Occurrence and risk assessment of polycyclic aromatic hydrocarbons in the Hanjiang River Basin and the Danjiangkou Reservoir, China

Yuan

et al. 2019

Atmosphere

Extreme events such as rainstorms and floods are likely to increase in frequency due to the influence of global warming, which is expected to put considerable pressure on water resources. This paper presents a regional frequency analysis of precipitation extremes and its spatio-temporal pattern characteristics based on well-known index-flood L-moments methods and the application of advanced statistical tests and spatial analysis techniques. The results indicate the following conclusions. First, during the period between 1969 and 2015, the annual precipitation extremes at Fengjie station show a decreasing trend, but the Wuhan station shows an increasing trend, and the other 24 stations have no significant trend at a 5% confidence level. Secondly, the Hanjiang River Basin can be categorized into three homogenous regions by hierarchical clustering analysis with the consideration of topography and mean precipitation in these areas. The GEV, GNO, GPA and P III distributions fit better for most of the basin and MARE values range from 3.19% to 6.41% demonstrating that the best-fit distributions for each homogenous region is adequate in predicting the quantiles estimates. Thirdly, quantile estimates are reliable enough when the return period is less than 100 years, however estimates for a higher return period (e.g., 1000 years) become unreliable. Further, the uncertainty of quantiles estimations is growing with the growing return periods and the estimates based on R95P series have a smaller uncertainty to describe the extreme precipitation in the Hanjiang river basin (HJRB). Furthermore, In the HJRB, most of the extreme precipitation events (more than 90%) occur during the rainy season between May and October, and more than 30% of these extreme events concentrate in July, which is mainly impacted by the sub-tropical monsoon climate. Finally, precipitation extremes are mainly concentrated in the areas of Du River, South River and Daba Mountain in region I and Tianmen, Wuhan and Zhongxiang stations in region III, located in the upstream of Danjiangkou Reservoir and Jianghan Plain respectively. There areas provide sufficient climate conditions (e.g., humidity and precipitation) responsible for the occurring floods and will increase the risk of natural hazards to these areas.

Section: Study Area and Datamentioning

confidence: 99%

Section: Study Area and Datamentioning

confidence: 99%

Regional Frequency Analysis of Precipitation Extremes and Its Spatio-Temporal Patterns in the Hanjiang River Basin, China

Yuan

et al. 2019

Atmosphere

“…The Hanjiang River Basin (HJRB; 106°12′–114°14′E and 30°08′–34°11′N, Figure ) situates in the central part of China, involved in the provinces of Shanxi, Hubei, Henan, Sichuan, Gansu and Chongqing (Zhu et al, ; Tao et al, ). Hanjiang River (HJR) is the biggest tributary of Yangtze River, covering the total drainage area of 159,000 km 2 with the length of 1,557 km (Hong et al, ; Qi et al, ). The mainstream of the river originates from southern slope of Qinling Mountains and finally pours into Yangtze River at Wuhan City of Hubei Province.…”

Section: Study Region and Datamentioning

confidence: 99%

“…Danjiangkou Reservoir located in the upper HJR, consisting of Dan Reservoir and Han Reservoir, was constructed since 1958 and finished in 1973, designed as the important water source of the Middle Route of the South‐to‐North Water Diversion Project (Qi et al, ). HJRB is one of important production bases of fresh water aquaculture in China, and is of crucial importance for both economy and ecology in this region (Zhu et al, ).…”

Section: Study Region and Datamentioning

confidence: 99%

Non‐stationary modelling of extreme precipitation by climate indices during rainy season in Hanjiang River Basin, China

Shao

Intl Journal of Climatology

et al. 2019

The extreme precipitation regimes have been changing as the climate system has warmed. Investigating the non-stationarity and better estimating the changes of the extreme precipitation are valuable for informing policy decisions. In this study, two precipitation indices are employed to describe the extreme events, including maximum 5-day precipitation amount (RX5day) and the number of very heavy precipitation days (R20). The generalized additive models for location, scale and shape (GAMLSS) is employed to characterize non-stationarities in extreme precipitation events and related climate indices in 13 stations in the Hanjiang River basin (HJRB). Three models including stationary model without change (M0), nonstationary models over time (M1) and non-stationarity models with large-scale climate indices (M2) as predictors, respectively, are considered to analyse occurrence rates of extreme precipitation. The optimal model and the significant predictors were selected by the Akaike information criterion (AIC). To investigate the main predictors at regional scale, the homogeneous subregions for precipitation extremes are identified by clustering analysis. Results indicate that: (a) the non-stationarities of RX5day series and R20 series at all stations are identified in the HJRB; (b) extreme precipitation behaviour is significantly influenced by climate indices and non-stationary model 2 to describe the changes of extreme precipitation is better than non-stationary model 1, indicating the impact of large-scale climate forcing on the changes of extreme precipitation regimes; (c) the HJRB can be categorized into three homogenous regions. The optimal distributions and the main predictors of extreme precipitation events in most stations of each subregion are basically the same; (d) the dominated climate indices influencing the extreme precipitation events are different in different regions and have regional patterns. The results highlight the modelling of extreme precipitation events under non-stationarity conditions and provide information for developing strategies of mitigation and adaptation to climate change impacts on extreme precipitation.

“…Three soil samples were collected from each sampling site and immediately wrapped in polyethylene zip-lock bags. Then, the samples from each site were combined and lyophilized using a benchtop lab vacuum freeze-dryer at −40 °C for 48 h. All the samples were ground and passed through a 100-mesh (0.149 mm stainless steel sieve) [15] and stored in a refrigerator at −20 °C until the next extraction steps [28].…”

Section: Methodsmentioning

confidence: 99%

Occurrence and Ecological and Human Health Risk Assessment of Polycyclic Aromatic Hydrocarbons in Soils from Wuhan, Central China

Gereslassie

Workineh

Liu

et al. 2018

IJERPH

Self Cite

Polycyclic aromatic hydrocarbons are large groups of ubiquitous environmental pollutants composed of two or more fused aromatic rings. This study was designed to evaluate the distribution, potential sources, and ecological and cancer risks of eleven polycyclic aromatic hydrocarbons from Huangpi soils in Wuhan, central China. The soil samples for this study were taken from 0–10 cm and 10–20 cm soil depths. A modified matrix solid-phase dispersion extraction method was applied to extract analytes from the soil samples. A gas chromatograph equipped with a flame ionization detector was used to determine the concentrations of the compounds. The sum mean concentrations of the polycyclic aromatic hydrocarbons were 138.93 and 154.99 µg kg−1 in the 0–10 cm and 10–20 cm soil depths, respectively. Benzo[a]pyrene and fluorene were the most abundant compounds in the 0–10 cm and 10–20 cm soil depths, respectively. The quantitative values of the pyrogenic index, total index, and diagnostic ratio used in this study showed that the polycyclic aromatic hydrocarbons have a pyrogenic origin. The negligible and maximum permissible concentrations values for naphthalene, acenaphthylene, acenaphthene, phenanthrene, anthracene, pyrene, benz[a]anthracene, and benzo[a]pyrene indicated a moderate ecological risk. The incremental lifetime cancer risk values for adults and children showed a low and moderate cancer risk, respectively.