江苏省县域农业温室气体排放：时空差异与趋势演进

doi:10.18402/resci.2018.05.20

摘要/Abstract

摘要：

农业温室气体排放占温室气体排放比例很大,对气候变暖的影响不可忽视。本文以江苏省62个县域单元为研究对象,测算了2001—2014年各县域排放量和排放强度,分析了其空间格局变动、时空差异演变,进而开展了各县域农业温室气体排放承载系数和农业经济贡献系数差异分析,根据矩阵聚类分析进行了空间区域划分,全面揭示了农业温室气体排放的时空性、差异性。研究结果显示：①全省排放量年际变化波动较大,2007年以后快速增加,年均增长4.37％,而排放强度呈明显下降趋势,年均降幅4.26%。②排放量空间分布逐步集聚,而排放强度则逐步均衡化,到2014年已经相对离散。③排放量、排放强度及ESC基尼系数较为合理,而ECC（经济水平-温室气体排放）基尼系数超过了“0.4”警戒线,仍有上涨趋势,应引起特别注意。④为凸显排放对农业发展承载贡献的区域差异性,将62个县域单元划分为四类：“高承载力-高经济贡献”型、“高承载力-低经济贡献”型、“低承载力-高经济贡献”型、“低承载力-低经济贡献”型,并提出了不同类型区的农业发展与温室气体减排策略。本文对县域水平进行时空差异分析评价与聚类,不仅为江苏省及各县市制定农业节能减排政策、实现低碳农业提供科学依据,也为从微观县域层面在时间和空间2个维度上深化温室气体排放研究提供了新思路。

关键词: 农业温室气体排放, 县域, 时空差异, 基尼系数, 江苏

Abstract:

Agricultural greenhouse gases emissions account for a large proportion of global greenhouse gases emissions. The emission amount and intensity of greenhouse gases such as CO₂, CH₄ and N₂O in 62 counties in Jiangsu Province from 2001 to 2014 were studied. By analyzing spatial patterns and the evolution of spatial variation according to Gini coefficients, the bearing and contribution of agricultural development was obtained. In this analysis, according to matrix clustering analysis the spatial region was divided and the inter-county relationship was quantitatively analyzed, which fully revealed the feature of agricultural greenhouse gases emissions—difference among spatial regions and its revolution with time. The annual fluctuation in emissions in the province varied significantly and increased rapidly after 2007 with average annual growth of 4.37%. However, the emission intensity showed a decreasing trend and an average annual decrease of 4.26%. The spatial agglomeration of agricultural greenhouse gas emissions was obvious. The emission intensity gradually tends to be balanced. Emission amount, emission intensity and ESC Gini coefficient were becoming more reasonable. However, ECC (economic level - greenhouse gases emission) Gini coefficient was still larger than 0.4 and showed a rising trend, which should receive special attention. In order to highlight regional differences in the bearing and contribution of agricultural development resulting from emissions, 62 county-units were divided into four categories: "High bearing capacity - high economic contribution" type", High bearing capacity - low economic contribution" type, "Low bearing capacity - high economic contribution" type, "Low bearing capacity-low economic contribution" type. This study provides a scientific basis for counties in Jiangsu Province to develop energy-saving and emission-reduction policies to achieve low-carbon agriculture.

Key words: agricultural greenhouse gases emission, county, spatial and temporal variation, Gini coefficient, Jiangsu

陈慧, 付光辉, 刘友兆. 江苏省县域农业温室气体排放：时空差异与趋势演进[J]. 资源科学, 2018, 40(5): 1084-1094.

Hui CHEN, Guanghui FU, Youzhao LIU. Spatial and temporal variation and trend evolution of county-based agricultural greenhouse gas emissions in Jiangsu Province[J]. Resources Science, 2018, 40(5): 1084-1094.

图/表 8

表1

江苏省主要农业温室气体排放量测算体系"

温室气体	主要途径	计算公式	说明	参考文献
CO₂	化肥生产、农业机械和用电	$C O 2 = (F × k 1 + Area × k 2 + Machine × k 3 + Electric × k 4) × 44 / 12 000$ （4）	CO₂为农业CO₂排放总量;F为化肥使用量;Area为农作物种植面积;Machine为农业机械总动力;Electric为农业生产用电总量;k₁、k₂、k₃、k₄为碳转换系数,其中k₁=857.54,k₂=16.47,k₃=0.18,k₄=0.18	[11,28]
CH₄	稻田CH₄排放	$C H 4 - 水稻 = E F 水稻 × Are a 水稻$ （5）	CH_4-水稻为稻田CH₄排放量;EF_水稻为224.6 kg/hm²;Area_水稻为水稻年播种面积	[11]
CH₄	蓄养动物CH₄排放	$C H 4 - 动物 = ∑ i n T i × ? i + ∑ i n T i × ∈ i$ （6）	CH_4-动物为蓄养动物CH₄排放量;T_i为饲养量; $? i$ 、 $∈ i$ 分别为动物肠道、粪便发酵的CH₄排放系数	[1]
N₂O	农田土壤N₂O	$N 2 O - 土壤 = (2.22 × P + 0.0213 × P × N) × Are a 化肥 × 44 / 28$ （7）	N₂O_-土壤为农田土壤N₂O排放量;P为年降水量;N为施氮量;Area_化肥为化肥使用面积	[11]
	蓄养动物粪便管理N₂O排放	$N 2 O - 动物 = ∑ i n T i × γ i$ （8）	N₂O_-动物为蓄养动物N₂O排放量;T_i为饲养量;γ_i为粪便发酵的N₂O排放系数	[1]
	剩余农产品N₂O排放	$N 2 O - 剩余农产品 = (1 + 0.0125 × N 剩余农产品) × 44 / 2800$ （9）	N₂O_{-剩余农产品}为剩余农产品N₂O排放量;N_{剩余农产品}为剩余农产品总含氮量	[11]
排放总量		$G i = ∑ C O 2 i + 25$ $∑ C H 4 i + 298 × ∑ N 2 O i$ （10）	G_i为第i个县域单元农业温室气体排放量	[11]

表1

图1

图2

图3

图4

表2

2001年、2014年各县域单元ESC与ECC"

序号	地区	2001年		2014年		序号	地区	2001年		2014年
序号	地区	ESC	ECC	ESC	ECC	序号	地区	ESC	ECC	ESC	ECC
1	南京市辖区	0.85	1.01	1.02	1.19	32	灌云县	1.06	0.39	0.97	0.50
2	浦口区	1.71	0.47	1.04	1.67	33	灌南县	1.03	0.36	1.07	0.51
3	江宁区	0.60	0.87	1.23	1.54	34	淮安市辖区	0.88	1.13	1.10	1.27
4	六合区	1.12	0.56	1.05	0.84	35	涟水县	0.60	0.81	1.07	0.44
5	溧水区	1.28	0.56	1.23	1.02	36	洪泽县	1.13	0.27	1.19	0.63
6	高淳区	1.26	0.68	1.29	1.58	37	盱眙县	0.69	0.56	1.02	0.39
7	无锡市辖区	1.18	1.90	1.18	9.60	38	金湖县	1.30	0.28	1.27	0.50
8	江阴市	1.10	0.66	1.03	1.57	39	盐城市辖区	0.88	5.90	1.09	4.60
9	宜兴市	0.60	1.16	1.21	0.86	40	响水县	0.92	0.27	0.87	0.42
10	徐州市辖区	0.96	2.43	0.80	2.07	41	滨海县	1.00	0.48	0.83	0.35
11	丰县	0.82	0.42	0.62	0.39	42	阜宁县	1.12	0.35	0.95	0.39
12	沛县	0.99	0.54	0.88	0.68	43	射阳县	1.12	1.01	1.15	0.70
13	睢宁县	0.92	0.36	0.75	0.39	44	建湖县	1.29	0.56	1.16	0.55
14	新沂市	0.87	0.56	0.75	0.47	45	东台市	0.78	0.47	0.83	0.47
15	邳州市	1.05	0.55	0.82	0.61	46	大丰市	1.11	0.65	0.99	0.56
16	常州市辖区	1.04	2.15	1.03	3.33	47	扬州市辖区	1.30	1.62	1.26	2.14
17	溧阳市	0.95	0.69	1.27	0.74	48	宝应县	0.80	1.08	1.29	0.64
18	金坛市	1.27	0.48	1.11	0.99	49	仪征市	1.07	0.43	1.19	0.57
19	苏州市辖区	1.04	3.06	0.98	6.17	50	高邮市	1.33	0.64	1.32	0.70
20	常熟市	0.81	1.15	1.19	0.95	51	镇江市辖区	1.06	2.69	1.07	3.00
21	张家港市	1.18	0.65	1.20	1.00	52	丹阳市	1.13	0.55	1.25	0.76
22	昆山市	1.12	0.96	1.19	1.95	53	扬中市	1.14	0.83	1.15	0.95
23	太仓市	1.16	1.11	1.04	1.17	54	句容市	1.24	0.50	1.26	0.81
24	南通市辖区	1.14	3.60	1.10	3.51	55	泰州市辖区	1.10	2.06	1.13	1.80
25	海安县	1.00	0.53	0.93	0.56	56	兴化市	1.41	0.61	1.28	0.56
26	如东县	1.01	0.54	1.06	0.55	57	靖江市	1.01	0.40	1.08	0.44
27	启东市	0.69	0.66	0.86	0.83	58	泰兴市	0.88	0.42	1.04	0.44
28	如皋市	0.86	0.35	0.93	0.47	59	宿迁市辖区	0.94	2.54	0.97	1.88
29	海门市	0.71	0.54	0.82	0.73	60	沭阳县	1.02	0.44	1.02	0.44
30	连云港市辖区	0.87	2.96	0.95	1.87	61	泗阳县	0.83	0.41	0.95	0.53
31	东海县	0.92	0.38	0.96	0.39	62	泗洪县	0.89	0.37	0.92	0.38

表2

图5

图6

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