Integration of Reverse Osmosis Desalination With Cold-Heat-Power Production in the Tertiary Sector

Integration of desalination with cold-heat-power production in the agro-food industry

Design, economic analysis and environmental considerations of mini-grid hybrid power system with reverse osmosis desalination plant for remote areas

Recently, the reverse osmosis (RO) process is widely used in the field of desalinating brackish water and seawater to produce freshwater, but the disadvantage of using this technology is the increase in the rates of electrical energy consumption necessary to manage these units. To reduce the rates of electrical energy consumption in RO desalination plants, geothermal energy and photovoltaic/thermal panels were used as preheating units to heat the feed water before entering RO desalination plants. The proposed system in this study consists of an RO desalination plant with an energy recovery device, photovoltaic/thermal panels, and a geothermal energy extraction unit. To evaluate the system performance, three incorporated models were studied and validated by previous experimental data. The results indicated that incorporating the geothermal energy and photovoltaic/thermal panels with the RO desalination plants has positive effects in terms of increasing productivity and reducing the rates of specific power consumption in RO desalination plants. The average saving in the specific power consumption for utilizing the thermal recovery system of PV panels and geothermal energy as preheating units reached 29.1% and 40.75% for the treatment of seawater and brackish water, respectively. Additionally, the economic feasibility showed the saving in the cost of freshwater produced from the RO desalination plants for incorporating both geothermal energy and photovoltaic panels with a thermal recovery system with reverse osmosis desalination plants of up to 39.6%.

With a reverse osmosis (RO) desalination plant designed to satisfy only the contracted-for water supply, the water company would be missing out on potential benefits that could have been obtained selling water in periods of high demand. On the other hand, sizing the RO desalination plant to produce water to satisfy peak demand means incurring additional costs as well as having the plant partially idle during periods of average or low demand. A model was developed using Excel macros to perform dynamic programming to optimize the capacity expansion of an RO desalination plant. The objective function is to maximize the present value of the total net benefits over the lifetime of the RO desalination plant. The model can be used to test different scenarios to capture time-variant tourism demand and price uncertainties on investment decisions. This study focuses on tourism dominated arid coastal regions, using Sharm El Sheikh (Sharm) in South Sinai, Egypt, as an example.19 RO plants in Sharm were surveyed and data were collected including unit production costs, O&M costs, energy consumption rates, contracted-for water supply, and utilization. Unit production cost of an RO desalination plant varies according to the degree of operation of the plant. This fact has to be taken into consideration when calculating the costs of RO desalination and when deciding on the plant capacity in order to maximize the total net benefit. Using the collected data, cost functions were developed for O&M costs as a function of utilization and plant capacity. The cost model calculated similar values to the actual total net benefit for one of the surveyed RO plant taken as an example. Using the optimization model, the maximum total net benefit is obtained with a smaller installed capacity than the actual case. A modified pricing structure is suggested in the paper that ties the water selling price to consumption in an effort to reduce demand in excess of contracted-for water supply aiding the water company to fulfill its contractual commitments to all users. However, price elasticity has to be taken into consideration to determine the impact of price change on water demand.

In alignment with the global issue of increasing clean water demand while aiming at achieving sustainability and enhancing energy efficiency. The implementation of Artificial Neural Networks (ANN) in Reverse Osmosis (RO) desalination plants has exhibited a substantial success. This study introduces a new approach that implements Deep Neural Network (DNN) with multi-output, employing Adam optimizer, to predict two critical parameters for desalination plants: output water quality in terms of Total Dissolved Solids (TDS) and the required membrane pressure during the plant’s operation. As these two predicted targets are the main reference parameters when evaluating the production quality and energy consumption for RO desalination plants. The consideration of multiple membrane configurations and feed flow rates, which are relatively unexplored features in ANN research on desalination, is the key innovation of this study. The multi-output DNN achieved an R2 score of 0.99, signifying a high level of prediction accuracy of the model, which was additionally validated by using experimental data to endorse the proposed model. The integration of the DNN model in RO desalination plants will enhance output water quality and operational efficiency, which will be reflected in reduced energy consumption. The model’s capability to adapt to multiple plants’ parameters and membrane configurations will lead to resource optimization, reduce environmental impacts, and boost profitability, while consistently producing high-quality water. This will benefit the industry through providing advanced water treatment solutions. This innovation underscores the potential of AI-driven solutions in revolutionizing desalination technologies and fostering sustainable water management practice.

This study looks into the design, performance analysis, and optimization of a solar PV system to power a reverse osmosis desalination plant (RODP). The main goal is to compare the proposed grid connected solar PV to the conventional utility grid in terms of technical (balance supply and demand – meet the desalination plant's daily, monthly, and yearly electrical load), economic (cost of electricity COE), and environmental (CO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> emission reductions) performance. This study employed modeling and simulation analyses to develop and assess the performance of a grid connected solar PV system for the RODP in Sharjah. The RODP's daily electricity load is 125.2 kWh/day (high pressure, feed, and dosing pumps). The results demonstrate that 82.7 percent of the energy produced by the grid-connected solar PV system is produced by the solar PV system, while 17.3 percent is acquired from the grid. All of the RODP's electrical load was met on a daily, monthly, and annual basis (no capacity shortfall), and 11.3 percent of the total electricity generated by the solar PV system was sold back to the grid. The price of power fell from ＄0.12 per kWh (grid purchase price) to ＄0.0856 per kWh (renewable power system). With the grid connected solar PV system, the renewables fractions for power generation grew from 0 to 81.2 percent. The grid connected solar PV system resulted in net emissions reductions of 78.8%, 89.6%, and 56.6 percent for CO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> , NO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">X</inf> , and SO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> , respectively.

Book Reviews

Triangle of Environment, Water and Energy: A Sociological Appraisal

Rising agricultural water scarcity in China is driven by expansion of irrigated cropland in water scarce regions

Co-development of East African regional water scenarios for 2050

Progress in improving the quality and quantity of water used by people in rural areas of the developing world has been unsatisfactory in two respects: (1) supplies that have been built are frequently neither used correctly nor properly maintained and (2) extension of improved service to unserved populations has been slow. Though this poor record is not the result of a single factor, a major impediment to improved performance is inadequate information on the response of consumers to new service options. The behavioral assumptions that typically underlie most rural water supply planning efforts are simple. It is commonly assumed that so long as financial requirements do not exceed 5% of income, rural consumers will choose to abandon their existing water supply in favor of the "improved" system. Several reviews by the World Bank, bilateral donors, and water supply agencies in developing countries have shown, however, that this simple model of behavioral response to improved water supplies has usually proved incorrect.1 In rural areas many of those "served" by new systems have chosen to continue with their traditional water use practices.

A novel newsvendor model-based framework for regional industrial water resources allocation that considers uncertainties in water supply and demand was proposed in this study. This framework generates optimal water allocation schemes while minimizing total costs. The total cost of water allocation consists of the allocated water cost, the opportunity loss for not meeting water demand, and the loss of the penalty for exceeding water demand. The uncertainties in water demand and supply are expressed by cumulative distribution functions. The optimal water allocation for each water use sector is determined by the water price, the unit loss of the penalty and opportunity loss, and the cumulative distribution functions. The model was then applied to monthly water allocation for domestic, industrial, and agricultural water use in two counties of Huizhou City, China, whose water supply mainly depends on Baipenzhu Reservoir. The water demand for each water use sector and the monthly reservoir inflow showed good fits with the uniform and P-III distributions, respectively. The water demand satisfied ratio for each water use sector was stable and increased for the optimal water allocation scheme from the newsvendor model-based framework, and the costs were lower compared with the actual water allocation scheme. The novel framework is characterized by less severe water shortages, lower costs, and greater similarity to actual water use compared with the traditional deterministic multi-objective analysis model, and demonstrates strong robustness in the advantages of lower released surplus water and higher water demand satisfied ratio. This novel framework yields the optimal water allocation for each water use sector by integrating the properties of the market (i.e., determining the opportunity loss for not meeting water demand) with the government (i.e., determining the water price and the loss of the penalty for exceeding water demand) under the strictest water resources management systems.

Introduction The research developed strategies to be adopted in Qatar to enhance agricultural production and improve the food security situation of the country. The government of Qatar has instituted plans to boost its food security and, as part of the wider food security plan, the country needs improved agricultural technologies and in-country farming techniques to increase crop yields. This QNRF-funded food security project sought to apply innovative technologies and decision support tools to provide strategies for successful vegetable food production on the local Qatari scene. The research has provided methodologies to assist Qatari researchers and Policy makers to make informed decisions about appropriate crops and timing for profitable in-country farming. Rationale The agricultural production problems faced by Qatar are similar to many other arid and semi-arid countries. The challenges faced by Qatar in improving agricultural production represent a wide range of sustainable agriculture issues including limited arable land and water resources, high temperatures associated with high humidity, salinity, plant pests and plant diseases. This research addresses these problems by contributing to the application of innovative ways of maximizing water and nutrient use efficiency for agriculture, and choosing the appropriate planting times for vegetable cultivation. Appropriate preservation of soils for agricultural purposes is not practiced in Qatar. Therefore, this research was carried out to showcase modern technological innovations with the potential to accelerate in-country vegetable production so as to enhance food security in Qatar. Methods The project consisted of four sub-projects, namely Sub-Project 1 (crop management), Sub-Project 2 (soil management and desertification), Sub-Project 3 (financial risk management) and Sub-Project 4 (combination of the three sub-Projects). The respective tasks of the sub-Projects were as follows Sub-Project 1 developed a decision-making framework for sustainable and profitable cropping in Qatar, and used the FAO AquaCrop model to carry out crop growth simulations of cucumber, squash, and tomato (Qatar), and wheat (Australia). Sub-Project 2 utilised the Soil Constraints and Management Package (SCAMP) to assess intrinsic soil and site constraints for sustainable production. The sub-Project also identified several strategies to improve crop productivity. Sub-project 3 derived an integrated drought derivative model that incorporated geo-specific weather factors, crop-growth cycles, and soil management practices to minimize financial risk. Sub-Project 4 combined the climate, crop, soil and financial components to develop an integrated decision-making framework as well as a targeted partner engagement and communication strategy. Results and Discussion The AquaCrop model is recommended for use in simulating yields of crops to assess the effects of agronomic practices including planting dates, soil characteristics, and water/nutrient use efficiency. Months for optimum vegetable planting are September and December. March planting can produce similar yields but more water is required. Because of higher temperatures and greater vapour pressure deficits during the March to June period, field crop yields from these planting dates are highly variable, resulting in very inefficient use of water. It is therefore recommended that planting during this time period in the field should be avoided. It is critically important to maximize water use efficiency in irrigated field crops in Qatar because of the link between water use efficiency and nitrogen use efficiency. It is essential that N fertilizer inputs closely match crop N requirements, and ammonium-based N fertilizers be used in preference to nitrate-N fertilizers. Regular monitoring of the salinity of the irrigation water is required to ensure that it does not exacerbate the current soil salinity status. As nutrient budgets of field-grown squash and tomato have identified a mismatch between nutrient inputs and crop demand in current management practices, the key soil fertility analyses of extractable phosphorus, organic carbon and exchangeable potassium should be undertaken to inform fertilizer management.The Financial Drought model developed using the reconnaissance drought index (RDI) can be used. A policy brief is available on the operation of derivative systems to protect farmers from production risk.The optimization model developed by incorporating a risk measure is recommended for further application. The developed user-friendly output interface for the model can be used for effective application. Significance The project initiated new dialogue between Government and private sector stakeholders in Qatar on food security strategies. Stakeholders were made aware of the lack of current information on the fertility of soils and quality of irrigation water used for vegetable crops in Qatar. The project concentrated on field production of vegetable crops (cucumber, squash and tomato) identified by a preliminary survey of local consumers. Training opportunities were provided for six students in Qatar, Canada and Australia. Results were presented at eight international conferences where QNRF was acknowledged. An analysis of evapotranspiration data for Qatar was conducted and results published. This is the first study of its type for Qatar (Issaka et al. 2017). Conclusions The research has developed a strategy that is in alignment with QNRS Grand Challenge # 1 - Water Security, by focusing on water use efficiency for crop production. It also informs on the optimal times for planting vegetable crops, and reduces fertilizer inputs and costs by avoiding excessive fertilizer use. A key component of the strategy is the need for fertilizer inputs to be closely matched to crop nutrient requirements using a nutrient budget and soil test approach. Regular monitoring of irrigation water salinity is essential to avoid increased salinization. The Financial Drought model will be beneficial in protecting farmers from production risk. Finally, the optimization model will be beneficial in improving farming decisions. Recommendations for Future Research and Development There are major advances in water and nutrient use efficiency that could be applied in both open field and greenhouse agriculture in Qatar, with the objective of making maximum effective use of their very limited water and arable soil resources. Examine how project outputs (AquaCrop/economic and crop selection model, soil / water/ nutrient/ solar radiation use efficiency, communication packages) can be embedded in Qatar's Research and Educational programs. Engage more actively with the Department of Agriculture of the Ministry of Municipality and Environment, and its particular interests in both the broader food security issues, and the tools being offered by the project. Acknowledgement This research was made possible by a NPRP award [NPRP 6-064-4-001] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements in the Report are solely the responsibility of the authors. References A.K.S. Huda, A.I. Issaka, S. Kaitibie, M. M. Haq, I. Goktepe, A. Moustafa, K. Abdella, M. Pollanen, P.W. Moody, N. Vock, N. Huda, and K.J. Coughlan (2017). Improving Food Security in Qatar: Assessing Alternative Cropping Systems Feasibility and Productivity in Variable Climates, Soil and Marketing Environments (NPRP 6-064-4-001). Final Report, Qatar National Research Foundation, 79pp A. I. Issaka, J. Paek, K. Abdella, M. Pollanen, A. Huda, S. Kaitibie, I. Goktepe, M. Haq and A. Moustafa (2017). «Analysis and Calibration of Empirical Relationships for Estimating Evapotranspiration in Qatar: Case Study.» Journal of irrigation and drainage engineering 143(2): 05016013.

A review on the applicability of integrated/hybrid membrane processes in water treatment and desalination plants

S team systems are a ubiquitous element in nearly every type of manufacturing plant. In the United States, steam systems are the single largest consumer of energy in the industrial sector, where they account for 37% of annual onsite energy use. Steam use is particularly prominent in the chemicals, paper, petroleum refining, and food and beverage industries, where it is used in a wide range of processes, including reforming, distillation, concentration, cooking, and drying. Together, these four industries comprise nearly 90% of U.S. industrial steam demand, with chemicals manufacturing (30%) and paper manufacturing (30%) holding the largest shares. At the national level, industrial steam systems account for around 6% of U.S. total primary energy use, or 5,900 trillion British thermal units (TBtu). As such, much attention has been paid to steam system energy efficiency improvements as part of corporate, utility, and government energy and air pollution initiatives. Key incentives include local utility rebates, tax incentives, and lowor no-cost steam system energy efficiency audits. Steam system energy efficiency not only makes sense from an environmental perspective, but also from an economic perspective. As of 2006, U.S. manufacturers spent $21 billion on externally purchased boiler fuels. The actual price tag of industrial steam is likely much higher; nearly one-half of U.S. boiler fuels are self-generated within plants in the form of waste gas, black liquor, wood wastes, and other byproducts. These byproduct fuels are not free, as they are generated from purchased materials and typically require further processing for efficient combustion. Reducing demand for boiler fuels can, therefore, help reduce operating costs and improve profit margins. While clearly justified, the historical focus on reducing energy use has overlooked an increasingly compelling benefit of steam system efficiency: namely, reduced water use. Compared to the many public and private incentives for industrial energy efficiency, there are surprisingly few external incentives for industrial water efficiency. One key barrier to such incentives is the lack of credible data on industrial water use, which, unlike data on energy use, are not compiled at the manufacturing industry or process level in regular national surveys. This dearth of data contributes to a general lack of awareness of the sources and scale of industrial water use within the engineering and policy communities, which limits broader attention to water efficiency beyond the plant floor. Another barrier to steam system water efficiency is that the cost of boiler water—and the associated chemicals required for its treatment—typically only represents a small fraction of boiler operating costs, which are dominated by the costs of fuel. However, as we discuss in this Perspective, U.S. industrial steam systems consume copious amount of water. It follows that steam systems are worth a closer look as a manufacturing water efficiency target. Several current trends suggest that water efficiency will play an increasingly prominent role in the financial and sustainability plans of U.S. manufacturers. Recent water stress due to droughts and rising water infrastructure costs have led to increased public water rates around the country. These conditions may worsen with a changing climate. An increasing number of manufacturers are reporting water use as an important environmental indicator in annual corporate sustainability reports, which raises both public awareness of and accountability for water efficiency. Many manufacturers are also being asked by their corporate customers for environmental “footprint” data as part of large-scale sustainable Correspondence concerning this article should be addressed to E. Masanet at eric.masanet@northwestern.edu; M.E. Walker at mwalker9@hawk.iit.edu.