Sensitivity of fluvial sediment source apportionment to mixing model assumptions: A Bayesian model comparison

Mixing models have become increasingly common tools for apportioning fluvial sediment load to various sediment sources across catchments using a wide variety of Bayesian and frequentist modeling approaches. In this study, we demonstrate how different model setups can impact upon resulting source apportionment estimates in a Bayesian framework via a one-factor-at-a-time (OFAT) sensitivity analysis. We formulate 13 versions of a mixing model, each with different error assumptions and model structural choices, and apply them to sediment geochemistry data from the River Blackwater, Norfolk, UK, to apportion suspended particulate matter (SPM) contributions from three sources (arable topsoils, road verges, and subsurface material) under base flow conditions between August 2012 and August 2013. Whilst all 13 models estimate subsurface sources to be the largest contributor of SPM (median ∼76%), comparison of apportionment estimates reveal varying degrees of sensitivity to changing priors, inclusion of covariance terms, incorporation of time-variant distributions, and methods of proportion characterization. We also demonstrate differences in apportionment results between a full and an empirical Bayesian setup, and between a Bayesian and a frequentist optimization approach. This OFAT sensitivity analysis reveals that mixing model structural choices and error assumptions can significantly impact upon sediment source apportionment results, with estimated median contributions in this study varying by up to 21% between model versions. Users of mixing models are therefore strongly advised to carefully consider and justify their choice of model structure prior to conducting sediment source apportionment investigations

High-temporal resolution fluvial sediment source fingerprinting with uncertainty: a Bayesian approach

This contribution addresses two developing areas of sediment fingerprinting research. Specifically, how to improve the temporal resolution of source apportionment estimates whilst minimizing analytical costs and, secondly, how to consistently quantify all perceived uncertainties associated with the sediment mixing model procedure. This first matter is tackled by using direct X-ray fluorescence spectroscopy (XRFS) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analyses of suspended particulate matter (SPM) covered filter papers in conjunction with automatic water samplers. This method enables SPM geochemistry to be quickly, accurately, inexpensively and non-destructively monitored at high-temporal resolution throughout the progression of numerous precipitation events. We then employed a Bayesian mixing model procedure to provide full characterization of spatial geochemical variability, instrument precision and residual error to yield a realistic and coherent assessment of the uncertainties associated with source apportionment estimates. Applying these methods to SPM data from the River Wensum catchment, UK, we have been able to apportion, with uncertainty, sediment contributions from eroding arable topsoils, damaged road verges and combined subsurface channel bank and agricultural field drain sources at 60- and 120-minute resolution for the duration of five precipitation events. The results presented here demonstrate how combining Bayesian mixing models with the direct spectroscopic analysis of SPM-covered filter papers can produce high-temporal resolution source apportionment estimates that can assist with the appropriate targeting of sediment pollution mitigation measures at a catchment level

Asymmetric Tax Competition with Formula Apportionment

This paper analyzes asymmetric tax competition under formula apportionment. It sets up a model with multinationals where two welfare-maximizing jurisdictions of different size levy source-based corporate taxes and allocate taxes using the formula approach. At the Nash equilibrium, tax rates are too low and public goods quantities are too small. The paper shows that the larger country levies a larger tax rate compared to the smaller country as it does under separate accounting. Citizens of the larger country are worse off than those of the smaller country.Multinational enterprises, corporate taxation, formula apportionment, asymmetric tax competition.

The Impact of Losses on Income Tax Revenue and Implicit Tax Rates of Different Income Sources: Evidence from Microsimulation Using Tax Statistics for Germany

In order to calculate the burden of a comprehensive and progressive income tax falling on a certain income source, an apportionment scheme for the entire tax burden has to be chosen. This raises the question of how to deal with losses, which is relevant for Germany in view of the heavy losses from renting. Using micro data from tax statistics we analyze the income tax shares of functional income sources for three apportionment schemes. The choice of the apportionment scheme markedly affects the tax shares of income sources and the implicit tax rates, in particular those of capital income.Income and business income taxation, implicit tax rates by income sources

Profiling SO2 air pollution patterns in 9 EU Aphekom cities: The Aphekom Project

A detailed analysis of hourly pollutant concentrations mainly focusing on SO2 data obtained from 9 centres involved in the Aphekom project was conducted. This involved the generation of individual diurnal SO2 profiles in order to: (i) identify city specific patterns including source apportionment and quantification, (ii) track changes over time, (iii) analyse the changes in SO2 concentrations from different emission sources, i.e. traffic, heating, shipping and industrial sources, overtime