A frequently overlooked topic in the food life cycle assessment studies is the environmental impact of food storage and retailing. In the cold food supply chains, the perishables distribution centers (PDCs) and supermarkets play a vital role and are the most energy intensive commercial buildings due to cooling. Thus, this study focused on energy, water, and refrigerant use of PDCs and supermarkets and their implications on the environmental impacts of perishables in the United States. First, the life cycle assessment (LCA) method was used to calculate the climate change impact, non renewable energy use, and water scarcity impact of perishables freezers and coolers and supermarkets' departments. In addition, the national storage and supermarket impacts were allocated to different perishables based on the average food length of stay, storage packability, and supermarket sales. For example, in California, which has the largest retailing network, the PDCs and supermarkets produce more than 3,941 million kg of CO2-eq, 61,920 million of MJ, and 302 million of m(3) annually over their life cycle. The climate change impact results for an average length of stay of perishables at the storage was from 1.9E-04 to 0.016 kg CO2-eq/kg for vegetables and fruit, respectively, and for retailing from 0.002 to 8.12 kg CO2-eq/kg for fish and seafood and frozen seafood, respectively. The research provided flexible and adaptive formulae, procedures, and data, which can be used to assess the environmental impacts of perishables storage and retailing in any state. As the cold food supply chain expands, this research may help reduce environmental impacts of food storage and retailing, inform future storage and supermarket management and planning, optimize the supply chain network design, and provide support for a more effective food waste policy.

Buildings consume half the global electricity and generate one third of greenhouse gas (GHG) emissions. Distribution centers (DCs) have an important role in food distribution and sustainability. Omitting food distribution from food life cycle assessments (LCAs) is a data gap that may affect the overall impacts of food. We showed multi-facility state-level environmental impacts of the largest DC network in the United States. Our method included regional resolution of the life cycle inventory (LCI) combined with the regional life cycle impact assessment (LCIA) method. Three types of food DCs in different climate zones were assessed using the LCA method. Primary energy use in grocery and perishable DCs was refrigeration (80%) and in general merchandise were conveyor systems (50%). Building material and lighting became relevant for non-refrigerated spaces and in low-energy impact states. The location-specific provenance of electricity energy sources such as coal affected the process and substance impact contributors and magnitude of the environmental impacts, for example, in the energy, climate, water, and land nexus. Water impact depended on energy sources and local water availability. Land use was dominated by activities in the supply chain and not building construction area. Achieving a low environmental impact supply chain is a major goal of producers, distributors and retailers. Energy efficiency through green building standards and distributed energy may improve sustainability of DCs. (C) 2018 Elsevier B.V. All rights reserved.

Walmart Inc., the U.S. and world's largest grocery retailer, owns a perishables, grocery, and general merchandise distribution center network, which stores and distributes refrigerated and non-refrigerated food. Finding cost-effective strategies to implement solar and wind-powered electricity in their distribution centers was the central objective of this research. The study analyzed the tradeoffs and effects on costs and climate change impact related to the increase of renewable energy use in the distribution centers. The research combined the life cycle assessment and quantitative methods including the Monte Carlo uncertainty analysis and the multi-objective optimization. A life cycle assessment-based multi-objective optimization model was built to find cost-effective strategies to minimize fossil energy use and mitigate the impact of the Walmart Inc. distribution center network on climate change. The bi-objective and the triple-objective optimization included a number of combinations of minimal costs, non-renewable fossil energy use, and climate change impact criteria. The results of the multi objective optimizations were Pareto-optimal solutions obtained by weighing the importance of chosen criteria from the baseline to the zero energy scenarios. A selection of the Pareto-optimal solutions included the good, the better, and the zero energy building scenarios. A better building was a Pareto-optimal set of buildings, which demonstrated superiority from the life cycle assessment perspective. The superiority of Pareto-optimal solutions was evaluated using the Monte Carlo pairwise comparison. The good distribution centers were characterized by the Pareto-optimal solutions between the baseline and the better distribution centers. Finally, the zero energy general merchandise distribution centers were mostly the Pareto-optimal solutions with a 100% share of solar energy. For the zero energy grocery and perishables distribution centers the solutions were a combination of solar and supplemental wind energy because refrigerated warehouses are more energy intensive. The study provided the benchmark results that may improve distribution centers and other buildings and a framework to test environmental and renewable energy policies in buildings.

SummaryBeverage producers in the United States choose packaging based on cost and consumer preference. Monolayer high‐density polyethylene (HDPE) and gable‐top carton containers have long dominated the U.S. fluid milk market, but pressure for more sustainable packaging is increasing. We present a broad discussion on environmental sustainability of 18 fluid milk containers through life cycle assessment. Because different container types require unique milk processing, distribution, and disposal and incur or avoid milk losses, fluid milk delivery systems (FMDSs) are evaluated, rather than containers in isolation. By assessing FMDSs, a complete measure of containers’ environmental sustainability was obtained. Despite conservative assumptions about milk losses, differences in container size, milk processing, distribution, and container recycling, pair‐wise cradle‐to‐grave comparisons of FMDSs show there are no superior FMDSs. But, 500‐ to 1,000‐milliliter FMDSs are potentially superior to ≥half gallon if they prevent milk losses. Thus, the future of FMDSs in the United States depends on the industry's ability to prevent distribution (12%) and consumption milk losses (20% to 35%). Farm‐gate‐to‐grave comparisons showed that chilled HDPE FMDSs are superior to other plastic and chilled paperboard FMDSs for climate‐change impact, but the result is inconclusive for chilled HDPE to ambient (unrefrigerated) paperboard or plastic pouch FMDS comparisons. Plastic pouch FMDSs show potential to reduce nonrenewable fossil energy, but need to be recyclable. Ambient FMDSs are superior to chilled FMDSs for water depletion. Eight‐ounce paperboard FMDSs are superior to 8‐ounce plastic FMDSs. Thus, alternative FMDSs may improve environmental sustainability of the U.S. postfarm fluid milk supply chain.

Measurement and verification (M&V) of energy efficiency projects is an important activity for energy managers, government agencies, building owners, and utility representatives. Misapplication or misunderstanding of M&V protocol requirements can cause significant error in energy savings calculations. Additionally, incomplete knowledge of how common data loggers function can create confusion around the measurements being taken and the results being reported. This article seeks to further the understanding of data collection intervals, M&V costs, and M&V plan uncertainty. Additionally, a detailed description of how several types of electrical data loggers function is presented, showing the advantages and potential disadvantages of each.

One-half of the total electrical energy use in Saudi Arabia is consumed by the residential building sector. This is a higher proportion than other countries, due largely to inefficient buildings and the harsh climate of the Arabian Peninsula. In this study, a typical residential building (Villa) is modeled using eQuest 3.65, a building energy simulation program, to estimate the impact of dust storms on building energy performance across 13 regions in the Kingdom of Saudi Arabia. In particular, hourly dust fallout was modeled to predict monthly averaged dust accumulation on the flat roof surface. Based on the predicted dust accumulation amounts, a newly developed transient absorptivity model was used to calculate the Villa's roof solar absorptivity. Model predictions showed that monthly averaged dust accumulation varied between 8.0 and 81.6 g/m(2)/month for the selected sites. It was found that accumulated dust on cool roof (lambda=0.2) leads to cooling increase from 110.3 to 181.9 kWh/m(2)/year with using a roof U-value of 2.84 W/m(2) K. Similarly, accumulated dust on a typical roof (lambda=0.4) leads to cooling increase between 53.6 and 126.8 kWh/m(2)/year for the selected sites. Heating reduction was found to be only between 0.1 and 4.6 kWh/m(2)/year, an insignificant benefit compared to the annual cooling increase. Overall, dust storms were found to have a significant impact on energy use, especially for poorly or uninsulated residential buildings.

This article evaluates the impact of effective sky temperatures on building radiation exchange under clear, cloudy, and dusty conditions for extremely hot and dry climates. In part, a dusty sky temperature model has been introduced as a function of atmospheric aerosol optical depth. The sky radiative exchange was evaluated using a one-dimensional transient heat transfer model with numerical calculations performed using the fully implicit finite-difference method. The newly available ASHRAE 2013 clear sky model was evaluated and implemented to calculate the hourly incident solar radiation for a horizontal roof under the extremely hot-dry climate conditions of Riyadh, Saudi Arabia. Results showed that in clear sky conditions, sky longwave radiation contributes to a reduction of the total heat gain. A daily mean clear sky cooling around 2645 and 2385 W-hr/m(2) was estimated for July and January, respectively. In contrast, cloud and dust covers increase effective sky temperature and diminish the role of sky radiative cooling. Depending on severity, the mean contributed sky cooling heat exchange was found to range between 436 and 1636 W-hr/m(2) for dust storm and scattered cloudy sky conditions, respectively. Similarly, the ASHRAE 2013 clear sky model and the sky temperature models were shown for four other extremely hot-dry global sites.

Buildings consume 79% of Saudi electricity, of which 70% is consumed by air conditioning (AC) systems as a result of the high ambient temperatures during the long summer season and heavily subsidized cost of electricity. Fossil fuels are burned as the primary energy source in power plants causing environmental impacts. A cradle-to grave regional life cycle assessment (LCA) of residential building air conditioning has been performed to evaluate these impacts. The results show that the use phase is responsible for largest share of the environmental impacts, and that the type of primary fuel used influences the magnitude of the impacts in each region. Copper and steel production dominate the manufacturing phase impact and the end-of-life (EOL) phase results in environmental benefits by reduction in the need for virgin materials. The overall contribution of transportation is minor. Economic considerations influence decisions more than environmental concerns in a developing country like Saudi Arabia. To evaluate the relationship of economics to environmental effects, life cycle cost (LCC), and payback period (PBP) are included with the use of Monte Carlo simulation (MCS) to model the effect of the variability in input prices on the uncertainty associated with the final results. (C) 2015 Elsevier B.V. All rights reserved.

This paper presents an effort to estimate the impact of dust accumulation on exterior building roof absorptivity and total radiative heat gain. A new model is introduced to calculate a building solar absorptivity as a function of dust accumulation rate. Hourly dust deposition is modeled using the Non-hydrostatic Multi-scale Model (NMMB) to predict monthly averaged dust accumulation over time. The correlation sensitivities to its input parameters and the impact of dust accumulation on building annual loads are also studied. Results show that dust accumulation increases the roof solar absorptivity from its initial value up to dust absorptivity based on the site climatic condition and roof characteristics. The predicted monthly averaged accumulated dust for all studied sites varies between 1.3 and 73.8 g/m(2)/month. The new model has resulted in an annual cooling space increase of 44.7-181.1 kWh/m(2)/year, for the selected hot-dry sites with moderate to extreme dust storm conditions. Heating reductions were found to be 0.5-13.1 kWh/m(2)/year which are not significant in comparison to the increase in annual cooling load. The results of this work were attempted to improve the predictive capability of current building simulation models. (C) 2015 Elsevier B.V. All rights reserved.

Energy use for a poultry broiler processing plant was analyzed using available monthly utility bill information, utility-provided 15-minute interval data, and short-term 30-second sub-metered data at the unit operation level. Energy intensities were determined in terms of the whole plant and unit operations, and both compared to three broiler processing plants that operated in the late 1970s. It was found that secondary utilities, including water chilling, ice making, and compressed air, are the largest energy consumers in the process, followed by offal, receiving, killing and picking (RKP) and evisceration. On a total energy (MMBtu) basis, natural gas usage for steam generation by boilers was higher than site electricity consumption. Overall, the total annual energy intensity was found to be 2.46 MMBtu/1000 head of broilers processed. The largest opportunities for reducing energy intensity exist in the process refrigeration and hot water generation systems. Finally, it was concluded that measuring and tracking energy intensity on a unit operations level provides valuable insight into how energy is used, how that compares to similar facilities and where potentially to target energy efficiency efforts.

Computer simulation is a useful tool for benchmarking electrical and fuel energy consumption and water use in a fluid milk plant. In this study, a computer simulation model of the fluid milk process based on high temperature, short time (HTST) pasteurization was extended to include models for processes for shelf-stable milk and extended shelf-life milk that may help prevent the loss or waste of milk that leads to increases in the greenhouse gas (GHG) emissions for fluid milk. The models were for UHT processing, crossflow microfiltration (MF) without HTST pasteurization, crossflow MF followed by HTST pasteurization (MF/HTST), crossflow MF/HTST with partial homogenization, and pulsed electric field (PEF) processing, and were incorporated into the existing model for the fluid milk process. Simulation trials were conducted assuming a production rate for the plants of 113.6 million liters of milk per year to produce only whole milk (3.25%) and 40% cream. Results showed that GHG emissions in the form of process-related CO2 emissions, defined as CO2 equivalents (e)/kg of raw milk processed (RMP), and specific energy consumptions (SEC) for electricity and natural gas use for the HTST process alone were 37.6 g of CO(2)e/kg of RMP, 0.14 MJ/kg of RMP, and 0.13 MJ/kg of RMP, respectively. Emissions of CO2 and SEC for electricity and natural gas use were highest for the PEF process, with values of 99.1 g of CO(2)e/kg of RMP, 0.44 MJ/kg of RMP, and 0.10 MJ/kg of RMP, respectively, and lowest for the UHT process at 31.4 g of CO(2)e/kg of RMP, 0.10 MJ/kg of RMP, and 0.17 MJ/kg of RMP. Estimated unit production costs associated with the various processes were lowest for the HTST process and MF/HTST with partial homogenization at $0.507/L and highest for the UHT process at $0.60/L. The increase in shelf life associated with the UHT and MF processes may eliminate some of the supply chain product and consumer losses and waste of milk and compensate for the small increases in GHG emissions or total SEC noted for these processes compared with HTST pasteurization alone. The water use calculated for the HTST and PEF processes were both 0.245 kg of water/kg of RMP. The highest water use was associated with the MF/HTST process, which required 0.333 kg of water/kg of RMP, with the additional water required for membrane cleaning. The simulation model is a benchmarking framework for current plant operations and a tool for evaluating the costs of process upgrades and new technologies that improve energy efficiency and water savings.

The objective of this project was to characterize the energy uses in a broiler processing facility, and identify specific measures to improve energy efficiency. Electricity was used for refrigeration, lighting, air conditioning, pumps, compressed air and other mechanical drives. Natural gas was used for production of steam, further used to generate hot water, for processing and sanitation, as well as space heating. On total energy (MMBtu) basis, natural gas usage for steam generation by boilers was higher than site electricity consumption. Energy efficiency recommendations included insulating steam pipes and valves, installing boiler combustion control and automatic blowdown system to improve boiler efficiency, adding variable speed drives and inverter duty motors to the cooling towers of the refrigeration system, upgrading to energy efficient lighting, upgrading to more efficient air compressor for the plant air system, etc. Many of these measures have guaranteed payback periods of 2 years, with some measures leveraging utility rebate program. Results from this project demonstrated that cost-effective energy saving opportunities are available in poultry processing plants and warrant investigation.

An analysis of greenhouse gas emissions (carbon dioxide equivalents, CO(2)e) was conducted from 2007 databases for 211,216 round trips of tank trucks that delivered raw milk from farms to processing plants in the United States of America. The total amount of milk was 4.81 x 10(9) kg, or about 17.4% of the 2007 total USA production for use as fluid milk products. Average round trip distance was 850 km resulting in tailpipe emissions of 0.050 kg CO(2)e kg(-1) milk delivered or 0.071 kg CO(2)e kg(-1) milk consumed representing 3.5% of the total greenhouse gas emissions for fluid milk consumed. Based on this we estimate the total emissions for fluid milk delivery from farm to processor in the US at 1.3 x 10(9) kg CO(2)e y(-1). Some overall reduction in total delivery distance could be realized by realigning farm-to-processor relationships, especially in regions where farms are equally distant from multiple processors. (C) 2012 Elsevier Ltd. All rights reserved.

In recent years, nanoparticles have received considerable attention as a potential additive to heat transfer fluids (e. g., refrigerant) in order to increase their overall heat transfer capabilities. The potential of carbon nanotubes (CNT) to circulate throughout a vapor compression air-conditioning system was experimentally investigated in this research. Six grams of CNT were added to the R-410A and polyol ester oil used by a 2.5 ton (8.79 kW) unitary air-conditioning system, and then continuously operated for 168 hours. A distribution map of CNT was developed based on post-experiment destructive inspection of the system. For the 92.6 grains (6 g) initially placed into the compressor, approximately 38.6 grains (2.5 g) were recovered from inside the compressor, leaving 54 grains (3.5 g) distributed elsewhere throughout the system. A portion of the CNT found were in the process of flowing with the refrigerant and oil (18.5 gr [1.2 g]) outside the compressor after the 168 hour test), but the majority had become strongly adhered to the interior surface walls. The location of the heaviest fouling was found in the first two to three feet (0.61-0.91 m) of tubing in each aluminum condenser circuit and a total of 25.5 grains (1.65 g) throughout the condenser.

Energy-savings measures have been implemented in fluid milk plants to lower energy costs and the energy-related carbon dioxide (CO2) emissions. Although these measures have resulted in reductions in steam, electricity, compressed air, and refrigeration use of up to 30%, a benchmarking framework is necessary to examine the implementation of process-specific measures that would lower energy use, costs, and CO2 emissions even further. In this study, using information provided by the dairy industry and equipment vendors, a customizable model of the fluid milk process was developed for use in process design software to benchmark the electrical and fuel energy consumption and CO2 emissions of current processes. It may also be used to test the feasibility of new processing concepts to lower energy and CO2 emissions with calculation of new capital and operating costs. The accuracy of the model in predicting total energy usage of the entire fluid milk process and the pasteurization step was validated using available literature and industry energy data. Computer simulation of small (40.0 million L/yr), medium (113.6 million L/yr), and large (227.1 million L/yr) processing plants predicted the carbon footprint of milk, defined as grams of CO2 equivalents (CO2e) per kilogram of packaged milk, to within 5% of the value of 96 g of CO 2e/kg of packaged milk obtained in an industry-conducted life cycle assessment and also showed, in agreement with the same study, that plant size had no effect on the carbon footprint of milk but that larger plants were more cost effective in producing milk. Analysis of the pasteurization step showed that increasing the percentage regeneration of the pasteurizer from 90 to 96% would lower its thermal energy use by almost 60% and that implementation of partial homogenization would lower electrical energy use and CO2e emissions of homogenization by 82 and 5.4%, respectively. It was also demonstrated that implementation of steps to lower non-process-related electrical energy in the plant would be more effective in lowering energy use and CO2e emissions than fuel-related energy reductions. The model also predicts process-related water usage, but this portion of the model was not validated due to a lack of data. The simulator model can serve as a benchmarking framework for current plant operations and a tool to test cost-effective process upgrades or evaluate new technologies that improve the energy efficiency and lower the carbon footprint of milk processing plants.

Greenhouse gas (GHG) emissions were evaluated from crop production through the on-farm portion of the milk supply chain for five production regions in the USA derived from publicly available data and from 536 surveys of farm operations collected from dairy operations nationwide. The production weighted national average footprint at the farm gate was 1.23 kg carbon dioxide equivalent (CO(2)e) per kg of fat and protein corrected milk (fat, 4%; protein 3.3%). Regional differences in GHG emissions per kg milk produced can be primarily traced to differences in production and management practices. Feed-to-milk conversion efficiency is shown to be the single most important explanatory variable, followed by choice of manure management technology. While there is no one-size-fits-all solution, GHG emissions reduction opportunities exist across the spectrum of dairy management options. However, as with all decisions, it is important to weigh potential trade-offs with other environmental and economic impacts. (C) 2012 Elsevier Ltd. All rights reserved.

A life cycle assessment was conducted to determine a baseline for environmental impacts of cheddar and mozzarella cheese consumption. Product loss/waste, as well as consumer transport and storage, is included. The study scope was from cradle-to-grave with particular emphasis on unit operations under the control of typical cheese-processing plants.

This article presents a cradle-to-grave analysis of the United States fluid milk supply chain greenhouse gas (GHG) emissions that are accounted from fertilizer production through consumption and disposal of milk packaging. Crop production and on-farm GHG emissions were evaluated using public data and 536 farm operation surveys. Milk processing data were collected from 50 dairy plants nationwide. Retail and consumer GHG emissions were estimated from primary data, design estimates, and publicly available data. Total GHG emissions, based primarily on 2007 to 2008 data, were 2.05(90% confidence limits: 1.77-2.4) kg CO(2)e per kg milk consumed, which accounted for loss of 12% at retail and an additional 20% loss at consumption. A complementary analysis showed the entire dairy sector contributes approximately 1.9% of US GHG emissions. While the largest GHG contributors are feed production, enteric methane, and manure management; there are opportunities to reduce impacts throughout the supply chain. (C) 2012 Elsevier Ltd. All rights reserved.