Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Targeting for carbon sequestration retrofit planning in the power generation sector for multi-period problems

Carbon constrained energy planning (CCEP) is useful to ensure that the CO2 emissions limit for a region is met through deployment of low-carbon technologies. The increased demand in energy consumption due to economic growth requires additional energy supply and generation which would subsequently increase the carbon emissions. Nevertheless, most countries are now committed to reduce carbon emission to achieve long term sustainability goals. However, the development of alternative energy sources or carbon capture and storage (CCS) initiatives for power plants entails major capital investments. This paper demonstrates how these issues may be handled using CCEP with insight- and optimisation-based targeting techniques for multi-period scenarios. Both approaches were developed recently for CCEP problems, but previous techniques were limited to single-period planning. The extensions to multi-period scenarios are demonstrated in this work with hypothetical illustrative examples, as well as a Malaysian case study. © 2013 Elsevier Ltd

Process integration approaches to optimal planning of unconventional gas field development

In recent years, the oil and gas industry has been moving to develop unconventional gas fields, which include those contaminated with high carbon dioxide (CO2) content. Typically, the CO2 has to be separated from the natural gas (NG) in offshore processing facilities (in situ) before the NG can be sent for processing at the gas plant onshore. To date, commercial-scale CO2 capture and storage (CCS) has proven to be viable mainly for CO2 that is separated from NG and subsequently injected at or near the gas field itself for permanent storage (CO2 sequestration) or utilized for the purpose of Enhanced Oil Recovery (EOR). In the case of multiple adjacent reservoirs exhibiting variations in NG quality and CO2 content, it may be necessary to have in situ CO2 removal using NG sweetening processes (e.g. membrane or amine absorption) to achieve a quality level such that the pooled NG streams meets the sales gas specification required for further processing at an onshore facility for sales. In this work, new process integration approaches are proposed to aid in the integrated planning of such joint field development projects, to rationalize the development of contaminated gas fields together with conventional sweet gas fields in meeting the required sales gas specifications of CO2 content. These approaches are based on analogous techniques previously developed for distributed effluent treatment systems and carbon capture planning for the power generation sector. A case study is used to illustrate how general insight-based policies for gas field development can be drawn from process integration perspectives. © 2016 Elsevier Ltd

An algebraic targeting approach for optimal planning of gas sweetening problem in non-conventional gas field development

An algebraic technique based on pinch analysis has been developed for the planning of non-conventional natural gas (NG) field development projects. The development of NG fields with high carbon dioxide (CO2) content has become increasingly common in the oil and gas industry. In such cases, the raw NG needs to be treated in situ for CO2 removal to meet the sales gas specifications before being sent to the onshore gas processing plants (GPPs). The captured CO2 can either be reinjected into the reservoir for permanent storage, or utilised for enhanced oil recovery (EOR), for which partial sequestration may also be achieved. These options create the need to develop systematic techniques to provide high-level decision support for field development planning. The algebraic technique developed in this work overcomes the limitations of a recently developed graphical technique (Foo et al., 2016), as it relaxes the previous simplistic assumptions on stream purity requirements. Two case studies are used to illustrate the methodology. © 2018 Institution of Chemical Engineer

Design and scheduling of CO2 enhanced oil recovery with geological sequestration operations as a strip packing problem

Copyright © 2015, AIDIC Servizi S.r.l.,. Carbon capture and storage (CCS) is an important technology that enables the reduction of CO2 emissions while allowing the use of power plants running in fossil fuels. Coupled with enhanced oil recovery (EOR), it allows additional revenues to be realized by increased oil production through the injection of captured CO2 into depleted oil reservoirs. For a system with multiple reservoirs, it is necessary to determine the amount of CO2 to be supplied and the schedule of EOR operations to be conducted. This also requires the optimal design and scheduling of each operation to maximize profitability. In this study, a mixed integer linear program (MILP) was developed using the analogy of the strip packing problem. A case study is presented to illustrate the model

Planning and scheduling of CO2 capture, utilization and storage (CCUS) operations as a strip packing problem

CO2 capture, utilization and storage (CCUS) is an important carbon management strategy that involves capturing CO2 from flue gas, transporting it, utilizing it for economically productive activities (carbon capture and utilization, or CCU), and/or permanently disposing it in non-atmospheric sinks (carbon capture and storage, or CCS). Some technologies, such as enhanced oil recovery (EOR) allow simultaneous CCUS, while other alternatives are either purely CCS (e.g., geological storage) or purely CCU (e.g., use of CO2 as a process plant feedstock). In this work, CCUS is addressed in the context of a large-scale CO2 chain that contains both CCS and CCU options. It is necessary to consider the availability of CO2 sources and sinks to develop a profitable allocation plan for such CCUS systems. Thus, a modeling framework using a geometric representation is proposed to optimize both scheduling and allocation in a CCUS system, given multiple CO2 sources and sinks. Two mixed integer linear programming (MILP) models are developed to address three important factors for planning downstream CCUS operations, i.e., scheduling of CO2 capture and EOR operations, allocation of CO2 supply for EOR operations, and source–sink matching subject to injectivity and capacity constraints. Two case studies are then solved to illustrate the two MILP models. © 2016 Institution of Chemical Engineer

CO2 allocation for scheduling enhanced oil recovery (EOR) operations with geological sequestration using discrete-time optimization

Carbon capture and storage (CCS) can be carried out in conjunction with enhanced oil recovery (EOR) to yield complementary environmental and economic gains. Thus, CCS in combination with EOR will provide economical value from incremental oil recovery besides providing source for CO2 sequestration. Given a fixed CO2 supply to be distributed to different reservoirs, it is necessary to develop an allocation model to maximize profit from EOR operations. In this study, a discrete-Time optimization model is developed subject to scheduling, capacity and flow rate constraints. A case study is presented to illustrate the model. © 2014 The Authors. Published by Elsevier Ltd