scholarly journals Pressures imposed by energy production on compliance with China's ‘Three Red Lines’ water policy in water-scarce provinces

Water Policy ◽  
2018 ◽  
Vol 21 (1) ◽  
pp. 38-48 ◽  
Author(s):  
Xiawei Liao ◽  
Jing Ming

Abstract In 2015, 16.52 km3 of water was consumed for energy production in China, of which coal production, thermoelectric power and coke used 57.7%, 28.8% and 6.2%, respectively. Most water is consumed in China's northern (north and northwest) provinces where water is scarce and energy production's impact on water resources is further intensified in the north when this water scarcity is taken into account. The top five provinces with the largest consumption of scarce water by energy production are predominantly concentrated in the North China Plain. In 2015, nine provinces did not meet their Industrial Water Efficiency Improvement targets set by the ‘Three Red Lines’ water policy. Of these nine, five provinces (Shanxi, Shandong, Hebei, Xinjiang and Ningxia) are located in northern regions and face severe water stresses. Water consumed by energy production occupied more than 20% of the Industrial Water Allowances (IWAs) that were allowed by the ‘Three Red Lines’ policy in all five provinces. In Shanxi, energy consumption exceeded more than three times its IWA. Our findings underscore that energy production imposes severe pressure on water-scarce provinces' compliance with the ‘Three Red Lines’ policy and thus suggest a necessity to coordinate cross-sectoral policies, planning and investments.

Author(s):  
Min Xue ◽  
Jianzhong Ma ◽  
Guiqian Tang ◽  
Shengrui Tong ◽  
Bo Hu ◽  
...  

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 46
Author(s):  
Gangqiang Zhang ◽  
Wei Zheng ◽  
Wenjie Yin ◽  
Weiwei Lei

The launch of GRACE satellites has provided a new avenue for studying the terrestrial water storage anomalies (TWSA) with unprecedented accuracy. However, the coarse spatial resolution greatly limits its application in hydrology researches on local scales. To overcome this limitation, this study develops a machine learning-based fusion model to obtain high-resolution (0.25°) groundwater level anomalies (GWLA) by integrating GRACE observations in the North China Plain. Specifically, the fusion model consists of three modules, namely the downscaling module, the data fusion module, and the prediction module, respectively. In terms of the downscaling module, the GRACE-Noah model outperforms traditional data-driven models (multiple linear regression and gradient boosting decision tree (GBDT)) with the correlation coefficient (CC) values from 0.24 to 0.78. With respect to the data fusion module, the groundwater level from 12 monitoring wells is incorporated with climate variables (precipitation, runoff, and evapotranspiration) using the GBDT algorithm, achieving satisfactory performance (mean values: CC: 0.97, RMSE: 1.10 m, and MAE: 0.87 m). By merging the downscaled TWSA and fused groundwater level based on the GBDT algorithm, the prediction module can predict the water level in specified pixels. The predicted groundwater level is validated against 6 in-situ groundwater level data sets in the study area. Compare to the downscaling module, there is a significant improvement in terms of CC metrics, on average, from 0.43 to 0.71. This study provides a feasible and accurate fusion model for downscaling GRACE observations and predicting groundwater level with improved accuracy.


Author(s):  
Weiqi Xu ◽  
Chun Chen ◽  
Yanmei Qiu ◽  
Conghui Xie ◽  
Yunle Chen ◽  
...  

Organic aerosol (OA), a large fraction of fine particles, has a large impact on climate radiative forcing and human health, and the impact depends strongly on size distributions. Here we...


2021 ◽  
Vol 20 (6) ◽  
pp. 1687-1700
Author(s):  
Li-chao ZHAI ◽  
Li-hua LÜ ◽  
Zhi-qiang DONG ◽  
Li-hua ZHANG ◽  
Jing-ting ZHANG ◽  
...  

2021 ◽  
Vol 351 ◽  
pp. 129349
Author(s):  
Bisma Riaz ◽  
Qiuju Liang ◽  
Xing Wan ◽  
Ke Wang ◽  
Chunyi Zhang ◽  
...  

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