A lightweight network for detecting and monitoring wildfire cores using UAV thermal imagery DOI
Linfeng Wang, Oualid Doukhi,

Dong Soo Kang

et al.

Published: Oct. 29, 2024

Language: Английский

Simulated fire observables as indicators for optimizing wireless sensor networks in wildfire risk monitoring DOI
Juan Luis Gómez-González,

Effie Marcoulaki,

Alexis Cantizano

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 175, P. 113509 - 113509

Published: May 17, 2025

Language: Английский

Citations

0
Wildfires and Human Health DOI
Raj P. Fadadu,

Gina Solomon,

John R. Balmes

et al.

JAMA, Journal Year: 2024, Volume and Issue: 332(12), P. 1011 - 1011

Published: July 10, 2024

This JAMA Insights explores the adverse effects of wildfires on human health and care systems offers suggestions how clinicians can help mitigate threats posed by wildfires.

Language: Английский

Citations

3
Evaluating estimation methods for wildfire smoke and their implications for assessing health effects DOI Creative Commons
Minghao Qiu, Makoto Kelp, Sam Heft-Neal

et al.

EarthArXiv (California Digital Library), Journal Year: 2024, Volume and Issue: unknown

Published: June 13, 2024

Growing wildfire smoke represents a substantial threat to air quality and human health in the US across much of globe. However, impact on remains imprecisely understood, due uncertainties both measurement population exposure dose-response functions linking health. Here, we compare daily smoke-related surface fine particulate matter (PM2.5) concentrations estimated using three approaches, including two chemical transport models (CTMs): GEOS-Chem Community Multiscale Air Quality (CMAQ), one machine learning (ML) model over contiguous 2020, historically active fire year. We study consequences these different approaches for estimating PM2.5 effects mortality. In western US, compared against measurements from Environmental Protection Agency (EPA) PurpleAir sensors, find that CTMs overestimate during extreme episodes by up 3-5 fold, while ML estimates are largely consistent with measurements. eastern where levels were lower show modestly better agreement develop calibration framework integrates CTM- ML-based yields outperform each individual approach. When combining county-level mortality rates, low-level but large discrepancies high-level methods. Our research highlights benefits costs estimation methods understanding impacts smoke, demonstrates importance bench-marking available

Language: Английский

Citations

2
A Novel Flexible Geographically Weighted Neural Network for High-Precision PM2.5 Mapping across the Contiguous United States DOI Creative Commons
Dongchao Wang, Jianfei Cao, Baolei Zhang

et al.

ISPRS International Journal of Geo-Information, Journal Year: 2024, Volume and Issue: 13(7), P. 217 - 217

Published: June 22, 2024

Air quality degradation has triggered a large-scale public health crisis globally. Existing machine learning techniques have been used to attempt the remote sensing estimates of PM2.5. However, many models ignore spatial non-stationarity predictive variables. To address this issue, study introduces Flexible Geographically Weighted Neural Network (FGWNN) estimate PM2.5 based on multi-source data. FGWNN incorporates Geographical Neuron (FGN) and Activation Function (GWAF) within framework Artificial (ANN) capture intricate non-stationary relationships among A robust air estimation model was constructed using data Aerosol Optical Depth (AOD), Normalized Difference Vegetation Index (NDVI), Temperature (TMP), Specific Humidity (SPFH), Wind Speed (WIND), Terrain Elevation (HGT) as inputs, Ground-Based observation. The results indicated that successfully generates with 2.5 km resolution for contiguous United States (CONUS) in 2022. It exhibits higher regression accuracy compared traditional ANN Regression (GWR) models. holds potential applications high-precision high-resolution scenarios.

Language: Английский

Citations

2
Prescribed burn related increases of population exposure to PM2.5 and O3 pollution in the southeastern US over 2013–2020 DOI Creative Commons
Kamal Jyoti Maji, Zongrun Li, Yongtao Hu

et al.

Environment International, Journal Year: 2024, Volume and Issue: 193, P. 109101 - 109101

Published: Oct. 28, 2024

Language: Английский

Citations

1
Evaluating Chemical Transport and Machine Learning Models for Wildfire Smoke PM2.5: Implications for Assessment of Health Impacts DOI
Minghao Qiu, Makoto Kelp, Sam Heft-Neal

et al.

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 18, 2024

Growing wildfire smoke represents a substantial threat to air quality and human health. However, the impact of on health remains imprecisely understood due uncertainties in both measurement exposure population dose-response functions linking Here, we compare daily smoke-related surface fine particulate matter (PM

Language: Английский

Citations

1
The Impact of Wildfire Smoke Exposure on Excess Mortality and Later-Life Socioeconomic Outcomes: The Great Fire of 1910 DOI
Sarah Meier,

Eric Strobl,

Robert Elliott

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Seasonal persistence of the nitrogen oxides production in Mexico City DOI Creative Commons

S. Matias-Gutierres,

Edgar Israel García Otamendi, Hugo David Sánchez Chávez

et al.

International Journal of Environmental Science and Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 8, 2024

Abstract This study investigates the seasonal influence on nitrogen oxide NO x pollution records at four monitoring sites in Mexico City from 2010 to 2018. The analysis employs second-order structure function examine trends concentration fluctuations. findings reveal that fluctuations follow a power law pattern characterized by Hurst exponents, predominantly statistical persistence regime, with scaling range spanning three orders of magnitude. Specifically, autumn period exhibits an exponent $$\overline{H}=0.72$$ H ¯ = 0.72 , indicating relatively smaller compared other seasons, but potential for concentrations surpass those periods. In contrast, spring, summer, and winter, are exponents $$\overline{H}=0.59$$ 0.59 $$\overline{H}=0.61$$ 0.61 $$\overline{H}=0.62$$ 0.62 respectively, demonstrating greater lower autumn. These results consistent various studies conducted worldwide. Additionally, negative correlation between ozone ( O 3 ) has been established during winter season, as display persistent anti-persistent behavior, respectively.

Language: Английский

Citations

0
Drivers of environmental externality reduction in China's electric power industry: A spatial-temporal analysis DOI
Jiqiang Wang, Ya Wang, Shaohui Zhang

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123612 - 123612

Published: Dec. 5, 2024

Language: Английский

Citations

0
A lightweight network for detecting and monitoring wildfire cores using UAV thermal imagery DOI
Linfeng Wang, Oualid Doukhi,

Dong Soo Kang

et al.

Published: Oct. 29, 2024

Language: Английский

Citations

0