|
|
Bourgeois, C., Fradj, N. B., & Jayet, P. - A. (2014). How cost-effective is a mixed policy targeting the management of three agricultural N-pollutants. Environmental Modelling & Assessment, 19(5), 389–405.
Abstract: This paper assesses the cost-effectiveness of a mixed policy in attempts to reduce the presence of three nitrogen pollutants: NO (3), N O-2, and NH (3). The policy under study combines a tax on nitrogen input and incentives promoting perennial crops assumed to require low input. We show that the mixed policy improves the cost-effectiveness of regulation with regard to nitrates, whereas no improvement occurs, except for a very low level of subsidy in some cases, for gas pollutants. A quantitative analysis provides an assessment of impacts in terms of land use, farmers’ income, and nitrogen losses throughout France and at river-basin scale.
|
|
|
|
Popp, A., Rose, S. K., Calvin, K., Van Vuuren, D. P., Dietrich, J. P., Wise, M., et al. (2014). Land-use transition for bioenergy and climate stabilization: model comparison of drivers, impacts and interactions with other land use based mitigation options. Clim. Change, 123(3-4), 495–509.
Abstract: In this article, we evaluate and compare results from three integrated assessment models (GCAM, IMAGE, and ReMIND/MAgPIE) regarding the drivers and impacts of bioenergy production on the global land system. The considered model frameworks employ linked energy, economy, climate and land use modules. By the help of these linkages the direct competition of bioenergy with other energy technology options for greenhouse gas (GHG) mitigation, based on economic costs and GHG emissions from bioenergy production, has been taken into account. Our results indicate that dedicated bioenergy crops and biomass residues form a potentially important and cost-effective input into the energy system. At the same time, however, the results differ strongly in terms of deployment rates, feedstock composition and land-use and greenhouse gas implications. The current paper adds to earlier work by specific looking into model differences with respect to the land-use component that could contribute to the noted differences in results, including land cover allocation, land use constraints, energy crop yields, and non-bioenergy land mitigation options modeled. In scenarios without climate change mitigation, bioenergy cropland represents 10-18 % of total cropland by 2100 across the different models, and boosts cropland expansion at the expense of carbon richer ecosystems. Therefore, associated emissions from land-use change and agricultural intensification as a result of bio-energy use range from 14 and 113 Gt CO2-eq cumulatively through 2100. Under climate policy, bioenergy cropland increases to 24-36 % of total cropland by 2100.
|
|
