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.

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.

Data management plan for the grant, "DISES: Integrating environmental justice into urban forest assessment and valuation tools: blueprint for the future."

Article asserts that individual tree structure mapping in cities is important for urban environmental studies. The authors produced an individual tree dataset including tree locations, height, crown area, crown volume, and biomass over the entire New York City, USA for 6,005,690 trees, which enables the evaluation of urban forest ecosystem services.

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 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 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.

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 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.

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.