A high resolution spatiotemporal model for in-vehicle black carbon exposure : quantifying the in-vehicle exposure reduction due to the Euro 5 particulate matter standard legislation

Several studies have shown that a significant amount of daily air pollution exposure is inhaled during trips. In this study, car drivers assessed their own black carbon exposure under real-life conditions (223 h of data from 2013). The spatiotemporal exposure of the car drivers is modeled using a data science approach, referred to as microscopic land-use regression (mu LUR). In-vehicle exposure is highly dynamical and is strongly related to the local traffic dynamics. An extensive set of potential covariates was used to model the in-vehicle black carbon exposure in a temporal resolution of 10 s. Traffic was retrieved directly from traffic databases and indirectly by attributing the trips through a noise map as an alternative traffic source. Modeling by generalized additive models (GAM) shows non-linear effects for meteorology and diurnal traffic patterns. A fitted diurnal pattern explains indirectly the complex diurnal variability of the exposure due to the non-linear interaction between traffic density and distance to the preceding vehicles. Comparing the strength of direct traffic attribution and indirect noise map-based traffic attribution reveals the potential of noise maps as a proxy for traffic-related air pollution exposure. An external validation, based on a dataset gathered in 2010-2011, quantifies the exposure reduction inside the vehicles at 33% (mean) and 50% (median). The EU PM Euro 5 PM emission standard (in force since 2009) explains the largest part of the discrepancy between the measurement campaign in 2013 and the validation dataset. The mu LUR methodology provides a high resolution, route-sensitive, seasonal and meteorology-sensitive personal exposure estimate for epidemiologists and policy makers

Airborne sound propagation over sea during offshore wind farm piling

Offshore piling for wind farm construction has attracted a lot of attention in recent years due to the extremely high noise emission levels associated with such operations. While underwater noise levels were shown to be harmful for the marine biology, the propagation of airborne piling noise over sea has not been studied in detail before. In this study, detailed numerical calculations have been performed with the Green's Function Parabolic Equation (GFPE) method to estimate noise levels up to a distance of 10 km. Measured noise emission levels during piling of pinpiles for a jacket-foundation wind turbine were assessed and used together with combinations of the sea surface state and idealized vertical sound speed profiles (downwind sound propagation). Effective impedances were found and used to represent non-flat sea surfaces at low-wind sea states 2, 3, and 4. Calculations show that scattering by a rough sea surface, which decreases sound pressure levels, exceeds refractive effects, which increase sound pressure levels under downwind conditions. This suggests that the presence of wind, even when blowing downwind to potential receivers, is beneficial to increase the attenuation of piling sound over the sea. A fully flat sea surface therefore represents a worst-case scenario

Evolution of building façade road traffic noise levels in Flanders

The evolution of daytime facade noise levels by road traffic at 250 dwellings in Flanders is assessed. Three identical man-operated measurement campaigns have been conducted in the years 1996, 2001 and 2009, during fall. A practical methodology has been developed, based on short time noise measurements and context observations at these locations. The uncertainty introduced by short-term sampling has been quantified as a function of the noise level. Furthermore, a correction is proposed for measuring at a random moment during daytime. Analysis of the data showed that road traffic noise levels hardly changed globally over this period of 13 years. The distribution of changes in noise level at corresponding measurement locations is nevertheless rather wide-all improvements are equally compensated by increases in noise levels at other locations. The percentage of the dwelling facades exposed to daytime noise levels above 65 dBA has increased slightly between 1996 and 2001, but seems to stagnate in 2009. In spite of the increased interest and actions of policy makers during the past decades, noise exposure caused by road traffic at dwelling facades is a persistent problem

The assessment of traffic livability, including local effects at home, during trips and at the destination, based on the individual activity pattern and trip behaviour

The environmental quality of the living environment is mainly linked to the direct and indirect impact of traffic in the neighborhood of the dwellings. In the Flemish mobility and urban planning, the term ‘livability’ is used focusing on the living conditions of people’s home location: what is the satisfaction about their living environment? The more specific term ‘traffic livability’ is used to describe the impact of all types of traffic on the livability of a dwelling location. Some methodologies were developed for an objective measurement of the traffic impact on quality of life. In Flanders the most commonly used methodologies are the ‘traffic livability index’ and the ‘bearing capacity’, which use a very narrow interpretation of the traffic livability, as they are highly based on the local road design (number of lanes, cycle path, …) and the local traffic characteristics (traffic flow, speed, traffic safety, …) of the street of the dwelling. The main critic is that these methods should measure over the complete living environment of a person, rather than just at the dwelling. For this reason, an alternative methodology was developed for an objective measurement of the impact of traffic on the local quality of the living environment. Compared to the current practice, this new methodology aims at the following objectives: • The evaluation is not done for the average person, but includes individual needs and travel patterns, based on personal characteristics, representing the large diversity of the mobility needs. • The methodology should reflect a daily activity pattern, including the traveled routes and destinations. The traffic livability of a specific household in a specific area will reflect the full extent of their needs at home, during the trips and at the destinations. • Traffic livability is measured by means of a broad set of indicators, representing different types of traffic impacts (accessibility, traffic noise, traffic emissions, …). The separate indicators are combined into an evaluation of the traffic livability, including an extensive set of secondary effects. This is mainly realized by a better simulation of the personal trip behavior, using the data from the Flemish Trip Behavior Survey. In order to evaluate the livability at a certain home location (a number of) households are sampled from this database, with the specific characteristics of the household (composition, car availability, children, …), the people in the household (age, employment, …) and their activities and trip pattern. With this information, the different indicators for traffic livability can be evaluated on the home location, as well as during the trip and at the destination