Environmental cost and impacts of chemicals used in agriculture: An integration of emergy and Life Cycle Assessment

Modern intensive agriculture worldwide is generating increasing environmental pressure, which prevents its sustainable development. A number of agricultural sustainability assessment approaches and methodological frameworks have been developed by research worldwide to assess the environmental costs and impacts of resources used in agricultural production. A joint use of Life Cycle Assessment (LCA, to assess a process' performance and environmental impacts) and Emergy Accounting (EMA, to estimate environmental support to resource generation and provision) is proposed in this study. The goal is not only to ascertain the environmental ‘cost’ of production of selected chemical resources used in agricultural processes, but also to develop a reliable calculation procedure capable to integrate the two approaches (LCA and EMA), while considering their different allocation algebra and space-time scales of application. Specifically, the UEVs of glyphosate and urea, which are respectively the most used herbicide and nitrogen fertilizer used in worldwide agriculture, are calculated, yielding values of 2.47E+13 sej/kg and 7.07E+12 sej/kg, respectively. In order to do so, UEVs of intermediate process chemicals such as ammonia, acetic anhydride, chlorine gas, formaldehyde, phosphorous chloride, and sodium hydroxide have also been calculated or updated, thus providing at the same time a procedure and a set of values potentially useful for future studies. The LCA impacts of agro-chemicals in China are compared to worldwide averages from the Ecoinvent database, and the UEVs for several chemicals are also compared to previous estimates from published emergy literature

Negative Cooperativity in the Nitrogenase Fe Protein Electron Delivery Cycle

Nitrogenase catalyzes the ATP-dependent reduction of dinitrogen (N2) to two ammonia (NH3) molecules through the participation of its two protein components, the MoFe and Fe proteins. Electron transfer (ET) from the Fe protein to the catalytic MoFe protein involves a series of synchronized events requiring the transient association of one Fe protein with each αβ half of the α2β2 MoFe protein. This process is referred to as the Fe protein cycle and includes binding of two ATP to an Fe protein, association of an Fe protein with the MoFe protein, ET from the Fe protein to the MoFe protein, hydrolysis of the two ATP to two ADP and two Pi for each ET, Pi release, and dissociation of oxidized Fe protein-(ADP)2 from the MoFe protein. Because the MoFe protein tetramer has two separate αβ active units, it participates in two distinct Fe protein cycles. Quantitative kinetic measurements of ET, ATP hydrolysis, and Pi release during the presteady-state phase of electron delivery demonstrate that the two halves of the ternary complex between the MoFe protein and two reduced Fe protein-(ATP)2 do not undergo the Fe protein cycle independently. Instead, the data are globally fit with a two-branch negative-cooperativity kinetic model in which ET in one-half of the complex partially suppresses this process in the other. A possible mechanism for communication between the two halves of the nitrogenase complex is suggested by normal-mode calculations showing correlated and anticorrelated motions between the two halves

What are the energy and environmental impacts of adding battery storage to photovoltaics? A generalized life cycle assessment

Renewable electricity generation is intermittent and its large‐scale deployment will require some degree of energy storage. Although best assessed at grid level, the incremental energy and environmental impacts of adding the required energy storage capacity may also be calculated specifically for each individual technology. This paper deals with the latter issue for the case of photovoltaics (PV) complemented by lithium‐ion battery (LIB) storage. A life cycle assessment (LCA) of a 100MW ground‐mounted PV system with 60MW of (lithium‐manganese oxide) LIB, under a range of irradiation and storage scenarios, show that energy pay‐back time and life‐cycle global warming potential increase by 7% to 30% (depending on storage duration scenarios), with respect to those of PV without storage. Thus the benefits of PV when displacing conventional thermal electricity (in terms of carbon emissions and energy renewability) are only marginally affected by the addition of energy storage

Energy return on investment (EROI) of solar PV: an attempt at reconciliation

In a recent Point of View piece, William Pickard made an excellent case for the importance of energy return on investment (EROI) as a useful metric for assessing longterm viability of energy-dependent systems from bands of hunter-gatherers, to modern society and, finally to the specific case of a solar electricity generating project. The author then highlighted a seeming disparity between a number of different research groups 1) Fthenakis group at Brookhaven, 2) Prieto group in Madrid, 3) Weißbach group in Berlin, and 4) Brandt group at Stanford all of whom have recently published values for the EROI (or similar metric) for solar photovoltaic (PV) technologies. Unfortunately, in so doing, the author directly compares results calculated using different system boundaries, methodologies, and assumptions. It is the purpose of this response to (1) adjust the results for the four groups to better compare like systems and (2) outline details of two methodological issues common in the EROI literature. The objective of these two activities is to explain much of the apparent disparity between the different EROI values produced by the different research groups