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Ji M, Liao H, Lu Z, Mao L, Zhou X, Yang F, Feng D, Wang Q. Analyzing the variation of greenhouse gas emissions from typical municipal wastewater treatment plants in Beijing during 2007-2021. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 360:124655. [PMID: 39097260 DOI: 10.1016/j.envpol.2024.124655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Revised: 07/19/2024] [Accepted: 07/31/2024] [Indexed: 08/05/2024]
Abstract
With the proposal of dual carbon goals and stringent effluent standards, the path of mitigating greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) has gained significant research attention. Here, we evaluate the impact of season, elevated standards, operating parameters, and using clean energy on GHG emissions from 8 typical WWTPs in Beijing based on 180 monthly monitoring data. Coupled with the increasing demand for wastewater treatment and 77% more chemical oxygen demand being removed in 2017, total GHG emissions from 5 WWTPs increased by 89% compared to the status quo in 2007, and after energy structure reform total GHG emissions decreased by 17% in 2021. Scenario analysis reveals that energy recovery and clean energy utilization provide 64% and 48% mitigation potential by 2050, respectively. We argue stricter effluent standard leads to GHG emissions growth in WWTPs; meanwhile, process optimization, proper temperature and targeted policies at WWTPs can reduce GHG emissions.
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Affiliation(s)
- Meichen Ji
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China
| | - Haiqing Liao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Zhibo Lu
- College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China
| | - Lianhua Mao
- Beijing Drainage Group Company, Beijing, 100044, China
| | - Xingxuan Zhou
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Fang Yang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Dongxia Feng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Qianqian Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
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Zhu M, Yu X, Chen K, Tan H, Yuan J. Spatiotemporal characteristics and driving factors of chemical oxygen demand emissions in China’s wastewater: An analysis based on spatial autocorrelation and geodetector. ECOLOGICAL INDICATORS 2024; 166:112308. [DOI: 10.1016/j.ecolind.2024.112308] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2025]
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Chen J, Ao Z, Chen H, Wang Y, Jiang M, Qi L, Liu G, Wang H. Analyzing greenhouse gas emissions and influencing factors of 247 actual wastewater treatment plants in China using emission factor and operational data integrated methods (ODIM). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:37387-37403. [PMID: 38769261 DOI: 10.1007/s11356-024-33731-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 05/16/2024] [Indexed: 05/22/2024]
Abstract
In response to China's policies on pollution control and carbon emission (CE) reductions, more stringent regulations have been implemented to evaluate CE in wastewater treatment facilities. In this study, we have analyzed CE from China's wastewater treatment plants (WWTPs) and influencing factor. Emission factor (EF) and operational data integrated methods (ODIM) were utilized to measure emissions, using data collected from 247 WWTPs over a 1-year period across seven regions in China. The average CE intensity was 0.45 kgCO2-eq/m3, affected by region, season, influent water quality, treatment processes, effluent discharge standards, and facilities. The scale effect was obvious only in the range of 2 × 105 m3/day. Underground WWTPs exhibited significantly higher CE compared to aboveground WWTPs. In summary, the assessment of CE in 247 actual WWTPs not only identifies emission reduction potential but also provides a scientific basis for formulating targeted emission reduction measures.
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Affiliation(s)
- Jiabo Chen
- Research Center for Low Carbon Technology of Water Environment, School of Environment & Natural Resources, Renmin University of China, Beijing, 100872, China
| | - Ziding Ao
- Research Center for Low Carbon Technology of Water Environment, School of Environment & Natural Resources, Renmin University of China, Beijing, 100872, China
| | - Huiling Chen
- Research Center for Low Carbon Technology of Water Environment, School of Environment & Natural Resources, Renmin University of China, Beijing, 100872, China
| | - Yanan Wang
- Research Center for Low Carbon Technology of Water Environment, School of Environment & Natural Resources, Renmin University of China, Beijing, 100872, China
| | - Mei Jiang
- Beijing Drainage Group Co., Ltd, Beijing, 100022, China
| | - Lu Qi
- Research Center for Low Carbon Technology of Water Environment, School of Environment & Natural Resources, Renmin University of China, Beijing, 100872, China
| | - Guohua Liu
- Research Center for Low Carbon Technology of Water Environment, School of Environment & Natural Resources, Renmin University of China, Beijing, 100872, China
| | - Hongchen Wang
- Research Center for Low Carbon Technology of Water Environment, School of Environment & Natural Resources, Renmin University of China, Beijing, 100872, China.
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Shang Z, Cai C, Guo Y, Huang X, Peng K, Guo R, Wei Z, Wu C, Cheng S, Liao Y, Hung CY, Liu J. Direct and indirect monitoring methods for nitrous oxide emissions in full-scale wastewater treatment plants: A critical review. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 358:120842. [PMID: 38599092 DOI: 10.1016/j.jenvman.2024.120842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 03/17/2024] [Accepted: 04/02/2024] [Indexed: 04/12/2024]
Abstract
Mitigation of nitrous oxide (N2O) emissions in full-scale wastewater treatment plant (WWTP) has become an irreversible trend to adapt the climate change. Monitoring of N2O emissions plays a fundamental role in understanding and mitigating N2O emissions. This paper provides a comprehensive review of direct and indirect N2O monitoring methods. The techniques, strengths, limitations, and applicable scenarios of various methods are discussed. We conclude that the floating chamber technique is suitable for capturing and interpreting the spatiotemporal variability of real-time N2O emissions, due to its long-term in-situ monitoring capability and high data acquisition frequency. The monitoring duration, location, and frequency should be emphasized to guarantee the accuracy and comparability of acquired data. Calculation by default emission factors (EFs) is efficient when there is a need for ambiguous historical N2O emission accounts of national-scale or regional-scale WWTPs. Using process-specific EFs is beneficial in promoting mitigation pathways that are primarily focused on low-emission process upgrades. Machine learning models exhibit exemplary performance in the prediction of N2O emissions. Integrating mechanistic models with machine learning models can improve their explanatory power and sharpen their predictive precision. The implementation of the synergy of nutrient removal and N2O mitigation strategies necessitates the calibration and validation of multi-path mechanistic models, supported by long-term continuous direct monitoring campaigns.
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Affiliation(s)
- Zhenxin Shang
- College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China
| | - Chen Cai
- College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China; Institute of Carbon Neutrality, Tongji University, Shanghai, 200092, PR China.
| | - Yanli Guo
- College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China
| | - Xiangfeng Huang
- College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China; Institute of Carbon Neutrality, Tongji University, Shanghai, 200092, PR China
| | - Kaiming Peng
- College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China; Institute of Carbon Neutrality, Tongji University, Shanghai, 200092, PR China
| | - Ru Guo
- College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China; Institute of Carbon Neutrality, Tongji University, Shanghai, 200092, PR China
| | - Zhongqing Wei
- Fuzhou Water Group Co., Ltd, Fuzhou, 350000, PR China
| | - Chenyuan Wu
- Fuzhou Water Group Co., Ltd, Fuzhou, 350000, PR China
| | - Shunjian Cheng
- Fuzhou City Construction Design & Research Institute Co., Ltd, Fuzhou, 350000, PR China
| | - Youxiang Liao
- Fuzhou City Construction Design & Research Institute Co., Ltd, Fuzhou, 350000, PR China
| | - Chih-Yu Hung
- Environment and Climate Change, 351 Saint-Joseph Blvd., 9th Floor. Gatineau, Quebec, K1A 0H3, Canada
| | - Jia Liu
- College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China; Institute of Carbon Neutrality, Tongji University, Shanghai, 200092, PR China
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