Environmental Engineering Reference
In-Depth Information
substrates for microbial activity. Moreover, water content exerts diffusion con-
straints on soil O
2
, thus increasing the probability of occurrence of micro sites of
anaerobic activity where denitrification can take place (Smith
1990
) and high rates
of N
2
O production can be obtained. In this respect, soil texture and structure also
represent a proximal controlling factor. Distal controls are ecosystem processes
which have a direct effect on proximal controls, such as climate, disturbance,
agricultural management, NEP.
9.3 Available Approaches to Quantify Soil N
2
O Emissions
As underlined in the previous paragraph, multiple factors concur to determine the
temporal and spatial dynamics and the magnitude of N
2
O emissions, some exert-
ing a clear predominant role. The main drive is undoubtedly the availability of N
substrate, however, a strong interacting effect exists between N substrate and soil
water content, leading to high emission rates only when the soil water content is
sufficiently high to enhance substrate diffusion and lower oxygen tensions (Rees
et al.
2013
).
Different levels of complexity can be achieved in order to predict N
2
O emis-
sions from agricultural soils. The most complex are biogeochemical models
(Century, DNDC, ORCHIDEE, etc.) which simulate all the processes involved
in N transformations and the interaction with proximal and distal controlling fac-
tors. These models require an elevated number of data to parameterize, initialize
and eventually validate N
2
O emissions, which make the scaling up at regional or
national level quite difficult.
A general and simple procedure to produce estimates of N
2
O emissions from
agricultural practices at national scale is proposed by the IPCC Guidelines (
1997
,
2006
). In this technical document, the amount of direct emissions of N
2
O from
fertilizer addition as well as the amount of N losses via leaching or volatilization,
which contribute to indirect N
2
O production, are calculated by multiplying emis-
sion factors “EFs” by the rates of N applications. The environmental parameters
which might influence N losses are not explicitly included in the calculations with
few exceptions, where EFs might change with quality or semi-quantitative classes
of environmental variables. Also, direct N
2
O emissions from soils are linearly
dependent from fertilizer addition rates (EF 1 % of added N for temperate agricul-
tural ecosystems).
Although at present the IPCC approach is, in most cases, the sole approach
which can be used due to lack of data for a more detailed analysis, it presents lim-
its which must be taken into account. For example, environmental conditions
vary widely between countries and within each country. In Italy, for example, cli-
mate variations from sub-humid to arid bioclimate, going from the Alps to the
Southern regions, might significantly influence the magnitude of direct and indirect
N
2
O emissions in different regions. Also, Bouwman et al. (
2002b
) has shown that
N
2
O emissions increase exponentially with increase of N fertilizer input and that
