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Peng Jiang
Department of Industrial Engineering and Engineering Management, Business School, Sichuan University, Chengdu 610064, China

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Journal article
Published: 23 August 2021 in Journal of Cleaner Production
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Waste segregation, recycling and reduction have been prioritised in the Circular Economy transition of household waste management to reduce environmental impacts. With digitalisation and innovation developments in waste management, residents become more active on waste management-related social media platforms. However, there is still needed a tangible analysis of resident engagement (e.g. user comments and interactions) and related sentiment changes on such platforms to enhance waste management and ease the environmental burden at source. This study develops an integrated solution to analyse resident engagement by leveraging statistical analysis and text-mining methods. Four interrelated components are incorporated in the solution: population behaviour quantification, sentiment analysis and dynamics, popular concerns and probability distribution fitting, and rule-based managerial insight identification. The novel solution is applied to a real-world case study on a subscription account related to waste management in Shanghai. This research produces several major observations based on the studied case: (i) The resident engagement Monday-to-Thursday was more active than Friday-to-Sunday. (ii) Compared to 2018, the resident engagement by commenting on online posts was elevated by 107.1% in 2019 when Shanghai introduced a new management policy. Meanwhile, the yearly resource-type waste collection was increased by 114.5% in 2019. (iii) It took approximately one year to recover positive sentiments in user comments after introducing the policy. However, the comments with negative sentiments assisted in improving waste management. (iv) The best-fitted negative binomial distribution of the number of votes for user comments could guarantee the managerial insight identification from the minority of comments with popular concerns.

ACS Style

Peng Jiang; Jieyu Zhou; Yee Van Fan; Jiří Jaromír Klemeš; Meimei Zheng; Petar Sabev Varbanov. Data analysis of resident engagement and sentiments in social media enables better household waste segregation and recycling. Journal of Cleaner Production 2021, 319, 128809 .

AMA Style

Peng Jiang, Jieyu Zhou, Yee Van Fan, Jiří Jaromír Klemeš, Meimei Zheng, Petar Sabev Varbanov. Data analysis of resident engagement and sentiments in social media enables better household waste segregation and recycling. Journal of Cleaner Production. 2021; 319 ():128809.

Chicago/Turabian Style

Peng Jiang; Jieyu Zhou; Yee Van Fan; Jiří Jaromír Klemeš; Meimei Zheng; Petar Sabev Varbanov. 2021. "Data analysis of resident engagement and sentiments in social media enables better household waste segregation and recycling." Journal of Cleaner Production 319, no. : 128809.

Journal article
Published: 13 July 2021 in Renewable and Sustainable Energy Reviews
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Challenges of high energy efficiency, water saving, low-carbon emissions, waste management and food saving have been considerable pressures on both regional and global sustainable development. This paper reviews the water-energy extended nexuses (e.g. food, greenhouse gases, waste, pollution, land and others) from the perspective of relationship and practicability in relieving the challenges towards environmentally-related sustainable development goals. A specific issue identified is that with the popularity of “nexus” and extension beyond resources nexus, the positioning and identity of nexuses become ambiguous. In most cases, nexus is a more attractively sounding term to replace specific expressions such as multi-criteria optimisation, trade-offs, correlation/relationship, input-output assessment, material flow analysis, and integrated design. The methodologies (e.g. input-output analysis and life cycle assessment) entail needing to be adequately integrated or expanded for diverse water-energy extended nexuses. It is crucial for evaluating resource flows in multiple regions and sectors and assessing the associated environment-economic impacts. A standardised understanding like establishing life cycle assessment and even more quantified footprints could ensure that the nexus would not fall as the group of a buzzword and contribute to sustainable development goals. This study serves as a stepping stone to establish quantified characteristics or components as eligibility to classify as nexus approaches and studies.

ACS Style

Xue-Chao Wang; Peng Jiang; Lan Yang; Yee Van Fan; Jiří Jaromír Klemeš; Yutao Wang. Extended water-energy nexus contribution to environmentally-related sustainable development goals. Renewable and Sustainable Energy Reviews 2021, 150, 111485 .

AMA Style

Xue-Chao Wang, Peng Jiang, Lan Yang, Yee Van Fan, Jiří Jaromír Klemeš, Yutao Wang. Extended water-energy nexus contribution to environmentally-related sustainable development goals. Renewable and Sustainable Energy Reviews. 2021; 150 ():111485.

Chicago/Turabian Style

Xue-Chao Wang; Peng Jiang; Lan Yang; Yee Van Fan; Jiří Jaromír Klemeš; Yutao Wang. 2021. "Extended water-energy nexus contribution to environmentally-related sustainable development goals." Renewable and Sustainable Energy Reviews 150, no. : 111485.

Review article
Published: 06 July 2021 in Renewable and Sustainable Energy Reviews
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The COVID-19 pandemic developed the severest public health event in recent history. The first stage for defence has already been documented. This paper moves forward to contribute to the second stage for offensive by assessing the energy and environmental impacts related to vaccination. The vaccination campaign is a multidisciplinary topic incorporating policies, population behaviour, planning, manufacturing, materials supporting, cold-chain logistics and waste treatment. The vaccination for pandemic control in the current phase is prioritised over other decisions, including energy and environmental issues. This study documents that vaccination should be implemented in maximum sustainable ways. The energy and related emissions of a single vaccination are not massive; however, the vast numbers related to the worldwide production, logistics, disinfection, implementation and waste treatment are reaching significant figures. The preliminary assessment indicates that the energy is at the scale of ~1.08 × 1010 kWh and related emissions of ~5.13 × 1012 gCO2eq when embedding for the envisaged 1.56 × 1010 vaccine doses. The cold supply chain is estimated to constitute 69.8% of energy consumption of the vaccination life cycle, with an interval of 26–99% depending on haul distance. A sustainable supply chain model that responds to an emergency arrangement, considering equality as well, should be emphasised to mitigate vaccination's environmental footprint. This effort plays a critical role in preparing for future pandemics, both environmentally and socially. Research in exploring sustainable single-use or reusable materials is also suggested to be a part of the plans. Diversified options could offer higher flexibility in mitigating environmental footprint even during the emergency and minimise the potential impact of material disruption or dependency.

ACS Style

Jiří Jaromír Klemeš; Peng Jiang; Yee Van Fan; Awais Bokhari; Xue-Chao Wang. COVID-19 pandemics Stage II – Energy and environmental impacts of vaccination. Renewable and Sustainable Energy Reviews 2021, 150, 111400 -111400.

AMA Style

Jiří Jaromír Klemeš, Peng Jiang, Yee Van Fan, Awais Bokhari, Xue-Chao Wang. COVID-19 pandemics Stage II – Energy and environmental impacts of vaccination. Renewable and Sustainable Energy Reviews. 2021; 150 ():111400-111400.

Chicago/Turabian Style

Jiří Jaromír Klemeš; Peng Jiang; Yee Van Fan; Awais Bokhari; Xue-Chao Wang. 2021. "COVID-19 pandemics Stage II – Energy and environmental impacts of vaccination." Renewable and Sustainable Energy Reviews 150, no. : 111400-111400.

Journal article
Published: 01 June 2021 in Journal of Cleaner Production
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Cyanobacterial blooms under global warming are increasing worldwide, producing emerging contaminants, which threaten the health of human beings and aquatic ecosystems. The health burdens warrant the development of a useful risk-assessment tool and a holistic preventive-control scheme to prevent cyanobacterial blooms. This paper aims to integrate cyanobacterial risk assessment and risk preventive control by investigating the relationships amongst cyanobacterial blooms and multi-dimensional influencing variables. Two challenges hinder such a task. First, the time-series variations in cyanobacteria and influencing variables are uncertain and nonlinear. Second, there rarely exists an explicit modelling framework for integrating cyanobacterial risk assessment and risk preventive control. This study builds an extended Bayesian network model and proposes an integrated framework with functions of assessment, inference, preventive control, and visualisation of the risk of cyanobacterial blooms. Field data from a tropical lake are used to evaluate the model and framework. The proposed model achieves better performance than the seven models in comparison. The cyanobacterial risk is anticipated to increase by 38.5% under global warming. On the contrary, guided by the model and framework, the risk could be reduced by about 60% by taking the identified risk preventive control scheme. The cyanobacterial risk prevention would reduce aquatic emerging contaminants in drinking and recreational water sources.

ACS Style

Peng Jiang; Xiao Liu; Jingjie Zhang; Shu Harn Te; Karina Yew-Hoong Gin; Yee Van Fan; Jiří Jaromír Klemeš; Christine A. Shoemaker. Cyanobacterial risk prevention under global warming using an extended Bayesian network. Journal of Cleaner Production 2021, 312, 127729 .

AMA Style

Peng Jiang, Xiao Liu, Jingjie Zhang, Shu Harn Te, Karina Yew-Hoong Gin, Yee Van Fan, Jiří Jaromír Klemeš, Christine A. Shoemaker. Cyanobacterial risk prevention under global warming using an extended Bayesian network. Journal of Cleaner Production. 2021; 312 ():127729.

Chicago/Turabian Style

Peng Jiang; Xiao Liu; Jingjie Zhang; Shu Harn Te; Karina Yew-Hoong Gin; Yee Van Fan; Jiří Jaromír Klemeš; Christine A. Shoemaker. 2021. "Cyanobacterial risk prevention under global warming using an extended Bayesian network." Journal of Cleaner Production 312, no. : 127729.

Journal article
Published: 05 May 2021 in Energy Policy
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The European Union (EU) has the world's most extensive regional power trade, making it essential for the EU environmental energy policies. Understanding the nexus amongst water, power and CO2 emissions is essential for sustainable water and energy resource management. Although a number of related studies on the nexus have been conducted, integrating virtual water and CO2 emission footprints for the power sector requires further attention. The current study analyses the virtual water and CO2 emissions embodied in the power supply, demand and regional trade. A network model is developed to track the virtual water and CO2 emissions of the inter-regional power trade for the case of EU-27 countries in 2017. The total virtual CO2 emissions and the embodied virtual water in the EU inter-regional power trade are estimated as 7.0 × 104 t CO2 and 5.6 × 108 m3, with a hydropower contribution of 37.8%. The largest virtual water and CO2 emissions exporters are identified by France (8.8 × 107 m3) and Germany (2 × 104 t), whilst the largest virtual CO2 importer is Austria (1 × 104 t). The identified synergy of climate mitigation and water scarcity provides a benchmark for policymakers to develop strategies for sustainable power development considering the virtual footprint in trade flow simultaneously.

ACS Style

Like Wang; Yee Van Fan; Peng Jiang; Petar Sabev Varbanov; Jiří Jaromír Klemeš. Virtual water and CO2 emission footprints embodied in power trade: EU-27. Energy Policy 2021, 155, 112348 .

AMA Style

Like Wang, Yee Van Fan, Peng Jiang, Petar Sabev Varbanov, Jiří Jaromír Klemeš. Virtual water and CO2 emission footprints embodied in power trade: EU-27. Energy Policy. 2021; 155 ():112348.

Chicago/Turabian Style

Like Wang; Yee Van Fan; Peng Jiang; Petar Sabev Varbanov; Jiří Jaromír Klemeš. 2021. "Virtual water and CO2 emission footprints embodied in power trade: EU-27." Energy Policy 155, no. : 112348.

Review
Published: 14 January 2021 in International Journal of Environmental Research and Public Health
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The coronavirus disease 2019 (COVID-19) pandemic has magnified the insufficient readiness of humans in dealing with such an unexpected occurrence. During the pandemic, sustainable development goals have been hindered severely. Various observations and lessons have been highlighted to emphasise local impacts on a single region or single sector, whilst the holistic and coupling impacts are rarely investigated. This study overviews the structural changes and spatial heterogeneities of changes in healthcare, energy and environment, and offers perspectives for the in-depth understanding of the COVID-19 impacts on the three sectors, in particular the cross-sections of them. Practical observations are summarised through the broad overview. A novel concept of the healthcare–energy–environment nexus under climate change constraints is proposed and discussed, to illustrate the relationships amongst the three sectors and further analyse the dynamics of the attention to healthcare, energy and environment in view of decision-makers. The society is still on the way to understanding the impacts of the whole episode of COVID-19 on healthcare, energy, environment and beyond. The raised nexus thinking could contribute to understanding the complicated COVID-19 impacts and guiding sustainable future planning.

ACS Style

Peng Jiang; Jiří Klemeš; Yee Fan; Xiuju Fu; Yong Bee. More is Not Enough: A Deeper Understanding of the COVID-19 Impacts on Healthcare, Energy and Environment is Crucial. International Journal of Environmental Research and Public Health 2021, 18, 684 .

AMA Style

Peng Jiang, Jiří Klemeš, Yee Fan, Xiuju Fu, Yong Bee. More is Not Enough: A Deeper Understanding of the COVID-19 Impacts on Healthcare, Energy and Environment is Crucial. International Journal of Environmental Research and Public Health. 2021; 18 (2):684.

Chicago/Turabian Style

Peng Jiang; Jiří Klemeš; Yee Fan; Xiuju Fu; Yong Bee. 2021. "More is Not Enough: A Deeper Understanding of the COVID-19 Impacts on Healthcare, Energy and Environment is Crucial." International Journal of Environmental Research and Public Health 18, no. 2: 684.

Journal article
Published: 21 November 2020 in Resources, Conservation and Recycling
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The building of new waste treatment plants has not been closely following the Circular Economy (CE) hierarchy, and the incurred cost and social acceptance have been challenging. Integrated regional waste management by waste trading can offer the sharing of resources to achieve a mutually beneficial system in CE transition. This study aims to minimise the environmental footprints, with the consideration of economic feasibility, in integrated regional waste management by developing an extended Pinch Analysis-based targeting method. The proposed graphical decision-support method is applied to a case study where the waste trading amongst Central Europe (Austria, the Czech Republic, Germany, Poland, and Slovakia) is considered. A monthly waste trading network is identified with Germany, and Austria serves as the country with a surplus of waste treatment capacity. The pessimistic estimation indicated that the GHG emission of the waste trading design is 0.311 t CO2eq/t of waste, where the GHG emission of 1 t waste is reduced by 20 kg – 30 kg compared to the baseline scenario. The assessment suggested that when the amount of waste to be transported by lorry is >5 t and the transport distance to the incineration plant compared to the landfill is less than ~500 – 940 km, waste trading for recovery offers a lower net GHG emission. However, to prevent pollution haven and to consider the economic feasibility, the landfill fees have to be increased significantly. The developed method can identify integrated waste management network for different levels of administrative division to minimise environmental footprints.

ACS Style

Yee Van Fan; Peng Jiang; Jiří Jaromír Klemeš; Peng Yen Liew; Chew Tin Lee. Integrated regional waste management to minimise the environmental footprints in circular economy transition. Resources, Conservation and Recycling 2020, 168, 105292 .

AMA Style

Yee Van Fan, Peng Jiang, Jiří Jaromír Klemeš, Peng Yen Liew, Chew Tin Lee. Integrated regional waste management to minimise the environmental footprints in circular economy transition. Resources, Conservation and Recycling. 2020; 168 ():105292.

Chicago/Turabian Style

Yee Van Fan; Peng Jiang; Jiří Jaromír Klemeš; Peng Yen Liew; Chew Tin Lee. 2020. "Integrated regional waste management to minimise the environmental footprints in circular economy transition." Resources, Conservation and Recycling 168, no. : 105292.

Articles
Published: 11 November 2020 in International Journal of Production Research
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ACS Style

Peng Jiang; Yibin Huang; Xiao Liu. Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model. International Journal of Production Research 2020, 1 -18.

AMA Style

Peng Jiang, Yibin Huang, Xiao Liu. Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model. International Journal of Production Research. 2020; ():1-18.

Chicago/Turabian Style

Peng Jiang; Yibin Huang; Xiao Liu. 2020. "Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model." International Journal of Production Research , no. : 1-18.

Perspective
Published: 30 September 2020 in International Journal of Energy Research
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ACS Style

Jiří Jaromír Klemeš; Yee Van Fan; Peng Jiang. COVID ‐19 pandemic facilitating energy transition opportunities. International Journal of Energy Research 2020, 45, 3457 -3463.

AMA Style

Jiří Jaromír Klemeš, Yee Van Fan, Peng Jiang. COVID ‐19 pandemic facilitating energy transition opportunities. International Journal of Energy Research. 2020; 45 (3):3457-3463.

Chicago/Turabian Style

Jiří Jaromír Klemeš; Yee Van Fan; Peng Jiang. 2020. "COVID ‐19 pandemic facilitating energy transition opportunities." International Journal of Energy Research 45, no. 3: 3457-3463.

Journal article
Published: 02 September 2020 in Resources, Conservation and Recycling
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Household waste segregation and recycling is ranked at a high priority of the waste management hierarchy. Its management remains a great challenge due to the high dependency on social behaviours. The integration of Internet of Things (IoT) and subscription accounts on social media platforms related to household waste management could be an effective and environmentally friendly publicity approach than traditional publicity via posters and newspapers. However, there is a paucity of literature on measuring social media publicity in household waste management, which brings challenges for practitioners to characterise and improve this publicity pathway. In this study, under an integrated framework, data mining approaches are employed or extended for multidimensional publicity analytics using the data of online footprints of propagandist and users. A real-world case study based on a subscription account on the WeChat platform, Shanghai Green Account, is analysed to reveal useful insights for personalised improvements of household waste management. This study suggests that the current publicity related to household waste management leans towards propagandist-centred in both timing and topic dimensions. The identified timing, which has high user engagement, is 12:00–13:00 and 21:00–22:00 on Thursday. The overall relative publicity quality of historical posts is calculated as 0.95. Average user engagement under the macro policy in Shanghai was elevated by 138.5% from 2018 to 2019, during which the collections of biodegradable food waste and recyclable waste were elevated by 88.8% and 431.8%. Intelligent decision support by publicity analytics could enhance household waste management through effective communication.

ACS Style

Peng Jiang; Yee Van Fan; Jiří Jaromír Klemeš. Data analytics of social media publicity to enhance household waste management. Resources, Conservation and Recycling 2020, 164, 105146 -105146.

AMA Style

Peng Jiang, Yee Van Fan, Jiří Jaromír Klemeš. Data analytics of social media publicity to enhance household waste management. Resources, Conservation and Recycling. 2020; 164 ():105146-105146.

Chicago/Turabian Style

Peng Jiang; Yee Van Fan; Jiří Jaromír Klemeš. 2020. "Data analytics of social media publicity to enhance household waste management." Resources, Conservation and Recycling 164, no. : 105146-105146.

Journal article
Published: 27 August 2020 in Energy
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The still escalating COVID-19 pandemic also has a substantial impact on energy structure, requirements and related emissions. The consumption is unavoidable and receives a lower priority in the critical situation. However, as the pandemic continues, the impacts on energy and environment should be assessed and possibly reduced. This study aims to provide an overview of invested energy sources and environmental footprints in fighting the COVID-19. The required energy and resources consumption of Personal Protection Equipment (PPE) and testing kits have been discussed. The protecting efficiency returned on environmental footprint invested for masks has been further explored. The main observation pinpointed is that with a proper design standard, material selection and user guideline, reusable PPE could be an effective option with lower energy consumption/environmental footprint. Additional escalated energy consumption for aseptic and disinfection has been assessed. This includes the energy stemming from emergency and later managed supply chains. The outcomes emphasised that diversifying solutions to achieve the needed objective is a vital strategy to improve the susceptibility and provide higher flexibility in minimising the environmental footprints. However, more comprehensive research proof for the alternative solution (e.g. reusable option) towards low energy consumption without compromise on the effectiveness should be offered and advocated.

ACS Style

Jiří Jaromír Klemeš; Yee Van Fan; Peng Jiang. The energy and environmental footprints of COVID-19 fighting measures – PPE, disinfection, supply chains. Energy 2020, 211, 118701 -118701.

AMA Style

Jiří Jaromír Klemeš, Yee Van Fan, Peng Jiang. The energy and environmental footprints of COVID-19 fighting measures – PPE, disinfection, supply chains. Energy. 2020; 211 ():118701-118701.

Chicago/Turabian Style

Jiří Jaromír Klemeš; Yee Van Fan; Peng Jiang. 2020. "The energy and environmental footprints of COVID-19 fighting measures – PPE, disinfection, supply chains." Energy 211, no. : 118701-118701.

Journal article
Published: 26 August 2020 in Science of The Total Environment
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COVID-19 has been sweeping the world. The overall number of infected persons has been increased from 5 M in March 2020 to over 22 M in August 2020 and growing, which seems not to get its peak at the current stage. This has contributed to waste generation and different phases of challenges in waste management practices. The impacts including change in waste amount, composition, timing/frequency (temporal), distribution (spatial) and risk, which affects the handling and treatment practices. Recent impacts, challenges and developments on waste management in the response of COVID-19 have been assessed in this update. Singapore, the cities of Shanghai in China and Brno in the Czech Republic (a member state of the European Union), representing different pandemic development situation and also various cultural attitudes, are specifically analysed and discussed with current data. However, it should be noted that it is still fast developing. A varying trend in term of the waste amount is identified. Shanghai is showing a ~23% decline in household waste amount; however, Singapore is showing a ~3% increase, and Brno is showing a ~1% increase in household waste amount but ~40% decline in business and industrial waste. Manual sorting and recycling have been reported as restricted due to safety precaution. This is supported by the interview communication with ZEVO SAKO (the largest incineration plant in the Czech Republic). This study highlighted that the practices or measures at each place could serve as a guideline and reference. However, adaption is required according to the geographical and socioeconomic factors.

ACS Style

Yee Van Fan; Peng Jiang; Milan Hemzal; Jiří Jaromír Klemeš. An update of COVID-19 influence on waste management. Science of The Total Environment 2020, 754, 142014 -142014.

AMA Style

Yee Van Fan, Peng Jiang, Milan Hemzal, Jiří Jaromír Klemeš. An update of COVID-19 influence on waste management. Science of The Total Environment. 2020; 754 ():142014-142014.

Chicago/Turabian Style

Yee Van Fan; Peng Jiang; Milan Hemzal; Jiří Jaromír Klemeš. 2020. "An update of COVID-19 influence on waste management." Science of The Total Environment 754, no. : 142014-142014.

Journal article
Published: 19 August 2020 in Journal of Cleaner Production
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Coronavirus disease-2019 (COVID-19) poses a significant threat to the population and urban sustainability worldwide. The surge mitigation is complicated and associates many factors, including the pandemic status, policy, socioeconomics and resident behaviours. Modelling and analytics with spatial-temporal big urban data are required to assist the mitigation of the pandemic. This study proposes a novel perspective to analyse the spatial-temporal potential exposure risk of residents by capturing human behaviours based on spatial-temporal car park availability data. Near real-time data from 1,904 residential car parks in Singapore, a classical megacity, are collected to analyse car mobility and its spatial-temporal heat map. The implementation of the circuit breaker, a COVID-19 measure, in Singapore has reduced the mobility and heat (daily frequency of mobility) significantly at about 30.0%. It contributes to a 44.3%–55.4% reduction in the transportation-related air emissions under two scenarios of travelling distance reductions. Urban sustainability impacts in both environment and economy are discussed. The spatial-temporal potential exposure risk mapping with space-time interactions is further investigated via an extended Bayesian spatial-temporal regression model. The maximal reduction rate of the defined potential exposure risk lowers to 37.6% by comparison with its peak value. The big data analytics of changes in car mobility behaviour and the resultant potential exposure risks can provide insights to assist in (a) designing a flexible circuit breaker exit strategy, (b) precise management via identifying and tracing hotspots on the mobility heat map, and (c) making timely decisions by fitting curves dynamically in different phases of COVID-19 mitigation. The proposed method has the potential to be used by decision-makers worldwide with available data to make flexible regulations and planning.

ACS Style

Peng Jiang; Xiuju Fu; Yee Van Fan; Jiří Jaromír Klemeš; Piao Chen; Stefan Ma; Wanbing Zhang. Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour. Journal of Cleaner Production 2020, 279, 123673 -123673.

AMA Style

Peng Jiang, Xiuju Fu, Yee Van Fan, Jiří Jaromír Klemeš, Piao Chen, Stefan Ma, Wanbing Zhang. Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour. Journal of Cleaner Production. 2020; 279 ():123673-123673.

Chicago/Turabian Style

Peng Jiang; Xiuju Fu; Yee Van Fan; Jiří Jaromír Klemeš; Piao Chen; Stefan Ma; Wanbing Zhang. 2020. "Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour." Journal of Cleaner Production 279, no. : 123673-123673.

Other
Published: 05 August 2020 in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects
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The plastics are becoming one of the most discussed topics in media and research. They have been branded sometimes as evil, which has to be replaced, in some cases at any cost. However, an equitable analysis and assessment are needed comparing all pros and cons based on environmental footprints quantification with a complete life cycle assessment. These should include assessment of possible health risks, consumed energy, released emissions and effluents, as well as consumption of raw materials, water and dealing with the wastewater. The assessment of recyclability, reprocessing and environmental burden of disposal phases are also needed. This presented work tends to contribute to the discussion of what recommendations should be developed to the industry and business to minimize the environmental impacts. A novel Plastic Waste Footprint is proposed to understand the net potential impacts of plastic and to facilitate the decision making for plastic replacement. This study highlighted that plastic could be a friend if the Circular Economy (CE) is appropriately followed. Reduction (refrain, redesign/reduce, reuse, repair, refurbish, remanufacture, repurpose), recycle and recovery (no leaking into the ocean or other streams) play the decisive roles to minimize and recover the embodied energy, promoting sustainable plastic values chain. Policy to regulate/encourage manufacturers toward sustainable practice (taxation, end of life collection, an incentive of using secondary raw materials) and education (refrain, reuse, separation and recycle) on the potential users are important from not evolving the plastic from friend with high functionality to foe.

ACS Style

Jiří Jaromír Klemeš; Yee Van Fan; Peng Jiang. Plastics: friends or foes? The circularity and plastic waste footprint. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 2020, 43, 1549 -1565.

AMA Style

Jiří Jaromír Klemeš, Yee Van Fan, Peng Jiang. Plastics: friends or foes? The circularity and plastic waste footprint. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 2020; 43 (13):1549-1565.

Chicago/Turabian Style

Jiří Jaromír Klemeš; Yee Van Fan; Peng Jiang. 2020. "Plastics: friends or foes? The circularity and plastic waste footprint." Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 43, no. 13: 1549-1565.

Journal article
Published: 27 April 2020 in Renewable and Sustainable Energy Reviews
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The COVID-19 pandemic has had growing environmental consequences related to plastic use and follow-up waste, but more urgent health issues have far overshadowed the potential impacts. This paper gives a prospective outlook on how the disruption caused by COVID-19 can act as a catalyst for short-term and long-term changes in plastic waste management practices throughout the world. The impact of the pandemic and epidemic following through the life cycles of various plastic products, particularly those needed for personal protection and healthcare, is assessed. The energy and environmental footprints of these product systems have increased rapidly in response to the surge in the number of COVID-19 cases worldwide, while critical hazardous waste management issues are emerging due to the need to ensure destruction of residual pathogens in household and medical waste. The concept of Plastic Waste Footprint (PWF) is proposed to capture the environmental footprint of a plastic product throughout its entire life cycle. Emerging challenges in waste management during and after the pandemic are discussed from the perspective of novel research and environmental policies. The sudden shift in waste composition and quantity highlights the need for a dynamically reponsive waste management system. Six future research directions are suggested to mitigate the potential impacts of the pandemic on waste management systems.

ACS Style

Jiří Jaromír Klemeš; Yee Van Fan; Raymond R. Tan; Peng Jiang. Minimising the present and future plastic waste, energy and environmental footprints related to COVID-19. Renewable and Sustainable Energy Reviews 2020, 127, 109883 -109883.

AMA Style

Jiří Jaromír Klemeš, Yee Van Fan, Raymond R. Tan, Peng Jiang. Minimising the present and future plastic waste, energy and environmental footprints related to COVID-19. Renewable and Sustainable Energy Reviews. 2020; 127 ():109883-109883.

Chicago/Turabian Style

Jiří Jaromír Klemeš; Yee Van Fan; Raymond R. Tan; Peng Jiang. 2020. "Minimising the present and future plastic waste, energy and environmental footprints related to COVID-19." Renewable and Sustainable Energy Reviews 127, no. : 109883-109883.

Journal article
Published: 01 February 2020 in Waste Management
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Waste sorting at the source is a vital strategy of waste management and to improve urban sustainability. If the strategy is implemented by relying solely on publicity and civic awareness, the impact is less significant. Proactive measures, such as policy regulations, supervisory guidance, and stimulating incentives, play essential roles for better management. The unknown waste-dumping behaviour of residents is a great challenge for decision-makers to allocate resources for waste-collection operations and to refine regulations. Traditional behaviour analysis methods such as questionnaire surveys and simulation methods have limitations considering the population size and the complexity of individual behaviour. This study aims to design a data-driven analytical framework to analyse household waste-dumping behaviour and facilitate policy regulations by using the Internet of Things (IoT) and data mining technologies. The analytical framework is further developed into a four-step management cycle. A case study in Shanghai is employed to demonstrate the effectiveness of the analytical framework and management cycle. The results of behaviour analyses reveal that (1) waste-dumping frequency is high in the evening but negligible in the early afternoon; (2) compared to working days, peak-value time at weekends occurs later in the morning and earlier in the evening; (3) residents require longer waste-dumping time windows than those empirically recommended by administrators. Managerial insights and decision support based on these research results have been presented for decision-makers to guide operations management and facilitate policy regulations.

ACS Style

Peng Jiang; Yee Van Fan; Jieyu Zhou; Meimei Zheng; Xiao Liu; Jiří Jaromír Klemeš. Data-driven analytical framework for waste-dumping behaviour analysis to facilitate policy regulations. Waste Management 2020, 103, 285 -295.

AMA Style

Peng Jiang, Yee Van Fan, Jieyu Zhou, Meimei Zheng, Xiao Liu, Jiří Jaromír Klemeš. Data-driven analytical framework for waste-dumping behaviour analysis to facilitate policy regulations. Waste Management. 2020; 103 ():285-295.

Chicago/Turabian Style

Peng Jiang; Yee Van Fan; Jieyu Zhou; Meimei Zheng; Xiao Liu; Jiří Jaromír Klemeš. 2020. "Data-driven analytical framework for waste-dumping behaviour analysis to facilitate policy regulations." Waste Management 103, no. : 285-295.

Journal article
Published: 25 December 2019 in IFAC-PapersOnLine
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We consider a manufacturer-retailer supply chain which faces a high demand uncertainty. To mitigate the overage and underage costs caused by the high demand uncertainty, an emergency order is provided by the manufacturer to the retailer. However, due to the limited capacity, the manufacturer would impose a maximum supply commitment on the emergency order. The manufacturer needs to make more initial production or reserve capacity in advance for the supply commitment for the retailer’s emergency order. We find that when the emergency order opportunity is provided, the manufacturer may be worse off although the retailer would be not.

ACS Style

Meimei Zheng; Cunwu Sun; Peng Jiang. Capacitated Supply Chain with Demand Uncertainty. IFAC-PapersOnLine 2019, 52, 767 -772.

AMA Style

Meimei Zheng, Cunwu Sun, Peng Jiang. Capacitated Supply Chain with Demand Uncertainty. IFAC-PapersOnLine. 2019; 52 (13):767-772.

Chicago/Turabian Style

Meimei Zheng; Cunwu Sun; Peng Jiang. 2019. "Capacitated Supply Chain with Demand Uncertainty." IFAC-PapersOnLine 52, no. 13: 767-772.

Journal article
Published: 25 December 2019 in IFAC-PapersOnLine
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Day-ahead emergency blood demand (EBD) forecasts after earthquakes play a key role in the success emergency blood operations. Demand uncertainties and limited data pose great challenges for accurate EBD forecasts. Given such challenges, we build an adaptive evolutionary support vector regression (AESVR) model to forecast daily EBD. We also build seven other potential models for comparison. Real-word case and data are used to evaluate these models. Computational results demonstrate that the AESVR generates a favorable accuracy. Ranking orders regarding accuracy and complexity of all models can provide guidance for decision-makers and practitioners to make tradeoffs according to their own preferences.

ACS Style

Peng Jiang; X. Liu; M. Zheng. Emergency Blood Demand Forecasting after Earthquakes. IFAC-PapersOnLine 2019, 52, 773 -777.

AMA Style

Peng Jiang, X. Liu, M. Zheng. Emergency Blood Demand Forecasting after Earthquakes. IFAC-PapersOnLine. 2019; 52 (13):773-777.

Chicago/Turabian Style

Peng Jiang; X. Liu; M. Zheng. 2019. "Emergency Blood Demand Forecasting after Earthquakes." IFAC-PapersOnLine 52, no. 13: 773-777.

Conference paper
Published: 01 December 2018 in 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
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Cyanobacterial blooms increasingly pose threats to ecosystems and human health. This paper is aimed to propose systematic risk pre-control schemes by understanding the complex causalities between cyanobacteria and multiple influencing variables. This research remains a challenge for three reasons. Firstly, the time-series evolution of cyanobacteria is characterized by deep uncertainties and nonlinear dynamics. Secondly, latent variables with hidden information usually exist in this kind of complex aquatic system. Thirdly, it is difficult to identify an efficient pre-control scheme that specifies variables for preferential regulation. To address these problems, we propose a latent variable structured Bayesian network model and a corresponding parameter learning algorithm. The model is tested by real-time spatio-temporal data. The computational results reveal that the proposed model demonstrates better performance in terms of inference accuracy and degree of system understanding. Based on sensitivity analysis and combination-effect analysis, a systematic risk pre-control scheme is proposed for decision-makers to prevent cyanobacterial blooms under the scenario of global warming.

ACS Style

Peng Jiang; X. Liu; Jingjie Zhang; S.H. Te; K.Y. H. Gin. Latent Variable Structured Bayesian Network for Cyanobacterial Risk Pre-control. 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) 2018, 829 -833.

AMA Style

Peng Jiang, X. Liu, Jingjie Zhang, S.H. Te, K.Y. H. Gin. Latent Variable Structured Bayesian Network for Cyanobacterial Risk Pre-control. 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). 2018; ():829-833.

Chicago/Turabian Style

Peng Jiang; X. Liu; Jingjie Zhang; S.H. Te; K.Y. H. Gin. 2018. "Latent Variable Structured Bayesian Network for Cyanobacterial Risk Pre-control." 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) , no. : 829-833.

Journal article
Published: 01 July 2017 in IFAC-PapersOnLine
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Erratic demand patterns are common in spare parts supply networks. Owing to the characteristics of nonlinear dynamics, aperiodic variations and deep uncertainties, erratic demand forecasting remains to be a challenge. This paper is devoted to forecast this type of demand in a more difficult situation where regular explanatory variables are not available and historical data are limited. To address this problem, we propose an Adaptive Autoregressive Support Vector Machine model in which: 1) autocorrelated attributes are generated from historical demand time-series data automatically; 2) the attribute dimension and the suitable nonlinear kernel mapping function are identified in a data-driven manner; and 3) key model parameters are adaptively controlled by a parallel heuristic algorithm to cope with data uncertainties and guarantee the model generalization ability. We test this model by erratic demands of heavy truck spare parts. Computational results demonstrate that the proposed model outperforms seven sound time-series forecasting models and general Support Vector Machine models.

ACS Style

P. Jiang; X. Liu; Y. Huang; Y. Yuan. An Adaptive Data-driven Model for Erratic Demand Forecasting. IFAC-PapersOnLine 2017, 50, 9020 -9025.

AMA Style

P. Jiang, X. Liu, Y. Huang, Y. Yuan. An Adaptive Data-driven Model for Erratic Demand Forecasting. IFAC-PapersOnLine. 2017; 50 (1):9020-9025.

Chicago/Turabian Style

P. Jiang; X. Liu; Y. Huang; Y. Yuan. 2017. "An Adaptive Data-driven Model for Erratic Demand Forecasting." IFAC-PapersOnLine 50, no. 1: 9020-9025.