Nitric acid rain (NAR) seriously affects the biogeochemical cycles of forest communities’ ecosystems. However, the effects of NAR on the composition and diversity of the soil bacterial community remain unclear. In this study, a typical subtropical forest of Quercus acutissima was selected and simulated spraying of NAR at pH 2.5 (AR2.5), 3.5 (AR3.5), and 4.5 (AR4.5) was implemented to investigate the response of the forest soil bacterial communities to NAR. The results showed that the total number of OTUs of soil bacteria in AR2.5 and AR3.5 treatments was 1.11 and 1.23 times that in the control treatment without NAR (CK), respectively. Acidobacteria, Proteobacteria, and Actinobacteria were the dominant phyla in the subtropical forest, accounting for more than 80% of the community’s relative abundance. Concurrently, simulated NAR changed the relative abundance of Rhodanobacter significantly, which could be an indicator of soil bacterial community structure under NAR stress. Moreover, the Chao1, Shannon, and Simpson indices of strong acid rain treatments (i.e., AR2.5 and AR3.5) increased by 9.55%–22.5%, 3.6%–7.43%, and 0.15%–0.26%, respectively, compared to CK. Redundancy and correlation analysis illustrated that the phylum level structure of the bacterial community was significantly affected by soil total carbon, total nitrogen, and ammonium nitrogen. Our findings contribute to a better understanding of the effects of NAR on soil microbial communities and potential soil element cycling in north subtropical forests.

Establishing road shelter forests is a key method to reduce traffic noise pollution. However, the characteristics of various types of road shelter forests and their effectiveness in reducing traffic noise remain extensively unexplored. This study focused on five types of pure road shelter forests (PFs) and one type of mixed coniferous broad-leaved forest (MCBLF). By conducting field noise monitoring and spectrum simulations, we analyzed average mass density, additional noise reduction and economic benefits. With a forest belt width of 60 m, the MCBLF reduced additional noise by 6.6 dB(A). Additionally, Forest height, crown shape, average mass density and noise frequency were all positively linked to noise reduction. The width of shelter forests was the main factor affecting noise reduction. Linear regression analysis results showed that cumulative mass surface density was a significant factor in noise reduction (p < 0.01, R² = 0.93). Furthermore, the type and composition of the shelter forest had indirect effects on noise reduction. The MCBLF had better noise-reducing effects compared to both broad-leaved PFs and needle-leaved PFs due to its more complex structure. Interestingly, as the forest belt became wider, the noise reduction benefits per unit area decreased, implying that a 10 m wide forest belt offered higher economic returns. Considering that a 10 m wide shelter forest belt did not meet noise reduction requirements. This study suggested that the 20 m wide MCBLF was an optimal choice as an urban road shelter forest, providing both effective noise reduction and maximized economic benefits. Our findings provide a basis for the construction and sustainable development of road shelter forests with noise reduction functions.