Estimating Emissions at the Regional Scale

Knox et al. (2000) and Matthews et al. (2000b) have coupled a field-scale model of CH4 emissions from rice to GIS systems, and used available regional data on weather, soil, agronomic management and otlier variables to make regional-scale estimates of emissions. The model is based on the approach described earlier. The extrapolation is based on the following framework. 

This approach is of course limited by the availability of reliable data and the resolution of the data. An inherent problem in the np-scaling process is the interaction between variance in input parameters and non-linearity in models. This may prodnce chaotic behaviour, van Bodegom et al. (2002) discuss this in relation to CH4 emission from rice. The point at which inpnt data are averaged before making model runs may also be limited by the available computing 

Source van der Gon et al. (2000). Reproduced with kind permission of Kluwer Academic Publishers. 

However, as yet monitoring networks on atmospheric mixing ratios are not sufficiently extensive or close to continental CH4 sources to make this approach entirely reliable for rice. 

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