Sun Colostate 0053A 10705.Pdf (2.555Mb)

Total Page:16

File Type:pdf, Size:1020Kb

Sun Colostate 0053A 10705.Pdf (2.555Mb) DISSERTATION INVESTIGATION OF MOLECULAR EFFECTS OF THE SOY-DERIVED PHYTOESTROGEN GENISTEIN ON CARDIOMYOCYTES BY PROTEOMIC ANALYSIS Submitted by Zeyu Sun Department of Chemical and Biological Engineering In partial fulfillment of the requirements For the Degree of Doctor of Philosophy Colorado State University Fort Collins, Colorado Fall 2011 Doctoral Committee: Advisor: Kenneth Reardon Co-Advisor: Karyn Hamilton Christopher Orton Bradley Reisfeld ABSTRACT INVESTIGATION OF MOLECULAR EFFECTS OF THE SOY-DERIVED PHYTOESTROGEN GENISTEIN ON CARDIOMYOCYTES BY PROTEOMIC ANALYSIS The soy-derived phytoestrogen genistein (GEN) has received attention for its potential to benefit the cardiovascular system by providing protection to cardiomyocytes against pathophysiological stresses. Although GEN is a well-known estrogen receptor (ER) agonist and a non-specific tyrosine kinase inhibitor, current understanding of the complex cellular and molecular effects of GEN in cardiomyocytes is still incomplete. The overall goal of this dissertation is to use high throughput proteomics methodologies to better understand the molecular action of GEN in cardiomyocytes and to identify proteins and pathways that respond to GEN treatment. The first study of this project focused on the concentration-dependent proteome changes in cultured HL-1 cardiomyocytes due to GEN treatments. Proteins from HL-1 cardiomyocytes treated with 1 µM and 50 µM GEN were prefractionated into hydrophilic and hydrophobic protein fractions and were analyzed by two-dimensional electrophoresis followed by protein identification using tandem mass spectrometry (MS). In total, 25 and 62 differential expressed proteins were identified in response to 1 µM and 50 µM of GEN treatment, respectively. These results suggest that 1 µM GEN enhanced the expression of heat shock proteins and anti-apoptotic proteins, while 50 µM GEN down-regulated glycolytic and antioxidant enzymes, potentially making cardiomyocytes more susceptible to energy depletion and apoptosis. The second study, employing a two-dimensional liquid chromatography and tandem MS shotgun proteomics workflow, was carried out to dissect the cellular functions changed in cardiomyocytes by ER-dependent or ER-independent actions of GEN. In this study, ii primary cardiomyocytes isolated from male adult SD rats were treated with 10 µM GEN without or with 10 µM ER antagonist ICI 182,780 (ERA) before proteomics comparison. A total of 14 and 15 proteins were found differentially expressed in response to the GEN, and the GEN+ERA treatment, respectively. Cellular functions such as glucose and fatty acid metabolism and cardioprotection were found to be modulated by GEN in an ER-dependent fashion, while proteins involved with steroidogenesis and estrogen signaling were identified as novel effectors of GEN via ER-independent actions. In this study, a consensus-iterative searching strategy was also developed to enhance the sensitivity of the shotgun proteomic approach. In the last study, an attempt to explore the response to a GEN stimulus in the signaling pathways, we developed a phosphopeptide enrichment method to assist the detection of protein phosphorylation in a complex peptide mixture. The quantitative performance of a sequential immobilized metal affinity chromatography (SIMAC) protocol was evaluated. We further conducted a preliminary application of this protocol in a large-scale, quantitative, label-free phosphoproteomics study to explore the alterations of protein phosphorylation patterns due to ER-independent GEN action in the SD rat cardiomyocytes. This project demonstrates the usefulness of proteomics methodologies to screen novel molecular targets influenced by GEN in cardiomyocytes. This is also the first investigation of the complex cellular impact of this soy-derived phytoestrogen in cardiomyocytes via a systems biology perspective. iii ACKNOWLEDGEMENT I would like to express my gratitude to all my committee members, Dr. Kenneth Reardon, Dr. Karyn Hamilton, Dr. Christopher Orton and Dr. Bradley Reisfeld who gave me the possibility to complete this dissertation and all the assistance along the journey. I owe my deepest gratitude to my advisor Dr. Reardon and co-advisor Dr. Hamilton for being extraordinary mentors for me by sharing their academic expertise and experience with me, and by providing guidance and encouragement throughout my Ph.D. work. It is an honor for me to work with them these years. I like to show my gratitude to all helping hands of all past and present members in Dr.Reardon’s lab and Dr. Hamilton’s lab. I also want to thank the following people who provided critical technical assistance and constructive advices: Dr. Carla Lacerda, Dr. Nichole Reisdorph, Dr. Jessica Prenni, Dr. Ann Hess, Dr. Andrey Ptitsyn, Dr. William Claycomb, Brian Cranmer, Delian Yang, Laurie Biela and Reuland Nellie. This work cannot be accomplished without their generous assistance and valuable input. Two outstanding undergraduate students have actively participated in my research: Kathryn Knopinski and Caitlin Mitchel. I want to use this opportunity to thank their hard working and their contributions to my research progress. Finally, I would like to say thank you to all my family and friends who have encouraged me during these years. Especially, I would like to give my special thanks to my mother Jiali Zhou, father Weiqiang Sun, and my fiancée Bing Chi for their patient support behind me to complete this work. Zeyu Sun At Dept. of Chemical and Biological Engineering Sep-11-2011 iv TABLE OF CONTENTS Chapter 1 Background and Objectives ......................................................................................... 1 1. Introduction ................................................................................................................. 1 1.1. Soy phytoestrogens and cardiovascular health .......................................................... 1 1.2. Cardiomyocytes and cardioprotection ...................................................................... 3 1.3. Genistein, chemical and biological properties ........................................................... 6 1.4. Proteomics and phosphoproteomics ....................................................................... 14 1.5. Models .................................................................................................................. 16 2. Objectives and Contributions of This Dissertation ...................................................... 18 Chapter 2 Phosphoproteomics and Molecular Cardiology: Techniques, Applications and Challenges ................................................................................................................................ 42 1. Introduction ............................................................................................................... 42 2. General Sample Preparation Strategies ....................................................................... 44 3. Subcellular Fractionation ........................................................................................... 45 4. 2DE Workflow .......................................................................................................... 47 4.1. Autoradiography .................................................................................................... 48 4.2. Phosphoprotein stains ............................................................................................ 49 4.3. Immunoblotting ..................................................................................................... 49 5. Liquid Chromatographic Methods .............................................................................. 50 5.1. Strong cation exchange liquid chromatography ...................................................... 52 5.2. Strong anion exchange liquid chromatography ....................................................... 53 5.3. Hydrophilic interaction liquid chromatography ...................................................... 54 5.4. Electrostatic repulsion hydrophilic interaction chromatography .............................. 55 6. Affinity Enrichment Strategies ................................................................................... 56 6.1. General considerations of using enrichment strategy .............................................. 56 6.2. Immunoaffinity method ......................................................................................... 58 6.3. Immobilized metal affinity chromatography ........................................................... 58 6.4. Metal oxide affinity chromatography ..................................................................... 60 6.5. Chemical derivatization methods ........................................................................... 61 7. Identification of Phosphopeptides by Tandem Mass Spectrometry .............................. 63 7.1. General considerations ........................................................................................... 63 7.2. Collision-induced dissociation with neutral loss scan ............................................. 64 7.3. Electron transfer dissociation ................................................................................. 66 8. Bioinformatics for Phosphoproteomics ...................................................................... 67 8.1. General procedure .................................................................................................. 67 8.2. Peptide identification ............................................................................................
Recommended publications
  • Development Team
    Paper No: 16 Environmental Chemistry Module: 01 Environmental Concentration Units Development Team Prof. R.K. Kohli Principal Investigator & Prof. V.K. Garg & Prof. Ashok Dhawan Co- Principal Investigator Central University of Punjab, Bathinda Prof. K.S. Gupta Paper Coordinator University of Rajasthan, Jaipur Prof. K.S. Gupta Content Writer University of Rajasthan, Jaipur Content Reviewer Dr. V.K. Garg Central University of Punjab, Bathinda Anchor Institute Central University of Punjab 1 Environmental Chemistry Environmental Environmental Concentration Units Sciences Description of Module Subject Name Environmental Sciences Paper Name Environmental Chemistry Module Name/Title Environmental Concentration Units Module Id EVS/EC-XVI/01 Pre-requisites A basic knowledge of concentration units 1. To define exponents, prefixes and symbols based on SI units 2. To define molarity and molality 3. To define number density and mixing ratio 4. To define parts –per notation by volume Objectives 5. To define parts-per notation by mass by mass 6. To define mass by volume unit for trace gases in air 7. To define mass by volume unit for aqueous media 8. To convert one unit into another Keywords Environmental concentrations, parts- per notations, ppm, ppb, ppt, partial pressure 2 Environmental Chemistry Environmental Environmental Concentration Units Sciences Module 1: Environmental Concentration Units Contents 1. Introduction 2. Exponents 3. Environmental Concentration Units 4. Molarity, mol/L 5. Molality, mol/kg 6. Number Density (n) 7. Mixing Ratio 8. Parts-Per Notation by Volume 9. ppmv, ppbv and pptv 10. Parts-Per Notation by Mass by Mass. 11. Mass by Volume Unit for Trace Gases in Air: Microgram per Cubic Meter, µg/m3 12.
    [Show full text]
  • The Vertical Distribution of Soluble Gases in the Troposphere
    UC Irvine UC Irvine Previously Published Works Title The vertical distribution of soluble gases in the troposphere Permalink https://escholarship.org/uc/item/7gc9g430 Journal Geophysical Research Letters, 2(8) ISSN 0094-8276 Authors Stedman, DH Chameides, WL Cicerone, RJ Publication Date 1975 DOI 10.1029/GL002i008p00333 License https://creativecommons.org/licenses/by/4.0/ 4.0 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Vol. 2 No. 8 GEOPHYSICAL RESEARCHLETTERS August 1975 THE VERTICAL DISTRIBUTION OF SOLUBLE GASES IN THE TROPOSPHERE D. H. Stedman, W. L. Chameides, and R. J. Cicerone Space Physics Research Laboratory Department of Atmospheric and Oceanic Science The University of Michigan, Ann Arbor, Michigan 48105 Abstrg.ct. The thermodynamic properties of sev- Their arg:uments were based on the existence of an eral water-soluble gases are reviewed to determine HC1-H20 d•mer, but we consider the conclusions in- the likely effect of the atmospheric water cycle dependeht of the existence of dimers. For in- on their vertical profiles. We find that gaseous stance, Chameides[1975] has argued that HNO3 HC1, HN03, and HBr are sufficiently soluble in should follow the water-vapor mixing ratio gradi- water to suggest that their vertical profiles in ent, based on the high solubility of the gas in the troposphere have a similar shape to that of liquid water. In this work, we generalize the water va•or. Thuswe predict that HC1,HN03, and moredetailed argumentsof Chameides[1975] and HBr exhibit a steep negative gradient with alti- suggest which species should exhibit this nega- tude roughly equal to the altitude gradient of tive gradient and which should not.
    [Show full text]
  • Package 'Marelac'
    Package ‘marelac’ February 20, 2020 Version 2.1.10 Title Tools for Aquatic Sciences Author Karline Soetaert [aut, cre], Thomas Petzoldt [aut], Filip Meysman [cph], Lorenz Meire [cph] Maintainer Karline Soetaert <[email protected]> Depends R (>= 3.2), shape Imports stats, seacarb Description Datasets, constants, conversion factors, and utilities for 'MArine', 'Riverine', 'Estuarine', 'LAcustrine' and 'Coastal' science. The package contains among others: (1) chemical and physical constants and datasets, e.g. atomic weights, gas constants, the earths bathymetry; (2) conversion factors (e.g. gram to mol to liter, barometric units, temperature, salinity); (3) physical functions, e.g. to estimate concentrations of conservative substances, gas transfer and diffusion coefficients, the Coriolis force and gravity; (4) thermophysical properties of the seawater, as from the UNESCO polynomial or from the more recent derivation based on a Gibbs function. License GPL (>= 2) LazyData yes Repository CRAN Repository/R-Forge/Project marelac Repository/R-Forge/Revision 205 Repository/R-Forge/DateTimeStamp 2020-02-11 22:10:45 Date/Publication 2020-02-20 18:50:04 UTC NeedsCompilation yes 1 2 R topics documented: R topics documented: marelac-package . .3 air_density . .5 air_spechum . .6 atmComp . .7 AtomicWeight . .8 Bathymetry . .9 Constants . 10 convert_p . 11 convert_RtoS . 11 convert_salinity . 13 convert_StoCl . 15 convert_StoR . 16 convert_T . 17 coriolis . 18 diffcoeff . 19 earth_surf . 21 gas_O2sat . 23 gas_satconc . 25 gas_schmidt . 27 gas_solubility . 28 gas_transfer . 31 gravity . 33 molvol . 34 molweight . 36 Oceans . 37 redfield . 38 ssd2rad . 39 sw_adtgrad . 40 sw_alpha . 41 sw_beta . 42 sw_comp . 43 sw_conserv . 44 sw_cp . 45 sw_dens . 47 sw_depth . 49 sw_enthalpy . 50 sw_entropy . 51 sw_gibbs . 52 sw_kappa .
    [Show full text]
  • Calculation Exercises with Answers and Solutions
    Atmospheric Chemistry and Physics Calculation Exercises Contents Exercise A, chapter 1 - 3 in Jacob …………………………………………………… 2 Exercise B, chapter 4, 6 in Jacob …………………………………………………… 6 Exercise C, chapter 7, 8 in Jacob, OH on aerosols and booklet by Heintzenberg … 11 Exercise D, chapter 9 in Jacob………………………………………………………. 16 Exercise E, chapter 10 in Jacob……………………………………………………… 20 Exercise F, chapter 11 - 13 in Jacob………………………………………………… 24 Answers and solutions …………………………………………………………………. 29 Note that approximately 40% of the written exam deals with calculations. The remainder is about understanding of the theory. Exercises marked with an asterisk (*) are for the most interested students. These exercises are more comprehensive and/or difficult than questions appearing in the written exam. 1 Atmospheric Chemistry and Physics – Exercise A, chap. 1 – 3 Recommended activity before exercise: Try to solve 1:1 – 1:5, 2:1 – 2:2 and 3:1 – 3:2. Summary: Concentration Example Advantage Number density No. molecules/m3, Useful for calculations of reaction kmol/m3 rates in the gas phase Partial pressure Useful measure on the amount of a substance that easily can be converted to mixing ratio Mixing ratio ppmv can mean e.g. Concentration relative to the mole/mole or partial concentration of air molecules. Very pressure/total pressure useful because air is compressible. Ideal gas law: PV = nRT Molar mass: M = m/n Density: ρ = m/V = PM/RT; (from the two equations above) Mixing ratio (vol): Cx = nx/na = Px/Pa ≠ mx/ma Number density: Cvol = nNav/V 26 -1 Avogadro’s
    [Show full text]
  • Lecture 3. the Basic Properties of the Natural Atmosphere 1. Composition
    Lecture 3. The basic properties of the natural atmosphere Objectives: 1. Composition of air. 2. Pressure. 3. Temperature. 4. Density. 5. Concentration. Mole. Mixing ratio. 6. Gas laws. 7. Dry air and moist air. Readings: Turco: p.11-27, 38-43, 366-367, 490-492; Brimblecombe: p. 1-5 1. Composition of air. The word atmosphere derives from the Greek atmo (vapor) and spherios (sphere). The Earth’s atmosphere is a mixture of gases that we call air. Air usually contains a number of small particles (atmospheric aerosols), clouds of condensed water, and ice cloud. NOTE : The atmosphere is a thin veil of gases; if our planet were the size of an apple, its atmosphere would be thick as the apple peel. Some 80% of the mass of the atmosphere is within 10 km of the surface of the Earth, which has a diameter of about 12,742 km. The Earth’s atmosphere as a mixture of gases is characterized by pressure, temperature, and density which vary with altitude (will be discussed in Lecture 4). The atmosphere below about 100 km is called Homosphere. This part of the atmosphere consists of uniform mixtures of gases as illustrated in Table 3.1. 1 Table 3.1. The composition of air. Gases Fraction of air Constant gases Nitrogen, N2 78.08% Oxygen, O2 20.95% Argon, Ar 0.93% Neon, Ne 0.0018% Helium, He 0.0005% Krypton, Kr 0.00011% Xenon, Xe 0.000009% Variable gases Water vapor, H2O 4.0% (maximum, in the tropics) 0.00001% (minimum, at the South Pole) Carbon dioxide, CO2 0.0365% (increasing ~0.4% per year) Methane, CH4 ~0.00018% (increases due to agriculture) Hydrogen, H2 ~0.00006% Nitrous oxide, N2O ~0.00003% Carbon monoxide, CO ~0.000009% Ozone, O3 ~0.000001% - 0.0004% Fluorocarbon 12, CF2Cl2 ~0.00000005% Other gases 1% Oxygen 21% Nitrogen 78% 2 • Some gases in Table 3.1 are called constant gases because the ratio of the number of molecules for each gas and the total number of molecules of air do not change substantially from time to time or place to place.
    [Show full text]
  • Interactions Between Polymers and Nanoparticles : Formation of « Supermicellar » Hybrid Aggregates
    1 Interactions between Polymers and Nanoparticles : Formation of « Supermicellar » Hybrid Aggregates J.-F. Berret@, K. Yokota* and M. Morvan, Complex Fluids Laboratory, UMR CNRS - Rhodia n°166, Cranbury Research Center Rhodia 259 Prospect Plains Road Cranbury NJ 08512 USA Abstract : When polyelectrolyte-neutral block copolymers are mixed in solutions to oppositely charged species (e.g. surfactant micelles, macromolecules, proteins etc…), there is the formation of stable “supermicellar” aggregates combining both components. The resulting colloidal complexes exhibit a core-shell structure and the mechanism yielding to their formation is electrostatic self-assembly. In this contribution, we report on the structural properties of “supermicellar” aggregates made from yttrium-based inorganic nanoparticles (radius 2 nm) and polyelectrolyte-neutral block copolymers in aqueous solutions. The yttrium hydroxyacetate particles were chosen as a model system for inorganic colloids, and also for their use in industrial applications as precursors for ceramic and opto-electronic materials. The copolymers placed under scrutiny are the water soluble and asymmetric poly(sodium acrylate)-b-poly(acrylamide) diblocks. Using static and dynamical light scattering experiments, we demonstrate the analogy between surfactant micelles and nanoparticles in the complexation phenomenon with oppositely charged polymers. We also determine the sizes and the aggregation numbers of the hybrid organic-inorganic 1 2 complexes. Several additional properties are discussed, such
    [Show full text]
  • Problem Set #1 Due Tues., Sept
    ATM 507 Problem Set #1 due Tues., Sept. 13, 2011 (note: late problem sets will not receive full credit unless you make prior arrangements!) Watch your units - make sure they are consistent - check conversions and cancellations! Also – watch significant figures!!! No answer should have more than 2 or 3 significant figures (without a very good reason). 1. Convert a number density (absolute concentration) of 7.5x1012 molecules cm-3 to an appropriate volume mixing ratio at a) 1 atm, 20°C. b) 100 mbar, 243 K. c) 800 mbar, 0°C. -3 2. Convert a concentration of SO2 of 0.1 ppmv to μg m at T = 298 K and 1 atm. Do the same for 0.1 ppmv of NO, NO2, and O3. 3. From the following table a) At 10 km altitude, to what absolute concentration does a mixing ratio of 3 ppmv correspond? b) At 10 km altitude, to what volume mixing ratio does an absolute concentration of 1.7x1010 molecules cm-3 correspond? c) At what altitude does a mixing ratio of 3 ppmv correspond to an absolute concentration of 5.1x1011 molecules cm-3? d) An OH mixing ratio of 10 pptv corresponds to what absolute concentrations at i) 0 and ii) 25 km altitude? Atmospheric Parameters Altitude (km) Temperature (K) H (km) [M] (cm-3) Pressure (mb) 0 288.8 8.6 2.5(19) 1013.0 5 259.3 7.7 1.5(19) 542.0 10 229.7 6.8 8.5(18) 269.0 15 212.6 6.3 4.2(18) 122.0 20 215.5 6.4 1.8(18) 55.0 25 218.6 6.5 8.3(17) 25.0 30 223.7 6.6 3.7(17) 11.5 35 235.1 7.0 1.7(17) 5.4 40 249.9 7.4 7.7(16) 2.7 45 266.1 7.9 3.8(16) 1.4 50 271.0 8.0 2.0(16) 0.73 55 265.3 7.9 1.1(16) 0.38 60 253.7 7.5 5.7(15) 0.20 65 237.0 7.0 3.0(15) 0.10 70 220.2 6.5 1.5(15) 0.046 75 203.4 6.0 7.4(14) 0.021 80 186.7 5.5 3.4(14) 0.0089 85 170.0 5.0 2.3(14) 0.0055 4.
    [Show full text]
  • Redalyc.Calcite Dissolution by Mixing Waters: Geochemical Modeling And
    Geologica Acta: an international earth science journal ISSN: 1695-6133 [email protected] Universitat de Barcelona España SANZ, E.; AYORA, C.; CARRERA, J. Calcite dissolution by mixing waters: geochemical modeling and flow-through experiments Geologica Acta: an international earth science journal, vol. 9, núm. 1, marzo, 2011, pp. 67-77 Universitat de Barcelona Barcelona, España Available in: http://www.redalyc.org/articulo.oa?id=50522124007 How to cite Complete issue Scientific Information System More information about this article Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Journal's homepage in redalyc.org Non-profit academic project, developed under the open access initiative Geologica Acta, Vol.9, Nº 1, March 2011, 67-77 DOI: 10.1344/105.000001652 Available online at www.geologica-acta.com Calcite dissolution by mixing waters: geochemical modeling and flow-through experiments 1 2 1 E. SANZ C. AYORA J. CARRERA 1 ExxonMobil Upstream Research Company Houston, Texas, USA E-mail: [email protected] 2 Institute of Enviromental Assessment and Water Research, IDAEA-ECSIC Barcelona, Spain ABSTRACT TABLE CAPTIONS Dissolution of carbonates has been commonly predicted by geochemical models to occur at the seawater-freshwater mixing zone of coastal aquifers along a geological time scale. However, field evidences are inconclusive:dissolution TABLE 1 Input end-member solutions used in the experiments and numerical simulations. Ω accounts for saturation, and I for ionic strength. vs. lack of dissolution. In this study we investigate the process of calcite dissolution by mixing waters of different salinities and pCO2, by means of geochemical modeling and laboratory experiments.
    [Show full text]
  • Mole Fraction - Wikipedia
    4/28/2020 Mole fraction - Wikipedia Mole fraction In chemistry, the mole fraction or molar fraction (xi) is defined as unit of the amount of a constituent (expressed in moles), ni divided by the total amount of all constituents in a mixture (also [1] expressed in moles), ntot: .These expression is given below:- The sum of all the mole fractions is equal to 1: The same concept expressed with a denominator of 100 is the mole percent or molar percentage or molar proportion (mol%). The mole fraction is also called the amount fraction.[1] It is identical to the number fraction, which is defined as the number of molecules of a constituent Ni divided by the total number of all molecules Ntot. The mole fraction is sometimes denoted by the lowercase Greek letter χ (chi) instead of a Roman x.[2][3] For mixtures of gases, IUPAC recommends the letter y.[1] The National Institute of Standards and Technology of the United States prefers the term amount-of- substance fraction over mole fraction because it does not contain the name of the unit mole.[4] Whereas mole fraction is a ratio of moles to moles, molar concentration is a quotient of moles to volume. The mole fraction is one way of expressing the composition of a mixture with a dimensionless quantity; mass fraction (percentage by weight, wt%) and volume fraction (percentage by volume, vol%) are others. Contents Properties Related quantities Mass fraction Molar mixing ratio Mixing binary mixtures with a common component to form ternary mixtures Mole percentage Mass concentration Molar concentration Mass and molar mass Spatial variation and gradient References https://en.wikipedia.org/wiki/Mole_fraction 1/5 4/28/2020 Mole fraction - Wikipedia Properties Mole fraction is used very frequently in the construction of phase diagrams.
    [Show full text]
  • 1 Atmospheric Sciences 501. Course Notes Autumn 1998. 1. Ideal Gas
    1 Atmospheric Sciences 501. Course Notes Autumn 1998. 1. Ideal Gas Law and Hydrostatics. 1.1 Ideal Gas Law. Basic thermodynamic variables are: Pressure, p (N m-2; 1 N m-2 = 1 pascal (Pa) = 0.01 millibar (mb) = 0.01hectoPascals (hPa). Density, r (kgm-3) Temperature, T (K) . If the energy due to intermolecular forces is small relative to molecular kinetic energy, the ideal gas law is an excellent approximation to the equation of state relating these variables: pRT=r (1.1) R* where R = = gas constant; R* = universal gas constant = 8314J kmol-1 K-1; M = molar M weight (kg/kg-mole) and R = specific gas constant for dry air = 287 J kg-1 K-1. 1.2 Molecules and the ideal gas law, Maxwell's kinetic interpretation. Note that r=nmÃà (1.2) where nà = number density (number of molecules per unit volume m-3), and mà = molecular mass (kg). Also MmA= à (1.3) where A = Avogadro's Number = 6.022x1026 molecules per mole; note that, since SI units are used, moles here are kilogram-moles, not gram-moles. Substituting (1.2) and (1.3) into (1.1): 2 æ R* ö p = ç ÷ nTÃÃ= knT (1.4) è A ø * æ R ö -23 -1 where k = ç ÷ = 1.381x10 J K is Boltzmann's Constant. è A ø Now consider the pressure exerted by molecules of gas on a surface perpendicular to the x- axis in a Cartesian reference frame. This is the force per unit area and is equivalent to the average flux in the x-direction of molecules with x-momentum mvà , mvÃà nv x ()xx× where () represents averaging over molecular velocities.
    [Show full text]
  • The Atmosphere
    The Atmosphere Atmospheric composition Measures of concentration Atmospheric pressure Barometric law Literature connected with today’s lecture: Jacob, chapter 1 - 2 Exercises: 1:1 – 1:6; 2:1 – 2:4 The Atmosphere The atmosphere –Thin “skin” of air surrounding the planet Description Role of natural atmosphere Effects of changed composition Atmospheric change Climate UV protection Acidification Health 1 Composition of the Atmosphere Dry atmosphere (excl. H2O): Gas Mixing ratio Dry atmosphere: (mole/mole) Dominated by nitrogen and oxygen Nitrogen (N2)0.78 Noble gases, in particular argon Oxygen (O2)0.21 Argon (Ar) 0.0093 Conc. (O2 + N2 + Ar) 1 mole/mole -6 Remaining components trace gases: E.g. Carbon dioxide (CO2) 365x10 Carbon dioxide, ozone, methane Neon (Ne) 18x10-6 -6 Ozone (O3) 0.01-10x10 Helium (He) 5.2x10-6 Humid atmosphere: -6 Water vapour: Varies, up to approx. 0.03 Methane (CH4) 1.7x10 moles/mole Krypton (Kr) 1.1x10-6 -9 Hydrogen (H2) 500x10 -9 Nitrous oxide (N2O) 320x10 Calculation Example: Calculate the density of dry air at T = 280 K and P = 1000 hPa! The atmosphere an ideal gas (in most cases): PV = nRT Density: = m/V = nM/V From the gas law: n/V = P/RT => =MP/RT Air is a mixture of gases – average molar mass: Ma = 29,0 kg/kmole Gas constant: R = 8314,3 J/(kmole K) Insert numbers: 3 = MaP/RT = 29,0*1000*100/(280*8314,3) = 1,25 kg/m 2 Atmospheric Concentration of Species Mixing ratio: Expressions atmospheric concentration: (No. moles of X)/(No. moles air molecules) Number concentration: Or: mass X/mass
    [Show full text]
  • Supplement of Tropospheric Sources and Sinks of Gas-Phase Acids in the Colorado Front Range
    Supplement of Atmos. Chem. Phys., 18, 12315–12327, 2018 https://doi.org/10.5194/acp-18-12315-2018-supplement © Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. Supplement of Tropospheric sources and sinks of gas-phase acids in the Colorado Front Range James M. Mattila et al. Correspondence to: Delphine K. Farmer ([email protected]) The copyright of individual parts of the supplement might differ from the CC BY 4.0 License. Supplemental Figures Figure S1. Timeseries of tower elevator carriage altitude throughout the reported measurement period. Representative noon, night, and morning vertical profiles were measured at the periods denoted ‘A’, ‘B’, and ‘C’, respectively. Figure S2. Mixing ratio data timeseries for all detected gas-phase acids spanning the reported data acquisition period. All data were collected at 1 Hz acquisition rates. Figure S3. Vertical profiles of O3, NOx, CO, relative humidity, and air temperature at representative noon, night, and morning periods. Figure S4. Vertical profiles for all detected gas-phase acids at representative noon, night, and morning periods, showing mixing ratios as a function of altitude. Data are binned by altitude (10 m per bin). Data points are means of each bin. Error bars represent ± one standard deviation of binned values. Figure S5. Diel profile of NOx measured at the site throughout the reported measurement period. Data are binned by hour of day. Data points are binned means, and error bars are ± one standard deviation of binned data. Figure S6. Wind plot of ammonia measured at the BAO tower during the reported measurement period.
    [Show full text]