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It's urgent to clarify the quantitative relationship between declining fine−particle (PM 2.5) concentrations and increasing ozone (O 3) levels as ozone pollution is increasingly severe in China. Here, we analyze the ground–based data of aerosol optical properties, particulates, and gaseous pollutants collected in a simultaneous observation in Kunming, locate in the Yunnan–Guizhou Plateau, from June 2014 to May 2017. The data exhibit slightly rising levels of PM 2.5 , O 3 , and carbon monoxid (CO), declining AOD (aerosol optical depth) but increasing AE (Angstrom exponent). Both the seasonal PM 2.5 and CO concentrations were low in the wet season and high in the dry season. The seasonal ozone levels and AE almost increased monotonically while the seasonal AOD decreased wavelike. Overall, the maximum daily 8 h average (MDA8) O 3 concentrations positively related to PM 2.5 concentrations with temperature>22 °C, RH<45%, and AOD<1.0 in the wet season. Generally, MDA8 O 3 concentrations didn't fluctuate with PM 2.5 concentrations in the dry season. High SSA (single scattering albedo) corresponded to high MDA8 O 3 concentrations and low SSA corresponded to low MDA8 O 3 concentrations in the wet season. However, lower SSA values in the dry season were observable. Most high MDA8 O 3 concentrations (>100 μg m−3) in the wet season occurred with AE at 1.0–1.5. High MDA8 O 3 concentrations (>100 μg m−3) in dry season appeared with an AE range of ~0.75–1.75. Low MDA8 O 3 concentrations occurred with AOD>2.0 and RH>75%, despite T>20 °C. The biomass−burning/urban aerosols were dominant (71.11% in the wet season and 74.40% in the dry season). The PSCF (Potential Source Contribution Function) results revealed the air pollutants from inside and outside China will have great impacts on the pollutant levels in Kunming besides the local emissions. Particularly, the severe pollution in India may aggravate Kunming's air pollution. • High SSA corresponded to high MDA8 O 3 concentrations and positive MDA8 O 3 − PM 2.5 relations were observable with SSA>0.95. • Most high MDA8 O 3 concentrations (>100 μg m−3) in the wet season occurred with AE at 1.0–1.5. • Biomass−burning/urban aerosols were dominant, accounting for over 70% of the whole aerosol types. • The air pollutants from outside China may have an important impact on the pollutant levels in Kunming. [ABSTRACT FROM AUTHOR]

It is known that air pollution is harmful to creatures, though until now most of the human thermal comfort indices that existed were calculated only with meteorological conditions. Therefore, a new index - meteorology and environment comfort (MEC) - was given out in this paper that considers both meteorology and air pollution conditions and presents the comprehensive and synergistic effects of meteorological and air pollution. The meteorology and air pollution data were used to establish the influence function of the five air pollutants (PM 2.5 , PM 10 , O 3 , NO 2 , and SO 2 ) according to Fechner's law; then, we calculated the somatosensory temperature (ST, a class of human thermal comfort indices) and MEC values of five typical cities (Beijing, Xining, Nanjing, Kunming, and Guangzhou). The results showed average improvements of five cities on MEC as a new comprehensive human comfort index to new ST. In spring, the MEC comfort proportion fell by 29.25%. Besides, the extreme heat discomfort ratio in Nanjing and Kunming has increased over 20%. In summer, the comfort proportion fell 12.54%; the extreme heat discomfort proportion of Beijing increased 37.86% and Kunming increased 24.09%. Air pollution significantly raised discomfort stress in Beijing. In fall, the comfort proportion fell by 20.87%; and the extreme heat discomfort of Nanjing increased 23.67% caused by poor air quality. About winter, the comfort ratio decreased 12.72%, and the cold discomfort proportion of Nanjing increased 30.30%, signifying awful air quality in winter. Air pollution levels significantly affect the comfort levels in all seasons, which is more evident with good weather patterns. MEC can offer early warnings of extreme weather events and provide a basis for the better prevention and control of air pollution to protect human health basing on the predictions of meteorological and environmental impact factors., (Copyright © 2020 Elsevier Inc. All rights reserved.)