Development of viable bioenergy economies will require large increases in biomass feedstock production. Improved methods are needed to quantify production potential based on land availability, land suitability, biomass yield, and cost. We developed such a method and applied it throughout New York State. While maintaining existing forest and agricultural production, we quantified additional sustainable biomass production potential using geospatial and yield modeling that integrates remotely sensed and survey data for land cover, soil type, climate patterns, and crop yields and then applied multiple sustainability constraints. Nearly 680,000 ha with varying quality was found to be available and suitable for new biomass production. Predicted yields ranged from 7.8 to 18.3 Mg/ha for short-rotation willow and 6.9-16.3 Mg/ha for perennial grasses for a total production potential of 8.2 Tg/ year. Increased forest harvest could produce an additional 4.3 Tg/year of hardwood and 1.6 Tg/year of softwood. In total, an additional 14.2 Tg/year of biomass for bioenergy could be produced while maintaining existing agricultural and forest production. This new biomass, before processing, would contain energy equivalent to 7.4 % of 2012 New York energy use (3.4 % if converted to ethanol). AbbreviationsDEM Digital elevation model ESRI Environmental Systems Research Institute GHG Greenhouse gas GIS Geographic information system K P o t a s s i u m LULC Land use/land cover Mg/year Megagram/year (assume dry matter unless otherwise stated) MRLC Multi-Resolution Land Characteristics NCCPI National Commodity Crop Productivity Index NY New York N N i t r o g e n NLCD National Land Cover Database P P h o s p h a t e
Background: Since the industrial revolution, human population and fossil energy consumption have steadily increased. With concerns over fossil energy impact on air quality and global climate, there is increasing interest in collection and conversion of non-fossil energy feedstocks. These finite renewable feedstocks (biomass, solar, wind) provide a challenge based on their land-limited supply and temporal availability. Consequently, society needs methodologies to increase end-user efficiency to maximize the energetic utility and sociological benefit from the finite land base. Methods: This paper presents a methodology for evaluating whole system effectiveness from a finite unit of biomass feedstock. By analyzing conversion of raw energy inputs into final energy services (FES) delivered in the form of transport or heat to society, we assess the FES returned on energy investment (ERoEI fes). Comparison of ERoEI fes across 11 different conversion pathways illustrates the relative delivered social benefit of each pathway derived from the same finite feedstock. Results: We found previously that New York (NY) could sustainably produce 14.2 Tg/y of biomass feedstocks from agriculture and forestry (equivalent to 7% of NY's primary energy consumption of 3.9 EJ). We found that high value FES as a percentage of energy in the biomass feedstock ranged from 5 to 15% for transport and 12 to 71% for heat (residential or commercial). However, the FES provided for six pathways was more than 2-fold higher if co-products were used. This method (1) internalizes energetic processing and use losses (2) to compare pathways and systems (3) that maximize services and value derived from land-limited sustainably harvested resources (4) thus providing a holistic approach increasing the value of a unit of land to generate primary energy resources, sustainably. Conclusion: This case study provides a framework to assess a range of conversion pathways for any finite energy feedstock for society. Across all biomass types and conversion processes, the replicable ERoEI fes methodology provides a foundation for decision-makers to compare FES delivered and then develop policies that reap the most benefit per unit of finite feedstock, thus assisting in more effective transition away from fossil-based feedstocks.
Livestock manure can be a significant source of greenhouse gases (GHG) including methane (CH) and nitrous oxide (NO). However, GHG emissions are strongly affected by the type of waste management system (WMS) used. For example, CH emissions increase substantially under anaerobic conditions that occur in many WMSs. There is a need for improved estimates at regional and national scales of the effect of WMSs on GHG emissions and identification of opportunities and associated costs to mitigate these emissions. As New York State is the fourth largest dairy producer in the country, our objectives were to quantify (i) the changes in WMS and associated GHG emissions over time, (ii) a methane conversion factor (MCF) derived from existing data from three covered manure storage units in New York, and (iii) the benefit and cost of installing covers and flares to destroy CH from existing storage units. We found that GHG emissions from changing manure management increased from 0.7 Tg carbon dioxide equivalents per year (COe yr) in 1992 to 1.6 Tg COe yr in 2012. We derived an MCF of 0.61 based on data from dairy manure storage units with covers that captured and flared CH in 2010 and used this MCF to project GHG reductions for a statewide mitigation scenario in year 2022. This scenario, covering and flaring CH from 662 manure storage units, mitigates 1.8 Tg COe annually or 62% of manure GHG (CH and NO) at an estimated cost of $224 million ($0.005 L milk or $13 Mg COe).
Herman Daly once identified the absurdity of shipping Danish cookies to the United States; if efficiency were in fact ‘economic’, one might just e-mail the recipe, save the fuel, reduce the greenhouse gases and still enjoy the cookie. This argument playfully illustrates that resources are scarce, ideas are Inherently Not Scarce (INS) and current financial systems are inefficient and not ‘economical’. The unprecedented industry of 7.5 billion people is now concerned about the resulting scarcity and pollution of the finite resource base. Until humanity shares inherently-not-scarce ideas for effectively managing what is in a steady state, scarcity and pollution will be a constant source of crisis on the landscape. Since 2004, I have made transforming colour field paintings with mud taken from the most pristine to the most toxic landscapes of northeast United States of America (NE USA). Although difficult to see individually, microbes existing within mud photosynthesize pigments. As a species grows from individual to colony, it becomes visible as pointillist pigments amass horizontal blocks of transient colour. As these bacteria express themselves (i.e., live: consume, reproduce, deplete resources, release wastes), they exhaust their habitat and create an altered landscape suitable to a successor. Like us, bacteria are bound by the law of conservation of mass; they constantly select and reject resources from the finite landscape. The resulting processes of growth and decay are intimately linked inversions resulting in beautiful transforming colourfields. As evidenced by my vibrant and literal portraits made from mud, these simple, highly adaptable, single-cell organisms craft a unique, colourful and synthetic existence. As a model system, they exhibit a viable steady state of infinite expression in a finite landscape where life and landscape is an intimate, malleable and reciprocal whole. Here I discuss the beauty of our landfill paradises, made evident by mud taken at two different kinds of landfilled ecosystems in New York City.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.