Impact Quantification Research Articles

Environmental benefits of construction and demolition debris recycling: Evidence from an Indian case study using life cycle assessment

The adversarial effects of construction and demolition (C&D) waste on the environment are on the increase. While materials such as metals, wood, glass and plastics are segregated and diverted for reuse/recycling, C&D debris consisting of concrete, bricks and tiles are landfilled in most of the countries. LCA studies have indicated a clear preference for recycling. However, it has been inferred that the environmental credits obtained in these studies were mainly from recycling of metals and wood and studies focusing on environmental impacts/benefits evaluation of C&D debris recycling is limited. This is particularly relevant in the cases of developing countries like India, where C&D debris forms a bulk of C&D waste generation. Therefore, this paper evaluates the environmental impacts of four different scenarios for managing C&D debris comprising the present (S1) and future (S2) landfilling options and recycling options without transfer stations (S3) and with transfer stations (S4). LCA according to ISO methodology is performed based on locally sourced data supplemented with Ecoinvent database. IMPACT 2002+ impact assessment method has been applied for environmental impact quantification using SimaPro software. Landfilling of C&D debris generates environmental impacts, and recycling scenarios generate environmental benefits in all 15 impact categories. Single score values of landfilling scenarios are 1.83 mPt (S1) and 2.78 mpt (S2) and that of C&D debris recycling are −2.56 mPt (S3) and −1.91 mPt (S4). The robustness of the results was shown through sensitivity analysis. Recycling remains beneficial compared to landfilling as long as the diesel and electricity consumption of C&D debris recycling facility remains less than 475% of the current consumption. Furthermore, even if the transportation distance from quarry to crushing unit is reduced to zero, recycling still remains a better alternative. The merit of considering the future landfilling scenario in the decision making has been discussed since the challenges that might be encountered in setting up new landfills are underestimated. The implications of the findings and their relevance to urban local bodies have also been discussed to help policymakers take informed decisions while facing challenges of managing C&D debris.

Impact Quantification of Decentralization in Urban Growth by Extracting Impervious Surfaces Using ISEI in Model Maker

Decentralization problems in Africa have caused some infrastructure disparity between country capitals and distant districts. In Ghana, less public investment has created a gap between implementation results and theoretical benefits. Spectral indices are a good approach to extracting impervious surfaces, which is a good method of measuring urbanization. These are restricted by complexity, sensor limitation, threshold values, and high computational time. In this study, we measure the urbanization dynamics of Wa District in Ghana by applying a proposed method of impervious surface extraction index (ISEI), to evaluate the decentralization policy using Landsat images from 1984–2018 and a single S2A data. Comparing our proposed method with five other existing indexes, ISEI provided good discriminated results between target feature and background, with pixel values ranging between 0 and +1. Other indexes produced negative values. ISEI accuracy varied from 84.62–94.00% while existing indexes varied from 73.85–90.00%. Our results also showed increased impervious surface areas of 83.26 km2, which is about 7.72% of total area while the average annual urban growth was recorded as 4.42%. These figures proved that the quantification of decentralization is very positive. The study provides a foundation for urban environment research in the context of decentralization policy.

Bond Graph-Based Modelling for Parameter Identification of 5 kW Photovoltaic Group

Nowadays, photovoltaic is becoming more popular, reliable, and widely used. Despite its popularity, there are several problems related to instability and non-availability in almost all the Photovoltaic applications. Various parameters cause those problems such as solar irradiation, temperature, the material used in the photovoltaic cells, as well as the battery's storage capacity, and the connecting cables. For a better understanding of those problems, it is needed to model photovoltaic installations trough Multi-physics modeling, which allows the simulation of photovoltaic installations and the impact quantification of each one of the parameters mentioned above. In this paper, a mathematical model based on graphical methodology (Bond Graph) for a 5 kW Photovoltaic Group is presented. The developed model demonstrates the effect of solar radiation and the ambient temperature on the output voltage, current, and power. This model is possible without going through an iterative process. In this work, all the photovoltaic group parameters are given according to ambient temperature, solar irradiation, materials of photovoltaic cells, and the conducting wires. The expected values for voltage and current have been successfully compared to the actual physical data. Good results have been demonstrated using RMSE, with values of 3.1775 V for voltage, and 0.04 A for current.

The functional and environmental performance of mixed cathode ray tubes and recycled glass as partial replacement for cement in concrete

Concrete is one of the most abundantly produced and commonly used construction materials in the world. The production of cement—the main binder in concrete—is energy-intensive, using roughly ten times the national average ratio for energy to gross output of goods and services. Given the high demand for concrete globally and the amount of energy used to produce cement, it is worthwhile to find lower embodied-energy materials to partially replace cement to improve the environmental impacts of concrete without decreasing the concrete performance. One such potential cement replacement is the panel glass found in discarded cathode-ray tubes (CRTs). It is against this backdrop that this study aimed to investigate the technical feasibility and the environmental impacts of using a novel blend of recycled glass and CRT panel glass as pozzolanic material for replacing a portion of ordinary portland cement (OPC) in concrete. Additionally, this study simultaneously looked at the concrete functional performance and environmental impact, and the study was performed at an industrial scale using existing production infrastructure, production volumes, standardized testing, and a life-cycle assessment (LCA) to support the functional testing and environmental impact quantification. Results show that the novel blend of glass met the required performance standards, and when it was blended with cement, the mixture produced concrete with similar or improved functional performance and significantly reduced environmental impacts across all examined impact categories. Future work is needed to examine the additional benefits of diverting CRTs from their current end-of-life pathways and de-risking CRT storage.

A social impact quantification framework for the resource extraction industry

The objective of this study was to develop a social impact quantification framework for the resource extraction industry. The framework was developed to incorporate two approaches—scale-based and quantitative approaches. It aimed to be used for assessing upstream social impacts for products incorporating mined materials to produce a full social life cycle assessment (S-LCA). The framework consists of measurable indicators and impact assessment methods. The quantitative approach simulates S-LCA by applying a two-step impact assessment: (1) calculation of impact scores at the social topic level, and (2) normalization and aggregation to the social theme and stakeholder level. The framework was demonstrated via a case study to compare one material issue—health and safety—from the material extraction phase of two major photovoltaic (PV) technologies in the USA: poly-Si and CdTe PV under stakeholder workers. A temporal analysis on a key mineral was performed. The results showed large variations in the social impact scores for selected topics on key raw materials associated with the two PVs. While the case study is limited in deriving practical implications due to preset assumptions, the framework itself can be extended and integrated with a whole product S-LCA to enhance the understanding of and promote social sustainability of the resource extraction industry. A framework to measure both positive and negative social impacts was developed to follow the S-LCA methodology. The framework was illustrated by comparing two dominant PV technologies in the USA for the social theme of health and safety. Our case study demonstrated inspiring patterns for assessing upstream social impacts from the resource extraction industry, especially when incorporating a temporal analysis.

Impact quantification of satellite outages on air navigation continuity

Advanced receiver autonomous integrity monitoring (ARAIM) using multiple global navigation satellite system constellations is expected to bring significant navigation performance improvement to civil aviation. However, using multiple constellations, the higher number of satellite outages due, for example, to routine station keeping manoeuvres, could significantly increase continuity risk. In response, this study proposes a new method to rigorously quantify the impact of satellite outages on navigation safety. To achieve this, integrity and continuity risk bounds are derived, which account for all possible outage conditions. In addition, the proposed approach allows to determine whether an exclusion function is needed following an outage event. The method is implemented to analyse horizontal ARAIM (H-ARAIM) availability performance. Results indicate that dual-constellation H-ARAIM can provide high service availability, where both integrity and continuity requirements are met.

Competency framework: environmental approval specialists

Environmental approvals take time, and scheduling and planning for their preparation and submission should be high on the list of priorities when planning a project. Understanding the regulatory process and knowing what level of information is required at each stage is critical. Providing quality environmental support to the oil and gas industry requires not only an understanding of the range of petroleum activities and their potential impacts and risks, but extensive knowledge of environmental receptors in each operational area, an understanding of complex technical methods for impact and risk quantification and a solid understanding of relevant regulations with an ability to navigate complex approval processes. A common environmental competency framework could support the industry to: • identify gaps in skills and knowledge for individuals, teams or across industry sectors • develop people across the broad range of skills they require • recruit the right people into the right positions for more effective teams • engage environmental professionals to encourage longevity in their careers • develop learning and development solutions including mentoring and coaching opportunities that will have increased relevance to the industry. Green Light Environmental have developed an internal environmental competency framework as a means of assessing and documenting competency for staff and contractors working under the Green Light Environmental brand. The framework consists of a series of competency standards that reflect the core responsibilities for environmental consultant resources during planning, construction, operation and decommissioning of petroleum activities. Each standard clearly identifies the knowledge and experience required to achieve competence and is supported by assessment tools. The adoption of a shared competency framework would further support the shared desire across industry, regulator and stakeholders to increase collaboration and transparency in environmental approval processes and documentation.

Quantitative sustainability analysis of water desalination – A didactic example for reverse osmosis

Water desalination continues to evolve to a currently mature stage that, similarly to all large human endeavors, must be planned, designed, and operated according to the quantitative holistic sustainability paradigm and criteria that are defined by the interrelated aspects of the environmental, economic, and social pillars of the endeavor. A methodology for such evaluation was described in [1], including equations for formulating a composite sustainability index as a function of relevant parameters, which thus allows mathematical analysis in general and sensitivity analysis and optimization in particular. This is the first paper that demonstrates this methodology and its use for desalination by presenting an example of a comprehensive and detailed original sustainability analysis of reverse osmosis (RO) desalination plants and of their comparison. It includes the selection and calculation of metrics (for simplicity, a small number and partially synthetic) and weights, as well as their aggregation to a composite sustainability indicator, using typical data values. The aggregation is performed by an original concept of impact quantification and monetization. An analysis of sensitivity to choice of weights and to the combined environmental and social impact factors was conducted. The presented sustainability analysis example should be helpful for both didactic and practical purposes, and the methodology is flexible, modular, adaptable, and enhancable to meet other and evolving needs.

Scheduling of recovery actions in the supply chain with resilience analysis considerations

Supply chain engineering models with resilience considerations have been mostly focused on disruption impact quantification within one analysis layer, such as supply chain design or planning. Performance impact of disruptions has been typically analysed without scheduling of recovery actions. Taking into account schedule recovery actions and their duration times, this study extends the existing literature to supply chain scheduling and resilience analysis by an explicit integration of the optimal schedule recovery policy and supply chain resilience. In particular, we compute a schedule optimal control policy and analyse the performance of this policy by varying the perturbation vector and representing the outcomes of variations in the form of an attainable set. We propose a scheduling model that considers the coordination of recovery actions in the supply chain. Further, we suggest a resilience index by using the notion of attainable sets. The attainable sets are known in control theory; their calculation is based on the schedule control model results and the minimax regret approach for continuous time parameters given by intervals. We show that the proposed indicator can be used to estimate the impact of disruption and recovery dynamics on the achievement of planned performance in the supply chain.

Developing drought impact functions for drought risk management

Abstract. Drought management frameworks are dependent on methods for monitoring and prediction, but quantifying the hazard alone is arguably not sufficient; the negative consequences that may arise from a lack of precipitation must also be predicted if droughts are to be better managed. However, the link between drought intensity, expressed by some hydrometeorological indicator, and the occurrence of drought impacts has only recently begun to be addressed. One challenge is the paucity of information on ecological and socioeconomic consequences of drought. This study tests the potential for developing empirical drought impact functions based on drought indicators (Standardized Precipitation and Standardized Precipitation Evaporation Index) as predictors and text-based reports on drought impacts as a surrogate variable for drought damage. While there have been studies exploiting textual evidence of drought impacts, a systematic assessment of the effect of impact quantification method and different functional relationships for modeling drought impacts is missing. Using Southeast England as a case study we tested the potential of three different data-driven models for predicting drought impacts quantified from text-based reports: logistic regression, zero-altered negative binomial regression (hurdle model), and an ensemble regression tree approach (random forest). The logistic regression model can only be applied to a binary impact/no impact time series, whereas the other two models can additionally predict the full counts of impact occurrence at each time point. While modeling binary data results in the lowest prediction uncertainty, modeling the full counts has the advantage of also providing a measure of impact severity, and the counts were found to be reasonably predictable. However, there were noticeable differences in skill between modeling methodologies. For binary data the logistic regression and the random forest model performed similarly well based on leave-one-out cross validation. For count data the random forest outperformed the hurdle model. The between-model differences occurred for total drought impacts and for two subsets of impact categories (water supply and freshwater ecosystem impacts). In addition, different ways of defining the impact counts were investigated and were found to have little influence on the prediction skill. For all models we found a positive effect of including impact information of the preceding month as a predictor in addition to the hydrometeorological indicators. We conclude that, although having some limitations, text-based reports on drought impacts can provide useful information for drought risk management, and our study showcases different methodological approaches to developing drought impact functions based on text-based data.

Integrated natural resource management as pathway to poverty reduction: Innovating practices, institutions and policies

Poverty has many faces and poverty reduction many pathways in different contexts. Lack of food and income interact with lack of access to water, energy, protection from floods, voice, rights and recognition. Among the pathways by which agricultural research can increase rural prosperity, integrated natural resource management deals with a complex nexus of issues, with tradeoffs among issues that are in various stages of denial, recognition, analysis, innovation, scenario synthesis and creation of platforms for (policy) change. Rather than on a portfolio of externally developed ‘solutions’ ready for adoption and use, the concept of sustainable development may primarily hinge on the strengths and weaknesses of local communities to observe, analyse, innovate, connect, organize collective action and become part of wider coalitions. ‘Boundary work’ supporting such efforts can help resolve issues in a polycentric governance context, especially where incomplete understanding and knowledge prevent potential win-win alternatives to current lose-lose conflicts to emerge. Integrated research-development approaches deal with context (‘theory of place’) and options (‘theory of change’) in multiple ways that vary from selecting sites for studying pre-defined issues to starting from whatever issue deserves prominence in a given location of interest. A knowledge-to-action linkage typology recognizes three situations of increasing complexity. In Type I more knowledge can directly lead to action by a single decision maker; in Type II more knowledge can inform tradeoff decisions, while in Type III negotiation support of multiple knowledge+multiple decision maker settings deals with a higher level of complexity. Current impact quantification can deal with the first, is challenged in the second and inadequate in the third case, dealing with complex social-ecological systems. Impact-oriented funding may focus on Type I and miss the opportunities for the larger ultimate impact of Type II and III involvements.

Application of Eco-Design and Life Cycle Assessment Standards for Environmental Impact Reduction of an Industrial Product

Eco-design is included within the framework of the standard for “Environmental management systems—Guidelines for incorporating Eco-design” (ISO 14006:2011). Eco-design process, as defined in standard, has six steps: (i) Specify product functions; (ii) Environmental assessment of products; (iii) Strategies of improvement; (iv) Environmental objectives; (v) Product specification; and (vi) Technical solutions. Step (ii), determination of the stage or process of the product life cycle that has the highest environmental impact; this is perhaps the most controversial step because the standard does not specify which tool should be used. This lack of specification has generated some distrust with regard to eco-design, hindering its development. In order to make a trustworthy eco-design, Life Cycle Assessment (LCA) should be applied as a tool for environmental impact quantification. The main objective of this work is to apply standardised eco-design methodology for the reduction of the environmental impact of an industrial product in Spain using LCA as a tool for the environmental product assessment. LCA standardised process (ISO 14040,14044:2006) is included in the eco-design process. A glass container intended for cough syrup delivery has been selected as an industrial product to be eco-designed. Following the methodology described, the overall normalised impact decreased 35.1% when a PET container substituted a glass container. Environmental impacts have been reduced following standardised eco-design and LCA methodologies, serving as an example to industry and administration regarding how to eco-design with the confidence of obtaining reliable results.

Life cycle sustainability assessment of grid-connected photovoltaic power generation: A case study of Northeast England

This paper proposes a comprehensive sustainability assessment model incorporating (a) life cycle approach and sustainability theory. In the model, sustainability is assessed from three categories: techno-economic, environmental and social. A total of thirteen indicators were included in the proposed model, with five evaluating the techno-economic performance, six evaluating the environmental performance, and two examining the social impact. The effectiveness of this model is then demonstrated through its application to a case study of solar photovoltaic in the North East region of England. Three types of the most commonly deployed solar photovoltaic electricity generation systems are included in the case study: monocrystalline (s-Si), polycrystalline (p-Si) and Cadmium telluride (CdTe) thin film.The multi-silicon solar photovoltaic system is found to be the most sustainable option for its high performance in the techno-economic and environmental categories; the CdTe based system is the least-favoured option across all three categories; and the polycrystalline system has the best performance across all categories. Energy conversion efficiency appears to be one of the most influential factors for the solar photovoltaic system’s sustainability performance. Despite being the least costly system among the three, the CdTe system appears to be the least financially viable option mainly due to its low energy-conversion efficiency.This study estimates the environmental impact of selected technologies using the CML2001 method and then employs ReCiPe method to cross-validate the estimated results. Identical results were found for all indicators apart from eutrophication potential, due to the difference in impact quantification methods between CML and ReCiPe.

Understanding the emission impacts of high-occupancy vehicle (HOV) to high-occupancy toll (HOT) lane conversions: Experience from Atlanta, Georgia

ABSTRACTConverting a congested high-occupancy vehicle (HOV) lane into a high-occupancy toll (HOT) lane is a viable option for improving travel time reliability for carpools and buses that use the managed lane. However, the emission impacts of HOV-to-HOT conversions are not well understood. The lack of emission impact quantification for HOT conversions creates a policy challenge for agencies making transportation funding choices. The goal of this paper is to evaluate the case study of before-and-after changes in vehicle emissions for the Atlanta, Georgia, I-85 HOV/HOT lane conversion project, implemented in October 2011. The analyses employed the Motor Vehicle Emission Simulator (MOVES) for project-level analysis with monitored changes in vehicle activity data collected by Georgia Tech researchers for the Georgia Department of Transportation (GDOT). During the quarterly field data collection from 2010 to 2012, more than 1.5 million license plates were observed and matched to vehicle class and age information using the vehicle registration database. The study also utilized the 20-sec, lane-specific traffic operations data from the Georgia NaviGAtor intelligent transportation system, as well as a direct feed of HOT lane usage data from the State Road and Tollway Authority (SRTA) managed lane system. As such, the analyses in this paper simultaneously assessed the impacts associated with changes in traffic volumes, on-road operating conditions, and fleet composition before and after the conversion. Both greenhouse gases and criteria pollutants were examined.Implications: A straight before-after analysis showed about 5% decrease in air pollutants and carbon dioxide (CO2). However, when the before-after calendar year of analysis was held constant (to account for the effect of 1 yr of fleet turnover), mass emissions at the analysis site during peak hours increased by as much as 17%, with little change in CO2. Further investigation revealed that a large percentage decrease in criteria pollutants in the straight before-after analysis was associated with a single calendar year change in MOVES. Hence, the Atlanta, Georgia, results suggest that an HOV-to-HOT conversion project may have increased mass emissions on the corridor. The results also showcase the importance of obtaining on-road data for emission impact assessment of HOV-to-HOT conversion projects.

Quantitative assessment of social and economic impact of African swine fever outbreaks in northern Uganda

African swine fever (ASF) is one of the most important pig diseases, causing high case fatality rate and trade restrictions upon reported outbreaks. In Uganda, a low-income country with the largest pig population in East Africa, ASF is endemic.Animal disease impact is multidimensional and include social and economic impact along the value chain. In low-income settings, this impact keep people poor and push those that have managed to escape poverty back again. If the diseases can be controlled, their negative consequences can be mitigated. However, to successfully argue for investment in disease control, its cost-benefits need to be demonstrated. One part in the cost-benefit equations is disease impact quantification. The objective of this study was therefore to investigate the socio-economic impact of ASF outbreaks at household level in northern Uganda.In a longitudinal study, structured interviews with two hundred, randomly selected, pig-keeping households were undertaken three times with a six month interval. Questions related to family and pig herd demographics, pig trade and pig business.Associations between ASF outbreaks and economic and social impact variables were evaluated using linear regression models. The study showed that pigs were kept in extreme low-input-low-output farming systems involving only small monetary investments. Yearly incidence of ASF on household level was 19%. Increasing herd size was positively associated with higher economic output. The interaction between ASF outbreaks and the herd size showed that ASF outbreaks were negatively associated with economic output at the second interview occasion and with one out of two economic impact variables at the third interview occasion. No significant associations between the social impact variables included in the study and ASF outbreaks could be established. Trade and consumption of sick and dead pigs were coping strategies used to minimize losses of capital and animal protein.The results indicate that causality of social and economic impact of ASF outbreaks in smallholder systems is complex. Pigs are mostly kept as passive investments rather than active working capital, complicating economic analyses and further disqualifying disease control arguments based only on standard economic models.

Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems

The first-ever Ukraine cyberattack on power grid has proven its devastation by hacking into their critical cyber assets. With administrative privileges accessing substation networks/local control centers, one intelligent way of coordinated cyberattacks is to execute a series of disruptive switching executions on multiple substations using compromised supervisory control and data acquisition (SCADA) systems. These actions can cause significant impacts to an interconnected power grid. Unlike the previous power blackouts, such high-impact initiating events can aggravate operating conditions, initiating instability that may lead to system-wide cascading failure. A systemic evaluation of "nightmare" scenarios is highly desirable for asset owners to manage and prioritize the maintenance and investment in protecting their cyberinfrastructure. This survey paper is a conceptual expansion of real-time monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework that emphasizes on the resulting impacts, both on steady-state and dynamic aspects of power system stability. Hypothetically, we associate the combinatorial analyses of steady state on substations/components outages and dynamics of the sequential switching orders as part of the permutation. The expanded framework includes (1) critical/noncritical combination verification, (2) cascade confirmation, and (3) combination re-evaluation. This paper ends with a discussion of the open issues for metrics and future design pertaining the impact quantification of cyber-related contingencies.

A robust transfer inference algorithm for public transport journeys during disruptions

Disruptions in public transport have major impact on passengers and disproportional effects on passenger satisfaction. The availability of smart card data gives opportunities to better quantify disruption impacts on passengers’ experienced journey travel time and comfort. For this, accurate journey inference from raw transaction data is required. Several rule-based algorithms exist to infer whether a passenger alighting and subsequent boarding is categorized as transfer or final destination where an activity is performed. Although this logic can infer transfers during undisrupted public transport operations, these algorithms have limitations during disruptions: disruptions and subsequent operational rescheduling measures can force passengers to travel via routes which would be non-optimal or illogical during undisrupted operations. Therefore, applying existing algorithms can lead to biased journey inference and biased disruption impact quantification. We develop and apply a new transfer inference algorithm which infers journeys from raw smart card transactions in an accurate way during both disrupted and undisrupted operations. In this algorithm we incorporate the effects of denied boarding, transferring to a vehicle of the same line (due to operator rescheduling measures as short-turning), and the use of public transport services of another operator on another network level as intermediate journey stage during disruptions. This results in an algorithm with an improved transfer inference performance compared to existing algorithms.

Techno-economic analysis and environmental impact assessment of lignocellulosic lactic acid production

Lignocellulosic Lactic acid (LA) production is considered for the diversification and value addition to an existing sugar industry by annexing a biorefinery using lignocellulosic residues, sugarcane bagasse and leaves (SCBL). In biorefinery, the hemicellulose (C5 sugars) and cellulose (C6 sugars), resulting from lignocellulosic matrix fractionation, can be converted into building block chemicals and fuels by biotechnological or chemical pathways. To co-produce LA with other fuels and chemicals from SCBL, it is important to determine whether LA production from C5 or C6 sugars should be preferred, based on economic viability and environmental impacts. In this paper we developed six process scenarios for LA production from either the hemicellulose liquid fraction and cellu-lignin solid fractions of SCBL after steam explosion pretreatment, based on 200tonne/day of SCBL feed. The lignocellulose fraction not used for LA production will be used for integrated production of other marketable products in a biorefinery. Scenarios S1, S3, & S5 use the hemicellulose liquid fraction as feed for LA production, while scenarios S2, S4, & S6 use the cellu-lignin solid fraction. Two scenarios, S1 & S2, use Ca(OH)2 as neutralizer in fermentation, resulting in co-production of gypsum as solid waste, scenarios S3 and S4 use an isolated acid-tolerant thermophilic bacteria, Bacillus coagulans isolates for fermentation, thus avoiding the need for neutralization, while Scenarios S5 and S6 use Mg(OH)2 as neutralizer in fermentation, with recycling of Mg(OH)2. LA was separated and purified from the fermentation broth by reactive distillation. The six process scenarios were modeled and simulated by Aspen Plus® with the resulting mass & energy balance and equipment-sizing used as inputs to economic analysis and environmental impact assessment. Standard life cycle assessment (LCA) method is used in SimaPro® for environmental impact quantification. Cellulose based processes have larger LA production rates than the hemicellulose based processes, for the same flow rate of SCBL, which impacts on their total capital investment (TCI), operating cost (OPEX) and revenues for the same process technology. Increases of 7.08%, 58.13%, 12.04% and 60% in TCI, revenue, OPEX and LA production rates, respectively were observed in moving from S1 to S2. Similar increases of 10.88%, 86.52%, 18.52% and 91.07% in TCI, revenue, OPEX and LA production respectively in moving from S3 to S4. An increment of 10.08%, 61.57%, 18.32% and 63.90% in TCI, revenue, OPEX and LA production respectively was also found in moving from S5 to S6. Scenarios S3 and S4 are found to have lower TCI and OPEX but their production rate is low as well making them economically less attractive with internal rate of return (IRR) of 9.13% and 15.23% respectively. While S1 and S2 have IRR of 13.11% and 19.4% respectively and yet higher TCI and OPEX. S5 and S6 have the highest IRR, 14.72% and 21.28% respectively with TCI and OPEX of way below their equivalent scenarios S1 and S2 respectively. From the environmental point of view S1 and S2 are found to be environmentally less friendly with higher environmental burdens in almost all impact categories considered. Gypsum free scenarios, S5 and S6, are found to be the most attractive processes from both economic and environmental points of view, with S6 being superior than S5.

9.K. Workshop: Health impact quantification for a culture of “foresight”? Dyadic Workshop, part 2

9.K. Workshop: Health impact quantification for a culture of “foresight”? Dyadic Workshop, part 2

8.K. Workshop: Health impact quantification for a culture of “foresight”? Dyadic Workshop, part 1

8.K. Workshop: Health impact quantification for a culture of “foresight”? Dyadic Workshop, part 1