近30年京津冀电镀场地时空演变特征及趋势预测

doi:10.16258/j.cnki.1674-5906.2023.01.020

生态环境学报 ›› 2023, Vol. 32 ›› Issue (1): 183-194.DOI: 10.16258/j.cnki.1674-5906.2023.01.020

近30年京津冀电镀场地时空演变特征及趋势预测

孙正¹^,²(), 曹亚非³, 王德彩², 刘峰¹^,⁴, 宋效东¹, 张甘霖¹^,⁴^,⁵, 吴华勇¹^,⁴^,^*()

1.中国科学院南京土壤研究所/土壤与农业可持续发展国家重点实验室，江苏南京 210008
2.河南农业大学林学院，河南郑州 450003
3.《江苏农业科学》杂志社，江苏南京 210014
4.中国科学院大学，北京 100049
5.中国科学院南京地理与湖泊研究所/中国科学院流域地理学重点实验室，江苏南京 210008

收稿日期:2022-10-07 出版日期:2023-01-18 发布日期:2023-04-06
通讯作者: *吴华勇，E-mail: hywu@issas.ac.cn
作者简介:孙正（1998年生），男，硕士研究生，主要从事资源环境遥感与空间分析研究。E-mail: zsun@issas.ac.cn
基金资助:
国家重点研发计划项目(2018YFC1800104);国家重点研发计划项目(2018YFC1801806)

Spatial-temporal Evolution Characteristics and Trend Prediction of Electroplating Sites in the Beijing-Tianjin-Hebei Region over the Past 30 Years

SUN Zheng¹^,²(), CAO Yafei³, WANG Decai², LIU Feng¹^,⁴, SONG Xiaodong¹, ZHANG Ganlin¹^,⁴^,⁵, WU Huayong¹^,⁴^,^*()

1. State Key Laboratory of Soil and Sustainable Agriculture/Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, P. R. China
2. College of forestry, Henan Agricultural University, Zhengzhou 450003, P. R. China
3. Periodical Office of Jiangsu Agricultural Science, Nanjing 210014, P. R. China
4. University of Chinese Academy of Sciences, Beijing 100049, P. R. China
5. Key Laboratory of Watershed Geographic Science/Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China

Received:2022-10-07 Online:2023-01-18 Published:2023-04-06

摘要/Abstract

摘要：

电镀场地时空分布深刻地影响电镀场地的重金属等污染物的排放特征，进而影响生态环境和人体健康。为解析和预测电镀场地时空分布格局，采用统计分析、核密度估计、时序模型等，分析了1990—2020年京津冀电镀场地的时空演变特征及其驱动因子，预测了2025年电镀场地数量变化的关键驱动因子及场地数量的空间分布格局。发现1990—2005年京津冀电镀场地数量空间分布格局的变化较大，场地数量增加了1.8倍，从主要集中于天津市和北京市，明显发展至周边多个地区；2005—2020年电镀场地数量空间分布格局的变化较小，场地数量增加了0.8倍，形成了以天津市最多、环绕天津市的城市次之、其他城市较少的空间分布格局；京津冀电镀场地数量的变化基本符合“S”型增长模式，经历了逐步增长期（1990—2001年）、快速增长期（2002—2016年）和平稳期（2017—2020年）；天津市对京津冀电镀场地数量增长模式的贡献较大。相关分析显示，地区生产总值、第二产业总产值、常住人口数量等驱动因子与场地数量呈极显著正相关关系，基于打分量化的相关政策因素与场地数量呈极显著负相关关系。发现逐步增长期和平稳期的主要驱动因子为经济发展速度和政策因素，快速增长期的主要驱动因子为经济发展速度。构建的时序模型较好地预测了2025年京津冀电镀场地数量变化的关键驱动因子和场地数量的空间分布格局。预测结果显示，与2020年相比，2025年电镀场地数量空间分布格局的变化较小，场地数量预计将减少5%。研究结果对电镀场地污染预测与监管、生态环境宏观政策及电镀行业发展规划的制定有重要意义。

关键词: 电镀场地, 时空分布, 政策量化, 时序模型, 京津冀地区

Abstract:

Spatial-temporal distribution of electroplating sites at regional and national scales impacts the release of pollutants, including heavy metals from electroplating sites, which further influences the eco-environment and human health. Statistical analyses and kernel density estimation were used to analyze the spatial-temporal distribution of electroplating sites and the driving factors in the Beijing-Tianjin-Hebei region from 1990 to 2020. Time series models were used to predict the spatial distribution of the driving factors and the number of electroplating sites in the region in 2025. The spatial distribution pattern of electroplating sites in the region changed greatly during 1990-2005 and the number of electroplating sites increased by 1.8 times. The electroplating sites which were mainly distributed in Tianjin and Beijing notably increased around the two cities during this period. The spatial distribution pattern of electroplating sites in the region changed slightly during 2005-2020 and the number of electroplating sites increased by 0.8 times. In terms of the number of electroplating sites, Tianjin had the largest number, followed by the surrounding cities and other cities. Temporal changes in the number of electroplating sites followed a S-type growth curve. The 1990-2020 period was divided into a gradual growth period (1990-2001), a rapid growth period (2002-2016) and a steady period (2017-2020). The number of electroplating sites showed significant positive correlations with the driving factors, including gross regional product, total output value of the secondary sector of the economy, resident population, and significant negative correlations with quantified policy factors. The gradual growth period and the steady period were found to be primarily driven by the rate of economic growth and policy factors, whereas the rapid growth period was found to be primarily driven by the rate of economic growth. The established time series models well predicted the spatial distribution of the key driving factors and the number of electroplating sites in the region in 2025. It was projected that the spatial distribution pattern of electroplating sites in the region would change slightly, and the number of sites would decrease by 5% from 2020 to 2025. The findings in this study are important to predict and supervise pollution conditions of electroplating sites, and to formulate macro-policies for eco-environment and development plans for the electroplating industry.

Key words: electroplating industry, spatial-temporal distribution, policy factor quantification, time series model, Beijing-Tianjin-Hebei region

中图分类号:

S158.5
X825

孙正, 曹亚非, 王德彩, 刘峰, 宋效东, 张甘霖, 吴华勇. 近30年京津冀电镀场地时空演变特征及趋势预测[J]. 生态环境学报, 2023, 32(1): 183-194.

SUN Zheng, CAO Yafei, WANG Decai, LIU Feng, SONG Xiaodong, ZHANG Ganlin, WU Huayong. Spatial-temporal Evolution Characteristics and Trend Prediction of Electroplating Sites in the Beijing-Tianjin-Hebei Region over the Past 30 Years[J]. Ecology and Environment, 2023, 32(1): 183-194.

图/表 14

图1 研究区位置

Figure 1 Location of study area

表1 京津冀地区政策因素量化打分规则

Table 1 Quantitative scoring rules for policy factors in the Beijing-Tianjin-Hebei region

政策因素类型及层级	分值
国家级法律法规	±4
国家级规划纲要	±3
省级法律法规	±2
省级规划纲要及市级相关政策	±1

表2 ARIMA模型中的参数汇总

Table 2 Summary of parameters in the ARIMA model

城市	地区生产总值			第二产业总产值
城市	p	d	q	p	d	q
北京	0	2	0	0	2	2
天津	0	2	0	1	1	0
石家庄	0	1	0	0	1	1
承德	0	1	1	0	1	1
张家口	1	1	0	2	1	0
秦皇岛	0	2	1	0	1	0
唐山	0	1	0	1	1	0
廊坊	0	2	1	1	1	0
保定	0	1	0	1	1	0
沧州	0	1	0	0	1	1
衡水	0	1	0	0	1	1
邢台	2	2	1	0	1	1
邯郸	1	1	0	1	1	0

表3 1990—2020年以5 a为时间节点统计的京津冀地区电镀场地数量及其相对增长率

Table 3 The number and relative growth rate of electroplating sites in the Beijing-Tianjin-Hebei region from 1990 to 2020

年份	1990	1995	2000	2005	2010	2015	2020
电镀场地数量	154	190	259	427	562	681	759
相对增长率/%	—	23.38	36.32	64.86	31.62	21.17	11.45

图2 1990—2020年京津冀地区电镀场地数量时空分布

Figure 2 Spatial-temporal distribution of the number of electroplating sites in the Beijing-Tianjin-Hebei region from 1990 to 2020

图3 1990—2020年京津冀地区（a）及各城市（b）电镀场地数量变化

Figure 3 Changes in the number of electroplating sites in the Beijing-Tianjin-Hebei region from 1990 to 2020

图4 1990—2020年京津冀地区电镀场地核密度时空分布

Figure 4 Spatial-temporal distribution of kernel density of electroplating sites in the Beijing-Tianjin-Hebei region from 1990 to 2020

图5 1990—2020年京津冀地区各城市电镀场地数量与驱动因子相关性矩阵 *、**及***分别表示在0.05、0.01及0.001水平上差异显著

Figure 5 Correlation matrix between the number of electroplating sites and driving factors for each city in the Beijing-Tianjin-Hebei region from 1990 to 2020

图6 1990—2020年京津冀地区生产总值（a）和第二产业总产值（b）

Figure 6 Gross regional product (a) and total output value of the secondary sector of the economy (b) of the Beijing-Tianjin-Hebei region from 1990 to 2020

图7 2025年京津冀地区电镀场地数量变化驱动因子的预测结果

Figure 7 Predicted results of factors driving the changes of the number of electroplating sites in the Beijing-Tianjin-Hebei region in 2025

图8 2000—2020年京津冀地区常住人口数量（a）及政策因素打分累加值（b）

Figure 8 Resident population (a) and policy factors (b) of the Beijing-Tianjin-Hebei region from 2000 to 2020

表4 京津冀地区各城市常住人口数量及政策因素拟合平均相对误差分布

Table 4 Mean relative error (MRE) for modelling resident population and policy factors in the Beijing-Tianjin-Hebei region

地区	平均相对误差
地区	常住人口	政策因素
北京	0.098	0.082
天津	0.091
石家庄	0.052
承德	0.078
张家口	0.084
秦皇岛	0.091
唐山	0.095
廊坊	0.099
保定	0.097
沧州	0.068
衡水	0.071
邢台	0.085
邯郸	0.081

图9 1990—2020年及2000—2020年京津冀地区电镀场地数量观测值与拟合值

Figure 9 Observed and predicted number of electroplating sites in the Beijing-Tianjin-Hebei region from 1990 to 2020 or from 2000 to 2020

图10 2025年京津冀地区电镀场地数量（a）及变化（b）空间分布预测结果

Figure 10 The predicted number (a) and its changes (b) of electroplating sites in the Beijing-Tianjin-Hebei region in 2025

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近30年京津冀电镀场地时空演变特征及趋势预测

Spatial-temporal Evolution Characteristics and Trend Prediction of Electroplating Sites in the Beijing-Tianjin-Hebei Region over the Past 30 Years

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