Hydrological models play an important role in water resource management, but they always suffer from various sources of uncertainties. Therefore, it is necessary to implement uncertainty analysis to gain more confidence in numerical modeling. The study employed three methods (i.e., Parameter Solution (ParaSol), Sequential Uncertainty Fitting (SUFI2), and Generalized Likelihood Uncertainty Estimation (GLUE)) to quantify the parameter sensitivity and uncertainty of the SWAT (Soil and Water Assessment Tool) model in a mountain-loess transitional watershed—Jingchuan River Basin (JCRB) on the Loess Plateau, China. The model was calibrated and validated using monthly observed streamflow at the Jingchuan gaging station and the modeling results showed that SWAT performed well in the study period in the JCRB. The parameter sensitivity results demonstrated that any of the three methods were capable for the parameter sensitivity analysis in this area. Among the parameters, CN2, SOL_K, and ALPHA_BF were more sensitive to the simulation of peak flow, average flow, and low flow, respectively, compared to others (e.g., ESCO, CH_K2, and SOL_AWC) in this basin. Although the ParaSol method was more efficient in capturing the most optimal parameter set, it showed limited ability in uncertainty analysis due to the narrower 95CI and poor P-factor and R-factor in this area. In contrast, the 95CIs in SUFI2 and GLUE were wider than ParaSol, indicating that these two methods can be promising in analyzing the model parameter uncertainty. However, for the model prediction uncertainty within the same parameter range, SUFI2 was proven to be slightly more superior to GLUE. Overall, through the comparisons of the proposed evaluation criteria for uncertainty analysis (e.g., P-factor, R-factor, NSE, and R²) and the computational efficiencies, SUFI2 can be a potentially efficient tool for the parameter optimization and uncertainty analysis. This study provides an insight into selecting uncertainty analysis method in the modeling field, especially for the hydrological modeling community.

The emissions of nitrogen oxides (NO_x) decreased under China’s air quality control policies. However, concern remains regarding the response of ozone (O₃) in the metropolitan areas. The characteristics and trends of ambient O₃ and NO_x in Shenzhen were investigated during the 2011–2017 period. Both the human population and vegetation are exposed to higher O₃ at suburban and rural sites than at the urban site. The O₃ weekend effect is significant (p = 0.062) at the urban site, with O₃ levels 1.19 ppb higher on Sunday than on weekdays. Solar radiation, precipitation, and relative humidity are the most relevant meteorological factors that affect O₃ daily variations. Wind speed is the least relevant factor, but wind direction is related to the presence of high O₃ air concentrations. Both 1-h and 8-h O₃ exhibit an increase, opposite to the trend of NO_x. A slight decline in O₃ occurs in autumn at less urbanized sites. The increase in O₃ is more prevalent and rapid in the winter at more urbanized sites. This can be due to the transport of increased O₃ from northern China, as well as a lowered O₃ titration effect with NO_x reduction. O₃ increases fastest at the urban site, with an estimated rate of 4.3% (95% confidence intervals (CIs): 0.96, 8.25) per year (p < 0.05) for 8-h O₃ and 2.5% (95% CIs: −0.46, 6.12) per year (p > 0.1) for 1-h O₃, posing greater human health risks to areas with high population density.

Vegetation is essential for maintaining urban ecosystems, climate regulation, and resident health. To explore the variations in city-level vegetation greening (VG) and its relationship to urban expansion, VG in 439 Chinese cities was extracted using the Theil–Sen and Mann–Kendall algorithms based on Moderate Resolution Imaging Spectroradiometer EVI (enhanced vegetation index) data from 2001 to 2020. The spatial variations in VG and its patterns, as well as its relationship with urban expansion, were then analyzed. The following results were obtained: (1) cities with larger greening areas were primarily located in the central and eastern provinces of China, followed by the southeastern, southwestern, and western provinces. The 48 cities with the largest greening areas accounted for 60.47% of the total greening area. (2) VG patches in northern China exhibited better integrity. (3) The centralization trend of VG was evident; the location of VG patterns was influenced by the form of urban expansion. (4) The intensity of artificial impervious area expansion had a weak negative correlation with the VG. Therefore, we must enhance vegetation in new urban areas to improve the spatial balance of VG. The present results of this study can provide a foundation for developing effective policies for the construction and management of urban greenery projects.

Uniformly inserting points on the sphere has been found useful in many scientific and engineering fields. Different from the offline version where the number of points is known in advance, we consider the online version of this problem. The requests for point insertion arrive one by one and the target is to insert points as uniformly as possible. To measure the uniformity we use gap ratio which is defined as the ratio of the maximal gap to the minimal gap of two arbitrary inserted points. We propose a two-phase online insertion strategy with gap ratio of at most $3.69$ . Moreover, the lower bound of the gap ratio is proved to be at least $1.78$ .

Shenzhen is China’s top ten clean air city and the cleanest air megacity. Even so, epidemiologic studies have shown ambient air pollution had significant adverse impacts on human health in this less polluted city. In this study, the concentrations of six criteria air pollutants (PM2.5, PM10, O3, NO2, SO2, and CO) from 2014 to 2017 were analyzed and compared to thresholds of both national and international air quality standards. The results showed concentrations of all air pollutants were below target values of current national air quality standard, but levels of particulate matter (PM) and O3 were still much higher than the recommended levels by the World Health Organization. Within national air quality standards, the number of over-limit days was rare with few variations between highly polluted and low pollution areas. The air quality improvement was slowing down recently. Our results suggest annual and daily thresholds for PM are too loose for air quality improvement in Shenzhen. Hence, we call for evaluation and establishment of tougher air quality standard.