Spatial Characteristics and Driving Factors of Provincial Wastewater Discharge in China

Chen, Kunlun; Liu, Xiaoqiong; Ding, Lei; Huang, Guo‐Shing; Li, Zhigang

doi:10.3390/ijerph13121221

Cited by 38 publications

(36 citation statements)

References 32 publications

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“…The success of WWTPs in urban regions has provided abundant engineering skills and administrative experience. However, it cannot be transferred directly into the rural wastewater treatment field [3] due to the characteristics of rural wastewater, including fluctuating quality and quantity [4,5]. An analysis of rural wastewater in China from the perspectives of legislation (e.g.…”

Section: Introductionmentioning

confidence: 99%

Expected Rural Wastewater Treatment Promoted by Provincial Local Discharge Limit Legislation in China

Wang

Gong

2019

Sustainability

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Wastewater treatment in a rural region in China was undeveloped both in treatment capacity and legislation. The successful fast development of urban wastewater treatment plants (WWTPs) demonstrated the importance of legislation, including discharge limits. However, most provinces, with as high as 79.8% of the rural population in China, released no specific local discharge limits. Newly issued top-designed nationwide policy in September of 2018 by central China government required all provinces to issue their local rural wastewater discharge limits before June 2019. For the first time, this research analyzed the requirements of the newly issued policy and their inconsistence with several existing provincial limits. It proposed flexible principles for determination of discharge limits under various conditions to improve the rural residential environment as a whole. This study also proposed the use of the ratio between wastewater treatment cost and life expense to describe economic burden. Economic burden calculation for wastewater treatment in rural and urban regions was established respectively. Based on three conditions described in the new policy, the average burden for all urban residents was estimated as 0.122 ± 0.038% of the total life expense. In comparison, average nationwide rural burden was 0.087 ± 0.035% and 0.564 ± 0.196% for condition I (Total nitrogen(TN)/total phosphorus(TP) for resource recovery) and condition III (TN/TP for pollutant removal), respectively. It was also revealed that a stringent rural discharge limit lead to a Gini value as high as 0.38, indicting policy-related subsidies for rural residents should be carefully considered to ensure a balanced burden. Local discharge limit legislation and suitable financial policy is expected to promote rural wastewater treatment in China in the near future.

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Section: Introductionmentioning

confidence: 99%

Expected Rural Wastewater Treatment Promoted by Provincial Local Discharge Limit Legislation in China

Wang

Gong

2019

Sustainability

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“…The results showed that the model has higher precision than the support vector machine method and adaptive regression splines method [11]. Chen et al investigated the overall status of wastewater discharge in China to analyze its driving factors [12]. Yin et al developed a neural network model to forecast and analyze urban water-energy demand in China [13].…”

Section: Introductionmentioning

confidence: 99%

Forecasting of Wastewater Discharge and the Energy Consumption in China Based on Grey Model

Zou

2019

Mathematical Problems in Engineering

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Water pollution control is currently an important development strategy for China. Analysis and forecasting of wastewater discharge and the energy consumption are critical for this strategy. In this paper, we proposed the two time series models, namely, improved GM(0,n) model (IGM(0,n)) and optimized FGM(1,1) model (OFGM(1,1)). Two numerical experiments were used to test the validity of these models. It was indicated that the forecasting ability of two models had remarkably improved, compared to traditional FGM(1,1) and GM(0,n), respectively. We applied the two models to forecast wastewater discharge and energy consumption in China. The forecasting results have shown that the current growth rate in treated wastewater could meet the planning target of the 13th Five-Year Plan. The wastewater discharge and the energy consumption would reach 77.39 billion tons and 22.75 billion kWh, respectively, in 2020.

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“…Urban wastewater discharge is one of the main sources of surface and groundwater pollution in China [ 1 ]. It has exceeded industrial pollution and, since 1998, it has become the largest source of environmental pollution in China [ 2 , 3 ]. With economic development and the intensification of urbanization, the discharge of urban wastewater is increasing year by year.…”

Section: Introductionmentioning

confidence: 99%

“…Most past studies paid attention mainly to the simple description of the spatial variation of urban wastewater treatment efficiency without detailed analysis [ 8 ]. Others studied the spatial variations of wastewater discharge [ 3 ]. However, research that focuses on analyzing the urban wastewater treatment efficiency and its spatial variation in China is lacking.…”

Section: Introductionmentioning

confidence: 99%

Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China

Degefu

et al. 2018

IJERPH

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With the rapid economic development, water pollution has become a major concern in China. Understanding the spatial variation of urban wastewater discharge and measuring the efficiency of wastewater treatment plants are prerequisites for rationally designing schemes and infrastructures to control water pollution. Based on the input and output urban wastewater treatment data of the 31 provinces of mainland China for the period 2011–2015, the spatial variation of urban water pollution and the efficiency of wastewater treatment plants were measured and mapped. The exploratory spatial data analysis (ESDA) model and super-efficiency data envelopment analysis (DEA) combined Malmquist index were used to achieve this goal. The following insight was obtained from the results. (1) The intensity of urban wastewater discharge increased, and the urban wastewater discharge showed a spatial agglomeration trend for the period 2011 to 2015. (2) The average inefficiency of wastewater treatment plants (WWTPs) for the study period was 39.2%. The plants’ efficiencies worsened from the eastern to western parts of the country. (3) The main reasons for the low efficiency were the lack of technological upgrade and scale-up. The technological upgrade rate was −4.8%, while the scale efficiency increases as a result of scaling up was −0.2%. Therefore, to improve the wastewater treatment efficiency of the country, the provinces should work together to increase capital investment and technological advancement.

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Spatial Characteristics and Driving Factors of Provincial Wastewater Discharge in China

Cited by 38 publications

References 32 publications

Expected Rural Wastewater Treatment Promoted by Provincial Local Discharge Limit Legislation in China

Expected Rural Wastewater Treatment Promoted by Provincial Local Discharge Limit Legislation in China

Forecasting of Wastewater Discharge and the Energy Consumption in China Based on Grey Model

Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China

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