Almost 60% of all ammonia (NH3) emissions are from livestock manure. Understanding the sources and magnitude of NH3 emissions from manure systems is critical to implement mitigation strategies. This ...study models 13 archetypical conventional (5 farms), organic (5 farms), and grazing (3 farms) dairy farms to estimate NH3 emissions from manure at the barn, storage, and after land application. Mitigation practices related to management of the herd, crop production, and manure are subsequently modeled to quantify the change in NH3 emissions from manure by comparing archetypical practices with these alternative practices. A mass balance of nutrients is also conducted. Emissions per tonne of excreted manure for the manure system (barn, storage, and land application) range from 3.0 to 4.4 g of NH3 for conventional farms, 3.5 to 4.4 g of NH3 for organic farms, and 3.4 to 3.9 g of NH3 for grazing farms. For all farm types, storage and land application are the main sources of NH3 emissions from manure. In general, solid manures have higher emission intensities due to higher pH during storage (pH = 7.4 for liquid, 7.8 for slurry, and 8.5 for solid manure) and lower infiltration rates after land application when compared with slurry and liquid manures. The most effective management practices to reduce NH3 emissions from manure systems are combining solid-liquid separation with manure injection (up to 49% reduction in NH3 emissions), followed by injection alone, and reducing crude protein in the dairy ration, especially in organic and grazing farms that have grazing and forages as the main component of the dairy ration. This study also shows that the intensity of NH3 emissions from manure depends significantly on the functional unit and presents results per manure excreted, total solids in excreted manure, animal units, and fat- and protein-corrected milk.
In today's manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision-makers to prioritize green manufacturing. The Internet ...of Things paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from manufacturing processes can be collected easily, and then analyzed, to improve energy-aware decision-making. Relying on a comprehensive literature review and on experts' insight, this paper contributes to the understanding of energy-efficient production management practices that are enhanced and enabled by the Internet of Things technology. In addition, it discusses the benefits that can be obtained thanks to adopting such management practices. Eventually, a framework is presented to support the integration of gathered energy data into a company's information technology tools and platforms. This is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage on such data in order to improve energy efficiency, and therefore competitiveness, of manufacturing companies. With the outcomes of this paper, energy managers can approach the Internet of Things adoption in a benefit-driven manner, addressing those energy management practices that are more aligned with company maturity, measurable data and available information systems and tools.
•Illustrates energy management practices at production level which will be enhanced and enabled by Internet of Things.•Illustrates the benefits of adopting IoT-based energy management practices at production level.•Proposes IoT-based energy management in production.•Provides a framework to support the integration of energy data gathered in real-time into production management.•Shows how much room there is for improved energy efficiency once integrating real-time energy data in production management.
This publication summarizes N cycling, different types of N losses, and approaches that may help to minimize N loss in row crop production systems in Florida. Written by Hardeep Singh, Lakesh Sharma, ...Libbie Johnson, Ethan Carter, and Pratap Devkota, and published by the UF/IFAS Agronomy Department, January 2023.
•Optimal designs of green roof, bioretention and porous pavement are derived.•Peak flow reduction and life cycle cost are computed for various designs and storms.•Porous pavement and green roof are ...respectively most and least cost-effective.•All practices are more cost-effective in Seattle than in Hong Kong.•Sensitivity to design parameters does not influence main conclusions.
Low impact development (LID) practices have become more important in urban stormwater management worldwide. However, most research on design optimization focuses on relatively large scale, and there is very limited information or guideline regarding individual LID practice designs (i.e., optimal depth, width and length). The objective of this study is to identify the optimal design by assessing the hydrological performance and the cost-effectiveness of different designs of LID practices at a household or business scale, and to analyze the sensitivity of the hydrological performance and the cost of the optimal design to different model and design parameters. First, EPA SWMM, automatically controlled by MATLAB, is used to obtain the peak runoff of different designs of three specific LID practices (i.e., green roof, bioretention and porous pavement) under different design storms (i.e., 2yr and 50yr design storms of Hong Kong, China and Seattle, U.S.). Then, life cycle cost is estimated for the different designs, and the optimal design, defined as the design with the lowest cost and at least 20% peak runoff reduction, is identified. Finally, sensitivity of the optimal design to the different design parameters is examined. The optimal design of green roof tends to be larger in area but thinner, while the optimal designs of bioretention and porous pavement tend to be smaller in area. To handle larger storms, however, it is more effective to increase the green roof depth, and to increase the area of the bioretention and porous pavement. Porous pavement is the most cost-effective for peak flow reduction, followed by bioretention and then green roof. The cost-effectiveness, measured as the peak runoff reduction/thousand Dollars of LID practices in Hong Kong (e.g., 0.02L/103US$s, 0.15L/103US$s and 0.93L/103US$s for green roof, bioretention and porous pavement for 2yr storm) is lower than that in Seattle (e.g., 0.03L/103US$s, 0.29L/103US$s and 1.58L/103US$s for green roof, bioretention and porous pavement for 2yr storm). The optimal designs are influenced by the model and design parameters (i.e., initial saturation, hydraulic conductivity and berm height). However, it overall does not affect the main trends and key insights derived, and the results are therefore generic and relevant to the household/business-scale optimal design of LID practices worldwide.
Implementing biosecurity protocols is necessary to reduce the spread of disease on dairy farms. In Ontario, biosecurity implementation is variable among farms and barriers to biosecurity are unknown. ...Thirty-five semi-structured interviews were conducted between July 2022 and January 2023 with dairy producers (n = 17) and veterinarians (n = 18). Participants also completed a demographic survey. Thematic analysis was performed with constructivist and grounded theory paradigms. Thematic coding was done inductively using NVivo software. Dairy producers' understanding of the definition of biosecurity varied, with all understanding that it was to prevent the spread of disease. Furthermore, the most common perception was that biosecurity prevented the spread of disease onto the farm. Both veterinarians and producers stated that closed herds were one of the most important biosecurity protocols. Barriers to biosecurity implementation included a lack of resources, internal and external business influencers, individual perceptions of biosecurity, and a lack of industry initiative. Understanding the barriers producers face provides veterinarians with the chance to tailor their communication to ensure barriers are reduced, or for other industry members to reduce the barriers.
Urban greenspace (UGS) is recognized to confer significant societal benefits, but few studies explored the microbial communities and antibiotic resistance genes (ARGs) from different urban greenspace ...types. Here, we collected leaf and soil samples from forest, greenbelt, and parkland to analyze microbial community assembly and ARG profile. For phyllosphere fungal community, the α-diversity was higher in forest, compared to those in greenbelt and parkland. Moreover, urban greenspace types altered the community assembly. Stochastic processes had a greater effect on phyllosphere fungal community in greenbelt and parkland, while in forest they were dominated by deterministic processes. In contrast, no significant differences in bacterial community diversity, community assembly were observed between the samples collected from different urban greenspace types. A total of 153 ARGs and mobile genetic elements (MGEs) were detected in phyllosphere and soil with resistance to the majority classes of antibiotics commonly applied to humans and animals. Structural equation model further revealed that a direct association between greenspace type and ARGs in the phyllosphere even after considering the effects of all other factors simultaneously. Our findings provide new insights into the microbial communities and antibiotic resistome of urban greenspaces and the potential risk linked with human health.
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•Urban greenspace (UGS) types alter the microbial community assembly.•UGS types influence the fungal community α diversity in phyllosphere.•UGS types had a direct effect on the abundance of ARGs in the phyllosphere.•Phyllosphere microbes were more sensitive to human disturbances than soils.
This study proposes a novel framework to identify smart-sustainable SCMP (supply chain management practices) as supplier selection criteria for a smart supply chain. Supplier selection consists of ...two parts: criteria weights determination and suppliers ranking. DEMATEL (Decision Making Trial and Evaluation Laboratory) has been acknowledged as a relatively feasible method for determining the criteria weights due to its effectiveness in acquiring the interrelationships between criteria. TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) has been identified as the most frequently used method for supplier ranking due to its superiority in quickly finding the best alternatives. However, most existing research contains scant study of the simultaneous manipulation of internal uncertainty (individual linguistic vagueness) and external uncertainty (group preference diversity), which are involved in the supplier selection process. Therefore, this study proposes a hybrid rough-fuzzy DEMATEL-TOPSIS approach to sustainable supplier selection for a smart supply chain. The proposed method combines the strength of the fuzzy set in handling internal uncertainty and the advantages of the rough set in manipulating external uncertainty. The effectiveness and accuracy of the proposed methodology are illustrated through its application in sustainable vehicle transmission supplier selection and through comparisons with other methods.
•New topic on sustainable supplier selection for smart supply chain is put forward.•A novel rough-fuzzy TOPSIS-DEMATEL is proposed for sustainable supplier selection.•Internal and external uncertainties are manipulated by proposed rough-fuzzy numbers.•Decision uncertainty is measured through the presented rough-fuzzy polygons.•Showed the method’s feasibility with vehicle transmission supplier selection.
This paper explores relationships between lean manufacturing practices, environmental management (e.g., environmental management practices and environmental performance) and business performance ...outcomes (e.g., market and financial performance). The hypothesized relationships of this model are tested with data collected from 309 international manufacturing firms (IMSS IV) by using AMOS. The findings suggest that prior lean manufacturing experiences are positively related to environmental management practices. Environmental management practices alone are negatively related to market and financial performance. However, improved environmental performance substantially reduces the negative impact of environmental management practices on market and financial performance. The paper provides empirical evidences with large sample size that environmental management practices become an important mediating variable to resolve the conflicts between lean manufacturing and environmental performance. Additional contextual analyses suggest that differences exist in terms of the strengths and statistical significance of some of the proposed relationships. Thus, for effective implementation of environmental management, firms need to measure environmental performance through which the impact of environmental management on other business performance outcomes is examined.
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