Peasants and Revolution in Rural China: Rural Political Change in the North China Plain and the Yangzi Delta, 1850–1949. Chang Liu. London and New York: Routledge, 2007. xiv + 258 pp. £80.00. ISBN 978-0-415-42176-8

2008 ◽  
Vol 194 ◽  
pp. 456-457
Author(s):  
Lucien Bianco
Keyword(s):  
New York ◽  
North China Plain ◽  
North China ◽  
Political Change ◽  
Rural China ◽  
The North ◽  
The North China Plain ◽  
Yangzi Delta

scholarly journals Wintertime photochemistry in Beijing: Observations of RO<sub>x</sub> radical concentrations in the North China Plain during the BEST-ONE campaign

2018 ◽  
Author(s):  
Zhaofeng Tan ◽  
Franz Rohrer ◽  
Keding Lu ◽  
Xuefei Ma ◽  
Birger Bohn ◽  
...  
Keyword(s):  
New York ◽  
Primary Production ◽  
North China Plain ◽  
North China ◽  
Oxidative Capacity ◽  
Oh Radicals ◽  
Peroxy Radicals ◽  
The North ◽  
The North China Plain ◽  
Secondary Pollutants

Abstract. The first wintertime in-situ measurements of hydroxyl (OH), hydroperoxy (HO2) and organic peroxy (RO2) radicals (ROx = OH + HO2 + RO2) in combination with observations of total reactivity of OH radicals, kOH in Beijing are presented. The field campaign “Beijing winter finE particle STudy – Oxidation, Nucleation and light Extinctions” (BEST-ONE) was conducted at the suburban site Huairou near Beijing from January to March 2016. It aimed to understand oxidative capacity during wintertime and to elucidate the secondary pollutants formation mechanism in the North China Plain (NCP). OH radical concentrations at noontime ranged from 2.4 × 106 cm−3 in severely polluted air (kOH ~ 27 s−1) to 3.6 × 106 cm−3 in relatively clean air (kOH ~ 5 s−1). These values are nearly two-fold larger than OH concentrations observed in previous winter campaign in Birmingham, Tokyo, and New York City. During this campaign, the total primary production rate of ROx radicals was dominated by the photolysis of nitrous acid accounting for 46 % of the identified primary production pathways for ROx radicals. Other important radical sources were alkene ozonolysis (28 %) and photolysis of oxygenated organic compounds (24 %). A box model was used to simulate the OH, HO2 and RO2 concentrations based on the observations of their long-lived precursors. The model was capable of reproducing the observed diurnal variation of the OH and peroxy radicals during clean days with a factor of 1.5. However, it largely underestimated HO2 and RO2 concentrations by factors up to 5 during pollution episodes. The HO2 and RO2 observed-to-modeled ratios increased with increasing NO concentrations, indicating a deficit in our understanding of the gas-phase chemistry in the high NOx regime. The OH concentrations observed in the presence of large OH reactivities indicate that atmospheric trace gas oxidation by photochemical processes can be highly effective even during wintertime, thereby facilitating the vigorous formation of secondary pollutants.

scholarly journals Wintertime photochemistry in Beijing: observations of RO<sub><i>x</i></sub> radical concentrations in the North China Plain during the BEST-ONE campaign

2018 ◽  
Vol 18 (16) ◽  
pp. 12391-12411 ◽  
Author(s):  
Zhaofeng Tan ◽  
Franz Rohrer ◽  
Keding Lu ◽  
Xuefei Ma ◽  
Birger Bohn ◽  
...  
Keyword(s):  
New York ◽  
Primary Production ◽  
North China Plain ◽  
North China ◽  
Oxidative Capacity ◽  
Oh Radicals ◽  
Peroxy Radicals ◽  
The North ◽  
The North China Plain ◽  
Secondary Pollutants

Abstract. The first wintertime in situ measurements of hydroxyl (OH), hydroperoxy (HO2) and organic peroxy (RO2) radicals (ROx=OH+HO2+RO2) in combination with observations of total reactivity of OH radicals, kOH in Beijing are presented. The field campaign “Beijing winter finE particle STudy – Oxidation, Nucleation and light Extinctions” (BEST-ONE) was conducted at the suburban site Huairou near Beijing from January to March 2016. It aimed to understand oxidative capacity during wintertime and to elucidate the secondary pollutants' formation mechanism in the North China Plain (NCP). OH radical concentrations at noontime ranged from 2.4×106cm-3 in severely polluted air (kOH∼27s-1) to 3.6×106cm-3 in relatively clean air (kOH∼5s-1). These values are nearly 2-fold larger than OH concentrations observed in previous winter campaigns in Birmingham, Tokyo, and New York City. During this campaign, the total primary production rate of ROx radicals was dominated by the photolysis of nitrous acid accounting for 46 % of the identified primary production pathways for ROx radicals. Other important radical sources were alkene ozonolysis (28 %) and photolysis of oxygenated organic compounds (24 %). A box model was used to simulate the OH, HO2 and RO2 concentrations based on the observations of their long-lived precursors. The model was capable of reproducing the observed diurnal variation of the OH and peroxy radicals during clean days with a factor of 1.5. However, it largely underestimated HO2 and RO2 concentrations by factors up to 5 during pollution episodes. The HO2 and RO2 observed-to-modeled ratios increased with increasing NO concentrations, indicating a deficit in our understanding of the gas-phase chemistry in the high NOx regime. The OH concentrations observed in the presence of large OH reactivities indicate that atmospheric trace gas oxidation by photochemical processes can be highly effective even during wintertime, thereby facilitating the vigorous formation of secondary pollutants.

ROx Budgets and O3 Formation during Summertime at Xianghe Suburban Site in the North China Plain

2021 ◽  
Author(s):  
Min Xue ◽  
Jianzhong Ma ◽  
Guiqian Tang ◽  
Shengrui Tong ◽  
Bo Hu ◽  
...  
Keyword(s):  
North China Plain ◽  
North China ◽  
The North ◽  
The North China Plain ◽  
Suburban Site

scholarly journals Improving the Resolution and Accuracy of Groundwater Level Anomalies Using the Machine Learning-Based Fusion Model in the North China Plain

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 46
Author(s):  
Gangqiang Zhang ◽  
Wei Zheng ◽  
Wenjie Yin ◽  
Weiwei Lei
Keyword(s):  
Machine Learning ◽  
Data Fusion ◽  
Groundwater Level ◽  
North China Plain ◽  
North China ◽  
Gradient Boosting ◽  
Fusion Model ◽  
The North ◽  
The North China Plain ◽  
Prediction Module

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.

scholarly journals The water-saving potential of using micro-sprinkling irrigation for winter wheat production on the North China Plain

2021 ◽  
Vol 20 (6) ◽  
pp. 1687-1700
Author(s):  
Li-chao ZHAI ◽  
Li-hua LÜ ◽  
Zhi-qiang DONG ◽  
Li-hua ZHANG ◽  
Jing-ting ZHANG ◽  
...  
Keyword(s):  
Winter Wheat ◽  
North China Plain ◽  
North China ◽  
Water Saving ◽  
Wheat Production ◽  
The North ◽  
The North China Plain
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