Monterrey-LCS-PM2.5: A Dataset for Hybrid Calibration and Spatial Transferability Analysis

This dataset contains high-frequency atmospheric monitoring data collected over 18 months (January 2023 – July 2024) in the Monterrey Metropolitan Area (MMA), Mexico. The data was generated to evaluate the resilience, aging, and spatial transferability of low-cost sensor (LCS) networks under extreme semi-arid conditions. The dataset includes collocated measurements from three Plantower PMSA003 sensors and federal-grade reference instruments (Beta-ray Attenuation Monitor - BAM) across four strategic urban sites. This data supports the research presented in the manuscript: "A Scalable and Resilient Hybrid XGB-L Framework for Long-term Urban $PM_{2.5}$ Monitoring: Enhancing Data Integrity across Complex Physicochemical Gradients.

本数据集涵盖2023年1月至2024年7月共18个月期间，于墨西哥蒙特雷大都会区（Monterrey Metropolitan Area, MMA）采集的高频大气监测数据。本数据集旨在评估极端半干旱环境下低成本传感器（low-cost sensor, LCS）网络的鲁棒性、老化特性与空间迁移能力。数据集包含四个战略城市监测点位的同步共址观测数据，涉及三台Plantower PMSA003传感器与联邦级标准参考仪器——β射线衰减监测仪（Beta-ray Attenuation Monitor, BAM）。本数据集支撑了下述手稿刊载的研究工作：《面向长期城市细颗粒物（PM₂.₅）监测的可扩展鲁棒混合XGB-L框架：强化复杂理化梯度下的数据完整性》。