The picture is from the poster of the movie “Fury Road”. In the movie, desertification symbolizes the extreme deterioration of the environment and the severe scarcity of resources, with human civilization having vanished completely. Although the movie presents an extreme scenario, in reality, extreme weather events occur frequently in the world now and affect human health. Extreme weather on Earth deserves our profound reflection.
Sand and dust storms (SDS) are extreme weather events that are closely associated with air pollution and the health effects of particulate matter (PM). The World Health Organization has proposed comprehensive global air quality guidelines aimed at mitigating the health hazards associated with SDS. However, there remains a notable lack of comprehensive understanding for conducting both quantitative and qualitative assessments of the health risks posed by SDS. Exploring the health effects of SDS-related pollutants can provide evidence to formulate uniform air quality guidelines and facilitate the achievement of sustainable development goals. This study aimed to understand how oxidative potential (OP) and environmentally persistent free radicals (EPFRs) in dust particles affect human health, which are two critical PM metrics that induce oxidation stress. In the spring of 2021, the China Meteorological Administration announced that a severe sandstorm was imminent in China. We promptly initiated synchronous PM sampling across nine cities, a task that persisted for three years during the SDS events that occurred in China from 2021 to 2023. Collaborative teamwork has played a pivotal role in not only the successful collection of samples but also the subsequent publication of our research findings.
A total of 190 dust particle samples were gathered and subjected to testing for the occurrence of OP and EPFRs associated with the dust storm particles. We conducted an analysis of the spatial distribution and health risks associated with OP and EPFRs in dust particles, leveraging a multidisciplinary approach that intersects analytical chemistry, machine learning, big data analysis, and epidemiological modeling. Utilizing a comprehensive database of measured concentrations of OP and EPFRs, coupled with readily available air quality data and meteorological parameters, we established machine learning models for predicting OP and EPFR concentrations. These models enabled us to map the spatial distribution of OP and EPFR across China during SDS events. The OP and EPFRs regional distributions exhibited a diffusion pattern radiating inland from the northern and southwest boundaries. We integrated exposure–response model and estimated the association between OP and EPFRs and hospitalization during SDS events. The OP and EPFRs were more sensitive than PM for disease risk assessments. Short-term exposure to OP and EPFRs had significant adverse effects, especially on heart disease and hypertension-related disease. The OP and EPFRs can create an all-cause hospitalization health burden during SDS periods. Our results show that these two factors are crucial for evaluating SDS health risks and the spatial characteristics of health burdens, which could be used to develop effective sand and dust risk prevention measures in dust-prone countries. We hope that by increasing awareness of the health risks associated with SDS, we can contribute to improved public health outcomes and ultimately avoid going down the path of the “Fury Road”.