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Air-entraining Agents01:27

Air-entraining Agents

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Air-entraining agents improve the durability and workability of concrete in climates with frequent freezing and thawing. These agents prevent cracks by introducing small air bubbles into the mix, creating spaces accommodating water expansion when temperatures drop. The air-entraining agents lower the surface tension of water, forming stable, small air bubbles. This method is more effective than having accidental large voids, as the intentional, smaller, and evenly distributed air voids improve...
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Air entrainment in concrete significantly enhances the material's durability, especially in environments subjected to freeze-thaw cycles. Introducing small air bubbles into the concrete mix acts as internal voids that accommodate the expansion of water when it freezes, thereby alleviating internal stress and preventing structural cracks. This function is crucial in climates with significant freezing and thawing, as it protects the concrete from repeated stresses that could lead to premature...
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Air content measurement in concrete is critical for ensuring structural integrity and durability of concrete structures, especially in environments prone to severe weather conditions. Accurate air content analysis optimizes concrete's resistance to freeze-thaw cycles and enhances its workability and strength. Several methods are standardized under ASTM guidelines to measure the air content in fresh concrete, each suitable for different concrete types and conditions.
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Related Experiment Video

Updated: Feb 11, 2026

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
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Air Pollution Forecasts: An Overview.

Lu Bai1, Jianzhou Wang2, Xuejiao Ma3

  • 1School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China. baildctg@hotmail.com.

International Journal of Environmental Research and Public Health
|April 21, 2018
PubMed
Summary
This summary is machine-generated.

Accurate air pollution forecasting is crucial for environmental protection. This review covers statistical, artificial intelligence, and numerical methods, including hybrid models, to aid researchers in selecting optimal forecasting techniques.

Keywords:
air pollution forecastartificial intelligence methodsforecasting modelshybrid modelsnumerical forecast methodsstatistical methods

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Area of Science:

  • Environmental Science
  • Atmospheric Chemistry
  • Data Science

Background:

  • Air pollution poses significant risks to ecological systems and human well-being.
  • Accurate air pollution forecasting is essential for implementing effective control measures.
  • Research in air pollution forecasting is critical due to escalating environmental concerns.

Purpose of the Study:

  • To provide a comprehensive overview of air pollution forecasting models.
  • To review the theoretical foundations and practical applications of various forecasting methods.
  • To facilitate informed decision-making for researchers in the field.

Main Methods:

  • Categorization of forecasting methods into statistical, artificial intelligence, and numerical approaches.
  • Exploration of recently developed hybrid models for enhanced forecast accuracy.
  • Comparative analysis of the strengths and weaknesses of different forecasting techniques.

Main Results:

  • Identification of three classical categories of air pollution forecasting methods.
  • Highlighting the potential of hybrid models to improve prediction accuracy.
  • Presentation of a comparative analysis of various forecasting approaches.

Conclusions:

  • Air pollution forecasting is a vital component of environmental management.
  • Understanding the diverse range of forecasting methods is key to accurate predictions.
  • This review serves as a valuable resource for researchers advancing air pollution control strategies.