State-dependent Kalman filters for robust engine control

Vehicle emissions variations impose significant challenges to the automotive industry. In these simulation studies, nonlinear estimation techniques based on state-dependent and extended Kalman filtering are developed for spark ignition engines to enhance robustness of the feedforward fuel controllers to changes in nominal system parameters and measurement errors. A model-based approach is used to derive the optimal filters. Numerical simulations indicate the superiority of estimation-based approaches to enhance robustness of in-cylinder air estimation which directly contributes to the precision of engine exhaust air-fuel ratio and, consequently the consistency of the tailpipe emissions. The results obtained are for an aggressive driving profile and are presented and discusse

Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods

We present a hierarchical Bayesian method for atmospheric trace gas inversions. This method is used to estimate emissions of trace gases as well as "hyper-parameters" that characterize the probability density functions (PDFs) of the a priori emissions and model-measurement covariances. By exploring the space of "uncertainties in uncertainties", we show that the hierarchical method results in a more complete estimation of emissions and their uncertainties than traditional Bayesian inversions, which rely heavily on expert judgment. We present an analysis that shows the effect of including hyper-parameters, which are themselves informed by the data, and show that this method can serve to reduce the effect of errors in assumptions made about the a priori emissions and model-measurement uncertainties. We then apply this method to the estimation of sulfur hexafluoride (SF6) emissions over 2012 for the regions surrounding four Advanced Global Atmospheric Gases Experiment (AGAGE) stations. We find that improper accounting of model representation uncertainties, in particular, can lead to the derivation of emissions and associated uncertainties that are unrealistic and show that those derived using the hierarchical method are likely to be more representative of the true uncertainties in the system. We demonstrate through this SF6 case study that this method is less sensitive to outliers in the data and to subjective assumptions about a priori emissions and model-measurement uncertainties than traditional methods

A Structural nonparametric reappraisal of the CO2 emissions-income relationships.

Relying on a structural nonparametric estimation, we show that CO2 emissions clearly increase with income at low income levels. For higher income levels, we observe a decreasing relationship, though not significant. We also find that CO2 emissions monotonically increases with energy use at a decreasing rate.Nonparametric triangular systems, EKC; Energy use; CO2 emissions.

A structural nonparametric reappraisal of the CO2 emissions-income relationship

Relying on a structural nonparametric estimation, we show that CO2 emissions clearly increase with income at low income levels. For higher income levels, we observe a decreasing relationship, though not significant. We also find that CO2 emissions monotonically increases with energy use at a decreasing rate.Nonparametric triangular systems, EKC, Energy use, CO2 emissions

The Effect of Emissions on U.S. State Total Factor Productivity Growth

This paper investigates the effect of sulphur dioxide (SO2) and nitrogen oxide (NOx) emissions on the Total Factor Productivity (TFP) growth among 48 contiguous U.S. states, for the period 1965-2002. The relationship between TFP growth and emissions is examined using nonparametric econometric techniques that allow for the estimation of the elasticity of pollution for each state and each period and to account for possible nonlinearities in the data. The results indicate that both pollutants positively affect TFP growth. Moreover this effect is nonlinear. The average output elasticity for all states is 0.005 for SO2 and 0.04 for NOx emissions.TFP growth, emissions, semiparametric estimation

Vehicle Choices, Miles Driven, and Pollution Policies

Mobile sources contribute large percentages of each pollutant, but technology is not yet available to measure and tax emissions from each vehicle. We build a behavioral model of household choices about vehicles and miles traveled. The ideal-but-unavailable emissions tax would encourage drivers to abate emissions through many behaviors, some of which involve market transactions that can be observed for feasible market incentives (such as a gas tax, subsidy to new cars, or tax by vehicle type). Our model can calculate behavioral effects of each such price and thus calculate car choices, miles, and emissions. A nested logit structure is used to model discrete choices among different vehicle bundles. We also consider continuous choices of miles driven and the age of each vehicle. We propose a consistent estimation method for both discrete and continuous demands in one step, to capture the interactive effects of simultaneous decisions. Results are compared with those of the traditional sequential estimation procedure.

Environmental impact of biofuel blends - theoretical estimation

It is a well known fact that climate change is one of the most urging problems nowadays. There is evidence that most of the observed global warming is attributable to human activities. Among the many human activities transportation plays a considerable role in contributing to CO2 emissions. In the future transportation is projected to grow further on and since other energy consuming sectors are unable to compensate for transportation related emissions, therefore the transportation sector has to contribute to emissions abatement. Using environment friendly energy resources is the only way to reduce environmental load without restricting mobility. One way to decrease CO2 emissions of the transportation sector is the application of biofuels. The aim of this paper is the theoretical estimation of the environmental impact of ethanol─gasoline and diesel oil─ethanol─biodiesel blends respectively

High-global warming potential F-gas emissions in California: comparison of ambient-based versus inventory-based emission estimates, and implications of refined estimates.

To provide information for greenhouse gas reduction policies, the California Air Resources Board (CARB) inventories annual emissions of high-global-warming potential (GWP) fluorinated gases, the fastest growing sector of greenhouse gas (GHG) emissions globally. Baseline 2008 F-gas emissions estimates for selected chlorofluorocarbons (CFC-12), hydrochlorofluorocarbons (HCFC-22), and hydrofluorocarbons (HFC-134a) made with an inventory-based methodology were compared to emissions estimates made by ambient-based measurements. Significant discrepancies were found, with the inventory-based emissions methodology resulting in a systematic 42% under-estimation of CFC-12 emissions from older refrigeration equipment and older vehicles, and a systematic 114% overestimation of emissions for HFC-134a, a refrigerant substitute for phased-out CFCs. Initial, inventory-based estimates for all F-gas emissions had assumed that equipment is no longer in service once it reaches its average lifetime of use. Revised emission estimates using improved models for equipment age at end-of-life, inventories, and leak rates specific to California resulted in F-gas emissions estimates in closer agreement to ambient-based measurements. The discrepancies between inventory-based estimates and ambient-based measurements were reduced from -42% to -6% for CFC-12, and from +114% to +9% for HFC-134a

Carbon assessment for cocoa cropping systems in Lampung, Indonesia

Cocoa (Theobroma cacao L.) production plays a key role in the economics of Indonesia, the world’s fourth largest cocoa bean producing country. With more than 1.6 million hectares of land planted with cocoa, small improvements in emissions efficiencies or carbon sequestration opportunities can have a relatively large mitigating effect on emissions from agroforestry and land use. The carbon assessment in Lampung, Sumatra was done to evaluate environmental impacts of cocoa as a commodity through estimation of carbon stock and carbon footprint, GHG emissions during the cultivation of cocoa in different cropping systems. Segmentation of cropping systems along density of intercropping, inputs use intensity and residue management practices identify opportunities for climate smart practices tailored to each segment