Air Quality and Europeans' Subjective Well-being

[EN]Happiness economics deals with self-reported subjective well-being, or life satisfaction, and its relationship to a wide variety of other variables. On the study of these other factors, this line of research has helped demonstrate that higher levels of environmental quality increase people’s subjective well-being. This paper focuses on analyzing the relationship between subjective well-being and air quality. On the one hand, the life satisfaction approach to environmental valuation is cautiously described, and on the other hand, the method is implemented in an empirical analysis that seeks to assess how an increase in the level of air pollution at a regional level affects individual-level subjective well-being in Europe. We use a dataset that merges the third wave of the European Social Survey (ESS) with a dataset that includes regional air pollution (including CO, PM10, NO2, SO2 and Benzene) and other regional variables. We find a robust negative impact for CO, a positive impact for SO2, and no conclusive evidence of any effect on subjective well-being for the remaining three pollutants.

Water quality management on the enhancement of shrimp (Penaeus monodon Fab.) production in the traditional and improved-traditional ghers of Bangladesh

On-farm research on enhancement of P. monodon production through water quality management was carried out in five ghers of Paikgacha, Khulna. Based on the prevailing condition of the ghers, lime in the form of CaCO(sub 3), urea and TSP were used as the major inputs to minimize the soil-water acidity and to ensure the availability of natural food particles in the water bodies. Exchange of water at required level also practiced for the qualitative improvement of culture water. Ghers of varying sizes showed that water quality management and fertilization have a positive impact on production performance of P. monodon (61.59% increment) that yielded an average production of 385.43 kg/ha/crop against the present traditional rate of 238.50 kg/ha/year.

Air quality and public health impacts of UK airports. Part I: Emissions

The potential adverse human health and climate impacts of emissions from UK airports have become a significant political issue, yet the emissions, air quality impacts and health impacts attributable to UK airports remain largely unstudied. We produce an inventory of UK airport emissions - including aircraft landing and takeoff (LTO) operations and airside support equipment - with uncertainties quantified. The airports studied account for more than 95% of UK air passengers in 2005. We estimate that in 2005, UK airports emitted 10.2 Gg [-23 to +29%] of NOx, 0.73 Gg [-29 to +32%] of SO2, 11.7 Gg [-42 to +77%] of CO, 1.8 Gg [-59 to +155%] of HC, 2.4 Tg [-13 to +12%] of CO2, and 0.31 Gg [-36 to +45%] of PM2.5. This translates to 2.5 Tg [-12 to +12%] CO2-eq using Global Warming Potentials for a 100-year time horizon. Uncertainty estimates were based on analysis of data from aircraft emissions measurement campaigns and analyses of aircraft operations.The First-Order Approximation (FOA3) - currently the standard approach used to estimate particulate matter emissions from aircraft - is compared to measurements and it is shown that there are discrepancies greater than an order of magnitude for 40% of cases for both organic carbon and black carbon emissions indices. Modified methods to approximate organic carbon emissions, arising from incomplete combustion and lubrication oil, and black carbon are proposed. These alterations lead to factor 8 and a 44% increase in the annual emissions estimates of black and organic carbon particulate matter, respectively, leading to a factor 3.4 increase in total PM2.5 emissions compared to the current FOA3 methodology. Our estimates of emissions are used in Part II to quantify the air quality and health impacts of UK airports, to assess mitigation options, and to estimate the impacts of a potential London airport expansion. © 2011 Elsevier Ltd.

Comparison of stochastic methods for control in air traffic management

This paper provides a direct comparison of two stochastic optimisation techniques (Markov Chain Monte Carlo and Sequential Monte Carlo) when applied to the problem of conflict resolution and aircraft trajectory control in air traffic management. The two methods are then also compared to another existing technique of Mixed-Integer Linear Programming which is also popular in distributed control. © 2011 IFAC.