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From 2013 to 2019, a series of air pollution control actions significantly reduced PM pollution in China. Control actions included changes in activity levels, structural adjustment (SA) policy, energy and material saving (EMS) policy, and end-of-pipe (EOP) control in several sources, which have not been systematically studied in previous studies. Here, we integrate an emission inventory, a chemical transport model, a health impact assessment model, and a scenario analysis to quantify the contribution of each control action across a range of major emission sources to the changes in PM concentrations and associated mortality in China from 2013 to 2019. Assuming equal toxicity of PM from all the sources, we estimate that PM-related mortality decreased from 2.52 (95 % confidence interval, 2.13-2.88) to 1.94 (1.62-2.24) million deaths. Anthropogenic emission reductions and declining baseline incidence rates significantly contributed to health benefits, but population aging partially offset their impact. Among the major sources, controls on power plants and industrial boilers were responsible for the highest reduction in PM-related mortality (∼80 %), followed by industrial processes (∼40 %), residential combustion (∼40 %), and transportation (∼30 %). However, considering the potentially higher relative risks of power plant PM, the adverse effects avoided by their control could be ∼2.4 times the current estimation. Our power plant sensitivity analyses indicate that future estimates of source-specific PM health effects should incorporate variations in individual source PM effect coefficients when available. As for the control actions, while activity levels increased for most sources, SA policy significantly reduced the emissions in residential combustion and industrial boilers, and EOP control dominated the contribution in health benefits in most sources except residential combustion. Considering the emission reduction potential by source and control actions in 2019, our results suggest that promoting clean energy in residential combustion and enforcing more stringent EOP control in the iron and steel industry should be prioritized in the future.
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http://dx.doi.org/10.1016/j.envint.2024.108470 | DOI Listing |
JCO Glob Oncol
May 2025
Department of Obstetrics and Gynaecology, Stanford University School of Medicine, Stanford, CA.
Purpose: Expanding high-risk human papillomavirus (HPV) vaccine coverage in resource-constrained settings is critical to bridging the cervical cancer gap and achieving the global action plan for elimination. Mobile health (mHealth) technology via short message services (SMS) has the potential to improve HPV vaccination uptake. The mHealth-HPVac study evaluated the effectiveness of mHealth interventions in increasing HPV vaccine uptake among mothers of unvaccinated girls aged 9-14 years in Lagos, Nigeria.
View Article and Find Full Text PDFJ Agric Food Chem
September 2025
College of Forestry, East China Woody Fragrance and Flavor Engineering Research Center of National Forestry and Grassland Administration; Jiangxi Provincial Key Laboratory of Improved Variety Breeding and Efficient Utilization of Native Tree Species, Jiangxi Agricultural University, Nanchang 330045,
To discover novel preservatives for treating wood-decaying fungi, 48 novel eugenol quaternary ammonium salt derivatives were designed and synthesized. Among them, compounds , , , , , , and showed remarkable antifungal activity against (), affording EC values ranging from 2.11-7.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
September 2025
In essence, reinforcement learning (RL) solves optimal control problem (OCP) by employing a neural network (NN) to fit the optimal policy from state to action. The accuracy of policy approximation is often very low in complex control tasks, leading to unsatisfactory control performance compared with online optimal controllers. A primary reason is that the landscape of value function is always not only rugged in most areas but also flat on the bottom, which damages the convergence to the minimum point.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Max Planck Institute for Solar System Research, Göttingen 37077, Germany.
Turbulent convection governs heat transport in both natural and industrial settings, yet optimizing it under extreme conditions remains a significant challenge. Traditional control strategies, such as predefined temperature modulation, struggle to achieve substantial enhancement. Here, we introduce a deep reinforcement learning (DRL) framework that autonomously discovers optimal control policies to maximize heat transfer in turbulent Rayleigh-Bénard convection.
View Article and Find Full Text PDFJ Neurooncol
September 2025
Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Purpose: Glioblastoma (GBM) remains one of the most aggressive primary brain tumors with poor survival outcomes and a lack of approved therapies. A promising novel approach for GBM is the application of photodynamic therapy (PDT), a localized, light-activated treatment using tumor-selective photosensitizers. This narrative review describes the mechanisms, delivery systems, photosensitizers, and available evidence regarding the potential of PDT as a novel therapeutic approach for GBM.
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