Study of summer microclimate and PM2.5 concentration in campus plant communities.

Understanding the influencing effect of meteorological factors and air pollutants in the campus plot and the relationship between them is an important topic in the planning and design of campus green space. The changes of pollutant concentrations and meteorological factors in campus green space have certain patterns and specific influencing factors. In this study, we selected four sample plots in Nanjing Forestry University as the research objects, and collected various environmental parameters of the four plots on July 25, 2022. The results showed that the main influences of meteorological factors are the type of the underlying surface of the site, the degree of plant canopy density and the shade coverage area of the building. These factors mainly have a great influence on the value of temperature and humidity. The comprehensive influencing factors can be concluded that the cooling and humidifying effect of the site is ranked as follows: forest > lawn > asphalt road > concrete Square. The main influencing factors of pollutants are: illumination, wind speed, temperature and relative humidity. Among them, illumination and temperature have a negative correlation with PM2.5, wind speed and relative humidity have a positive correlation with PM2.5. Our research shows that the adjustment of campus green space factors can reduce the concentration of pollutants by changing the meteorological factors.

Effect of different plant communities on NO2 in an urban road greenbelt in Nanjing, China.

As an important part of urban ecosystems, plants can reduce NO2 concentrations in the air. However, there is little evidence of the effects of different plant communities on NO2 concentrations in street-scale green spaces. We used a multifunctional lifting environmental detector to investigate the impact of environmental factors and small plant communities on NO2 concentrations in street green spaces during the summer and winter in Nanjing, China. The results showed that temperature, atmospheric pressure, and noise were significantly (P < 0.05) correlated with seasonal changes, temperature and humidity significantly (P < 0.01) influenced NO2 concentrations in winter and summer, and the average NO2 concentration in summer was generally higher than in winter. By comparing NO2 concentrations in different plant community structures and their internal spaces, we found that the plant community structure with tree-shrub-grass was more effective in reducing pollution. These findings will help predict the impact of plant communities on NO2 concentrations in urban streets and help city managers and planners effectively reduce NO2 pollution.

Comprehensive Transcriptome Analysis of Rare Carpinus putoensis Plants under NO2 stress.

We evaluated a transcriptome using high-throughput Illumina HiSeq sequencing and related it to the morphology, leaf anatomy, and physiological parameters of Carpinus putoensis putoensis under NO2 stress. The molecular mechanism of the C. putoensis NO2 stress response was evaluated using sequencing data. NO2 stress adversely affected the morphology, leaf anatomy, and total peroxidase (POD) activity. Through RNA-seq analysis, we used NCBI to compare the transcripts with nine databases and obtained their functional annotations. We annotated up to 2255 million clean Illumina paired-end RNA-seq reads, and 250,200 unigene sequences were assembled based on the resulting transcriptome data. More than 89% of the C. putoensis transcripts were functionally annotated. Under NO2 stress, 1119 genes were upregulated and 1240 were downregulated. According to the KEGG pathway and GO analyses, photosynthesis, chloroplasts, plastids, and the stimulus response are related to NO2 stress. Additionally, NO2 stress changed the expression of POD families, and the HPL2, HPL1, and POD genes exhibited high expression. The transcriptome analysis of C. putoensis leaves under NO2 stress supplies a reference for studying the molecular mechanism of C. putoensis resistance to NO2 stress. The given transcriptome data represent a valuable resource for studies on plant genes, which will contribute towards genome annotations during future genome projects.