European air quality maps 2005 including uncertainty analysis

The objective of this report is (a) the updating and refinement of European air quality maps based on annual statistics of the 2005 observational data reported by EEA Member countries in 2006, and (b) the further improvement of the interpolation methodologies. The paper presents the results achieved and an uncertainty analysis of the interpolated maps and builds upon earlier reports from Horalék et al. (2005; 2007)

Environmental risk assessment in the mediterranean region using artificial neural networks

Los mapas auto-organizados han demostrado ser una herramienta apropiada para la clasificación y visualización de grupos de datos complejos. Redes neuronales, como los mapas auto-organizados (SOM) o las redes difusas ARTMAP (FAM), se utilizan en este estudio para evaluar el impacto medioambiental acumulativo en diferentes medios (aguas subterráneas, aire y salud humana). Los SOMs también se utilizan para generar mapas de concentraciones de contaminantes en aguas subterráneas simulando las técnicas geostadísticas de interpolación como kriging y cokriging. Para evaluar la confiabilidad de las metodologías desarrolladas en esta tesis, se utilizan procedimientos de referencia como puntos de comparación: la metodología DRASTIC para el estudio de vulnerabilidad en aguas subterráneas y el método de interpolación espacio-temporal conocido como Bayesian Maximum Entropy (BME) para el análisis de calidad del aire. Esta tesis contribuye a demostrar las capacidades de las redes neuronales en el desarrollo de nuevas metodologías y modelos que explícitamente permiten evaluar las dimensiones temporales y espaciales de riesgos acumulativos

A review of urban air pollution monitoring and exposure assessment methods

The impact of urban air pollution on the environments and human health has drawn increasing concerns from researchers, policymakers and citizens. To reduce the negative health impact, it is of great importance to measure the air pollution at high spatial resolution in a timely manner. Traditionally, air pollution is measured using dedicated instruments at fixed monitoring stations, which are placed sparsely in urban areas. With the development of low-cost micro-scale sensing technology in the last decade, portable sensing devices installed on mobile campaigns have been increasingly used for air pollution monitoring, especially for traffic-related pollution monitoring. In the past, some reviews have been done about air pollution exposure models using monitoring data obtained from fixed stations, but no review about mobile sensing for air pollution has been undertaken. This article is a comprehensive review of the recent development in air pollution monitoring, including both the pollution data acquisition and the pollution assessment methods. Unlike the existing reviews on air pollution assessment, this paper not only introduces the models that researchers applied on the data collected from stationary stations, but also presents the efforts of applying these models on the mobile sensing data and discusses the future research of fusing the stationary and mobile sensing data

Mapping climatic risks in the EU agriculture

Replaced with revised version of paper 11/18/08.Agrometeorological models, climatic risk, European Union, Vegetation indices, Environmental Economics and Policy, Risk and Uncertainty,

Measuring Welfare Loss Caused by Air Pollution in Europe: A CGE Analysis

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).To evaluate the socio-economic impacts of air pollution, we develop an integrated approach based on computable general equilibrium (CGE). Applying our approach to Europe shows that even there, where air quality is relatively high compared with other parts of the world, health-related damages caused by air pollution are substantial. We estimate that in 2005, air pollution in Europe caused a consumption loss of around 220 billion Euro (year 2000 prices, around 3 percent of consumption level) and a social welfare loss of around 370 billion Euro, measured as the sum of lost consumption and leisure (around 2 percent of welfare level). In addition, we estimated that a set of 2020-targeting air quality improvement policy scenarios, which are proposed in the 2005 CAFE program, would bring 18 European countries as a whole a welfare gain of 37 to 49 billion Euro (year 2000 prices) in year 2020 alone.This study received support from the MIT Joint Program on the Science and Policy of Global Change, which is funded by a consortium of government, industry and foundation sponsors

Forecasting environmental equity: Air quality responses to road user charging in Leeds, UK

Sustainable development requires that the goals of economic development, environmental protection and social justice are considered collectively when formulating development strategies. In the context of planning sustainable transport systems, trade-offs between the economy and the environment, and between the economy and social justice have received considerable attention. In contrast, much less attention has been paid to environmental equity, the trade-off between environmental and social justice goals, a significant omission given the growing attention to environmental justice by policy makers in the EU and elsewhere. In many countries, considerable effort has been made to develop clean transport systems by using, for example, technical, economic and planning instruments. However, little effort has been made to understand the distributive and environmental justice implications of these measures. This paper investigates the relationship between urban air quality (as NO2) and social deprivation for the city of Leeds, UK. Through application of a series of linked dynamic models of traffic simulation and assignment, vehicle emission, and pollutant dispersion, the environmental equity implications of a series of urban transport strategies, including road user cordon and distance based charging, road network development, and emission control, are assessed. Results indicate a significant degree of environmental inequity exists in Leeds. Analysis of the transport strategies indicates that this inequity will be reduced through natural fleet renewal, and, perhaps contrary to expectations, road user charging is also capable of promoting environmental equity. The environmental equity response is however, sensitive to road pricing scheme design

Accurate estimation of air pollution in outdoor routes for citizens and decision making

There is clear evidence of the effects of air pollution on health. In this paper, we present an innovative application designed to assess Air Quality (AQ) exposure based on the World Health Organization’s AQ Guidelines, analysing pollutants and their concentrations independently. Our aim is to provide this information to citizens based on their health profile (medical history or requirements) before and during outdoor trips of their choice, both walking and cycling, empowering them to proactively make informed personal decisions about their route choices and identifying potentially unhealthy travel environments. For this purpose, we have access to official data from AQ monitoring stations that are updated periodically every 10 min. Then, by using spatial interpolation techniques (with Ordinary Kriging), we estimate each pollutant over a grid superimposed on the city map. Once the pollutants have been mapped on each route, they are analysed in order to consider the different alternatives for deciding and planning changes in speed or trajectory. We evaluated the application in the city of Valencia (Spain) as a use case under different scenarios, and showed the results to assess exposure to pollution on the routes of citizens

Mapping Cumulative Environmental Risks: Examples from The EU NoMiracle Project

We present examples of cumulative chemical risk mapping methods developed within the NoMiracle project. The different examples illustrate the application of the concentration addition (CA) approach to pesticides at different scale, the integration in space of cumulative risks to individual organisms under the CA assumption, and two techniques to (1) integrate risks using data-driven, parametric statistical methods, and (2) cluster together areas with similar occurrence of different risk factors, respectively. The examples are used to discuss some general issues, particularly on the conventional nature of cumulative risk maps, and may provide some suggestions for the practice of cumulative risk mapping