Transport energy demand: techno-economic modelling and scenarios for Irish climate policy

The case for energy policy modelling is strong in Ireland, where stringent EU climate targets are projected to be overshot by 2015. Policy targets aiming to deliver greenhouse gas and renewable energy targets have been made, but it is unclear what savings are to be achieved and from which sectors. Concurrently, the growth of personal mobility has caused an astonishing increase in CO2 emissions from private cars in Ireland, a 37% rise between 2000 and 2008, and while there have been improvements in the efficiency of car technology, there was no decrease in the energy intensity of the car fleet in the same period. This thesis increases the capacity for evidenced-based policymaking in Ireland by developing techno-economic transport energy models and using them to analyse historical trends and to project possible future scenarios. A central focus of this thesis is to understand the effect of the car fleet‘s evolving technical characteristics on energy demand. A car stock model is developed to analyse this question from three angles: Firstly, analysis of car registration and activity data between 2000 and 2008 examines the trends which brought about the surge in energy demand. Secondly, the car stock is modelled into the future and is used to populate a baseline “no new policy” scenario, looking at the impact of recent (2008-2011) policy and purchasing developments on projected energy demand and emissions. Thirdly, a range of technology efficiency, fuel switching and behavioural scenarios are developed up to 2025 in order to indicate the emissions abatement and renewable energy penetration potential from alternative policy packages. In particular, an ambitious car fleet electrification target for Ireland is examined. The car stock model‘s functionality is extended by linking it with other models: LEAP-Ireland, a bottom-up energy demand model for all energy sectors in the country; Irish TIMES, a linear optimisation energy system model; and COPERT, a pollution model. The methodology is also adapted to analyse trends in freight energy demand in a similar way. Finally, this thesis addresses the gap in the representation of travel behaviour in linear energy systems models. A novel methodology is developed and case studies for Ireland and California are presented using the TIMES model. Transport Energy

The toxicology of climate change: environmental contaminants in a warming world.

Climate change induced by anthropogenic warming of the earth's atmosphere is a daunting problem. This review examines one of the consequences of climate change that has only recently attracted attention: namely, the effects of climate change on the environmental distribution and toxicity of chemical pollutants. A review was undertaken of the scientific literature (original research articles, reviews, government and intergovernmental reports) focusing on the interactions of toxicants with the environmental parameters, temperature, precipitation, and salinity, as altered by climate change. Three broad classes of chemical toxicants of global significance were the focus: air pollutants, persistent organic pollutants (POPs), including some organochlorine pesticides, and other classes of pesticides. Generally, increases in temperature will enhance the toxicity of contaminants and increase concentrations of tropospheric ozone regionally, but will also likely increase rates of chemical degradation. While further research is needed, climate change coupled with air pollutant exposures may have potentially serious adverse consequences for human health in urban and polluted regions. Climate change producing alterations in: food webs, lipid dynamics, ice and snow melt, and organic carbon cycling could result in increased POP levels in water, soil, and biota. There is also compelling evidence that increasing temperatures could be deleterious to pollutant-exposed wildlife. For example, elevated water temperatures may alter the biotransformation of contaminants to more bioactive metabolites and impair homeostasis. The complex interactions between climate change and pollutants may be particularly problematic for species living at the edge of their physiological tolerance range where acclimation capacity may be limited. In addition to temperature increases, regional precipitation patterns are projected to be altered with climate change. Regions subject to decreases in precipitation may experience enhanced volatilization of POPs and pesticides to the atmosphere. Reduced precipitation will also increase air pollution in urbanized regions resulting in negative health effects, which may be exacerbated by temperature increases. Regions subject to increased precipitation will have lower levels of air pollution, but will likely experience enhanced surface deposition of airborne POPs and increased run-off of pesticides. Moreover, increases in the intensity and frequency of storm events linked to climate change could lead to more severe episodes of chemical contamination of water bodies and surrounding watersheds. Changes in salinity may affect aquatic organisms as an independent stressor as well as by altering the bioavailability and in some instances increasing the toxicity of chemicals. A paramount issue will be to identify species and populations especially vulnerable to climate-pollutant interactions, in the context of the many other physical, chemical, and biological stressors that will be altered with climate change. Moreover, it will be important to predict tipping points that might trigger or accelerate synergistic interactions between climate change and contaminant exposures.

Implications of shale gas development for climate change.

Advances in technologies for extracting oil and gas from shale formations have dramatically increased U.S. production of natural gas. As production expands domestically and abroad, natural gas prices will be lower than without shale gas. Lower prices have two main effects: increasing overall energy consumption, and encouraging substitution away from sources such as coal, nuclear, renewables, and electricity. We examine the evidence and analyze modeling projections to understand how these two dynamics affect greenhouse gas emissions. Most evidence indicates that natural gas as a substitute for coal in electricity production, gasoline in transport, and electricity in buildings decreases greenhouse gases, although as an electricity substitute this depends on the electricity mix displaced. Modeling suggests that absent substantial policy changes, increased natural gas production slightly increases overall energy use, more substantially encourages fuel-switching, and that the combined effect slightly alters economy wide GHG emissions; whether the net effect is a slight decrease or increase depends on modeling assumptions including upstream methane emissions. Our main conclusions are that natural gas can help reduce GHG emissions, but in the absence of targeted climate policy measures, it will not substantially change the course of global GHG concentrations. Abundant natural gas can, however, help reduce the costs of achieving GHG reduction goals.

GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy.

PURPOSE: The role of PM10 in the development of allergic diseases remains controversial among epidemiological studies, partly due to the inability to control for spatial variations in large-scale risk factors. This study aims to investigate spatial correspondence between the level of PM10 and allergic diseases at the sub-district level in Seoul, Korea, in order to evaluate whether the impact of PM10 is observable and spatially varies across the subdistricts. METHODS: PM10 measurements at 25 monitoring stations in the city were interpolated to 424 sub-districts where annual inpatient and outpatient count data for 3 types of allergic diseases (atopic dermatitis, asthma, and allergic rhinitis) were collected. We estimated multiple ordinary least square regression models to examine the association of the PM10 level with each of the allergic diseases, controlling for various sub-district level covariates. Geographically weighted regression (GWR) models were conducted to evaluate how the impact of PM10 varies across the sub-districts. RESULTS: PM10 was found to be a significant predictor of atopic dermatitis patient count (P<0.01), with greater association when spatially interpolated at the sub-district level. No significant effect of PM10 was observed on allergic rhinitis and asthma when socioeconomic factors were controlled for. GWR models revealed spatial variation of PM10 effects on atopic dermatitis across the sub-districts in Seoul. The relationship of PM10 levels to atopic dermatitis patient counts is found to be significant only in the Gangbuk region (P<0.01), along with other covariates including average land value, poverty rate, level of education and apartment rate (P<0.01). CONCLUSIONS: Our findings imply that PM10 effects on allergic diseases might not be consistent throughout Seoul. GIS-based spatial modeling techniques could play a role in evaluating spatial variation of air pollution impacts on allergic diseases at the sub-district level, which could provide valuable guidelines for environmental and public health policymakers.

Some models for discretized series of events

A discretized series of events is a binary time series that indicates whether or not events of a point process in the line occur in successive intervals. Such data are common in environmental applications. We describe a class of models for them, based on an unobserved continuous-time discrete-state Markov process, which determines the rate of a doubly stochastic Poisson process, from which the binary time series is constructed by discretization. We discuss likelihood inference for these processes and their second-order properties and extend them to multiple series. An application involves modeling the times of exposures to air pollution at a number of receptors in Western Europe.

Modelling high particulate matter and ozone episodes in the Trans-Manche region

There is concern in the Cross-Channel region of Nord-Pas-de-Calais (France) and Kent (Great Britain), regarding the extent of atmospheric pollution detected in the area from emitted gaseous (VOC, NOx, S02)and particulate substances. In particular, the air quality of the Cross-Channel or "Trans-Manche" region is highly affected by the heavily industrial area of Dunkerque, in addition to transportation sources linked to cross-channel traffic in Kent and Calais, posing threats to the environment and human health. In the framework of the cross-border EU Interreg IIIA activity, the joint Anglo-French project, ATTMA, has been commissioned to study Aerosol Transport in the Trans-Manche Atmosphere. Using ground monitoring data from UK and French networks and with the assistance of satellite images the project aims to determine dispersion patterns. and identify sources responsible for the pollutants. The findings of this study will increase awareness and have a bearing on future air quality policy in the region. Public interest is evident by the presence of local authorities on both sides of the English Channel as collaborators. The research is based on pollution transport simulations using (a) Lagrangian Particle Dispersion (LPD) models, (b) an Eulerian Receptor Based model. This paper is concerned with part (a), the LPD Models. Lagrangian Particle Dispersion (LPD) models are often used to numerically simulate the dispersion of a passive tracer in the planetary boundary layer by calculating the Lagrangian trajectories of thousands of notional particles. In this contribution, the project investigated the use of two widely used particle dispersion models: the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the model FLEXPART. In both models forward tracking and inverse (or·. receptor-based) modes are possible. Certain distinct pollution episodes have been selected from the monitor database EXPER/PF and from UK monitoring stations, and their likely trajectory predicted using prevailing weather data. Global meteorological datasets were downloaded from the ECMWF MARS archive. Part of the difficulty in identifying pollution sources arises from the fact that much of the pollution outside the monitoring area. For example heightened particulate concentrations are to originate from sand storms in the Sahara, or volcanic activity in Iceland or the Caribbean work identifies such long range influences. The output of the simulations shows that there are notable differences between the formulations of and Hysplit, although both models used the same meteorological data and source input, suggesting that the identification of the primary emissions during air pollution episodes may be rather uncertain.

Solving the advection-dispersion equation using the discrete puff particle method

A flexible, mass-conservative numerical technique for solving the advection-dispersion equation for miscible contaminant transport is presented. The method combines features of puff transport models from air pollution studies with features from the random walk particle method used in water resources studies, providing a deterministic time-marching algorithm which is independent of the grid Peclet number and scales from one to higher dimensions simply. The concentration field is discretised into a number of particles, each of which is treated as a point release which advects and disperses over the time interval. The dispersed puff is itself discretised into a spatial distribution of particles whose masses can be pre-calculated. Concentration within the simulation domain is then calculated from the mass distribution as an average over some small volume. Comparison with analytical solutions for a one-dimensional fixed-duration concentration pulse and for two-dimensional transport in an axisymmetric flow field indicate that the algorithm performs well. For a given level of accuracy the new method has lower computation times than the random walk particle method.

Mutual Solubilities of Water and Hydrophobic Ionic Liquids

The ionic nature of ionic liquids (ILs) results in a unique combination of intrinsic properties that produces increasing interest in the research of these fluids as environmentally friendly "neoteric" solvents. One of the main research fields is their exploitation as solvents for liquid-liquid extractions, but although ILs cannot vaporize leading to air pollution, they present non-negligible miscibility with water that may be the cause of some environmental aquatic risks. It is thus important to know the mutual solubilities between ILs and water before their industrial applications. In this work, the mutual solubilities of hydrophobic yet hygroscopic imidazolium-, pyridinium-, pyrrolidinium-, and piperidinium-based ILs in combination with the anions bis(trifluoromethylsulfonyl)imide, hexafluorophosphate, and tricyanomethane with water were measured between 288.15 and 318.15 K. The effect of the ILs structural combinations, as well as the influence of several factors, namely cation side alkyl chain length, the number of cation substitutions, the cation family, and the anion identity in these mutual solubilities are analyzed and discussed. The hydrophobicity of the anions increases in the order [C(CN)3] <[PF6] <[Tf2N] while the hydrophobicity of the cations increases from [Cnmim] <[Cnmpy] [Cnmpyr] <[Cnmpip] and with the alkyl chain length increase. From experimental measurements of the temperature dependence of ionic liquid solubilities in water, the thermodynamic molar functions of solution, such as Gibbs energy, enthalpy, and entropy at infinite dilution were determined, showing that the solubility of these ILs in water is entropically driven and that the anion solvation at the IL-rich phase controls their solubilities in water. The COSMO-RS, a predictive method based on unimolecular quantum chemistry calculations, was also evaluated for the description of the water-IL binary systems studied, where it showed to be capable of providing an acceptable qualitative agreement with the experimental data.

Mutual Solubilities of Water and the [Cnmim][Tf2N] Hydrophobic Ionic Liquids

Ionic liquids (ILs) have recently garnered increased attention because of their potential environmental benefits as "green" replacements over conventional volatile organic solvents. While ILs cannot significantly volatilize and contribute to air pollution, even the most hydrophobic ones present some miscibility with water posing environmental risks to the aquatic ecosystems. Thus, the knowledge of ILs toxicity and their water solubility must be assessed before an accurate judgment of their environmental benefits and prior to their industrial applications. In this work, the mutual solubilities for [C2-C8mim][Tf2N] (n-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide) and water between 288.15 and 318.15 K at atmospheric pressure were measured. Although these are among the most hydrophobic ionic liquids known, the solubility of water in these compounds is surprisingly large, ranging from 0.17 to 0.36 in mole fraction, while the solubility of these ILs in water is much lower ranging from 3.2 × 10-5 to 1.1 × 10-3 in mole fraction, in the temperature and pressure conditions studied. From the experimental data, the molar thermodynamic functions of solution and solvation such as Gibbs energy, enthalpy, and entropy at infinite dilution were estimated, showing that the solubility of these ILs in water is entropically driven. The predictive capability of COSMO-RS, a model based on unimolecular quantum chemistry calculations, was evaluated for the description of the binary systems investigated providing an acceptable agreement between the model predictions and the experimental data both with the temperature dependence and with the ILs structural variations.

Phase transition and decomposition temperatures, heat capacities and viscosities of pyridinium ionic liquids

Ionic liquids are organic salts with low melting points. Many of these compounds are liquid at room temperature in their pure state. Since they have negligible vapor pressure and would not contribute to air pollution, they are being intensively investigated for a variety of applications, including as solvents for reactions and separations, as non-volatile electrolytes, and as heat transfer fluids. We present melting temperatures, glass transition temperatures, decomposition temperatures, heat capacities, and viscosities for a large series of pyridinium-based ionic liquids. For comparison, we include data for several imidazolium and quaternary ammonium salts. Many of the compounds do not crystallize, but form glasses at temperatures between 188 K and 223 K. The thermal stability is largely determined by the coordinating ability of the anion, with ionic liquids made with the least coordinating anions, like bis(trifluoromethylsulfonyl)imide, having the best thermal stability. In particular, dimethylaminopyridinium bis(trifluoromethylsulfonyl)imide salts have some of the best thermal stabilities of any ionic liquid compounds investigated to date. Heat capacities increase approximately linearly with increasing molar mass, which corresponds with increasing numbers of translational, vibrational, and rotational modes. Viscosities generally increase with increasing number and length of alkyl substituents on the cation, with the pyridinium salts typically being slightly more viscous than the equivalent imidazolium compounds. (c) 2005 Elsevier Ltd. All rights reserved.

Microfaunal communities associated with epiphytic lichens in Belfast

The composition and richness of the microfauna on lime trees was surveyed in relation to the distribution and cover of lichens in Belfast. Parameters used to help interpret the results included distance from the city centre and available data on air quality. The percentage epiphyte cover on the trunks of lime trees was significantly correlated with distance from the city centre whereas that on tree bases as not. In contrast, the number of microfaunal species revealed strong positive correlations with distance for both the bases and the trunks of trees. Most of this increase in microfaunal species richness towards rural areas was due to protistans which are thus proposed as useful bioindicators of air pollution. The total species richness of fauna showed slight negative correlation with smoke but not SO2 levels.

Natural gas as a sustainable transport fuel

Environmental concerns relating to gaseous emissions from transport have led to growth in the use of compressed natural gas vehicles worldwide with an estimated 13 million Natural Gas Vehicles (NGVs) currently in operation. Across Europe, many countries are replacing traditional diesel oil in captive fleets such as buses used for public transport and heavy and light goods vehicles used for freight and logistics with CNG vehicles. Initially this was to reduce localised air pollution in urban environments. However, with the need to reduce greenhouse gas emissions CNG is seen as a cleaner more energy efficient and environmental friendly alternative. This paper briefly examines the growth of NGVs in Europe and worldwide. Then a case study on CNG the introduction in Spain and Italy is presented. As part of the case study, policy interventions are examined. Finally, a statistical analysis of private and public refuelling stations in both countries is also provided. CNG can also be mixed with biogas. This study and the role of CNG is relevant because of the existing European Union Directive 2009/28/EC target, requiring that 10% of transport energy come from renewable sources, not alone biofuels such as biogas. CNG offers another alternative transport fuel.

Environmental pricing of externalities from different sources of electricity generation in Chile

The rapid increase in electricity demand in Chile means a choice must be made between major investments in renewable or non-renewable sources for additional production. Current projects to develop large dams for hydropower in Chilean Patagonia impose an environmental price by damaging the natural environment. On the other hand, the increased use of fossil fuels entails an environmental price in terms of air pollution and greenhouse gas emissions contributing to climate change. This paper studies the debate on future electricity supply in Chile by investigating the preferences of households for a variety of different sources of electricity generation such as fossil fuels, large hydropower in Chilean Patagonia and other renewable energy sources. Using Double Bounded Dichotomous Choice Contingent Valuation, a novel advanced disclosure method and internal consistency test are used to elicit the willingness to pay for less environmentally damaging sources. Policy results suggest a strong preference for renewable energy sources with higher environmental prices imposed by consumers on electricity generated from fossil fuels than from large dams in Chilean Patagonia. Policy results further suggest the possibility of introducing incentives for renewable energy developments that would be supported by consumers through green tariffs or environmental premiums. Methodological findings suggest that advanced disclosure learning overcomes the problem of internal inconsistency in SB-DB estimates.