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Gautam K, Pandey N, Yadav D, Parthasarathi R, Turner A, Anbumani S, Jha AN. Ecotoxicological impacts of landfill sites: Towards risk assessment, mitigation policies and the role of artificial intelligence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 927:171804. [PMID: 38513865 DOI: 10.1016/j.scitotenv.2024.171804] [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: 12/20/2023] [Revised: 03/14/2024] [Accepted: 03/16/2024] [Indexed: 03/23/2024]
Abstract
Waste disposal in landfills remains a global concern. Despite technological developments, landfill leachate poses a hazard to ecosystems and human health since it acts as a secondary reservoir for legacy and emerging pollutants. This study provides a systematic and scientometric review of the nature and toxicity of pollutants generated by landfills and means of assessing their potential risks. Regarding human health, unregulated waste disposal and pathogens in leachate are the leading causes of diseases reported in local populations. Both in vitro and in vivo approaches have been employed in the ecotoxicological risk assessment of landfill leachate, with model organisms ranging from bacteria to birds. These studies demonstrate a wide range of toxic effects that reflect the complex composition of leachate and geographical variations in climate, resource availability and management practices. Based on bioassay (and other) evidence, categories of persistent chemicals of most concern include brominated flame retardants, per- and polyfluorinated chemicals, pharmaceuticals and alkyl phenol ethoxylates. However, the emerging and more general literature on microplastic toxicity suggests that these particles might also be problematic in leachate. Various mitigation strategies have been identified, with most focussing on improving landfill design or leachate treatment, developing alternative disposal methods and reducing waste volume through recycling or using more sustainable materials. The success of these efforts will rely on policies and practices and their enforcement, which is seen as a particular challenge in developing nations and at the international (and transboundary) level. Artificial intelligence and machine learning afford a wide range of options for evaluating and reducing the risks associated with leachates and gaseous emissions from landfills, and various approaches tested or having potential are discussed. However, addressing the limitations in data collection, model accuracy, real-time monitoring and our understanding of environmental impacts will be critical for realising this potential.
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Affiliation(s)
- Krishna Gautam
- Ecotoxicology Laboratory, REACT Division, CSIR-Indian Institute of Toxicology Research, CRK Campus, Lucknow 226008, Uttar Pradesh, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Namrata Pandey
- Ecotoxicology Laboratory, REACT Division, CSIR-Indian Institute of Toxicology Research, CRK Campus, Lucknow 226008, Uttar Pradesh, India
| | - Dhvani Yadav
- Computational Toxicology Facility, CSIR-Indian Institute of Toxicology Research, Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India
| | - Ramakrishnan Parthasarathi
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India; Computational Toxicology Facility, CSIR-Indian Institute of Toxicology Research, Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India
| | - Andrew Turner
- School of Geography, Earth and Environmental Sciences, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK
| | - Sadasivam Anbumani
- Ecotoxicology Laboratory, REACT Division, CSIR-Indian Institute of Toxicology Research, CRK Campus, Lucknow 226008, Uttar Pradesh, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Awadhesh N Jha
- School of Biological and Marine Sciences, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK.
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Tan Q, Liu Y, Ye Q. The impact of clean development mechanism on energy-water-carbon nexus optimization in Hebei, China: A hierarchical model based discussion. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2020; 264:110441. [PMID: 32250886 DOI: 10.1016/j.jenvman.2020.110441] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 02/18/2020] [Accepted: 03/14/2020] [Indexed: 06/11/2023]
Abstract
Clean development mechanism (CDM) is an important principle in CO2 emissions mitigation since it was proposed. However, there will be a long way for the large-scale application of CDM in China, for thermal power is still in the dominant position, while renewable power is far from being competitive. In this study, a mix integer bi-level hierarchical programming model (MIBLHP) is developed to investigate the potential impact of the CDM application on the regional energy-water-carbon nexus optimization in electric power system in China. The model integrates the advantages of bi-level programming and mix integer liner programming in dealing with conflicting objectives with hierarchical and sequential decision making process and help to achieve the optimized strategies with the highest overall system satisfaction degree. Results show that CDM will play an important role in the regional energy-water-carbon nexus optimization, the MIBLHP is able to stabilize the increasing trend of system cost and make better tradeoffs between the economic and environmental goals. Optimal strategies including power generation and capacity expansion path, system cost control, CO2 emissions abatement strategies, water consumption and waste water discharge are presented. The system would reach the supreme satisfaction degrees (λ = 0.934) when the CO2 reduction level is 40%, which means that every part of the system has achieved the best condition. The proposed model has great potential in dealing with similar regional planning problems in energy-water-carbon nexus optimization.
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Affiliation(s)
- Qinliang Tan
- School of Economics and Management, North China Electric Power University, Beijing, 102206, China; Beijing Key Laboratory of Renewable Electric Power and Low Carbon Development, North China Electric Power University, Beijing, 102206, China; Research Center for Beijing Energy Development, Beijing, 102206, China.
| | - Yuan Liu
- School of Economics and Management, North China Electric Power University, Beijing, 102206, China.
| | - Qi Ye
- School of Economics and Management, North China Electric Power University, Beijing, 102206, China
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An Empirical Study on Greenhouse Gas Emission Calculations Under Different Municipal Solid Waste Management Strategies. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10051673] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The Chinese government is committed to ensuring separation of municipal solid waste (MSW), promoting the integrated development of the MSW management system with the renewable resource recovery system, and achieving construction of ecological civilization. Guided by the methods in Intergovernmental Panel on Climate Change (IPCC) guidelines, the greenhouse gas (GHG) emissions under five waste disposal scenarios in Beijing under the life cycle framework were assessed in this research. The study included collection and transportation, as well as three end disposal methods (sanitary landfill, incineration, and composting), and the emission reduction benefits of electricity generation from incineration and recycling of renewable resources were taken into account. The results show that an emission reduction benefit of 70.82% could be achieved under Scenario 5 in which kitchen waste and recyclables are sorted and recycled and the residue is incinerated, and the selection of the optimal strategy was not affected by changes in the separation rate. In addition, landfill would emit more GHG than incineration and composting. The results of this study are helpful for the government to make a decision on MSW management considering the goal of GHG emission reduction.
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