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Author  |
Bennetzen, E.H.; Smith, P.; Porter, J.R. |
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Title |
Decoupling of greenhouse gas emissions from global agricultural production: 1970-2050 |
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Journal Article |
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Year |
2016 |
Publication |
Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
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Volume |
22 |
Issue |
2 |
Pages |
763-781 |
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Keywords |
climate change; energy use; global agriculture; greenhouse gas emissions; land use; mitigation; sustainable intensification |
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Abstract |
Since 1970 global agricultural production has more than doubled; contributing ~1/4 of total anthropogenic greenhouse gas (GHG) burden in 2010. Food production must increase to feed our growing demands, but to address climate change, GHG emissions must decrease. Using an identity approach, we estimate and analyse past trends in GHG emission intensities from global agricultural production and land-use change and project potential future emissions. The novel Kaya-Porter identity framework deconstructs the entity of emissions from a mix of multiple sources of GHGs into attributable elements allowing not only a combined analysis of the total level of all emissions jointly with emissions per unit area and emissions per unit product. It also allows us to examine how a change in emissions from a given source contributes to the change in total emissions over time. We show that agricultural production and GHGs have been steadily decoupled over recent decades. Emissions peaked in 1991 at ~12 Pg CO2 -eq. yr(-1) and have not exceeded this since. Since 1970 GHG emissions per unit product have declined by 39% and 44% for crop- and livestock-production, respectively. Except for the energy-use component of farming, emissions from all sources have increased less than agricultural production. Our projected business-as-usual range suggests that emissions may be further decoupled by 20-55% giving absolute agricultural emissions of 8.2-14.5 Pg CO2 -eq. yr(-1) by 2050, significantly lower than many previous estimates that do not allow for decoupling. Beyond this, several additional costcompetitive mitigation measures could reduce emissions further. However, agricultural GHG emissions can only be reduced to a certain level and a simultaneous focus on other parts of the food-system is necessary to increase food security whilst reducing emissions. The identity approach presented here could be used as a methodological framework for more holistic food systems analysis. |
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1354-1013 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4706 |
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Author |
Bourgeois, C.; Fradj, N.B.; Jayet, P.-A. |
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Title |
How cost-effective is a mixed policy targeting the management of three agricultural N-pollutants |
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Journal Article |
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Year |
2014 |
Publication |
Environmental Modelling & Assessment |
Abbreviated Journal |
Environmental Modelling & Assessment |
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Volume |
19 |
Issue |
5 |
Pages |
389-405 |
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Keywords |
cost-effectiveness; mixed policy; n-input tax; land use policy; nitrogen pollutants; bioeconomic model; mathematical linear programming; miscanthus; nonpoint pollution-control; reed canary grass; biomass production; abatement costs; energy crop; miscanthus; nitrogen; model; efficiencies; instruments |
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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. |
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1420-2026 |
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TradeM |
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MA @ admin @ |
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4661 |
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Author |
Camacho, C.; Pérez-Barahona, A. |
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Title |
Land use dynamics and the environment |
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Journal Article |
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Year |
2015 |
Publication |
Journal of Economic Dynamics and Control |
Abbreviated Journal |
Journal of Economic Dynamics and Control |
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52 |
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Pages |
96-118 |
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Keywords |
land use; spatial dynamics; pollution; climate-change; air-pollution; agriculture; instability; allocation; principle; pattern; quality; health; impact |
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This paper builds a benchmark framework to study optimal land use, encompassing land use activities and environmental degradation. We focus on the spatial externalities of land use as drivers of spatial patterns: land is immobile by nature, but local actions affect the whole space since pollution flows across locations resulting in both local and global damages. We prove that the decision maker problem has a solution, and characterize the corresponding social optimum trajectories by means of the Pontryagin conditions. We also show that the existence and uniqueness of time-invariant solutions are not in general guaranteed. Finally, a global dynamic algorithm is proposed in order to illustrate the spatial-dynamic richness of the model. We find that our simple set-up already reproduces a great variety of spatial patterns related to the interaction between land use activities and the environment. In particular, abatement technology turns out to play a central role as pollution stabilizer, allowing the economy to reach a time-invariant equilibrium that can be spatially heterogeneous. (C) 2014 Elsevier B.V. All rights reserved. |
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2015-10-09 |
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0165-1889 |
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TradeM, ft_macsur |
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Call Number |
MA @ admin @ |
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4698 |
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Author |
Cantelaube, P.; Jayet, P. |
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Title |
Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level |
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Journal Article |
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Year |
2012 |
Publication |
Land Use Policy |
Abbreviated Journal |
Land Use Policy |
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29 |
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Pages |
35-44 |
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Keywords |
Downscaling; Land use; Spatial statistics; Farm-groups; Farm Accountancy Data Network; FADN |
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There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses). European farm-groups are provided through the Farm Accountancy Data Network (FADN) as statistical information delivered at regional level. The aim of the study is to map locally farm-group probabilities within each region. The mapping of the farm-groups is done in two steps: (1) by mapping locally the co-variables associated to the farm-groups, i.e. altitude and land uses; (2) by using regional FADN data as a priori knowledge for transforming land uses and altitude information into farm-groups location probabilities within each region. The downscaling process focuses on the land use mapping since land use data are originally point information located every 18 km. Interpolation of land use data is done at 100 m by using co-variables like land cover, altitude, climate and soil data which are continuous layers usually provided at fine resolution. Once the farm-groups are mapped, European Policy and global changes scenarios are run through an agro-economic model for assessing environmental impacts locally. |
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Notes |
TradeM, ftnotmacsur |
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Call Number |
MA @ admin @ |
Serial |
4582 |
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Author |
Dietrich, J.P.; Popp, A.; Lotze-Campen, H. |
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Title |
Reducing the loss of information and gaining accuracy with clustering methods in a global land-use model |
Type |
Journal Article |
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Year |
2013 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
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Volume |
263 |
Issue |
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Pages |
233-243 |
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Keywords |
aggregation; downscaling; clustering; information conservation; land use model; scale; scales; agriculture; simulation; dynamics; pattern |
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Abstract |
Global land-use models have to deal with processes on several spatial scales, ranging from the global scale down to the farm level. The increasing complexity of modern land-use models combined with the problem of limited computational resources represents a challenge to modelers. One solution of this problem is to perform spatial aggregation based on a regular grid or administrative units such as countries. Unfortunately this type of aggregation flattens many regional differences and produces a homogenized map of the world. In this paper we present an alternative aggregation approach using clustering methods. Clustering reduces the loss of information due to aggregation by choosing an appropriate aggregation pattern. We investigate different clustering methods, examining their quality in terms of information conservation. Our results indicate that clustering is always a good choice and preferable compared to grid-based aggregation. Although all the clustering methods we tested delivered a higher degree of information conservation than grid-based aggregation, the choice of clustering method is not arbitrary. Comparing outputs of a model fed with original data and a model fed with aggregated data, bottom-up clustering delivered the best results for the whole range of numbers of clusters tested. (C) 2013 Elsevier B.V. All rights reserved. |
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0304-3800 |
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TradeM |
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MA @ admin @ |
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4488 |
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