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The biomass/plastic ratio in wood plastic composites (WPCs) has been evaluated because of the great practical importance of this topic. To this purpose, FTIR spectra of 59 polypropylene (PP)-based WPCs from three biomass species (Chinese fir, poplar, and bamboo) were recorded and the spectral dates were evaluated by means of the partial least squares regression (PLSR) approach aiming at the prediction of the biomass/PP ratio in the WPCs. The results of the full cross-validation of the data showed that first derivative spectra corrected by standard normal variate (SNV) yielded the optimal model for prediction of the WPC composition. For both biomass and PP prediction, the coefficients of determination (R2) of external validation were above 0.94. The standard errors of prediction (SEP) were between 1.38 and 1.39. And the ratios of performance to deviation (RPD) were about 4.20. The relative prediction errors in this context were lower than ±6%. FTIR combined with PLSR is a useful tool for a rapid and reliable estimation of the biomass and PP contents in different types of PP-based WPCs.

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Estimating industrial carbon dioxide emissions at the national scale is crucial for China's carbon peak and carbon neutralization targets, as well as the low-carbon development of the Chinese furniture manufacturing industry. For this purpose, in this study the Intergovernmental Panel on Climate Change Tier-2 methodology was used to evaluate the carbon dioxide emissions of the Chinese furniture manufacturing industry at the national scale. The results show that carbon dioxide emissions increased from 219.50 × 10,000 tons of CO2 equivalent in 2000 to 850.68 × 10,000 tons of CO2 equivalent in 2019. Moreover, carbon dioxide emission intensity decreased from 9.50 tons of CO2 per million dollars to 1.73 tons of CO2 per million dollars in this period. Moreover, electricity and raw coal were observed to have a significant influence on carbon dioxide emissions, followed by diesel oil, gasoline, heat energy, and natural gas. The results reveal that the Chinese furniture manufacturing industry has generally realized low-carbon development over the past two decades. This work proposes several suggestions to reduce carbon dioxide emissions from the Chinese furniture manufacturing industry, including promoting the use of clean electricity, the installation of photovoltaic cells, industrial transformation and upgrading, the optimization of transport modes for product delivery and material supply, and the employment of low-carbon raw materials.

Quantifying carbon dioxide (CO2) emissions from China’s wood and bamboo processing industry is associated with China’s emissions reduction targets, as well as mitigating global climate change. This study employed the Intergovernmental Panel on Climate Change Tier-2 methodology to investigate spatio-temporal evolution characteristics of carbon dioxide emission from the wood and bamboo processing industry in China from 2000 to 2019. The results showed that energy consumption reached a maximum value of 312,900.35 TJ in 2012. Energy consumption has been gradually transformed from raw coal to electricity and other clean energy. Energy intensity dropped from 1.39 TJ per million yuan of corrected production value in 2000 to 0.15 TJ per million yuan of corrected production value in 2019. Accordingly, CO2 emissions reached their peak value of 31,148.1 thousand tons of CO2 in 2012. Raw coal and electricity had profound impacts on CO2 emissions. The CO2 emission intensity declined from 140.04 tons CO2 per million yuan of corrected production value in 2000 to 19.62 tons CO2 per million yuan of corrected production value in 2019. We conclude that China’s wood and bamboo processing sector is a green, low-carbon industry. The spatial distribution pattern of CO2 emissions is highly consistent with the industrial spatial layout. Furthermore, several mitigation paths were put forward.

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