Emission factors from road dust resuspension in a Mediterranean freeway

Particulate matter emissions from paved roads are currently one of the main challenges for a sustainable transport in Europe. Emissions are scarcely estimated due to the lack of knowledge about the resuspension process severely hampering a reliable simulation of PM and heavy metals concentrations in large cities and evaluation of population exposure. In this study the Emission Factors from road dust resuspension on a Mediterranean freeway were estimated per single vehicle category and PM component (OC, EC, mineral dust and metals) by means of the deployment of vertical profiles of passive samplers and terminal concentration estimate. The estimated PM10 emission factors varied from 12 to 47 mg VKT?1 (VKT: Vehicle Kilometer Traveled) with an average value of 22.7 ? 14.2 mg VKT?1. Emission Factors for heavy and light duty vehicles, passenger cars and motorbikes were estimated, based on average fleet composition and EPA ratios, in 187e733 mg VKT?1, 33e131 VKT?1, 9.4e36.9 VKT?1 and 0.8e3.3 VKT?1, respectively. These range of values are lower than previous estimates in Mediterranean urban roads, probably due to the lower dust reservoir on freeways. PM emitted material was dominated by mineral dust (9e10 mg VKT?1), but also OC and EC were found to be major components and approximately 14 e25% and 2e9% of average PM exhaust emissions from diesel passenger cars on highways respectively.

Independent doubly Adaptive Rejection Metropolis Sampling

Adaptive Rejection Metropolis Sampling (ARMS) is a wellknown MCMC scheme for generating samples from onedimensional target distributions. ARMS is widely used within Gibbs sampling, where automatic and fast samplers are often needed to draw from univariate full-conditional densities. In this work, we propose an alternative adaptive algorithm (IA2RMS) that overcomes the main drawback of ARMS (an uncomplete adaptation of the proposal in some cases), speeding up the convergence of the chain to the target. Numerical results show that IA2RMS outperforms the standard ARMS, providing a correlation among samples close to zero.

Comparison of micrometeorological techinques for estimating ammonia emission from covered slurry storage and land spreading of cattle slurry

The micrometeorological mass-balance integrated horizontal flux (IHF) technique has been commonly employed for measuring ammonia (NH3) emissions inon-field experiments. However, the inverse-dispersion modeling technique, such as the backward Lagrangian stochastic (bLS) modeling approach, is currently highlighted as offering flexibility in plot design and requiring a minimum number of samplers (Ro et al., 2013). The objective of this study was to make a comparison between the bLS technique with the IHF technique for estimating NH3 emission from flexible bag storage and following landspreading of dairy cattle slurry. Moreover, considering that NH3 emission in storage could have been non uniform, the effect on bLS estimates of a single point and multiple downwind concentration measurements was tested, as proposed by Sanz et al. (2010).