nature communicationsArticlehtps:/doi.org/10.1038/s41467-024-46491-6Intranational synergies and trade-offs revealcommon and differentiated priorities ofsustainable development goals in ChinaReceived:12 June 2023Qiang Xing2,Chaoyang Wu34☒，Fang Chen24☒，Jianguo Liu5,Prajal Pradhan .7,Brett A.Bryan,Thomas Schaubroeck,Accepted:28 February 2024Published online:13 March 2024Check for updatesAccelerating efforts for the Sustainable Development Goals requires under-standing their synergies and trade-offs at the national and sub-national levels,which will help identify the key hurdles and opportunities to prioritize them inan indivisible manner for a country.Here,we present the importance of the 17goals through synergy and trade-off networks.Our results reveal that 19 pro-vinces show the highest trade-offs in SDG13(Combating Climate Change)orSDG5(Gender Equality)consistent with the national level,with other 12 pro-vinces varying.24 provinces show the highest synergies in SDGI(No Poverty)or SDG6(Clean Water and Sanitation)consistent with the national level,withthe remaining 7 provinces varying.These common but differentiated SDGpriorities reflect that to ensure a coordinated national response,China shouldpay more attention to the provincial situation,so that provincial governmentscan formulate more targeted policies in line with their own priorities towardsaccelerating sustainable development.The 2030Agenda for Sustainable Development,consisting of the 17 interactions'.As a system of interacting components,SDGs haveSustainable Development Goals (SDGs)and 169 targets,is a globalcomplex interconnections with synergies (a pair of SDGs improve oragenda for people,the planet,and prosperity to lead the world onto adeteriorate together)and trade-offs (one SDG improves while thesustainable and resilient path'.However,the SDGs have had a limitedother deteriorates),which play essential roles in achievingor inhibitingtransformative impact so far.One reason for this failure of SDGs is their effectiveness.These complex interactions largely depend ontheir selective implementation without considering their complexthe strategies applied to achieve an SDG.For example,infrastructure'International Research Center of Big Data for Sustainable Development Goals,100094 Beijing.China."Key Laboratory of Digital Earth Science,AerospaceInformation Research Institute,Chinese Academy of Sciences,100094 Beijing,China.3The Key Laboratory of Land Surface Pattern and Simulation,InstituteofGeographicalSciencesand Natural Resources Research,Chinese Academy of Sciences,Beijing,China.4University of Chinese Academy of Sciences,Beijing,China.Center for Systems Integration and Sustainability,Department of Fisheries and Wildlife,Michigan State University,East Lansing,MI,USA.Integrated Researchon 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.School of Life and Environmental Sciences,Deakin University,Burwood,Victoria,Australia.Luxembourg Institute of Science and Technology,Belvaux,Luxembourg.Department of Biological Sciences,National University of Singapore,Singapore,Republic of Singapore."School of Earth Envir-onment Society,McMaster University,Hamilton,ON,Canada.College of Water Resources and Civil Engineering.China Agricultural University,Beijing.China.Luxembourg Institute of Socio-Economic Research,Maison des Sciences Humaines 11,Porte des Sciences,L-4366 Esch-sur-Alzette/Belval,Luxembourg.14Natural Capital Project,Stanford University,Stanford,CA,USA.5Department of Geography,the University of Hong Kong.HongKong,China.email:wucy@igsnrr.ac.cn;chenfang@radi.ac.cnNature Communications|(2024)15:22511Articlehtps:/doi.org/10.1038/s41467-02446491-6like roads is necessary for poverty alleviation (SDG1)and economicvalue of Spearman Correlation coefficient R)of 0.95 and 0.94 (Bon-development (SDG8)but may be detrimental for coast (SDG14)andferroni corrected p<0.05 and ABS(R)>0.6)(Fig.la,b for indicatorsland ecosystems (SDG15)'.Thus,to rescue SDGs from failure,oneessentialingredient is to understand their synergies and trade-offs forof "synergies and trade-offs"for more details on the different catedetermining priorities and improving the balance and integrity ofgories in Fig.la,Fig.2a,c for goals).The average Ratio (ratio of thepolicies towards achieving the 2030 Agenda holisticallynumber of the selected indicator pairs out of the total number of allSystems thinking and analysis to assess the complex interactionspossible combinations among goals)was 0.69 and 0.31 for synergiesamong all17 SDGs is at the forefront of sustainability research.Existingand trade-offs (Fig.2b,d).Overall,we found that China faced chal-SDG studies qualitatively evaluate SDG interactions by literaturelenges on SDG13 (Climate Change Action),SDG5 (Gender Equality),review-2,expert rating-6 and text mining.Model-based analysesSDG17 (Partnerships for the Goals),and SDG16 (Peace,Justice andhave focused more on environmental SDGs and less on the socioStrong Institutions),which showed highest hub scores in the trade-offeconomic dimensions's.With public databases,some research usednetwork (0.96,1,0.86 and 0.81)and lowest in the synergy networknetwork analysis to quantitatively analyze the differences in SDGs(0.16,0.46,0.52 and 0.65)(Fig.3a,b).SDG12 (Responsible Consump-interaction networks at global and national levels-2.However,due totion and Production)showed a comparable score between synergyeconomic,social and environmental heterogeneity,SDGs interactions(0.69)and trade-off(0.71).China achieved co-benefits on the other 12may vary at a local or sub-national level within a country.Under-goals with the score in synergies higher than trade-offs (Fig.3a,b,standing SDGs interactions at these sub-national levels is essential sinceplease see supplementary text in SIfor more details on the priorities ofit is where the SDGs are implemented.Understanding variationsSDGs at the national level with source data in Supplementary Data 3).in SDGs interaction networks at different spatial levels,especially at theChina became the world's largest emitter of carbon dioxide (CO2)sub-national level,remains a fundamental research gap,which isin 2006%.China slipped from 63rd position in 2006 to 106th in theessential for identifying context-and location-specific strategies for anglobal gender gap rankings among 153 countries in 20193.Theseintegrated SDG implementation,especially for big countries like China.brought serious trade-offs in SDG13(Climate Action)and SDG5(Gen-As a large developing country in geographic area and population,der Equality)along with the rapid economic development.GivenChina has experienced rapid economic development over the past fewcombatting climate change can reinforce all 17 SDGs".Gender equalitydecades.However,it has also faced social problems and environmentalis an enabler and accelerator for all the SDGs",the most important ischallenges while striving for rapid economic development Forthat China overall needs to take decisive actions to mitigate theexample,climate change has exerted persistent impacts on China'snegative impact from SDG13 (Climate Action)and SDG5 (Genderecological environment and socioeconomic development and broughtEquality).These findings address explicitly the common priorities ofserious threats to its food,water,ecology,energy,and urban operationthe SDGs in trade-off(SDG13 and SDG5)and synergy (SDGI and SDG6)security,as well as people's safety and property.China's carbonamong the different spatial levels in China.emissions have significantly increased by around 10times over the pastChina's trade-offs in SDG13 (Climate Action)and SDG5 (Gender50 years.Gender equality plays an important role in improving pro-Equality)are at a high level,and it needs to increase efforts at theductivity and reducing gender discrimination and violence to promotenational level for top-level design.For SDG13 (Climate Action),Chinaeconomic development and social progress".However,the genderneeds to strengthen the top-level design of carbon peak and carbongap in labor force participation between men and womenrose from9%neutral,propose a systematic,all-round plan for every sector,lead all-to almost 15%between the 1990s and 2020.Further,studies high-round green transformation to combat climate change.On one side,itlighted the challenges and disparities in SDG progress within China,requires reductions in high carbon emissions from economic devel-suggesting that the uneven progress among the 17 SDGs at the sub-opment (SDG8),especially the industry (SDG9)and traditionalnational level is a significant challenge for China's sustainableenergy sectors (SDG7),and from agriculture (SDG2);on the otherdevelopment We fill the above-highlighted research gaps byside,it requires reinforcing the carbon sink in China's terrestrial eco-addressing the following two questions from the SDGs'synergies andsystems (SDG15)33.Besides,it also needs reducing the threat to watertrade-offs perspectives.(1)what are the common SDG priorities amongsupplies and sanitation services (SDG6)4,quality educationsubnational and national levels?(2)How do these priorities differ.(SDG4)240,and human health(SDG3)442.For SDG5(Gender Equality),entiate for synergies and trade-offs?the central government should take the lead to strengthen the top-To this end,we aim to address the research gaps by analyzing thelevel design and launch a package of much stronger plans and mea-synergies and trade-offs among the 17 SDGs in China at the national.sures in every sector in the short and long terms to promote the all-provincial and regional levels.We collected as much data as possible toround development of women and girl.In particular,China shouldcover all 17 SDGs at the national and sub-national levels on a yearlyreduce gender gap in women's employment rate and wage (SDG8 andbasis from 2000 to 2020.In total,an annual dataset of 102 indicatorsSDG9),participation in decision-making (SDG5)4,healthcarewere used in our analysis(see Methods).We built synergy and trade-off(SDG3)5,rural and secondary education(SDG4)4446,poverty reductionnetworks at the national and sub-national levels,respectively.The(SDGI)",rights protection in agriculture,forestry and animal hus-synergy and trade-off intensity were set to be the weighted edge andbandry (SDG2 and SDG15)+5,water and sanitation (SDG6)49,andthe hub score of the 17 goals were in the nodes in the networks (seebuilding partnership (SDG17)Methods).We analyzed the hub score to determine which goal servedWe chose the SDG indicators with the most available data at theas the central hub in the synergy and trade-off networks.The larger thenational and sub-national levels simultaneously in our study to ensurehub score,the more important the node as the central hub in thethe reliability of the results.The data came from a variety of officialnetworks was.We analyzed these variations at national,provincial andstatistical yearbooks.Each type of data was collected by the corre-regional levels among the 17 goals.Our findings can provide essentialsponding official national ministries and provincial counterparts andknowledge and insights into the priority of the SDGs to accelerate theirwas the most authoritative data currently available.Faced with suchimplementation holistically at different spatial levels in China.large-scale data collection,there were indeed varying degrees of datamissing problems across the country and in different provinces due toResultsdifferences in data collection capabilities,local conditions,personnel,The SDGs priorities at the national levelbudgets,etc.At the national scale,none of the indicator show no dataAt the national level,1023 out of 5151 indicator pairs showed synergies,and the data integrity is overall good.The ratio of indicators coveringand 374 pairs showed trade-offs with the average ABS(R)(absolutemore than 15 years accounted for over 94%.The indicator of 9.c.1 withNature Communications|(2024)15:22512