学会抄録

<p><b>Observation of pulmonary artery sections</b> (200X, HE) The pulmonary artery wall thickness of disease (D) is noticeably increased. In the D sample, 1) the tunica adventicia was more compact and exhibited increased connective tissue; 2) the smooth muscle fiber was thicker; 3) there was excessive fiber production; and 4) the intima was more compact. The arrows indicate the pathological changes.</p

Spatial distribution of average values of parameters (a) CentralHeat (b) AOD*diff (c) R_AOD*diff from 2004–2012.

<p>The blue line along the Qin Mountains and Huai River is the traditional dividing line between north and south China.</p

Spatial distribution of average AOD*annual from 2004–2012.

<p>The blue line along the Qin Mountains and Huai River is the traditional dividing line between north and south China. AOD^*_annual varied greatly across the study domain and north China has higher aerosol loading relative to south China generally.</p

Global daily PM2.5 related to 2023 wildfires

Global daily PM2.5 related to 2023 wildfires</p

Source data from Global PM_2.5 exposure and health impacts from 2023 Canadian wildfires

Source data from Global PM2.5 exposure and health impacts from 2023 Canadian wildfires</p

Summary statistics of meteorological and social-economic parameters.

<p>Summary statistics of meteorological and social-economic parameters.</p

Estimates of parameters in the linear regression models.

<p>^ap-value< 0.01</p><p>Estimates of parameters in the linear regression models.</p

Average AOD^* in different spatio-temporal groups.

<p>The black line shows the AOD^*_annual over the entire study region as a reference. The average AOD^* during the heating season in the heating area was consistently higher than other spatio-temporal groups.</p

Tracking Daily Concentrations of PM_2.5 Chemical Composition in China since 2000

PM2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China’s PM2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting–Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM2.5 data. PM2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of −9.0, −7.2, −8.1, −8.4, and −9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM2.5 components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China