Search

The objective of our research is to extend current conservation applications of modern portfolio theory (MPT) to develop a framework for the cost-efficient budget distribution for a forest carbon payment program that optimizes risk-reward trade-offs in the presence of economic growth uncertainty over time. We consider correlation across space and time of the fluctuating opportunity costs of restoring forestland under changing future economic conditions using a case study of eight states in the central and southern Appalachian region of the United States. The findings suggest that optimal budget allocation decisions that ignore the covariance component of the spatial variance-covariance structure of forest carbon returns fail to minimize the true risk of conservation investment for any level of expected return. The importance of incorporating the spatial covariance in targeting conservation payments is made explicit through alternative approaches using multi-objective (mean-variance) optimization and an ex post analysis with and without the covariance component of the spatial variance-covariance structure of forest carbon return on investment (ROI). A comparison of these approaches against our MPT-based approach revealed misleading risk-return expectations if the ROI covariance is ignored in the spatial targeting of forest carbon payments under uncertainty. Key words: forest carbon payment, economic growth uncertainty, modern portfolio theory, return on investment, spatial variance-covariance. L'objectif de notre recherche est d'etendre les applications actuelles de la theorie moderne du portefeuille (TMP) dans le domaine de la conservation pour developper un cadre budgetaire rentable applique a un programme de paiement pour le carbone forestier qui optimise les compromis entre les risques et les recompenses dans un contexte d'incertitude de croissance economique, et ce, dans le temps. Nous considerons les correlations spatiale et temporelle de la fluctuation des couts d'opportunite de la restauration des terres forestieres dans des conditions economiques futures changeantes en utilisant une etude de cas pour huit etats des regions centrale et meridionale des Appalaches aux Etats-Unis. Les resultats indiquent que les decisions d'allocations budgetaires optimales qui ignorent la covariance en lien avec la structure de la variance-covariance spatiale des rendements du carbone forestier ne parviennent pas a minimiser le risque reel des investissements en conservation, et ce, pour tous les niveaux de rendement attendu. L'importance d'integrer la covariance spatiale dans le ciblage des paiements de conservation est explicite par le biais d'approches alternatives qui utilisent l'optimisation multi-objectifs (moyenne-variance). Une analyse ex post avec et sans la composante de covariance de la structure variance-covariance spatiale du retour sur investissement (RSI) du carbone forestier est aussi utilisee. Une comparaison de ces approches par rapport a notre approche basee sur la TMP a revele des previsions erronees en matiere de risque et de rendement si la covariance du RSI etait ignoree dans le ciblage spatial des paiements pour le carbone forestier dans un contexte d'incertitude. [Traduit par la Redaction] Mots-cles : paiement pour le carbone forestier, incertitude de la croissance economique, theorie moderne du portefeuille, retour sur investissement, variance-covariance spatiale., 1. Introduction Anthropogenic climate change, a consequence of long-standing increments in atmospheric greenhouse gas (GHG) concentrations, remains a major global issue (Boden et al. 2017). In the United States alone, [...]

Determining optimal management practices for the profitable production of perennial energy crops is critical for scaling up production beyond experimental levels. Although many experimental field studies have examined the effects of management practices on the performance of miscanthus and switchgrass, there are no recommendations for economically optimal nitrogen (N) application rates and how they should vary spatially and with the age of the energy crop as well as on optimal rotation age of the energy crop to maximize profits. We develop a modeling framework to determine economically optimal crop management decisions and simulate the variability under various scenarios for miscanthus and switchgrass production across 2287 counties in the rainfed United States. We find that profit‐maximizing N recommendations for these crops vary across maturity stages and regions and can increase the landowner's profits compared with a uniform N rate across ages and regions. We also find that the optimal rotation for these crops is shorter than the productive physical lifespan (15–20 and 10 years for miscanthus and switchgrass, respectively). Specifically, the N rate that maximizes the economic returns is negligible for miscanthus and 111 kg ha−1 for switchgrass production at age 2. The mean profit‐maximizing N rate increases with age for miscanthus, peaking at 151 kg ha−1 at age 11 before declining to 114 kg ha−1 at the optimal rotation age of 13 years while that for switchgrass is 150 kg ha−1 for middle‐aged stands and declines to 114 kg ha−1 at the optimal rotation of 8–9 years. We find that miscanthus is the most profitable energy crop in the northern region of the rainfed United States while switchgrass is most profitable in the south of the rainfed United States. Our findings are useful for improving assessments of the profitability of energy crops and guiding future management decisions by landowners. Experimental field studies have examined the effects of management practices on the performance of miscanthus and switchgrass, but there are no recommendations for economically optimal nitrogen (N) application rates and how they should vary spatially and with the age of the energy crop as well as the optimal rotation age of these crops to maximize the economic returns. We develop a modeling framework to determine economically optimal management decisions for miscanthus and switchgrass production in the rainfed United States under various scenarios. Our findings are useful for guiding future energy crop management decisions by landowners. [ABSTRACT FROM AUTHOR]

This study reports size-resolved dithiothreitol (DTT)-based oxidative potential (OP: total and water-soluble) in rural kitchens using liquefied petroleum gas (LPG), firewood (FW), and mixed biomass (MB) fuels in northeastern (NE) India. In comparison to LPG, volume-normalized total OP (OP total(v) DTT) was enhanced by a factor of ∼5 in biomass-using kitchens (74 ± 35 to 78 ± 42 nmol min−1 m−3); however, mass-normalized total OP (OP total(m) DTT) was similar between LPG and FW users and higher by a factor of 2 in MB-using kitchens. The water-insoluble OP (OP wi(v, m) DTT) fraction in OP total(v, m) DTT was greater than 50% across kitchens. Size distributions across kitchens and OPDTT categories ranged from unimodal to trimodal. OP ws(v) DTT was driven by metals as well as organics across size fractions while OP wi(v) DTT was majorly constrained by metals with an increasing importance of organics in fine particles of biomass-using kitchens. Multiple linear regression analysis revealed that Cu and Ba explained 71% of the OP total(v) DTT variability in LPG-using kitchens, while water-soluble organic carbon (WSOC) and Ba were responsible for 44% variability in FW-using kitchens. Finally, the high internal dose of OP total(v) DTT (28–31 nmol min−1 m−3) in biomass-using kitchens established the severity of oxidative stress on the exposed population. [Display omitted] • Size-resolved measurement of oxidative potential (OP) in indoor kitchens of NE India. • Biomass-using kitchens show ∼5 times enrichment of extrinsic total OP over LPG. • Water-insoluble OP contributes more than 50% to total OP across kitchens. • Differential role of metals and organics in driving OP across particle size and fuel types. [ABSTRACT FROM AUTHOR]