The Parameters Estimation for a PM<sub>2.5</sub> Transport Model with the Adjoint Method

<div>The mean field of PM<sub>2.5</sub> concentrations (<i>μ</i>g/m<sup>3</sup>), where “<svg height="7.35473pt" id="M79" style="vertical-align:-0.3499303pt" version="1.1" viewbox="-0.0498162 -7.0048 4.94072 7.35473" width="4.94072pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M326 255C326 330 263 391 186 391S46 330 46 255S109 119 186 119S326 180 326 255ZM274 255C274 204 235 163 186 163S98 204 98 255S137 347 186 347S274 306 274 255Z" id="g117-73"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="371" vert-adv-y="371"></glyph.data></g></svg>” represents that in this city the correlation coefficient is positive and “<svg height="8.69875pt" id="M80" style="vertical-align:-0.3499298pt" version="1.1" viewbox="-0.0498162 -8.34882 8.85534 8.69875" width="8.85534pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M666 12L340 567H330L4 12L11 0H659L666 12ZM579 50H91L335 465L579 50Z" id="g114-162"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="671" vert-adv-y="671"></glyph.data></g></svg>” represents that the correlation coefficient is negative in this city.</div>

Advances in Meteorology

fig7

Figure 7

Figure 7: The Parameters Estimation for a PM<sub>2.5</sub> Transport Model with the Adjoint Method 

Advances in Meteorology

The Parameters Estimation for a PM2.5 Transport Model with the Adjoint Method

Figure 7

The Parameters Estimation for a PM_2.5 Transport Model with the Adjoint Method