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Mapping Urban Biomass Production of Food and Fuel(Saha et al., 2014)Proceedings of the International Symposium on Sustainable Systems and Technologies, v2 (2014)

Mapping Urban Biomass Production for Food and Fuel

Mithun Saha Doctoral Candidate, Northeastern University, saha.m@husky.neu.eduLauren Martin Graduate Student, Northeastern University, martin.la@husky.neu.eduMatthias Ruth Professor, Northeastern University, m.ruth@neu.eduJane Amidon Professor, Northeastern University, j.amidon@neu.eduMatthew Eckelman Assistant Professor, Northeastern University, m.eckelman@neu.edu

Abstract. This study describes the geospatial cataloging and mapping existing and potential locations and schemes for urban biomass production in Boston. Long-standing research from engineering thermodynamics and energy systems has shown that densely settled cities will never be practically able to provide all of their energy or food needs. Apparently, there is an increasing interest in producing bioenergy in the Northeast US because it is one of the few promising local renewable source of fuels that can be used both for heat and power. As with many coastal cities, the Boston metro area has many small-scale terrestrial production sites for food and fuel that makes the city a favorable location for biomass production. Here we performed a geographic information system (GIS) based analysis of high-resolution aerial images using ArcGIS and Google earth pro to identify and analyze suitable parcels that include existing public and private vacant spaces and potential marginal lands with favorable soil quality and ground slopes. 5150 ha (52 km2) of available areas have been estimated that include both above ground and rooftop areas. Among the bioenergy crops evaluated, miscanthus and willow were found most suitable and productive energy crops that can be grown. The resulting spatial dataset demonstrates that urban biomass production is an extensive land use type with wide variations in the distribution of sites across the city. The net bioenergy outcome from miscanthus production can be approximately 50GWh which is 10% of the city of Boston primary energy consumption in the year 2011. The study results also suggest opportunities for scaling up existing food production networks as well as identifying possible locations for biomass cogeneration within the city limits.

Proceedings of the International Symposium on Sustainable Systems and Technologies (ISSN 2329-9169) is published annually by the Sustainable Conoscente Network. Melissa Bilec and Jun-Ki Choi, co-editors. ISSSTNetwork@gmail.com.

Copyright 2014 by Mithun Saha, Lauren Martin, Matthias Ruth, Jane Amidon, Matthew Eckelman, Licensed under CC-BY 3.0.Cite as:Mapping urban biomass production for food and fuel, Proc. ISSST, Mithun Saha. Doi information v2 (2014)

Introduction. We are living in an energy hungry world. On one side, there is increasing demand of energy and on the other pressure is mounting to develop renewable energy sources that can fulfill demand as well as mitigate the effect of climate change. Accordingly, the production of renewable energy is increasing in the United States. A study conducted by Natural Resource Defense Council reported an increase of more than 300% in the past decade (1). While no single type of renewable energy will fulfill the needs, bioenergy promises to become a growing portion of the US energy market (2). Many studies have documented renewable energy resource estimates for the United States that includes national, regional and local (city) scale.

The majority (75%) of energy demand is concentrated in urban areas, with more than 50% of the global population currently living in cities (3). While it may not be possible nor desirable to for cities to produce all of the final energy they require, there are sustainability and resilience benefits to locating energy production sites within cities. The focus of this work is on estimating the potential for urban bioenergy Some studies identified local scale bioenergy production study as best suited and reliable for identifying suitable parcels for biomass production by incorporating detailed soil data as well as road and riparian boundaries (4). Also, local scale studies can be capable of incorporating socio-economic inputs as well as mapping for a specific bioenergy species to achieve better management goals especially for the city dwellers.

The current work took the initiative of estimating the energy crop-based bioenergy potential for Boston, a coastal urban areas located in northeastern United States. The possible parcels have been spatially identified and specific suitable energy crops and crop yield information have been estimated based on the available data. Later, the bioenergy production potential and community based survey will be performed to identify the socio-economic indicators affecting biomass and bioenergy production scenarios. The outcome of the study looks to provide policy makers and bioenergy developers with a better understanding of the distribution and size of potential bioenergy sites, to help determine if, where, and for what purpose urban biomass might be grown and utilized, and thus guides future strategic investment and policy formulation.

Hypothesis (or Research Question). The specific research question here is what is the extent to which Bostons marginal lands could be used for strategic biomass growth and processing to support small-scale bioenergy production for critical facilities and/or energy demand clusters such as district heating loops and microgrids.

Investigative Method. The study method incorporates identifying suitable existing and potential parcels within the city that can be used for biomass production. Based on the literature survey, GIS based site suitability model was developed using ArcGIS Model Builder tool (ESRI Inc.) that incorporates input landcover (parcel) data and other necessary spatial datasets, geo-processing tools and output marginal land layer (Figure 1). Existing land cover data from MassGIS was used as the input features. Then the potential marginal land areas have been estimated by excluding water areas, roads, rails, buildings and conservation lands from input parcel data. Later, the above ground areas have been further trained by using fine scale soils data obtained from the Soil Survey Geographic Database (SSURGO), 1:24,000) that includes soil quality and ground slope data (