Estimates Of Savings Research Articles

Quantitative Evaluation of Flood Control Measures and Educational Support to Reduce Disaster Vulnerability of the Poor Based on Household-level Savings Estimates

In developing countries, where budget constraints make it difficult to invest in disaster risk reduction, disasters worsen the poverty trap. To alleviate poverty by reducing the risk of disasters, not only the immediate direct impacts of disasters but also their long-term and indirect impacts should be considered. However, since the effects of individual policies are often evaluated based on the extent of damage reduction, the impact on the poor, who have few assets and thus small losses, is generally ignored. Here, we aimed to quantitatively evaluate the effects of flood control measures and educational support in terms of the flood vulnerability of the poor at the household level. We constructed a model to calculate the savings of individual households and used the flood damage-to-savings ratio to determine their flood vulnerability. Next, we estimated the extent to which the flood vulnerability is reduced by various policies. We found that educational support is suitable for reducing the flood vulnerability of the poor cost-effectively, especially when the budgets are small. Gini coefficient predictions confirmed that educational support is effective in reducing income inequality. The novelty of this study is that it quantitatively links flood damage, savings, and education, which are factors that affect the flood vulnerability of the poor, and it compares the effects of various flood control measures and educational support at the household level in terms of the flood vulnerability. While the model was developed using household survey data from Bago, Myanmar, the framework should be applicable to other regions as well.

MARTINI: Smart meter driven estimation of HVAC schedules and energy savings based on Wi-Fi sensing and clustering

HVAC systems account for a significant portion of building energy use. Nighttime setback scheduling is an Energy Conservation Measure (ECM) where cooling and heating setpoints are increased and decreased respectively during unoccupied periods with the goal of obtaining energy savings. However, knowledge of a building’s real occupancy is required to maximize the success of this measure. In addition, there is the need for a scalable way to estimate energy savings potential from ECMs that is not limited by building specific parameters and experimental or simulation modeling investments. Here, we propose MARTINI, a sMARt meTer drIveN estImation of occupant-derived Heating, Ventilation and Air Conditioning (HVAC) schedules and energy savings that leverages the ubiquity of energy smart meters and Wi-Fi infrastructure in commercial buildings. We estimate the schedules by clustering Wi-Fi derived occupancy profiles and, estimate energy savings by shifting ramp-up and setback times observed in typical operational/static load profiles that are obtained by clustering smart meter energy profiles. Our case-study results with five buildings over seven months show an average of 8.1%–10.8% (summer) and 0.2%–5.9% (fall) chilled water energy savings when HVAC system operation is aligned with occupancy. We validate our method with results from Building Energy Performance Simulation (BEPS) and find that estimated average savings of MARTINI are within 0.9%–2.4% of the BEPS predictions. In the absence of occupancy information, we can still estimate potential savings from increasing ramp-up time and decreasing setback start time. In 51 academic buildings, we find savings potentials between 1%–5%.

The visible hand: benchmarks, regulation, and liquidity

According to recent theoretical work, a more transparent and precise benchmark assessment should positively impact liquidity in the underlying market. We exploit a benchmark regime change in the $289 trillion interest rate swaps market to test this prediction. Utilizing proprietary electronic order book data, we find improved liquidity effects in the USD swaps market following the transition to the regulated ICE Swap Rate. Regulations that improve the methodology and oversight of benchmarks can, therefore, impact markets positively. Conservative estimates of direct savings in a single swap tenor on one trading platform are in the region of $4 million - $7 million.

Water conservation can reduce future water-energy-food-environment trade-offs in a medium-sized African river basin

The need for achieving efficient and sustainable use of water resources is pressing, however, this often requires better understanding of the potential of water conservation, taking into account the impact on return flows, and the costs in relation to sectoral benefits. Using modelling and limited observational data we explore the costs and potential water savings of 24 combinations of water conservation measures in the Rufiji basin, Tanzania. We compare these costs with estimates of the value such water savings could generate from water use in three important economic sectors; agriculture, energy and downstream ecosystems with high tourism potential. The cost of water conservation measures (median: 0.07 USD m−3) is found to be: higher than the value of most uses of water for agriculture (growing crops in expanded irrigation sites) and the median value for hydropower generation (from a new mega dam currently under construction); and lower than the ecosystem value. Nevertheless, under our modelling assumptions, the volume of additional water required to supply planned irrigation expansion in the basin could be reduced by 1.5 BCM using water conservation methods that would be financially viable, given the value of competing uses of water. Water savings of this magnitude would reduce potential trade-offs between use of water for hydropower and ecosystem services, by allowing peak environmental flow releases even in dry years, and without reducing firm energy generation. This methodology is transferable and relevant for producing realistic assessments of the financial incentives for long-term sustainable water use in agriculture, given incentives for other uses. With most reservoirs now being built for multiple purposes improved understanding of trade-offs between different sectors and functions is needed.

Estimation of Potential Savings Associated With Switching Medication Formulation

This cross-sectional study describes the price differences between capsule and tablet or ointment and cream forms of prescription drugs for insured patients.

Are coupled renewable-battery power plants more valuable than independently sited installations?

Coupling battery storage to renewable plants is increasingly common in the United States, where a third of proposed solar capacity now includes battery storage. Adding batteries to renewable plants increases the average value of energy sold, can reduce energy losses to curtailment, and is incentivized through the investment tax credit. Additionally, coupling renewables with batteries saves on permitting, planning, and construction costs compared to developing the projects separately. However, collocation limits the potential locations at which the batteries might be sited. This limitation leads to an opportunity cost, or “coupling penalty,” which is the missed value that could be realized by independently siting the batteries in an optimal location away from the wind or solar resources. In this paper, we assess the opportunity costs of coupling batteries with wind and solar plants. Our analysis is based on United States wholesale power markets, and we explore how the coupling penalty varies over time (2012–2019) and across location (across the seven major wholesale markets). We find the coupling penalty ranges from $2.3/MWh to $13.7/MWh, depending on battery integration assumptions. This penalty is the same order of magnitude as cost savings estimates for coupled project development and construction. This rough equivalence in opportunity cost and cost savings suggests that the net value of coupling renewables and batteries is highly sensitive to site-level market conditions and configuration decisions. The current structure of the investment tax credit, which only reduces storage costs when charged by a renewable generator, will often ‘tip the balance’ towards coupling.

Biogas Generation in Hypothetical Full-Scale Ansbbr Reactor from Cassava Starch Wastewater: Energy Production and Savings Estimate

Biogas Generation in Hypothetical Full-Scale Ansbbr Reactor from Cassava Starch Wastewater: Energy Production and Savings Estimate

Biogas Generation in Hypothetical Full-Scale Ansbbr Reactor from Cassava Starch Wastewater: Energy Production and Savings Estimate

Biogas Generation in Hypothetical Full-Scale Ansbbr Reactor from Cassava Starch Wastewater: Energy Production and Savings Estimate

Mathematical Modelling of an Intermittent Anoxic/Aerobic Mbbr: Estimation of Nitrification Rates and Energy Savings

Mathematical Modelling of an Intermittent Anoxic/Aerobic Mbbr: Estimation of Nitrification Rates and Energy Savings

Mathematical Modelling of an Intermittent Anoxic/Aerobic Mbbr: Estimation of Nitrification Rates and Energy Savings

Mathematical Modelling of an Intermittent Anoxic/Aerobic Mbbr: Estimation of Nitrification Rates and Energy Savings

Energy savings estimation of a distribution system in presence of intelligent volt-VAr control based on IEEE Std. 1547-2018

Energy savings estimation of a distribution system in presence of intelligent volt-VAr control based on IEEE Std. 1547-2018

Reassessing Ireland’s economic development through the lens of sustainable development

Abstract After a century of Irish independence, this study constructs long run Genuine Savings estimates, a leading economic indicator of sustainable development, to reassess Irish economic history from the vantage of sustainable development. The main difference uncovered surrounds the post-1950 period where Ireland failed to achieve economic convergence and was considered an economic failure in growth terms. From a sustainability perspective, Ireland may have been an overachiever during a “great transition” of sustainable development driven by improved institutions and policies. The findings show the value of the sustainable development perspective in shedding new light on a country’s development experience.

Estimation of energy consumption due to the elimination of an environmental tax in Ecuador

The National Assembly of Ecuador repealed the Environmental Tax on Vehicle Pollution, which taxed the engine displacement of vehicles. This article aims to make an estimate of the energy savings that would have been achieved if this tax had been maintained and executed as originally planned. A methodology was applied to forecast energy consumption, using the Long-range Energy Alternative Planning software, with which two scenarios were analyzed. In the first one, it was considered that new vehicles would be acquired, with the same behavior a buyer would have had from 2012 to 2019, when this tax was a current law. The second scenario, without this imposition, considered that new vehicles would be acquired according to the demand pattern between 2008 and 2011, the period prior to this demand. From the analysis of each scenario, it was concluded that by 2025, there would have been an approximate reduction of 29,200,000 gal of gasoline eq. that represents a saving of 5% in the respective energy consumption, as well as a lower emission of carbon dioxide. A tax on the engine displacement of the vehicle discourages the purchase of unnecessarily large vehicles, which implies a lower consumption of petroleum derivatives and a lower emission of greenhouse gases.

Bridging the impactibility gap in population health management: a systematic review

ObjectivesAssess whether impactibility modelling is being used to refine risk stratification for preventive health interventions.DesignSystematic review.SettingPrimary and secondary healthcare populations.PapersArticles published from 2010 to 2020 on the use or implementation...

The influence of home care supply on delayed discharges from hospital in England

BackgroundDelayed transfers of care (DTOC) of patients from hospital to alternative care settings are a longstanding problem in England and elsewhere, having negative implications for patient outcomes and costs to health and social care systems. In England, a large proportion of DTOC are attributed to a delay in receiving suitable home care. We estimated the relationship between home care supply and delayed discharges in England from 2011 to 2016.MethodsReduced form fixed effects OLS models of annual DTOC attributed to social care at local authority (LA)-level from 2011 to 2016 were estimated, using both number of days and patients as the dependent variable. A count of home care providers at LA-level was utilised as the measure of home care supply. Demand (e.g. population, health, income) and alternative supply (e.g. care home places, local unemployment) measures were included as controls. Instrumental Variable (IV) methods were used to control for any simultaneity in the relationship between DTOC and home care supply. Models for DTOC attributed to NHS and awaiting a home care package were used to assess the adequacy of the main model.ResultsWe found that home care supply significantly reduced DTOC. Each extra provider per 10 sq. km. in the average local authority decreased DTOC by 14.9% (equivalent to 449 days per year), with a per provider estimate of 1.6% (48 days per year). We estimated cost savings to the public sector over the period of analysis from reduced DTOC due to increased home care provision between £73 m and £274 m (95% CI: £0.24 m to £545.3 m), with a per provider estimate of savings per year of £12,600 (95% CI: £900 to £24,500).ConclusionDTOC are reduced in LAs with better supply of home care, and this reduces costs to the NHS. Further savings could be achieved through improved outcomes of people no longer delayed. Appropriate levels of social care supply are required to ensure efficiency in spending for the public sector overall.

Quantification of energy and cost reduction from decreasing dissolved oxygen levels in full-scale water resource recovery facilities.

Aeration systems often lack the efficiency to maintain a desired residual dissolved oxygen (DO) concentration in the tank in part because little consideration is given to the dynamic daily and seasonal loading conditions. Although advanced aeration controllers exist, the majority of plants have DO set points typically based on common practice and literature values rather than site-specific conditions, which can result in DO set points higher than those necessary to meet treatment objectives. DO set point reduction strategies have primarily been proposed through either static or dynamic simulations. In this study, the substantial improvements associated with DO set point reduction are demonstrated at full scale. A yearlong characterization of full-scale aeration dynamics captured the effect of diurnal and seasonal fluctuations on oxygen transfer and energy demand and so facilitated the estimation of the potential savings of DO reduction strategies. Full-scale validation provided direct evidence of DO reduction strategies inducing an overall enhancement of oxygen transfer efficiency along the different bioreactors, while confirming that energy savings as high as 20% were feasible. This study quantifies the influence of oxygen transfer efficiency on operating choices and site-specific conditions (control strategy, loading conditions, and influent flow variability). PRACTITIONER POINTS: We quantified the energy reduction and cost savings associated with a DO reduction in an aeration tank. For each 0.2mg/L of DO decreased, the average power demand reduction per unit water treated exceeded 17%. Field measurements of dynamic alpha values eliminate the uncertainty in estimating aeration energy and cost savings from DO variations.

Improved preventive care clinical decision-making efficiency: leveraging a point-of-care clinical decision support system

BackgroundElectronic medical records are widely used in family practices across Canada and can improve health outcomes. However, recent reports indicate that physicians using electronic medical records work longer and have less direct patient contact which may contribute to burnout. Therefore, new and innovative digital tools are essential to reduce physician workloads and improve patient-physician interaction to address physician burnout. The objective of this study was to assess the efficiency and accuracy of clinical decision-making when using a new preventive care point-of-care clinical decision support system (CDSS). An estimate of the potential annual time savings was also determined. This study also assessed physician reported perceived usefulness and ease of use of the CDSS.MethodsQuantitative and qualitative data were collected during this study. Each participant evaluated two simulated patient charts and identified which preventive care metrics were due. The participants recorded their decisions and the time required to assess each chart. Participants then completed a Technology Acceptance Model survey regarding the perceived usefulness and ease of use of the CDSS, which included qualitative feedback. The amount of time saved was determined and participants’ clinical decision-making accuracy was scored against current Canadian preventive care guidelines. The number of preventive care specific visits completed per year was determined using clinic billing data.ResultsThe preventive care CDSS saved an average of 195.7 s of chart review time (249.5 s vs 445.2 s; P < 0.001). A total of 1520 preventive visits were performed at Primrose and Bruyère Family Medicine Centres. Extrapolated across the organization, implementation of the new tool could save 82.6 h per year. Decision-making accuracy was not affected by the new tool (78.4% vs 80.9%, P > 0.05). Participants rated the perceived ease of use and usefulness to be very high.ConclusionsNew digital tools may reduce providers’ workload without impacting clinical decision-making accuracy. Participants indicated that the preventive care CDSS was useful and easy to use. Further software development and clinical studies are required to further improve and characterize the effect this new CDSS has when implemented in clinical practice.

The role of hygrothermal modelling for different housing typologies by estimating indoor relative humidity, energy usage and anticipation of fuel poverty

The nature of deem-to-satisfy standards in building energy performance results in a lack of insight over their consequences. As a result, there is a huge gap between regulation and implementation in the construction industry. The procedure proposed in this article aims to implement the probabilistic approach method to design retrofitting solutions for building energetic rehabilitation and relative humidity management. This is completed by considering the uncertainty associated with a building's physical parameters, savings estimation, weather forecast, occupants' behaviour and building ventilation. A computational hygrothermal modelling approach is utilised to emphasise the differences in the indoor conditions for two typologies of residential houses common in the United Kingdom, located in three cities with different weather conditions and fuel poverty levels: Liverpool, Aberdeen, and Kent. The first model corresponds to houses built to standards from the 1920s′, with solid external walls, and the second house model uses the 2010s′ construction solution, where the double-glazed windows and the wall insulation materials are implemented. The indoor temperature is demonstrated to be efficient in the range between 16 °C - 20 °C. Lowering the current temperature set point to about 16 °C will give healthier indoor conditions regardless of dwelling, highlighting the need to review the regulation. The simulation shows that 2% heating energy can be conserved for indoor thermal comfort and extensive environmental benefits. On particular assumption of energy use per household, this work will annually contribute to the carbon footprint reduction of approximately 635.8–847 thousand tonnes.

Cost-benefit Analysis of the Coping and Promoting Strength Program.

This study sought to estimate the net benefits and return on investment (ROI, %) of the Coping and Promoting Strength (CAPS) program to families and insurers, respectively, using data from a multi-year follow up of 136 US families who had participated in a randomized efficacy trial of CAPS. CAPS is a brief parent-focused psychosocial intervention that was compared to information monitoring in the trial. Of the 136 original participants, 113 (83%) completed follow-up interviews 7.1 years, on average, after the CAPS study baseline (mean follow-up age: 15.8 years; range: 13.1 to 20.8 years). Parent-reported willingness-to-pay values and estimates of behavioral healthcare cost savings from delayed onset of anxiety were used to simulate the average net benefits of CAPS to families and insurance plans, respectively, assuming patients pay 20% coinsurance. Psychologists in private offices were expected to charge an average of approximately $195 per CAPS session or $1417 in total in 2020 dollars. The estimated family share of the total CAPS session cost was $283 per youth, while the insurer share was $1134 per youth. Given these costs, the CAPS intervention was estimated to result in average overall net benefits of $1033 per youth (95% CI: -$546 to $2611). Families gained $344 (95% CI: $232 to $455 per family) for an ROI of 121%. Insurance plans on average gained a net savings of $689 per youth (95% CI: -$778 to $2156 per youth) for an average ROI of 61%. In this multiyear follow-up of offspring of anxious parents, exposure to the CAPS pediatric anxiety prevention program was found to be more economically efficient than was waiting for an anxiety disorder to be diagnosed.ClinicalTrials.gov Identifier:NCT00847561.

Estimating Smart Wi-Fi Thermostat-Enabled Thermal Comfort Control Savings for Any Residence

Nowadays, most indoor cooling control strategies are based solely on the dry-bulb temperature, which is not close to a guarantee of thermal comfort of occupants. Prior research has shown cooling energy savings from use of a thermal comfort control methodology ranging from 10 to 85%. The present research advances prior research to enable thermal comfort control in residential buildings using a smart Wi-Fi thermostat. “Fanger’s Predicted Mean Vote model” is used to define thermal comfort. A machine learning model leveraging historical smart Wi-Fi thermostat data and outdoor temperature is trained to predict indoor temperature. A Long Short-Term-Memory neural network algorithm is employed for this purpose. The model considers solar heat input estimations to a residence as input features. The results show that this approach yields a substantially improved ability to accurately model and predict indoor temperature. Secondly, it enables a more accurate estimation of potential savings from thermal comfort control. Cooling energy savings ranging from 33 to 47% are estimated based upon real data for variable energy effectiveness and solar exposed residences.