Dear all,
i'm writing an english paper for an international conference.
The paper has to be formatted according to the organizer supplied latex
style, which is called iemss.sty. I've installed it without any problem
running texhash.
My lyx document is a two column article class, while the abstract is
formatted on a single column, through a package available on Lyx site.
Problems:
*if a insert in my latex preamble the instruction
"\usepackage{iemss.sty}", Lyx doesn't compile the document.
*by trial and error (i'm not a latex master:(( ) I've found that Lyx
compiles if i set the options "fleqn" in Layout->Document->extra .
(I've tried this options since it is included in the provided tex
sample file ).However taking a look at the generated postscript: *title, section styles are correct; *i've got no more abstract (!!) *although I set to 0 the skip between paragraphs, I get a medskip between each other. Can someone help me?? thanks a lot in advance!! I attach my lyx source, the provided style, and the provided tex sample. -Giorgio Corani
iemss.tex
Description: TeX document
%%%% iEMSs 2002 Stylesheet.
%%%%
%%%% Copy the iemss.sty file in the main latex file directory
%%%% The source of the LaTeX file should start with
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#LyX 1.1 created this file. For more info see http://www.lyx.org/ \lyxformat 218 \textclass article \begin_preamble \usepackage{iemss} \end_preamble \options fleqn \language english \inputencoding auto \fontscheme times \graphics default \float_placement !htp \paperfontsize 10 \spacing single \papersize a4paper \paperpackage a4 \use_geometry 1 \use_amsmath 0 \paperorientation portrait \leftmargin 2cm \topmargin 2cm \rightmargin 2cm \bottommargin 2cm \secnumdepth 3 \tocdepth 3 \paragraph_separation skip \defskip medskip \quotes_language english \quotes_times 2 \papercolumns 2 \papersides 1 \paperpagestyle default \layout Standard \latex latex \backslash date{} \layout Title A neural emission-receptor model for ozone reduction planning \layout Author Giorgio Corani \layout OneColAbstract Ground level ozone pollution is a complex phenomenon heavily affecting industria lized and populated areas. Ozone is produced by a series of photochemical reactions, activated by the emissions of nitrogen oxides and volatile organic compounds and may reach maximum concentrations at kilometers of distance form the precursors sources, depending on the meteorological conditions. Models to compute ozone concentrations are equally complex and cannot be directly used to optimize emission reduction policies. For this reason, a neural network has been trained on the results of a photochemical model (CALGRID) to represent the emission-receptor relationships in critical conditions. Such a network in then entered in an optimization problem that determines the least cost alternatives to obtain a given air quality standard. The decision variables of the problem are the emission reductions of ozone precursors in each industrial sector. These reductions are in turn the result of the application of a number of technologies, whose costs and performances are known. The approach has been used to estimate the optimal reduction alternatives for the Lombardia region in Northern Italy and showed that a consistent improvement of air quality can be attained with moderate investments, provided that they are concentrated in some sectors, such as industrial solvents, that have a major impact on ozone dynamics. (211 parole) \layout Section Introduction \layout Standard High ozone concentrations at the tropospehere level are a major concern in air pollution studies because of their impact on human health (Lippman,1993; Bascomb et al., 1996) and agricultural crops and forests (Loibl and Smidt, 1996; Hogsett et al., 1997). Elevated ozone has been observed since the 1970s in the United States and in Europe (Guicherit et al., 1977); since high temperatures result in a much quicker ozone formation, cities with warm climates experience usually the most important ozone problems, as observed for Athens (Giovannoni et al., 1995; Moussiopoulos et al., 1997) and Milan (Prevot et al., 1997, Silibello et al., 1998). In particular Lombardy region, located in Northern Italy, experiences heavy photochemical pollution during the summer season. \layout Standard In order to be effective in the ozone concentration lowering, control policies should be focused on ozone precursors reduction, i.e. \begin_inset Formula \( NO_{x} \) \end_inset and volatile organic compounds \begin_inset Formula \( (VOC) \) \end_inset . As well known, ozone formation is controlled either from \begin_inset Formula \( NO_{x} \) \end_inset or \begin_inset Formula \( VOC \) \end_inset , depending on the ratio between their concentrations: when \begin_inset Formula \( NO_{x}/VOC \) \end_inset is \begin_inset Quotes eld \end_inset low \begin_inset Quotes erd \end_inset , the rate of ozone formation increases with \begin_inset Formula \( NO_{x} \) \end_inset and changes due to increased \emph on VOC \emph default are negligible ( \begin_inset Formula \( NO_{x}-sensitive \) \end_inset regime). Further increases of \begin_inset Formula \( NO_{x} \) \end_inset result in a slower increase rate of ozone; at higher ratio levels, ozone rate decreases increasing \begin_inset Formula \( NO_{x} \) \end_inset and increases increasing \begin_inset Formula \( VOC \) \end_inset ( \emph on VOC-limited \emph default or \begin_inset Formula \( NO_{x}-saturated \) \end_inset regime). Hence, chemical sensitivity analysis plays a key role in developing successfull y ozone reduction policies: as an example, \begin_inset Formula \( NO_{x} \) \end_inset reductions will be effective only in \begin_inset Formula \( NO_{x}-sensitive \) \end_inset regimes. \layout Standard According to the \emph on CORINAIR \emph default classification, emission sources can be grouped in 11 sectors \begin_float footnote \layout Standard \emph on CORINAIR \emph default emission sectors are precisely: \layout Enumerate Combustion in energy and transformation industries \layout Enumerate Non-industrial combustion plants \layout Enumerate Combustion in manufacturing industry \layout Enumerate Production processes without combustion \layout Enumerate Extraction and distribution of fossil fuels / geothermal energy \layout Enumerate Solvent and other product use \layout Enumerate Road transport \layout Enumerate Other mobile sources and machinery (off road transports) \layout Enumerate Waste treatment and disposal \layout Enumerate Agriculture and forestry, land use and wood stock change \layout Enumerate Nature \end_float ; the policy design has hence to take into account that precursors emission reduction will have different costs depending on the considered emission sector. An evaluation of the marginal costs for precursors emission reduction in each sector can be found in (Schopp et al.,1998). \layout Standard >From a modelling point of view, the relationship between ozone and its precursor s is captured through a neural network, thus exploiting the network ability in recognizing highly non linear relationships; in fact artificial neural networks have been showed to be able to well represent air pollution phenomena in many previous works (Prybutok, 2000; Perez, 2000; Soja,1999). Although photochemical three dimensional models such as CALGRID (Yamartino et el., 1992) provide a very detailed simulation of the complex photochemical processes, the requested computational burden makes impossible their use in an optimization task. On the contrary, neural network can be successfully used in such application because also of their computational speed. \layout Section Lombardy case study \layout Standard Region Lombardy, which measures overall about 24000 \begin_inset Formula \( km^{2} \) \end_inset , is compound by a plain part (47%) located in the Po Valley and by a hilly (12%) and a mountainous district (41%). The plain part, heavily industrialized and populated, presents frequently stagnating meteorological conditions which cause during summer high ozone levels . \layout Standard The national law establishes that \begin_inset Formula \( 200\mu g/m^{3} \) \end_inset for hourly average cannot be exceeded more than once for month ( \emph on DPCM 28/3/83 \emph default ), while alarm and attention level are fixed for hourly average by a Regional law ( \emph on DGR 11/10/2000 \emph default ) to \begin_inset Formula \( 180\mu g/m^{3} \) \end_inset and \begin_inset Formula \( 360\mu g/m^{3} \) \end_inset respectively. Moreover, thresholds for population health is fixed to \begin_inset Formula \( 110\mu g/m^{3} \) \end_inset for 8h average. \layout Standard The pointed out dissimetry has to be carefully taken into account in order to design effective reduction policies. Moreover such analysis pointed out that the mountain part of the region is quite insensitive to precursors reduction even in the order of 30%, and that the overall air quality in the region improves decreasing only \begin_inset Formula \( VOC \) \end_inset emissions. \layout Subsection State of the art \layout Standard A simplified quadratic \emph on source-receptor \emph default model can be found in (Schopp et al.,1998); the model predicts daily ozone concentration at each receptor taking into account \emph on VOC \emph default and \begin_inset Formula \( NO_{x} \) \end_inset emission rates at the sources. \emph on \emph default This \series bold \series default simplified description of the source-receptor relationship can be used within an integrated assessment model, thus allowing for a systematic cost effectivene ss analysis; it should be noticed that more complex models, which contain a high degree of detail of chemical and meteorological processes, can not be employed in optimization analysis because of their computational requests. \layout Subsection Priorities of emission abatments \layout Standard In order to find out the \emph on geographical \emph default differences in solving the problem, two different ANN models - \emph on Plan \emph default region model and \emph on Mountain \emph default region model - have been developed. The optimization problem of reducing the pollution keeping as low as possible the reduction emission costs has been solved using the constrain method: the \emph on Pareto-bound \emph default of fig. \begin_inset LatexCommand \ref{ParetoBound} \end_inset shows the solution of the problem. \layout Standard Some differences between the \emph on Mountain \emph default and the \emph on Plan \emph default region exist for the reduction levels suggested from the \emph on highest-curvature criterion \emph default . This is the most interesting result of the whole analysis: the need of developing a \emph on geographical \emph default -based pollution reduction strategie is stressed. \layout Standard The whole analysis appears as an introduction to a methodological approach, but some future developments can be immediatly suggested: \layout Itemize a highest number of omogeneous geographical areas should be detected, in order to give a more detailed solution to the problem; \layout Itemize the functions \emph on c \emph default \begin_inset Formula \( _{s} \) \end_inset \emph on (r \emph default \begin_inset Formula \( _{s}^{i,j} \) \end_inset \emph on ) \emph default - the reduction costs for unity of the removed pollutant - should be built for the Lombardy case study. \layout Bibliography \bibitem [Bishop, 1995]{bishop} Bishop, C.M., Neural networks for pattern recognition, Oxford University Press, 1994. \layout Bibliography \bibitem [Norgaard et al., 2000]{Norgaard} Norgaard, M., O. Ravn, N.K. Poulsen, L.K. Hansen, Neural networks for modelling and control of dynamic systems, Springer- Verlag, London, 2000. \layout Bibliography \bibitem [Jolliffe, 1986]{PCA} Jolliffe, I.T., Principal Component Analysis, Springer-Verlag, 1986. \the_end
