[Effect of Different Multi-pond Network Landscape Structures on Nitrogen Retention Over Agricultural Watersheds].

Nitrogen (N) loss from agricultural fields can cause eutrophication in downstream freshwater systems, but the use of multi-pond networks can mitigate N losses from agricultural runoff. This study presents an analysis of the relationships between N retention and land use before and after rainfall events with the goal of identifying differences in agricultural runoff in four sub-watersheds with 3, 3, 7, and 7 ponds, respectively. The total N concentrations before rainfall ranged from 1.32 mg·L-1 to 6.32 mg·L-1, and total N (TN) levels in the ponds after rainfall varied from 2.8 mg·L-1 to 16.99 mg·L-1 and typically contained 20%-74% nitrate (NO3--N). The mean concentration retention efficiencies in the four sub-watersheds for TN, NO3--N, and ammonium (NH4+-N) were 50.09%, 48.71%, and 52.75%, respectively. The N retention efficiency in sub-watershed 1 (3 ponds) was the lowest among the four sub-watersheds. The N retention mass in sub-watershed 2 (3 ponds) was only 56.10 kg, and this value was far lower than that of sub-watershed 4 (324.43 kg, 7 ponds). The number of ponds in the sub-watersheds was not the only factor that contributed to the effective retention of non-point source N in-situ, but pond area and ditch density also significantly affected N retention. Thus, pond area and ditch density should be increased for similar multi-pond areas. However, managing multi-ponds to maximize N retention requires dynamic monitoring and management over the long term.

Socioeconomic Drivers of PM2.5 in the Accumulation Phase of Air Pollution Episodes in the Yangtze River Delta of China.

Recent studies in PM2.5 sources show that anthropogenic emissions are the main contributors to haze pollution. Due to their essential roles in establishing policies for improving air quality, socioeconomic drivers of PM2.5 levels have attracted increasing attention. Unlike previous studies focusing on the annual PM2.5 concentration (Cyear), this paper focuses on the accumulation phase of PM2.5 during the pollution episode (PMAE) in the Yangtze River Delta in China. This paper mainly explores the spatial variations of PMAE and its links to the socioeconomic factors using a geographical detector and simple linear regression. The results indicated that PM2.5 was more likely to accumulate in more developed cities, such as Nanjing and Shanghai. Compared with Cyear, PMAE was more sensitive to socioeconomic impacts. Among the twelve indicators chosen for this study, population density was an especially critical factor that could affect the accumulation of PM2.5 dramatically and accounted for the regional difference. A 1% increase in population density could cause a 0.167% rise in the maximal increment and a 0.214% rise in the daily increase rate of PM2.5. Additionally, industry, energy consumption, and vehicles were also significantly associated with PM2.5 accumulation. These conclusions could serve to remediate the severe PM2.5 pollution in China.