用可穿戴数据预测黄包车夫在极端高温下的生存风险
Forecasting Occupational Survivability of Rickshaw Pullers in a Changing Climate with Wearable Data
- 构建贝叶斯模型，结合天气、活动和人口特征预测生理指标
- 32%当前面临高热暴露风险，2026-2030年或升至37%
- 融合实地访谈与气候预测，揭示底层劳动者气候脆弱性
黄包车夫极易受极端高温影响，但其生理反应尚不明确。本研究通过可穿戴传感器，在孟加拉国达卡采集了100名黄包车夫的实时气象与生理数据，并对12名车夫进行访谈，了解其对气候变化的认知与体验。我们构建了线性高斯贝叶斯网络（LGBN）回归模型，基于活动、天气和人口特征预测关键生理指标。模型在皮肤温度、相对心率成本、皮肤电反应和皮肤电水平上的归一化平均绝对误差分别为0.82、0.47、0.65和0.67。结合18个CMIP6气候模型的预测，将LGBN应用于未来气候情景，分析2023–2025年及2026–2100年的生存能力。基于湿球黑球温度（WBGT）超过31.1°C、皮肤温度超过35°C的阈值，当前已有32%的黄包车夫面临高热暴露风险。到2026–2030年，该比例可能上升至37%，平均暴露时间近12分钟，约占全程的三分之二。访谈的定性分析进一步表明，黄包车夫已意识到自身气候脆弱性，并担忧其对健康与职业生存的影响。
原文摘要 · Abstract (English)
Cycle rickshaw pullers are highly vulnerable to extreme heat, yet little is known about how their physiological biomarkers respond under such conditions. This study collected real-time weather and physiological data using wearable sensors from 100 rickshaw pullers in Dhaka, Bangladesh. In addition, interviews with 12 pullers explored their knowledge, perceptions, and experiences related to climate change. We developed a Linear Gaussian Bayesian Network (LGBN) regression model to predict key physiological biomarkers based on activity, weather, and demographic features. The model achieved normalized mean absolute error values of 0.82, 0.47, 0.65, and 0.67 for skin temperature, relative cardiac cost, skin conductance response, and skin conductance level, respectively. Using projections from 18 CMIP6 climate models, we layered the LGBN on future climate forecasts to analyze survivability for current (2023-2025) and future years (2026-2100). Based on thresholds of WBGT above 31.1°C and skin temperature above 35°C, 32% of rickshaw pullers already face high heat exposure risk. By 2026-2030, this percentage may rise to 37% with average exposure lasting nearly 12 minutes, or about two-thirds of the trip duration. A thematic analysis of interviews complements these findings, showing that rickshaw pullers recognize their increasing climate vulnerability and express concern about its effects on health and occupational survivability.
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