dust pulses over the ocean may range from one to four days, and the transport and deposition may also vary seasonally. In many regions, long-range transport of the mineral matter takes place in the upper troposphere, often up to 5 km over the North Atlantic and 8 km over the North Pacific (Schutz et al. 1990; Merrill 1989; Prospero 1995). After a relatively stable size distribution has been attained, it appears that the primary removal process for dust is rain rather than dry deposition (Duce 1995). Due to the episodic character of both the atmospheric dust concentrations and local rainfall, input to the ocean in a particular region can often occur during a few events covering a relatively short period of time. In Bermuda, Arimoto et al. (1992) found that mineral aerosol concentrations ranged over four orders of magnitude, from 0.001 to 1 gm-3 . 1.3. Iron in mineral aerosol over the oceans
The atmospheric deposition of iron is associated with the eroded mineral aerosol particles, and the iron is primarily bound in the aluminosilicate matrix. It is thus possible to convert mineral aerosol concentrations or fluxes to an iron concentration or flux by knowing the abundance of iron in the earth's crust. This ranges from ~3 to 5% (Taylor and McClennan 1985). Typically a value of 3.5% is used (Duce and Tindale, 1991). With a mineral aerosol flux of 500-2000 Tg yr-1 , the input of iron would be approx. 15-100 Tg yr-1 . However, before the atmospheric deposited iron can be utilised by phytoplankton must be in a form that is available to these organisms. Processes that change the solubility or lability of the iron in the atmosphere will then have potential for influencing the availability of the iron when the atmospheric material enters the ocean. Jickells and Spokes (2000) have carefully reviewed the information to date on the mechanisms that may control the dissolved/particulate distribution of iron in the material entering the ocean from the atmosphere. Some studies have observed Fe (II) in aerosol iron and its formation is postulated to occur via photochemical reduction of Fe (III) hydroxides. Certain organic species such as oxalate, acetate, and formate can facilitate this photoreduction. It has been suggested by several authors that the low pH (0-5) in the cloud cycling process, to produce acidic hygroscopic aerosols, combined with possible photochemical reactions results in an increase in the lability of crustally derived metals, such as iron, in the atmosphere over that seen in the parent material. In turn, this will play a factor in the availability of the iron when the aerosol enters the ocean (e.g., Andreae et al. 1981, Jickells and Spokes 2000; Zhu et al. 1992). This increase in lability influences the subsequent solubility of aeroso metals on wet or dry deposition to seawater. In addition, high ionic strength solutions and alternating wet and dry cycles during cloud formation and evaporation would be common. There are likely many such cycles before the particles are ultimately removed by dry deposition or precipitation. 1.4. Iron and marine biogeochemistry
Once the atmospheric iron has entered the oceans by either wet or dry deposition, it is hypothesised to play potentially important roles in the primary productivity of surface waters in some areas remote from land. These HNLC regions are estimated to cover 20-25 % of the area of the oceans, i.e a (highly) significant proportion of the surface of the globe. In this section we review some of the approaches that have been taken to study this phenomenon. An up to date and detailed assessment of the chemical form of iron in seawater and how this relates to its uptake by marine organisms is to be found in several chapters in the book edited by Turner and Hunter (2000). 2. Nitrogen deposition on estuarine ecosystems: A Case Study, the Pamlico Sound System, North Carolina, USA.
The sensitivity and response of receiving estuarine and coastal waters to specific N inputs vary along longitudinal salinity gradients. In an estuary's predominantly fresh headwaters, riverine (terrigenous) discharge dominates new N inputs. Further downstream, in mesohaline segments of the estuary and open sound, significant fractions of the terrigenous N load are usually assimilated by phytoplankton and benthic flora, or are microbially denitrified to biologically unreactive N2 gas (Kennedy 1983, Nixon 1986, Seitzinger 1988). Inputs of N that result from direct atmospheric deposition (AD), however, can by-pass this estuarine N filter (Kennedy 1983, Paerl 1995, 1997). As such, AD assumes an increasingly important role as a new N source in lower estuarine, sound and coastal waters below the biological N filtering zone (Figure 18). The role of AD in estuarine nutrient and primary productivity dynamics has recently been examined in North Carolina s Albemarle Pamlico Sound System (APSS), the Nation's 2nd largest estuarine system and largest lagoonal estuary in North America (Paerl 1995, 1997). F. Paleorecord of past marine biogenic emissions: The example of MSA in polar ice cores
Global DMS emissions may be modulated by climatic conditions. Could global warming trigger a change of marine biogenic activity and consequently of DMS emissions? Man-induced atmospheric changes could also disturb the oxidation processes of DMS and modify the branching ratio of the MSA and nssSO4 formation. Ice core studies may help to elucidate these questions, provided that DMS or at least a DMS-related species is recorded in polar ice. In this regard, MSA has been considered as the most promising parameter to determine in polar ice cores. Over the last decade, a few firn and ice cores have been analysed in detail for MSA and nssSO4, in the hope of finding a correlation between concentrations in ice and climate fluctuations on various time scales. Some interesting results have been obtained, but glaciological phenomena have been pointed out recently that obscures the interpretation of the data.
Synoptic fire information derived from satellites provides a source of information for augmenting available national fire statistics. Satellite detection of active fire occurrence has been used to identify the timing and location of fires and has been used in emission product transport studies, for example. The first global data set of annual satellite fire distributions was developed directly as a contribution to BIBEX (Stroppiana et al., 1999). Since that time, both polar orbiting and geostationary satellite systems have been used to provide other fire information (Elvidge et al., 1996; French et al., 1996; Prins et al., 1998).
Automated algorithms for direct estimation of burned area are currently under development with the intent of providing direct input to emissions modeling (Roy et al., 1999). Satellite based techniques for direct estimation of emitted energy, fire intensity, atmospheric aerosol loading and vegetation recovery are also being developed. As in most cases the data products are to be used in numerical modeling, there is a need to provide a quantitative assessment of their accuracy. For satellite products, validation using independent data sources needs to be undertaken to determine product accuracy.
New satellite systems are planned for launch, which will improve our current fire monitoring capability (e.g., Kaufman et al., 1998b). The requirements for these systems come in part from the experience gained from the BIBEX experiments. The satellite fire research community is working to secure the necessary long-term fire observations from the next generation of operational satellite systems, such as the US National Polar Orbiting Environmental Satellite System (NPOESS).
With the operational availability of satellite derived fire information on the location and timing of fires and on the area burned, it will be feasible to run an improved class of models to estimate emissions on an annual basis. These improved models will require ground based estimates of emission factors and modeled estimates of fuel load and fuel consumed for a given year, rather than representative values for a given vegetation type. As new satellite information becomes available on fire intensity, emitted energy and fuel moisture content, these first order emissions estimates can be improved. Providing robust models that can be used for operational generation of annual emissions estimates and developing approaches to validate them provides the next challenge for the fire and global change research community.
The aerosols from biomass fires, the most obvious and visible sign of pyrogenic air pollution, may have an important impact on climate. Biomass burning is the second largest source of anthropogenic submicron aerosol (after sulfates from fossil fuel combustion), and possibly the largest source of black carbon particles. These aerosols influence climate and the hydrological cycle by scattering and absorbing solar radiation, and by changing the properties of clouds in ways that are just now being elucidated (Hobbs et al., 1997; Kaufman et al., 1998a; Ramanathan et al., 2000). Further characterization of the radiative and cloud-nucleating properties of pyrogenic aerosols and their effect on regional and global climate remains a major challenge to the scientific community.
Whether impact of biomass burning will grow in the future depends both on climate change and on human factors. The amount of fuel available for burning at a given place and time is a function of ecological factors, e.g., soil fertility, precipitation, and temperature. It also depends on land use, i.e., if the area has been burned previously, is used for grazing or agriculture, and so on. If climatic variations become more extreme, as climate models have suggested, we can expect a more frequent occurrence of drought years following very wet years. This would result in large amounts of fuel ready to burn in the fire season. Furthermore, in a warmer climate, fire frequency is likely to increase, which would reduce biomass carbon storage by changing the age class structure of vegetation, as well as causing increased emissions of ozone precursors. To monitor the regional and global evolution of pyrogenic emissions, it would be very useful to develop unique tracers for biomass burning, and to set up continuous measurements of these tracers at selected sites.
Human activities are of central importance to the frequency and severity of biomass fires. If large parts of the humid tropics are further deforested, they will transition from a biome essentially free of fires (the tropical rainforest) to biomes with much more frequent fires (grazing lands, agricultural lands, and wastelands). With a higher human population density, the frequency of ignition will go up as well. And finally, the amount of biomass burned for cooking and domestic heating, already a major source of emissions in tropical countries, will increase further. To follow these changes, we will need to further develop and validate techniques to determine the spatial and temporal distribution of biomass burning and the amounts of biomass burned in the various fire regimes.
III. Marine highlights
A. Air-water gas exchange parameterization
The transfer across the boundary layer at an interface shows characteristic mean properties that can be described by a transfer velocity k, a boundary layer thickness z, and time constant t. The flux density divided by the concentration difference between the surface and the bulk at some reference level is defined as the transfer velocity k (also known as the piston velocity o transfer coefficient). The solubility is another key parameter of air - water gas transfer. A high solubility shifts control of the transfer process to the gas-phase boundary layer, and a low solubility to the aqueous layer. The solubility value for a transition from air -sided to water -sided control depends on the ratio of the transfer velocities. For all sparingly soluble gases only the water -sided process is relevant (Fig.12). Only a few environmentally important species lie in a transition zone where it is required to consider both transport processes. For reactive gases, as for SO2, the high transfer resistance in the water is shortcut by the chemical reaction, and the transfer of SO2 is controlled, as water vapor, on the air side (compare SO2 only physically dissolved at a low pH with SO2 at pH=6 in Fig.12).
Figure 12. Schmidt number /solubility diagram including various volatile tracers, momentum, and heat for a temperature range ( °C) as indicated. Filled circles refer to only a temperature of 20 °C. The regions for air -sided, mixed, and water -sided control of transfer process between the gas and liquid phase are ma ked. At the solid lines the transfer resistance is equal in both phases. The following dimensional transfer resistances were used: ra = 31, rw = 12Sc 2/3 (smooth), rw = 6.5Sc 1/2 (wavy surface) with ra = Ra u* a and rw = Rw u* w . After Jähne (1982) and Jähne and Haußecke (1998).
The intensity of turbulence determines the transfer resistance. The more intense the turbulence is, the thinner the boundary layers are. At the scales of the viscous boundary layer, turbulence is strongly attenuated by viscous forces. Thus, the turbulent diffusivity must decrease much faster to zero at the interface than the linear decrease found in the turbulent layer. A free water surface is, however, not solid, nor is it smooth as soon as short wind waves are generated. On a free water surface velocity fluctuations are possible that make convergence or divergence zone at the surface possible. A film on the water surface, however, creates pressure that works against the contraction of surface elements. This is the point at which the physicochemical structure of the surface influences the structure of the near -surface turbulence as well as the generation of waves. As at a rigid wall, a strong film pressure at the surface maintains two-dimensional continuity at the interface.
The significant influence of surfactants from oceanic conditions has been verified by Goldman et al. (1988) and Frew et al. (1990). The effect of surface films on the boundary layer processes is also discussed in detail in the GESAMP report (1995).
Given the lack of knowledge, all theories (for a recent review, see e. g., Jähne and Haußecke, 1998) about the enhancement of gas transfer by waves are rather speculative. Even worse, by just measuring the transfer rates and the wave parameters the current state of the art it is impossible to verify one of these models conclusively. At high wind speeds, wave braking with the entrainment of bubbles enhances gas transfer further. The uncertainties of this phenomenon are also large; less soluble gases are affected most (Keeling, 1993; Woolf, 1993).
A collection of field data is shown in Fig. 13. Although the data show a clear increase of the transfer velocity with wind speed, there is significant scatter in the data that can only partly be attributed to uncertainties and systematic errors in the measurements. The gas transfer velocity is not simply a function of the wind speed. The scatter mainly reflects the additional influence of the wind wave field, which may vary with all parameters that modify the microturbulence in the boundary layer such as the viscoelastic properties of the surface films present and the wind wave field.
Figure 13. Summary of gas exchange field data normalized to a Schmidt number of 600 and plotted vs. wind speed with two empirical relationsships. Sources of data: 14C: Broecker et al. (1985), Broecker et al. (1986), and Cember (1989), SF6 / 3 He: Watson et al. (1991), Wanninkhof et al. (1993), 222Rn: Emerson et al. (1991), Glove & Reeburgh (1987), Kromer & Roethe (1983), Peng et al. (1979), Peng et al. (1974), Smethie et al. (1985), heat: Haußecke (1996), empirical relationships: Liss and Merlivat (1986), Wanninkhof (1992).
Part of the data shown in Fig. 13 is based on geochemical trace methods such as the 14C, 3He/T, or 222Rn/226Ra methods. The transfer velocities obtained in this way are only mean values. Thus a parameterization is only possible under steady state conditions over extended periods and questionable under intermittent conditions. The changes of the parameters (e. g. wind speed) are some orders of magnitude faster. Thus mass balance methods are not suitable for a study of the mechanisms of air -water gas transfer. This is also true for the trace injection techniques pioneered by Wanninkhof et al. (1985, 1987). Progress in the better understanding for the mechanisms of air - water gas exchange has been hindered by inadequate measuring technology. Promising new techniques are now available (Jähne and Haußecke , 1998) but still no systematic measurements using them. Thus empirical gas exchange/ wind speed relationships (compare Fig. 13) have still to be applied with caution since they have an uncertainty of at least a factor of two.
The biogenic origin of DMS and it relationship to cloud nuclei formation 6 and hence radiative forcing and climate change, has been well established (Andreae and Crutzen 1997). However, despite many laboratory and field measurements devoted to the topic, the chemical pathway of oxidation of DMS to form clould nuclei is far from fully understood; gaps and controversies still exist, and there seemed to be even direct contradictory evidence in our knowledge prior to 1995 (Berresheim et al. 1995). Recent measurements, particularly in the remote Pacific marine environment, have further illuminated these topics. To ensure accurate measurements to compare with models, sulfur compound instrument intercomparison campaigns have been undertaken.
Early measurements provided various conflicting conclusions. In the north Pacific, DMS produced SO2 with very little yield and with no diurnal variation (Bandy et al. 1992). In the north Atlantic, DMS was oxidized in the MBL but SO2 was controlled by advection of polluted air (Blomquist et al. 1996). Airborne instruments on the PEM West A in the central Pacific found convection was again important for SO2 (Thornton et al. 1996); PEM West B showed the same for polluted air from East Asia (Andronache et al. 1997). Ground-based measurements in very clean MBL air on Christmas Island (Bandy et al. 1996) showed anticorrelation in the diurnal variation between DMS and SO2, establishing this pathway for these conditions. 62% of the DMS in the MBL was oxidized to SO2; contradiction with earlier measurements can be explained by temperature differences. SCATE was performed in 1994 in Antartica (Davis et al. 1998). Importantly, a new instrument was added, capable of determining both H2SO4 and DMSO2 simultaneously, or OH, H2SO4, and MSA simultaneously. The addition of OH was a major advance, because measured, not estimated, OH could be used for interpretation. H2SO4 was likely formed by reaction of OH with precursors, including SO2 in the layer above the MBL and DMS in the free troposphere. About 60% of SO2 is formed by OH oxidation of DMS.
PEM Tropics A in the southeastern Pacific in 1996 was the first fully comprehensive set of relevant chemical species measurements including OH (Davis et al. 1999). In a single air parcel, DMS and SO2 diurnal profiles clearly anticorrelated, with a 72% conversion efficiency; and H2SO4 was produced by the reaction sequence initiated by OH with SO2. A model constrained by and compared to observations produces more detailed conclusions.
A first comparison, CITE-3, was airborne, off the coast of north and south America, summer 1989, in regions of both high and low mixing ratios of various sulfur compounds (Hoell et al. 1993). Comparisons with standards, performed on the ground, were favourable. In the second phase, instruments were compared in the air. In the case of all but one sulfur species, the airborne results were also in agreement. For DMS, six instruments agreed to within 10- 20% below about 50 pptv. H2S was determined by three instruments to within 5 pptv, often below 25 pptv. COS varies little in the troposhere; over a range of 420 to 580 pptv, each of three instruments agreed to within 5% of their average. CS2, typically present in the MBL between 1-2 pptv, could only be measured by one instrument at these low levels. Measurements of SO2 were in sharp constrast. Five different techniques were tried for this compound. Whereas measurements are needed at mixing ratios < 50 pptv, there was no meaningful correlation among any pair below 200 pptv. It was concluded that SO2 could not be reliably determined for remote tropospheric purposes.
A second blind, ground-based comparison, known as GASIE (Stecher et al. 1997), was devoted to SO2 and involved seven different methods. Most tests were performed by sampling SO2 from a common delivery system at mixing ratios from 20 to 500 pptv, plus blanks, and with interferents added: H2O; NOx + O3; and CO2 + CH4 + DMS + CO. Diluted ambient air was also used over a two-day period. Six of the seven instruments compared well, although one suffered from small amounts of H2O interference. One instrument correlated well but was biased high, suggesting a calibration issue. All six instruments could distinguish mixing ratios of 0 pptv from 40 pptv, and four could distinguish among 0, 20, and 40. Typical run to run precison was a few pptv plus a few per cent.
The seventh instrument tested in GASIE suffered badly from H2O vapour interference, later addressed by addition of a NAFIONä dryer. This instrument was retested against the standard delivery system in GASIE 2 (Crosley et al. 1999), using the same protocol as in the original GASIE. Now, interference problems were null except for a small residual (~10 pptv) problem with H2O. From day to day, the instrument/delivery combination can distinguish among 0, 30, and 60 pptv, but on a given day differences of 20 pptv can be discerned. Of course, both these ground-based GASIE experiments do not certify airborne operation because the inlets are different, and SO2 instruments should be compared in flight. New instruments have since been developed and future, field comparisons will be a valuable effort.
The Global Emissions Inventory Activity (GEIA) (www.onesky.umich.edu/geia/), a component of IGAC, was created in 1990 to develop and distribute scientifically sound, policy-relevant of gases and aerosols emitted into the atmosphere from natural and anthropogenic (human- caused) sources. The long-term goal is to develop inventories of all trace species that are involved in global atmospheric chemistry. Computer model assessments of past, present, and future atmospheric chemistry, air quality and climate change rely on inventories of emissions constructed on appropriate spatial and temporal scales with appropriate chemical species. Accurate emissions inventories also are useful to field measurement scientists and the regulatory and policy communities. The GEIA products are expected to become standard inventories for the international community.
Most GEIA inventories currently available are for emissions from anthropogenic sources and less for emissions from natural sources. The latter include nitrous oxide (N2O) and volatile organic compounds (VOC). Inventories are in progress for natural sources of methane, reduced sulfur, and some source-specific emissions such as biomass burning.
Other inventories, mostly smaller in scale, are being organized by, for example, Emission Database for Global Atmospheric Research (EDGAR) for and Halocarbons and other Trace Species (HATS) in connection with GEIA. Current inventories for natural sources include emissions of N2O, NOx, non- methane VOC, and organic halogens.
The global N2O flux from the ocean to the atmosphere has been calculated based on more than 60,000 field measurements of surface water anomaly (Nevison et al. 1995). The expedition data was data was extrapolated globally and coupled with daily air-sea gas transfer coefficients. One of the most recent global climatologies of emissions to the atmosphere has been created using the data from 16,000+ observations of surface ocean DMS concentrations (Kettle et al., 1999). These observations were extrapolated to a global grid and coupled with estimates of global DMS transfer velocity patterns. The estimates of DMS emitted from the ocean to the atmosphere are better constrained largely due to the increased number of field observations and mass balance of the sulfur budget in the marine boundary layer (Chen et al. 1999; Davis et al. 1999).
There is still significant uncertainty, however, associated with all global estimates of ocean to atmosphere N2O and DMS flux. The extrapolation of limited, in space and time, observations to regional and global scales invites many venues for error. In particular, coastal regions typically have higher concentrations than open ocean regions but the patterns are very local and may result in error when extrapolated. The underlying uncertainty of the empirical gas exchange/wind speed relationships described below further compound these errors. Gas measurements in the surface ocean are expensive and time consuming; however, these measurements are the only way to get real ground truth estimates of the flux. Since high resolution, global measurements of surface ocean concentrations over several seasonal cycles are not readily feasible (e.g., Turner et al 1996, Dacey 1998), it is critical that empirical relationships between DMS concentration, for example, and remotely sensed ocean color, temperature, wind speed and other variables be developed. The surface ocean, DMS concentration database used in Kettle et al. (1999) should be continually updated as new measurements become available and could be used to guide observational programs for greatest scientific impact. A few studies have included the effects of anthropogenic sulfur (Erickson et al., 1995; Meehl et al., 1996; Haywood et al., 1997) on climate but much further research is required to include a very detailed treatment of sulfur and other aerosol dynamics in on-line climate simulations. No GCM climate runs have examined the climate response of DMS emissions from the oceans or variability thereof. Similar work is required for the emissions of many other compounds as well as for deposition to the surface.
1. Dimethyl sulfide and related compounds
1.1. Introduction
In the years since publication of the DMS/CCN/Climate hypothesis, almost 1000 papers have been published discussing the biogeochemistry of DMS (and its precursors) and its link to climate. Under the IGAC umbrella, several studies addressed aspects of the DMS-aerosol-climate connection, most prominently among them ASTEX/MAGE (Huebert et al., 1995) and ACE-1 (Bates et al., 1998). As a result of these large projects, and the large number of independently conducted studies related to the CLAW hypothesis, we now understand many of the details of DMS production in the oceans, its transfer to the atmosphere, and the atmospheric oxidation processes that lead to the formation of aerosols that can act as CCN. However, in spite of this progress, fundamental gaps remain in our understanding of key issues in this biosphere-climate interaction, in particular with regard to the processes that regulate the concentration of DMS in seawater. While the basic processes have been identified, and even quantified in specific locations (e.g., Bates et al., 1994), generally applicable models of DMS-plankton relationships are still in their infancy (Kwint and Kramer, 1996; Gabric et al., 1998). Therefore, we are still not able to represent the DMS/CCN/Climate hypothesis in the form of a process-based, quantitative, and predictive model. Even the overall sign of the feedback cannot be deduced with certainty, since it is not known yet if a warming climate would result in an increase or decrease of DMS emissions. Glacial-to-interglacial changes in the amounts of DMS oxidation products in polar ice cores cannot answer this question unambiguously, as they may reflect variations in atmospheric transport patterns as much as differences in DMS production (Whung et al., 1994; Saltzman et al., 1997).
Early, limited data sets had suggested a possible correlation between DMS and phytoplankton concentration (e.g., Andreae and Barnard, 1984). This correlation is particularly evident in vertical profiles of DMS and chlorophyll a, which in most instances show a sharp drop of both parameters around the depth corresponding to a light penetration of 1% of the surface light flux. Close correlations between DMS and phytoplankton densities were also found in situations where a single species accounted for much of the DMS production or phytoplankton biomass (e.g., Barnard et al., 1984; Holligan et al., 1993; Matrai and Keller, 1994). These findings led to the hope that global DMS distributions could be estimated from chlorophyll concentrations obtained by remote sensing, but experimental investigations of this proposal were not encouraging (Matrai et al., 1993). Furthermore, a recent statistical analysis of almost 16,000 measurements of DMS in surface seawater failed to show any useful correlations between DMS and chlorophyll or other chemical or physical parameters (Kettle et al., 1999). One reason for the absence of a general correlation between plankton biomass and DMS is that the intracellular concentration of its metabolic precursor, dimethylsulfoniopropionate (DMSP), varies between different phytoplankton species over a range of 5 orders of magnitude. While it is clear that some taxonomic groups typically contain higher amounts of DMSP, these relationships are by no means clear-cut (Keller et al., 1989; Matrai and Keller, 1994; Townsend and Keller, 1996; Liss et al., 1997). At least as important, however, are the complexities of DMS cycling by biological and abiotic processes in the surface ocean, which will be addressed below. In the following sections, we will review some of the results obtained and attempt to put them into the larger context of Global Change research, as done with the Terrestrial section.
Very high concentrations of DMS and dissolved DMSP have been reported from several coastal and/or high latitude areas, especially where blooms of DMSP-producing phytoplankton such as Emiliania huxleyi and Phaeocystis pouchetii occur (e.g. Malin et al 1993, Matrai & Keller 1993, Liss et al 1994, Turner et al 1995; Matrai and Vernet, 1997). In this context, it is interesting to note that Kettle et al (1999) s DMS data base revealed that high DMS regions corresponded roughly to the coccolithophorid bloom areas given by Brown and Yoder (1994). Blooms of marine phytoplankton provide convenient natural laboratories for investigating the production of DMS in relation to phytoplankton community dynamics and species succession, and associated processes, including grazing and bacterial turnover. However, this apparent focus on hotspots of DMS production in relatively nutrient rich areas can be criticised in that oligotrophic areas of the oceans, which generally have relatively low levels of DMS and DMSP throughout the year, make up a large fraction of the total ocean area and so must contribute significantly to the total global flux of DMS (Bates et al 1992). These pioneering studies established the link between phytoplankton and DMS accumulation, but failed to account for a large part of the natural variability in DMS concentrations. Blooms of marine phytoplankton are usually relatively short lived, so assessing seasonality brings problems with respect to spatial coverage (vertical and horizontal) and frequency of sampling. In addition, there have been rather few actual DMS time-series studies. Turner et al (1996) took near- surface samples at 120 geographically defined stations in the southern North Sea from a ship at monthly intervals for a 9-month period. In contrast, Dacey et al (1998) made measurements on samples from 140 m deep vertical profiles at a station in the Sargasso Sea that was visited biweekly over a 2 year period. Despite the contrasting trophic regimes, periods of elevated DMS concentration were noted in both studies. For the oligotrophic Sargasso Sea station, the data revealed a correlation between DMS and water temperature that fitted with the DMS/climate hypothesis of Charlson et al (1987).
Prymnesiophytes and dinoflagellates are phytoplankton groups that tend to have high DMSP cell quotas (REF) and, not surprisingly, DMS is often relatively high when phytoplankton assemblages are dominated by these groups (REF). Diatoms, on the other hand, tend to have low intracellular DMSP concentrations and it is generally believed that diatoms are less important than the major DMSP-producing groups (REF). Predicting DMS concentrations from the algal assemblage is not straightforward, however. For example, Matrai and Vernet (REF) recently reported that DMS concentrations were as high in diatom-dominated, arctic waters as they were in those dominated by Phaeocystis sp. It is now recognized that these phytoplankton species not only produce high intracellular concentrations of DMSP, but they also have cell-surface (REF) and intracellular (REF) DMSP lyase enzymes that may be actively involved in DMS production, thereby contributing to the elevated DMS concentrations associated with these organisms. The ecological roles of these lyase enzymes are not well understood but several recent studies have pointed to very interesting functions such as in grazing deterrence, carbon acquisition, and bacterial inhibition (REF). Recently, it has been shown that viruses are significant agents in the control of bacterio- and phytoplankton. Viral infections can cause a total release of intracellular DMSP (Hill et al., 1998) and viruses are known to infect DMSP-containing, bloom organisms, such as E. huxleyi (Brussaard et al., 1996) and Phaeocystis sp. (Malin et al., 1998). It seems clear from studies such as these that the overall food web dynamics, including macro- and microzooplankton grazing, bacterial, and viral activities, as well as the physicochemical dynamics of the upper ocean (e.g. UV, mixing, temperature, air-sea exchange) can be important factors governing DMS accumulation.
The recent revolution in understanding of how certain trace nutrients limit primary productivity in the ocean has also improved knowledge of DMS biogeochemistry (see Box #3). The experimental fertilization with Fe of Fe- poor regions of the equatorial Pacific with subsequent Lagrangian time series sampling revealed dramatic increases in phytoplankton (primarily diatom) production and biomass. The general increase in phytoplankton biomass was accompanied by increases in DMSPp and shortly thereafter in DMS concentrations. Such a fertilization experiment is akin to a batch culture perturbation and it is not clear whether long term Fe enrichment and sustained higher productivity would lead to higher steady state DMS concentrations. Given enough time, shifts in the population structure, or simply growth of the microbial populations, might reestablish low steady state DMS concentrations with perhaps higher turnover of both DMSP and DMS. Our present understanding of the response of microbial populations to changes in DMSP and DMS supply is insufficient at present to make confident predictions in this regard.
We now realize that microbial, especially bacterial, processes are very important in the overall DMS cycle. The biological turnover of the dissolved form of DMSP in seawater has been measured at 3-130 nM d-1 in non-bloom waters (REF), with even higher rates being observed in blooms of DMSP- producing phytoplankton (REF). The potential for DMS production is therefore quite large, but recent studies indicate that most of the DMSP in the sea is not converted to DMS. A demethylation/demethiolation pathway 18 leading to production of methanethiol (MeSH) accounts for 70-95% of DMSP metabolism in situ thereby diverting sulfur away from DMS (REF). This process acts as a major biogeochemical control on DMS formation. The predominance of the non-DMS producing demethylation/demethiolation pathway is explained by the fact that bacteria use it to assimilate the sulfur from DMSP into protein amino acids (REF). Further understanding of this DMSP/DMS/MeSH/bacteria interaction is critical because a relatively small change in the yield of DMS from DMSP could have a major impact on the gross production of DMS.
Removal of DMS from the water column by biological (REF) and photochemical (REF) mechanisms also exerts a great influence on the net accumulations of DMS in surface waters. Biological consumption is an important sink for DMS under pseudo steady state conditions, but appears to be slow to respond to rapid increases in DMS production (REF). This may partially explain the rise in DMS concentrations observed at the peak and initial decline phases of phytoplankton blooms (REF). Net consumption of DMS appears to occur in the later stages of blooms after DMS-consuming bacteria have had time to develop (REF). The photochemistry of DMS in seawater remains poorly understood, despite the fact that it has been identified as a major removal mechanism under some circumstances (REF). DMS photooxidaton appears to depend on photosensitizers in seawater which are most likely part of the colored dissolved organic matter (CDOM) (REF). In the open ocean CDOM originates from autochthonous primary productivity and food web processes so the interaction with DMS is probably complex. Add to this the fact that DMS producing and consuming bacterial populations are likely to be strongly influenced by UV-B in surface waters, and one can easily see the importance of understanding photophysical effects on the DMS cycle.
Our current knowledge base is not sufficient to develop and constrain predictive DMS production models for diverse biogeographic regions, in order to, e.g., interpret the role of DMS in climate change. Future research will need to focus on 1) gaining a full understanding of the processes which control DMS production and allow the prediction of DMS emissions, and 2) obtaining much more data concerning spatial, temporal and interannual variation in the concentration of DMS and related compounds. Emphasis on undersampled areas and seasons would be valuable. For process studies, there is an increasing need to cross disciplinary and international boundaries to bring together experts on different aspects of DMS and related compounds for integrated field campaigns. For analysis of variability, remote sampling systems could be considered (such as attempeted in ACE-I). It might be possible to develop a buoy-mounted monitoring system whereby samples were stored on a carousel for later analysis. Alternatively, we might follow the example of the pCO2 measuring community, who have demonstrated that it is feasible to employ unmanned instruments installed on merchant ships (Cooper et al., 1998). This would enable the collection of large data sets during long passage routes, covering diverse biogeographic areas, different seasons and the chance to investigate interannual variability at relatively low cost. New techniques will be needed to circumvent the present lack of a reliable storage method for DMS samples. In the first instance, it might be more realistic to concentrate on DMSP analyses.
The emissions of DMS from the world's oceans are a significant source of sulfur to the atmosphere (Bates et al., 1992; Spiro et al., 1992; Kettle et al., 1999) and contribute to both the marine boundary layer and free tropospheric sulfur burden (Chin and Jacob, 1996). In the marine boundary layer (MBL), DMS is photochemically oxidized to sulfur dioxide (Bandy et al., 1996; Yvon et al., 1996; De Bruyn et al., 1998) and methanesulfonate (MSA), which contribute sulfur mass to existing particles (Covert et al., 1996; Huebert et al., 1996; Bates et al., 1998), but may also lead to the formation of new particles (Andreae et al., 1995). In areas of active cloud convection, DMS is pumped up to the free troposphere. In the cloud outflow regions of the free troposphere, where aerosol surface areas are low and water vapor mixing ratios are intermediate between moist surface layers and dry regions aloft and above cloud, DMS oxidation leads to the nucleation of new particles (Perry and Hobbs, 1994; Clarke et al., 1998). Through coagulation, these ultra-fine (UF) mode (Dp = 5-20 nm) particles grow into Aitken mode (Dp = 20-80 nm) particles. In areas of cloud pumping and subsidence following cold frontal passages, the UF and Aitken mode particles are mixed back down into the MBL (Raes and Van Dingenen, 1992; Covert et al., 1996; Bates et al., 1998, Clarke et al., 1998). In regions of high pressure systems, there is a continuous slow replenishment of Aitken mode particles to the MBL through entrainment at the top of the mixed layer (Covert et al., 1996).
In the decade following the initial DMS/CCN/Climate hypothesis (Charlson et al., 1987), there have been numerous studies linking regions (periods) of high DMS fluxes to regions (periods) of high particle concentration and enhanced cloud albedo (e.g. Bates et al., 1987; Ayers et al., 1991; Ayers and Gras, 1991; Berresheim et al., 1991; Huebert et al., 1993; Quinn et al., 1993; Andreae et al., 1995). However, the climatic significance of the DMS sulfur depends not on the total aerosol number or non-sea-salt sulfur mass but on the contribution of DMS to the aerosol number population in the accumulation (Dp = 80-300 nm) and coarse (Dp > 300 nm) modes, i.e. aerosols in the size range that efficiently scatter solar radiation and serve as CCN. Recent results from ACE 1 showed that greater than 70% of the particles with diameters greater than 80 nm (Kreidenweis et al., 1998) and over 90% of the particles with diameters greater than 130 nm (Murphy et al., 1998) contained sea-salt. In this isolated region of the Southern Ocean, sea- salt particles dominated (95% +-4%) the direct back-scatter of solar radiation (Quinn et al., 1998) and likely served as the main source of CCN (Murphy et al., 1998; Covert et al., 1998). While DMS sulfur contributed mass to the accumulation and coarse mode particles, it appeared to have little effect on the radiative and cloud nucleating properties of these particles. These observations should, however, not be generalized to the remote ocean worldwide, as the area studied in ACE 1 is characterized by higher than average wind speeds, resulting in unusually high seasalt particle densities. A reliable assessment of the global role of DMS in regulating cloud properties and climate will require integrated studies of DMS emission, oxidation, particle formation and characteristics, and cloud properties in other ocean regions.
The photochemical source of COS was first recognized by Ferek and Andreae (1984), who demonstrated a clear diurnal cycle in the sea surface concentration of the compound. A mechanism of formation of COS was proposed by Pos et al. (1998) who suggested that the photochemical production of COS and carbon monoxide proceeds along a coupled pathway which first involves the photochemical formation of an acyl radical from colored dissolved organic matter (CDOM). Flöck et al. (1997) and Ulshöfer et al. (1996) suggested that cysteine is probably implicated in the reaction mechanism of COS formation as the result of its reactivity and abundance in the oceans. The photochemical COS production in natural seawater is probably not limited by the concentration of a precursor sulfur compound but rather by the concentration of CDOM represented by its ultraviolet attenuation coefficient (Ulshöfer et al., 1996; Uher and Andreae, 1997). Zepp and Andreae (1994) and Weiss et al. (1995) quantified the wavelength dependence of COS photoproduction from CDOM and found that quantum efficiency of photoproduction decreases monotonically with increasing wavelength. The dark (or nonphotochemical) production of COS has been proposed on the basis of the nonzero COS concentration observed at ocean depths where there is no photochemical production and where there is no mixing from the surface (Radford-Knoery and Cutter, 1994; Flöck and Andreae, 1996) and also on the basis of careful interpretation of sea surface COS concentration measurements using inverse models (Ulshöfer, 1995). COS hydrolysis varies as a function of temperature and pH and has been evaluated several times over the last decade (Elliott et al., 1989; Radford-Knoery et al., 1994; and Uher and Andreae, 1997).
Recent models have used laboratory results for the photoproduction and hydrolysis rate constants to explain COS sea surface measurements obtained during expeditions made in the 1980's and 1990's (see Ulshöfer (1995) for a review of recent sea surface COS concentration measurements). Andreae and Ferek (1992) developed the first chemical box model to explain the diurnal variation of COS in terms of photochemical formation and hydrolysis destruction. Ulshöfer (1995) adopted an optimization scheme based on the coupled photochemical mixed layer used by Kettle (1994) to calculate the photoproduction and dark production constants for COS from a series of sea surface measurements in the North Atlantic Ocean made between 1992 and 1994. von Hobe (1999) extended this work for other models and expedition measurements. Najjar et al. (1995) generalized a simplified coupled physical- chemical model on a global scale to investigate the sensitivity of COS sea surface concentration on ozone reduction and tropospheric increases of carbon dioxide. Kettle and Andreae (?1995)? (1998) and Preiswerk and Najjar (1998) have used existing measurements of the CDOM absorption coefficient of seawater to predict a seasonal variation in the absolute COS concentration with maximum at high latitudes in the summer hemisphere.
Future work on COS should aim to more accurately quantify the role of the oceans as a source or sink of the gas to the atmosphere. The global application of the photochemical production model for COS is currently limited by the absence of an algorithm to predict the global CDOM absorption coefficient and by the suggestion that the apparent quantum yield of COS formation may vary by more than an order of magnitude in different regions of the ocean. The scarcity of profile measurements of COS concentration has been problematic for modeling efforts which have so far been developed to explain only the surface COS concentration distributions. Finally, the precise quantification of the sea-air flux of all gases produced in the upper ocean (including COS) is currently limited by the absence of an effective gas exchange parameterization based on wind speed, average wave slope, or other measure of upper ocean turbulence, as already indicated.
Ammonia exists in seawater as both ionized ammonium, NH4+ (s), and dissolved ammonia, NH3 (s). NH3 (s) makes up about 10% of the total seawater ammonium concentration, NHx (s), at a pH of 8.2 and a temperature of 25°C (Quinn et al., 1996) and is the species that is emitted across the air- sea interface. NHx (s) is produced in the upper ocean from the degradation of organic nitrogen containing compounds and excretion from zooplankton. It also is released from bottom sediments to overlying waters. Loss processes for NHx (s) include bacterial nitrification, uptake by phytoplankton and bacteria, and emission across the air-sea interface. There will be a net flux of ammonia from the ocean to the atmosphere if the actual atmospheric NH3 (g) concentration is less than the gas phase concentration computed to be in Henry s Law equilibrium with NH3 (s). Alternatively, there will be a net flux into the ocean if the atmospheric NH3 (g) concentration is greater than the Henry s Law equilibrium gas phase concentration. Hence, the magnitude and direction of the flux is determined by the difference between the Henry's Law equilibrium gas-phase concentration and the actual atmospheric concentration and by the transfer velocity.
Attempts to estimate the air-sea flux of ammonia have been hindered by a lack of techniques with sufficient sensitivity and by difficulties in avoiding sample contamination (Williams et al., 1992). As a result, the contribution of NH3 to the oceanic biogeochemical cycling of N is poorly understood (Gibbs et al., 1999). The few estimates of the air-sea flux of NH3 that have been reported and that are based on measurements of ammonia in the gas, particle, and/or seawater phases are summarized below.
The first estimates of the flux for the Pacific Ocean were based on filter collection of NH3 (g) and NH3 (s) (Quinn et al. 1988, 1990). These measurements indicated a net flux of ammonia from the ocean to the atmosphere in the NE and central Pacific ranging between 1.8 and 16 µmol m-2 d-1 . Clarke and Porter (1993) used measurements of aerosol volatility (which indicate the degree of neutralization of sulfate aerosol by ammonia) to infer an efflux of ammonia from the ocean to the atmosphere of about 10 µmol m-2 d-1 over the equatorial Pacific. Similar results have been reported for the Atlantic Ocean and the Arabian Sea. Based on aircraft measurements of aerosol ammonium during a Langrangian experiment near the Azores, Zhuang and Huebert (1996) estimated a flux of NH3 from the ocean to the atmosphere of 26 ± 20 µmol m-2 d-1 . Simultaneous measurements of NHx (s) and NH3 (g) were made in the Arabian Sea (Gibb et al., 1999). It was found that in both coastal and remote oligotrophic regions there was a flux of NH3 from the ocean to the atmosphere. Hence, to date, measurements over portions of the Pacific, the Atlantic, and the Arabian Sea indicate that the remote ocean serves as a source of NH3 to the atmosphere even in regions of low nutrient concentrations.
Given the importance of NHx (s) as an oceanic micronutrient, the loss of ammonia through venting to the atmosphere may seem surprising. However, only a small percentage of NHx (s) exists as NH3 (s) so that this efflux most likely represents a relatively minor loss of NH3 (Gibb et al., 1999). In addition, this loss can be episodically compensated for through the wet and dry deposition of ammonium-containing aerosol particles. For example, Quinn et al. (1988) estimated that, over the NE Pacific, the transfer of NH3 (g) from the ocean to the atmosphere was balanced by wet and dry deposition processes. In certain regions, such as the Southern Bight of the North Sea, there is a flux of ammonia from the atmosphere to the ocean due to the advection of high concentrations of ammonia from adjacent land (Asman et al., 1994). The extent and impact of the deposition of continentally-derived ammonia to marine regions is unknown but may be significant. Model results suggest that about 6% of the global continental emissions of ammonia are deposited to the North Atlantic and Caribbean (Prospero et al., 1996). The impact would be greatest in coastal waters.
It is clear that ammonia, as an oceanic micronutrient and the dominant atmospheric gas phase species, plays a unique role in both the ocean and the atmosphere. The flux of ammonia from the ocean to the atmosphere affects aerosol chemical composition, pH, and hygroscopicity. The reverse flux, of ammonia from the atmosphere to the ocean, may affect biological productivity. Simultaneous measurements of ammonia in the atmospheric gas and particle phases, in seawater, and in rainwater are needed to improve our understanding of the multi-phase marine ammonia system in general and the air-sea exchange of ammonia in particular.
During the past decade there have been significant improvements in our understanding of oceanic processes of N2O production, of the distribution of N2O in the surface and subsurface ocean, and of the magnitude of the oceanic N2O source to the global atmosphere. The relative roles of nitrification and denitrification processes have been addressed by measuring nitrogen stable isotopes and their fractionation among N2O and other dissolved nitrogen- bearing species. The interpretation of these difficult measurements is complicated by the likelihood that both nitrification and denitrification are coupled in many oceanic systems, and no clear picture has yet emerged. There have also been recent advances in the study of air-sea gas exchange processes, as indicated above, which will lead to improvements in the quantification of N2O exchange coefficients as a function of wind speed.
Finally, our understanding of the large-scale distribution of N2O in the oceans has been improved through a number of shipboard measurement programs, such as those associated with the WOCE and JGOFS programs. These have generally reinforced our view that open ocean upwelling regions along eastern ocean boundaries and in equatorial regions, as well as coastal regions, represent major sources of atmospheric N2O. By contrast, the great subtropical gyres, which represent a large portion of the surface area of the oceans, are relatively close to atmospheric equilibrium for N2O. In recent years, some extremely high N2O concentrations have been found in the eastern Arabian Sea, in suboxic waters over the Indian Shelf (Naqvi et al., 2000). Since anthropogenic impingements on the coastal ocean may cause an increase in hypoxia, suboxia, and inoxia in some coastal areas, these recent observations from the Arabian Sea are provocative. By modeling these distributions together with the wind field, the global oceans are believed to constitute a net source to the atmosphere of about 5 Tg of N2O, or about one third of the global natural source strength, although this value may increase as more is learned about the diverse distribution of N2O in coastal waters.
Methyl bromide (CH3Br) in the environment began to receive considerable attention in the early 1990 s when it was being evaluated as an ozone-depleting gas, along with chlorofluorocarbons, chlorocarbons, and halons. First-order calculations indicated that methyl bromide was likely to be a significant contributor to stratospheric ozone depletion. Before then, only a few studies of CH3Br in the ocean and atmosphere had been conducted. Lovelock (1975) detected CH3Br in coastal waters of England and suggested that this gas could have a large natural source. Singh et al. (1983) later reported widespread supersaturations greater than 200% off the west coast of North America, lending support to the ocean as a large natural source of CH3Br. Khalil et al (1993) suggested that the open ocean was supersaturated in methyl bromide by 40-80%. However, prompted in part by calculations showing that the ocean simultaneously had to be a large sink for CH3Br because of reaction with Cl- in seawater (Elliott and Rowland 1995, Jeffers and Wolfe 1996, King and Saltzman 1997), numerous investigations, using in situ mass spectrometry-gas chromatography, demonstrated that the ocean on average was a net sink for atmospheric methyl bromide, with tropical and subtropical waters of the open ocean highly undersaturated and coastal waters often supersaturated in this gas (Lobert et al. 1995, 1996, 1997, Moore and Webb 1996, Groszko and Moore 1998). Certain species of phytoplankton produce CH3Br, but apparently not at rates sufficient to explain the observed saturation levels (Saemundsdottir and Matrai 1998, Moore et al. 1995, Scarratt and Moore 1996). Most recently, there have been suggestions that methyl bromide in temperate and coastal waters might undergo a seasonal cycle, with higher concentrations or supersaturations in the spring and early summer and undersaturations the rest of the year (Baker et al. 1999, King et al. 2000). About the same time, it also became clear that chemical and biological removal of methyl bromide in seawater constituted such a large sink for this gas that it would have a profound effect on the lifetime of methyl bromide in the atmosphere, even if the ocean were everywhere a net source (Butler 1994, Yvon and Butler 1996, Yvon-Lewis and Butler 1997). In the latest budget calculations, irreversible loss of atmospheric methyl bromide to the ocean accounts for ¼ -1/3 of the total removal (Kurylo et al. 1999).
These two findings ¾ that the oceanic source was outweighed by its sinks and that the lifetime of atmospheric methyl bromide depended strongly upon its reaction in seawater ¾ necessitated a re-evaluation of the global budget of this gas in the atmosphere. Once the apparently large soil sink was discovered and confirmed (Serca et al. 1998, Shorter et al. 1995, Varner et al. 1999), the calculated budget of atmospheric methyl bromide was no longer in balance. The latest calculations have sinks outweighing sources by 80Gg y-1 , out of a budget of 205 Gg y-1 (Kurylo et al. 1999). It is unlikely that this additional source will come from the ocean, as the current global coverage of surface measurements, although not complete, is representative of the various oceanic regimes, although with reduced coverage of coastal waters; the small net sink now calculated for the ocean (3-30 Gg y-1 ) is unlikely to change much, unless, of course, there is some significant global change driving it. Furthermore, recent studies are identifying terrestrial sources from plants and salt marshes that are making the budget gap smaller (Gan et al. 1998, Rhew et al. 2000 , Dimmer et al. 1999).
Perhaps one of the most significant things to come out of these intensified studies of methyl bromide in the ocean is that other gases, particularly organic halogens, may behave in similar, quantifiable ways. When gases are produced and destroyed in seawater and exchanged with the atmosphere on similar time scales, their exchange with the atmosphere can be controlled in good part by reaction in seawater. Many of these gases, which may include CH3I, CHBr3, CH2Br2, CH2BrCl, C2H5Br, among others, have climatic implications through their chemistry or radiative effects. Study of them in the past has been limited (e.g., Sturges et al. 1992, 1993, Nightingale et al. 1995), but as potential global change drives more research in the future, the responses of aquatic ecosystems to changes in temperature, or precipitation, or ocean circulation may be of paramount importance to understanding not only the ocean, but the atmosphere as well.
1.1. Introduction
The major reason why this topic has received very considerable research effort over the last decade is because of the role iron has been hypothesized to play in controlling marine primary productivity over large areas of the oceans remote from land. Because of their distance from riverine and shelf inputs, in these regions (e.g. Southern Oceans, North and Equatorial Pacific) the main way in which 'new' iron gets into the system is via deposition from the atmosphere of terrestrially derived material. It should be pointed out that the idea of iron being a major control on ocean production is not new. In the early decades of the 20th century it was hypothesized that the reason why large areas of the Southern Oceans contained residual conventional plant nutrients (nitrate and phosphate), when light and other conditions for plant growth were favourable (the HNLC, high nutrient-low chlorophyll, regions), was because of iron deficiency in the water (see, for example, Gran 1931, Harvey 1933, 15 Hart 1934 and the recent review by DeBaar and Boyd (2000). However, it is only in the last decade that analytical techniques for iron and field- going experimental approaches have been good enough to begin to test the hypothesis critically.
Here, we first review the sources of iron to the remote oceans and how it is transported there via the atmosphere. Then the form of iron in the depositing atmospheric aerosol is discussed along with its solubility once it is in the seawater. Finally, we briefly present some of the various attempts which have been made to test the iron limitation hypothesis in the laboratory and, particularly, by in situ fertilisation involving addition of iron directly to small areas of the oceans. In this, we concentrate on the effect of Fe-induced fertilisation on the production/consumption of trace gases of particular relevance to atmospheric chemistry (e.g. CO2, DMS, etc.).
As pointed out by Jickells and Spokes (2000), our ability to estimate dust inputs to the ocean is compromised by the very few data sets of dust concentrations collected over long periods of time. In general, the highest atmospheric concentrations of dust in marine areas are found over the North Pacific and the tropical Atlantic. Other high concentration areas are found in the Arabian Sea and the northern Indian Ocean, but there are very limited data in these regions. Accurate estimation or calculation of dust deposition is still quite difficult and this problem is discussed in some detail by Jickells and Spokes (2000). Figure 14 presents an estimate of the geographical distribution of the flux of mineral matter to the global ocean (Duce et al., 1991). Note that by far the major fraction of mineral dust is deposited in the Northern Hemisphere. It is estimated that of the total deposition, roughly one third is delivered to the North Atlantic and about one half to the North Pacific (Jickells and Spokes, 2000). The atmospheric deposition has clearly fluctuated significantly in the past, as seen in ice core and deep sea sediment samples, but this will not be discussed further here (see, for example, Maher and Hounslow 1998; Rea 1994; Andersen et al. 1998).
Figure 14. Calculated global fluxes of atmospheric mineral matter to the ocean (from Duce et al., 1991).
Jickells and Spokes (2000, and refs. therein) state, in summary, that it is likely that the overall iron solubility of dry deposited mineral aerosol is < 1% at seawater pH of 8, and that a high proportion of this iron is photoreduced, Fe (II), which is bioavailable. The solubility of iron in marine rains with a pH of 4-7 is ~14%. Thus the input of soluble atmospheric iron to the oceans is apparently dominated by wet deposition. These estimates, based on laboratory studies, are somewhat lower than those made earlier by other authors. However, Jickells and Spokes (2000) made other oceanographic approaches to estimate the solubility of atmospheric iron. All of these approaches result in low iron solubility, probably less than 2%. Their final conclusion is that approximately 0.8 to 2.1% of the total iron deposited in the ocean is soluble. With a total input of 15 to 100 Tg yr-1 , this would result in a total soluble iron atmospheric input of from 0.12 to 2.1 Tg yr-1 . This is somewhat lower than the estimate of ~3 Tg yr-1 made by Duce et al. (1991), primarily because of new and better estimates of the fraction of mineral aerosol iron that is soluble in the 1ocean.
Although the idea had been around since the early decades of the 20th century, serious testing of the iron limitation hypothesis had to await the development of analytical techniques for (sub)nanomolar concentrations of iron, as well as clean sample handling procedures so that the analyses were not compromised by ingress of contaminant from the laboratory or sampling and storage procedures. These improvements in techniques have taken place in the last two decades, initially under the leadership of the late John Martin. He and his colleagues made some of the first reliable measurements of iron in the oceans and conducted shipboard incubation studies in flasks of seawater that had been amended with soluble iron. The results were promising (e.g., Martin and Fitzwater 1988) and clearly showed that addition of iron (normally added as ferrous sulphate or other simple inorganic salt) could lead to substantial increases in plankton growth, as indicated by increasing chlorophyll concentrations with time in the experimental flasks. An interesting variant on this basic experiment, which is particularly relevant in the present context, was a study conducted in the equatorial Pacific by Johnson et al. (1994). They used a 20 litre carboys of seawater and added the iron in a variety of inorganic and organically complexed forms. In addition, they also used natural Asian dust aerosol particles (collected in Hawaii) and added them to one of the carboys of seawater. In this carboy the rate of plankton growth was found to be the most rapid and attained the highest chlorphyll levels, indicating that the aerosol particles were more effective at promoting growth than artificial iron supplements.
However, a criticism of all attempts to mimic environmental processes in a necessarily confined, shipboard, laboratory experiment is uncertainty as to how well what happens in the flasks (or carboys) mirrors what is happening in the real oceans, for example whether zooplankton grazing is properly captured. Further, and rather disturbingly, in some cases in the enrichment experiments the blank flasks (no added iron) also showed similar levels of enhanced plankton growth, almost certainly due to contamination with iron when the water used in the experiments was collected (Fitzwater et al. 1996).
In the light of these difficulties other avenues have been explored to attack the problem in a more direct way. A novel and interesting approach is that adopted by Young et al. (1991), who monitored natural dust inputs to the north Pacific and examined any resulting change in productivity in the receiving water. Several dust deposition events occurred during the time the research vessel was at sea and these appeared to be correlated with increases in primary productivity measured in on deck incubators, but with a four day lag between the dust input and the peak in productivity. Although suggestive of a relationship, the results are too few and insufficiently clear-cut to be totally convincing. In additon, interpretation is complicated because productivity change was measured in a deck incubator not in the ocean itself, and when deposition occurred meteorological conditions also changed with greater stirring of the near-surface water which in itself may have changed the productivity. However, this experiment represents a novel and potentially powerful tool since it uses the natural atmosperic input and examines the response of the real oceanic system. This experiment would certainly be worth further and more sophisticated repetition.
A different approach to testing the iron hypothesis is that of adding inorganic iron (FeSO4) directly to a small patch (of order 100 Km2 ) of the oceans. In order to be able to track the iron enriched patch as it moves in the ocean, the gas SF6 is added along with the iron. Sulphur hexafluoride can be easily measured at tracer (femtomolar) concentrations in almost real time on the research vessel, and this enables the enriched patch to be tracked. The principles underlying this approach are outlined in Watson et al. (1991). It has been deployed three times to date; twice in the equatorial Pacific (IronEx I: Martin et al. 1994 and IronEx II: Coale et al. 1996) and very recently in the southern oceans (SOIREE: Boyd et al. 2000). On all three occasions, raising the iron level in the water by a few nanomoles produced a significant enhancement in phytoplankton activity, as measured by chlorophyll concentration increase; thus 'proving' the iron hypothesis. In the case of IronEx II, the increase was at least an order of magnitude, whereas in IronEx I it was only 3-fold. The overall increase over the 13 days of the experiment was about 5-fold, somewhat smaller than in IronEx II probably due to the colder water temperature. Smaller organisms were the first to utilise the iron supplement, with the larger plankton (mainly diatoms) benefiting later.
Trace gases measured in these experiments were CO2 and DMS. The former was drawn down due the enhanced primary production. The extent of CO2 removal roughly mirrors the increase in chlorophyll, except for IronEx I where it was very small, probably due to rapid recycling of the fixed carbon by grazers. For DMS, 3- to 5-fold increases occurred in all three studies, with much less variation than for CO2. Fig. 15 shows CO2 changes between inside and outside the enriched patch during the course of SOIREE, and in Fig.16 a vertical section gives the time evolution of DMS and its precursor DMSP. To put these results in a broader time context, Fig. 17 is a compendium of results from ice cores for iron, CO2, MSA (an atmospheric oxidation product of DMS), and several other parameters. It is noteworthy that the elevated iron and MSA and lowered CO2 levels in the last glacial period are consistent with a scenario where ocean productivity was higher then due to enhanced atmospheric inputs of iron.
Figure 15. CO2 changes inside and outside the enriched patch during the course of SOIREE (from Boyd et al. 2000).
Figure 16. Time evolution of DMS and DMSP inside and outside the enriched patch during the course of SOIREE (from Turner and Hunter 2000).
Figure 17. Compendium of results from ice cores for iron, CO2 , MSA, and several other parameters (from Turner et al. 1996).
Figure 18. Airshed, Upper Estuarine and Lower Estuarine Processes.
The APSS is representative of shallow N-sensitive estuarine and coastal waters nationwide (NOAA 1997) in which there is the need to understand estuarine responses to changing new N sources. Historically, tributaries of the APSS have exhibited widespread and chronic N-limitation (Hobbie et al. 1975, Kuenzler et. al. 1979, Copeland and Gray 1991, Paerl 1983, Stanley 1988, Rudek et al. 1991). Anthropogenic N enrichment to this estuary has been closely linked to eutrophication and associated declines in water quality and fisheries resources (Copeland and Gray 1991, Christian et al. 1991, Paerl et al. 1995, 1998). The Neuse River Estuary receives N inputs from a mosaic of upstream and upwind agricultural, urban and industrial sources. Fossil fuel combustion and agricultural and industrial N emissions represent a significant and growing source of new N to this system (Paerl and Fogel 1994), reflecting a national and worldwide trend (Duce, 1986, Luke and Dickerson, 1987, Asman, 1994, Paerl, 1995, Holland et al. 2000). Depending on the relationship between watershed-estuary surface areas, degree of watershed N-retention, seasonal rainfall, discharge and flow patterns, and proximity of atmospheric sources, an important fraction of AD-N is directly deposited on the estuary. Current estimates of the percentage of total (natural + anthropogenic) new N loading attributed to direct AD-N range from 5% to over 50% (Duce 1991, Fisher and Oppenheimer 1991, Valigura et al. 1996, Dennis 1997, Holland et al. 2000); the recent estimates for the APSS, on the order of 20% (for its estuarine tributaries) to 40% (for the downstream waters of Pamlico Sound) (Paerl and Fogel 1994, Paerl 1995, 1997) appear to be within the range of these values.
Atmospheric N generated from expanding animal operations is of particular concern. Examination of the long-term record of atmospheric NH4+ and NO3- deposition in Sampson County, Eastern North Carolina, shows a nearly 3-fold increase in annual NH4+ deposition (also relative to NO3- ) since 1977, with a particularly precipitous rise since the late 1980's (Figure 19). Within the past 10 years, proliferating commercial swine operations have made the mid-Atlantic/ Southeast one of the Nation's leading pork producers, with North Carolina ranking only second to Iowa. Unlike human waste, swine waste is stored in open lagoons and remains largely untreated. Substantial amounts (30 to >80%) of N are lost via NH3 volatilization alone (O Halloran 1993), which may be a prime mechanism responsible for the increases in annual NH4+ deposition observed.
Figure 19. Trends in annual atmospheric deposition (wet deposition as NH4+ and NO3- ) collected during a 20 year period at NADP site NC-35 in Sampson County, NC. Data replotted from NADP information.
The spatial and temporal interactions of these growing new N inputs must be integrated in the overall scheme of N cycling and resultant productivity/eutrophication responses of estuarine and coastal waters. This means that we must consider impacts of AD-N and other new N sources contemporaneously and contiguously with internal N cycling (i.e., sediment- water column exchange and regeneration of N), which is known to play a significant role in controlling N availability, productivity and resultant trophic state of the APSS (Christian et al. 1991, Rizzo et al. 1992).
Atmospheric wet and dry deposition introduce into estuaries a variety of biologically-available inorganic (NO3- , NH4+ ; DIN) compounds, most of which result from human activities (Likens et al. 1974, Galloway et al. 1994). In addition, organic nitrogen (ON) comprises a significant fraction (from 15 to over 30%) of atmospheric deposition (wet and dry) in coastal watersheds (Correll and Ford 1982, Skudlark and Church 1993, Peierls and Paerl 1997). Although the composition of atmospheric ON is poorly known, recent work (Peierls and Paerl 1997, Seitzinger and Sanders 1997) indicates that constituents of this pool are biologically utilized and hence should be included in eutrophication assessments. Impacts of AD-N on the biological communities of any estuary are first felt at the bottom of the food web in the phytoplankton. Both overall phytoplankton productivity and community composition respond to chemically-diverse atmospheric N sources. In situ bioassays and field surveys show that enrichment with the major AD-N constituents NH4+ and NO3- at natural dilutions and AD-N-derived DON results in enhanced phytoplankton primary production and increased biomass (Paerl 1985, Willey and Paerl 1993, Paerl and Fogel 1994, Peierls and Paerl 1997). NO3- and NH4+ uptake rates vary spatially and seasonally in the Neuse River, suggesting differential community responses to varying N sources (Boyer et al. 1994). AD-DON may selectively stimulate growth of facultative heterotrophic and photoheterotrophic phytoplankton taxa (especially potentially toxic dinoflagellates and cyanobacteria) (Neilson and Lewin 1974, Antia et al. 1991). Taxa-selective phytoplankton responses to specific AD-N inputs, and changes in stoichiometric C:N ratios resulting from these inputs may induce changes at the zooplankton, herbivorous fish, invertebrate and higher trophic levels. The Neuse Estuary, APSS and coastal systems nationwide require a functional understanding of how anthropogenic terrigenous and atmospheric N loading affect the composition and activity of primary producers mediating nutrient cycling, water quality, habitat suitability, fisheries resources, and yields.
At Antarctic locations where accumulation is relatively high (>20 g/cm_/yr), MSA concentration records seem to be reliable and decadal variations can be seen in shallow firn cores. In the Weddell Sea area, Pasteur et al. (1995) found from an ice core covering the last centuries that MSA marine production increases at warmer temperatures, in relation probably to the amount of broken sea ice where phytoplankton can develop favourably. MSA concentration in coastal Antarctic snow seems to be linked with sea-ice extent (Welch et al., 1993). On the other hand, the validity of MSA ice records is questionable inland. A marked decreasing trend of MSA concentration was found in upper firn layers (the first 6 m) at Vostok (Wagnon et al., 1999). It is suggested that MSA scavenged in the snow crystals is progessively released from the solid phase by snow metamorphism. Part of the initially deposited MSA probably escapes back to the atmosphere. The profile obtained at Dome F (Dome-F Ice Core Research Group, 1998) shows very low MSA concentrations between about 30 and 70 m depth, thereafter a rise from about 70 m up to 110 m. The effect can be attributed tentatively to the trapping of interstitial gaseous MSA in the air bubbles at the firn/ice transition (pore close-off). These observations, corroborated by MSA measurements at Byrd Station (West Antarctica) (Langway et al., 1994), lead to the conclusion that MSA concentration depth-profiles from central Antarctica are most probably strongly affected by post-deposition phenomena. Sulfate records are not perturbed.
At Amundsen Scott Station (the South Pole), some decreasing trend of MSA concentrations, as a function of depth, is observable in the firn layers, but it is less steep than at Vostok, probably related to the higher snow accumulation rate. Interestingly, Legrand and Feniet-Saigne (1991) detected at this site marked spikes of MSA concentration in the upper 12 meters of firn (i.e. over the last 60 years). They were attributed to the impact of El Niño events on the production rate of MSA in the sub-antarctic marine areas or on its transport to inner Antarctica. The changes are superimposed on the general decreasing trend of MSA profiles found in the upper firn layers.
MSA records in Greenland firn cores over the last 200 years show a rise starting from surface layers and lasting several decades (Whung et al., 1994; Legrand et al. 1997). This surprising trend, opposite to what is found at the South Pole, could be attributed to a change in DMS marine productivity during this period or to the marked increase of atmospheric acidity caused by anthropogenic sulfur emissions. In the latter case, the amount of MSA remaining in the snow could depend on the pH of the atmosphere or of the snow.
Long-term changes in DMS-derived species can be seen in both Antarctica and Greenland records. The covariance of MSA and nssSO4 concentrations observed in the Vostok core suggests that both species are mainly derived from marine DMS emissions. MSA and nssSO4 concentrations are both higher in glacial conditions, with higher values of the ratio MSA/nssSO4 found for ice ages. An increase of marine biogenic productivity has been put forward to explain this observation (Legrand et al., 1988, 1991, 1992), but the glaciological artefacts reported above for MSA records in central Antarctic firn layers cast some doubt on the proposition. Clearly more work has to be done on the understanding of chemical composition changes of ice on the scale of several glaciations, all the more since Greenland data are opposite to Antarctic observations. In the Renland ice core (East Greenland), MSA concentration and the MSA/nssSO4 ratio are markedly lower for cold than for warm climatic stages (Hansson and Saltzman, 1993). For the two deep cores recovered at Summit (GRIP and GISP 2), conclusions are similar (Saltzman et al., 1997; Legrand et al., 1997). These observations suggest that, for the sulfur cycle, the cases of the northern and the southern hemispheres have to be discussed differently. In particular, the interaction of primary aerosol (continental dust, sea salt) with acid sulfur species has to be investigated.
The sulfur cycle is now well documented in both hemispheres over various time scales, making possible speculations about the changes of marine biogenic activity in the past in relation with climate. Unfortunately, in present climatic conditions, MSA records of central Antarctic regions are found to be seriously affected by post deposition processes occurring in the firn layers. These artifacts presently obscure the interpretation of the environmental signal recorded in ice cores. In coastal regions, the links between MSA concentration in the snow, El Niño events, sea ice extent and marine productivity have yet to be confirmed.
Paleorecords for other atmospheric species mostly of marine origin are not very abundant, with some exploratory data but not records- available for iodine and COS. Methane and dust, on the other hand, have multiple paleorecords but their source is mostly continental. New proxies for atmospheric species are needed to better understand, and predict, current signals. Some of the best candidates are iodine, bromine and, perhaps, selenium.
IV. Conclusions
References (Terrestrial)
Last modified: Wed Apr 26 09:25:15 CEST 2000
