Article asserts that urban tree canopies are a significant sink for atmospheric elemental carbon (EC)--and air pollutant that is a powerful climate-forcing agent and threat to human health. The authors' findings indicate that complex configurations of roads, buildings, and vegetation produce “urban edge trees” that contribute to heterogeneous EC deposition patterns across urban systems, with implications for greenspace planning.

Article describes how the soil moisture daily diagnostic equation (SMDE) evaluates the relationship between the loss function coefficient and the summation of the weighted average of precipitation. The study has confirmed that using actual solar radiation data in the soil moisture daily diagnostic equation can improve its accuracy.

Article describes how the low-cost sensor has changed the air quality monitoring paradigm with the capacity for efficient network expansion and community engagement. This study comprehensively assessed ten widely used data techniques, namely AdaBoost, Bayesian ridge, gradient tree boosting, K-nearest neighbors, Lasso, multivariable linear regression, neural network, random forest, ridge regression, and support vector machine.

Article discusses how China implemented the first phase of its National Healthy Cities pilot program from 2016-20. Authors recommend aligning the Healthy Cities initiative in China with strategic national and global level agendas such as Healthy China 2030 and the Sustainable Development Goals (SDGs) by providing an integrative governance framework to facilitate a coherent intersectoral program to systemically improve population health.

Article describes the efficient and accurate identification of canopy gaps is the basis of forest ecosystem research, which is of great significance to further forest monitoring and management. One major limitation of the traditional methods of remote sensing to map canopy gaps is that they cannot finely extract the complex edges of canopy gaps in mountainous areas. The authors proposed an object-oriented classification method that integrates multi-source information.