Comparative life-cycle sustainability assessment of centralized and decentralized remediation strategies at the city level.

Remediation of contaminated soil at industrial sites has become a challenge and an opportunity for sustainable urban land use, considering the substantial secondary impacts resulting from remediation activities. The design of soil remediation strategies for multi-site remediation from a regional perspective is of great significance for cities with a large number of brownfields. Centralized and decentralized facilities have been studied in different environmental fields, yet limited research has focused on centralized soil remediation, specifically the treatment of contaminated soil from different sites through the construction of shared soil treatment facilities. This study proposes a framework for comparing centralized and decentralized strategies for contaminated soil remediation based on the integration of life-cycle sustainability assessment and multi-objective optimization. With Zhuzhou, an industrial city in China, serving as an example, results show that after optimization, the centralized scenario can reduce total environmental impacts by 25 %-41 %. In addition, the centralized scenario can reduce economic costs by 27 %-39 %, saving up to 176 million USD. The advantages of the centralized soil remediation strategy include: (1) increased use of soil washing, (2) reduced use of off-site disposal, and (3) reduced construction and efficient utilization of soil treatment facilities. In conclusion, the centralized strategy is relatively suitable for cities or areas with a large number of medium or small-sized contaminated sites. The built framework can quantitatively evaluate multiple sites soil remediation at both the city and individual site level, allowing for a straightforward and objective comparison with the optimal remediation design.

Adding marrow R2∗ to proton density fat fraction improves the discrimination of osteopenia and osteoporosis in postmenopausal women assessed with 3D FACT sequence.

OBJECTIVE: To evaluate the role of three-dimensional Fat Analysis & Calculation Technique sequence in improving the diagnostic accuracy for the detection of osteopenia and osteoporosis by simultaneous quantification of proton density fat fraction (PDFF) and fat-corrected R2∗. METHODS: Fat Analysis & Calculation Technique imaging of lumbar spine was obtained in 99 postmenopausal women including 52 normal bone mass, 29 osteopenia, and 18 osteoporosis. The diagnostic performance of PDFF and R2∗ in the differentiation of different bone-density groups was evaluated with the receiver operating characteristic curve. RESULTS: The reproducibility of PDFF and R2∗ measures was satisfactory with the root mean square coefficient of variation, 2.16% and 2.70%, respectively. The intra- and interobserver agreements for the PDFF and R2∗ were excellent with the intraclass correlation coefficient > 0.9 for all. There were significant differences in PDFF and R2∗ among the three groups (P < 0.05). Bone density had a moderate inverse correlation with PDFF (r  = -0.659) but a positive association with R2∗ (r = 0.508, P < 0.001). Adjusted for age, years since menopause and body mass index, odds ratios (95% confidence interval) for osteopenia and osteoporosis per standard deviation higher marrow PDFF and R2∗ were 2.9 (1.4-5.8) and 0.4 (0.2-0.8), respectively. The areas under the curve were 0.821 for PDFF, 0.784 for R2∗, and 0.922 for both combined for the detection of osteoporosis (P < 0.05). Similar results were obtained in distinguishing osteopenia from healthy controls. CONCLUSIONS: Simultaneous estimation of marrow R2∗ and PDFF improves the discrimination of osteopenia and osteoporosis in comparison with the PDFF or R2∗ alone.