山东省农业净碳汇时空演化特征分析
|
摘要
基于农地利用、水稻种植、畜禽养殖、秸秆焚烧4大方面25类主要碳源和17类主要农作物碳汇,测算了山东省2000—2015年及全省17个地级市2000年、2007年、2015年的农业碳排放量和碳汇量,在此基础上计算出农业净碳汇量和净碳汇强度,并对其时空演化特征进行分析。结果表明,2000—2015年间山东省农业净碳汇总量和净碳汇强度均呈上升趋势,分别增长33.05%和39.14%,农业发展的碳效应以碳汇为主,减排增汇效果明显;农业净碳汇量区域差异明显且随时间的变化呈扩大趋势,存在净碳汇量持续增长型、波动增长型、波动下降型和持续下降型4种类型区;农业净碳汇强度区域差异较明显,亦随时间变化呈扩大趋势,存在净碳汇强度持续增长型和波动下降型2种类型区;基于空间分布特征,将各地级市净碳汇量和净碳汇强度分别划分为低、较低、中、较高和高5个等级区,2000—2015年间净碳低汇区空间分布格局相对稳定,其他4个等级区发生了较大幅度的变化,净碳高汇区向鲁西地区集中,净碳较高汇区向鲁东南地区分布;净碳汇强度空间分布格局发生了较大幅度的变化,净碳汇高强度区由鲁中向鲁西和鲁西南地区扩展,净碳汇较高强度区由鲁中向鲁东南地区扩展。
Based on the 25 categories of the major carbon resources from four aspects including agricultural land use, rice planting, livestock and poultry breeding and straw burning and the 17 categories of major crops carbon sink species, this study calculated the carbon emissions and carbon sink in Shandong Province from 2000 to 2015, and also calculated those of 17 prefecture-level cities in 2000, 2007 and 2015. Then, the agricultural net carbon sink and the intensity of net carbon sink were calculated, and the characteristics of spatial-temporal evolution were analyzed. The results showed that the amount of agricultural net carbon sink and net carbon sink intensity in Shandong province from 2000 to 2015 showed the upward trend, with the increase of 33.05% and 39.14% respectively. Carbon sink was the main carbon effect in agricultural development, and the effect of reduce emission on the increased carbon sink was obvious. The regional difference of agricultural net carbon sink was obvious and showed a trend of expansion with time, and there were four types of regions: "continuous increase", "fluctuant increase", "fluctuant decrease" and "continuous decrease". The regional difference of agricultural net carbon sink intensities was obvious and also showed a trend of expansion with time, and there were two types of regions: "continuous increase" and "fluctuant decrease". Based on spatial distribution features, the net carbon sink and net carbon sink intensities of each city were divided into five grades: lowest, lower, medium, higher and highest, from 2000 to 2015. The spatial distribution pattern of lowest net carbon sink area was relatively stable, while the other four grades of areas changed greatly. The highest net carbon sink areas were concentrated in the west of Shandong Province, and the higher net carbon sink areas in the southeast. The spatial distribution pattern of net carbon sink intensities changed greatly, the highest intensity areas of net carbon sink expanded from the middle to the west and southwest of Shandong Province, and the higher intensity areas from the middle to the southeast.
Based on the 25 categories of the major carbon resources from four aspects including agricultural land use, rice planting, livestock and poultry breeding and straw burning and the 17 categories of major crops carbon sink species, this study calculated the carbon emissions and carbon sink in Shandong Province from 2000 to 2015, and also calculated those of 17 prefecture-level cities in 2000, 2007 and 2015. Then, the agricultural net carbon sink and the intensity of net carbon sink were calculated, and the characteristics of spatial-temporal evolution were analyzed. The results showed that the amount of agricultural net carbon sink and net carbon sink intensity in Shandong province from 2000 to 2015 showed the upward trend, with the increase of 33.05% and 39.14% respectively. Carbon sink was the main carbon effect in agricultural development, and the effect of reduce emission on the increased carbon sink was obvious. The regional difference of agricultural net carbon sink was obvious and showed a trend of expansion with time, and there were four types of regions: "continuous increase", "fluctuant increase", "fluctuant decrease" and "continuous decrease". The regional difference of agricultural net carbon sink intensities was obvious and also showed a trend of expansion with time, and there were two types of regions: "continuous increase" and "fluctuant decrease". Based on spatial distribution features, the net carbon sink and net carbon sink intensities of each city were divided into five grades: lowest, lower, medium, higher and highest, from 2000 to 2015. The spatial distribution pattern of lowest net carbon sink area was relatively stable, while the other four grades of areas changed greatly. The highest net carbon sink areas were concentrated in the west of Shandong Province, and the higher net carbon sink areas in the southeast. The spatial distribution pattern of net carbon sink intensities changed greatly, the highest intensity areas of net carbon sink expanded from the middle to the west and southwest of Shandong Province, and the higher intensity areas from the middle to the southeast.
引文
[1] IPCC. Climate change 2013: The physical science basis. Contribution of Working Group Ⅰ to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[M]. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press,2013.
[2] 孙傅,何霄嘉.国际气候变化适应政策发展动态及其对中国的启示[J].中国人口·资源与环境,2014,24(5):1-9.
[3] IPCC. Climate change 2007: Mitigation of climate change contribution of working group iii to the fourth assessment report of the intergovernmental panel on climate change[M].Cambridge: United Kingdom, Cambridge University Press,2007:63-67.
[4] 谢淑娟,匡耀求,黄宁生.中国发展碳汇农业的主要路径与政策建议[J].中国人口·资源与环境,2010,20(12):46-51.
[5] Fearnside P M, Lmbrozio B R. Soil carbon changes from conversion of forest to pasture in Brazilian Amazonia[J].Forest Ecology and Management,1998,108(1):147-166.
[6] US-EPA. Global Anthropogenic non-CO2 greenhouse gas emissions: 1990—2020[R].United States Environmental Protection Agency EPA430-R-06-005,Washington DC,2006.
[7] Wood S, Cowie A. A review of greenhouse gas emission factors for fertilizer production[R].IEA Bioenergy Tas38,2004.
[8] Bhat M G, English B C, Turhollow A F, et al. Energy in synthetic fertilizers and pesticides: Revisited[R]ORNL/Sub/90-99732/2.Oak Ridge National Laboratory, Oak Ridge,Tennessee,1994.
[9] Lal R. Soil carbon sequestration impacts on global climate change and food security[J].Science,2004,304:1623-1627.
[10] Lubowski R N, Plantinga A J, Stavins R N. Land-use change and carbon sinks: Econometric estimation of the carbon sequestration supply function[J].Journal of Environmental Economics and Management,2005,51(2):135-152.
[11] 田云,张俊飚.中国省级区域农业碳排放公平性研究[J].中国人口·资源与环境,2013,23(11):36-44.
[12] 田云,张俊飚,尹朝静,等.中国农业碳排放分布动态与趋势演进:基于31个省(市、区)2002—2011年的面板数据分析[J].中国人口·资源与环境,2014,24(7):91-98.
[13] 田云,张俊飚,吴贤荣,等.中国种植业碳汇盈余动态变化及地区差异分析:基于31个省(市、区)2000—2012年的面板数据[J].自然资源学报,2015,30(11):1885-1895.
[14] 鲁丰先,张艳,秦耀辰,等.中国省级区域碳源汇空间格局研究[J].地理科学进展2013,32(12):1751-1759.
[15] 田云,张俊飚.中国农业生产净碳效应分异研究[J].自然资源学报,2013,28(8):1298-1309.
[16] 陈罗烨,薛领,雪燕.中国农业净碳汇空间集聚与分异[J].生态环境学报,2015,24(11):1777-1784.
[17] 陈罗烨,薛领,雪燕.中国农业净碳汇时空演化特征分析[J].自然资源学报,2016,31(4):596-607.
[18] 李明杰,王国刚,张红日.山东省县域粮食生产格局演变及其影响因素[J].农业现代化研究,2018,39(2):248-255.
[19] 王梁,赵杰,陈守越.山东省农田生态系统碳源、碳汇及其碳足迹变化分析[J].中国农业大学学报,2016,21(7):133-141.
[20] 王梁,赵杰,秦利,等.临沂市农田生态系统碳源/汇时空变化及其影响因素分析[J].水土保持学报, 2015,29(2):183-187.
[21] 祁兴芬.区域农田生态系统正、负服务价值时空变化及影响因素分析:以山东省为例[J].农业现代化研究,2013,34(5):622-626.
[22] 赵其国,钱海燕.低碳经济与农业发展思考[J].生态环境学报,2009,18(5):1609-1614.
[23] 李迎春,林而达,甄晓林.农业温室气体清单方法研究最新进展[J].地球科学进展,2007(10):1076-1080.
[24] 闵继胜,胡浩.中国农业生产温室气体排放量的测算[J].中国人口·资源与环境,2012,22(7):21-27.
[25] 胡向东,王济民.中国畜禽温室气体排放量估算[J].农业工程学报,2010,26(10):247-252.
[26] 马龙,顾玮,魏纯学,等.银川市畜禽养殖温室气体排放估算[J].农业科学研究,2015,36(4):1-7.
[27] 李胜利,金鑫,范学珊,等.反刍动物生产与碳减排措施[J].动物营养学报,2010,22(1):2-9.
[28] 曹国良,张小曳,王丹,等.秸秆露天焚烧排放的TSP等污染物清单[J].农业环境科学学报,2005,24(4):800-804.
[29] 毕于运,高春雨,王亚静,等.中国秸秆资源数量估算[J].农业工程学报,2009,25(12):211-217.
[30] 田云,张俊飚,李波.中国农业碳排放研究:测算、时空比较及脱钩效应[J].资源科学,2012,34(11):2097-2105.
[31] Johnson J M F. Agricultural opportunities to mitigate greenhouse gas emissions[J].Environmental Pollution,2007,150:107-124.
[32] 段华平,张悦,赵建波,等.中国农田生态系统的碳足迹分析[J].水土保持学报,2011,25(5):203-208.
[33] 刘洁,梁红梅,曾业隆,等.基于投入视角的山东省农地利用碳排放与经济发展脱钩研究[J].水土保持通报,2016,36(4):303-308.
[34] 栾健,周玉玺.基于灰色预测模型的山东省粮食灾损量评估及灾害关联度分析[J].农业现代化研究, 2016,37(6):1068-1075.
[35] 栾健,周玉玺.自然灾害对山东省粮食生产影响的实证分析[J].干旱区资源与环境,2016,30(4):127-131.
[36] 山东省农业农村厅.2015年山东省农业和农村经济发展报告[EB/OL].(2016-01-15)[2018-09-01].http://sdnyj.sdny.gov.cn/zwgk/sdny/fzlc/201605/t20160519_407479.html
[37] 韩玮,韩永红,杨沈斌.1961-2011年山东气候资源及气候生产力时空变化特征[J].地理科学进展,2013,32(3):425-434.
[38] 田云,张俊飚,罗小锋.中国种植业净碳效益与经济效益协调性区域比较研究[J].经济地理,2014,34(3):142-148.
[2] 孙傅,何霄嘉.国际气候变化适应政策发展动态及其对中国的启示[J].中国人口·资源与环境,2014,24(5):1-9.
[3] IPCC. Climate change 2007: Mitigation of climate change contribution of working group iii to the fourth assessment report of the intergovernmental panel on climate change[M].Cambridge: United Kingdom, Cambridge University Press,2007:63-67.
[4] 谢淑娟,匡耀求,黄宁生.中国发展碳汇农业的主要路径与政策建议[J].中国人口·资源与环境,2010,20(12):46-51.
[5] Fearnside P M, Lmbrozio B R. Soil carbon changes from conversion of forest to pasture in Brazilian Amazonia[J].Forest Ecology and Management,1998,108(1):147-166.
[6] US-EPA. Global Anthropogenic non-CO2 greenhouse gas emissions: 1990—2020[R].United States Environmental Protection Agency EPA430-R-06-005,Washington DC,2006.
[7] Wood S, Cowie A. A review of greenhouse gas emission factors for fertilizer production[R].IEA Bioenergy Tas38,2004.
[8] Bhat M G, English B C, Turhollow A F, et al. Energy in synthetic fertilizers and pesticides: Revisited[R]ORNL/Sub/90-99732/2.Oak Ridge National Laboratory, Oak Ridge,Tennessee,1994.
[9] Lal R. Soil carbon sequestration impacts on global climate change and food security[J].Science,2004,304:1623-1627.
[10] Lubowski R N, Plantinga A J, Stavins R N. Land-use change and carbon sinks: Econometric estimation of the carbon sequestration supply function[J].Journal of Environmental Economics and Management,2005,51(2):135-152.
[11] 田云,张俊飚.中国省级区域农业碳排放公平性研究[J].中国人口·资源与环境,2013,23(11):36-44.
[12] 田云,张俊飚,尹朝静,等.中国农业碳排放分布动态与趋势演进:基于31个省(市、区)2002—2011年的面板数据分析[J].中国人口·资源与环境,2014,24(7):91-98.
[13] 田云,张俊飚,吴贤荣,等.中国种植业碳汇盈余动态变化及地区差异分析:基于31个省(市、区)2000—2012年的面板数据[J].自然资源学报,2015,30(11):1885-1895.
[14] 鲁丰先,张艳,秦耀辰,等.中国省级区域碳源汇空间格局研究[J].地理科学进展2013,32(12):1751-1759.
[15] 田云,张俊飚.中国农业生产净碳效应分异研究[J].自然资源学报,2013,28(8):1298-1309.
[16] 陈罗烨,薛领,雪燕.中国农业净碳汇空间集聚与分异[J].生态环境学报,2015,24(11):1777-1784.
[17] 陈罗烨,薛领,雪燕.中国农业净碳汇时空演化特征分析[J].自然资源学报,2016,31(4):596-607.
[18] 李明杰,王国刚,张红日.山东省县域粮食生产格局演变及其影响因素[J].农业现代化研究,2018,39(2):248-255.
[19] 王梁,赵杰,陈守越.山东省农田生态系统碳源、碳汇及其碳足迹变化分析[J].中国农业大学学报,2016,21(7):133-141.
[20] 王梁,赵杰,秦利,等.临沂市农田生态系统碳源/汇时空变化及其影响因素分析[J].水土保持学报, 2015,29(2):183-187.
[21] 祁兴芬.区域农田生态系统正、负服务价值时空变化及影响因素分析:以山东省为例[J].农业现代化研究,2013,34(5):622-626.
[22] 赵其国,钱海燕.低碳经济与农业发展思考[J].生态环境学报,2009,18(5):1609-1614.
[23] 李迎春,林而达,甄晓林.农业温室气体清单方法研究最新进展[J].地球科学进展,2007(10):1076-1080.
[24] 闵继胜,胡浩.中国农业生产温室气体排放量的测算[J].中国人口·资源与环境,2012,22(7):21-27.
[25] 胡向东,王济民.中国畜禽温室气体排放量估算[J].农业工程学报,2010,26(10):247-252.
[26] 马龙,顾玮,魏纯学,等.银川市畜禽养殖温室气体排放估算[J].农业科学研究,2015,36(4):1-7.
[27] 李胜利,金鑫,范学珊,等.反刍动物生产与碳减排措施[J].动物营养学报,2010,22(1):2-9.
[28] 曹国良,张小曳,王丹,等.秸秆露天焚烧排放的TSP等污染物清单[J].农业环境科学学报,2005,24(4):800-804.
[29] 毕于运,高春雨,王亚静,等.中国秸秆资源数量估算[J].农业工程学报,2009,25(12):211-217.
[30] 田云,张俊飚,李波.中国农业碳排放研究:测算、时空比较及脱钩效应[J].资源科学,2012,34(11):2097-2105.
[31] Johnson J M F. Agricultural opportunities to mitigate greenhouse gas emissions[J].Environmental Pollution,2007,150:107-124.
[32] 段华平,张悦,赵建波,等.中国农田生态系统的碳足迹分析[J].水土保持学报,2011,25(5):203-208.
[33] 刘洁,梁红梅,曾业隆,等.基于投入视角的山东省农地利用碳排放与经济发展脱钩研究[J].水土保持通报,2016,36(4):303-308.
[34] 栾健,周玉玺.基于灰色预测模型的山东省粮食灾损量评估及灾害关联度分析[J].农业现代化研究, 2016,37(6):1068-1075.
[35] 栾健,周玉玺.自然灾害对山东省粮食生产影响的实证分析[J].干旱区资源与环境,2016,30(4):127-131.
[36] 山东省农业农村厅.2015年山东省农业和农村经济发展报告[EB/OL].(2016-01-15)[2018-09-01].http://sdnyj.sdny.gov.cn/zwgk/sdny/fzlc/201605/t20160519_407479.html
[37] 韩玮,韩永红,杨沈斌.1961-2011年山东气候资源及气候生产力时空变化特征[J].地理科学进展,2013,32(3):425-434.
[38] 田云,张俊飚,罗小锋.中国种植业净碳效益与经济效益协调性区域比较研究[J].经济地理,2014,34(3):142-148.