新旧动能转换背景下广东省耕地低碳利用效率时空演变与差异化提升路径

doi:10.3864/j.issn.0578-1752.2025.11.010

中国农业科学 ›› 2025, Vol. 58 ›› Issue (11): 2206-2224.doi: 10.3864/j.issn.0578-1752.2025.11.010

• 土壤肥料·节水灌溉·农业生态环境 • 上一篇下一篇

新旧动能转换背景下广东省耕地低碳利用效率时空演变与差异化提升路径

朱庆莹¹^,²^,³(), 何耿毅¹, 孙萍³()

¹ 华南农业大学公共管理学院，广州 510642
² 自然资源部华南热带亚热带自然资源监测重点实验室，广州 510700
³ 自然资源部滨海城市地下空间地质安全重点实验室，山东青岛 266101

收稿日期:2024-07-29 接受日期:2024-09-07 出版日期:2025-06-01 发布日期:2025-06-09
通信作者:
孙萍，E-mail：15254201109@163.com
联系方式: 朱庆莹，Tel：18720989054，E-mail：1257019206@qq.com。
基金资助:
教育部人文社科基金(24YJC630323); 广东省社科基金(GD24YGL03); 广东省软科学面上基金(2024A1010030007); 广州市社会科学基金(2023GZQN28); 广州市自科基金(2024A04J3280); 自然资源部华南热带亚热带自然资源监测重点实验室课题(2024NRMZ06); 自然资源部滨海城市地下空间地质安全重点实验室课题(BHKF2023Y02)

Research on the Spatio-Temporal Evolution and Differentiated Improvement Path of Low-Carbon Utilization Efficiency of Cultivated Land Under the Background of New and Old Kinetic Energy Conversion——A Case Study of Guangdong Province

ZHU QingYing¹^,²^,³(), HE GengYi¹, SUN Ping³()

¹ School of Public Management, South China Agricultural University, Guangzhou 510642
² Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources, Guangzhou 510700
³ Key Laboratory of Geological Safety of Coastal Urban Underground Space, Ministry of Natural Resources, Qingdao 266101, Shandong

Received:2024-07-29 Accepted:2024-09-07 Published:2025-06-01 Online:2025-06-09

摘要/Abstract

摘要：

【目的】科学揭示新旧动能转换背景下耕地低碳利用效率时空演变特征，深入辨析耕地低碳利用效率提升的差异化组态路径，以期为耕地高效可持续利用、农业新质生产力培育乃至农业高质量发展提供决策依据。【方法】在界定新旧动能转换背景下耕地低碳利用效率内涵及构建其组态路径理论框架基础上，基于广东省2010—2021年间21个地级市的面板数据，采用非期望产出的Super-SBM模型评估新旧动能转换背景下的耕地低碳利用效率并刻画时空演化特征，运用模糊集定性分析法（fsQCA）探讨耕地低碳利用效率提升的差异化组态路径。【结果】（1）从时序特征看，2010—2021年广东省耕地低碳利用效率呈现在波动中缓慢上升的特征，均值为0.947；珠三角和粤北地区的演变特征与省级层面类似，粤东波动较小，粤西则呈现在波动中下降的态势，只有珠三角效率均值大于1；从空间分布看，广东省耕地低碳利用效率空间分异特征显著，呈高、低效率区多核心成片分布，尤以珠三角高效率及粤北低效率现象突出。（2）广东省耕地低碳利用效率提升路径可归纳为社会经济或政府支持单因素、技术赋能-政府支持或社会经济-政府支持双因素、资源禀赋-社会经济-政府支持多因素主导三类组态路径。（3）社会经济发展水平和政府支持程度是影响耕地低碳利用效率的最具普遍性因素，而耕地资源禀赋条件和农业技术投入水平的影响相对较弱。这些因素在特定的条件下能发生等效替代，耕地资源禀赋能够被其他三类因素单独或形成的组合所取代，构成提升耕地低碳利用效率“殊途同归”的路径。【结论】耕地低碳利用是一个受“资源-经济-技术-政策”复杂系统因素交互影响的组态问题，实际中应注重其提升路径设计的整体谋划和因地施策。当前耕地数量受到严重威胁，持续在社会经济发展、财政支农力度以及农业生产技术水平等方面发力应成为促进耕地低碳高效利用长期坚持的方向。

关键词: 新旧动能转换, 耕地低碳利用效率, 时空演化特征, 组态路径, 广东省

Abstract:

【Objective】 To scientifically reveal the spatio-temporal evolution characteristics of the low-carbon use efficiency of cultivated land under the background of new and old kinetic energy conversion, and deeply analyze the differentiated configuration paths for improving the low-carbon use efficiency of cultivated land, so as to provide decision-making basis for the efficient and sustainable use of cultivated land, the cultivation of new agricultural productive forces, and even the high-quality development of agriculture.【Method】 Based on defining the connotation of the low-carbon use efficiency of cultivated land under the background of new and old kinetic energy conversion and constructing a theoretical framework for its configuration path, using the panel data of 21 prefecture-level cities in Guangdong Province from 2010 to 2021, the Super-SBM model with undesired outputs was adopted to evaluate the low-carbon use efficiency of cultivated land under the background of new and old kinetic energy conversion and depict the spatio-temporal evolution characteristics, and the fuzzy-set qualitative comparative analysis (fsQCA) was used to explore the differentiated configuration paths for improving the low-carbon use efficiency of cultivated land. 【Result】 (1) From the perspective of temporal characteristics, the low-carbon use efficiency of cultivated land in Guangdong Province showed a slow upward trend with fluctuations from 2010 to 2021, with an average value of 0.947; the evolution characteristics of the Pearl River Delta and Northern Guangdong were similar to those at the provincial level, Eastern Guangdong had small fluctuations, while Western Guangdong showed a downward trend with fluctuations, and only the Pearl River Delta had an average efficiency value greater than 1; from the perspective of spatial distribution, the spatial differentiation characteristics of the low-carbon use efficiency of cultivated land in Guangdong Province were significant, showing a multi-core and contiguous distribution of high and low efficiency areas, especially the prominent phenomena of high efficiency in the Pearl River Delta and low efficiency in Northern Guangdong. (2) The paths for improving the low-carbon use efficiency of cultivated land in Guangdong Province could be summarized into three types of configuration paths: single-factor dominated by socio-economic or government support, two-factor dominated by technological empowerment-government support or socio-economic-government support, and multi-factor dominated by resource endowment-socio-economic-government support. (3) The level of socio-economic development and the degree of government support were the most universal factors affecting the low-carbon use efficiency of cultivated land, while the influence of cultivated land resource endowment conditions and the level of agricultural technology investment was relatively weak. These factors could undergo equivalent substitution under specific conditions, and cultivated land resource endowment could be replaced by other three types of factors alone or in combination, forming the "same goal through different paths" for improving the low-carbon use efficiency of cultivated land.【Conclusion】 The low-carbon use of cultivated land is a configuration problem affected by the interaction of factors in the "resource-economy-technology-policy" complex system. In practice, attention should be paid to the overall planning of the design of improvement paths and policy implementation according to local conditions. At present, the quantity of cultivated land is under serious threat, and continuous efforts in socio-economic development, financial support for agriculture, and the level of agricultural production technology should become the long-term direction for promoting the low-carbon and efficient use of cultivated land.

Key words: new and old kinetic energy conversion, low-carbon use efficiency of cultivated land, spatio-temporal evolution characteristics, configuration path, Guangdong Province

朱庆莹, 何耿毅, 孙萍. 新旧动能转换背景下广东省耕地低碳利用效率时空演变与差异化提升路径[J]. 中国农业科学, 2025, 58(11): 2206-2224.

ZHU QingYing, HE GengYi, SUN Ping. Research on the Spatio-Temporal Evolution and Differentiated Improvement Path of Low-Carbon Utilization Efficiency of Cultivated Land Under the Background of New and Old Kinetic Energy Conversion——A Case Study of Guangdong Province[J]. Scientia Agricultura Sinica, 2025, 58(11): 2206-2224.

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图/表 11

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图2

表1

表2

表3

表4

2010—2021年广东省21个地级市耕地低碳利用效率值"

城市 City	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	均值 Mean
珠三角 The Pearl River Delta	0.935	0.937	0.989	1.002	1.038	1.015	1.069	1.061	1.059	1.013	1.066	1.076	1.022
广州Guangzhou	1.024	1.014	1.123	1.097	1.144	1.157	1.168	1.180	1.103	1.090	1.098	1.134	1.111
珠海Zhuhai	0.905	0.730	0.753	0.965	0.958	1.018	1.049	1.062	1.053	1.071	1.071	1.089	0.977
深圳Shenzhen	1.210	1.379	1.646	1.522	1.728	1.495	1.899	1.782	1.811	1.672	1.928	1.990	1.672
佛山Foshan	0.686	0.723	0.927	0.963	0.968	0.968	0.972	0.969	0.968	0.928	0.873	0.962	0.909
惠州Huizhou	0.901	0.912	0.910	0.909	0.912	0.916	0.927	0.891	0.801	0.651	0.869	0.858	0.871
东莞Dongguan	0.957	0.941	0.941	0.995	1.027	1.051	1.141	1.145	1.205	1.226	1.040	1.112	1.065
中山Zhongshan	1.211	1.216	1.143	1.132	1.170	1.080	1.035	0.990	0.945	0.990	1.116	1.049	1.090
江门Jiangmen	0.908	0.910	0.926	0.919	0.900	0.909	0.918	0.918	0.927	0.918	0.918	0.915	0.916
肇庆Zhaoqing	0.616	0.611	0.530	0.519	0.531	0.537	0.513	0.610	0.716	0.572	0.680	0.572	0.584
粤东East Guangdong	0.906	0.907	0.902	0.901	0.918	0.924	0.915	0.874	0.915	0.888	0.927	0.905	0.907
潮州Chaozhou	0.900	0.900	0.900	0.909	0.900	0.936	0.936	0.756	0.891	0.882	0.889	0.887	0.891
汕头Shantou	1.001	1.012	0.974	0.961	1.029	1.018	0.968	0.998	1.004	0.925	1.021	0.986	0.991
揭阳Jieyang	0.959	0.957	0.966	0.980	0.986	0.992	1.034	0.947	0.959	0.925	0.999	0.975	0.973
汕尾Shanwei	0.763	0.757	0.767	0.754	0.755	0.749	0.720	0.796	0.807	0.821	0.798	0.771	0.772
粤北 Northern Guangdong	0.826	0.820	0.827	0.835	0.834	0.837	0.836	0.852	0.878	0.863	0.840	0.866	0.843
河源Heyuan	0.978	0.973	0.974	0.972	0.975	0.978	0.977	0.975	0.990	0.981	0.978	0.978	0.977
梅州Meizhou	0.842	0.839	0.850	0.876	0.888	0.889	0.877	0.882	0.981	0.965	0.946	0.973	0.901
韶关Shaoguan	0.851	0.845	0.842	0.842	0.838	0.837	0.834	0.851	0.896	0.849	0.851	0.934	0.856
清远Qingyuan	0.680	0.671	0.695	0.712	0.709	0.724	0.730	0.716	0.720	0.711	0.716	0.717	0.708
云浮Yunfu	0.779	0.770	0.773	0.775	0.761	0.756	0.760	0.838	0.802	0.810	0.711	0.729	0.772
粤西 West Guangdong	0.957	1.004	0.980	0.979	0.968	0.962	0.956	0.939	0.934	0.942	0.908	0.903	0.953
湛江Zhanjiang	1.072	1.079	1.017	1.031	1.042	1.039	1.047	1.045	1.031	1.045	0.968	1.040	1.038
茂名Maoming	0.991	0.989	0.986	0.987	0.913	0.911	0.914	0.979	0.968	0.971	0.973	0.950	0.961
阳江Yangjiang	0.807	0.945	0.937	0.919	0.950	0.935	0.908	0.793	0.802	0.810	0.783	0.718	0.859
均值Mean	0.906	0.913	0.932	0.940	0.957	0.948	0.968	0.959	0.970	0.943	0.963	0.968	0.947

表4

图3

表5

2010—2021年广东省耕地低碳利用效率空间分布及其变化"

区域 Region	年份 Year
区域 Region	2010	2014	2018	2022
珠三角 The Pearl River Delta	高效率区（中山市、深圳市） High efficiency zone (Zhongshan City, Shenzhen City) 较高效率区（广州市） Higher efficiency zone (Guangzhou City) 中等效率区（东莞市） Medium efficiency zone (Dongguan City) 较低效率区（珠海市、江门市、惠州市） Lower efficiency zone (Zhuhai City, Jiangmen City, Huizhou City) 低效率区（肇庆市、清远市、佛山市） Low efficiency zone (Zhaoqing City, Qingyuan City, Foshan City)	高效率区（广州市、中山市、深圳市） High efficiency zone (Guangzhou City, Zhongshan City, Shenzhen City) 较高效率区（东莞市、佛山市、珠海市） Higher efficiency zone (Dongguan City, Foshan City, Zhuhai City) 较低效率区（江门市、惠州市） Lower efficiency zone (Jiangmen City, Huizhou City) 低效率区（肇庆市） Low efficiency zone (Zhaoqing City)	高效率区（东莞市、深圳市） High efficiency zone (Dongguan City, Shenzhen City) 较高效率区（广州市、珠海市） Higher efficiency zone (Guangzhou City, Zhuhai City) 中等效率区（江门市、中山市、佛山市） Medium efficiency zone (Jiangmen City, Zhongshan City, Foshan City) 较低效率区（惠州市） Lower efficiency zone (Huizhou City) 低效率区（肇庆市） Low efficiency zone (Zhaoqing City)	高效率区（深圳市） High efficiency zone (Shenzhen City) 较高效率区（广州市、中山市、东莞市、珠海市） Higher efficiency zone (Guangzhou City, Zhongshan City, Dongguan City, Zhuhai City) 中等效率区（佛山市） Medium efficiency zone (Foshan City) 较低效率区（江门市、惠州市） Lower efficiency zone (Jiangmen City, Huizhou City) 低效率区（肇庆市） Low efficiency zone (Zhaoqing City)
粤东 East Guangdong	较高效率区（汕头市） High efficiency zone (Shantou City) 中等效率区（揭阳市） Medium efficiency zone (Jieyang City) 较低效率区（潮州市） Lower efficiency zone (Chaozhou City) 低效率区（汕尾市） Low efficiency zone (Shanwei City)	较高效率区（汕头市） Higher efficiency zone (Shantou City) 中等效率区（揭阳市） Medium efficiency zone (Jieyang City) 较低效率区（潮州市） Lower efficiency zone (Chaozhou City) 低效率区（汕尾市） Low efficiency zone (Shanwei City)	较高效率区（汕头市） Higher efficiency zone (Shantou City）中等效率区（揭阳市） Medium efficiency zone (Jieyang City）较低效率区（汕尾市、潮州市） Lower efficiency zone (Shanwei City, Chaozhou City）	中等效率区（揭阳市、汕头市） Medium efficiency zone (Jieyang City, Shantou City）较低效率区（潮州市） Lower efficiency zone (Chaozhou City）低效率区（汕尾市） Low efficiency zone (Shanwei City）
粤北 Northern Guangdong	中等效率区（河源市） Medium efficiency zone (Heyuan City) 较低效率区（云浮市、韶关市、梅州市） Lower efficiency zone (Yunfu City, ShaoGuan City, Meizhou City) 低效率区（清远市） Low efficiency zone (Qingyuan City)	中等效率区（河源市） Medium efficiency zone (Heyuan City）较低效率区（韶关市、梅州市） Lower efficiency zone (Shaoguan City, Meizhou City）低效率区（云浮市、清远市） Low efficiency zone (Yunfu City, Qingyuan City）	较高效率区（河源市） Higher efficiency zone (Heyuan City）中等效率区（梅州市） Medium Efficiency zone (Meizhou City）较低效率区（云浮市、韶关市） Lower efficiency zone (Yunfu City, Shaoguan City）低效率区（清远市） Low efficiency zone (Qingyuan City）	中等效率区（韶关市、河源市、梅州市） Medium efficiency zone (Shaoguan City, Heyuan City, Meizhou City) 低效率区（云浮市、清远市） Low efficiency zone (Yunfu City, Qingyuan City)
粤西 West Guangdong	较高效率区（湛江市、茂名市） High efficiency zone (Zhanjiang City, Maoming City) 较低效率区（阳江市） Lower efficiency zone (Yangjiang City)	较高效率区（湛江市） Higher efficiency zone (Zhanjiang City）中等效率区（阳江市） Medium efficiency zone (Yangjiang City）较低效率区（茂名市） Lower efficiency zone (Maoming City）	较高效率区（湛江市） Higher efficiency zone (Zhanjiang City）中等效率区（茂名市） Medium efficiency zone (Maoming City) 较低效率区（阳江市） Lower efficiency zone (Yangjiang City)	较高效率区（湛江市） Higher efficiency zone (Zhanjiang City) 中等效率区（茂名市） Medium efficiency zone (Maoming City) 低效率区（阳江市） Low efficiency zone (Yangjiang City)

表5

表6

表7

图4

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集合 Collection	条件和结果 Conditions and results	统计性描述 Statistical description		校准 Calibration
集合 Collection	条件和结果 Conditions and results	平均值 Mean	标准差 Standard deviation	完全隶属 Fully affiliated	交叉点 Intersection	完全不隶属 Completely not affiliated
结果变量 Variables of results	耕地低碳利用效率 Low-carbon use efficiency of cultivated land	1.053	0.242	1.348	1.041	0.756
资源禀赋 Endowment	耕地面积 Cultivated area (×10³hm²)	128520.74	115248.95	342098.41	104500.00	10644.92
资源禀赋 Endowment	水田面积占比 Proportion of paddy field (%)	0.608	0.264	0.932	0.679	0.018
社会经济 Socio-economic	农村人口数Rural population (×10⁴)	3178326.79	1587428.32	6420402.80	3021550.00	495642.00
社会经济 Socio-economic	农村居民人均可支配收入 Per capita disposable income of rural residents (yuan)	18118.73	8402.38	35473.91	16439.10	7495.65
政府支持 Government support	农林水支出 Agriculture, forestry and water expenditure (×10⁸yuan)	330946.50	207348.69	692572.60	299667.00	60559.35
农业生产技术 Agricultural production technology	有效灌溉率Effective irrigation rate (%)	0.606	0.231	0.981	0.589	0.174
农业生产技术 Agricultural production technology	农业技术人员数量 Number of agricultural technicians	535.37	1029.23	2144.85	164.00	61.00

变量类型 Variable type			具体变量 Specific variables
投入指标 Input indicators	旧动能 Old kinetic energy	土地 Land	农作物播种面积Planting area of crops (×10³ hm²)
		劳动Labor	第一产业从业人员数Employees number of the primary industry (×10⁴)
		灌溉 Irrigation	耕地有效灌溉面积 Effective irrigated area of cultivated land (×10³ hm²)
		机械 Machinery	农业机械总动力 Total power of agricultural machinery (×10⁴kW)
		化肥 Chemical fertilizer	化肥折纯量Fertilizer purity conversion (×10³t)
		农药Pesticide	农药使用量 Pesticide usage (t)
		农膜 Agricultural film	农用塑料薄膜使用量Agricultural film usage (t)
	新动能 New kinetic energy	知识 Knowledge	农村专业技术协会数 Rural professional and technical associations number
		信息 Information	农村居民家庭每百户计算机拥有量 Number of computers per 100 households in rural areas
		技术 Technology	科研课题投入经费Research project investment funds (×10⁴yuan)
期望产出指标 Expected output indicators	经济效益Economic benefits		农业总产值Total agricultural output value (×10⁸yuan)
	社会效益 Social benefits		粮食总产量Total grain output (×10⁴t)
	环境效益 Environmental benefits		耕地碳汇总量Total carbon sink of cultivated land (×10⁴t)
非期望产出指标 Unexpected output indicators	环境损失 Environmental losses		耕地碳排放总量Total carbon emissions of cultivated land (t)

变量类别 Variable type			具体变量 Specific variables
结果变量 Outcome variable	耕地低碳利用效率 Low-carbon use efficiency of cultivated land		Super-SBM模型测算值 Calculation value of Super-SBM model
条件变量 Conditional variable	耕地资源禀赋 Endowment of cultivated land	耕地面积 Cultivated area	年末耕地面积 Cultivated land area in end of year (×10³hm²)
	耕地资源禀赋 Endowment of cultivated land	水田面积占比 Proportion of paddy field	水田面积/耕地面积 Paddy fields area/Cultivated area
	社会经济发展水平 Level of socio-economic development	农村人口总数 Rural population	农村人口数Rural population (×10⁴)
	社会经济发展水平 Level of socio-economic development	农村居民人均可支配收入 Per capita disposable income of rural residents	农村居民人均可支配收入 Per capita disposable income of rural residents (yuan)
	政府支持 Government support	农林水支出 Agriculture, forestry and water expenditure	地方一般预算农林水支出 Local agricultural, forestry and water expenditure budget (×10⁸yuan)
	农业技术投入水平 Agricultural technology investment level	有效灌溉率 Effective irrigation rate	有效灌溉面积/耕地面积 Effective irrigation area/Cultivated land area
	农业技术投入水平 Agricultural technology investment level	农业技术人员人数 Number of agricultural technicians	农业技术人员数量 Number of agricultural technicians

条件 Condition	一致性 Consistency	覆盖率 Coverage rate
耕地面积 Cultivated area	0.555	0.582
~耕地面积 ~ Cultivated area	0.801	0.715
水田面积占比 Proportion of paddy field	0.639	0.588
~水田面积占比 ~ Proportion of paddy field	0.717	0.728
农村人口数Rural population	0.691	0.677
~农村人口数 ~ Rural population	0.700	0.665
农村居民人均可支配收入 Per capita disposable income of rural residents	0.738	0.755
~农村居民人均可支配收入 ~ Per capita disposable income of rural residents	0.619	0.565
农林水支出 Agriculture, forestry and water expenditure	0.703	0.706
~农林水支出 ~ Agriculture, forestry and water expenditure	0.654	0.607
有效灌溉率 Effective irrigation rate	0.676	0.618
~有效灌溉率 ~ Effective irrigation rate	0.656	0.669
农业技术人员数量 Number of agricultural technicians	0.578	0.650
~农业技术人员数量 ~ Number of agricultural technicians	0.721	0.609

条件变量 Conditional variable		单要素主导 Single element dominance				双要素主导 Dual element dominance				多要素主导 Multi element dominance
		P₁			P₂	P₃	P₄			P₅
		P_1a	P_1b	P_1C	P₂	P₃	P_4a	P_4b	P_4c	P_5a	P_5b	P_5C
耕地资源禀赋 Endowment of cultivated land	耕地面积 Cultivated area	☆	☆	☆	☆	●	●	○			●	☆
耕地资源禀赋 Endowment of cultivated land	水田面积占比 Proportion of paddy field	☆	○	●		☆			●	★	★	★
社会经济发展水平 Level of socio-economic development	农村人口数 Rural population		○	●	●	☆	★		●	★	★	★
社会经济发展水平 Level of socio-economic development	农村居民人均可支配收入 Per capita disposable income of rural residents	★	★	★	○	○	★	★	★	○
政府支持程度 Government support	农林水支出 Agriculture, forestry and water expenditure	⊙		●	★	★	★	★	★	★	★	★
农业技术投入水平 Agricultural technology investment level	有效灌溉率 Effective irrigation rate		☆	☆	☆	☆	○	●	●	☆	☆	●
农业技术投入水平 Agricultural technology investment level	农业技术人员数量 Number of agricultural technicians	☆	●	●	○	★	☆	☆	☆	☆	☆	☆
一致性 Consistency		0.867	0.876	0.852	0.865	0.855	0.864	0.860	0.860	0.857	0.851	0.847
原始覆盖度 Original coverage		0.357	0.275	0.204	0.253	0.213	0.255	0.257	0.269	0.293	0.297	0.270
唯一覆盖度 Unique coverage		0.085	0.034	0.017	0.003	0.012	0.012	0.005	0.009	0.000	0.000	0.000
总体解的一致性 Consistency of overall solution		0.837
总体解的覆盖度 Coverage of the overall solution		0.641

新旧动能转换背景下广东省耕地低碳利用效率时空演变与差异化提升路径

Research on the Spatio-Temporal Evolution and Differentiated Improvement Path of Low-Carbon Utilization Efficiency of Cultivated Land Under the Background of New and Old Kinetic Energy Conversion——A Case Study of Guangdong Province

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