广东省农业源污染对水环境的影响及其空间分异格局

doi:10.16258/j.cnki.1674-5906.2023.12.012

生态环境学报 ›› 2023, Vol. 32 ›› Issue (12): 2207-2215.DOI: 10.16258/j.cnki.1674-5906.2023.12.012

广东省农业源污染对水环境的影响及其空间分异格局

黄国锋¹(), 贺斌², 谢志宜¹, 刘军¹, 王安侯¹, 廖彤¹, 王博瑾¹, 郝贝贝²^,^*()

1.广东省生态环境监测中心，广东广州 510308
2.广东省科学院生态环境与土壤研究所/华南土壤污染控制与修复国家地方联合工程研究中心/广东省农业环境综合治理重点实验室，广东广州 510650

收稿日期:2023-06-12 出版日期:2023-12-18 发布日期:2024-02-05
通讯作者: *郝贝贝。E-mail: bbhao@soil.gd.cn
作者简介:黄国锋（1974年生），男，高级工程师，研究方向为生态环境监测。E-mail: gdsthjt_huangguofeng@gd.gov.cn
基金资助:
广东省重点领域研发计划项目(2023B0202030001);广东省科学院发展专项资金项目(2023GDASZH-2023010103)

Impact of Agricultural Pollution on Water Environment and Its Spatial Differentiation pattern in Guangdong Province

HUANG Guofeng¹(), HE Bin², XIE Zhiyi¹, LIU Jun¹, WANG Anhou¹, LIAO Tong¹, WANG Bojin¹, HAO Beibei²^,^*()

1. Guangdong Environmental Monitoring Center, Guangzhou 510308, P. R. China
2. National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China/Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management/Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, P. R. China

Received:2023-06-12 Online:2023-12-18 Published:2024-02-05

摘要/Abstract

摘要：

掌握农业农村面源污染现状和排放特征，对开展农业源污染防控、农业可持续发展和农村生态环境改善具有重要意义。基于2022年广东省276个农业农村面源污染控制断面的监测数据，分析广东省珠三角、粤东、粤西和粤北4个区域农村生活污染、种植业流失和养殖业污染对农村水环境的影响，在县域尺度上评价农业农村面源污染状况及空间分异格局。结果表明，1）水质COD、TN、TP、NH₄⁺和NO₃⁻浓度最大值和内梅罗综合污染指数最高值均出现在农村生活污染监测断面，表明全省农村生活源污染对地表水环境污染的贡献最大。2）粤北地区监测断面水质指标浓度和污染指数显著小于其他区域（P<0.001）；珠三角地区生活源和养殖源污染指数（I_i =2.59和1.97）最大，以及种植源和养殖源污染比例（37%和36%）最高；而粤东地区种植源污染指数最大（I_i =1.93），生活源污染比例最高（51%）。3）县域尺度农村生活源污染状况最严重，尤其珠三角和粤东地区重污染和严重污染区县较多，以珠海金湾区（I_i =9.76）、东莞市（I_i=7.29）、潮州饶平县（I_i =6.75）和汕头潮南区（I_i =5.83）污染最突出；养殖源和种植源暂无严重污染等级，重污染区县也相对较少，零星分布在珠三角、粤东和粤西地区。4）全省109个区县，农业源污染等级为清洁、轻度污染、污染、重污染和严重污染的比例依次为20%、43%、20%、15%和2%，清洁区县主要分布在粤北地区，严重污染和重污染区县则主要分布在珠三角和粤东地区。综上，广东省农村生活源对地表水环境的影响较大，珠三角和粤东地区农业源污染状况较粤西严重，粤北污染程度最低。

关键词: 面源污染, 种植业, 养殖业, 生活污染, 空间特征, 来源解析

Abstract:

Understanding the current status and emission characteristics of agricultural and rural non-point source pollution is of great significance for the prevention and control of agricultural non-point source pollution, sustainable agricultural development and improvement of rural ecological environment. Based on the monitoring data of 276 agricultural and rural non-point source pollution control sites in Guangdong Province in 2022, this study analyzed the water environment quality of monitoring sites for rural living pollution, planting loss, and animal pollution in the Pearl River Delta, eastern Guangdong, western Guangdong, and northern Guangdong. And the pollution status of rural living pollution, planting loss, and animal pollution was assessed on a county scale. The main results are as follows. 1) The water quality COD, TN, TP, NH₄⁺, NO₃⁻ concentrations and Nemerow integrated pollution index in the rural living pollution point are the highest, indicating that it contributes the most to the rural surface water pollution in the province. 2) The water concentration and pollution index in northern Guangdong are significantly smaller than those in other regions (P<0.001). The Pearl River Delta has the highest pollution indexes from rural living and animal pollution (I_i =2.59 and 1.97), as well as the pollution proportions from planting loss and animal pollution (37% and 36%). Whereas, the highest value of pollution index from planting sources (I_i =1.93) and the highest proportion of rural living pollution (51%) occur in eastern Guangdong. 3) At the county level, the pollution status of rural living is the most serious, especially in the Pearl River Delta and eastern Guangdong where there are many heavily polluted and seriously polluted counties and districts. For planting loss and animal pollution, there is currently no serious polluted status, and the number of heavily polluted counties is relatively small, scattered in the Pearl River Delta, eastern Guangdong and western Guangdong. 4) Among the 109 counties in the province, the proportions of agricultural non-point source pollution status of clean, lightly polluted, polluted, heavy polluted and serious polluted are 20%, 43%, 20%, 15% and 2% respectively. Generally speaking, the spatial distribution of agricultural and rural non-point source pollution in Guangdong Province is uneven. The pollution status of rural living is more serious than that of planting loss and animal pollution. The Pearl River Delta and eastern Guangdong areas are more serious than western Guangdong, while northern Guangdong has the lowest pollution level.

Key words: non-point source pollution, planting loss, animal pollution, domestic sewage, spatial characteristics, source analysis

中图分类号:

黄国锋, 贺斌, 谢志宜, 刘军, 王安侯, 廖彤, 王博瑾, 郝贝贝. 广东省农业源污染对水环境的影响及其空间分异格局[J]. 生态环境学报, 2023, 32(12): 2207-2215.

HUANG Guofeng, HE Bin, XIE Zhiyi, LIU Jun, WANG Anhou, LIAO Tong, WANG Bojin, HAO Beibei. Impact of Agricultural Pollution on Water Environment and Its Spatial Differentiation pattern in Guangdong Province[J]. Ecology and Environment, 2023, 32(12): 2207-2215.

图/表 8

图1 广东省农业农村面源污染监测点位概况

Figure 1 Distribution of agricultural and rural non-point source pollution monitoring sites in Guangdong Province

表1 农业源污染状况分级标准

Table 1 Classification standards for agricultural non-point source pollution

内梅罗综合污染指数I_i	0‒1.0	1.0‒2.0	2.0‒3.0	3.0‒5.0	≥5.0
分类等级	清洁	轻度污染	污染	重污染	严重污染

表2 不同区域、不同监测断面水质指标和内梅罗综合污染指数（Ii）方差分析结果

Table 2 Two-way ANOVA results of water quality index and Nemerow integrated pollution index (Ii) in different regions and different monitoring sites

水质指标	断面类型			区域			断面类型×区域
水质指标	自由度	F值	P值	自由度	F值	P值	自由度	F值	P值
ρ_(CODCr)	2	2.420	0.089	3	52.488	<0.001	6	4.429	0.000
ρ_(CODMn)	2	0.245	0.783	3	41.793	<0.001	6	2.479	0.022
ρ_(TN)	2	2.228	0.108	3	56.380	<0.001	6	1.812	0.094
ρ_(TP)	2	0.458	0.633	3	35.441	<0.001	6	1.256	0.276
ρ_(NH4+)	2	6.484	0.002	3	18.244	<0.001	6	1.678	0.123
ρ_(NO3−)	2	0.458	0.633	3	35.441	<0.001	6	1.256	0.276
I_i	2	2.724	0.066	3	61.436	<0.001	6	3.564	0.002

图2 广东省不同地区农业农村面源污染监测断面水质比较图右上角表示水质指标浓度在4个区域间存在显著差异，P<0.05；图中不同小写字母表示同一断面类型的水质浓度在4个区域存在显著差异，P<0.05

Figure 2 Comparison of water quality at agricultural and rural non-point source pollution monitoring sites in different regions of Guangdong Province

图3 广东省不同地区农业农村监测断面水质情况

Figure 3 Water quality conditions at agricultural and rural monitoring sites in different regions of Guangdong Province

表3 不同区域、不同类型监测断面TN超标倍数

Table 3 Excessive multiples of TN in different regions and different monitoring sites

断面类型	珠三角	粤东	粤西	粤北
农村生活污染	3.04	2.17	1.84	0.36
种植业流失	1.42	1.39	1.46	0.35
养殖业污染	1.51	1.05	1.52	0.77

图4 广东省不同地区农业农村监测断面污染状况

Figure 4 Pollution status of agricultural and rural monitoring sites in different regions of Guangdong Province

图5 广东省县域农业源污染状况分级

Figure 5 Classification of agricultural source pollution status in counties in Guangdong Province

参考文献 30

[1]	ADU J T, KUMARASAMY M V, 2018. Assessing non-point source pollution models: A review[J]. Polish Journal of Environmental Studies, 27(5): 1913-1922. DOI URL
[2]	BOUWMAN L, GOLDEWIJK K K, VAN DER HOEK K W, et al., 2013. Exploring global changes in nitrogen and phosphorus cycles in agriculture induced by livestock production over the 1900-2050 period[J]. Proceedings of the National Academy of Sciences, 110(52): 20882-20887. DOI URL
[3]	BRYAN B A, JOHN M K, 2011. Designing a policy mix and sequence for mitigating agricultural non-point source pollution in a water supply catchment[J]. Water Resources Management, 25: 875-892. DOI URL
[4]	JIN G, LI Z H, DENG X Z, et al., 2019. An analysis of spatiotemporal patterns in Chinese agricultural productivity between 2004 and 2014[J]. Ecological Indicators, 105: 591-600. DOI URL
[5]	JIN M, REN Z, SHI J P, et al., 2010. Impact of agricultural non-point source pollution in eutrophic-water body of Taihu Lake[J]. Environmental Science & Technology (China), 33(10): 106-119.
[6]	MAO Y P, ZHANG H, TANG W Z, et al., 2021. Net anthropogenic nitrogen and phosphorus inputs in Pearl River Delta region (2008-2016)[J]. Journal of Environmental Management, 282: 111952. DOI URL
[7]	RUDRA R P, MEKONNEN B A, SHUKLA R, et al., 2020. Currents status, challenges, and future directions in identifying critical source areas for non-point source pollution in Canadian conditions[J]. Agriculture, 10(10): 468. DOI URL
[8]	WANG J L, LU J Z, ZHANG Z, et al., 2022. Agricultural non-point sources and their effects on chlorophyll-a in a eutrophic lake over three decades (1985-2020)[J]. Environmental Science and Pollution Research, 29(31): 46634-46648. DOI
[9]	XU K, WANG Y P, SU H, et al., 2013. Effect of land-use changes on nonpoint source pollution in the Xizhi River watershed, Guangdong, China[J]. Hydrological Processe, 27(18): 2557-66. DOI URL
[10]	ZHANG T, YANG Y H, NI J P, et al., 2019. Adoption behavior of cleaner production techniques to control agricultural non-point source pollution: A case study in the Three Gorges Reservoir Area[J]. Journal of Cleaner Production, 223: 897-906. DOI URL
[11]	ZOU L L, LIU Y S, WANG Y S, et al., 2020. Assessment and analysis of agricultural non-point source pollution loads in China: 1978-2017[J]. Journal of Environmental Management, 263: 110400. DOI URL
[12]	曹佳霖, 胡茂川, 贺凯, 等, 2023. 广东省农业面源污染现状及变化的多尺度评价[J]. 生态与农村环境学报, 39(7): 924-933.
	CAO J L, HU M C, HE K, et al., 2023. Multi-scale assessment of agricultural non-point source pollution loadings and its changing characteristics in Guangdong Province[J]. Journal of Ecology and Rural Environment, 39(7): 924-933.
[13]	邓玉娇, 王捷纯, 徐杰, 等, 2022. 广东省植被固碳量时空变化及气象贡献率研究[J]. 生态环境学报, 31(1): 1-8. DOI
	DENG Y J, WANG J C, XU J, et al., 2022. Spatiotemporal variation of vegetation carbon sequestration and its meteorological contribution in Guangdong Province[J]. Ecology and Environmental Sciences, 31(1): 1-8.
[14]	冯亚芬, 俞万源, 雷汝林, 2017. 广东省传统村落空间分布特征及影响因素研究[J]. 地理科学, 37(2): 236-243. DOI
	FENG Y F, YU W Y, LEI R L, 2017. Spatial distribution features and controlling factors of traditional villages in Guangdong Province[J]. Scientia Geographica Sinica, 37(2): 236-243. DOI
[15]	葛小君, 黄斌, 袁再健, 等, 2022. 近20年来广东省农业面源污染负荷时空变化与来源分析[J]. 环境科学, 43(6): 3118-3127.
	GE X J, HUANG B, YUAN Z J, et al., 2022. Temporal and spatial variation characteristics and source analysis of agricultural non-point source pollution load in Guangdong during the past 20 years[J]. Environment Science, 43(6): 3118-3127.
[16]	贺斌, 胡茂川, 2022. 广东省各区县农业面源污染负荷估算及特征分析[J]. 生态环境学报, 31(4): 771-776. DOI
	HE B, HU M C, 2022. Evaluation of agriculture non-point pollution load and its characteristics in all districts and counties of Guangdong[J]. Ecology and Environmental Sciences, 31(4): 771-776.
[17]	林兰稳, 朱立安, 曾清苹, 2020. 广东省农业面源污染时空变化及其防控对策[J]. 生态环境学报, 29(6): 1245-1250. DOI
	LIN L W, ZHU L A, CAO Q P, 2020. Spatial and temporal changes of agricultural non-point source pollution in Guangdong province and its prevention and control measures[J]. Ecology and Environmental Sciences, 29(6): 1245-1250.
[18]	刘丽辉, 辛焕平, 2018. 粮食安全与农业结构调整水平的协整分析——以广东省为例[J]. 中国农业资源与区划, 39(10): 23-29.
	LIU L H, XIN H P, 2018. Co-integration analysis of grain security and agricultural structure adjustment: Taking Guangdong as an example[J]. Chinese Journal of Agricultural Resources and Regional Planning, 39(10): 23-29.
[19]	刘明庆, 陈秋会, 杨育文, 等, 2021. 发展有机农业控制面源污染的实践与对策[J]. 环境与可持续发展, 46(6): 98-104.
	LIU M Q, CHEN Q H, YANG Y W, et al., 2021. Practice and countermeasures of developing organic agriculture to control non-point source pollution[J]. Environment and Sustainable Development, 46(6): 98-104.
[20]	丘雯文, 钟涨宝, 原春辉, 等, 2018. 中国农业面源污染排放的空间差异及其动态演变[J]. 中国农业大学学报, 23(1): 152-163.
	QIU W W, ZHONG Z B, YUAN C H, et al., 2018. Spatial differences and dynamic evolution of agricultural non-point source pollution in China[J]. ournal of China Agricultural University, 23(1): 152-163.
[21]	宋欢, 2013. 广东农村生活环境分析及对策研究[J]. 广东农业科学, 40(8): 161-164.
	SONG H, 2013. Analysis and countermeasures of Guangdong rural living environment[J]. Guangdong Agricultural Sciences, 40(8): 161-164.
[22]	王楠, 郝贝贝, 张思毅, 等, 2023. 1991-2021年广东省农业面源污染源特征分析[J]. 农业工程学报, 39(9): 190-200.
	WANG N, HAO B B, ZHANG S Y, et al., 2023. Agricultural non-point source pollution in Guangdong Province of China from 1991 to 2021[J]. Transactions of the Chinese Society of Agricultural Engineering, 39(9): 190-200.
[23]	夏丽佳, 余慕琴, 严萌, 等, 2021. 珠三角四市农业面源污染源解析与评价[J]. 人民珠江, 42(5): 35-41.
	XIA L J, YU M Q, YAN M, et al., 2021. Analysis and evaluation of agricultural non-point source pollution sources in four cities in the Pearl River Delta[J]. Pearl River, 42(5): 35-41.
[24]	熊凡, 林晓君, 曾经文, 等, 2018. 广州市农业面源污染概况及特征分析[J]. 广东农业科学, 45(3): 81-87.
	XIONG F, LIN X J, ZENG J W, et al., 2018. Overview and feature analysis of agricultural non-point source pollution in Guangzhou[J]. Guangdong Agricultural Sciences, 45(3): 81-87.
[25]	杨滨键, 尚杰, 于法稳, 2019. 农业面源污染防治的难点、问题及对策[J]. 中国生态农业学报, 27(2): 236-245.
	YANG B J, SHANG J, YU F W, 2019. Difficulty, problems and countermeasures of agricultural non-point sources pollution control in China[J]. Chinese Journal of Eco-Agriculture, 27(2): 236-245.
[26]	杨林章, 冯彦房, 施卫明, 等, 2013. 我国农业面源污染治理技术研究进展[J]. 中国生态农业学报, 21(1): 96-101.
	YANG L Z, FENG Y F, SHI W M, et al., 2013. Review of the advances and development trends in agricultural non-point source pollution control in China[J]. Chinese Journal of Eco-Agriculture, 21(1): 96-101.
[27]	杨林章, 吴永红, 2018. 农业面源污染防控与水环境保护[J]. 中国科学院院刊, 33(2): 168-176.
	YANG L Z, WU Y H, 2018. Prevention and control of agricultural non-point source pollution and aquatic environmental protection[J]. Bulletin of Chinese Academy of Sciences, 33(2): 168-176.
[28]	叶延琼, 章家恩, 李逸勉, 等, 2013. 基于GIS的广东省农业面源污染的时空分异研究[J]. 农业环境科学学报, 32(2): 369-377.
	YE Y Q, ZHANG J E, LI Y M, et al., 2013. Spatial-temporal variation of agricultural non-point source pollution based on GIS technology in Guangdong province, China[J]. Journal of Agro-Environment Science, 32(2): 369-377.
[29]	中国环境监测总站, 2022. 农村环境质量综合评价技术规定(修订征求意见稿)[S].
	China National Environmental Monitoring Centre,2022. Technical provisions on comprehensive assessment of rural environmental quality (Revised Draft for Comments)[S].
[30]	中国国家环境保护总局,2002. 地表水环境质量标准: GB 3838—2002[S].
	PRC State Environmental Protection Administration,2022. Surface water environmental quality standards: GB 3838—2002[S].

广东省农业源污染对水环境的影响及其空间分异格局

Impact of Agricultural Pollution on Water Environment and Its Spatial Differentiation pattern in Guangdong Province

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 30

相关文章 6

编辑推荐

Metrics

本文评价

[1]	钱海铭, 张运林, 李娜, 王玮佳, 孙晓, 张毅博, 施坤, 冯胜, 高阳辉. 典型降雨过程中河流饮用水源地水质高频监测研究[J]. 生态环境学报, 2023, 32(3): 579-589.
[2]	李姝亭, 胡冠九, 罗小三. 大气环境中全（多）氟烷基化合物（PFASs）的来源、分布及健康风险研究进展[J]. 生态环境学报, 2023, 32(12): 2103-2114.
[3]	吴昊平, 秦红杰, 贺斌, 尤毅, 陈金峰, 邹春萍, 杨思雨, 郝贝贝. 基于碳中和的农业面源污染治理模式发展态势刍议[J]. 生态环境学报, 2022, 31(9): 1919-1926.
[4]	张桂莲. 基于遥感估算的上海城市森林碳储量空间分布特征[J]. 生态环境学报, 2021, 30(9): 1777-1786.
[5]	石慧斌, 黄艺, 程馨, 李婷, 何敏, 王进进. 成都市冬季PM_2.5中碳组分污染特征及来源解析[J]. 生态环境学报, 2021, 30(7): 1420-1427.
[6]	他维媛, 康桢, 孟昭君, 金盛华, 杨幸, 郭龙飞, 赵东旭, 张馨. 秦岭典型停产关闭锌冶炼企业场地土壤重金属污染特征研究[J]. 生态环境学报, 2021, 30(7): 1513-1521.