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A Comparison of Major Petroleum Life Cycle Models.

ABSTRACT: Many organizations have attempted to develop an accurate well-to-pump life cycle model of petroleum products in order to inform decision makers of the consequences of its use. Our paper studies five of these models, demonstrating the differences in their predictions and attempting to evaluate their data quality. Carbon dioxide well-to-pump emissions for gasoline showed a variation of 35%, and other pollutants such as ammonia and particulate matter varied up to 100%. Differences in allocation do not appear to explain differences in predictions. Effects of these deviations on well-to-wheels passenger vehicle and truck transportation life cycle models may be minimal for effects such as global warming potential (6% spread), but for respiratory effects of criteria pollutants (41% spread) and other impact categories, they can be significant. A data quality assessment of the models' documentation revealed real differences between models in temporal and geographic representativeness, completeness, as well as transparency. Stakeholders may need to consider carefully the tradeoffs inherent when selecting a model to conduct life cycle assessments for systems that make heavy use of petroleum products.

SUBMITTER: Vineyard D

PROVIDER: S-EPMC6134862 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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A Comparison of Major Petroleum Life Cycle Models.

Vineyard Donald D Ingwersen Wesley W WW

Clean technologies and environmental policy 20170401 3

Many organizations have attempted to develop an accurate well-to-pump life cycle model of petroleum products in order to inform decision makers of the consequences of its use. Our paper studies five of these models, demonstrating the differences in their predictions and attempting to evaluate their data quality. Carbon dioxide well-to-pump emissions for gasoline showed a variation of 35%, and other pollutants such as ammonia and particulate matter varied up to 100%. Differences in allocation do ...[more]

PMID: 30220903

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Project description:An investigation into the causes of species decline should include examination of habitats important for multiple life stages. Integrating habitat impacts across life stages with life-cycle models (LCMs) can reveal habitat impairments inhibiting recovery and help guide restoration efforts. As part of the final elements of the Habitat Restoration Planning model (HARP; Beechie et al. this volume), we developed LCMs for four populations of three species of anadromous salmonids (Oncorhynchus kisutch, O. tshawytscha, and O. mykiss), and ran diagnostic scenarios to examine effects of barrier removal, fine sediment reduction, wood augmentation, riparian shade, restoration of the main channel and bank conditions, beaver pond restoration, and floodplain reconnection. In the wood scenario, spawner abundance for all populations increased moderately (29-48%). In the shade scenario, spring-run Chinook salmon abundance increased the most (48%) and fall-run Chinook salmon and steelhead were much less responsive. Coho responded strongly to the beaver pond and floodplain scenarios (76% and 54%, respectively). The fine sediment scenario most benefitted fall- and spring-run Chinook salmon (32-63%), whereas steelhead and coho were less responsive (11-21% increase). More observations are needed to understand high fine sediment and its impacts. Our LCMs were region-specific, identifying places where habitat actions had the highest potential effects. For example, the increase in spring-run Chinook salmon in the wood scenario was driven by the Cascade Mountains Ecological Region. And, although the overall response of coho salmon was small in the barrier removal scenario (6% increase at the scale of the entire basin), barrier removals had important sub-regional impacts. The HARP analysis revealed basin-wide and regional population-specific potential benefits by action types, and this habitat-based approach could be used to develop restoration strategies and guide population rebuilding. An important next step will be to ground-truth our findings with robust empirically-based estimates of life stage-specific survivals and abundances.

Project description:A matrix population model is a convenient tool for summarizing per capita survival and reproduction rates (collectively vital rates) of a population and can be used for calculating an asymptotic finite population growth rate (?) and generation time. These two pieces of information can be used for determining the status of a threatened species. The use of stage-structured population models has increased in recent years, and the vital rates in such models are often estimated using a life table analysis. However, potential bias introduced when converting age-structured vital rates estimated from a life table into parameters for a stage-structured population model has not been assessed comprehensively. The objective of this study was to investigate the performance of methods for such conversions using simulated life histories of organisms. The underlying models incorporate various types of life history and true population growth rates of varying levels. The performance was measured by comparing differences in ? and the generation time calculated using the Euler-Lotka equation, age-structured population matrices, and several stage-structured population matrices that were obtained by applying different conversion methods. The results show that the discretization of age introduces only small bias in ? or generation time. Similarly, assuming a fixed age of maturation at the mean age of maturation does not introduce much bias. However, aggregating age-specific survival rates into a stage-specific survival rate and estimating a stage-transition rate can introduce substantial bias depending on the organism's life history type and the true values of ?. In order to aggregate survival rates, the use of the weighted arithmetic mean was the most robust method for estimating ?. Here, the weights are given by survivorship curve after discounting with ?. To estimate a stage-transition rate, matching the proportion of individuals transitioning, with ? used for discounting the rate, was the best approach. However, stage-structured models performed poorly in estimating generation time, regardless of the methods used for constructing the models. Based on the results, we recommend using an age-structured matrix population model or the Euler-Lotka equation for calculating ? and generation time when life table data are available. Then, these age-structured vital rates can be converted into a stage-structured model for further analyses.

Dataset Information

A Comparison of Major Petroleum Life Cycle Models.

Publications

A Comparison of Major Petroleum Life Cycle Models.

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