Impact Mechanism and Improvement Strategy on Urban Ventilation, Urban Heat Island and Urban Pollution Island: A Case Study in Xiangyang, China

There has been a growing interest in finding mitigation measures for urban heat islands and urban pollution islands that focus mainly on urban landscape mechanisms. However, relatively little research has considered spatial non-stationarity and temporal non-stationarity, which are both intrinsic properties of the environmental system, simultaneously. At the same time, the relevance of and differences between the thermal environment and air pollution has also been rarely discussed, and both issues are of great importance to urban planning. In this study, which is aimed at improving urban ventilation to reduce the urban heat island and urban pollution island effects, an urban ventilation potential evaluation, land surface temperature time-series clustering and air pollution source identification are comprehensively applied to identify the operational areas, compensation areas and ventilation corridors in Xiangyang, China, thus bridging the gap between academic research and urban planning. The specific research areas include: (1) defining the operational areas for urban ventilation corridor planning through an urban ventilation potential evaluation featuring urban morphology indicators, land surface temperature time-series clustering with k-means and an urban air pollution source diffusion analysis via the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and geographically weighted regression (GWR) methods; (2) identifying urban cold islands through land surface temperatures and delimiting the compensation areas in urban ventilation corridor planning; (3) designating urban ventilation corridors through an urban ventilation potential evaluation and computational fluid dynamics (CFD); and (4) improving urban ventilation corridor planning through defining operational areas, compensation areas and ventilation corridors as well as proposing corresponding control measures

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties