Supporting Information for research article "Life cycle comparison of environmental emissions from three disposal options for unused pharmaceutical". This spreadsheet provides the calculations and values used for this study; please refer to the manuscript and supporting information (as text) available at http://dx.doi.org/10.1021/es203987b for details about how to use this spreadsheet. We use life cycle assessment methodology to compare three disposal options for unused pharmaceuticals: (i) incineration after take-back to a pharmacy, (ii) wastewater treatment after toilet disposal, and (iii) landfilling or incineration after trash disposal. For each option, emissions of active pharmaceutical ingredients to the environment (API emissions) are estimated along with nine other types of emissions to air and water (non-API emissions). Under a scenario with 50% take-back to a pharmacy and 50% trash disposal, current API emissions are expected to be reduced by 93%. This is within 6% of a 100% trash disposal scenario, which achieves an 88% reduction. The 50% take-back scenario achieves a modest reduction in API emissions over a 100% trash scenario while increasing most non-API emissions by over 300%. If the 50% of unused pharmaceuticals not taken-back are toileted instead of trashed, all emissions increase relative to 100% trash disposal. Evidence suggests that 50% participation in take-back programs could be an upper bound. As a result, we recommend trash disposal for unused pharmaceuticals. A 100% trash disposal program would have similar API emissions to a take-back program with 50% participation, while also having significantly lower non-API emissions, lower financial costs, higher convenience, and higher compliance rates.
The Evans Old Field Plant Database contains FileMaker and Excel files of data collected by Dr. Francis C. Evans during a 50-year study on successional change on Evans Old Field on the Edwin S. George Reserve. Data include plant phenology, location, and abundances observed from 1948 to 1997.
In a sensitive cochlea, the basilar membrane response to transient excitation of any kind--normal acoustic or artificial intracochlear excitation--consists of not only a primary impulse but also a coda of delayed secondary responses with varying amplitudes but similar spectral content around the characteristic frequency of the measurement location. The coda, sometimes referred to as echoes or ringing, has been described as a form of local, short term memory which may influence the ability of the auditory system to detect gaps in an acoustic stimulus such as speech. Depending on the individual cochlea, the temporal gap between the primary impulse and the following coda ranges from once to thrice the group delay of the primary impulse (the group delay of the primary impulse is on the order of a few hundred microseconds). The coda is physiologically vulnerable, disappearing when the cochlea is compromised even slightly. The multicomponent sensitive response is not yet completely understood. We use a physiologically-based, mathematical model to investigate (i) the generation of the primary impulse response and the dependence of the group delay on the various stimulation methods, (ii) the effect of spatial perturbations in the properties of mechanically sensitive ion channels on the generation and separation of delayed secondary responses. The model suggests that the presence of the secondary responses depends on the wavenumber content of a perturbation and the activity level of the cochlea. In addition, the model shows that the varying temporal gaps between adjacent coda seen in experiments depend on the individual profiles of perturbations. Implications for non-invasive cochlear diagnosis are also discussed.
Kansas City, MO emissions can affect a severe weather system by altering the number of CCN, which drives changes in the hydrometeor development. The hydrometeor changes affect cold pool strength, size, and propagation which ultimately determine the strength of the squall line that crosses Kansas City, MO.
This data is in support of the WRR paper by Fries and Kerkez: Big Ship Data: Using Vessel Measurements to Improve Estimates of Temperature and Wind Speed on the Great Lakes
Code is also provided
This includes data for all the plots and maps I created for my paper publication entitled "Improvement of Mars surface snow albedo modeling in LMD Mars GCM with SNICAR".
Included are RegCM simulations driven by three different types of boundary conditions 1. ERA - present day only (1979-2005) 2. GFDL - present day (1978-2005) and future (2041-2065) 3. HadGEM - present day (1978-2005) and future (2041-2065) Each directory has three files with monthly averaged values: ATM: includes 4D (t,z,y,x) atmospheric fields (pressure, winds, temperature, specific humidity, cloud water) and some 3D fields (t,y,x) precipitation, soil temperature, soil water SRF: includes 3D (t,y,x) surface variables (surface pressure, 10m winds, drag coefficient, surface temperature, 2m air temperature, soil moisture, precipitation, runoff, snow, sensible heat flux, latent heat flux, surface radiation components (SW, LW), PBL height, albedo, sunshine duration) RAD: includes 4D radiative transfer variables (SW and LW heating, TOA fluxes, cloud fraction, ice water content) clm_h0 files: CLM land surface files, includes canopy variables, surface fluxes, soil moisture by layers, etc. "
Mathematica Diffusion Simulation: Programmed by Coburn, Caleb. Simulation of diffusion in organic heterostructures, including least square fits and statistical goodness of fit analysis. Used to calculate fits to transient data in Fig 1, 3 and Extended Data Fig.2. Example data file included for download
Matlab Montecarlo simulation: Programmed by Coburn, Caleb. Montecarlo simulation of charge diffusion on a cubic lattice to determine lateral diffusion length as a function of barrier height, assuming thermionic emission over the barrier.
Matlab 2D Diffusion Simulation:Programmed by Coburn, Caleb. Modified from BYU Physics 430 Course Manual. Simulates diffusion around a film discontinuity, such a cut. Used to generate fits to Extended Data Fig. 1
