Historic blocks are valuable architectural and landscape heritage, and it is important to explore the distribution characteristics of tourists to historic blocks and their landscape preferences to realize the scientific construction and conservation of historic blocks and promote their sustainable development. At present, few studies combine the analysis of tourist distribution characteristics with landscape preferences. This study takes the historic block of Three Lanes and Seven Alleys in Fuzhou as an example, combines field research and questionnaires to construct a landscape preference evaluation indicator system for the historic block, measures the distribution characteristics of tourists in the block through the heat value of tourist flow obtained from the Tencent regional heat map, and analyses the influence of landscape preference indicators on the heat value of tourist flow in the block through stepwise multiple linear regression. The research shows that: (1) the spatial and temporal variation in the heat value of tourist flow tends to be consistent throughout the block, from 7 a.m. to 6 p.m., showing a “rising, slightly fluctuating and then stabilizing” state, both on weekdays and on weekends. (2) The factors influencing the heat value of tourist flow in the different spatial samples are various, with commercial atmosphere, plant landscape, accessibility of the road space, architecture, and the surrounding environment having a significant impact on the heat value of tourist flow. Based on the analysis of the landscape preferences of tourists in the historic block, a landscape optimization strategy is proposed to provide a reference for the management and construction of the block.

Air pollution has become worldwide environmental issue in present day. In this study, the concentrations of PM10 was analyzed with hourly datasets, and the data of meteorological conditions were measured per 3 hours from 1st Sep 2014 to 30th Sep 2016 at Fuzhou city in the southeastern China. The mean value of mass concentration of PM10 is 54.65±24.07μg m−3 in the study period. The correlation coefficient between mass concentrations of PM10 and meteorological factors were analyzed, it shows that there existed a negative correlation between PM10 and T (−0.03), RU (-0.27), WS (−0.10), HCC (−0.04), VIS (−0.31), DPT (-0.15) and RF (-0.14). Subsequently, the impacts of typhoons on the mass concentrations of PM10 during September 10th 2016 to September 16th 2016 were analyzed during which the mass concentration of PM10 decreased at a large extent and the particulates have more prominent changes during the typhoon period compared with coarse particulates.

Simultaneous measurements of mass concentrations of PM2.5 along with other co-existence pollutants viz., SO2, CO, NO2 and O3, were studied with hourly datasets and the data of meteorological conditions were measured per 3 hours from 1st Sep 2014 to 30th Sep 2016 at Fuzhou city, China. The concentration of PM2.5 is 28.42 ± 14.75 in the study period. Meanwhile, the seasonal ratio of PM2.5 was also analysed, with the maximal value as 0.61 in winter, 0.52 in spring, 0.49 in autumn and 0.44 in summer. This implied that fine particulate reaches the maximal value in winter and the minimum value in summer. The correlation coefficient between concentrations of PM2.5 and SO2, CO, NO2, and O3 concentrations were 0.64, 0.52, 0.53 and 0.67. There existed negative correlation between PM2.5 and T (– 0.27), HCC (– 0.13), WS (– 0.16), VIS (– 0.46), DT (-0.31) and RF (-0.10). Subsequently, the impacts of typhoons on the mass concentrations of PM2.5 during September 10th 2016 to September 16th 2016 were analyzed during which the mass concentration of PM2.5 decreased at a large extent and the fine particulates have more prominent changes during the typhoon period compared with coarse particulates.