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<p>PM<span class="inline-formula">_2.5</span>, generated via both direct emission and secondary formation, can have varying environmental impacts due to different physical and chemical properties of its components. However, traditional methods to quantify different PM<span class="inline-formula">_2.5</span> components are often based on online or offline observations and numerical models, which are generally high economic cost- or labor-intensive. In this study, we develop a new method, named Multi-Tracer Estimation Algorithm (MTEA), to identify the primary and secondary components from routine observation of PM<span class="inline-formula">_2.5</span>. By comparing with long-term and short-term measurements of aerosol chemical components in China and the United States, it is proven that MTEA can successfully capture the magnitude and variation of the primary PM<span class="inline-formula">_2.5</span> (PPM) and secondary PM<span class="inline-formula">_2.5</span> (SPM). Applying MTEA to the China National Air Quality Network, we find that (1) SPM accounted for 63.5 % of the PM<span class="inline-formula">_2.5</span> in cities in southern China on average during 2014–2018, while the proportion dropped to 57.1 % in the north of China, and at the same time the secondary proportion in regional background regions was <span class="inline-formula">∼</span> 19 % higher than that in populous regions; (2) the summertime secondary PM<span class="inline-formula">_2.5</span> proportion presented a slight but consistent increasing trend (from 58.5 % to 59.2 %) in most populous cities, mainly because of the recent increase in O<span class="inline-formula">₃</span> pollution in China; (3) the secondary PM<span class="inline-formula">_2.5</span> proportion in Beijing significantly increased by 34 % during the COVID-19 lockdown, which might be the main reason for the observed unexpected PM pollution in this special period; and finally, (4) SPM and O<span class="inline-formula">₃</span> showed similar positive correlations in the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions, but the correlations between total PM<span class="inline-formula">_2.5</span> and O<span class="inline-formula">₃</span> in these two regions, as determined from PPM levels, were quite different. In general, MTEA is a promising tool for efficiently estimating PPM and SPM, and has huge potential for future PM mitigation.</p>