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Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

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Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
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The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
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Predicting Precipitation
The equation that describes the equilibrium between solid calcium carbonate and its solvated ions is:
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Precipitation Gravimetry01:03

Precipitation Gravimetry

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Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
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IR Spectrometers01:25

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There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
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Types of Coprecipitation01:10

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Coprecipitation is the contamination of a precipitate by otherwise soluble species and occurs via different processes. In colloidal precipitates, coprecipitation occurs via surface adsorption. For instance, barium sulfate has a primary layer of adsorbed barium ions and a secondary layer of nitrate counterions. This results in contamination of the precipitate by barium nitrate.
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The Climate Hazards Center Infrared Precipitation with Stations, Version 3.

Chris Funk1, Pete Peterson2, Laura Harrison2

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Summary
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The updated Climate Hazards Center Infrared Precipitation with Stations (CHIRPS3) dataset offers improved precipitation estimates. It better represents rainfall mean and variance, enhancing drought monitoring and hydrologic modeling.

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Area of Science:

  • Hydrology and Climate Science
  • Remote Sensing and Geospatial Analysis
  • Atmospheric Science

Background:

  • The Climate Hazards Center Infrared Precipitation with Stations (CHIRPS) dataset is crucial for various applications, including drought monitoring and agricultural decision-making.
  • CHIRPS version 2 (CHIRPS2) has been widely used, but improvements in data processing and sources are needed.
  • Accurate precipitation data is essential for understanding climate variability and its impacts.

Purpose of the Study:

  • To evaluate the performance of the new CHIRPS version 3 (CHIRPS3) satellite precipitation data.
  • To compare CHIRPS3 with CHIRPS2 and other satellite precipitation products (IMERG, PERSIANN-CCS, GPI).
  • To demonstrate the benefits of CHIRPS3, including extended spatial coverage and improved estimation methods.

Main Methods:

  • Performance evaluation of CHIRPS3, CHIRPS2, IMERG, PERSIANN-CCS, and GPI using high-quality, dense station data in twelve regions.
  • Assessment of precipitation mean and variance representation.
  • Case study in Morocco to illustrate CHIRPS3's rainfall variability capture and the importance of gauge-undercatch correction.

Main Results:

  • CHIRPS3 demonstrates superior performance compared to CHIRPS2, accurately representing both the mean and variance of observed precipitation.
  • CHIRPS3 captures observed rainfall variability more effectively than CHIRPS2, as shown in the Morocco case study.
  • The study highlights the necessity of gauge-undercatch correction for station data when validating satellite precipitation products like CHIRPS3.

Conclusions:

  • CHIRPS3 represents a significant advancement over CHIRPS2, offering more accurate and reliable precipitation estimates.
  • The improved accuracy of CHIRPS3 enhances its utility for critical applications such as drought monitoring, hydrologic modeling, and agricultural planning.
  • Proper data validation methodologies, including gauge-undercatch correction, are essential for maximizing the benefits of advanced satellite precipitation products.