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Two-way coupled meteorology and air quality models, which account for aerosol–radiation–cloud interactions, have been employed to simulate meteorology and air quality more realistically. Although numerous related studies have been conducted, none have compared the performances of multiple two-way coupled models in simulating meteorology and air quality over eastern China. Thus, we systematically evaluated annual and seasonal meteorological and air quality variables simulated by three open-source, widely utilized two-way coupled models (Weather Research and Forecasting (WRF)–Community Multiscale Air Quality (WRF–CMAQ), WRF coupled with chemistry (WRF–Chem), and WRF coupled with a regional chemistry-transport model named CHIMERE (WRF–CHIMERE)) by validating their results with surface and satellite observations for eastern China in 2017. Although we have made every effort to evaluate these three coupled models by using configurations that are as consistent as possible, there are still unavoidable differences between them in their treatments of physical and chemical processes. Our thorough evaluations revealed that all three two-way coupled models captured the annual and seasonal spatiotemporal characteristics of meteorology and air quality reasonably well. Notably, the role of the aerosol–cloud interaction (ACI) in improving the models' performances was limited compared to that of the aerosol–radiation interaction (ARI). The sources of uncertainties and bias in the different ACI schemes in the two-way coupled models were identified. With sufficient computational resources, these models can provide more accurate air quality forecasting to support atmospheric environment management and deliver timely warnings of heavy air pollution events. Finally, we propose potential improvements to two-way coupled models for future research. [ABSTRACT FROM AUTHOR]

Open-field crop residue burning (OCRB) is a widespread agricultural practice with significant impacts on regional environments and public health. The effective management of OCRB remains a challenging task that requires timely access to various forms of monitored and forecasted information. Addressing this worldwide need, an open-source platform named AgriFireInfo v1.0, which is specifically tailored to monitoring and regulating regional OCRB activities, was developed. This technical note thoroughly illustrates the platform's architecture, major modules, and visualization processes. Through AgriFireInfo v1.0, government agencies can access timely information about the spatial distribution of fire spots and emissions as well as meteorological conditions and air quality status. AgriFireInfo v1.0 also introduces an innovative Prevention Alarming Index, designed to identify regions prone to OCRB and promote comprehensive crop residue utilization. Furthermore, it offers the burning window and crop residue yields for controlled OCRB activities and can be used to analyze shifts in farmers' burning behaviors and intensities. Future enhancements will focus on supplying holistic information on the burning windows and burning amounts of crop residues to further facilitate refined controlled burning activities and optimize decision-making processes. The flexibility and scalability of this platform can potentially allow users to easily customize and apply it to other regions or countries. [ABSTRACT FROM AUTHOR]

The ISAT (Inventory Spatial Allocation Tool) v2.0 is an integrated tool that has been developed to configure nested domains, downscale regional emission inventories, allocate local emission inventories, and generate model-ready emission inventories for the Weather Research and Forecasting (WRF)–Air Quality Numerical Model (AQM). The tool consists of four modules, namely "Prepgrid", "Downscale", "Mapinv", and "Prepmodel", which are designed to perform specific tasks. The Prepgrid module utilizes a nested-domain configuration algorithm based on WRF-AQM nested rules and the target domain shapefile. The Downscale module establishes a "sub-grid nearest" method to downscale the regional emission inventory based on spatial surrogate, thereby improving the accuracy and computational efficiency of the process. The Mapinv module allocates a user-defined regional- and/or city-level emission inventory to grid level based on the target domain shapefile and the spatial surrogate. Finally, the Prepmodel module generates the model-ready inventories by introducing unique user-friendly emission sector IDs using abbreviations and speciation profiles based on species in the emission inventory and chemical mechanisms, which is available for both the CMAQ and CAMx models. The ISAT v2.0 tool provides a user-friendly solution for model users to configure and run WRF-AQM. And it provides a framework and related algorithms for researchers to develop similar tools for WRF-AQM. [ABSTRACT FROM AUTHOR]

Introduction: Critically ill patients are at a heightened risk for post-traumatic stress disorder (PTSD). While the intensive care unit (ICU) diary has been shown to improve the mental health and quality of life of ICU patients, the handwritten version still has some limitations such as a lack of support for multimedia content and writing by remote family members, as well as being time-consuming and labour-intensive. We hypothesise that constructing an ICU electronic diary platform based on a co-design approach and verifying its applicability could alleviate these limitations, making the ICU diary more convenient for users., Methods and Analysis: This sequential exploratory mixed-methods study will consist of four consecutive phases: understanding the ICU diary research content and implementation, developing an ICU electronic diary platform after conducting qualitative interviews with stakeholders, verifying the applicability of the platform and verifying its effectiveness., Ethics and Dissemination: Ethics approval was obtained from the Biomedical Research Ethics Committee of the Affiliated Hospital of Zunyi Medical University (approval number: KLL-2023-602). The results of this study will be distributed through peer-reviewed journals., Trial Registration Number: Chinese Clinical Trial Register (ChiCTR2400079903)., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)