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 there is a growing need to apply geospatial artificial intelligence analysis to disparate environmental datasets to find solutions that benefit frontline communities. This research addresses these challenges by leveraging a strategically deployed, extensive low-cost sensor (LCS) network that was rigorously calibrated through an optimized neural network.

Article describes how forests are generally extracted from remotely sensed images based on the spectral features, ignoring other important auxiliary information, and the techniques of precise extraction need to be further improved. By using the Sentinel–2 image and auxiliary factors (AFs) including site conditions (SCs) and vegetation indices (VIs), the random forest model with AFs (RF–AFs) was adopted for the extraction of the economic forests in Lancang County, which is a mountainous area with rich biodiversity and is witnessing rapid development of economic forests in Yunnan province of China.

Article describes study which assesses the relative accuracy of volunteer water quality data collected by the Texas Stream Team (TST) citizen science program from 1992–2016 across the State of Texas by comparing it to professional data from corresponding stations during the same time period.

Article describes how environmental air pollution remains a major contributor to negative health outcomes and mortality, but the relationship between socially vulnerable populations and air pollution is not well understood. This paper seeks to understand how air pollution monitor placement strategies and policy may neglect social vulnerabilities and therefore potentially underestimate exposure burdens in vulnerable populations.

Article describes how forests are generally extracted from remotely sensed images based on the spectral features, ignoring other important auxiliary information, and the techniques of precise extraction need to be further improved. By using the Sentinel–2 image and auxiliary factors (AFs) including site conditions (SCs) and vegetation indices (VIs), the random forest model with AFs (RF–AFs) was adopted for the extraction of the economic forests in Lancang County.

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 airborne hyperspectral data has high spectral-spatial information, but mining and using this information effectively is still a great challenge. Therefore, a 3D-1D-CNN model was proposed for feature extraction in complex urban with hyperspectral images affected by cloud shadows.

Study examines factors that affect power corridor classification using LiDAR (light detection and ranging) point clouds, including the class distribution, feature selection, classifier type and neighborhood radius for classification feature extraction.

Authors of the article state that airborne particulate matter (PM) can accumulate on feather surfaces and alter feather appearance, so they quantified PM accumulation on Rock Pigeon feathers and analyzed the spectral properties of extracted particulates. Their findings suggest that wild birds could incur an urban pollution penalty as PM accumulation has the potential to alter feather properties.

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.

Article describes how soil moisture (SM) and atmospheric humidity (AH) are crucial climatic variables that significantly affect the climate system. However, the combined influencing mechanisms of SM and AH on the land surface temperature (LST) under global warming are still unclear. The authors systematically analyzed the interrelationships among annual mean values of SM, AH, and LST using ERA5-Land reanalysis data and revealed the role of SM and AH on the spatiotemporal variations of LST through mechanism analysis and regression methods.

Article describes how the COVID-19 pandemic has caused unprecedented losses for small businesses in cities across the globe. The authors' study examines the spatial distribution of PPP loans at the neighborhood level.

Authors of the article declare that, with growing health risks from climate change and a trend of increasing carbon emissions from coal, it is time for China to take action. The 2023 China report of the Lancet countdown continues to track progress on health and climate change in China, while now also attributing the health risks of climate change to human activities and providing examples of feasible and effective climate solutions.