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Biogenic volatile organic compounds (BVOCs) have significant effects on atmospheric chemistry, ozone formation and secondary organic aerosol formation. Considering few investigations about BOVCs emissions in north China where is facing serious air pollution in recent years, emissions of various BVOCs from 24 dominant forest species in Beijing were measured from June to September in 2018, using a dynamic headspace sampling method. More than one hundred BVOCs in the collected samples were identified by using an automatic thermal desorption-gas chromatography/mass spectrometry, and their emission rates based on leaf biomass were calculated. Isoprene and monoterpenes were verified to be the dominant BVOCs emitted from the tree species, accounting for more than 50% of the total BVOCs. Generally, broad-leaved species displayed high isoprene emission rates, especially the Platanus occidentalis (21.36 µg/(g⋅hr)), Robinia pseudoacacia (11.55 µg/(g⋅hr)), and Lonicera maackii (9.17 µg/(g⋅hr)), while coniferous species emitted high rates of monoterpenes, such as Platycladus orientalis (27.18 µg/(g⋅hr)), Pinus griffithii (23.11 µg/(g⋅hr)), and Pinus armandii (7.42 µg/(g⋅hr)). High emission rates of monoterpenes from the broad-leaved species of Buxus megistophylla (13.07 µg/(g⋅hr)) and Ligustrum vicaryi (5.74 µg/(g⋅hr)), and high isoprene emission rate from the coniferous tree of Taxus cuspidata (5.86 µg/(g⋅hr)) were also observed. The emission rates of sesquiterpenes from each tree were usually 10–100 times smaller than those of isoprene and monoterpenes. Additionally, relatively high emission rates of oxygenated volatile organic compounds and other alkenes than isoprene and monoterpenes were also found for several tree species. BVOCs emission rates from 24 dominant tree species in Beijing. Image, graphical abstract [ABSTRACT FROM AUTHOR]

In order to design an optimal carbon peak and carbon neutralization pathway for the high-density building sector, a dynamic prediction model is established using system-dynamics coupled building life cycle carbon emission model (SD-BLCA) with consideration of future evolutionary trajectory and time constraints. The model is applied in Beijing using the SD-BLCA combined with scenario analysis and Monte Carlo methods to explore optimal trajectory for its building sector under 30-year timeframe. The results indicate that by increasing the proportion of renewable energy generation by 7% and retrofitting 60 million m2 of existing buildings, these two mature measures can offset the growth of carbon emissions and achieve the peak target by 2025. However, achieving carbon neutrality necessitates a shift from isolated technologies to a comprehensive net-zero emissions strategy. The study proposes a time roadmap that integrates a zero-carbon energy supply system and the carbon reduction measures of the whole life cycle. This strategy primarily relies on renewable sources to provide heat, power, and hydrogen, resulting in estimated reductions of 29.8 Mt, 28.1 Mt, and 0.7 Mt, respectively. Zero energy buildings, green buildings, and renovated buildings can reduce carbon emissions through their own energy-saving measures by 8.4, 18.2, and 11.8 kg/m2, respectively. [Display omitted] • System-dynamics coupled life cycle dynamic prediction model were established. • The major CO 2 emission from building operation stage ranged 52%–73% in megacity. • CO 2 emission reduce 59 and 18 Mt from energy supply and consumption for building neutrality. • Renewable energy includes 51% Heat, 48% Power and 1% hydrogen in building neutrality. • Enhancement of energy efficiency and zero-carbon energy contribute building neutrality. [ABSTRACT FROM AUTHOR]