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Updated: Jul 2, 2026

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将低成本传感器与分散模型集成,以获得对城市空气质量的高分辨率洞察力

Anna C O'Regan1, Henrik Grythe2, Philipp Schneider2

  • 1Sustainable Futures Lab, School of Engineering & Architecture, University College Cork, Cork, Ireland; Sustainability Institute, University College Cork, Lee Rd, Sunday's Well, Cork T23 XE10, Ireland.

Environment international
|March 1, 2026
PubMed
概括

一个新的数据融合模型显著改善了城市空气质量预测,揭示了住宅区的PM2.5污染率更高. 这种先进的建模有助于制定有针对性的政策,以减少空气污染和保护公共健康.

关键词:
空气污染 大气污染空气质量建模空气质量建模空气质量政策 空气质量政策数据融合数据融合低成本的传感器 低成本的传感器

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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...