Characterizing Uncertainty in Air Pollution Damage Estimates

This study uses Monte Carlo methods to characterize the uncertainty associated with per-ton damage estimates for 100 power plants in the contiguous United States (U.S.) This analysis focuses on damage estimates produced by an Integrated Assessment Model (IAM) for emissions of two local air pollutants: sulfur dioxide (SO2) and .ne particulate matter (PM2:5). For each power plant, the Monte Carlo procedure yields an empirical distribution for the damage per ton of SO2 and PM2:5:For a power plant in New York, one ton of SO2 produces $5,160 in damages with a 90$1,000 and $14,090. A ton of PM2:5 emitted from the same facility causes$17,790 worth of damages with a 90% percentile interval of $3,780 and$47,930. Results for the sample of 100 fossil-fuel .red power plants shows a strong spatial pattern in the marginal damage distributions. The degree of variability increases by plant location from east to west. This result highlights the importance of capturing uncertainty in air quality modeling in the empirical marginal damage distributions. Further, by isolating uncertainty at each module in the IAM we .nd that uncertainty associated with the dose-response parameter, which captures the in.uence of exposure to PM2:5 on adult mortality rates, the mortality valuation parameter, and the air quality model exert the greatest in.uence on cumulative uncertainty. The paper also demonstrates how the marginal damage distributions may be used to guide regulators in the design of more efficient market-based air pollution policy in the U.S.Monte Carlo, Air Pollution, Market-based Pollution Policy

Sinusoidal Modeling Applied to Spatially Variant Tropospheric Ozone Air Pollution

This paper demonstrates how parsimonious models of sinusoidal functions can be used to fit spatially variant time series in which there is considerable variation of a periodic type. A typical shortcoming of such tools relates to the difficulty in capturing idiosyncratic variation in periodic models. The strategy developed here addresses this deficiency. While previous work has sought to overcome the shortcoming by augmenting sinusoids with other techniques, the present approach employs station-specific sinusoids to supplement a common regional component, which succeeds in capturing local idiosyncratic behavior in a parsimonious manner. The experiments conducted herein reveal that a semi-parametric approach enables such models to fit spatially varying time series with periodic behavior in a remarkably tight fashion. The methods are applied to a panel data set consisting of hourly air pollution measurements. The augmented sinusoidal models produce an excellent fit to these data at three different levels of spatial detail.Air Pollution, Idiosyncratic component, Regional variation, Semiparametric model, Sinusoidal function, Spatial-temporal data, Tropospheric Ozone

The Ancillary Benefits from Climate Policy in the United States

This study investigates the benefits to human health that would occur in the United States (U.S.) due to reductions in local air pollutant emissions stemming from a federal policy to reduce greenhouse gas emissions (GHG). In order to measure the impacts of reduced emissions of local pollutants, this study considers a representative U.S. climate policy. Specifically, the climate policy modeled in this analysis is the Warner-Lieberman bill (S.2191) of 2008 and the paper considers the impacts of reduced emissions in the transport and electric power sectors. This analysis provides strong evidence that climate change policy in the U.S. will generate significant returns to society in excess of the benefits due to climate stabilization. The total health-related co-benefits associated with a representative climate policy over the years 2006 to 2030 range between $90 and$725 billion in present value terms depending on modeling assumptions. The majority of avoided damages are due to reduced emissions of SO2 from coal-fired power plants. Among the most important assumptions is whether remaining coal-fired generation capacity is permitted to “backslide” up to the Clean Air Interstate Rule (CAIR) cap on emissions. This analysis models two scenarios specifically related to this issue. Co-benefits increase from $90 billion, when the CAIR cap is met, to$256 billion if SO2 emissions are not permitted to exceed current emission rates. On a per ton basis, the co-benefit per ton of GHG emissions is projected to average between $2 and$14 ($2006). The per ton marginal abatement cost for the representative climate policy is estimated at$9 ($2006).

Assessment of the potential of MERIS near-infrared water vapour products to correct ASAR interferometric measurements

Atmospheric water vapour is a major limitation for high precision Interferometric Synthetic Aperture Radar (InSAR) applications due to its significant impact on microwave signals. We propose a statistical criterion to test whether an independent water vapour product can reduce water vapour effects on InSAR interferograms, and assess the potential of the Medium Resolution Imaging Spectrometer (MERIS) near-infrared water vapour products for correcting Advanced SAR (ASAR) data. Spatio-temporal comparisons show c. 1.1mm agreement between MERIS and GPS/radiosonde water vapour products in terms of standard deviations. One major limitation with the use of MERIS water vapour products is the frequency of cloud free conditions. Our analysis indicates that in spite of the low global cloud free conditions (~25%), the frequency can be much higher for certain areas such as Eastern Tibet (~38%) and Southern California (~48%). This suggests that MERIS water vapour products show potential for correcting ASAR interferometric measurements in certain regions

Multisensory perception and action: development, decision-making, and neural mechanisms

Surrounded by multiple objects and events, receiving multisensory stimulation, our brain must sort through relevant and irrelevant multimodal signals to correctly decode and represent the information from the same and different objects and, respectively, events in the physical world. Over the last two decades, scientific interest has increased dramatically in how we integrate multisensory information and how we interact with a multisensory world, as evidenced by exponential growth of the relevant studies using behavioral and/or neuro-scientific approaches. The Special Issue topic of “Multisensory perception and action: psychophysics, neural mechanisms, and applications” emerged from a scientific meeting dedicated to these issues: the Munich Multisensory Perception Symposium held in Holzhausen am Ammersee, Germany (June 24–26, 2011). This volume, which collects research articles contributed by attendees of the symposium as well as the wider community, is organized into three interrelated sections: (I) Development, learning, and decision making in multisensory perception (II) Multisensory timing and sensorimotor temporal integration (III) Electrophysiological and neuro-imaging analyses of multisensory perceptio

Sinusoidal Modeling Applied to Spatially Variant Tropospheric Ozone Air Pollution

This paper demonstrates how parsimonious models of sinusoidal functions can be used to fit spatially variant time series in which there is considerable variation of a periodic type. A typical shortcoming of such tools relates to the difficulty in capturing idiosyncratic variation in periodic models. The strategy developed here addresses this deficiency. While previous work has sought to overcome the shortcoming by augmenting sinusoids with other techniques, the present approach employs station-specific sinusoids to supplement a common regional component, which succeeds in capturing local idiosyncratic behavior in a parsimonious manner. The experiments conducted herein reveal that a semi-parametric approach enables such models to fit spatially varying time series with periodic behavior in a remarkably tight fashion. The methods are applied to a panel data set consisting of hourly air pollution measurements. The augmented sinusoidal models produce an excellent fit to these data at three different levels of spatial detail

Temporal perception of visual-haptic events in multimodal telepresence system

Book synopsis: Haptic interfaces are divided into two main categories: force feedback and tactile. Force feedback interfaces are used to explore and modify remote/virtual objects in three physical dimensions in applications including computer-aided design, computer-assisted surgery, and computer-aided assembly. Tactile interfaces deal with surface properties such as roughness, smoothness, and temperature. Haptic research is intrinsically multi-disciplinary, incorporating computer science/engineering, control, robotics, psychophysics, and human motor control. By extending the scope of research in haptics, advances can be achieved in existing applications such as computer-aided design (CAD), tele-surgery, rehabilitation, scientific visualization, robot-assisted surgery, authentication, and graphical user interfaces (GUI), to name a few. Advances in Haptics presents a number of recent contributions to the field of haptics. Authors from around the world present the results of their research on various issues in the field of haptics

Magnetic behaviour of PrPd2B2C

We have synthesized a new quaternary borocarbide PrPd$_{2}$B$_{2}$C and measured its magnetization, electrical resistivity and specific heat. The compound crystallizes in the LuNi$_{2}$B$_{2}$C-type tetragonal structure (space group {\it I4/mmm}). Above 100 K the magnetic susceptibility follows Curie-Weiss behavior with effective moment $\mu_{eff}$ = 3.60 $\mu_{B}$, which is very close to the value expected for Pr$^{3+}$ ions. We do not find evidence for magnetic or superconducting transition down to 0.5 K. Specific heat exhibits a broad Schottky type anomaly with a peak at 24 K, very likely related to crystal electric field (CEF) excitation. The magnetic properties suggest the presence of a singlet CEF ground state leading to a Van-Vleck paramagnetic ground state.Comment: 2 pages, 2 figure

A volume-based hydrodynamic approach to sound wave propagation in a monatomic gas

We investigate sound wave propagation in a monatomic gas using a volume-based hydrodynamic model. In Physica A vol 387(24) (2008) pp6079-6094, a microscopic volume-based kinetic approach was proposed by analyzing molecular spatial distributions; this led to a set of hydrodynamic equations incorporating a mass-density diffusion component. Here we find that these new mass-density diffusive flux and volume terms mean that our hydrodynamic model, uniquely, reproduces sound wave phase speed and damping measurements with excellent agreement over the full range of Knudsen number. In the high Knudsen number (high frequency) regime, our volume-based model predictions agree with the plane standing waves observed in the experiments, which existing kinetic and continuum models have great difficulty in capturing. In that regime, our results indicate that the "sound waves" presumed in the experiments may be better thought of as "mass-density waves", rather than the pressure waves of the continuum regime.Comment: Revised to aid clarification (no changes to presented model); typos corrected, figures added, paper title change