Regional Scale Biofuel Impact Assessment on Land Use and Carbon Emission - A Case Study for Haryana, India

Abstract

In the past three decades the world has seen dramatic industrialization and population growth, arousing intense land-use competition. As a result, increasing pressure occurs in both food and energy supply. Bioenergy, especially biofuels that are both renewable clean supplements for non-renewable fossil fuels and also strong competitors of arable land for foodcrops, draw great attention from both sides. In India, biofuel initiatives have gained momentum with the national biofuel policy targeting 20% blending of fossil fuels by 2017 and 27% by 2050. Since India is also involved in fast development and owns the second largest population in the world, there are typical land-use conflicts between food production, biofuels and human settlement. This study, taking the middle-north state of Haryana as an example, aims at estimating the potential to achieve policy targets and its impacts on regional land-use conflicts as well as carbon emission. This report spatially analyses land-use conflicts owing to biofuel expansion. I used an integrated modeling framework to simulate land-use change and biofuel production under two scenarios – food production with/without exportation demand. Under each scenario, three pathways of biofuel production are compared, namely bioethanol from sugarcane molasses, bioethanol from sugarcane bagasse and bioethanol from low-input high-diversity grasses. An empirical model was introduced to measure food demand and human settlement requirements due to population growth. Based on a detailed land-use classification map of Haryana, a social-environmental land-use suitability index across a number of quantitative and qualitative characteristics is constructed for each land-use type in order to define the spatial distribution behaviors. Agricultural behaviors, including carbon emission, impacts on soil organic carbon by irrigation, as well as relations to natural elements such as climate and soil conditions, are simulated by DNDC (DeNitrification-DeComposition) model. An agent-based model is used to investigate how land-use change organized within the region. Each type of land-use is defined as an intelligent agent that is able to interact with surroundings, to choose the optimal position according to land-use suitability index and to make impacts to the environment. This simulation analyzes a period of 40 years from 2010 to 2050 with spatial resolution of 1.28m x 1.28m. Then I analyze annual gaps between biofuels yield and energy target under each scenario.