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Chen BR, Xiao Y, Ali M, Xu FY, Li J, Wang R, Zeng XA, Teng YX. Improving resistant starch content of cassava starch by pulsed electric field-assisted esterification. Int J Biol Macromol 2024; 276:133272. [PMID: 38906352 DOI: 10.1016/j.ijbiomac.2024.133272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/14/2024] [Accepted: 06/18/2024] [Indexed: 06/23/2024]
Abstract
This study aims to investigate the effect of pulsed electric field (PEF) assisted OSA esterification treatment on the multi-scale structure and digestive properties of cassava starch and structure-digestion relationships. The degree of substitution (DS) of starch dually modified at 1.5-4.5 kV/cm was 37.6-55.3 % higher than that of starch modified by the conventional method. Compared with native starch, the resistant starch (RS) content of esterified starch treated with 3 kV/cm significantly increased by 17.13 %, whereas that of starch produced by the conventional method increased by only 5.91 %. Furthermore, assisted esterification at low electric fields (1.5-3 kV/cm) promotes ester carbonyl grafting on the surface of starch granules, increases steric hindrance and promotes the rearrangement of the amorphous regions of starch, which increases the density of the double-helical structure. These structural changes slow down starch digestion and increase the RS content. Therefore, this study presents a potential method for increasing the RS content of starch products using PEF to achieve the desired digestibility.
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Affiliation(s)
- Bo-Ru Chen
- Department of Food Science, Foshan University, Foshan, Guangdong 528000, China; Guangdong Key Laboratory of Intelligent Food Manufacturing, Foshan University, Foshan, Guangdong 528225, China
| | - Yun Xiao
- Department of Food Science, Foshan University, Foshan, Guangdong 528000, China; Guangdong Key Laboratory of Intelligent Food Manufacturing, Foshan University, Foshan, Guangdong 528225, China
| | - Murtaza Ali
- Department of Food Science, Foshan University, Foshan, Guangdong 528000, China; Guangdong Key Laboratory of Intelligent Food Manufacturing, Foshan University, Foshan, Guangdong 528225, China
| | - Fei-Yue Xu
- Department of Food Science, Foshan University, Foshan, Guangdong 528000, China; Guangdong Key Laboratory of Intelligent Food Manufacturing, Foshan University, Foshan, Guangdong 528225, China
| | - Jian Li
- Department of Food Science, Foshan University, Foshan, Guangdong 528000, China; Guangdong Key Laboratory of Intelligent Food Manufacturing, Foshan University, Foshan, Guangdong 528225, China
| | - Rui Wang
- Department of Food Science, Foshan University, Foshan, Guangdong 528000, China; Guangdong Key Laboratory of Intelligent Food Manufacturing, Foshan University, Foshan, Guangdong 528225, China
| | - Xin-An Zeng
- Department of Food Science, Foshan University, Foshan, Guangdong 528000, China; Guangdong Key Laboratory of Intelligent Food Manufacturing, Foshan University, Foshan, Guangdong 528225, China; School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China.
| | - Yong-Xin Teng
- School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China.
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Xiao X, Zhang Y, Sun K, Liu S, Li Q, Zhang Y, Godspower BO, Xu T, Zhang Z, Li Y, Liu Y. Enzymatic and ultrasound assisted β-cyclodextrin extraction of active ingredients from Forsythia suspensa and their antioxidant and anti-inflammatory activities. ULTRASONICS SONOCHEMISTRY 2024; 108:106944. [PMID: 38878712 PMCID: PMC11227030 DOI: 10.1016/j.ultsonch.2024.106944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 06/04/2024] [Accepted: 06/05/2024] [Indexed: 07/09/2024]
Abstract
With the proposal of the 2030 Agenda for Sustainable Development, the Chinese medicine extraction technology has been innovatively improved to prioritize low energy consumption, sustainability, and minimized organic solvent utilization. Forsythia suspensa (FS) possesses favorable pharmacological properties and is extensively utilized in traditional Chinese medicine. However, due to the limitations of the composition and extraction methods, its potential has not been fully developed. Thus, a combination of ultrasound-assisted extraction (UAE), enzyme-assisted extraction (EAE), and β-cyclodextrin extraction (β-CDE) was employed to isolate and purify rutin, phillyrin, and forsythoside A from FS. The results demonstrated that the efficiency of extracting enzymatic and ultrasound assisted β-cyclodextrin extraction (EUA-β-CDE) was highly influenced by the temperature and duration of hydrolysis, as well as the duration of the extraction process. According to the results of the single-factor experiment, Box-Behnken design (BBD) in Response surface method (RSM) was used to optimize the experimental parameters to achieve the maximum comprehensive evaluation value (CEV) value. The EUA-β-CDE compared with other extraction methods, has good extraction effect and low energy consumption by high performance liquid chromatography (HPLC), scanning electron microscopy (SEM), calculation of power consumption and CO2 emission The EUA-β-CDE compared with other extraction methods, has good extraction effect and low energy consumption by HPLC, SEM, calculation of power consumption and CO2 emission. Then, the structural characteristics of EUA-β-CDE of FS extract had significant interaction with β-CD by Fourier infrared spectroscopy (FT-IR) and differential scanning calorimetry (DSC). In addition, EUA-β-CDE extract has good antioxidant and anti-inflammatory activities. The establishment of EUA-β-CDE of FS provides a new idea for the development and application of other sustainable extraction methods of traditional Chinese medicine.
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Affiliation(s)
- Xiaoyue Xiao
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China
| | - Yang Zhang
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China
| | - Kedi Sun
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China
| | - Shuoqi Liu
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China
| | - Qingmiao Li
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China
| | - Yu Zhang
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China
| | - Bello-Onaghise Godspower
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China; Department of Animal Science, Faculty of Agriculture, University of Benin City, Nigeria
| | - Tong Xu
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China
| | - Zhiyun Zhang
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China
| | - Yanhua Li
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China.
| | - Yanyan Liu
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Key Laboratory for Animal Disease Control and Pharmaceutical Development, Harbin, China.
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3
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Pham-Truffert M, Pfund JL. Linking Forest Ecosystem Services to the SDGs: Semi-quantitative Mapping of Perceptions towards Integrated Decision-making. ENVIRONMENTAL MANAGEMENT 2024; 74:148-158. [PMID: 38047917 PMCID: PMC11208211 DOI: 10.1007/s00267-023-01915-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 11/15/2023] [Indexed: 12/05/2023]
Abstract
With this study, we test and present the results of a reproducible semi-quantitative methodological approach, which enables us to map perceptions of complex systems, linking the forest ecosystem services (FES) of a given spatial level to the wider policy domains represented by the 2030 Agenda and its Sustainable Development Goals (SDGs). Through a participative process, we used integrated forest management and FES as entry point concepts to support and inform dialog towards a normative desired future as framed by the SDGs, taking into account interdependencies across sectors and policy domains. The scales used in the test were national (Switzerland) and international but it is possible to use the approach at any level of integration, especially the landscape one in the case of forest or other ecosystem issues to be transdisciplinary solved. We stress that the semi-quantitative aspects of the approach - be it the ranking of the importance of FES across the different SDGs, or the positive or negative weighting of interactions among these FES in cross-impact matrices - enable the perceptions held by actors to be more explicit and significant for governance or goal prioritization. The results illustrate the perceptions of selected actors on the effects of integrated forest management and provide a basis for multi-actor deliberation on emerging potential synergies or conflicts, thereby genuinely supporting science-policy-practice dialog, which is crucial to foster integrated decision-making.
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Affiliation(s)
- Myriam Pham-Truffert
- Earth System Science (ESS), Remote Sensing Laboratories, Department of Geography, University of Zurich, Zurich, Switzerland.
- Centre for Development and Environment (CDE), University of Bern, Bern, Switzerland.
- Digital Society Initiative (DSI), University of Zurich, Zurich, Switzerland.
| | - Jean-Laurent Pfund
- Forest Division, Federal Office for the Environment (FOEN), Bern, Switzerland
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Ipkovich Á, Czvetkó T, A. Acosta L, Lee S, Nzimenyera I, Sebestyén V, Abonyi J. Network science and explainable AI-based life cycle management of sustainability models. PLoS One 2024; 19:e0300531. [PMID: 38870225 PMCID: PMC11175538 DOI: 10.1371/journal.pone.0300531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 02/29/2024] [Indexed: 06/15/2024] Open
Abstract
Model-based assessment of the potential impacts of variables on the Sustainable Development Goals (SDGs) can bring great additional information about possible policy intervention points. In the context of sustainability planning, machine learning techniques can provide data-driven solutions throughout the modeling life cycle. In a changing environment, existing models must be continuously reviewed and developed for effective decision support. Thus, we propose to use the Machine Learning Operations (MLOps) life cycle framework. A novel approach for model identification and development is introduced, which involves utilizing the Shapley value to determine the individual direct and indirect contributions of each variable towards the output, as well as network analysis to identify key drivers and support the identification and validation of possible policy intervention points. The applicability of the methods is demonstrated through a case study of the Hungarian water model developed by the Global Green Growth Institute. Based on the model exploration of the case of water efficiency and water stress (in the examined period for the SDG 6.4.1 & 6.4.2) SDG indicators, water reuse and water circularity offer a more effective intervention option than pricing and the use of internal or external renewable water resources.
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Affiliation(s)
- Ádám Ipkovich
- HUN-REN-PE Complex Systems Monitoring Research Group, University of Pannonia, Veszprém, Hungary
| | - Tímea Czvetkó
- HUN-REN-PE Complex Systems Monitoring Research Group, University of Pannonia, Veszprém, Hungary
| | - Lilibeth A. Acosta
- Climate Action and Inclusive Development (CAID) Unit, Global Green Growth Institute, Jung-gu, Seoul, Republic of Korea
| | - Sanga Lee
- Climate Action and Inclusive Development (CAID) Unit, Global Green Growth Institute, Jung-gu, Seoul, Republic of Korea
| | - Innocent Nzimenyera
- Climate Action and Inclusive Development (CAID) Unit, Global Green Growth Institute, Jung-gu, Seoul, Republic of Korea
| | - Viktor Sebestyén
- HUN-REN-PE Complex Systems Monitoring Research Group, University of Pannonia, Veszprém, Hungary
- Sustainability Solutions Research Lab, Faculty of Engineering, University of Pannonia, Veszprém, Hungary
| | - János Abonyi
- HUN-REN-PE Complex Systems Monitoring Research Group, University of Pannonia, Veszprém, Hungary
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Xing Q, Wu C, Chen F, Liu J, Pradhan P, Bryan BA, Schaubroeck T, Carrasco LR, Gonsamo A, Li Y, Chen X, Deng X, Albanese A, Li Y, Xu Z. Intranational synergies and trade-offs reveal common and differentiated priorities of sustainable development goals in China. Nat Commun 2024; 15:2251. [PMID: 38480716 PMCID: PMC10937989 DOI: 10.1038/s41467-024-46491-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 02/28/2024] [Indexed: 03/17/2024] Open
Abstract
Accelerating efforts for the Sustainable Development Goals requires understanding their synergies and trade-offs at the national and sub-national levels, which will help identify the key hurdles and opportunities to prioritize them in an indivisible manner for a country. Here, we present the importance of the 17 goals through synergy and trade-off networks. Our results reveal that 19 provinces show the highest trade-offs in SDG13 (Combating Climate Change) or SDG5 (Gender Equality) consistent with the national level, with other 12 provinces varying. 24 provinces show the highest synergies in SDG1 (No Poverty) or SDG6 (Clean Water and Sanitation) consistent with the national level, with the remaining 7 provinces varying. These common but differentiated SDG priorities reflect that to ensure a coordinated national response, China should pay more attention to the provincial situation, so that provincial governments can formulate more targeted policies in line with their own priorities towards accelerating sustainable development.
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Affiliation(s)
- Qiang Xing
- International Research Center of Big Data for Sustainable Development Goals, 100094, Beijing, China
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, 100094, Beijing, China
| | - Chaoyang Wu
- The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
| | - Fang Chen
- International Research Center of Big Data for Sustainable Development Goals, 100094, Beijing, China.
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, 100094, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
| | - Jianguo Liu
- Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | - Prajal Pradhan
- Integrated Research on Energy, Environment and Society (IREES), Energy and Sustainability Research Institute Groningen (ESRIG), University of Groningen, Groningen, 9747 AG, Netherlands
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, 14473, Potsdam, Germany
| | - Brett A Bryan
- School of Life and Environmental Sciences, Deakin University, Burwood, Victoria, Australia
| | | | - L Roman Carrasco
- Department of Biological Sciences, National University of Singapore, Singapore, Republic of Singapore
| | - Alemu Gonsamo
- School of Earth, Environment & Society, McMaster University, Hamilton, ON, Canada
| | - Yunkai Li
- College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China
| | - Xiuzhi Chen
- College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China
| | - Xiangzheng Deng
- The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Andrea Albanese
- Luxembourg Institute of Socio-Economic Research, Maison des Sciences Humaines, 11, Porte des Sciences, L-4366, Esch-sur-Alzette/Belval, Luxembourg
| | - Yingjie Li
- Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
- Natural Capital Project, Stanford University, Stanford, CA, USA
| | - Zhenci Xu
- Department of Geography, the University of Hong Kong, Hong Kong, China
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Cheng Q, Zhang C, Zou Y, Pu X, Jin H. Unraveling interactions and priorities under sustainable development goals in less-developed mountainous areas: case study on the National Innovation Demonstration Zone for the 2030 Agenda for Sustainable Development, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:5254-5274. [PMID: 38112871 DOI: 10.1007/s11356-023-31478-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 12/06/2023] [Indexed: 12/21/2023]
Abstract
Understanding the intricate relationships between progress and the United Nations' 17 Sustainable Development Goals (SDGs) is vital for informed and adaptable sustainable development policy formulation. This study focused on the Lincang National Innovation Demonstration Zone for the 2030 Agenda for Sustainable Development (LC-NIDZASD) in China. By evaluating sustainability scores at the county level from 2011 to 2020, the trade-offs and synergies among SDGs were explored. Priority SDGs for development were identified, and targeted recommendations were established based on these findings. The key findings are as follows: (1) The SDG index scores of Lincang and its counties showed an increase from 2011 to 2020, with scores riding from 42.1 to 52.2. SDG6 (Clean Water and Sanitation) and SDG12 (Responsible Production and Consumption) had the highest scores, while SDG1 (No Poverty) and SDG4 (Quality Education) increased significantly. However, the COVID-19 pandemic led to a decrease in the scores of SDG1, SDG8 (Decent Jobs and Economic Growth), and SDG17 (Partnerships for the Goals) in 2020 decreased compared to 2019. Decreased scores in SDG13 (Climate Action) and SDG15 (Life on Land) may be attributable to climate change. (2) The relationship between "Objectives" and ''Governance" appears to be synergistic, while ''Essential Needs" mainly shows a trade-off relationship with ''Objectives" and ''Governance." (3) To promote achievements in the construction of LC-NIDZASD, priority should be given to SDG3 (Health and Well-Being), SDG8, SDG9 (Industry, Innovation, and Infrastructure), and SDG12; SDG4 should not be ignored. (4) Overall, Lincang has made significant progress in sustainable development. However, to further consolidate these achievements, adjustments should be made for SDG7 (Energy Consumption and Production Structure). Efforts should be made to strengthen climate governance measures and improve warning and forecasting capabilities to promote the synergistic development of SDG7 (Affordable and Clean Energy) and SDG13 with other SDGs. This study's dynamic monitoring of changes in the SDGs in Lincang provides valuable insights into the synergies and trade-offs among these goals. Appropriate prioritization across various SDGs can allow for timely adjustments in sustainable management policies, ultimately contributing to the successful operation of the LC-NIDZASD.
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Affiliation(s)
- Qingping Cheng
- School of Geography and Ecotourism, Southwest Forestry University, Kunming, 650224, Yunnan, China.
- Southwest Research Centre for Eco-civilization, National Forestry and Grassland Administration, Kunming, 650224, Yunnan, China.
- Yunnan Key Lab of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming, 650091, Yunnan, China.
| | - Chunxiao Zhang
- School of Geography and Ecotourism, Southwest Forestry University, Kunming, 650224, Yunnan, China
| | - Yongna Zou
- School of Geography and Ecotourism, Southwest Forestry University, Kunming, 650224, Yunnan, China
| | - Xuefu Pu
- School of Geography and Ecotourism, Southwest Forestry University, Kunming, 650224, Yunnan, China
| | - Hanyu Jin
- School of Geography and Ecotourism, Southwest Forestry University, Kunming, 650224, Yunnan, China
- Yunnan Key Lab of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming, 650091, Yunnan, China
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Wu X, Fu B, Wang S, Song S, Lusseau D, Liu Y, Xu Z, Liu J. Bleak prospects and targeted actions for achieving the Sustainable Development Goals. Sci Bull (Beijing) 2023; 68:2838-2848. [PMID: 37741744 DOI: 10.1016/j.scib.2023.09.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/15/2023] [Accepted: 08/16/2023] [Indexed: 09/25/2023]
Abstract
At the mid-point to 2030, progress towards achieving the Sustainable Development Goals (SDGs) varies significantly across countries. While the classification of countries can lay the foundation for improving policy efficiency and promoting joint action, bottom-up, SDG data-driven country classifications have largely remained unexplored. Here, we classified 166 countries based on their performances in the 17 SDGs and further used the classification to analyze SDG interactions and compare development aid distributions. The countries were classified into five groups, ranging from "lowest development with good environment" to "high development needing climate action". None of them scored highly in all SDGs, and due to trade-offs related to environment and climate SDGs, none of them can achieve all SDGs eventually. To maximize the potential for achieving the SDGs, all countries need to undergo a sustainable transformation, and prioritizing certain SDGs, such as SDG 9 (industry, innovation and infrastructure), can help countries with lower sustainable development levels achieve more with less. Furthermore, global development aid should be better aligned with country needs, particularly in areas of education, energy, environment, and water supply and sanitation. By better characterizing different countries, this study reveals the bleak prospects of achieving all SDGs and provides valuable insights into more targeted actions for national sustainable development and global collaboration.
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Affiliation(s)
- Xutong Wu
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Bojie Fu
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Shuai Wang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Shuang Song
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - David Lusseau
- National Institute of Aquatic Resources, Technical University of Denmark, Kongens Lyngby 2800, Denmark
| | - Yanxu Liu
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Zhenci Xu
- Department of Geography, the University of Hong Kong, Hong Kong 999077, China
| | - Jianguo Liu
- Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing MI 48823, USA
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Qin C, Su J, Xiao Y, Qiang Y, Xiong S. Assessing the Beautiful China Initiative from an environmental perspective: indicators, goals, and provincial performance. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:84412-84424. [PMID: 37365367 DOI: 10.1007/s11356-023-27997-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 05/25/2023] [Indexed: 06/28/2023]
Abstract
The Beautiful China Initiative (BCI) is part of China's national strategy for implementing the long-term goals of building an ecological civilization and promoting sustainable development. However, currently, there is no goal-oriented, comparable, and standardized indicator framework for monitoring the performance of the BCI. Here, we established the BCI from an environmental perspective (BCIE) index comprising 40 indicators and targets in eight fields and used a systematic approach to measure the distance and progress towards the goal of building a "Beautiful China" by 2035 at the national and subnational levels. Our analyses indicate that the BCIE index score (range: [0, 1]) was 0.757 at the national level and 0.628-0.869 at the provincial level in 2020. Between 2015 and 2020, the BCIE index scores of all provinces improved; however, large spatio-temporal variations were evident. Provinces with better BCIE performances exhibited relatively balanced scores across different sectors and cities. Our study revealed that the BCIE index scores at the city level surpassed provincial administrative boundaries, resulting in a wider range of aggregation. By focusing on the strategic arrangement of BCI, this study provides an effective index system and evaluation method for dynamic monitoring and phased evaluations at all levels of government in China.
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Affiliation(s)
- Changbo Qin
- The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing, 100041, China
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, 15 Shixing Street, Shijingshan District, Beijing, 100041, China
| | - Jieqiong Su
- The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing, 100041, China
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, 15 Shixing Street, Shijingshan District, Beijing, 100041, China
| | - Yang Xiao
- The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing, 100041, China
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, 15 Shixing Street, Shijingshan District, Beijing, 100041, China
| | - Ye Qiang
- The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing, 100041, China.
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, 15 Shixing Street, Shijingshan District, Beijing, 100041, China.
| | - Shangao Xiong
- The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing, 100041, China
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, 15 Shixing Street, Shijingshan District, Beijing, 100041, China
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9
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Luttikhuis N, Wiebe KS. Analyzing SDG interlinkages: identifying trade-offs and synergies for a responsible innovation. SUSTAINABILITY SCIENCE 2023; 18:1-19. [PMID: 37363308 PMCID: PMC10214325 DOI: 10.1007/s11625-023-01336-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 04/17/2023] [Indexed: 06/28/2023]
Abstract
This paper responds to recent calls to address the indivisible nature of the Sustainable Development Goal (SDG) framework and the related knowledge gap on how SDG targets interlink with each other. It examines how SDG targets interact in the context of a specific technology, point of care (PoC) microfluidics, and how this relates to the concept of responsible innovation (RI). The novel SDG interlinkages methodology developed here involves several steps to filter the relevant interlinkages and a focus group of experts for discussing these interlinkages. The main findings indicate that several social synergies occur when deploying PoC microfluidics, but that the environmental trade-offs may jeopardize the total progress toward the SDGs. More specifically, the environmental sacrifices (use of plastics and lack of recyclability) resulted in the product being cheaper and, thus, better accessible. This work suggests that attention should be given (and prioritized) to the use of renewable and recyclable materials without jeopardizing the accessibility of the product. This should minimize the identified trade-offs. These findings inform how analyzing SDG interlinkages relates to the responsibilities and dimensions of RI in several ways. First, analyzing SDG interlinkages helps to execute the governance responsibility by using the RI dimensions (anticipation, reflexivity, inclusion and responsiveness). Second, analyzing SDG interlinkages gives insights into if and how a technology relates to the do-good and avoid-harm responsibility. This is important to assess the responsiveness of the technology to ensure that the technology can become truly sustainable and leaves no one behind.
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Affiliation(s)
- Nikki Luttikhuis
- Sustainable Energy Technology, SINTEF, Torgarden, P.O. Box 4760, 7465 Trondheim, Norway
- Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
| | - Kirsten S. Wiebe
- Sustainable Energy Technology, SINTEF, Torgarden, P.O. Box 4760, 7465 Trondheim, Norway
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Grah C. Klimafreundliches Arbeiten im Gesundheitswesen. PNEUMO NEWS 2023; 15:32-37. [PMID: 37128243 PMCID: PMC10132913 DOI: 10.1007/s15033-023-3477-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Affiliation(s)
- Christian Grah
- Gemeinschaftskrankenhaus Havelhöhe Abteilung für Pneumologie & LungenkrebszentrumForschungsinstitut Reallabor Climate Friendly Hospital, Kladower Damm 221, 14089 Berlin, Deutschland
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Moreno J, Van de Ven DJ, Sampedro J, Gambhir A, Woods J, Gonzalez-Eguino M. Assessing synergies and trade-offs of diverging Paris-compliant mitigation strategies with long-term SDG objectives. GLOBAL ENVIRONMENTAL CHANGE : HUMAN AND POLICY DIMENSIONS 2023; 78:102624. [PMID: 36846829 PMCID: PMC9941755 DOI: 10.1016/j.gloenvcha.2022.102624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 10/07/2022] [Accepted: 11/26/2022] [Indexed: 06/18/2023]
Abstract
The Sustainable Development Goals (SDGs) and the Paris Agreement are the two transformative agendas, which set the benchmarks for nations to address urgent social, economic and environmental challenges. Aside from setting long-term goals, the pathways followed by nations will involve a series of synergies and trade-offs both between and within these agendas. Since it will not be possible to optimise across the 17 SDGs while simultaneously transitioning to low-carbon societies, it will be necessary to implement policies to address the most critical aspects of the agendas and understand the implications for the other dimensions. Here, we rely on a modelling exercise to analyse the long-term implications of a variety of Paris-compliant mitigation strategies suggested in the recent scientific literature on multiple dimensions of the SDG Agenda. The strategies included rely on technological solutions such as renewable energy deployment or carbon capture and storage, nature-based solutions such as afforestation and behavioural changes in the demand side. Results for a selection of energy-environment SDGs suggest that some mitigation pathways could have negative implications on food and water prices, forest cover and increase pressure on water resources depending on the strategy followed, while renewable energy shares, household energy costs, ambient air pollution and yield impacts could be improved simultaneously while reducing greenhouse gas emissions. Overall, results indicate that promoting changes in the demand side could be beneficial to limit potential trade-offs.
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Affiliation(s)
- Jorge Moreno
- Basque Centre for Climate Change (BC3), Leioa, Spain
- Centre for Environmental Policy, Imperial College London, London SW7 2AZ, United Kingdom
| | | | - Jon Sampedro
- Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
| | - Ajay Gambhir
- Grantham Institute for Climate Change and the Environment, Imperial College London, London, United Kingdom
| | - Jem Woods
- Centre for Environmental Policy, Imperial College London, London SW7 2AZ, United Kingdom
| | - Mikel Gonzalez-Eguino
- Basque Centre for Climate Change (BC3), Leioa, Spain
- University of the Basque Country, Bilbao, Spain
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Svicher A, Gori A, Di Fabio A. The Sustainable Development Goals Psychological Inventory: A Network Analysis in Italian University Students. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:10675. [PMID: 36078391 PMCID: PMC9517867 DOI: 10.3390/ijerph191710675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 06/15/2023]
Abstract
The Sustainable Development Goals Psychological Inventory (SDGPI) is a recently developed self-report questionnaire that assesses interest, motivation, and self-efficacy associated with each of the 17 Sustainable Development Goals (SDGs) advanced by the United Nations. This study aims to investigate, via network analysis, (a) the relationships between interest, motivation, and self-efficacy for each SDG and (b) the most central SDGs. To this end, 417 Italian university students (73.9% females and 26.1% males; mean age: 22.20; DS = 3.02) were assessed through the SDGPI, and two network structures were estimated. The first network structure investigates links (edges) between interest, motivation, and self-efficacy in relation to each specific SDG. The second network structure investigates most central SDGs as the sum of interest, motivation, and self-efficacy for each specific SDG. Regarding results, the first network structure showed that five SDGs had strong and statistically significant edges between interest, motivation, and self-efficacy; seven SDGs had strong and statistically significant edges between interest and motivation but not self-efficacy; five SDGs had no statistically significant edges linking the other dimensions. The second network structure revealed that SDG 2 (Zero Hunger) and SDG 7 (Affordable and clean energy) were the most central nodes. Implications for research, tailor-made interventions, and prevention were discussed.
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Affiliation(s)
- Andrea Svicher
- Department of Education, Languages, Intercultures, Literatures, and Psychology (Psychology Section), University of Florence, 50135 Florence, Italy
| | - Alessio Gori
- Department of Health Sciences, University of Florence, 50135 Florence, Italy
| | - Annamaria Di Fabio
- Department of Education, Languages, Intercultures, Literatures, and Psychology (Psychology Section), University of Florence, 50135 Florence, Italy
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Untangling the interactions among the Sustainable Development Goals in China. Sci Bull (Beijing) 2022; 67:977-984. [PMID: 36546033 DOI: 10.1016/j.scib.2022.01.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 11/17/2021] [Accepted: 11/18/2021] [Indexed: 01/06/2023]
Abstract
Understanding the interactions (synergies and trade-offs) among the Sustainable Development Goals (SDGs) is crucial for enhancing policy coherence between different sectors. However, spatial differences in the SDG interactions and their temporal variations at the sub-national scale are still critical gaps that need to be urgently filled. Here, we assess the spatial and temporal variation of the SDG interactions in China based on the systematic classification framework of SDGs. The framework groups the seventeen SDGs into three categories, namely "Essential Needs", "Objectives", and "Governance". Spatially, we found that the SDGs in "Essential Needs" & "Objectives" and "Essential Needs" & "Governance" generally show trade-offs in the eastern provinces of China. Synergies among all three SDG categories are observed in some central and western China provinces, which implies that these regions conform to sustainable development patterns. In addition, temporally, the synergies of the three SDG categories have shown a weakening trend in the last decade, mainly due to the regional differences in the progress of SDG7 (Affordable and Clean Energy). Overall, our results identify the necessity for provinces to enhance the synergies between SDG12 (Responsible Production and Consumption) and other SDGs to tackle the trade-offs between the "Essential Needs" and "Objectives". Meanwhile, promoting the progress of SDG7 will also contribute to balanced development across provinces.
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Mindful Application of Digitalization for Sustainable Development: The Digitainability Assessment Framework. SUSTAINABILITY 2022. [DOI: 10.3390/su14053114] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Digitalization is widely recognized as a transformative power for sustainable development. Careful alignment of progress made by digitalization with the globally acknowledged Sustainable Development Goals (SDGs) is crucial for inclusive and holistic sustainable development in the digital era. However, limited reference has been made in SDGs about harnessing the opportunities offered by digitalization capabilities. Moreover, research on inhibiting or enabling effects of digitalization considering its multi-faceted interlinkages with the SDGs and their targets is fragmented. There are only limited instances in the literature examining and categorizing the impact of digitalization on sustainable development. To overcome this gap, this paper introduces a new Digitainability Assessment Framework (DAF) for context-aware practical assessment of the impact of the digitalization intervention on the SDGs. The DAF facilitates in-depth assessment of the many diverse technical, social, ethical, and environmental aspects of a digital intervention by systematically examining its impact on the SDG indicators. Our approach draws on and adapts concepts of the Theory of Change (ToC). The DAF should support developers, users as well policymakers by providing a 360-degree perspective on the impact of digital services or products, as well as providing hints for its possible improvement. We demonstrate the application of the DAF with the three test case studies illustrating how it supports in providing a holistic view of the relation between digitalization and SDGs.
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