Spatio-temporal patterns and drivers of CH4 and CO2 fluxes from rivers and lakes in highly urbanized areas.

Gaseous carbon exchange at the water-air interface of rivers and lakes is an essential process for regional and global carbon cycle assessments. Many studies have shown that rivers surrounding urban landscapes can be hotspots for greenhouse gas (GHG) emissions. Here we investigated the variability of diffusive GHG (methane [CH4] and carbon dioxide [CO2]) emissions from rivers in different landscapes (i.e., urban, agricultural and mixed) and from lakes in Suzhou, a highly urbanized region in eastern China. GHG emissions in the Suzhou metropolitan water network followed a typical seasonal pattern, with the highest fluxes in summer, and were primarily influenced by temperature and dissolved oxygen concentration. Surprisingly, lakes were emission hotspots, with mean CH4 and CO2 fluxes of 2.80 and 128.89 mg m-2 h-1, respectively, translating to a total CO2-equivalent flux of 0.21 g CO2-eq m-2 d-1. The global warming potential of urban and mixed rivers (0.19 g CO2-eq m-2 d-1) was comparable to that for lakes, but about twice the value for agricultural rivers (0.10 g CO2-eq m-2 d-1). Factors related to the high GHG emissions in lakes included hypoxic water conditions and an adequate nutrient supply. Riverine CH4 emissions were primarily associated with the concentrations of total dissolved solids (TDS), ammonia­nitrogen and chlorophyll a. CO2 emissions in rivers were mainly closely related to TDS, with suitable conditions allowing rapid organic matter decomposition. Compared with other types of rivers, urban rivers had more available organic matter and therefore higher CO2 emissions. Overall, this study emphasizes the need for a deeper understanding of the impact of GHG emissions from different water types on global warming in rapidly urbanizing regions. Flexible management measures are urgently needed to mitigate CO2 and CH4 emissions more effectively in the context of the shrinking gap between urban and rural areas with growing socio-economic development.

Simulated annealing-simplex hybrid algorithm for ellipsometric data inversion of multilayer films.

A simulated annealing-simplex hybrid algorithm that accurately measures the optical parameters of multilayer films is proposed for ellipsometric data inversion of multilayer films. In single-wavelength ellipsometry experiments, multiple groups of ellipsometric parameters measured by multiple incident angles can determine multiple optical parameters. Analysis of the measurement accuracy of multilayer films indicates that probabilities of uncertainty increase as films become thinner. Accurate measurements show that using the hybrid algorithm to obtain the optical parameters of multilayer films is feasible and reliable. The algorithm can be used for the inversion and the actual measurement of double-layer and multilayer films by single-wavelength ellipsometry.