6533b7defe1ef96bd12766e9

RESEARCH PRODUCT

Cropland and grassland management

Emanuele LugatoLoris VescovoD. GianelleAlessandro PeressottiAgata Novara

subject

Bilancio del carboniobusiness.industryAgroforestrySimulation modelingEddy covarianceGreenhouse gas inventoryContext (language use)AgricultureSoil carbonSoil carbonGHG balanceModellingAgricolturaSuoloAgricultureGreenhouse gasEnvironmental scienceLand use land-use change and forestryModellisticabusinessWater resource managementSettore AGR/02 - AGRONOMIA E COLTIVAZIONI ERBACEE

description

According to the latest National Inventory, the Italian agricultural sector is a source of GHGs with 34.5 Mt of CO2 eq in 2009, corresponding to 7 % of the total emissions (excluding LULUCF). In particular, more than half (19.1 Mt of CO2 eq) are N2O emissions from soils. Although the national methodology is in accordance with Tier 1 and 2 approaches proposed by the IPCC (2006), still empirical emission factors are used to assess the emission from fertilizer (e.g. 0.0125 kg N2O–N kg−1 N from synthetic fertilizers). Disaggregated data at sub-national level, including models and inventory measurement systems required by higher order methods (i.e. Tier 3), are not available in Italy so far and comparisons with the other two approaches cannot be performed at the moment. Despite the large soil organic carbon pool in the agricultural soils and the recent institutionalization of the ‘National Registry for Carbon sinks’ by a Ministerial Decree on 1st April 2008, the last Italian greenhouse gas Inventory did not report CO2 emissions from the agricultural sector. In this context, this chapter wants to summarize the main outcomes coming from the main long-term experiments present in Italy by integrating experimental and modeling approaches, which can provide national emission rates and a solid base to test and calibrate simulation models to estimate greenhouse gases emissions from Italian agricultural soils. What emerges clearly from the analysis is that the agro-ecosystems may sequester large amount of SOC if appropriate management practices are adopted. Moreover, the use of simulation models calibrated at local level and spatially applied, as done for the Carboitaly project, may certainly reduce the uncertainty of these estimations.

10.1007/978-3-642-32424-6_10http://hdl.handle.net/10449/25173