Utilizing LightGBM to Explore the Characterization of PM2.5 Emission Patterns from Broadleaf Tree Combustion in Northeastern China DOI Open Access

Bingbing Lu,

Hui Huang, Zhiyuan Wu

et al.

Forests, Journal Year: 2025, Volume and Issue: 16(5), P. 836 - 836

Published: May 18, 2025

PM2.5 emissions significantly impact atmospheric environments and human health in the context of forest fires. However, research on from fires remains insufficient. This study systematically investigated emission characteristics broadleaf tree combustion through controlled experiments examining three key factors: species variation (Acer tegmentosum [AT], Acer ukurunduense [AU], pictum [AP], Tilia amurensis [TA], Phellodendron amurense [PA], Ulmus davidiana [UD], laciniata [UL], Prunus padus [PP], maackii [PM]), moisture content (0%–20%), phenological stages (budding [A], growing [B], defoliation [C]). The results demonstrated: (1) Significant interspecies differences, with UL showing lowest, PM highest emissions; (2) A unimodal moisture—emission relationship peaking at 15% across most species, while AT, exhibited unique linear responses; (3) Distinct patterns, including triphasic fluctuations during phases. LightGBM model effectively predicted (R2 = 0.97), identifying (36.2% importance) (21.6%) as dominant factors. These findings provide critical data for wildfire modeling highlight need species-specific parameters air quality forecasts.

Language: Английский

Enhancing plant growth, polyphenols accumulation, and bioactivity of Mentha rotundifolia L. by dual application of exogenous indole acetic acid and adenine-like cytokinin DOI

Hadjer Kecis,

Fatiha Mekircha,

Lynda Gali

et al.

Process Biochemistry, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

Citations

0
Utilizing LightGBM to Explore the Characterization of PM2.5 Emission Patterns from Broadleaf Tree Combustion in Northeastern China DOI Open Access

Bingbing Lu,

Hui Huang, Zhiyuan Wu

et al.

Forests, Journal Year: 2025, Volume and Issue: 16(5), P. 836 - 836

Published: May 18, 2025

PM2.5 emissions significantly impact atmospheric environments and human health in the context of forest fires. However, research on from fires remains insufficient. This study systematically investigated emission characteristics broadleaf tree combustion through controlled experiments examining three key factors: species variation (Acer tegmentosum [AT], Acer ukurunduense [AU], pictum [AP], Tilia amurensis [TA], Phellodendron amurense [PA], Ulmus davidiana [UD], laciniata [UL], Prunus padus [PP], maackii [PM]), moisture content (0%–20%), phenological stages (budding [A], growing [B], defoliation [C]). The results demonstrated: (1) Significant interspecies differences, with UL showing lowest, PM highest emissions; (2) A unimodal moisture—emission relationship peaking at 15% across most species, while AT, exhibited unique linear responses; (3) Distinct patterns, including triphasic fluctuations during phases. LightGBM model effectively predicted (R2 = 0.97), identifying (36.2% importance) (21.6%) as dominant factors. These findings provide critical data for wildfire modeling highlight need species-specific parameters air quality forecasts.

Language: Английский

Citations

0