Cradle-to-grave emissions from food loss and waste represent half of total greenhouse gas emissions from food systems.

Global greenhouse gas (GHG) emissions from food loss and waste (FLW) are not well characterized from cradle to grave. Here GHG emissions due to FLW in supply chain and waste management systems are quantified, followed by an assessment of the GHG emission reductions that could be achieved by policy and technological interventions. Global FLW emitted 9.3 Gt of CO2 equivalent from the supply chain and waste management systems in 2017, which accounted for about half of the global annual GHG emissions from the whole food system. The sources of FLW emissions are widely distributed across nine post-farming stages and vary according to country, region and food category. Income level, technology availability and prevailing dietary pattern also affect the country and regional FLW emissions. Halving FLW generation, halving meat consumption and enhancing FLW management technologies are the strategies we assess for FLW emission reductions. The region-specific and food-category-specific outcomes and the trade-off in emission reductions between supply chain and waste management are elucidated. These insights may help decision makers localize and optimize intervention strategies for sustainable FLW management.

Developed compositional source profile and estimated emissions of condensable particulate matter from coal-fired power plants: A case study of Yantai, China.

The emission and environmental impact of condensable particulate matter (CPM) from coal-fired power plants (CFPPs) are of increasing concern worldwide. Many studies on the characteristics of CPM emission have been conducted in China, but its source profile remains unclear, and its emission inventory remains high uncertainty. In this work, the latest measurements reported in the latest 33 studies for CPM inorganic and organic species emitted from CFPPs in China were summarized, and then a compositional source profile of CPM for CFPPs was developed for the first time in China, which involved 10 inorganic species and 71 organic species. In addition, the CPM emission inventory of CFPPs in Yantai of China was developed based on surveyed activity data, continuous emission monitoring system (CEMS), and the latest measurement data. The results show that: (1) Inorganic species accounted for 77.64 % of CPM emitted from CFPPs in Yantai, among which SO42- had the highest content, accounting for 23.74 % of CPM, followed by Cl-, accounting for 11.95 %; (2) Organic matter accounted for 22.36 % of CPM, among which alkanes accounted for the largest proportion of organic fraction (72.7 %); (3) Emission concentration method (EC) and CEMS-based emission ratio method (ERFPM,CEMS) were recommended to estimate CPM emissions for CFPPs; (4) The estimated CPM emission inventories of Yantai CFPPs in 2020 by the EC method and the ERFPM,CEMS method were 1231 tons and 929 tons, respectively, with uncertainties of -34 % ∼ 33 % and -27 % ∼ 57 %, respectively; (5) CPM emissions were mainly distributed in the northern coastal areas of Yantai. This developed CPM source profile and emission inventory can provide basic data for assessing the impacts of CPM on air quality and health. In addition, this study can provide an important methodology for developing CPM emission inventories and CPM emission source profiles for stationary combustion sources in other regions.

The Association Between Sleep Disturbance and Proinflammatory Markers in Patients With Cancer: A Meta-analysis.

BACKGROUND: Sleep disturbance is one of the symptoms with high incidence and negative influence in patients with cancer. A better understanding of the biological factors associated with sleep disturbance is critical to predict, treat, and manage this condition. OBJECTIVE: The aim of this study was to determine the correlation between sleep disturbance and proinflammatory markers in adult patients with cancer. METHODS: A systematic search was conducted in 7 databases from inception to March 1, 2020, for this meta-analysis. Two reviewers independently screened the studies, extracted data, and appraised the quality of the studies. Meta-analyses were conducted using Stata 12.0 software. RESULTS: Sixteen studies were included. Results indicated that sleep disturbance was associated with higher levels of the overall proinflammatory markers and that the effect size was small yet significant. Further subgroup analyses suggested that sleep disturbance was significantly associated with interleukin-6 and C-reactive protein, but not with interleukin-1ß or tumor necrosis factor-α. Meta-regression results indicated that only the sample source affected the association between sleep disturbance and proinflammatory markers. CONCLUSION: There was a positive relationship between sleep disturbance and selected proinflammatory markers in adult patients with cancer. IMPLICATION FOR PRACTICE: This review provides empirical support for the association between sleep disturbance and certain proinflammatory markers. Healthcare providers can further explore specific biomarkers to precisely identify the individuals at risk of sleep disturbance and develop targeted strategies for therapeutic and clinical interventions.

Application of the IoT in the Food Supply Chain─From the Perspective of Carbon Mitigation.

With the rising demands on supply chain transparency and food security, the rapid outspread of the Internet of Things (IoT) to improve logistical efficiency, and the rising penetration of sensor technology into daily life, the extensive integration of the IoT in the food sector is well anticipated. A perspective on potential life cycle trade-offs in regard to the type of integration is necessary. We conduct life cycle assessment (LCA) integrated with shelf life-food loss (SL-FL) models, showing an overall 5-fold leverage on carbon reduction, which is diet dependent and a function of income. Meat presents the highest leverage, 35 ± 11-times, owing to its high carbon footprint. Two-thirds (65%) of global sensors (1 billion) engaged in monitoring fruits and vegetables can mitigate less than 7% of the total reduced carbon emissions. Despite the expected carbon emission reductions, widespread adoption of the IoT faces multiple challenges such as high costs, difficulties in social acceptance, and regional variability in technological development. Furthermore, changes in the distribution of transportation resources and dealer service models, requirements regarding the accuracy of sensor data analysis, efficient and persistent operation of devices, development of agricultural infrastructure, and farmer education and training have all increased uncertainty. Nonetheless, the research trend in smart sensors toward smaller chips and the potential integration of machine learning or blockchain as further steps make it possible to leverage these advantages to facilitate market penetration. These insights facilitate the future optimization of the application of IoT sensors for sustainability.

Predictive Model of Psychological Distress in Patients With Lung Cancer: A Cross-sectional Study.

BACKGROUND: Patients with lung cancer suffer from significant psychological distress. The underlying theoretical model that may explain what predicts or mediates the degree of psychological distress has not been elucidated. OBJECTIVES: To describe the incidence of psychological distress in patients with lung cancer and to test a predictive theoretical model of psychological distress based on symptom burden, type D personality, social support, and intrusive thoughts. METHODS: Three hundred eighty-nine patients with stages I to IV lung cancer were recruited. Participants completed a battery of scales, including measures of psychological distress, symptom burden, type D personality, perceived social support, intrusive thoughts, and demographic and clinical characteristics. The predictive theoretical model was tested using structural equation modeling. RESULTS: Experiencing clinically significant psychological distress was reported by 63.75% of participants. Consistent with the social cognitive processing model, symptom burden, type D personality, social support, and intrusive thoughts all significantly and directly predicted the level of psychological distress in patients with lung cancer. Moreover, intrusive thoughts mediated the effects of type D personality and symptom burden on psychological distress; social support and symptom burden mediated the effects of type D personality on psychological distress. CONCLUSIONS: The majority of the participants experienced psychological distress at a clinically significant level. Intrusive thoughts and social support mediated the effects of type D personality and symptom burden on psychological distress. IMPLICATIONS FOR PRACTICE: Patients with type D personality and symptom burden should be identified. Interventions for targeting social support and intrusive thoughts might ultimately reduce their psychological distress.

Development and validation of the Professional Nursing Support Scale for Chinese patients with cancer.

PURPOSE: This study aimed to develop and test the psychometric properties of a Professional Nursing Support Scale for patients with cancer in mainland China. METHODS: The study was conducted in two phases from January 2017 to January 2020. Phase I involved item generation and developing a preliminary version of Professional Nursing Support Scale through literature review, qualitative interviews, content validity evaluation and a pilot study. Phase II involved psychometric properties testing of the Professional Nursing Support Scale in 700 patients with cancer recruited from four public hospitals in Anhui Province, China. RESULTS: A 49-item Professional Nursing Support Scale was finally developed. Exploratory factor analysis showed a four-factor structure of the 49-item Professional Nursing Support Scale, accounting for 56.95% of variance. Cronbach's α ranged from 0.91 to 0.94 for the four subscales. Confirmatory factor analysis further confirmed the best model fit of four-factor structure of the Professional Nursing Support Scale. The Professional Nursing Support Scale also showed an acceptable concurrent validity with Supportive Care Needs Scale short form 34 (r = 0.75, p < 0.001) and Psychological Distress Thermometer (r = 0.39, p < 0.001). CONCLUSIONS: The Professional Nursing Support Scale is a reliable and valid instrument to assess perceived needs of professional nursing support and support acquisition in relation to the care in Chinese patients with cancer.

Clinical competence and its association with self-efficacy and clinical learning environments among Chinese undergraduate nursing students.

Evaluation and cultivation of clinical competence in undergraduate nursing students are essential in nursing education. Self-efficacy and good clinical learning environments are expected to have a positive influence on the clinical competence of undergraduate nursing students, but few studies have focused on the relationships among clinical competence, self-efficacy, and clinical learning environments. This study aimed to examine clinical competence and its association with self-efficacy and clinical learning environments among Chinese undergraduate nursing students. A cross-sectional questionnaire survey was conducted with 1518 undergraduate nursing students being recruited from five medical colleges in China. The nursing students' clinical competence, self-efficacy, and clinical learning environments were assessed using a set of self-reported questionnaires, including Chinese versions of the Holistic Clinical Assessment Tool; General Self-Efficacy Scale; and Clinical Learning Environment, Supervision, and Nurse Teacher Evaluation Scale. Factors significantly associated with the clinical competence of undergraduate nursing students were professional interest, self-efficacy, and clinical learning environments, accounting for 36.1% of the total variance. Self-efficacy played a mediating role between clinical learning environments and clinical competence. The results of this study can be applied as reference for the enhancement of a nursing education program to improve the clinical competence of Chinese undergraduate nursing students.

The caring experience and supportive care needs of male partners for women with gynaecologic cancer: A qualitative literature review.

OBJECTIVE: To systematically review male partners' caring experience and supportive care needs when caring for women with gynaecologic cancer. METHODS: The PRISMA guidelines were used to conduct this systematic review. We performed a comprehensive literature search in nine databases and qualitative studies published in English or Chinese from inception to January 2020. The included papers were appraised, using the Critical Appraisal Skills Program tool for qualitative research. An inductive thematic analysis method was adopted to synthesise major findings to construct core concepts and themes. RESULTS: Eight studies were included in this review, and four overarching themes emerged the following: the negative experience of disease, the need for supportive care to cope, adapting to a new life and post-traumatic growth. CONCLUSIONS: This study shows that male partners had both negative and positive experiences in the caring process, and they could adjust themselves to some extent. Their perceived supportive care needs were often neglected. RELEVANCE TO CLINICAL PRACTICE: Male partners of women with gynaecologic cancer are an under-recognised group. The couple-oriented or family-oriented supportive care programmes should be implemented to meet the supportive care needs of male partners to enhance their health and well-being.

Multiple geophysical surveys for old landfill monitoring in Singapore.

One-dimensional boring presents limitations on mapping the refuse profile in old landfills owning to waste heterogeneity. Electrical imaging (EI) and multiple-analysis of surface wave (MASW) were hereby deployed at an old dumping ground in Singapore to explore the subsurface in relation to geotechnical analysis. MASW estimated the refuse boundary with a higher precision as compared to EI, due to its endurance for moisture variation. EI and MASW transection profiles suggested spots of interest, e.g., refuse pockets and leachate mounds. 3D inversion of EI and MASW data further illustrated the transformation dynamics derived by natural attenuation, for instance the preferential infiltration pathway. Comparison of geophysical surveys at different years uncovered the subterranean landfill conditions, indicating strong impacts induced by aging, precipitation, and settlement. This study may shed light on a characterization framework of old landfills via combined geophysical models, thriving landfill knowledge with a higher creditability.

Insights for transformation of contaminants in leachate at a tropical landfill dominated by natural attenuation.

The purpose of this study was to track the long-term trends of contaminants distribution in the old landfill of Singapore through monitored natural attenuation and to explore the main parameters that rule such transition. Contaminants distribution, including dissolved organic matter (DOM), inorganic species, heavy metals, and organic compounds, was investigated via monitoring wells in the years 1997, 2004 and 2011. The data revealed that the distribution of contaminants possessed selective attention of spots associated with leachate movement. The hydrogeology of the landfill governed the fate and transportation of contaminants. More specifically, strong statistical correlations were identified between DOM and certain constituents in the leachate, suggesting enhanced mobilization potential. However, the leachate composition exhibited limited correspondence to the nearby solid waste, indicating the minor effect induced by the partitioning coefficient. The presence of sulphate unveiled air intrusion, suggesting increased stability of the landfill, where enhanced biodegradation occurred at earlier period responsible for higher BOD removal. Afterwards other parameters continued to facilitate the compounds removal resulting in overall low concentrations of the contaminants.

Influence of temperature on carbon and nitrogen dynamics during in situ aeration of aged waste in simulated landfill bioreactors.

The effect of temperature on carbon and nitrogen compounds during in situ aeration of aged waste was investigated in lab-scale simulated landfill bioreactors at 35, 45 and 55 °C, respectively. The bioreactor operated at 55 °C presented the highest carbon mineralization rate in the initial stage, suggesting accelerated biodegradation rates under thermophilic conditions. The nitrogen speciation study indicated that organic nitrogen was the dominant species of total N in aerobic bioreactors due to ammonia removal. Leachate organic nitrogen was further fractionated to elucidate the fate of individual constituent. Detailed investigation revealed the higher bioconversion rates of N-humic and N-fulvic compounds compared to hydrophilic compounds in thermophilic conditions. At the end, waste material in 55 °C bioreactor was richer in highly matured humic substances (HS) verifying the high bioconversion rates.

Monitoring transitory profiles of leachate humic substances in landfill aeration reactors in mesophilic and thermophilic conditions.

The presence of humic substances (HS) in landfill leachate is of great interest because of their structural stability and potential toxicity. This study examined the effects of temperature and waste age on the transformation of HS during in situ aeration of bioreactor landfills. By establishing aerobic conditions, dissolved organic carbon (DOC) rapidly accumulated in the bioreactor leachate. Fractional analysis showed that the elevated concentration of humic acids (HAs) was primarily responsible for the increment of leachate strength. Further structural characterization indicated that the molecular weight (MW) and aromacity of HS were enhanced by aeration in conjunction with thermophilic temperature. Interestingly, elevation of HAs concentration was not observed in the aeration reactor with a prolonged waste age, as the mobility of HAs was lowered by the high MW derived from extended waste age. Based on these results, aeration may be more favorable in aged landfills, since dissolution of HAs could be minimized by the evolution to larger MW compared to young landfills. Moreover, increased operation temperature during aeration likely offers benefits for the rapid maturation of HS.