Related Experiment Video
Updated: Jun 18, 2025

Real-time Breath Analysis by Using Secondary Nanoelectrospray Ionization Coupled to High Resolution Mass Spectrometry
Published on: March 9, 2018
Spatial and temporal changes of air quality in Shandong Province from 2016 to 2022 and model prediction
Xu Zhang1, Xinrui Zhang2, Huanhuan Yang3
1School of Municipal and Environmental Engineering, Shandong Jianzhu University, Jinan 250101, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Abstract:
This study investigates the spatial and temporal dynamics of air quality in Shandong Province from 2016 to 2022. The Air Quality Index (AQI) showed a seasonal pattern, with higher values in winter due to temperature inversions and heating emissions, and lower values in summer aided by favorable dispersion conditions. The AQI improved significantly, decreasing by approximately 39.4 % from 6.44 to 3.90. Coastal cities exhibited better air quality than inland areas, influenced by industrial activities and geographical features. For instance, Zibo's geography restricts pollutant dispersion, resulting in poor air quality. CO levels remained stable, while O3 increased seasonally due to photochemical reactions in summer, with correlation coefficients indicating a strong positive correlation with temperature (r = 0.65). Winter saw elevated NO2 levels linked to heating and vehicular emissions, with an observed increase in correlation with AQI (r = 0.78). PM2.5 and PM10 concentrations were higher in colder months due to heating and atmospheric dust, showing a significant decrease of 45 % and 40 %, respectively, over the study period. Predictive modeling forecasts continued air quality improvements, contingent on sustained policy enforcement and technological advancements. This approach provides a comprehensive framework for future air quality management and improvement.
Related Concept Videos
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
What is Climate?
Steps in Outbreak Investigation

