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Spatiotemporal Changes and the Driving Forces of Sloping Farmland Areas in the Sichuan Region
sustainability Article Spatiotemporal Changes and the Driving Forces of Sloping Farmland Areas in the Sichuan Region Meijia Xiao 1 , Qingwen Zhang 1,*, Liqin Qu 2, Hafiz Athar Hussain 1 , Yuequn Dong 1 and Li Zheng 1 1 Agricultural Clean Watershed Research Group, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-Environment, Ministry of Agriculture, Beijing 100081, China; [email protected] (M.X.); [email protected] (H.A.H.); [email protected] (Y.D.); [email protected] (L.Z.) 2 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China; [email protected] * Correspondence: [email protected]; Tel.: +86-10-82106031 Received: 12 December 2018; Accepted: 31 January 2019; Published: 11 February 2019 Abstract: Sloping farmland is an essential type of the farmland resource in China. In the Sichuan province, livelihood security and social development are particularly sensitive to changes in the sloping farmland, due to the region’s large portion of hilly territory and its over-dense population. In this study, we focused on spatiotemporal change of the sloping farmland and its driving forces in the Sichuan province. Sloping farmland areas were extracted from geographic data from digital elevation model (DEM) and land use maps, and the driving forces of the spatiotemporal change were analyzed using a principal component analysis (PCA). The results indicated that, from 2000 to 2015, sloping farmland decreased by 3263 km2 in the Sichuan province. The area of gently sloping farmland (<10◦) decreased dramatically by 1467 km2, especially in the capital city, Chengdu, and its surrounding areas. -
Spatial Association and Effect Evaluation of CO2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis
sustainability Article Spatial Association and Effect Evaluation of CO2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis Jinzhao Song 1, Qing Feng 1, Xiaoping Wang 1,*, Hanliang Fu 1 , Wei Jiang 2 and Baiyu Chen 3 1 School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China; [email protected] (J.S.); [email protected] (Q.F.); [email protected] (H.F.) 2 Department of Ecosystem Science and Management, Pennsylvania State University, Forest Resources Building, University Park, PA 16802, USA; [email protected] 3 College of Engineering, University of California Berkeley, Berkeley, CA 94720, USA; [email protected] * Correspondence: [email protected] Received: 29 October 2018; Accepted: 17 December 2018; Published: 20 December 2018 Abstract: Urban agglomeration, an established urban spatial pattern, contributes to the spatial association and dependence of city-level CO2 emission distribution while boosting regional economic growth. Exploring this spatial association and dependence is conducive to the implementation of effective and coordinated policies for regional level CO2 reduction. This study calculated CO2 emissions from 2005–2016 in the Chengdu-Chongqing urban agglomeration with the IPAT model, and empirically explored the spatial structure pattern and association effect of CO2 across the area leveraged by the social network analysis. The findings revealed the following: (1) The spatial structure of CO2 emission in -
Monitoring Report Form for CDM Programme of Activities (Version 01.0)
CDM-PoA-MR-FORM Monitoring report form for CDM programme of activities (version 01.0) Complete this form in accordance with the Attachment “Instructions for filling out the monitoring report form for CDM programme of activities” at the end of this form. MONITORING REPORT Title of the programme of activities (PoA) Sichuan Rural Poor-Household Biogas Development Programme UNFCCC reference number of the PoA 2898 Version number(s) of the PoA-DD(s) applicable to this monitoring report 1.7 Chengdu Oasis Science & Technology Co., Coordinating/managing entity (CME) Ltd. Version number of this monitoring report 1.2 Completion date of this monitoring report 24/08/2016 Monitoring period number and dates covered by this 4th monitoring period monitoring report 01/01/2015 – 31/12/2015 Monitoring report number for this monitoring period 1 Single monitoring report is prepared for all covered CPAs for this monitoring period Is this a host Party to a specific-case CPA Host Party(ies) of the covered in this PoA Host Party(ies) monitoring report?(yes/no) People’s Republic of Yes China Scope 1: Energy industries (renewable - / Sectoral scope(s) non-renewable sources) Scope 15: Agriculture AMS-I.C - Thermal energy production with or Selected methodology(ies) without electricity (version 19) (EB61, Annex 16); AMS-III.R - Methane recovery in agricultural activities at household/small farm level (version 02) (EB59, Annex 4). Selected standardized baseline(s) N/A Total amount of GHG emission reductions or net GHG emission GHG emission GHG removals by sinks for all specific-case-case reductions or net reductions or net CPAs in the PoA covered in this monitoring report GHG removals by GHG removals by sinks reported up to sinks reported from 1 31 December 2012 January 2013 onwards 0tCO2e 854,697tCO2e Version 01.0 Page 1 of 49 CDM-PoA-MR-FORM PART I - Programme of activities SECTION A. -
Spatial Disparities in Access to Healthcare Professionals in Sichuan: Evidence from County-Level Data
healthcare Article Spatial Disparities in Access to Healthcare Professionals in Sichuan: Evidence from County-Level Data Ning Zhang 1,2,3, Wei Ning 1,2, Tao Xie 1,2, Jinlin Liu 4, Rongxin He 1,2, Bin Zhu 5,* and Ying Mao 1,2,* 1 School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an 710049, China; [email protected] (N.Z.); [email protected] (W.N.); [email protected] (T.X.); [email protected] (R.H.) 2 Research Center for the Belt and Road Health Policy and Health Technology Assessment, Xi’an Jiaotong University, Xi’an 710049, China 3 Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London SW7 2AZ, UK 4 School of Public Policy and Administration, Northwestern Polytechnic University, Xi’an 710049, China; [email protected] 5 School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen 518055, China * Correspondence: [email protected] (B.Z.); [email protected] (Y.M.) Abstract: As a southwestern province of China, Sichuan is confronted with geographical disparities in access to healthcare professionals because of its complex terrain, uneven population distribution and huge economic gaps between regions. With 10-year data, this study aims to explore the county-level spatial disparities in access to different types of healthcare professionals (licensed doctors, registered nurses, pharmacists, technologists and interns) in Sichuan using temporal and spatial analysis methods. The time-series results showed that the quantity of all types of healthcare professionals Citation: Zhang, N.; Ning, W.; Xie, T.; increased, especially the registered nurses, while huge spatial disparities exist in the distribution Liu, J.; He, R.; Zhu, B.; Mao, Y. -
Time-Calibrated Milankovitch Cycles for the Late Permian
ARTICLE Received 31 Oct 2012 | Accepted 16 Aug 2013 | Published 13 Sep 2013 DOI: 10.1038/ncomms3452 OPEN Time-calibrated Milankovitch cycles for the late Permian Huaichun Wu1,2, Shihong Zhang1, Linda A. Hinnov3, Ganqing Jiang4, Qinglai Feng5, Haiyan Li1 & Tianshui Yang1 An important innovation in the geosciences is the astronomical time scale. The astronomical time scale is based on the Milankovitch-forced stratigraphy that has been calibrated to astronomical models of paleoclimate forcing; it is defined for much of Cenozoic–Mesozoic. For the Palaeozoic era, however, astronomical forcing has not been widely explored because of lack of high-precision geochronology or astronomical modelling. Here we report Milankovitch cycles from late Permian (Lopingian) strata at Meishan and Shangsi, South China, time calibrated by recent high-precision U–Pb dating. The evidence extends empirical knowledge of Earth’s astronomical parameters before 250 million years ago. Observed obliquity and precession terms support a 22-h length-of-day. The reconstructed astronomical time scale indicates a 7.793-million year duration for the Lopingian epoch, when strong 405-kyr cycles constrain astronomical modelling. This is the first significant advance in defining the Palaeozoic astronomical time scale, anchored to absolute time, bridging the Palaeozoic–Mesozoic transition. 1 State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Beijing 100083, China. 2 School of Ocean Sciences, China University of Geosciences, Beijing 100083, China. 3 Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland 21218, USA. 4 Department of Geoscience, University of Nevada, Las Vegas, Nevada 89154, USA. 5 State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China. -
Sustainability Report 2005
2004 Sustainability Report 2005 Steel, the essence of nature enter into endless recycle Steel, the success of endeavor bring to a bright prospect Steel, the cornerstone of society build up harmony of the world About the Report Content and Time Range Prior to this report, Baoshan Iron & Steel Co., Ltd. The report mainly describes economic, environmental (hereafter referred to as “Baosteel” or “Company”) has and social activities of Baosteel branches and subsidiaries in its issued its Environmental Report for 2003 and 2004 that major business of iron and steel industry (including: Baosteel conveyed the environmental information of the company Branch, Stainless Steel Branch, Special Steel Branch, Shanghai to the public in a systematic and transparent manner, Meishan Iron & Steel Co., Ltd., Ningbo Baoxin Stainless Steel increased the understanding and contact between the Co. Ltd., Baosteel-NSC/Arcelor Automotive Steel Sheets Co. society and the company and enhanced the motivation to Ltd., Yantai Lubao Steel Tube Ltd., Huangshi Coated Sheets improve environmental performance in the company. Co. Ltd.), Chemical Branch, Research Institute and so on from January 1st to December 31st 2005, and makes a brief review In order to provide a more comprehensive description of the relevant activities in the past as well, unless otherwise of the production and operation activities of Baosteel for specifi ed. a better understanding of the stakeholders, we rename this report as “Sustainability Report” with the expansion Financial data in the report is based on CNY unit. of economic and social content to promote continuous You may calculate according to the exchange rate of communication with the stakeholders. -
A Closer Look at China's Lgfvs: Sichuan
A Closer Look at China’s LGFVs: Sichuan May 21, 2020 Key Takeaways Primary Analyst Renyuan Zhang — Following a desktop analysis of 136 local government financing vehicles (LGFVs) in Sichuan Beijing Province, we believe the median indicative issuer credit quality of LGFVs in the province is +86-10 6516 6028 renyuan.zhang on a par with national median. @spgchinaratings.cn — We view that Chengdu has much stronger indicative support capability for LGFVs than other cities in the province, mainly benefiting from its stronger economy and fiscal position. Secondary Analysts Guangyuan, Ziyang, Bazhong, and Ya’an have relatively weaker indicative support capability. Yingxue Ren Beijing — We believe that the overall indicative issuer credit quality of the vehicles in Chengdu +86 10 6516 6037 is better than other regions, while the vehicles in cities like Suining and Bazhong have Yingxue.Ren relatively weaker overall indicative issuer credit quality. @spgchinaratings.cn Huang Wang Beijing To get a full picture of the overall credit quality of LGFVs in Sichuan Province, we carried out a +86 10 6516 6029 desktop analysis of 136 LGFVs in the region, using public information. Our sample includes LGFVs Huang.Wang at the city-level and below and subway companies, but excludes provincial-level LGFVs (like @spgchinaratings.cn transportation construction companies, investment holding companies and utility companies) Kexin Wang and city-level investment holding companies without operations in LGFV areas of business. Beijing The entities in the sample represent close to 88% of LGFVs with bonds outstanding in Sichuan, +86 10 6516 6033 covering 18 prefecture-level cities. We believe they offer a comprehensive reflection of the overall Kexin.Wang @spgchinaratings.cn indicative credit quality of LGFVs in Sichuan. -
Province City District Longitude Latitude Population Seismic
Province City District Longitude Latitude Population Seismic Intensity Sichuan Chengdu Jinjiang 104.08 30.67 1090422 8 Sichuan Chengdu Qingyang 104.05 30.68 828140 8 Sichuan Chengdu Jinniu 104.05 30.7 800776 8 Sichuan Chengdu Wuhou 104.05 30.65 1075699 8 Sichuan Chengdu Chenghua 104.1 30.67 938785 8 Sichuan Chengdu Longquanyi 104.27 30.57 967203 7 Sichuan Chengdu Qingbaijiang 104.23 30.88 481792 8 Sichuan Chengdu Xindu 104.15 30.83 875703 8 Sichuan Chengdu Wenqu 103.83 30.7 457070 8 Sichuan Chengdu Jintang 104.43 30.85 717227 7 Sichuan Chengdu Shaungliu 103.92 30.58 1079930 8 Sichuan Chengdu Pi 103.88 30.82 896162 8 Sichuan Chengdu Dayi 103.52 30.58 502199 8 Sichuan Chengdu Pujiang 103.5 30.2 439562 8 Sichuan Chengdu Xinjin 103.82 30.42 302199 8 Sichuan Chengdu Dujiangyan 103.62 31 957996 9 Sichuan Chengdu Pengzhou 103.93 30.98 762887 8 Sichuan Chengdu 邛崃 103.47 30.42 612753 8 Sichuan Chengdu Chouzhou 103.67 30.63 661120 8 Sichuan Zigong Ziliujin 104.77 29.35 346401 7 Sichuan Zigong Gongjin 104.72 29.35 460607 7 Sichuan Zigong Da'An 104.77 29.37 382245 7 Sichuan Zigong Yantan 104.87 29.27 272809 ≤6 Sichuan Zigong Rong 104.42 29.47 590640 7 Sichuan Zigong Fushun 104.98 29.18 826196 ≤6 Sichuan Panzihua Dong 101.7 26.55 315462 ≤6 Sichuan Panzihua Xi 101.6 26.6 151383 ≤6 Sichuan Panzihua Renhe 101.73 26.5 223459 ≤6 Sichuan Panzihua Miyi 102.12 26.88 317295 ≤6 Sichuan Panzihua Yanbian 101.85 26.7 208977 ≤6 Sichuan Luzhou Jiangyang 105.45 28.88 625227 ≤6 Sichuan Luzhou Naxi 105.37 28.77 477707 ≤6 Sichuan Luzhou Longmatan 105.43 28.9 436032 ≤6 -
Supplement of Local and Regional Contributions to Fine Particulate
Supplement of Atmos. Chem. Phys., 19, 5791–5803, 2019 https://doi.org/10.5194/acp-19-5791-2019-supplement © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. Supplement of Local and regional contributions to fine particulate matter in the 18 cities of Sichuan Basin, southwestern China Xue Qiao et al. Correspondence to: Qi Ying ([email protected]) and Hongliang Zhang ([email protected]) The copyright of individual parts of the supplement might differ from the CC BY 4.0 License. 26 Table S1. The area, population, and economic development, and the concentrations of PM2.5 and 27 O3 of the 18 prefectural cities in the SCB in 2015. GDP Annual Annual Region Population Area (×100 City ID City PM2.5 PM2.5 ID (×1000) (km2) million (μg m−3)# (μg m−3)* RMB) R1 & R5 1 Chongqing 33720 82400 15717.3 57 53 2 Bazhong 3795 12293 501.34 35 3 Dazhou 6828 16582 1350.76 59 R2 4 Guangyuan 3053 16311 605.43 21 5 Guang‘’an 4674 6341 1005.61 43 6 Nanchong 7423 12477 1516.2 61 58 7 Deyang 3900 5910 1605.06 53 53 8 Leshan 3538 12723 1301.23 55 9 Luzhou 5057 12236 1353.41 62 59 10 Meishan 3491 7140 1029.86 60 11 Mianyang 5455 20248 1700.33 47 45 R3 12 Neijiang 4204 5385 1198.58 60 13 Suining 3788 5323 915.81 49 14 Ya’an 1549 15046 502.58 34 15 Yibin 5521 13266 1525.9 58 56 16 Zigong 3275 4381 1143.11 74 72 17 Ziyang 5037 7960 1270.38 40 R4 18 Chengdu 12281 12119 10801.2 64 61 28 29 #data source: China Statistical Yearbook 2016, http://www.stats.gov.cn/tjsj/ndsj/2018/indexeh.htm; 30 *calculated by using the data published on the air quality data releasing platform, Ministry of 31 Ecology and Environment of the People’s Republic of China. -
The Cultural Revolution in the Countryside: Scope, Timing and Human Impact*
The Cultural Revolution in the Countryside: Scope, Timing and Human Impact* Andrew G. Walder and Yang Su ABSTRACT Information extracted from 1,520 county annals published after 1987 is used to estimate the timing and impact of the Cultural Revolution in rural China. Outside observers initially concluded that the movement had little impact on remote rural regions, while early post-Mao revelations suggested that the opposite was the case. Adjusting for the tendency of shorter accounts to report fewer casualties, and with additional assumptions about under-reporting in the longer and more detailed accounts, the authors derive an estimated death toll of between 750,000 and 1.5 million, a similar number of people permanently injured, and 36 million who suffered some form of political persecution. The vast majority of these casualties occurred from 1968 to 1971, after the end of the period of popular rebellion and factional conflict and the establishment of provisional organs of local state power. For more than two decades we have known that our early views of the Cultural Revolution in the countryside need to be re-assessed. An initial understanding was firmly established by Richard Baum’s careful analysis of evidence available in 1969, which portrayed the Cultural Revolution as primarily an urban affair. To the extent that it affected rural regions, it did so largely as a spillover from adjacent urban centres: “the many traumatic developments which took place in China’s cities during the Cultural Revolution did have their local counterparts in at least some rural communes … but this was clearly a minority phenomenon.”1 Baum’s exhaustive research led him to conclude that “for most of China’s 550 million or more rural peasants and basic-level cadres, most of the time, the Cultural Revolution was simply not a particularly salient fact of everyday life.”2 Early post-Mao revelations quickly cast doubt on this generalization. -
World Bank Document
INTEGRATED SAFEGUARDS DATA SHEET CONCEPT STAGE Report No.: ISDSC15568 Public Disclosure Authorized Date ISDS Prepared/Updated: 21-Oct-2015 Date ISDS Approved/Disclosed: 09-Jul-2015 I. BASIC INFORMATION Public Disclosure Copy A. Basic Project Data Country: China Project ID: P153548 Project Name: Lushan Earthquake Reconstruction and Risk Reduction Project (P153548) Task Team Madhu Raghunath Leader(s): Estimated 03-Dec-2015 Estimated 10-Mar-2016 Public Disclosure Authorized Appraisal Date: Board Date: Managing Unit: GSU08 Lending Investment Project Financing Instrument: Sector(s): Other social services (20%), General education sector (20%), Rural and Inter- Urban Roads and Highways (20%), Sanitation (20%), Water supply (20%) Theme(s): Natural disaster management (60%), City-wide Infrastructure and Service Delivery (20%), Rural services and infrastructure (10%), Oth er environment and natural resources management (10%) Financing (In USD Million) Total Project Cost: 327.50 Total Bank Financing: 300.00 Public Disclosure Authorized Financing Gap: 0.00 Financing Source Amount Borrower 27.50 International Bank for Reconstruction and Development 300.00 Public Disclosure Copy Total 327.50 Environmental B - Partial Assessment Category: Is this a No Repeater project? B. Project Objectives Public Disclosure Authorized The proposed objective is to build disaster resilient infrastructure and strengthen risk reduction and emergency preparedness. C. Project Description a. Overview On April 20, 2013, almost five years after the 2008 Great Wenchuan Earthquake, the magnitude 7.0 Lushan earthquake struck China¡¯s Sichuan province, with its epicenter in the Lushan County in the Ya¡¯an Municipality. Thirty-two counties (cities, districts) in Ya¡¯an, Chengdu, Leshan, Meishan, Ganzi, Liangshan, Deyang of Sichuan Province were impacted, with a total 2.184 million people affected. -
Gold Standard Verification Report Upm Umwelt-Projekt- Management Gmbh
GOLD STANDARD VERIFICATION REPORT UPM UMWELT-PROJEKT- MANAGEMENT GMBH VERIFICATION OF THE SICHUAN RURAL POOR -HOUSEHOLD BIOGAS DEVELOPMENT PROGRAMME REPORT NO.BVC/ CHINA -VR/8883/2016 REVISION NO.02 BUREAU VERITAS CERTIFICATION 62/71 Boulevard du Château 92571 Neuilly Sur Seine Cdx - France Report Template Revision 19, 23/06/2012 BUREAU VERITAS CERTIFICATION Report No: BVC/CHINA-VR/8873/2015 rev. 02 VERIFICATION REPORT Date of first issue: Organizational unit: 28/09/2016 Bureau Veritas Certification Holding SAS Client: Client ref.: UPM Umwelt-Projekt-Management GmbH Ms. Guo Gaiai Summary: Bureau Veritas Certification has conducted the 4rd periodic verification of Sichuan Rural Poor-Household Biogas Development Programme, GS Registration Reference Number GS1239, managed and communicated by Chengdu Oasis Science & Technology Co., Ltd., which is located in Yibin, Neijiang, Suining, Ziyang, Zigong, Luzhou, Leshan, Meishan, Mianyang, Guang’An, Ganzi, Aba and Dazhou, all of which are located in Sichuan, and applying the methodology AMS-I.C (Version 19) and AMS-III.R Version 02, on the basis of Gold Standard version 2.2 requirements, UNFCCC criteria for the CDM, as well as criteria given to provide for consistent project operations, monitoring and reporting. The verification scope is defined as an independent and objective review and ex-post determination of the monitored GHG emission reductions, and con sisted of the following three phases: i) desk review of the project design, the baseline and monitoring plan; ii) follow-up interviews with project stakeholders; iii) resolution of outstanding issues and the issuance of the final verification report and op inion. The overall verification, from Contract Review to Verification Report & Opinion, was conducted using Bureau Veritas Certification internal procedures.