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”.

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, PM_2.5, NO₂, and CO are affected by the secondary and tertiary industries, where PM_2.5 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 PM_2.5 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.

Air pollution is one of the major environmental problems that endanger human health. The COVID-19 pandemic provided an excellent opportunity to investigate the possible methods to improve Beijing’s air quality meanwhile considering Beijing’s economic impact. We used the TVP-VAR model to analyze the dynamic relationship among the pandemic, economy and air quality based on the daily data from 1 January to 30 August 2020. The result shows that the COVID-19 pandemic indeed had a positive effect on air governance which was good for human health, while doing business as usual would gradually weaken this effect. It shows that the Chinese authority’s production restriction effectively deals with air pollution in a short period of time since the pandemic is just like a quasi-experiment that suddenly suspended all the companies. However, as the limitation stops, the improvement decreases. It is not sustainable. In addition, a partial quarantine also has a positive impact on air quality, which means a partial limitation was also helpful in improving air quality and also played an important role in protecting people’s health. Second, the control measures really hurt Beijing’s economy. However, the partial quarantine had fewer adverse effects on the economy than the lockdown. It is supposed to be a reference for air governance and pandemic control. Third, the more the lag periods were, the smaller their impact. Thus, restrictions on production can only be used in emergencies, such as some international meetings, while it is hard to improve the air quality and create a healthy and comfortable living environment only by limitation in the long-term.

The research calculated the waste paper recovery rate, and analyzed the main factors influencing waste paper recovery rate in China with time series data from 1970 to 2012. The consequent recovery rate and utilization rate of waste paper show that the recovery of paper products has been experiencing a rapid growth in China, but it cannot meet the domestic need. The empirical analysis proves that demand is the main driver to stimulate the increase of waste paper recovery rate in China; the increased average GDP per capita and proportion of waste paper pulp are two other important factors; the increased urbanization rate does not exert significant influence. In the circumstance of insufficient timber supply, the policy of eliminating straw pulp capacities for paper-making indusrty improves the recovery rate of waste paper.