Siting analysis of farm-based centralized anaerobic digester systems for distributed generation using GIS

Ma, Jing; Scott, Norman R.; DeGloria, Stephen D.; Lembo, Arthur J.

doi:10.1016/j.biombioe.2004.12.003

Cited by 170 publications

(93 citation statements)

References 12 publications

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“…Table 2 lists the constraints on SPPSS, which are designed based on published data [12,26,49] in combination with the actual situation of the study area, with the aim of facilitating the transport of raw materials and reducing the impact of SPPs on human living and production activities. The geospatial data involved in the aforementioned constraints can be obtained using GIS spatial analysis methods.…”

Section: Constraintsmentioning

confidence: 99%

A Spatially Explicit Optimization Model for Agricultural Straw-Based Power Plant Site Selection: A Case Study in Hubei Province, China

Xiang

Wang

et al. 2017

Sustainability

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Using agricultural straw to generate electricity is an effective approach for relieving the pressure of procuring a reliable energy supply and reducing environmental pollution. Because the locations of the power plants have a significant impact on the supply of raw materials and the cost of transportation, it is important to choose reasonable locations for power plants. To solve the problem of straw-based power plant site selection (SPPSS), in this paper, a spatially explicit optimization model is proposed. Compared to the existing research, the present study makes the following major contributions: (1) The agricultural land quality evaluation dataset, combined with the cropping system and theoretical yield information, is used as the basic data to estimate agricultural straw yields, thereby increasing the accuracy of the straw yield and spatial distribution estimates. (2) Geographic information system (GIS) techniques are employed to improve an artificial immune system (AIS), which is an effective and flexible approach for solving optimization problems. The Chinese province of Hubei is selected as the experimental area to evaluate the effectiveness of the proposed model. The experimental results demonstrate that of the 34.89 million tons of agricultural straw produced in Hubei Province each year, 17.45 million tons can be used for electricity generation. The optimization schemes generated by the proposed model are feasible. Our results are expected to provide an important decision-making basis for straw-based power plant (SPP) development planning in Hubei Province.

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Section: Constraintsmentioning

confidence: 99%

A Spatially Explicit Optimization Model for Agricultural Straw-Based Power Plant Site Selection: A Case Study in Hubei Province, China

Xiang

Wang

et al. 2017

Sustainability

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“…GIS-based methods have been used to calculate regional biogas potential [6,[30][31][32][33][34]. Spatial distribution of biomass resources and the most effective utilization location for energy production can be investigated by combining location optimization methods and GIS.…”

Section: Energy Crops and Increased Bioenergy Production On Cutaway Pmentioning

confidence: 99%

Planning land use for biogas energy crop production: The potential of cutaway peat production lands

Laasasenaho

Lensu

Rintala

2016

Biomass and Bioenergy

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Each year, thousands of hectares of peatland that had been harvested are being released in Finland, which can offer an opportunity to increase energy crops and attain the bioenergy targets for non-agriculture lands. In this study, the Geographic Information System (GIS) method was used to improve the assessment of decentralized renewable energy resources. The amount of peat production lands and future cutaway areas for energy crop production was calculated as a case study by using ArcGIS and the Finnish Topographic database. There are almost 1,000 km 2 of peat production lands in Finland, and theoretically, approximately 300 km 2 of cutaway peatlands could be used for energy crops after 30 years. The dry biomass yield of reed canary grass (Phalaris arundinacea) or timothy-fescue grass (mix of Phleum pratense and Festuca pratensis)could be higher than 100 Gg y -1 in these lands indicating methane potential of approximately 2 300 GWh. The exhausted peat production areas in the western region of Finland have significant potential for use for energy crops; North and South Ostrobothnia account for almost 45% of the total peat production land. A future goal could be to use the cutaway peat production lands more efficiently for bioenergy to mitigate climate change. Since the use of wastelands (including peatlands) are being considered in Europe as a way to avoid competition with food production, the GIS method used in the study to identify suitable peat lands could be applicable to biomass resource studies being conducted in many countries.

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“…The design, location and fuelling of bioenergy and EfW facilities involves numerous economic and spatial choices, and GIS-based decision support systems are useful at all stages, from the identification of suitable facility locations and sources of biofuel and/or waste (Noon & Daly, 1996;Dagnall et al, 2000;Voivontas et al, 2001;Ma et al, 2005), to the routing of fuel materials to proposed facilities (Graham et al 1997;Perlack & Turhollow 2003). Specifically regarding MSW, Tyson et al (1996) have made extensive use of GIS to estimate quantities of MSW that can be potentially diverted from landfill, for use in either new biomass-ethanol or new MSW-electricity facilities, and to estimate where new facilities may be located.…”

Section: Decision Support In Waste Planningmentioning

confidence: 99%

Comparing transport emissions and impacts for energy recovery from domestic waste (EfW): Centralised and distributed disposal options for two UK Counties

Bastin

Longden

2009

Computers, Environment and Urban Systems

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Many local authorities (LAs) are currently working to reduce both greenhouse gas emissions and the amount of municipal solid waste (MSW) sent to landfill. The recovery of energy from waste (EfW) can assist in meeting both of these objectives. The choice of an EfW policy combines spatial and non-spatial decisions which may be handled using Multi-Criteria Analysis (MCA) and Geographic Information Systems (GIS). This paper addresses the impact of transporting MSW to EfW facilities, analysed as part of a larger decision support system designed to make an overall policy assessment of centralised (large-scale) and 2 distributed (local-scale) approaches. Custom-written ArcMap extensions are used to compare centralised versus distributed approaches, using shortest-path routing based on expected road speed. Results are intersected with 1-kilometre grids and census geographies for meaningful maps of cumulative impact.Case studies are described for two counties in the United Kingdom (UK); Cornwall and Warwickshire.For both case study areas, centralised scenarios generate more traffic, fuel costs and emitted carbon per tonne of MSW processed.3

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Siting analysis of farm-based centralized anaerobic digester systems for distributed generation using GIS

Cited by 170 publications

References 12 publications

A Spatially Explicit Optimization Model for Agricultural Straw-Based Power Plant Site Selection: A Case Study in Hubei Province, China

A Spatially Explicit Optimization Model for Agricultural Straw-Based Power Plant Site Selection: A Case Study in Hubei Province, China

Planning land use for biogas energy crop production: The potential of cutaway peat production lands

Comparing transport emissions and impacts for energy recovery from domestic waste (EfW): Centralised and distributed disposal options for two UK Counties

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