Stream Nitrogen Sources Apportionment and Pollution Control Scheme Development in an Agricultural Watershed in Eastern China

2013 ◽  
Vol 52 (2) ◽  
pp. 450-466 ◽  
Author(s):  
Dingjiang Chen ◽  
Jun Lu ◽  
Hong Huang ◽  
Mei Liu ◽  
Dongqin Gong ◽  
...  
2019 ◽  
Author(s):  
Jia Xing ◽  
Dian Ding ◽  
Shuxiao Wang ◽  
Zhaoxin Dong ◽  
James T. Kelly ◽  
...  

Abstract. Designing effective control policies requires efficient quantification of the nonlinear response of air pollution to emissions. However, neither the current observable indicators nor the current indicators based on response-surface modeling (RSM) can fulfill this requirement. Therefore, this study developed new observable RSM-based indicators and applied them to ambient fine particulate matter (PM2.5) and ozone (O3) pollution control in China. The performance of these observable indicators in predicting O3 and PM2.5 chemistry was compared with that of the current RSM-based indicators. H2O2 × HCHO/NO3 and total ammonia ratio, which exhibited the best performance among indicators, were proposed as new observable O3- and PM2.5-chemistry indicators, respectively. Strong correlations between RSM-based and traditional observable indicators suggested that a combination of ambient concentrations of certain chemical species can serve as an indicator to approximately quantify the response of O3 and PM2.5 to changes in precursor emissions. The observable RSM-based indicator for O3 (observable peak ratio) effectively captured the strong NOx-saturated regime in January and the NOx-limited regime in July, as well as the strong NOx-saturated regime in northern and eastern China and their key regions, including the Yangtze River Delta and Pearl River Delta. The observable RSM-based indicator for PM2.5 (observable flex ratio) also captured strong NH3-poor condition in January and NH3-rich condition in April and July, as well as NH3-rich in northern and eastern China and the Sichuan Basin. Moreover, analysis of these newly developed observable response indicators suggested that the simultaneous control of NH3 and NOx emissions produces greater benefits in provinces with higher PM2.5 exposure by up to 12 µg m−3 PM2.5 per 10 % NH3 reduction compared with NOx control only. Control of volatile organic compound (VOC) emissions by as much as 40 % of NOx controls is necessary to obtain the co-benefits of reducing both O3 and PM2.5 exposure at the national level when controlling NOx emissions. However, the VOC-to-NOx ratio required to maintain benefits varies significantly from 0 to 1.2 in different provinces, suggesting that a more localized control strategy should be designed for each province.


2019 ◽  
Vol 251 ◽  
pp. 185-192 ◽  
Author(s):  
Qitao Xiao ◽  
Zhenghua Hu ◽  
Congsheng Fu ◽  
Hang Bian ◽  
Xuhui Lee ◽  
...  

2010 ◽  
Vol 106 (3) ◽  
pp. 489-501 ◽  
Author(s):  
Xiaoyuan Yan ◽  
Zucong Cai ◽  
Rong Yang ◽  
Chaopu Ti ◽  
Yongqiu Xia ◽  
...  

2008 ◽  
Vol 87 (2) ◽  
pp. 169-179 ◽  
Author(s):  
Nengwang Chen ◽  
Huasheng Hong ◽  
Luoping Zhang ◽  
Wenzhi Cao

2013 ◽  
Vol 409-410 ◽  
pp. 208-213
Author(s):  
Mei Liu ◽  
Wen Qian Shi ◽  
Jun Lu

According to many uncertain problems of river eutrophication, a Bayesian hierarchical model was established to predict water quality. We applied the hierarchical method to assess river water quality in an agricultural watershed in eastern China. The procedure followed was developing a hierarchical model relating eutrophication response - the level of chlorophyll (Chla). Through Principal Component Analysis (PCA), five factors strong related with Chla were selected to establish Bayesian hierarchical model to predict the water quality. Results showed that Bayesian hierarchical model was very realistic. Furthermore, in Bayesian perspective, predictions expressed as probabilities, rather than a single value, involving more uncertainty information, can be essential to environmental management and decision-making.


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