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相关概念视频

Linear Approximations01:23

Linear Approximations

For a differentiable function of two variables, linear approximation estimates values near a known point by replacing the curved surface with its tangent plane. Consider the function\begin{equation*}f(x,y)=x^2+3y^2\end{equation*}near the point (2, 1). The exact value at this point is f(2, 1) = 22 + 3(1)2 = 4 + 3 = 7.The linear approximation of f(x, y)) near (a, b) is\begin{equation*}L(x,y)=f(a,b)+f_x(a,b)(x-a)+f_y(a,b)(y-b)\end{equation*}First, compute the partial derivatives: fx(x, y) = 2x and...

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Updated: Jun 18, 2026

Automated, High-resolution Mobile Collection System for the Nitrogen Isotopic Analysis of NOx
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高分辨率的城市空气污染映射

Joshua S Apte1,2, Chirag Manchanda1

  • 1Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.

Science (New York, N.Y.)
|July 25, 2024
PubMed
概括
此摘要是机器生成的。

了解城市空气质量需要先进的监测. 移动监测和密集的传感器网络提供了对污染动态,人类健康影响和环境正义的补充见解.

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科学领域:

  • 环境科学
  • 公共卫生
  • 大气化学

背景情况:

  • 城市空气污染是复杂的,受空间,时间和化学因素的影响.
  • 这些因素对人口暴露,人类健康和环境正义产生重大影响.
  • 描述多维城市空气质量系统对于有效的干预至关重要.

研究的目的:

  • 对城市空气质量评估的移动监测和密集传感器网络的见解进行审查和强调.
  • 讨论这些现场测量方法的独特但互补的优点.
  • 探索它们对了解细度过程和对健康和差异的影响的影响.

主要方法:

  • 在现场测量技术的审查:移动监测和密集的传感器网络.
  • 分析城市空气质量的每个方法的优点和局限性.
  • 检查组合方法如何提高对空间和时间污染模式的理解.

主要成果:

  • 移动监测在精细的空间尺度上测量多种污染物,有助于过程理解和控制策略.
  • 密集的传感器网络在许多地点提供高时间分辨率的数据.
  • 使用这两种方法的综合方法揭示了影响暴露和差异的详细时空模式.

结论:

  • 结合移动监测和密集的传感器网络, 提供了对城市空气质量动态的有力洞察.
  • 这些方法对于识别与污染相关的健康风险和环境不公正至关重要.
  • 使用这些技术的复杂研究提供了针对性干预的机制理解.