Unmasking air quality: A novel image-based approach to align public perception with pollution levels.

In the quest to reconcile public perception of air pollution with scientific measurements, our study introduced a pioneering method involving a gradient boost-regression tree model integrating PM2.5 concentration, visibility, and image-based data. Traditional stationary monitoring often falls short of accurately capturing public air quality perceptions, prompting the need for alternative strategies. Leveraging an extensive dataset of over 20,000 public visibility perception evaluations and over 8,000 stationary images, our models effectively quantify diverse air quality perceptions. The predictive prowess of our models was validated by strong performance metrics for perceived visibility (R = 0.98, RMSE = 0.19), all-day PM2.5 concentrations (R: 0.77-0.78, RMSE: 8.31-9.40), and Central Weather Bureau visibility records (R = 0.82, RMSE = 9.00). Interestingly, image contrast and light intensity hold greater importance than scenery clarity in the visibility perception model. However, clarity is prioritized in PM2.5 and Central Weather Bureau models. Our research also unveiled spatial limitations in stationary monitoring and outlined the variations in predictive image features between near and far stations. Crucially, all models benefit from the characterization of atmospheric light sources through defogging techniques. The image-based insights highlight the disparity between public perception of air pollution and current policy implementation. In other words, policymakers should shift from solely emphasizing the reduction of PM2.5 levels to also incorporating the public's perception of visibility into their strategies. Our findings have broad implications for air quality evaluation, image mining in specific areas, and formulating air quality management strategies that account for public perception.

UV-filter octyl methoxycinnamate causes reproductive toxicity associated with germline apoptosis and vitellogenin decrease in Caenorhabditis elegans.

Octyl methoxycinnamate (OMC) is a common UV filter found in personal care products such as sunscreen and cosmetics. However, OMC's presence in wastewater has raised concerns that it could potentially pollute aquatic ecosystems because of its limited biodegradability and its estrogenic disrupting properties. In this study, we investigated the environmental toxicity of OMC and its potential biomarkers using the nematode Caenorhabditis elegans. Our results showed that body length, eggs in utero, and total brood size decreased with increasing dose (experimental concentrations = 0, 1, 5, 10, 100, 500 µM for body length and eggs in utero, and 0, 5, 10 µM for total brood size) in C. elegans after L1 larval stage (the first larval stage for 0 - 12 hours post-hatching) larval stage exposure to OMC. The minimum effective concentrations were 1, 5, and 10 µM, respectively. Modeling results demonstrated that the threshold concentration of OMC inducing 10% inhibited eggs in utero was 0.33 µM (95.11 µg/L). Furthermore, germline apoptosis was induced in 10 µM OMC-treated worms (experimental concentrations = 0, 5, 10 µM). Decreased mRNA levels of vitellogenin-related genes (vit-2 and vit-6) and increased mRNA levels of apoptosis-related genes (egl-1 and ced-3) were observed in 10 µM OMC-treated C. elegans (experimental concentrations = 0, 10 µM), suggesting that reproductive toxicity was associated with decreased vitellogenin levels and germline apoptosis. In summary, our study shows that OMC is reproductively toxic and leads to reduced egg formation and decreased brood size in C. elegans by reducing vitellogenin levels and promoting germline apoptosis.