Methodology

Clustering Degree of MWPIIs

Location Entropy (LE) is a typical index for measuring the degree of regional industrial clustering. This index can identify the degree of industrial clustering of MWPIIs in the region. The larger the LE value is, the higher the degree of industrial clustering is. When the LE value is greater than 1, it indicates that the industrial clustering degree of the industry in a certain region exceeds that of the whole region, and it belongs to the regional specialized sector. Otherwise, the industrial clustering degree of the industry is low. The ISV of manufacturing industries in the YRD is used as the calculation index to calculate the LE of regional industries, and the calculation results in 2020 are shown in Table 1.

Fig. 3.

Number of manufacturing enterprises of three provinces and one municipality in the YRD in 2020.

Fig. 4.

Manufacturing wastewater discharge, GISV and Intensity of wastewater discharge from manufacturing industry in the YRD in 2020.

Type Identification of MWPIIs

Scholars have used different standards to provide different definition methods for WPIIs: comparative industry pollution reduction cost [20], comparative industry pollution emission intensity method, that is, the pollution emission per unit of output value [21–24], comparative industry pollution emission [25–27]. Some scholars comprehensively compare pollution emission intensity and pollution emission scale [28–30], and some scholars directly refer to the key polluting industries promulgated in the First National Pollution Source Survey Plan [31–33]. In this paper, the pollution-intensive manufacturing industry is defined by measuring the emission scale of water pollutant emissions (COD and AN) of an industry. The total discharge of water pollutants COD and AN will be calculated and represent water pollution emissions of the manufacturing industry.

Table 1.

The ISV and LE of 31 manufacturing industries in the YRD including three provinces and one municipality in 2020 (ISV unit: RMB billion Yuan)

Code Number	Jiangsu Province		Zhejiang Province		Anhui Province		Shanghai Municipality		The YRD
	ISV	LE	ISV	LE	ISV	LE	ISV	LE	ISV	LE
1	287.48	0.48	97.26	0.26	212.77	1.20	43.38	0.23	640.89	0.48
2	85.91	0.36	60.11	0.41	54.53	0.78	83.90	1.11	284.45	0.54
3	64.17	0.35	44.59	0.40	53.73	1.00	13.36	0.23	175.84	0.43
4	86.13	0.61	93.61	1.09	42.84	1.04	106.12	2.37	328.70	1.05
5	429.63	1.48	411.78	2.32	67.79	0.80	23.77	0.26	932.97	1.45
6	175.18	1.02	189.37	1.81	61.20	1.22	28.55	0.52	454.30	1.19
7	22.44	0.18	80.09	1.05	30.17	0.82	12.70	0.32	145.39	0.52
8	72.81	0.68	46.55	0.71	41.57	1.32	4.36	0.13	165.29	0.69
9	35.08	0.40	104.37	1.95	23.78	0.93	30.70	1.10	193.92	1.00
10	134.46	0.83	146.14	1.47	35.38	0.74	29.48	0.57	345.46	0.96
11	70.33	0.86	52.30	1.04	37.38	1.55	21.18	0.81	181.19	0.99
12	125.29	0.83	133.01	1.43	34.04	0.76	65.23	1.35	357.57	1.06
13	155.44	0.30	197.12	0.62	58.80	0.39	109.78	0.67	521.14	0.45
14	865.97	1.10	559.86	1.16	218.39	0.94	332.61	1.33	1976.83	1.13
15	362.20	1.17	179.72	0.95	90.49	1.00	101.44	1.03	733.84	1.07
16	211.79	2.15	276.96	4.58	10.28	0.35	2.02	0.06	501.04	2.28
17	333.89	1.06	288.14	1.49	137.58	1.48	100.16	1.00	859.77	1.22
18	450.20	0.63	375.92	0.86	301.59	1.43	83.88	0.37	1211.59	0.76
19	983.38	1.09	200.08	0.36	212.83	0.80	167.36	0.58	1563.65	0.78
20	418.74	0.63	275.41	0.67	246.95	1.25	42.29	0.20	983.39	0.66
21	634.71	1.32	352.74	1.20	148.61	1.05	107.46	0.70	1243.52	1.16
22	846.32	1.67	563.13	1.81	166.33	1.11	340.25	2.10	1916.03	1.70
23	604.05	1.45	239.25	0.93	101.81	0.83	159.11	1.20	1104.23	1.19
24	701.60	0.70	533.19	0.86	279.40	0.94	772.78	2.41	2286.97	1.02
25	272.83	1.43	82.39	0.70	16.36	0.29	88.29	1.45	459.86	1.08
26	1346.71	1.58	865.63	1.65	379.83	1.51	262.06	0.96	2854.22	1.50
27	1845.01	1.21	617.27	0.66	348.80	0.78	563.33	1.16	3374.40	0.99
28	187.97	1.86	125.42	2.03	14.88	0.50	44.71	1.39	372.97	1.66
29	13.94	0.47	24.01	1.31	9.33	1.06	5.08	0.53	52.36	0.79
30	31.19	0.43	35.79	0.81	45.18	2.12	4.79	0.21	116.96	0.72
31	2.19	0.18	14.52	1.92	5.56	1.53	26.75	6.81	49.02	1.78

[i] Note: Manufacturing Industry Code Number. 1~31 presents each manufacturing industry see APPENDIX 1.

S_ij represents the industry water pollution emissions scale index of manufacturing industry i in region j. Its formula is as Formula (1):

(1)

Sij=Aij/∑i=1nAij∑j=1mAij/∑j=1m∑i=1nAij

Fig. 5.

Type identification basis of regional MWPIIs.

In Formula (1), the A_ij represents water pollution emission of manufacturing industry i in region j, and ∑i=1nAij represents total water pollution emissions of all manufacturing industries in region j. ∑j=1mAij represents total water pollution emissions of the manufacturing industry i in China. ∑j=1m∑i=1nAij represents the total water pollution emissions of all manufacturing industries in China. So, S_ij > 1 means the scale of water pollution emissions in region j is bigger than the national average. S_ij = 1 means the scale of water pollution emissions in region j is equal to the national average. S_ij < 1 means the scale of water pollution emissions in region j is smaller than the national average.

I_ij represents the water pollution emissions intensity index of manufacturing industry i in region j. Its formula is as Formula (2):

(2)

Iij=Aij/Bij∑j=1mAij/∑j=1mBij

In Formula (2), the B_ij is ISV of manufacturing industry i in region j, and ∑j=1mBij is total ISV of manufacturing industry j in China. So, I_ij > 1 means the intensity of water pollution emissions in region j is higher than the national average. S_ij = 1 means the intensity of water pollution emissions in region j is equal to the national average. S_ij < 1 means the intensity of water pollution emissions in region j is lower than the national average.

In this paper, the scale index and intensity index of water pollution emission are used as the vertical and horizontal coordinates respectively to form the four-classification type identification basis of MWPIIs as shown in Fig. 5.

(1) Super-intensive MWPIIs. When S_ij ≥ 1, I_ij ≥ 1, it indicates that the manufacturing industry in this region has the highest water pollution emission intensity, which is higher than the national average.

(2) Large-scale MWPIIs. When S_ij ≥ 1, I_ij < 1, it indicates that the scale of water pollution emission of manufacturing industry i in region j is bigger than the national average, but its intensity of water pollution is lower than the national average.

(3) Intensity MWPIIs. When S_ij < 1, I_ij ≥ 1, it indicates that the scale of water pollution emission of manufacturing industry i in region j is smaller than the national average, but its intensity of water pollution is higher than the national average.

(4) Weak MWPIIs. When S_ij < 1, I_ij < 1, it indicates that the manufacturing industry in this region has the lowest water pollution emission intensity, which is lower than the national average.

Data Acquisition

In this paper, the scale index and intensity index of water pollution [34] are used to identify the types of MWPIIs. In the selection of indicators, in Formula (1) requests total discharge of water pollutants COD and ammonia nitrogen as the indicator of water pollution emission, and in Formula (2) requests GISV and ISV as the indicator of each manufacturing industry output. According to the availability of environmental data, this study uses GISV and ISV in 2018 and 2020 from China Industrial Statistical Yearbook (2019, 2021) and from the Statistical Yearbook (2019, 2021) of three provinces and one municipality in the YRD. The amount of water pollutants (COD and AN) of 31 manufacturing industries in 2018 and 2020 was disclosed by the Ministry of Ecology and Environment of China on request. The Department of Ecology and Environment and Bureau of Ecology and Environment of three provinces and one municipality in the YRD disclosed the amounts of water pollutants of 31 manufacturing industries. The data of GISV and ISV of 31 manufacturing industries are derived from the Statistical Yearbook (2019, 2021) of three provinces and one municipality. Therefore, the calculation results are true and effective.

Status Quo of the Clustering Degree of MWPIIs

The ISV of the manufacturing industry in the YRD reached RMB 26387.73 billion yuan in 2020, accounting for approximately 27% of China’s total manufacturing industry. This proportion remained unchanged from 2018. However, there were notable spatial-temporal evolution observed in the industrial clustering patterns within this region. Industrial clustering refers to an economic phenomenon where various production factors are concentrated in specific spatial layouts within an industry. Based on statistics and calculations, it is evident that the top ten manufacturing industries with high LE exhibited significant overlap in 2018 Vs. 2020 across the three provinces and one city within the YRD region. Nevertheless, there was a certain degree of dislocation observed in terms of industrial clustering development among these regions (Table 2).

To summarize, the manufacturing industries in the YRD region with high LE include the Manufacture of Chemical Fibers, Repair Service of Metal Products, Machinery and Equipment, Manufacture of General Purpose Machinery, Manufacture of Measuring Instruments and Machinery, and Manufacture of Electrical Machinery and Apparatus. These industries are classified as ten key special remediation industries in the “Action Plan for Water Pollution Prevention and Control” issued in 2019, which identifies paper making, coking, nitrogen fertilizer production, non-ferrous metals processing, printing and dyeing, agricultural and by-product food processing, raw material manufacturing, leather production, pesticide manufacturing, and electroplating as major contributors to water pollution. Therefore, it can be observed that the manufacturing industries with high LE calculated in this study mainly belong to these aforementioned sectors.

Spatial-Temporal Evolution of Manufacturing MWPIIs

In the context of temporal evolution, the MWPIIs in the region have undergone transformations in 2018 Vs. in 2020 due to the issuance of the “Overall Plan for the Integrated Development of Ecological Green Demonstration Zone in the Yangtze River Delta” in 2019. The S_ij and I_ij values of MWPIIs present an overall downward trend from 2018 to 2020 (Fig. 6 and 7). Moreover, high S_ij values are observed in the MWPIIs related to the Utilization of Waste Resources, Manufacture of Textiles, Manufacture of Electrical Machinery and Apparatus, Manufacture of Metal Products, Manufacture of Leather, Fur, Feather, and Related Products and Footwear, Smelting and Pressing of Ferrous Metals. On the other hand, MWPIIs with high I_ij values primarily focus on industries such as the Utilization of Waste Resources, Manufacture of Leather, Fur, Feather, and Related Products and Footwear, Manufacture of Liquor, Beverages and Refined Tea, Smelting and Pressing of Ferrous Metals, Manufacture of Non-metallic Mineral Products, Processing of Timber, Manufacture of Wood, Bamboo, Rattan, Palm, and Straw Products.

Fig. 6.

The S_ij of MWPIIs in the YRD in 2018 Vs. 2020. Note: Number meaning is manufacturing industry code number (see APPENDIX 1).

Fig. 7.

The I_ij of MWPIIs in the YRD in 2018 Vs. 2020. Note: Number meaning is manufacturing industry code number (see APPENDIX 1).

Among these MWPIIs with high S_ij and I_ij, it can be observed that, apart from 30 Utilization of Waste Resources which is the manufacture to deal with wastewater in city, Manufacture of Liquor, Beverages and Refined Tea, Manufacture of Textile, Manufacture of Leather, Fur, Feather, and Related Products and Footwear, Processing of Timber, Manufacture of Wood, Bamboo, Rattan, Palm and Straw Products, Smelting and Pressing of Ferrous Metals, and Manufacture of Electrical Machinery and Apparatus also fall under the category of MWPIIs with high S_ij and I_ij. However, the Manufacture of Electrical Machinery and Apparatus stands out as the MWPIIs with the highest S_ij values. Additionally, the ISV for this manufacturing industry is also the highest among all manufacturing GISVs in the YRD region (Fig. 8.).

Fig. 8.

The ISV and ISV proportion of MWPIIs with high S_ij and I_ij in the YRD in 2018 Vs. 2020. Note: Number meaning is manufacturing industry code number (see APPENDIX 1).

Fig. 9.

Type identification of regional WPIIs in the YRD in 2018. Note: Number meaning is manufacturing industry code number (see APPENDIX 1).

Therefore, from a temporal comparison perspective, the trend of water pollution caused by MWPIIs in the YRD region is characterized by both high intensity and large scale (Fig. 9 and 10). In 2020, there were more MWPIIs with high S_ij and I_ij compared to those in 2018. Moreover, pure high-intensity MWPIIs disappeared in 2020 and transformed into double-high MWPIIs.

Fig. 10.

Type identification of regional MWPIIs in the YRD in 2020. Note: Number meaning is manufacturing industry code number (see APPENDIX 1).

Fig. 11.

The S_ij values evolution of the three provinces and municipality in the YRD in 2018 Vs. 2020. Note: Number meaning is manufacturing industry code number (see APPENDIX 1).

In terms of spatial and temporal evolution, considering the scale index, significant changes can be observed among the three provinces and one municipality. Specifically, the S_ij value for Shanghai municipality exhibited a considerable decrease from 2018 to 2020, with the value in 2020 being lower than that in 2018. On the other hand, the S_ij values for the remaining three provinces remained relatively stable (Fig. 11). However, it is worth noting that despite this decline, Shanghai municipality still maintained a higher S_ij value compared to others. Furthermore, in 2020, within the YRD, Anhui province demonstrated the highest S_ij value for 30 Utilization of Waste Resource, the ISV of which accounted for only a small proportion (1.3%) of manufacturing industries in Anhui province. Additionally, it should be highlighted that Zhejiang province’s manufacturing sector specifically related to the Manufacture of Textile continued to exhibit higher S_ij values compared to its other manufacturing industries.

In contrast, considering the intensity index, it can be observed that the I_ij of Shanghai municipality exhibited a slight increase in 2020 compared to 2018. The elevated I_ij primarily focus on the Manufacture of Leather, Fur, Feather, and Related Products and Footwear, Manufacture of Rubber and Plastics Products, 18 Manufacture of Non-metallic Mineral Products, Smelting and Pressing of Ferrous Metals, Utilization of Waste Resources, Repair Service of Metal Products, Machinery and Equipment. Similarly, Anhui province demonstrated a similar trend as Shanghai municipality (Fig. 12). It is noteworthy that three provinces and one municipality experienced changes in their I_ij value within the region; regardless of the specific province or municipality considered, high S_ij or high I_ij values were consistently associated with the industry related to 30 Utilization of Waste Resource.

Fig. 12.

The I_ij values evolution of the three provinces and municipality in the YRD in 2018 Vs. 2020. Note: Number meaning is manufacturing industry code number (see APPENDIX 1).

Fig. 13.

The total proportion of ISV for the key MWPIIs in three provinces and one municipality of the YRD.

Meanwhile, based on the clustering degree of MWPIIs and the type identification of regional MWPIIs, the key MWPIIs identified in the region include five manufactures with industrial code numbers 5, 7, 21, 26, and 30. Furthermore, it is evident from the spatial distribution map that the total proportion of ISV for these key MWPIIs in three provinces and one municipality has increased from 2018 to 2020, except for Anhui province (Fig. 13). Jiangsu province and Anhui province act as upstream provinces in the YRD, where water pollutants from their key MWPIIs continue to pose a threat to Zhejiang province and Shanghai municipality downstream.

Suggestions for the Development Path of MWPIIs in the YRD

As the impact of environmental regulation on PIIs has both “crowding-out effect” and “innovation compensation effect”, there may be a nonlinear relationship between environmental regulation and pollution-intensive industry transfer [35]. Therefore, based on the analysis of spatial-temporal evolution of MWPIIs in the YRD, there are some suggestions for the development path of MWPIIs in the region.

Strengthening Environmental Regulation of MWPIIs

For manufactures with regional features, such as the Manufacture of Textile and Utilization of Waste Resources, which also belong to Super-intensive MWPIIs, strengthening the environmental regulation of MWPIIs can reduce the water pollution emissions of regional MWPIIs through incentive measures. The previous research results show that if a regional government implements stricter environmental supervision, regulation, and investment policies, it will greatly improve the production technology and product production process of the manufacturing industry, thus enhancing competitiveness. Especially for MWPIIs, strict regulatory policies can promote their improvement and upgrading of product standard system [36]. Therefore, the government should formulate positive and reasonable environmental regulation policies, classify MWPIIs into four types from intensity and scale, formulate environmental regulation policies according to different emission scales, and intensity of the manufacturing industry, and determine environmental standards and norms, even put the different type MWPIIs into industrial parks. At the same time, it is necessary to formulate corresponding fiscal policies, financial policies, talent policies, and other policies [37] to promote the investment in innovation resources for MWPIIs green updating and support technological innovation to reduce the average water pollutant emissions of the manufacturing industry. For Super-intensive and Intensity MWPIIs, the way of compulsory orders should be changed, but innovation support for MWPIIs should be increased through tax policies, and various means such as pollutant discharge charges, pollutant discharge rights trading, and emission reduction subsidies [38] should be used to stimulate the innovation enthusiasm of reducing water pollution emissions.

Discussion for an Integrated Strategy of Environmental Governance in the YRD

The implementation of independent control measures alone, without identifying the water pollution manufacturing industry in the region, falls significantly short. It is imperative to enhance the overall effectiveness of water environmental governance in the YRD through inter-governmental collaborative efforts under the Action Plan for Water Pollution Prevention and Control and the Overall Plan for the Demonstration Zone of Ecological and Green Integrated Development in the YRD in 2019.

Firstly, with regards to urban sewage treatment plants, where the total discharge of water pollutants accounts for nearly 40%, China has initiated a proposal to revise the national ‘Urban Sewage Treatment Plant Emissions’ standard (GB18918–2002) in 2022, focusing on enhancing the discharge concentration standards. However, Anhui Province, situated in the upper reaches of Taihu Lake Basin in the YRD, only issued the discharge limits standard (DB34/2710–2016) of major water pollutants in Chaohu Lake Basin for urban sewage treatment plants and industrial industries. Furthermore, there have been no established discharge limits for major water pollutants applicable to urban sewage treatment plants and industrial industries within Anhui province. The proposed discharge standards for major water pollutants concerning urban sewage treatment plants and industrial industries in Anhui Province’s Huaihe River Basin (draft for comments) were introduced in 2019; however, they have not yet been implemented despite covering a broader administrative scope. Meanwhile, Zhejiang Province and Shanghai municipality revised and released new discharge standards for main water pollutants applicable to polluted water treatment plants which are standard DB33/2169–2018 and standard DB31/199–2018, respectively. Both Zhejiang Province and Shanghai Municipality also adopted transitional standard limits before and after implementing these new standards. It is evident that significant disparities exist among the water pollutant discharge standards of urban sewage treatment plants across these three provinces and one city, which hinder integrated improvements in water pollutant treatment performance within the YRD.

Secondly, given the increasingly stringent environmental regulations in China, it is imperative to enhance regional water ecological and environmental performance through collaborative governance for MWPIIs management in the transboundary area of the Yangtze River Delta Eco-Green Integrated Development Demonstration Zone. It is necessary not only to request the low-end and high-intensity MWPIIs within the demonstration zone benchmarking water pollution emission standards in the region, but also to elevate the level of water pollution control through green upgrading and transformation. Furthermore, leveraging exceptional third-party water pollution control enterprises in the YRD can facilitate promoting water pollution control among public sector and MWPII enterprises while enhancing efficiency in regional water pollution control. So, this collaborative governance is not only among regions but also among different departments of governments, enterprises, and society, which need to break regional segmentation through the innovation of institutional mechanisms.

Thirdly, digital technology empowers collaborative governance of MWPIIs’ pollutants emission. To ensure the long-term effectiveness of governance performance in MWPII enterprises within the YRD, a monitoring platform and database for water pollutant discharge from these enterprises have been established. Using digital technology and data sharing enables real-time monitoring of discharge concentrations of various types of water pollutants from MWPII enterprises in the region, facilitating timely identification of issues such as excessive discharge, leakage, and unauthorized discharges. This is helpful to accurately, timely and comprehensively reflect the current situation and development trend of environmental quality in the YRD and provide a scientific basis for the collaborative governance of water pollutants emission. Meanwhile, the Yangtze River Delta Regional Emissions Trading Platform was established in June 2024. This new platform is now only available in the pilot region, including Qingpu district of Shanghai municipality, Wujiang city of Jiangsu Province, Jiashan city of Zhejiang Province, Guangde city of Anhui Province. In the future, it should explore the establishment of a unified regional system for accounting for the total amount of pollutants and allocating the right to ascertain the right to pollutant emission. So, this trading platform could accommodate a wider range of MWPIIs in the YRD with digital technology upgrading.

Finally, a compensation mechanism based on the Regional Emissions Trading Platform should be established to achieve integrated governance of total regional pollutants emissions and improve governance performance. The unified compensation standard and rates should be open and transparent to the public through a digital platform, which will enhance public understanding of and trust in environmental governance and promote public participation and oversight.