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The Beijing–Tianjin–Hebei region is the most dynamic region and largest economy in northern China; however, the air quality is the worst in the country. The study of the air quality in the cities around Beijing is of great significance for air pollution control. Therefore, this study analyzed whether the COVID-19 pandemic altered the periodic pattern of the air quality in Beijing and its neighboring cities. The study employed continuous wavelet transform to examine the impact of the COVID-19 pandemic on the air quality of Beijing and its neighboring cities. This method reveals the changes in the air quality from a periodic pattern perspective. The results showed that COVID-19 weakened the periodic changes in air quality in Beijing and five neighboring cities, and this effect was most pronounced during the outbreak of the pandemic in early 2020. The cycle synchronization analysis showed that the pandemic weakened the cycle synchronization of air quality of the cities in the north of Beijing, while less impact was found on the cities to the south of Beijing. Moreover, the periodic patterns in 2020 and 2021 were compared with that in 2019 (before the outbreak of the pandemic), and it was found that the periodic patterns during the outbreak of the pandemic in 2020 and 2021 were significantly different from that in the same period in 2019. Therefore, COVID-19 weakened the periodic pattern of air quality in the cities around Beijing and altered the connection to air quality among them. The changes reveal the connections of inter-city air pollutants caused by human economic and social activities in cities around Beijing. [ABSTRACT FROM AUTHOR]

The recovery rate of paper products is a key factor in measuring the recyscling potential and the sustainability of the paper industry. Accurately measuring the recovery rate of paper products holds important theoretical and practical value. This paper took the non-recycling part and time factor into account and built the Koyck model to estimate the recovery rate, storage loss rate and recovery cycle of paper products. The model results showed that the recovery rate of Chinese paper products in 2017 increased to 58.05%, which was 10% higher than the results of methods that did not contain the non-recycling part or the time factor. The model results also showed that the storage loss rate of Chinese paper products was much higher than that of developed countries while the recovery cycle was close to the level of developed countries. The distribution analysis showed that the storage loss rate and recovery cycle of Chinese paper products varied significantly over time, which may be the result of policies and the change of consumption structure. It is suggested that the Chinese government should take measures to reduce the storage loss rate of paper products and enhance their recycling ability to achieve sustainable development. [ABSTRACT FROM AUTHOR]

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The conflict between economic growth and environmental pollution has become a considerable bottleneck to future development throughout the world. The industrial structure may become the possible key factor in resolving the contradiction. Using the daily data of air quality from January to April in 2019 and 2020, we used the DID model to identify the effects of industrial structure on air quality by taking the COVID-19 pandemic as a quasi-experiment. The results show that, first, the impact of profit of the secondary industry on air quality is ten times higher than that of the tertiary industry. Therefore, the secondary industry is the main factor causing air pollution. Second, the effect of the reduction in the secondary industry on the improvement of air quality is better than that of the tertiary industry in Beijing. Therefore, the implementation of Beijing's non-capital function relief policy is timely and reasonable, and the adjustment of the industrial structure is effective in the improvement of air quality. Third, PM2.5, NO2, and CO are affected by the secondary and tertiary industries, where PM2.5 is affected most seriously by the second industry. Therefore, the transformation from the secondary industry to the tertiary industry can not only solve the problem of unemployment but also relieve the haze. Fourth, the result of O3 is in opposition to other pollutants. The probable reason is that the decrease of PM2.5 would lead to an increase in the O3 concentration. Therefore, it is difficult to reduce O3 concentrationby production limitation and it is urgent to formulate scientific methods to deal with O3 pollution. Fifth, the air quality in the surrounding areas can also influence Beijing. As Hebei is a key area to undertake Beijing's industry, the deterioration of its air quality would also bring pressure to Beijing's atmospheric environment. Therefore, in the process of industrial adjustment, the selection of appropriate regions for undertaking industries is very essential, which is worth our further discussion. [ABSTRACT FROM AUTHOR]

• Air pollution relationship has been weakening due to interregional air policies. • Industrial adjustment has achieved some progress in alleviating air pollution. • Industrial relocation policies in ZJK, CHD, TIJ could achieve incremental benefits. This study aims to clarify the correlation between air pollution of cities in Beijing Economic Belt from a time-varying perspective and estimate effects of joint prevention and control regulation of air pollution. The COVID-19 pandemic provides a unique opportunity. Based on daily data of air quality, we used TVP-VAR model and utilize the pandemic as a quasi-experiment to assess the policies. The results show air pollution in surrounding cities does influence Beijing's air quality, but the relationship has been weakening year by year, mainly due to industrial adjustment which have achieved progress on alleviating the path of air pollution. Therefore, it is necessary to implement joint regulation in areas with serious pollution. Specifically, the relationship between the air quality of Beijing and Zhangjiakou, Chengde, Tianjin decreased as the pandemic became worse. In contrast, there was no significant decline in Langfang and Baoding. So unlike Baoding and Langfang, industrial production increased relationships between air quality of Beijing and the other three cities, which highlights the validity of restrictions. However, restrictions implemented on Baoding and Langfang affect economic development but have little effect on Beijing's air governance. Therefore, joint regulation contributes to realizing sustainable cities, but more targeted policies should be formulated. [Display omitted] [ABSTRACT FROM AUTHOR]

China's wood industry is vulnerable to the COVID-19 pandemic since wood raw materials and sales of products are dependent on the international market. This study seeks to explore the speed of log price recovery under different control measures, and to perhaps find a better way to respond to the pandemic. With the daily data, we utilized the time-varying parameter autoregressive (TVP-VAR) model, which can incorporate structural changes in emergencies into the model through time-varying parameters, to estimate the dynamic impact of the pandemic on log prices at different time points. We found that the impact of the pandemic on oil prices and Renminbi exchange rate is synchronized with the severity of the pandemic, and the ascending in the exchange rate would lead to an increase in log prices, while oil prices would not. Moreover, the impulse response in June converged faster than in February 2020. Thus, partial quarantine is effective. However, the pandemic's impact on log prices is not consistent with changes of the pandemic. After the pandemic eased in June 2020, the impact of the pandemic on log prices remained increasing. This means that the COVID-19 pandemic has long-term influences on the wood industry, and the work resumption was not smooth, thus the imbalance between supply and demand should be resolved as soon as possible. Therefore, it is necessary to promote the development of the domestic wood market and realize a "dual circulation" strategy as the pandemic becomes a "new normal". [ABSTRACT FROM AUTHOR]

• An accounting scheme was built to evaluate national timber carbon stock value (TCSV). • The price ripple effects of quantifying TCSV were explored through input-output price model. • The top 10 surplus economies regarding the accumulated TCSV were the major contributors to production-based TCSV. • The top 10 deficit economies were dominated by developed economies with large net import-embodied TCSV. • The prices of harvested wood products and energy-fuel products were influenced most by integrating the TCSV into timber prices. Timber can mitigate climate change because it can store carbon for decades. However, the value of timber carbon stocks has been neglected for a long time, which has led to overemphasize the production yields of timber. This approach is detrimental to increasing forest carbon sinks. Therefore, quantifying the economic value of the timber carbon stocks and incorporating it into timber prices have great practical significance for sustainable forest development and climate change mitigation. Moreover, the leakage of the global timber carbon stock value (TCSV) is prominent, and the flow patterns of the global trade-embodied TCSV should be determined to precisely evaluate the forest assets of individual economies. Based on the Exiobase database and a multi-regional input-output model, this study calculated the TCSV of 43 economies and 5 regions from 1995-2011 considering the cross-border transfer of TCSV. Furthermore, the effects of incorporating TCSV into timber prices on various product prices were explored. The results show that the top 10 surplus economies regarding the accumulated TCSV between 1995 and 2011 are the major contributors of production-based timber carbon stock value, and the top 10 deficit economies are dominated by developed economies with large net import-embodied TCSV. The ripple effect of the rising price of timber caused by TCSV as an environmental cost mainly influenced harvested wood products and energy-fuel products. The research findings provide a scientific assessment of the TCSV and contribute to advancing the timber pricing mechanism to increase forest carbon sinks. [ABSTRACT FROM AUTHOR]

As a traditional energy and carbon intensive sector, it becomes imperative for the global paper industry to realize green development. This paper aims to provide guidance for the green transformation of global paper industry by evaluating the global paper industry green development level in a systematic and dynamic way. This paper employs text-mining method to develop paper industry green development evaluation indicator system and adopts market-extended LCA model and entropy-TOPSIS method to calculate the paper industry green development level of 48 countries/regions. The results show that during 2000–2030 the paper industry green development level of developing countries improves faster than developed countries, where those of developing and developed countries increase from 0.3369 to 0.3938 and from 0.5120 to 0.5517 respectively and the gap between them narrows from 0.1751 to 0.1579. The comparative analysis reveals that the paper industries of developed and developing countries are in different green development stages. Developing countries, represented by China, improve greatly in economic and social dimensions, but decline seriously in ecological dimension due to enlarging resource consumption and environmental damages. On the contrary, developed countries tend to saturate in economic and social dimensions and have been improving fast in ecological dimension, gradually realizing the decoupling of industrial economic development and environmental damages. To further promote the global paper industry green development, developing countries should focus on promoting the coordinated development between economic growth and environment protection and developed countries should play a leading role in the global green transformation by promoting optimal allocation of resources and cross-regional communications of green technologies. • A paper industry green development indicator system is developed based on text mining. • A global paper industry green development model is built with market-extended LCA. • Complex interactions among the indicators are internalized in the evaluation. • A spatial-temporal analysis is performed on global paper industry green development level. [ABSTRACT FROM AUTHOR]