Biomass Logistics Research Articles

Embracing the sustainable horizons through bioenergy innovations: a path to a sustainable energy future.

The urgent need for mitigating climate change necessitates a transformative shift in energy production and consumption paradigms. Amidst this challenge, bioenergy emerges as a pivotal contributor to the global energy transition, offering a diverse array of solid, liquid, and gaseous fuels derived from biomass. This mini review delves into the unique potential of bioenergy innovations, particularly renewable diesel, bio jet fuel, and ethanol, to reduce greenhouse gas emissions and transform various industries. The article highlights critical technological advancements, supportive policies, and cross-sector collaboration essential for a sustainable energy transition. Specific challenges such as ensuring a consistent biomass feedstock supply, decentralizing processing units, and navigating complex regulatory frameworks are examined. Innovative solutions like decentralized biomass processing and enhanced biomass logistics are discussed as pathways to overcome these barriers. The review provides specific recommendations for near-term policies and strategies to support decentralized facilities, showcasing bioenergy's role in achieving a sustainable future.

Straw Logistics Network Optimization Considering Cost Importance and Carbon Emission under the Concept of Sustainable Development

As biomass power generation projects progress, the supply chain of biomass resources has become a key link for the green development of biomass power facilities. The role of biomass recycling logistics in the sustainable development of biomass resources and power generation endeavors has grown increasingly significant. To realize environmentally friendly and economical straw logistics, it is imperative to establish an efficient, economic and sustainable straw recycling logistics network. Therefore, based on the weighting theory and top-down method, this study proposes a planning model aiming at minimum total cost and minimum carbon emission to locate the logistics network. The immune algorithm is applied to solve and analyze the proposed examples. It is concluded that under the condition that the total cost is reasonable, reducing transportation cost. The verification model can enhance the environmental and economic performance of straw logistics networks. From the perspective of theory and practice, we provide ideas for the optimization of relevant biomass logistics networks and promote the realization of low-carbon sustainable development of logistics networks.

Large-scale spatially explicit analysis of carbon capture at cellulosic biorefineries

The large-scale production of cellulosic biofuels would involve spatially distributed systems including biomass fields, logistics networks and biorefineries. Better understanding of the interactions between landscape-related decisions and the design of biorefineries with carbon capture and storage (CCS) in a supply chain context is needed to enable efficient systems. Here we analyse the cost and greenhouse gas mitigation potential for cellulosic biofuel supply chains in the US Midwest using realistic spatially explicit land availability and crop productivity data and consider fuel conversion technologies with detailed CCS design for their associated CO2 streams. Optimization methods identify trade-offs and design strategies leading to systems with attractive environmental and economic performance. Strategic and operational decisions depend on underlying spatial features and are sensitive to biofuel demand and CCS incentives. US CCS incentives neglect to motivate greenhouse gas mitigation from all supply chain emission sources, which leverage spatial interactions between CCS, electricity prices and the biomass landscape.

Economics of sustainable lignocellulose biomass and biofuel logistics in Malaysia

Lignocellulose biomass is an inedible and renewable resource that can be used to produce biofuels sustainably and thus help to mitigate climate change while helping to ensure energy security. Tropical countries like Malaysia are assumed to have abundant biomass resources, but the fragmented farming landscapes common in Southeast Asia raise challenges for biofuel production, which largely stem from logistics operations and have an adverse impact on economies of scale and the viability of biorefineries. This thesis seeks to understand the costs and supplies associated with biomass transport, assess the impacts of landscape fragmentation on biorefineries, and identify optimum biorefinery locations. Ten sources of biomass (agroforestry residues from fields, sawmills, and processing plants) were considered, taking into account various logistical factors, supply scenarios, and impacts of landscape fragmentation. The study began with a simulation of biomass transport across Peninsular Malaysia, using GRASS GIS software to estimate costs and supplies. Eighty-nine points within each district were designated as potential locations. Biomass transport was recorded as a major cost component in operational expenditures. The capital expenditures for various conversion pathways and biorefinery operations were estimated across relevant orders of magnitude, with the biofuel supplies also being simulated. The study identified four optimum locations for various types of biomass, presenting detailed cost and supply structures. The two most competitive biomass types are rice straw and pressed palm fibre (PPF). Costs ranged a) from 130.6 to 206.3 USD/tonne, yielding 0.47 to 0.97 million tonnes of PPF fermented biofuel per year, and b) 123.2 to 207.8 USD/tonne for rice straw, yielding 0.49 to 0.56 million tonnes of fermented biofuel per year. In tonnes of oil equivalent (toe), both together amounted to 5–7% of Malaysia’s annual petroleum consumption. Surprisingly, the findings suggest that an abundance of biomass does not necessarily result in lower biofuel costs, because factors such as spatial fragmentation and moisture content amplify transport costs. Our analysis emphasises the need for strategic planning, including the use of larger trucks, early moisture removal, and the establishment of local consolidation centres to manage biomass effectively. It highlights the need for a more holistic and strategic approach in order to understand supply zone specifics with a view to unlocking Malaysia’s potential for sustainable biofuel production.

Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy

AbstractBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine‐learning‐based forecasts, optimization, and feature selection are critical for improving biomass management techniques. In this research, we explore the influences of these techniques on the accurate forecasting of biochar yield and properties for a range of biomass sources. We emphasize the importance of the interpretability of a model, as this improves human comprehension and trust in ML predictions. Sensitivity analysis is shown to be an effective technique for finding crucial biomass characteristics that influence the synthesis of biochar. Precision prognostics have far‐reaching ramifications, influencing industries such as biomass logistics, conversion technologies, and the successful use of biomass as renewable energy. These advances can make a substantial contribution to a greener future and can encourage the development of a circular biobased economy. This work emphasizes the importance of using sophisticated data‐driven methodologies such as ML in biochar synthesis, to usher in ecologically friendly energy solutions. These breakthroughs hold the key to a more sustainable and environmentally friendly future.

Power Requirement and Energy Consumption of Small Bale Recompression

Highlights Compression pressure has a nonlinear relationship with bale density. Increasing compression speed increased the energy, power, and specific energy required to recompress bales. The effect of speed on compression pressure and density was dependent on type of crop. Abstract. Biomass densification can reduce space needs during storage and transportation. It is important to quantify the amount of energy needed to densify biomass. Small bales (0.36 × 0.46 × 0.86 m) of herbaceous biomass crops, corn stover, indiangrass, switchgrass, and wheat straw, were recompressed in a compression chamber to determine their compression behavior in baled form. This chamber had the same cross-sectional area as a small baler. On average, the volume of all bales that were recompressed was reduced by 67.4%. Mean bale densities (d.b.) for corn stover, indiangrass, switchgrass, and wheat straw were increased from 94 to 264 kg m-3, 117 to 352 kg m-3, 139 to 384 kg m-3, and 98 to 277 kg m-3, respectively. The baled crops follow a nonlinear density vs. pressure relationship that can be accurately predicted using an exponential equation. When increasing loading or compression speed, the energy, power, and specific energy required to recompress the baled crops also increased. However, since each crop behaved differently during recompression, the effect of speed on compression pressure and density was dependent on the type of crop. At 60% reduction in bale volume and at the lowest compression speed (2.54 mm s-1), switchgrass required 15.6%, 61.7%, and 55.4% more energy than indiangrass, corn stover, and wheat straw, respectively. There were no significant differences in power required to compress different crops at the slowest speed (a = 0.05), but wheat straw required a lower specific energy of 0.725 kJ kg-1(d.b.) compared to between 0.734 and 0.814 kJ kg-1(d.b.) for the other crops. At the fastest compression speed (106.7 mm s-1), switchgrass required 32.4%, 59.4%, and 73.0% more energy, 12.9%, 20.5%, and 27.0% more power, and 15.7%, 5.4%, and 20.7% more specific energy than indiangrass, corn stover, and wheat straw, respectively. The purpose of this study was to determine the power requirement and energy consumption required to densify small bales of biomass crops using recompression to high enough densities to allow tractor trailers to be fully loaded to legal weight capacities within legal dimensions for highway transportation. Results from this study will be helpful when calculating energy balances related to biomass bale recompression for use as a feedstock in biofuel production and also for structural design and component selection for bale recompression machinery. Keywords: Bale, Biomass logistics, Bulk densification, Recompression.

Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection

It is crucial to identify alternative energy sources owing to the ever-increasing demand for energy and the other environmental problems associated with using fossil fuels. Biomass as a source of bioenergy is considered a promising alternative to fossil fuels. This study aims to optimize the biomass supply chain by developing an integrated model incorporating typical tactical supply chain decisions based on market or demand selection decisions. To this end, a novel mixed-integer linear programming (MILP) model is proposed to maximize the profit of the corresponding biomass supply chain and to commercialize electricity production by selecting electricity demand and making supply chain decisions regarding power plant operations, biomass feedstock purchase and storage, and biomass transport trucks. Owing to the intricacy of the MILP model, a fix-and-optimize-based solution strategy is developed and validated by applying it to several instances of a real-world case study. The results demonstrate that the proposed strategy can significantly reduce computational time while preserving high solution quality. Additionally, it helps improve planning and decision-making as it reveals the effect of essential biomass logistics characteristics on routing outcomes.

Measuring Accessibility and Optimising Logistics of Marginal Land Grass Biomass in the Case of Northern Ostrobothnia, Finland

Abstract Grass biomass originating from marginal agricultural land unsuitable for food production can be utilised in variety of bio-based productions. The key profitability constraints for such productions are regional availability and transport costs. The aim of this paper is to methodologically test open access agricultural field parcel data – enabled by the EU INSPIRE directive – integrated with the road network in measuring biomass accessibility and optimising collection and transport using geographic information system (GIS) technology in two Finnish case areas. The analytical framework applies closest facility and vehicle routing analyses for tractor and truck transport scenarios. The key finding is that the area of field parcels and the amount of biomass accumulating within an observed area are not the only important factors influencing transport efficiency: cost-effectiveness of collection routes can be equally high in regions with scarce and abundant biomass areas.

Life Cycle Assessment of Poplar Biomass for High Value Products and Energy

The European Union has embarked on a European Green Deal programme that advocates for a transition from fossil fuels to sustainable production. Attempts are being made to identify biomass sources and bioproducts (pharmaceuticals, cosmetics, or biofuels) that do not compete significantly with food production and have a low environmental impact. Therefore, the aim of this study was to determine the environmental impact of the supercritical CO2 extraction of poplar biomass in a life cycle assessment (LCA). The production system was examined in a cradle-to-gate approach. In the analysed system, poplar biomass was extracted, and residual biomass was converted to pellets which were used to generate process heat. The functional unit was 1 kg of packaged extract. The results showed that the step of biomass extraction using S-CO2 (in subsystem II) made the greatest contribution to all but two impact categories, with contribution from 25.3% to 93.8% for land use and global warming categories, respectively. In contrast, the whole subsystem I (biomass production and logistics) had a low environmental impact. Heat generation from residual biomass led to a minor decrease in the system’s environmental impact. Greenhouse gases emission reached 440 kg of CO2 equivalents per 1 kg of the extract, and they were associated with high electricity consumption and steam production. Despite the application of residual biomass for heat generation, the overall environmental impacts, especially in terms of human health and ecosystem damage, remain significant, indicating the need for further optimisation and mitigation strategies in the production process. Moreover, the share of renewables in the energy mix supplied to biorefineries should mitigate the environmental impact of the extraction process.

Combustion Performance of Agropellets in an Experimental Fixed Bed Reactor versus a Commercial Grate Boiler. Validation of Ash Behavior.

Agrobiomass is presented as a suitable alternative to contribute to the fossil fuel decarbonization strategy at the European level. To achieve the ambitious objectives established in this regard: (i) new biomass resources need to be used and therefore initially tested in order to confirm its potential for different applications, such as energy production, and (ii) biomass supply capacity needs to be enlarged; therefore, agroindustries converted into Integrated Biomass Logistic Center (IBLC) can play a key role. In this research, eight different agropellets (blends of wheat straw and maize stalk with forestry wood) were produced in a IBLC and tested in a commercial boiler, comparing the results with previous ones obtained in a fixed bed reactor test campaign and to a base case (woody pellets). This paper includes both individual results in terms of bottom ash, deposition, and a final comparison of ash behavior in both facilities. All biofuels tested showed an adequate performance in terms of efficiency and emissions, being slightly better for the agropellets produced with wheat straw. Regarding sintering and deposition, the tendencies found in the reactor investigation were also observed in the commercial boiler. Moreover, the assessment of the results from the boiler and reactor's tests proved that reactor experiments are representative and may be used to test new biofuels more efficiently in terms of effort and time allocated and could be used to predict sintering and deposition phenomenon occurrence.

A Bilevel Model for Robust Network Design and Biomass Pricing Under Farmers’ Risk Attitudes and Supply Uncertainty

This paper addresses an integrated biomass pricing and logistics network design problem. A bilevel design and pricing model is proposed to capture the dynamic decision process between a biofuel producer as a Stackelberg leader and farmers as Stackelberg followers. The bilevel optimization model is transformed into a tractable single-level formulation by using optimality constraints. Other unique characteristics of our problem at hand include the incorporation of the harvesting time and frequency decisions in the biomass supply chain network design problem for the first time and consideration of the uncertainty in switchgrass yield in a robust optimization setting to take into account the risk-averse behavior of the farmers (suppliers). To efficiently solve the model, we propose a Benders decomposition algorithm enhanced by surrogate constraints, strengthened Benders cuts, and in-out cut loop stabilization. The numerical experiments show that the proposed algorithm is significantly superior to the branch-and-cut approach of CPLEX in terms of run times and gaps. We conduct a case study with data from Texas to validate the capabilities of our mathematical model and solution approach. Based on extensive experiments, the benefits of modeling are analyzed, and significant insights are explored. Funding: This research was partially supported by the National Natural Science Foundation of China [Grants 71771135, 72171129]; and the scholarship from China Scholarship Council (CSC) [Grant CSC 201906210092]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2021.0357 .

System Dynamics Modelling: Integrating Empty Fruit Bunch Biomass Logistics to Reduce GHG Emissions

The world is shifting toward renewable energy sources due to global warming and rising GHG emissions. Malaysia has joined other nations in the conference of parties to develop policies for the reduction of GHG and carbon emissions. Malaysia is switching towards sustainable, eco-friendly and renewable energy sources. EFB biomass, one of the by-products of palm oil, has enormous potential as a sustainable energy source. Malaysia, one of the top exporters of palm oil, is unable to employ EFB-biomass-based power generation due to storage, logistics and supply-chain-related constraints. Therefore, this study integrates EFB biomass supply-chain logistics to overcome the reported challenges. The current study employs the system dynamics (SD) approach to achieve the objectives as it explains the dynamics of interaction and behaviour among the sub-systems. A document-based model-building approach is employed to collect data to develop the base model. The document-based model-building approach and system dynamics modelling facilitates the achievement of two outcomes: integrated EFB biomass logistics and GHG reduction using EFB. These outcomes are crucial to enhancing the base model and realizing the zero-carbon emission goal to contribute to sustainable development goals.

Biomass supply chain resilience: integrating demand and availability predictions into routing decisions using machine learning

ABSTRACT Biomass sources have the potential to mitigate carbon emissions as a renewable source while reducing waste and residues. Seasonality and disruption risks are some of the disadvantages of biomass resources requiring that biomass supply chains be managed such that to withstand disruptions. There has been very limited research on integrating predictions for smart management on supply or demand sides of biomass supply chains. In this study, a number of predictive models are investigated for building energy demand and biomass stock availability subject to forecasts of weather conditions. On that basis, an allocation algorithm is proposed for optimal collection and logistics of biomass from land to depots. Accordingly, Google Maps API will be used to identify the best distribution routes for delivering biomass from depots to end-users. A case study with real (supply and demand) data is considered. The proposed integrated data-driven approach aims at improving the accuracy of biomass supply and demand predictions and coordinating these predictions to enhance the resiliency of bioenergy supply chain routing decisions.

Towards an integrated decision‐making support framework for the sustainable production and use of biomass

The decision-making landscape to maximize the use of sustainable biomass resources, and achieve long-term environmental and socioeconomic benefits, is complex with a high level of uncertainty in biomass supply and logistics, technical and economic performance of the biorefinery routes, lifecycle performance of the finished products, and other sustainability criteria. Numerous decision-making support models have been developed but these models usually assess only a few specific aspects of technology, regulations, economic, environment, and society. Decision-making support models with a limited capability to capture environmental and socioeconomic performance of the biorefining pathways are not able to identify the best available biorefining routes. This study reviews and discusses recent progress on the harmonization, standardization, and integration of the existing decision-making support models that aim to improve the comparability of the results of these models when different pathways are being assessed and align the decisions made at the strategic, tactical and operational levels. With the growing number of climate-change policies and greenhouse gas (GHG) emission reduction targets, national and international efforts to harmonize the input databases, the model assumptions and system boundaries, and the integration of the existing models have been increasing. However, the deployment of the integrated frameworks among the bioeconomy stakeholders that are capable of evaluating and identifying the promising biorefining routes with significant economic, social and environmental benefits is still not a common practice. This study proposes an integrated decision-making support framework to identify cost-competitive, low-carbon fuel production pathways that are technically viable and can potentially provide maximum GHG emission reduction.

Techno-economic assessment and logistics management of biomass in the conversion progress to bioenergy

Biomass has been known as a potential energy source for biofuel production to replace fossil fuels aiming to minimize greenhouse gas emissions. However, one of the hurdles to prevent biomass from being widely utilized as energy and producing fuel is its high cost because there has not still an efficient biofuel production technique, proper techno-economic assessment and logistics management strategy. In this paper, the application of the thermochemical process in the conversion of biomass to bioenergy was comprehensively presented. Besides, the techno-economic feasibility of converting agricultural biomass into biofuels was also carefully assessed according to the technical characteristics and applicability of the thermo-chemical techniques. Furthermore, this paper also mentioned significant logistics management features like supply-driven and demand-driven collection, storage at intermediate facilities, biomass collection in various forms, inter-modal delivery for transporting in long-distance, deterioration of biomass quality, biomass pre-processing planning, and operational-level transportation planning. Generally, biomass-derived biofuels could become the most efficient and appealing bioenergy. Nevertheless, production on a large scale is still a challenge, and it is critical to develop innovative technology to improve the efficiency of biofuel production and seek efficient biomass logistics management to meet the energy demand at present and in the future.

Enabling the circular economy of bio-supply chains employing integrated biomass logistics centers - A multi-stage approach integrating supply and production activities

Studies in the agro-industry sector have shown the importance to evaluate the feasibility of an IBLC (a multi-product transformation plant). This paper develops a model to simulate the performance of an IBLC in Spain, using a combined approach: AHP, TOPSIS, and a hybrid simulation model. Results show that profits can be incremented by about 55.7% and environmental emissions of KgCO2e per tonne of bio-commodity produced, reduced by 24.2%. The scientific contribution covers the development of a simulation model that dynamically select suppliers based on a combination of social, environmental, and economic criteria. In addition, the model can be used to evaluate the economic and environmental feasibility of the IBLC by integrating the suppliers selection with the operations of a multi-product transformation plant.

Novel Methodology to Assess Advanced Biofuel Production at Regional Level: Case Study for Cereal Straw Supply Chains

Nowadays, there is an urgent necessity for breakthrough technologies able to reduce process complexity and to lower costs to make the biomass-based biodiesel supply chain competitive. This paper presents an innovative methodology for the identification of secondary biomass potentials for biofuel production. The methodology, divided into four steps, defines the criteria that allow identification of promising scenarios of biomass supply chains for commercial application of innovative technologies. The model set up a scoring procedure based on carbon emission avoidance, efficient resource exploitation and sustainability indexes. Applying the four levels of analysis (biomass availability, suitability analysis, regionalization and multi-criteria analysis), the cereal straw supply chains in four European districts (Scandinavian, Hanseatic, Central European and Mediterranean) have been identified and grouped in 18 biomass supply regional clusters (BSRCs). The clusters represent the most promising hotspots where biomass availability, logistics and feedstock requirements for a novel conversion technology meet. Central European and Mediterranean districts are those with the highest cereal straw bioeconomic potentials which allow mono-feedstock supply chains and relatively high capacity of a conversion technology at 200 MWth and beyond. Central Europe has an overall bioeconomic potential of 16.249 kt (232.359 TJ) distributed over 36 regions and organized in 12 BSRCs. The Mediterranean district has an overall bioeconomic potential of 3541 kt (50.630 TJ) distributed over nine regions and organized in four BSRCs.

Ash Behaviour during Combustion of Agropellets Produced by an Agro-Industry—Part 1: Blends Design and Experimental Tests Results

Agropellets are presented as a suitable product to be produced in certain agro-industries which could become Integrated Biomass Logistic Centres (IBLC) by taking advantage of its current resources during those periods in which their facilities are underused. Wheat straw and maize stalk were selected to be blended with forestry wood in an agro-industry dedicated to animal feed production. The materials were characterized to assess the quality of the input material. Taking into account the former, different pellets (blends of woody and herbaceous biomass) were produced and tested in a fixed bed reactor in order to study their combustion behaviour. Additionally, several predictive indexes were also calculated to assess sintering and deposition occurrence probability. Ash sintering degree was found to be directly related to composition and highly dependent on Si content. Moreover, an increase of the wood content in the blend did not proportionally imply a higher quality of the final blend, as would be expected. Regarding deposition, due to the high number of factors involved in this phenomenon, it has not been possible to draw clear conclusions. To do this, it was necessary to delve into the deposition mechanisms, which is addressed in the second part of this paper. Thus, despite the appearance of sintering and deposition phenomena, the combustion behaviour was satisfactory in the test carried out. Additionally, it has been demonstrated that agro-industries can act as IBLCs, producing blended pellet for the energy market that aligns with the standard ISO 17225-6.

Biofuel supply chain management in the circular economy transition: An inclusive knowledge map of the field

Investment in biofuels, as sustainable alternatives for fossil fuels, has gained momentum over the last decade due to the global environmental and health concerns regarding fossil fuel consumption. Hence, effective management of biofuel supply chain (BSC) components, including biomass feedstock production, biomass logistics, biofuel production in biorefineries, and biofuel distribution to consumers, is crucial in transitioning towards a low-carbon and circular economy (CE). The present study aims to render an inclusive knowledge map of the BSC-related scientific production. In this vein, a systematic review, supported by a keywords co-occurrence analysis and qualitative content analysis, was carried out on a total of 1,975 peer-reviewed journal articles in the target literature. The analysis revealed four major research hotspots in the BSC literature, namely (1) biomass-to-biofuel supply chain design and planning, (2) environmental impacts of biofuel production, (3) biomass to bioenergy, and (4) techno-economic analysis of biofuel production. Besides, the findings showed that the following subject areas of research in the BSC research community have recently attracted more attention: (i) global warming and climate change mitigation, (ii) development of the third-generation biofuels produced from algal biomass, which has recently gained momentum in the CE debate, and (iii) government incentives, pricing, and subsidizing policies. The provided insights shed light on the understanding of researchers, stakeholders, and policy-makers involved in the sustainable energy sector by outlining the main research backgrounds, developments, and tendencies within the BSC arena. Looking at the provided knowledge map, potential research directions in BSCs towards implementing the CE model, including (i) integrative policy convergence at macro, meso, and micro levels, and (ii) industrializing algae-based biofuel production towards the CE transition, were proposed.

Optimizing Operational-Level Forest Biomass Logistic Costs for Storage, Chipping and Transportation through Roadside Drying

Forest biomass (FB) could supply more of Australia’s energy needs, but delivered costs must be reduced for it to be a viable energy source. Operational planning is critical to reducing delivered costs as it determines actual activities, though few operational FB supply chain (FBSC) planning tools have been published. This paper presents a “proof-of-concept” operational FBSC decision support system (DSS) to schedule FB deliveries for eight weeks from roadside storage for the least cost, taking in account moisture content changes. Four mathematical models are compared, solving a linear formulation of the FB delivery problem in terms of solution speed and delivered cost, and the practicality of implementing the solutions. The best performing model was a Greedy algorithm as it produced solutions not significantly different from those of the tested linear programming solver and was readily modified to significantly improve solution implementation through the addition of a non-linear element. FBSC planning tools typically assume accurate knowledge of stored FB quantities and that little or no rainfall occurs during storage. In practice, stored FB quantity estimates can be inaccurate due to variation in the bulk density of the piles. Improving these estimates is a critical area for future research. This study found that simulated rainfall with <20 mm during the first week of the scheduled period did not significantly effect delivered costs.